Systematic functional analysis of the Schistosoma mansoni genome using high-throughput (HT) RNA interference and high content imaging (HCI).

Background
The parasitic flatworm Schistosoma mansoni is one of three schistosome species responsible for 300,000 human deaths per annum. Recent re-assembly of this particular blood fluke’s 365 Mb genome revealed that 81% of the predicted 10,852 genes could be mapped to 8 chromosome pairs (7 autosomes and 1 sex-defining pair). This well curated genome coupled to a near complete chromosomal map allows us to drive investigations of gene function, gene expression regulation and comparative genomics in our search for urgently needed control strategies.
RNA interference (RNAi) is one methodology that we, and others, use to pursue functional genomics-led, reverse-genetics studies within S. mansoni. While effective in knocking down target transcript abundance, existing RNAi methodologies are slow, labour-intensive and involve subjective measurement of worm phenotype. We, therefore, propose a novel approach in performing objective RNAi screens in schistosomes, which simultaneously involves high throughput (HT) capacity and high content imaging (HCI) measures. By developing a fully-automated, reverse genetics pipeline for characterising schistosome gene function, anti-schistosomal targets will be identified at an unprecedented pace.

Project description
Due to its small size and gene complement, S. mansoni chromosome 7 will be the subject of this PhD project. Short interfering RNAs (siRNAs) will be designed for each of the 230 Ch.7 mRNAs by the PhD student and purchased from commercial suppliers. These siRNAs will be robotically transferred into 384 well tissue-culture plates containing 50 schistosomes/well. RNAi-mediated phenotypic alterations will be assessed at day 6 post-siRNA treatment using a Molecular Devices ImageXpress High Content screening system, an automated computational pipeline derived from mobility and phenotypic measures as well as our patented helminth fluorescent bioassay (HFB). To analyse/interrogate data resulting from this integrated approach, a schistosome phenotype database will be constructed by the student and made available for community access. In parallel to the HT/HC aspect of this project, the student will also be involved in assessment of RNAi knockdown and follow-on characterisation of gene function. Importantly, this project serves as the first attempt to develop an automated pipeline for systematic exploration of schistosome gene function, which could be adapted for whole genome studies and lead to a series of high impact publications.

Supervisory team
The supervisory team bring a synergistic set of skills to this project, which includes whole organism phenotyping, genome-wide analyses and large dataset processing. They have recently cooperated in securing IBERS high content imaging capacity and will use this PhD project to ensure phenomics-led projects develop across research themes and biological scales. To safeguard student development, the team provide weekly laboratory meetings, seminar series, support through post-graduate and post-doctoral scientists, exposure at national and international scientific meetings and access to London (LSHTM)- and Cambridge (WTSI) - based collaborators. Due to the multi-disciplinary nature of the proposal, the selected student will be trained in image analysis, computational biology, parasitology, bioinformatics, molecular techniques and database curation.

Supervisors
Karl F Hoffmann - http://www.aber.ac.uk/en/ibers/staff/staff_profiles/krh/
John Doonan - http://www.aber.ac.uk/en/ibers/staff/staff_profiles/doonan,-prof.-john/

"Candidates should have (or expect to achieve) a First Class or Upper second class honours degree and/or a masters degree
(or equivalent) in a relevant subject."

We encourage prospective candidates to contact the lead supervisor Professof Karl Hoffmann [Email Address Removed]; 01970 622237;
Karl F Hoffmann - http://www.aber.ac.uk/en/ibers/staff/staff_profiles/krh/

http://www.aber.ac.uk/en/ibers/opportunities-@-ibers/