Our main research objectives are:
- Understanding the evolution of groups and species with emphasis on dinoflagellates and haptophytes.
- Studying the phylogeny and population genetics of toxigenic microalgae. Estimation of diversity and biogeography harmful algal species.
- Studying the evolution of genes and processes related to growths, cell communication and defense/toxicity by applying genomic approaches.
Species interactions and underlying processes
To explain mass proliferation (bloom formation) of phytoplankton and the corresponding consequences on the ecosystem, it is crucial to understand the underlying processes of species interaction of the involved species which might un-couple the growth regulative processes such as biomass loss through grazing, competition and infection. Such processes may involve un-coupling intrinsic growth regulation, from extrinsic factors such as loss through grazing, competition and infection (virus or parasites). The introduction of genomic approaches into marine sciences has opened the opportunity to study the underlying processes of species interaction and the biosynthesis of the chemical compounds involved in communication, competition and defence. The combination of functional genomic tools - microarrays and next generation sequencing technologies as well as the accompanying bioinformatics tools - provide not only information about single biosynthetic pathways, but also about the “symphony” of regulation during transcription. In comparative approaches we investigate the impact of competition, grazing and infection to identify responses related to: a) species interactions in general; b) species contact/wounding; and c) chemical (waterborne cues) induction.
Diversity, phylogeny and population genetics
In order to understand the impact of potential harmful species on plankton communities we do have to know the biodiversity in a given environment. We study the diversity based on molecular markers using next generations sequencing (NGS). Those data can be linked with metatranscriptomic data in order to link diversity with potential related metabolic processes. We have an emphasis on Dinoflagellate metatranscriptomic since there mRNA transcript exhibit at the 5’ and a splice leader signature, which is unique to dinoflagellates and enables us to subtract the dinoflagllate signal from others. We study the biogeographic distribution of selected toxic target species with molecular method, such as fluorescence in situ hybridization and/or quantitative PCR.
To address question about the evolution of species and to understand their success in the environment we study the phylogeny of the species and the population structures. A microalgal bloom is comprised of a multitude of genotypes and is thus not clonal in the conventional sense. Particularly for microalgae, it is important to work with many well-characterised genotypes of a certain species/population, to account for the wide clonal variation. We focus on phenotypic characterisation in terms of growth, allelochemical properties and bioactive substance production, where bioassay systems exist. We apply molecular markers such as AFLP and microsatellites to genotype field isolates. Besides performing population genetic analysis, we investigate if certain phenotypic traits are linked to genetic markers (QTL mapping and association analysis) and are hence under selection. Any ecological important species interactions as well as ecophysiological tolerance limits are also selection pressures and drive genotypic diversity. If there is heritable variation (genotype diversity), evolutionary change will take place. Once selectively relevant polymorphisms are identified, predictions as to the evolutionary potential of populations are possible.
Growth and hence the success of a microalgae in the planktonic community is strongly depended on the basic growth-supporting processes. The so-called “bottom-up” control is primarily determined by abiotic factors, such as light, temperature, salinity, pH/CO2 and nutrients. We therefore conduct laboratory controlled growth experiments where the physiology of the cells is carefully investigated. We applying functional genomics approaches (microarray, EST libraries, qPCR) to study the underlying processes how our target species or communities (metatranscriptomics) regulate nutrient stress and or climate change related scenarios such as temperature increase and pH shifts/changes in carbon chemistry. Besides the process understanding we aim to identify marker genes, which might indicate a physiological status of the cell/community, like nutrient starvation or exponetional growth.
Genomics and Evolution
Genomic characterisation can be conducted on different levels. We cannot effort to sequence all species of interest, in particular in the evolutionary rich unicellular eukaryotic biota. In most of the case we generate express sequence tags (ESTs) libraries, which are short sequences fragments derived from cDNAs. Those EST dataset are excellent tools for genomic characterisation, estimation of the physiological capabilities, can be used for gene mining and phylogenomic studies. We generated several EST libraries over the last few years have been shown to be a rich source for –phylogeny, non-neutral markers, microarrays, gene candidates, and comparative genomics. However, we can reach with EST libraries approx. 70% of the potential gene content, hence for some target organisms we need whole genome projects. Genome projects have been shown to be a rich source for identifying unexpected pathways (urea cycle in diatoms) and foodprints of selection and evolution such as evolution of plastids across the eukaryotic crown lineages or more specific the multicellularity of cyaonobacteria due to comparative approaches. We are interested in the link between genomes and ecotypes: the genomic bases of ecological niche adaptation. For this approach we compare the genome sizes and we investigate in respect to a reference genome potential gene loss, sequence divergence or gene duplication, which can be analysed in respect for ecotypes and species divergence.