Computational and experimental analysis of virulence characteristics in pathogenic Candida species (360G-Wellcome-102406_Z_13_Z)

£155,242

The aim of this project is to identify virulence factor networks in the pathogenic fungus Candida parapsilosis using both computational and laboratorymethods. We will use RNA-seq, ChiP-seq and phenotypic knockout profiling data to assemble virulence factor networks. Data will be generated from C. parapsilosis cells growing in different environments, including during infection of the model host Galleria mellonella. Identifying these networks could be valuable in drug target discovery. In a second approach we will use newly generated transcriptional data in conjunction with the Candida Gene Order Browser (CGOB) to identify non-coding RNAs in C. parapsilosis. This project is an extension of rotation 2, where conserved regions in non-coding DNA were identified computationally. The computational approach will be complemented using RNA-seq data of total RNA compared to poly-selected RNA. RNA will be extracted from cells growing in conditions associated with virulence, such as different oxygen concentrations.Newly identified non-coding regions will be verified experimentally, and their

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Grant Details

Amount Awarded 155242
Applicant Surname Donovan
Approval Committee PhD Studentships
Award Date 2013-06-24T00:00:00+00:00
Financial Year 2012/13
Grant Programme: Title PhD Studentship (Basic)
Internal ID 102406/Z/13/Z
Lead Applicant Mr Paul Donovan
Partnership Value 155242
Planned Dates: End Date 2017-11-30T00:00:00+00:00
Planned Dates: Start Date 2013-09-01T00:00:00+00:00
Recipient Org: Country Ireland
Region Ireland
Sponsor(s) Prof Geraldine Butler