A dual-target qPCR coupled with high-resolution melting analysis for direct strain discrimination within the Leishmania donovani complex

Molecular diagnostic approaches, particularly qPCR-based assays targeting nuclear or kinetoplast DNA, have drastically improved the sensitivity of Leishmania detection. However, standard qPCR methods fail to directly differentiate closely related species, such as L. (L.) infantum and L. (L.) donovani , representing a critical limitation for accurate diagnosis and epidemiological surveillance. While whole-genome sequencing and multilocus microsatellite typing can resolve species and uncover L. (L.) infantum/L. (L.) donovani hybrids, both methods are costly and time-consuming. In this study, we developed a dual-target qPCR coupled with high-resolution melting (HRM) analysis to discriminate the Old World Leishmania species of medical interest, in particular L. (L.) infantum , L. (L.) donovani , and genotypes associated with putative L. (L.) infantum/L. (L.) donovani hybrids, directly from clinical specimens. The assays target specific polymorphisms within two metabolic genes: malic enzyme (ME) and nucleoside hydrolase (NH). The performance and discriminative power of this system were validated using a panel of reference strains, clinical isolates, and clinical samples of human and canine origin. The developed qPCR-HRM assays successfully differentiated L. (L.) infantum from L. (L.) donovani and identified L. (L.) infantum variants, including samples displaying putative L. (L.) infantum/L. (L.) donovani hybrid-like profiles. Importantly, the method demonstrated high analytical sensitivity (one parasite per reaction tube) and 82.7% typing rate when applied directly to clinical samples, allowing to discriminate among strains within the L. (L.) donovani complex bypassing parasite isolation. This dual-target qPCR-HRM approach provides a rapid and cost-effective screening tool for Old World Leishmania species identification and genotyping. By enabling direct analysis from clinical samples, this method holds strong potential to improve surveillance and epidemiological tracking of human and canine leishmaniasis. IMPORTANCE This study provides an affordable and rapid method to distinguish closely related Leishmania parasites directly from clinical samples, without the need for parasite isolation or expensive genome sequencing. Accurate identification of these parasites is important because different species and strains can have distinct geographical distributions, transmission cycles, and animal reservoirs, making them essential to track for effective disease surveillance and control. By combining high sensitivity with the ability to identify species and variants within the L . ( L .) donovani complex in a single workflow, this method fills an important gap between routine diagnostic tests and advanced genomic approaches. Its rapidity and low cost make it suitable for use in diagnostic laboratories, particularly in settings where access to sequencing technologies is limited. Ultimately, this approach can strengthen disease surveillance, improve monitoring of parasite transmission, and support more effective public health and veterinary control strategies for leishmaniasis.