# Metagenomic surveillance of tick-borne pathogens and microbiomes in Huntingdon County, Pennsylvania

## TL;DR

This study used metagenomic sequencing to detect tick-borne pathogens and analyze microbial communities in Pennsylvania ticks, revealing higher sensitivity than traditional methods and environmental influences on diversity.

## Contribution

The study demonstrates the enhanced sensitivity of metagenomic sequencing over PCR for tick-borne pathogen detection and identifies ecological associations with microbial diversity.

## Key findings

- Metagenomic sequencing detected low-abundance pathogens missed by PCR, including Rickettsia and Ehrlichia spp.
- Environmental factors like humidity, time of day, and land cover significantly influenced microbial diversity and gene function.
- Rickettsia was a central taxon in co-occurrence networks, showing strong associations with other microbes.

## Abstract

The rise in tick populations across the United States has contributed to a surge in tick-borne diseases, with Pennsylvania ranking among the highest in reported cases. To better understand local pathogen prevalence and microbial community structure, an integrative study of ticks collected from ten recreational trails in Huntingdon County, Pennsylvania during the summer of 2023 was conducted. A total of 96 ticks were sampled, with 33 PCR-positive specimens selected for shotgun metagenomic sequencing. Pathogen screening via qPCR detected Borreliella burgdorferi, Borrelia miyamotoi, Babesia spp., and Anaplasma phagocytophilum. Shotgun metagenomics revealed a broader diversity of tick-borne pathogens, including Rickettsia and Ehrlichia spp., and demonstrated increased sensitivity by detecting low-abundance pathogens in samples that were PCR-negative. Co-infections were common, and multivariate statistical analysis identified significant associations between environmental variables (e.g., humidity, time of day, land cover) and microbial diversity and predicted gene function. Notably, diversity was higher in ticks collected during early afternoon and from northern sites. Co-occurrence network analysis showed Rickettsia as a central taxon with multiple significant positive associations with other microbes while other pathogens were largely absent or peripheral. These findings underscore the enhanced resolution of metagenomic approaches for pathogen detection and the value of combining molecular surveillance with ecological metadata. Our study provides critical insights into local tick microbiomes and pathogen prevalence, which may inform public health interventions and vector management strategies in central Pennsylvania.

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•MG had higher specificity and sensitivity in detecting tick-borne pathogens over PCR.•Relationships among tickborne pathogens were elucidated.•Significant multivariate associations found between metadata and microbial species.

MG had higher specificity and sensitivity in detecting tick-borne pathogens over PCR.

Relationships among tickborne pathogens were elucidated.

Significant multivariate associations found between metadata and microbial species.