Molecular and ecophysiological diversity of phytoplankton-fungi associations.

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Fungal parasites of phytoplankton are ubiquitous and constitute an integral component of aquatic ecosystems. Despite the growing evidence that these parasitic fungi have profound effects on ecosystem functioning via top-down control of phytoplankton blooms and by providing alternative carbon and nutrient flows, yet, they remain largely understudied. This is mainly because of methodological biases, e.g., they are difficult to identify by morphology and consequently are frequently overseen. Recently, environmental DNA surveys reveal an unexpectedly large diversity of non-described fungi in aquatic ecosystems. A substantial part of these unknown sequences belong to phytoplankton parasitic fungi. Up to date they remain largely invisible for molecular ecologists since only a tiny proportion of validly described phytoplankton associated fungi is included in the molecular databases. Therefore, the main objective of the present project is to bridge this gap between morphological and molecular studies using both classical cultivation dependent and state of the art cultivation independent approaches. This will allow environmental genomics to obtain access to more than a century wealth of taxonomic knowledge and improve the linkage between diversity and function of fungi in aquatic ecosystems. Phylogenetic integration of this hitherto neglected group of parasitic fungi on phytoplankton will constitute a major contribution to resolving evolutionary key events at the base of the fungal tree. The second objective is to increase our knowledge on the ecophysiological features of phytoplankton-fungi interactions. Additionally, our unique set of model systems enables physiological experiments to assess the effect of temperature and light on the interaction of well characterized phytoplankton-fungal isolates displaying taxonomic and ecological (specialist vs. generalist) variability. These mechanistic studies will provide hitherto missing, but important baseline data regarding taxon-specific and trait related physiological responses of phytoplankton-fungi interactions. Such data is crucial to improve current and future predictions of fungal infections on phytoplankton dynamics as well as food web dynamics in the context of global change.