Tracking the spread of a naturally occurring Leishmania (L.) infantum mutant: a qPCR-based investigation in strains and clinical samples

Abstract

Background The co-circulation of Leishmania ( Leishmania ) infantum strains carrying a naturally occurring 12 kb genomic deletion (DEL) and the wild-type (NonDEL) parasites in the Americas raises important challenges for epidemiological surveillance, molecular diagnostics, and the interpretation of infection dynamics in visceral leishmaniasis (VL). In this study, we aimed to develop and apply a robust molecular approach to discriminate and quantify DEL and NonDEL genotypes and to assess their distribution, frequency, and patterns of co-infection across endemic regions. Methods We established a qPCR-based genotyping strategy combining a constitutive genomic target, present in all Leishmania (L.) infantum strains, with a NonDEL-specific target, enabling simultaneous genotype discrimination and parasite quantification. Results After validation using cultured parasites, the assay was applied to a large and diverse panel of strains isolates from humans and dogs preserved in a biobank, as well as clinical samples from dogs, cats, coatis, and sand flies across South and Central America. DEL parasites predominated (69.8%) and showed a wide geographic distribution in both strains and clinical samples, indicating their major contribution to transmission cycles. No significant association was observed between host type (human vs. canine) and genotype frequency. Notably, mixed-genotype infections were frequently detected, revealing within-host complexity not captured by conventional diagnostic methods. Quantification based on the constitutive target strongly correlated with kDNA-based parasite load estimates, supporting its simultaneous use for genotyping and quantification of L. ( L. ) infantum variants directly from clinical material. Conclusions This approach thus provides new insights into parasite population structure and infection dynamics and supports improved molecular surveillance and interpretation of diagnostic and epidemiological data in VL.