Lasers and ticks and AI, oh my! Mid-infrared spectroscopy as a novel form of pathogen surveillance in ticks

Tick-borne pathogens pose a significant threat to human, companion animal, and livestock health. In addition to the debilitating effects of the diseases they cause, tick-borne pathogens result in billions of dollars in economic losses each year. Current surveillance techniques are expensive and time consuming, relying on widespread molecular testing to identify tick infection status. Infrared spectroscopy has shown promise as a reagent-less method to detect certain pathogen infections in arthropods. By coupling mid-infrared spectroscopy (MIRS) with advances in artificial intelligence (AI) and computer vision, we hope to develop a streamlined process for more targeted testing that reduces the time and costs associated with pathogen surveillance in ticks. Colony-reared uninfected ticks will be scanned using MIRS alongside colony-reared ticks infected with parasitic and bacterial pathogens. The resulting spectra will be evaluated using trained AI classification algorithms to detect patterns and shifts in the spectra between specimens, and infection status will be confirmed via PCR testing to correlate MIRS results to infected and uninfected ticks. Preliminary results show that differences in MIRS spectra are sufficient to detect tick sex and position (rostral vs ventral) with 98% and 100% accuracy, respectively. We anticipate that pathogen infection in ticks will result in a shift in the MIR spectra enabling differentiation between infected and uninfected individuals. By rapidly determining the infection status of ticks, we hope to reduce the burden of cost and time associated with current testing protocols and enhance the tools available for tick-borne pathogen surveillance in veterinary and public health settings.