Abstract
Coccidioidomycosis (Valley Fever) is a reemerging, neglected fungal disease endemic to arid and semi-arid regions of the Americas, caused by the soil-dwelling fungi Coccidioides spp. Environmental detection remains challenging due to spatial heterogeneity, seasonal variability, low DNA abundance, PCR inhibitors, and lack of standardized methods. We conducted environmental surveillance in Baja California, Mexico, an understudied region near the U.S.-Mexico border, by collecting 74 soil samples from active rodent burrows across five locations. We evaluated droplet digital PCR (ddPCR) for Coccidioides detection and compared its performance to a nested PCR assay targeting the ITS1 region. ddPCR demonstrated greater sensitivity, detecting Coccidioides DNA at all sampling sites, whereas nested PCR detected it at only one. These findings highlight ddPCR as a sensitive and reliable method for environmental detection of Coccidioides . Integrating high-resolution molecular diagnostics with ecological data may enhance species distribution models and guide targeted public health interventions in endemic regions.
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Abstract
Coccidioidomycosis (Valley Fever) is a reemerging, neglected fungal disease endemic to arid and semi-arid regions of the Americas, caused by the soil-dwelling fungi Coccidioides spp. Environmental detection remains challenging due to spatial heterogeneity, seasonal variability, low DNA abundance, PCR inhibitors, and lack of standardized methods. We conducted environmental surveillance in Baja California, Mexico, an understudied region near the U.S.-Mexico border, by collecting 74 soil samples from active rodent burrows across five locations. We evaluated droplet digital PCR (ddPCR) for Coccidioides detection and compared its performance to a nested PCR assay targeting the ITS1 region. ddPCR demonstrated greater sensitivity, detecting Coccidioides DNA at all sampling sites, whereas nested PCR detected it at only one. These findings highlight ddPCR as a sensitive and reliable method for environmental detection of Coccidioides. Integrating high-resolution molecular diagnostics with ecological data may enhance species distribution models and guide targeted public health interventions in endemic regions.
Competing Interest Statement
The authors have declared no competing interest.
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