Background: American cutaneous leishmaniasis (ACL) is caused by different Leishmania parasites, which stimulate and direct the immune response against the infection.

Objective: To evaluate the TaqMan probe technology applicability to diagnose and identifying of Leishmania spp. related to the ACL etiology.

Methodology: Through the MEGA 6.0 software, performed an in silico analysis using multiple alignments of Leishmania spp. which were available on GenBank for different genomic targets. The efficiency (e), specificity and detection limit (DL) were calculated for each system, these were associated to compose a duplex-qPCR (DqPCR). The samples of blood, lesion biopsy and lesion imprint on filter paper from patients residing in states of Amazonas (AM) and Pernambuco (PE)-Brazil, (cases and controls) were used to perform the DqPCR technique. The capacity to identify the Leishmania species was determined by comparison with isoenzymes method and sequencing analysis.

Results: Internal Transcribed Spacer 1 (rDNA) was the target selected. Two sets of primers and probes were designed and combined: SVS for subgenus Viannia and LaS for L. (L.) amazonensis. The results were: SVSe = 93.24%, SVS DL = 50 fg/μL; LaSe = 89.3%, LaSLD = 5 fg/μL presented 100% of specificity. In total, 236 individuals participated of the present study, wherein were 101 blood samples, 33 biopsies and 147 lesion imprints. The imprint was the most sensitive sample, showing 83.06% of sensitivity, 86.96% of specificity and substantial agreement between the techniques analysis (k = 0.531; p < 0,001). Regarding the species identification, DqPCR and sequencing/isoenzymes have agreed at 100%, since the infection is caused by a single Leishmania species.

Conclusion: The DqPCR technique was applicable in diagnosis and identification of Leishmania spp. (subgenus Viannia and L. amazonensis). Furthermore, the lesion imprint is less invasive, allowing a fewer discomfort and greater acceptance by the patients, in addition of being low cost and easy handling.

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http://dx.doi.org/10.1016/j.exppara.2020.108019DOI Listing

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