Spatio-temporal Genetic Structuring of Leishmania major in Tunisia by Microsatellite Analysis

Abstract

In Tunisia, cases of zoonotic cutaneous leishmaniasis caused by Leishmania major are increasing and spreading from the south-west to new areas in the center. To improve the current knowledge on L. major evolution and population dynamics, we performed multi-locus microsatellite typing of human isolates from Tunisian governorates where the disease is endemic (Gafsa, Kairouan and Sidi Bouzid governorates) and collected during two periods: 1991-1992 and 2008-2012. Analysis (F-statistics and Bayesian model-based approach) of the genotyping results of isolates collected in Sidi Bouzid in 1991-1992 and 2008-2012 shows that, over two decades, in the same area, Leishmania parasites evolved by generating genetically differentiated populations. The genetic patterns of 2008-2012 isolates from the three governorates indicate that L. major populations did not spread gradually from the south to the center of Tunisia, according to a geographical gradient, suggesting that human activities might be the source of the disease expansion. The genotype analysis also suggests previous (Bayesian model-based approach) and current (F-statistics) flows of genotypes between governorates and districts. Human activities as well as reservoir dynamics and the effects of environmental changes could explain how the disease progresses. This study provides new insights into the evolution and spread of L. major in Tunisia that might improve our understanding of the parasite flow between geographically and temporally distinct populations.

Fig 1. Map of Tunisia and schematic illustration of gene flow between the study areas.

(A1) Location of Tunisia, North Africa. (B1) Location of the Gafsa, Sidi Bouzid and Kairouan Governorates within Tunisia. (C1) Zoom of the area under study to show Chrarda and Mnara (Nasrallah delegation) (Mnara and Chrarda are shown in the map with red asterisks) in the Kairouan Governorate.

Fig 2. Estimated population structure of L. major in Tunisia as inferred by the STRUCTURE software on the basis of the data on 10 microsatellite markers obtained for 137 recent isolates from the Gafsa (GF2008-2012; n = 66), Kairouan (KR2008-2012; n = 46) and Sidi Bouzid (SBZ2008-2012; n = 25) governorates.

(A) Plot of the mean posterior probability (LnP(D)) values per clusters (K), based on 10 replicates per K, generated by the STRUCTURE software, and (B) delta-K analysis of LnP(K). (C) STRUCTURE plots grouped by Q-matrix (estimated membership coefficient for each sample) showing the distribution of genetic variation (C.1) at K = 2 and (C.2) at K = 4. Each strain is represented by a vertical line, which is partitioned into the colored segments that represent the parasite estimated membership fractions in K. The same color indicates that the isolates belong to the same group. Different colors for the same isolate indicate the percentage of the genotype shared with each group. Gene flow between populations is indicated with arrows.

Fig 3. The unrooted neighbor-joining tree inferred from pair-wise Cavalli-Sforza and Edwards’ chord distances based on the 10 microsatellite data of 60 Leishmania major isolates (SBZ1991-1992 and SBZ2008-2012) shows that the historical isolates (SBZ1991-1992, n = 35; orange labels) and the recent isolates (SBZ2008-2012, n = 25; green labels) can be subdivided in five clusters.