Translocation of Cladosporium fulvum effectors in a tomato plant cell
During infection, C. fulvum secretes many peptide effectors in the apoplast of tomato that play a role in virulence and avirulence. It is assumed that some effectors will be translocated into the plant cell. The student will (i) clone candidate peptides in E. coli expression vectors, (ii) set up the culture conditions for protein production/purification, and (iii) analyse the peptide-GFP fusions for translocation into plant cells.
Identification of a tomato co-receptor complex involved in Cf-9/Avr9 resistance signalling
Cf resistance proteins contain a transmembrane domain and a expected to recognize the cognate effectors peptide at the plasma membrane (PM). Interactors that could make a functional complex with Cf-9 likely belong to the family of RLKs. The studen t will (i) clone candidate genes in a binary vector for transiest expression, (ii) transiently co-express Cf-9-YFP and putative interactors in N. benthamiana, and (iii) check whether Cf-9-YFP remains in the ER or is relocalized to the PM by fluoresence microscopy.
Functional characterization of a Cladosporium fulvum effector library
Effectors secreted during infection by C. fulvum enable the fungus to effectively colonize the tomato. The objective of this project is to identify and functionally characterize novel effectors and candidate effector genes/proteins. The studen will (i) clone candidate genes in a binary vector for transiest expression, (ii) functionally analyse the protein, (iii) knock-out the candidate genes in C. fulvum and (iv) study virulence of the mutants on tomato by fluorescence microscopy.
Identification of Avr1, Avr3, Avr5 and Avr11 avirulence genes from Cladosporium fulvum
Effectors secreted during infection by C. fulvum can be recognized by Cf proteins. In this project, we want to identify the effectors that are recognized by the matching proteins Cf-1, Cf-3, Cf-5 or Cf-11, respectively. Putative effectors will be cloned in the PVX vector which will subsequently be screened tomato plants carrying the different proteins. The student will (i) clone candidate genes into PVX vectors, (ii) screen each construct in tomato that contains Cf-1, Cf-3, Cf-5 and Cf-11 and (iii) functionally characterize the candidate genes.
Comparative genomics of related fungal plant pathogens Cladosporium fulvum and Dothistroma septosporum
The related Dothideomycete fungal plant pathogens Cladosporium fulvum and Dothistroma septosporum both grow in intercellular spaces in close vicinity of mesophyll cells, but have different lifestyles and infect different host plants. C. fulvum is a biotroph infecting tomato, while D. septosporum is a necrotroph infecting pine. We sequenced their genomes in order to find cues for their differences in pathogenic behaviour and host-specificity. Students with an interest in biology and bioinformatics of fungi can study, by bioinformatics approaches, the role of several biological components and processes in fungal pathogenicity including (i) secreted effectors and enzymes/ enzyme inhibitors, (ii) transposons and their activities, (iii) transcription factors (iv) secondary metabolite gene clusters, and (v) pseudogenization and repeat-induced point mutations.
Characterization of Cladosporium fulvum secondary metabolome
Analysis of C. fulvum genome showed that it contains many genes predicted to be involved in secondary metabolite biosynthetic pathways. As fungal secondary metabolites are biologically active compounds, including host-specific toxins and mycotoxins. Those produced by C. fulvum may play an important role during tomato infection. The student will (i) isolate secondary metabolites from in vitro cultures and from infected tomato, (ii) perform bioassays with these extracts to identify biological activities, (iii) construct knock-out mutants of candidate secondary metabolism genes, and (iv) evaluate secondary metabolite production in these mutants.
Role of pseudogenization in reducing the pathogenicity potential of the leaf mold pathogen Cladosporium fulvum
EffePlant pathogens use a wide arsenal of effectors to colonize their host. Among these effectors, proteases are thought to play a critical role by degrading plant defense proteins. C. fulvum is a biotrophic fungus of tomato. We identified in its genome 60 secreted proteases. Surprisingly, we found that six of them (10%) were wrongly annotated due to the presence of in frame stop codons, suggesting that these are pseudogenes. It seems as if pseudogenization occurs more frequently in genes encoding secreted proteases than in any other type of genes. We hypothesize that pseudogenization of proteins potentially harmful to the plant could be linked to the biotrophic lifestyle of C. fulvum. In order to answer this question, the student will be asked to remove the in frame stop codons of pseudogenes by using site-directed mutagenesis. The obtained full length genes will then be cloned in a vector for over-expression in C. fulvum. The transformants over-expressing these new proteases will be tested for pathogenicity on plant and for protease activity using an activity-based profiling approach.
Functional analysis of proteases and protease inhibitors of Cladosporium fulvum
The genome of the leaf mold tomato pathogen C. fulvum contains 60 secreted proteases and 5 secreted protease inhibitors. These two classes of secreted proteins play an important role in the pathogenicity and recognition of fungal pathogens and C. fulvum in particular. In order to identify C. fulvum proteases and protease inhibitors that are important for pathogenicity, the student will be asked to assess the expression profile of all these genes using quantitative RT-PCR. Those that are up-regulated during tomato infection will be chosen for functional analysis. Knock-out mutants of candidate genes will be characterized for their pathogenicity on tomato. In addition, these C. fulvum protease- and/or protease inhibitor-encoding genes will be cloned in a vector for production in Pichia pastoris. Purified proteins will then be used for performing in plant activity-based profiling.