Description: In May 2016, the remote-controlledAutomatedFiltration System forMarine Microbes (AUTOFIM) was implemented in parallel to the Long Term Ecological Research (LTER) observatory Helgoland Roads in the German Bight. We collected samples for characterization of dynamics within the eukaryotic microbial communities at the end of a phytoplankton bloom via 18S meta-barcoding. Understanding consequences of environmental change for key marine ecosystem processes, such as phytoplankton bloom dynamics requires information on biodiversity and species occurrences with adequate temporal and taxonomic resolution via time series observations. Sampling automation and molecular high throughput methods can serve these needs by improving the resolution of current conventional marine time series observations. A technical evaluation based on an investigation of eukaryotic microbes using the partial 18S rRNA gene suggests that automated filtration with the AUTOFIM device and preservation of the plankton samples leads to highly similar 18S community profiles, compared to manual filtration and snap freezing. The molecular data were correlated with conventional microscopic counts. Overall, we observed substantial change in the eukaryotic microbial community structure during the observation period. A simultaneous decline of diatom and ciliate sequences succeeded a peak ofMiracula helgolandica, suggesting a potential impact of these oomycete parasites on diatom bloom dynamics and phenology in the North Sea. As oomycetes are not routinely counted at Helgoland Roads LTER, our findings illustrate the benefits of combining automated filtration with metabarcodingto augment classical time series observations, particularly for taxa currently neglected due to methodological constraints.

Description: Dinoflagellate species of the genus Dinophysis have become target organisms for surveillance and monitoring of microalgae as they may produce potent diarrhetic shellfish toxins and therefore have negative socio-economic impacts. The formation of Dinophysis blooms as well as toxin composition and cellular toxin content depends on several multifactorial climate and environmental drivers and it might be expected that the occurrence of toxic events becomes more intense, widespread, frequent and unexpected in future decades due to climate variability. Conventional methods for the identification of microalgae e.g. microscopy, still have some deficiencies as they are very time-consuming and need special knowledge and experience, especially in case of difficult morphological species distinction. Standard quantification methods also might fail to detect and determine Dinophysis species due to their typically low cell densities and their spatial heterogeneity (=patchiness). Therefore innovative technologies for environmental monitoring of toxic microalgae are needed to prevent humans and aquatic environments from toxic threats and damage. We analysed the occurrence, abundance and dispersal of toxic dinoflagellate species in Nordic seas and the Arctic Ocean. Genetic analyses included a modular composed autonomous rRNA biosensor approach that allows rapid, precise and economically efficient high-resolution quantification and identification of microalgae in aquatic environments. Next generation sequencing (Illumina) was used to get additional information on distributional patterns of the most common dinoflagellate species in the observation area.

Description: Microalgae are the major producers of biomass and organic compounds in the aquatic environment. Among them there are toxic species (mainly dinoflagellates) known to have the potential to form Harmful Algal Blooms, the so called HABs. HABs are occurring more often and at new locations. In general, knowledge about biogeographic distribution of harmful algae in the northern hemisphere is limited and patchy. During this project, we will study the seasonal dynamics of marine protists, with special emphasis on toxic algae in the North Sea. Samples will be taken from four geographical distinct locations in the German Bight and from the Orkney Islands. Protist community composition will be assessed by Illumina sequencing and a newly developed fully automated biosensor system. The latter allows for automated sampling and filtration of water samples and automated detection of selected toxic algal species, while the detection is based upon electro chemical quantification of RNA by sandwich hybridization. Here we show first results of calibrating the biosensor for selected toxic algae that are known to occur in the North Sea. Furthermore, we also show preliminary results of the characterization of protist communities from spring to autumn 2016 at four different observation locations in the North Sea via Illumina sequencing.

Description: Information on recent biomass distribution and biogeography of photosynthetic marine protists with adequate temporal and spatial resolution is urgently needed to better understand consequences of environmental change for marine ecosystems. Here we introduce and review a molecular-based observation strategy for high resolution assessment of these protists in space and time. It is the result of extensive technology developments, adaptations and evaluations which are documented in a number of different publications and the results of recently accomplished field testing, which are introduced in this review. The observation strategy is organized at four different levels. At level 1, samples are collected at high spatio-temporal resolution using the remote-controlled automated filtration system AUTOFIM. Resulting samples can either be preserved for later laboratory analyses, or directly subjected to molecular surveillance of key species aboard the ship via an automated biosensor system or quantitative polymerase chain reaction (level 2). Preserved samples are analyzed at the next observational levels in the laboratory (level 3 and 4). This involves at level 3 molecular fingerprinting methods for a quick and reliable overview of differences in protist community composition. Finally, selected samples can be used to generate a detailed analysis of taxonomic protist composition via the latest Next Generation Sequencing Technology (NGS) at level 4. An overall integrated dataset of the results based on the different analyses provides comprehensive information on the diversity and biogeography of protists, including all related size classes. At the same time the cost effort of the observation is optimized in respect to analysis effort and time.

Description: nformation on recent diversity and biogeography of Arctic marine protists with adequate temporal and spatial resolution is urgently needed to better understand consequences of environmental change for marine ecosystems. Here, we introduce a molecular-based observation strategy for high resolution assessment of marine protists in space and time, even in remote areas such as the Arctic Ocean. The observation strategy involves molecular analyses (e.g. Next Generation Sequencing (NGS) or quantitative PCR) of samples, collected with a set of complementary methods such as a newly developed automated under-way sampling device, CTD-casts and moored sediment traps. This integrated approach allows generating detailed information on marine protist community composition or abundance with adequate resolution. Currently, the observation strategy is organized at four major levels. At level 1, samples are collected at high spatial and temporal resolution based on under-way sampling with the remote-controlled automated filtration system AUTOFIM (developed in the COSYNA-project), and sampling at fixed stations based on CTD-casts and moored sediment traps. Resulting samples can either be preserved for later laboratory analyses, or directly subjected to molecular surveillance of key species aboard the ship, e.g. via quantitative polymerase chain reaction (level 2). Preserved samples are analyzed at the next observational levels in the laboratory (level 3 and 4). This involves at level 3 molecular fingerprinting methods for a quick and reliable overview of differences in protist community composition. Finally, selected samples can be used to generate a detailed analysis of taxonomic protist composition via the latest Next Generation Sequencing Technology (NGS) at level 4. An overall integrated dataset of all results provides comprehensive information on the diversity and biogeography of protists, including all related size classes. In the future, the observation strategy for Arctic marine protists will be part of the Molecular Microbial Observatory envisioned for the Arctic observatory FRAM (Frontiers in Arctic Monitoring).

Description: Biohazards like harmful microalgae have negative impacts on human population, local environments and economies. Therefore innovative technologies for environmental monitoring and surveillance of harmful microalgae are needed to prevent humans and aquatic environments from toxic threats. In our project we developed a modular composed semi-autonomous approach for rapid, precise and economically efficient monitoring of microalgae in aquatic environments. The approach involves two modules. The automatic and remote-controlled filtration module is a unit for preparation of free nucleic acids from water samples. This includes sampling, filtration and cell lysis, mediated by ultrasound. Subsequently, the free nucleic acids e.g. rRNA can be detected with an automated nucleic acid biosensor, based on a sandwich-hybridization of target DNA with species-specific designed probes. Hybridization is transformed in an electrochemical and measureable signal. Probes, specific for different target organisms can be applied for molecular detection. Thus the nucleic acid biosensor allows the assessment of a broad spectrum of microorganisms including harmful microalgae. Filtration and detection module should be connected to one compact, autonomous system that can be used for different fields of application.

Description: Planktonic algae are the most abundant photosynthetic organisms. They are the basis of the marine food web, and changes in phytoplankton communities generally provide an early indication for climate-driven modifications of marine food webs and the whole ecosystem. Harmful algal blooms (HAB) are a subset of planktonic algal species that have negative impacts on humans and aquatic environments. The formation of HABs depends on several multifactorial climate and environmental drivers that influence timing and frequency of these algal blooms. There is some evidence that the occurrence of HAB might become more intense, widespread, frequent and unexpected in future decades due to climate variability. In North ocean regions the global climate change is reflected by changing environmental parameter, such as increasing sea surface temperature, modified water mass stratification and rising freshwater content in the Arctic realm. Within this study the occurrence, abundance and dispersal of toxic algae species is analysed in Nordic seas and the Arctic Ocean, based on molecular detection with a nucleic acid biosensor. Alongside with this it will be assessed whether biosensor systems can serve as an early warning system for human health policies in the field of water resource management.