RESUMEN
BACKGROUND: Leishmaniasis are widespread parasitic-diseases with an urgent need for more active and less toxic drugs and for effective vaccines. Understanding the biology of the parasite especially in the context of host parasite interaction is a crucial step towards such improvements in therapy and control. Several experimental approaches including SAGE (Serial analysis of gene expression) have been developed in order to investigate the parasite transcriptome organisation and plasticity. Usual SAGE tag-to-gene mapping techniques are inadequate because almost all tags are normally located in the 3'-UTR outside the CDS, whereas most information available for Leishmania transcripts is restricted to the CDS predictions. The aim of this work is to optimize a SAGE libraries tag-to-gene mapping technique and to show how this development improves the understanding of Leishmania transcriptome. FINDINGS: The in silico method implemented herein was based on mapping the tags to Leishmania genome using BLAST then mapping the tags to their gene using a data-driven probability distribution. This optimized tag-to-gene mappings improved the knowledge of Leishmania genome structure and transcription. It allowed analyzing the expression of a maximal number of Leishmania genes, the delimitation of the 3' UTR of 478 genes and the identification of biological processes that are differentially modulated during the promastigote to amastigote differentiation. CONCLUSION: The developed method optimizes the assignment of SAGE tags in trypanosomatidae genomes as well as in any genome having polycistronic transcription and small intergenic regions.
RESUMEN
BACKGROUND: Leishmania (L) are intracellular protozoan parasites that are able to survive and replicate within the harsh and potentially hostile phagolysosomal environment of mammalian mononuclear phagocytes. A complex interplay then takes place between the macrophage (MPhi) striving to eliminate the pathogen and the parasite struggling for its own survival. To investigate this host-parasite conflict at the transcriptional level, in the context of monocyte-derived human MPhis (MDM) infection by L. major metacyclic promastigotes, the quantitative technique of serial analysis of gene expression (SAGE) was used. RESULTS: After extracting mRNA from resting human MPhis, Leishmania-infected human MPhis and L. major parasites, three SAGE libraries were constructed and sequenced generating up to 28,173; 57,514 and 33,906 tags respectively (corresponding to 12,946; 23,442 and 9,530 unique tags). Using computational data analysis and direct comparison to 357,888 publicly available experimental human tags, the parasite and the host cell transcriptomes were then simultaneously characterized from the mixed cellular extract, confidently discriminating host from parasite transcripts. This procedure led us to reliably assign 3,814 tags to MPhis' and 3,666 tags to L. major parasites transcripts. We focused on these, showing significant changes in their expression that are likely to be relevant to the pathogenesis of parasite infection: (i) human MPhis genes, belonging to key immune response proteins (e.g., IFNgamma pathway, S100 and chemokine families) and (ii) a group of Leishmania genes showing a preferential expression at the parasite's intra-cellular developing stage. CONCLUSION: Dual SAGE transcriptome analysis provided a useful, powerful and accurate approach to discriminating genes of human or parasitic origin in Leishmania-infected human MPhis. The findings presented in this work suggest that the Leishmania parasite modulates key transcripts in human MPhis that may be beneficial for its establishment and survival. Furthermore, these results provide an overview of gene expression at two developmental stages of the parasite, namely metacyclic promastigotes and intracellular amastigotes and indicate a broad difference between their transcriptomic profiles. Finally, our reported set of expressed genes will be useful in future rounds of data mining and gene annotation.
