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 nutrient flows, they remain largely understudied. This is mainly because they are difficult to identify and as a consequence frequently overseen. Recently, environmental DNA surveys reveal an unexpectedly large diversity of undescribed fungi in aquatic ecosystems. A substantial part of these “unknown” sequences certainly belong to phytoplankton parasitic fungi. Up to date they remain, however, largely invisible for the molecular ecologist because so far, only a tiny proportion of validly described phytoplankton associated fungi is represented in molecular databases. For example, from >400 morphologically described chytrid species, i.e. zoosporic fungi known to be parasitic and/or saprotrophic on phytoplankton, less than 20 have currently18S rDNA sequences deposited in molecular sequence databases. This is an enormous drawback when trying to interpret sequence data obtained during field studies.
The first objective of my DFG project is bridging the current gap between morphological and molecular studies using both classical cultivation dependent and state of the art cultivation independent approaches (e.g. single cell/colony sequencing). 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 phytoplankton parasitic fungi will also provide a major contribution to resolving evolutionary key events in the basal fungal tree.
The second objective is to increase our knowledge on the ecophysiological features of phytoplankton-fungi interactions. A 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. This will provide important, hitherto missing, 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 in the context of global change.
In my research I use a combination of approaches and methods: cultivation, field monitoring/experiments, lab experiments, fluorescence microscopy, 1st, 2nd and 3rd generation sequencing, and agent-based simulation modeling.