Parasites & Vectors (Jan 2015)

Functional analysis of Girardia tigrina transcriptome seeds pipeline for anthelmintic target discovery

  • Nicolas J Wheeler,
  • Prince N Agbedanu,
  • Michael J Kimber,
  • Paula Ribeiro,
  • Tim A Day,
  • Mostafa Zamanian

DOI
https://doi.org/10.1186/s13071-014-0622-3
Journal volume & issue
Vol. 8, no. 1
pp. 1 – 12

Abstract

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Abstract Background Neglected diseases caused by helminth infections impose a massive hindrance to progress in the developing world. While basic research on parasitic flatworms (platyhelminths) continues to expand, researchers have yet to broadly adopt a free-living model to complement the study of these important parasites. Methods We report the high-coverage sequencing (RNA-Seq) and assembly of the transcriptome of the planarian Girardia tigrina across a set of dynamic conditions. The assembly was annotated and extensive orthology analysis was used to seed a pipeline for the rational prioritization and validation of putative anthelmintic targets. A small number of targets conserved between parasitic and free-living flatworms were comparatively interrogated. Results 240 million paired-end reads were assembled de novo to produce a strictly filtered predicted proteome consisting of over 22,000 proteins. Gene Ontology annotations were extended to 16,467 proteins. 2,693 sequences were identified in orthology groups spanning flukes, tapeworms and planaria, with 441 highlighted as belonging to druggable protein families. Chemical inhibitors were used on three targets in pharmacological screens using both planaria and schistosomula, revealing distinct motility phenotypes that were shown to correlate with planarian RNAi phenotypes. Conclusions This work provides the first comprehensive and annotated sequence resource for the model planarian G. tigrina, alongside a prioritized list of candidate drug targets conserved among parasitic and free-living flatworms. As proof of principle, we show that a simple RNAi and pharmacology pipeline in the more convenient planarian model system can inform parasite biology and serve as an efficient screening tool for the identification of lucrative anthelmintic targets.

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