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In May 2016, the remote-controlled Automated Filtration System for Marine 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 of Miracula 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.

Copyright: 2020 Metfies et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was supported by institutional funds of the Alfred -Wegener- Institut Helmholtz-Zentrum fr Polar-und Meeresforschung, Germany and funds of the Helmholtz Association for financing the Helmholtz-University Young Investigators Group PLANKTOSENS (Grant VH-NG-500).

Annually recurring spring phytoplankton blooms with high net primary production characterize coastal seas such as the North Sea. This productivity is fundamental for the associated marine ecosystems and biogeochemical cycles [1]. A number of environmental parameters drive the dynamics of plankton communities and phytoplankton blooms. These involve hydrographic and physical parameters, or nutrient availability, and interactions between planktonic organisms such as grazing or parasitism. Consequently, environmental shifts related to climate can be expected to significantly impact plankton composition, and bloom dynamics [2;3]. First experiments suggest that warming might accelerate termination of phytoplankton spring blooms by fungal parasites [4]. Long-term investigations of the composition of the marine microbial communities are a valuable approach for the overall understanding of impacts of environmental change on plankton communities and related marine ecosystem processes. Such data collections are ideal for illustration of patterns in phytoplankton bloom dynamics and for the elucidation of the underlying mechanisms such as environmental forcing or nutrient availability also at historical time scales. Several oceanographic monitoring programs and observation strategies exist which can provide interdisciplinary insights into processes and dynamics of the marine ecosystem, covering different research areas worldwide, including North Atlantic seas [2;3;5]. The Alfred Wegener Institute, Helmholtz Centre for Polar- and Marine Research maintains the LTER series of the Biologische Anstalt Helgoland, Helgoland Roads in the German Bight (North Sea, 5411'N 754'E), approximately 60 km off the German mainland. The dataset represents the longest most detailed daily dataset available [2]. It comprises a phytoplankton time series (started in 1962) and a zooplankton time series (started in 1975) along with time series for inorganic nutrients, salinity and temperature. More recently, these regular long-term measurements are complemented with automated measurements via a stationary FerryBox System that was installed on Helgoland in 2005. A FerryBox-System is an autonomous or semi-autonomous device located on ships of opportunity or fixed monitoring platforms (as on Helgoland) and has the capacity to autonomously generate information on chlorophyll a (Chla) concentration and other key oceanographic parameters [6]. The high sampling frequency of the Helgoland Roads time series has provided a unique opportunity to study long-term trends. This includes abiotic and biotic parameters, but also ecological phenomena such as dynamics and timing of the spring bloom, seasonal interactions between different food web components, niche properties, and the effects of newly introduced species [2;3;7]. The assessment of phytoplankton in the framework of the LTER Helgoland Roads is currently mainly based on microscopic identification and cell counts determined by morphological features of the observed cells. Light microscopy, commonly used for eukaryotic microbial assessment, is very time consuming and requires a high level of taxonomic expertise. Therefore, unlike the Helgoland Roads time series, most phytoplankton time series based on routine microscopy are limited with respect to both temporal and taxonomic resolution. Furthermore, information on occurrence and abundance of smaller phytoplankton species is limited, as different genera with lacking sufficient morphological characteristics for identification are often amalgamated into size classes of different unidentified species. Over the past two decades molecular techniques have become indispensable tools in phytoplankton research, encompassing both evolutionary and ecological studies [8;9;10]. These molecular techniques also hold great promise for overcoming the limitations of phytoplankton time series which rely predominantly on microscopic assessments as described above. Next generation sequencing (NGS) in particular has provided high resolution information on taxonomic composition of marine protist communities [11;12;13]. Decreasing analysis costs in this field coupled with considerable progress towards a greater level of automation into the sampling and analysis process now facilitate integration of molecular based observations into LTERs in order to refine regular observations of marine microbes.

In this study, we used the remote-controlled automated filtration system AUTOFIM (iSiTEC GmbH, Germany) to collect samples of marine microbes for molecular analyses. Measurements of key physicochemical parameters via an adjacent FerryBox-system complemented the sampling. Based on this unique combination of three cutting-edge marine observational approaches we were able to provide novel insights into changes in the eukaryotic microbial community composition towards the end of the spring bloom 2016 for better understanding eukaryotic plankton succession and bloom phenology in the context of the highly variable physicochemical environment at the island of Helgoland.

Photos and drawings of the entire automated filtration system AUTOFIM (upper panel). The arrow in the upper panel represents the linear working direction of the push bar and the stetting of the treatment units (A-D). A: sample reservoir, B: filtration unit, C: push bar for filter application, D: sample archive.

The samples for manual filtration were collected via one liter glass bottles (Schott, Germany). Manual filtration was carried out at maximum 200 mbar using Isopore Membrane Filters (Millipore, USA) with the pore-size 0.4 μm and a diameter of 45 mm. In accordance to standard sampling protocols for environmental DNA (e.g. Metfies et al., 2016), the samples collected via manual filtration were directly frozen at -20C.

The impact of automated filtration and preservation on the results of a molecular assessment of plankton community composition was evaluated by comparing sequence libraries obtained from samples collected at the FerryBox-sampling site via AUTOFIM with samples collected via manual filtration. The average number of OTUs retrieved from a sample was highly similar for both two approaches. Prior to exclusion of OTUs with overall sequence abundance

Dinoflagellata, haptophyte, chlorophyte, ciliophora, ochrophyta, and choanoflagellida constituted more than 90% of all eukaryotic microbial sequences identified in the individual samples (Fig 5). The community changed significantly from period A to period B. Sequence abundances of ochrophyta, ciliophora and choanoflagellida were higher in period A than in period B, while chlorophyta and haptophyta sequence abundances were lower in period A than in period B (Fig 5).

A decline in sequences of the larger phototrophic diatom genera Pseudo-nitzschia, and Chaetoceros specifically characterized the decline in ochrophyta sequences (Fig 6). An OTU with 99% similarity to the diatom parasite Miracula helgolandica increased during period A and peaked in abundance on May 12th. Subsequent to the peak in sequence abundance of Miracula helgolandica, sequence abundance of Pseudo-nitzschia pungens was significantly reduced, suggesting a potentially negative impact of the parasite on the growth rate of this diatom species.

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