High throughput analysis of microRNAs in Echinococcus spp.

NATALIA MACCHIAROLI; LAURA KAMENETZKY; MARCELA CUCHER; LAURA PRADA; LUCAS MALDONADO; MARA ROSENZVIT

Congreso; III Congreso Panamericano de Zoonosis. VIII Congreso Argentino de Zoonosis; 2014

High throughput analysis of microRNAs in Echinococcus spp. Natalia Macchiaroli1, Laura Kamenetzky1, Marcela Cucher1, Laura Prada1, Lucas Maldonado1, Mara Rosenzvit1. Instituto de Microbiología y Parasitología Médica, Facultad de Medicina, Paraguay 2155, piso 13, C1121ABG, Buenos Aires, Argentina. macchiaroli.natalia@gmail.com INTRODUCTION: Echinococcus granulosus sensu stricto G1 (sheep strain) and Echinococcus canadensis G7 (pig strain) are small tapeworms whose larval stage, the metacestode or hydatid cyst, is the causative agent of cystic hydatid disease, a zoonosis of public health concern. The complex life cycle and the unique biological features of these parasites make Echinococcus spp. an interesting model for gene regulation studies. MicroRNA (miRNAs) are a class of small (~22 nt), non-coding RNAs that are key regulators of gene expression at post-transcriptional level and play essential roles in important biological processes. In a previous work, we have shown the existence of miRNAs in Echinococcus spp. by using a low scale cloning procedure. In this study, we used a high throughput approach to discover new miRNAs in Echinococcus spp and to compare their expression between different life cycle stages and species. MATERIALS AND METHODS: Small RNA libraries from protoscoleces of E. granulosus s. s. G1 and from protoscoleces and cyst walls of E. canadensis G7 were sequenced using Illumina technology. Clean reads were mapped to E. multilocularis reference genome (version 4) with Bowtie. To identify previously reported and novel miRNAs, the miRDeep2 software was used. The initial output list of candidate precursors was hand curated to generate a final high confidence set of miRNAs. Differential expression analysis of microRNAs between two conditions (stages or species) was estimated with DESeq. Mapped sequences were classified by BLASTN against an in-house database into small RNA categories including miRNAs. RESULTS: Illumina deep sequencing of Echinococcus spp. libraries produced between ~ 2.0 and 5.3 million raw reads per sample, with a high percentage of genome mapping (46%-86%). We identified 38 precursor sequences, 23 previously reported in Echinococcus spp. and 15 novel ones. Differential expression analysis showed 16 miRNAs with stage biased expression in E. canadensis G7. No significant differences in the expression of miRNAs were found between protoscoleces from E. canadensis G7 and E. granulosus s. s. G1. Interestingly, miRNAs were the most abundant small RNA category in protoscolex libraries from both species, representing about half of the small RNA population. The porcentage of miRNAs in cyst walls of E. canadensis G7 was also high, but lower than that in protoscoleces. DISCUSSION: The recently generated reference genome for the related species E. multilocularis, together with improvement of high throughput technologies and available algorithms for miRNA discovery allowed us the identification of additional miRNAs in Echinococcus spp. Differential expression analysis showed highly regulated miRNAs between life cycle stages of E. canadensis G7 suggesting important functional roles in development. Finally, we found that miRNAs were abundantly expressed in all stages/species analyzed in this study, suggesting that these small RNAs could be an essential mechanism of gene regulation in Echinococcus spp. This study will provide valuable information for better understanding the complex biology of this parasite and could help to find new potential targets for therapy and/or diagnosis. References Cucher M, Prada L, Mourglia-Ettlin G, Dematteis S, Camicia F, Asurmendi S, Rosenzvit M. Identification of Echinococcus granulosus microRNAs and their expression in different life cycle stages and parasite genotypes. Int J Parasitol. 2011 Mar;41(3-4):439-48. Friedländer MR, Mackowiak SD, Li N, Chen W, Rajewsky N. miRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Res. 2012 Jan;40(1):37-52. Tsai IJ, Zarowiecki M, Holroyd N, Garciarrubio A et al. The genomes of four tapeworm species reveal adaptations to parasitism. Nature. 2013 Apr;496(7443):57-63