Fungi, like all living organisms, may be infected by viruses, obligate intracellular parasites that hijack the host cell machinery in order to replicate. Fungal viruses, or mycoviruses, are usually double-stranded or single-stranded RNA viruses, which may or may not have protein capsids. The majority of known mycoviruses do not have an extracellular phase in their replication cycle and are transmitted both horizontally, from one fungus to another, and vertically, from parent to offspring. Mycovirus infections are persistent and often cryptic, although in some cases mycoviruses produce toxins and modulate the virulence of their hosts and therefore can be utilised in biological control applications.
The extensively studied killer yeast system represents a rare case of symbiosis in fungi, since the mycoviral infection actually confers a distinct phenotype to the host. The Saccharomyces cerevisiae virus L-A (family Totiviridae, genus Totivirus), which is a helper virus, and its satellite RNA M, which encodes a toxin, do not cause cell lysis or growth inhibition to their host but offer a functional advantage, especially in highly populated and nutrient-restrictive environments, where the killer yeast strains eliminate their sensitive neighbours, securing access to the nutrients. Four distinct satellite M viruses have been described so far: M1, M2, M28 and Mlus, which encode K1, K2, K28 and Klus toxins, respectively, and have distinct ways of killing sensitive yeast strains. There are practical applications to understanding this system to optimise the growth and activity of yeasts which are used in food and beverage production and for biotechnological applications.
The aim of the project is to develop a computational model of viral infection in Saccharomyces cerevisiae, a tractable model organism with significant biotechnological applications in baking, brewing and winemaking. To this end, all S. cerevisiae genes and gene products reported to be associated with the L-A and M viruses or the viral toxins will be identified. This will be achieved by analysing transcriptome data of infected yeast cells and identifying differentially expressed genes at different time steps. These genes will be mapped to yeast functional data and protein interaction networks in order to identify cellular functions targeted by the virus. Transcription factors regulating altered genes will be analysed to identify potential regulatory mechanisms, and network control theory will be applied to discover crucial control proteins.
The project will be completed by an experimental component carried out at the University of Melbourne. This will involve screening an extensive collection of yeast strains of biotechnological interest for viruses, carrying out gene deletions to validate the crucial regulators identified by modelling, and carrying out transcriptomics analysis to be exploited for further modelling refinements in Manchester. This project offers the student an excellent opportunity to work in a truly interdisciplinary environment and acquiring skills on a wide range of cell culture, microbiology, bioinformatics, systems biology, data analysis and biotechnology methods.
This project is available to UK/EU candidates. Funding covers fees and stipend for 3.5 years. Candidates will be required to split their time between Manchester and Melbourne.
Applications should be submitted online and candidates should make direct contact with the Manchester supervisor to discuss their application directly. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.
As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.
• Winters M, Panayotides D, Bayrak M, Rémont G, Viejo C, Liu D, Le B, Liu Y, Luo J, Zhang P, Howell K (2019). Defined co‐cultures of yeast and bacteria modify the aroma, crumb and sensory properties of bread. J Appl Microbiol 127: 778-793.
• Schwartz JM, Otokuni H, Akutsu T, Nacher JC (2019). Probabilistic controllability approach to metabolic fluxes in normal and cancer tissues. Nature Communications 10: 2725.
• Filippou C, Garrido-Jurado I, Meyling NV, Quesada-Moraga E, Coutts RHA, Kotta-Loizou I (2018) Mycoviral population dynamics in Spanish isolates of the entomopathogenic fungus Beauveria bassiana. Viruses 10(12). pii: E665.
• Kotta-Loizou I, Coutts RHA (2017) Studies on the virome of the entomopathogenic fungus Beauveria bassiana reveal novel dsRNA elements and mild hypervirulence. PLoS Pathog 13(1): e1006183.
• Kanhayuwa L, Kotta-Loizou I, Özkan S, Gunning AP, Coutts RHA (2015) A novel mycovirus from Aspergillus fumigatus contains four unique dsRNAs as its genome and is infectious as dsRNA. Proc Natl Acad Sci U S A. 112(29): 9100-5.
• Oyeyemi OJ, Davies O, Robertson DL, Schwartz JM (2015). A logical model of HIV-1 interactions with the T-cell activation signalling pathway. Bioinformatics 31: 1075-83.
• Howell KS, Cozzolino D, Bartowsky EJ, Fleet GH, Henschke PA (2006). Metabolic profiling as a tool for revealing Saccharomyces interactions during wine fermentation. FEMS Yeast Res 6: 91-101.