Molecular epidemiology and diagnosis of Leishmania: what have we learnt from genome structure, dynamics and function?

This paper reviews our exploration of the dynamics of the Leishmania genome and its contribution to epidemiology and diagnosis. We used as a model Peruvian populations of L. (Viannia) braziliensis and L. (V.) peruviana, 2 species very close phylogenetically, but phenotypically very different in biotope and pathology. We initially focused on karyotype analysis. Our data showed that chromosomes were subject to a fast rate of evolution, and were sensitive indicators of genetic drift. Therefore, molecular karyotyping appeared an adequate tool for monitoring (i) emergence of close species, (ii) ecogeographical differentiation at the intraspecific level, and (iii) strain 'fingerprinting'. Chromosome size variation was mostly due to the number of tandemly repeated genes (rDNA, mini-exon, gp63, and cysteine proteinase genes), and could involve the deletion of unique genes (L. (V.) braziliensis-specific gp63 families). Considering the importance of these genes in parasitism, their rearrangement might have functional implications: adaptation to different environments and pleomorphic pathogenicity. Our knowledge of genome structure and dynamics was used to develop new polymerase chain reaction (PCR) techniques. Amplification of gp63 genes followed by cleavage with restriction enzymes and study of restriction fragment length polymorphism (gp63 PCR-RFLP) allowed the discrimination of all species tested, even directly in biopsies with 95% sensitivity (compared with PCR amplification of kinetoplast deoxyribonucleic acid). At the intra-specific level, RFLP was also observed and corresponded to mutations in major immunogen domains of gp63. These seem to be under strong selection pressure, and the technique should facilitate addressing how the host's immune pressure may modulate parasite population structure. Altogether, gp63 PCR-RFLP represents a significant operational improvement over the other techniques for molecular epidemiology and diagnosis: it combines sensitivity, discriminatory power and prognostic value.