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