Parasitic nematodes infect plants and animals to undermine global food production. They are the causative agents of a range of neglected tropical diseases, inflicting significant human morbidity and mortality, predominantly within the world's most impoverished communities. The development of anthelmintic resistance threatens the primary mode of parasite control and necessitates the development of alternatively management strategies. This thesis incorporates bioinformatic and reverse genetic analyses in an attempt to investigate the neuromuscular biology of parasitic nematodes. Firstly, a reciprocal BLAST-based gene mining methodology was employed to generate a pan-phylum view of FMRFamide-like peptide (flp) and flp-receptor gene diversity, revealing previously unrecognised variation within the FLPergic gene profiles present within the genomes of parasitic nematodes. These new data identify the most highly conserved neuropeptide ligand and receptor encoding genes within the FLPergic signalling system and facilitate future efforts to deorphanise and therapeutically exploit nematode FLP-receptors for parasite control. Secondly, this thesis attempts to optimise a gene silencing platform for the validation of novel anthelmintic targets within the neuromuscular signalling system of the model parasite Ascaris suum. The data presented characterise the spread and development of RNA interference (RNAi) within adult A. suum and demonstrate significant and potent transcript knockdown for multiple tissue-specific gene targets post-dsRNA injection. Despite this 100 % success rate, no post-RNAi phenotypes were recorded over the course of these investigations. This was inspite of efforts to: (i) target putatively essential genes; (ii) employ a highly quantitative electrophysiology-based phenotypic assay; (iii) improve the RNAi trigger delivery methodology; and (iv) develop a novel strategy to uncover a post-RNAi phenotype. The data described here highlight the potential utility of RNAi in adult A. suum and warrant further investigation
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:678821 |
| Date | January 2015 |
| Creators | McCoy, Ciaran J. |
| Publisher | Queen's University Belfast |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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