Dissemin is shutting down on January 1st, 2025

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Public Library of Science, PLoS Neglected Tropical Diseases, 12(9), p. e0004204, 2015

DOI: 10.1371/journal.pntd.0004204

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Comparison of Leishmania killicki (syn. L. tropica) and Leishmania tropica Population Structure in Maghreb by Microsatellite Typing

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Leishmania (L.) killicki (syn. L. tropica), which causes cutaneous leishmaniasis in Maghreb, was recently described in this region and identified as a subpopulation of L. tropica. The present genetic analysis was conducted to explore the spatio-temporal distribution of L. killicki (syn. L. tropica) and its transmission dynamics. To better understand the evolution of this parasite, its population structure was then compared with that of L. tropica populations from Morocco. In total 198 samples including 85 L. killicki (syn. L. tropica) (from Tunisia, Algeria and Libya) and 113 L. tropica specimens (all from Morocco) were tested. Theses samples were composed of 168 Leishmania strains isolated from human skin lesions, 27 DNA samples from human skin lesion biopsies, two DNA samples from Ctenodactylus gundi bone marrow and one DNA sample from a Phlebotomus sergenti female. The sample was analyzed by using MultiLocus Enzyme Electrophoresis (MLEE) and MultiLocus Microsatellite Typing (MLMT) approaches. Analysis of the MLMT data support the hypothesis that L. killicki (syn. L. tropica) belongs to the L. tropica complex, despite its strong genetic differentiation, and that it emerged from this taxon by a founder effect. Moreover, it revealed a strong structuring in L. killicki (syn. L. tropica) between Tunisia and Algeria and within the different Tunisian regions, suggesting low dispersion of L. killicki (syn. L. tropica) in space and time. Comparison of the L. tropica (exclusively from Morocco) and L. killicki (syn. L. tropica) population structures revealed distinct genetic organizations, reflecting different epidemiological cycles.