The majority of plant diseases are caused by fungi and, in spite of chemical fungicides in pest management, these fungi still are responsible for extensive economical losses. Chemical fungicides can have drastic effects on the environment and the consumer, and a reduction of their application in agriculture is therefore desirable. Trichoderma atroviride is a filamentous cosmopolitan fungus, commonly found in soil, and isolated from both tropic as well as temperate climates. It is best known for its biocontrol capabilities against a range of phytopathogenic fungi including Rhizoctonia solani and Botrytis cinerea, which are pests of hundreds of plant crops, including tomatoes, beans, cucumber, strawberries, cotton and grapes.
Although more than 50 different Trichoderma-based agricultural products are registered, the knowledge of the underlying intracellular mechanisms and the involved genes which enable the fungus to antagonize phytopathogenic fungi is still very limited. During the mycoparasitic interaction, the host fungus is recognized and attacked, followed by nutrient utilisation by the mycoparasite, killing the host before or just after invasion. Investigations on the underlying signal transduction pathways revealed that G-protein signalling and pathways involving MAP-kinases play important roles in the recognition of host-derived signals and in the activation of the mycoparasitic response in T. atroviride
The aim of the project is to identify mycoparasitism-relevant agents specifically induced by a living host fungus by combining genome-wide expression profiling and proteomic approaches. By including signaling mutants with altered mycoparasitic features as tools, information about key molecular processes participating in mycoparasitism will be obtained.
We collaborate with Drs Susanne Zeilinger and Martina Marchetti at the Technical University of Vienna. Dr Zeilinger is the expert on Trichoderma and leads the project. Dr Marchetti is responsible for the study of protein expression and phosphorylation, while our group contributes microarray design, transcription level expression profiling, and data analysis.