Molecular detection of medically relevant Sporothrix species in roadkilled wildlife in the Brazilian Atlantic forest.

Abstract

The rapid expansion of zoonotic sporotrichosis in South America necessitates innovative surveillance strategies to identify natural ecological niches. Roadkill provides a unique, underutilized opportunity to monitor Sporothrix circulation within human-impacted landscapes. We conducted a molecular survey via a triplex probe quantitative real-time PCR (qPCR) assay targeting pathogenic Sporothrix species in 81 roadkilled vertebrates (mammals, birds, and reptiles) collected along highways BR-376 and PR-445 traversing the Atlantic Forest in Paraná, Brazil (2017-2023). Genomic DNA from visceral organs (heart, liver, lung, and spleen) was screened for fungal DNA. Sporothrix DNA was detected in 13.6% (11/81) of the samples. Sporothrix schenckii predominated, identified in wild mammals (Leopardus guttulus, Didelphis albiventris, and Lepus europaeus) and diverse birds (Colaptes melanochloros, Piaya cayana, and Selenidera maculirostris), indicating systemic exposure. Strikingly, S. brasiliensis was detected in avian hosts (Columbina picui, Crypturellus tataupa), challenging the thermal-exclusion hypothesis and implicating birds as potential aerial vectors. Furthermore, S. globosa was found in Dasyprocta spp. and was co-detected with S. brasiliensis in Columbina picui. Notably, a reptile (Oxyrhopus spp.) was positive for S. globosa and S. schenckii, expanding the known host spectrum, potentially via trophic transmission. Although distinguishing transient DNA carriage from active infection requires histopathological validation, these findings suggest that wildlife in fragmented corridors may function as reservoirs, biological amplifiers, or mechanical vectors rather than incidental hosts, reinforcing the blurring boundaries between sylvatic and synanthropic transmission cycles. In this context, integrating roadkill biosurveillance into a One Health framework is vital for tracking environmental pathogen loads and anticipating zoonotic spillover.