Anti-schistosomal intervention targets identified by lifecycle transcriptomic analyses.

Background: Novel methods to identify anthelmintic drug and vaccine targets are urgently needed, especially for those parasite species currently being controlled by singular, often limited strategies. A clearer understanding of the transcriptional components underpinning helminth development will enable identification of exploitable molecules essential for successful parasite/host interactions. Towards this end, we present a combinatorial, bioinformatics-led approach, employing both statistical and network analyses of transcriptomic data, for identifying new immunoprophylactic and therapeutic lead targets to combat schistosomiasis.
Methodology/principal Findings: Utilisation of a Schistosoma mansoni oligonucleotide DNA microarray consisting of 37,632 elements enabled gene expression profiling from 15 distinct parasite lifecycle stages, spanning three unique ecological niches. Statistical approaches of data analysis revealed differential expression of 973 gene products that minimally describe the three major characteristics of schistosome development: asexual processes within intermediate snail hosts, sexual maturation within definitive vertebrate hosts and sexual dimorphism amongst adult male and female worms. Furthermore, we identified a group of 338 constitutively expressed schistosome gene products (including 41 transcripts sharing no sequence similarity outside the Platyhelminthes), which are likely to be essential for schistosome lifecycle progression. While highly informative, statistics-led bioinformatics mining of the transcriptional dataset has limitations, including the inability to identify higher order relationships between differentially expressed transcripts and lifecycle stages. Network analysis, coupled to Gene Ontology enrichment investigations, facilitated a re-examination of the dataset and identified 387 clusters (containing 12,132 gene products) displaying novel examples of developmentally regulated classes (including 294 schistosomula and/or adult transcripts with no known sequence similarity outside the Platyhelminthes), which were undetectable by the statistical comparisons.
Conclusions/significance: Collectively, statistical and network-based exploratory analyses of transcriptomic datasets have led to a thorough characterisation of schistosome development. Information obtained from these experiments highlighted key transcriptional programs associated with lifecycle progression and identified numerous anti-schistosomal candidate molecules including G-protein coupled receptors, tetraspanins, Dyp-type peroxidases, fucosyltransferases, leishmanolysins and the netrin/netrin receptor complex.