In this paper, we describe and evaluate the construction of a metatranscriptome dataset from a pelagic crustacean zooplankton community. We sampled zooplankton in one marine station, named LW02, in the North Sea, in both winter and summer, and generated transcripts using Oxford Nanopore Technology (ONT), a third-generation nanopore-based sequencing technology. ONT is, uniquely, capable of sequencing RNA directly, rather than depending on reverse transcription and PCR, and applicable to be used directly in the field. We found that metatranscriptomics is capable of species detection, including screening for the presence of endoparasites, hence competing with morphological identification. The most abundant mRNA transcripts with known function coded for essential metabolic processes. Although small in scale, our study provides the basis for future efforts to characterize the metatranscriptome of marine zooplankton communities and its application in biomonitoring programs.

In this research we investigated whether or not marine algae growth was affected when exposed to environmentally realistic mixtures of chemicals collected from the Belgian part of the North Sea (BPNS). To explore this, we used a specific sampling technique that “filters” chemicals from the seawater and collects them in a way allowing to transfer these mixtures from the field to the laboratory. Once brought to the lab, we determined the concentration levels of 88 personal care products, pesticides and pharmaceuticals. Next, we exposed marine algae to the so collected mixtures of chemicals and recorded the algae’s growth over three days. We surprisingly observed growth stimulation for those mixtures with less sample handling and short storage while those undergoing repeated handling and longer storage showed no effects. In an explorative try to define the differences in the mixture composition of the effect- and no-effect causing samples, we were indeed able to define these differences but our findings could not be linked to the biological effects observed. In conclusion, we have shown that environmentally realistic mixtures of contaminants collected in the BPNS can enhance the growth of a marine algae species but it remains challenging to define those substances within these mixtures that actually cause effects on algae growth.

Recent studies have shown that toxicity of metals to Daphnia magna depends on the temperature. In a population experiment, we investigated if the effect of temperature on nickel (Ni) sensitivity observed on the apical level can be extrapolated to the population level. However, we observed no consistent population-level effects of Ni at concentrations that significantly affected reproduction. An individual-based model (IBM) with the dynamic energy budget (DEB) theory for Daphnia magna was calibrated based on Ni toxicity data at three temperatures (15, 20 and 25°C). Using the model, we confirmed the unexpected absence of Ni effects at the population level.