Evaluating the diagnostic capabilities of nanopore sequencing for Borrelia burgdorferi detection in blacklegged ticks
Ticks pose substantial threats to public health. Blacklegged ticks (Ixodes scapularis) are responsible for most tick-borne diseases in the US, transmitting seven human pathogens. Molecular surveillance for tick-borne pathogens has been outpaced by their emergence, revealing a critical need to develop agnostic strategies that characterize emerging and putative pathogens. Oxford Nanopore Technologys nanopore adaptive sampling (NAS), an approach that selectively enriches or depletes for target genomes or genetic loci, provides an opportunity to generate real-time genomic insights into tick-borne pathogens. In the current study, we performed PCR and NAS on pooled Borrelia burgdorferi-infected and -uninfected ticks to evaluate the diagnostic capability of NAS. We found that NAS generates extensive datasets on tick-borne pathogens from individual ticks that aid in distinguishing true and false positive samples. Using a pooled approach consisting of whole genomic DNA from 168 total ticks multiplexed over seven sequencing experiments, our results indicated that NAS is extremely specific (0.97 [95% CI: 0.93, 1.00]) with moderate sensitivity (0.48 [95% CI: 0.41, 0.55]), suggesting a strong capacity to confirm B. burgdorferi when present at the expense of an elevated false-negative rate. We found that quality-based filtering of sequence data has a profound influence on diagnostic metrics, emphasizing the need to optimize pooling strategy, wet-lab procedures, and bioinformatic pipelines to enhance the sensitivity of NAS for detecting tick-borne pathogens. Author summaryTicks pose substantial threats to public health. In the United States, the blacklegged tick (Ixodes scapularis) can transmit seven (known) human pathogens and is responsible for most tick-borne disease cases. The most prevalent tick-borne pathogen, Borrelia burgdorferi, causes Lyme disease, which is consequently the most common tick-borne disease in the United States. As blacklegged ticks continue to expand across the United States, it is imperative to develop rapid molecular surveillance tools that agnostically detect emerging and putative pathogens. In the current study, we employ Oxford Nanopore Technologys nanopore adaptive sampling on PCR-infected and PCR-uninfected blacklegged ticks to determine the diagnostic capability of this technology for rapid Borrelia burgdorferi detection. Our results suggest that nanopore adaptive sampling can generate extensive sequence datasets on user-specified target reference genomes. We demonstrate that nanopore adaptive sampling is extremely specific, capable of confirming B. burgdorferi presence when detected, yet lacks sensitivity, leading to a high false negative rate. We highlight the methodological limitations that undoubtedly led to this lower sensitivity and provide future research directions for enhancing nanopore adaptive sampling as a real-time, unbiased molecular tool for tick-borne pathogen surveillance.