Skip to main content

Advertisement

Toxicity and neurotoxicity profiling of contaminated sediments from Gulf of Bothnia (Sweden): a multi-endpoint assay with Zebrafish embryos

Article metrics

Abstract

Background

The toxicological characterization of sediments is an essential task to monitor the quality of aquatic environments. Many hazardous pollutants may accumulate in sediments and pose a risk to the aquatic community. The present study provides an attempt to integrate a diagnostic whole mixture assessment workflow based on a slightly modified Danio rerio embryo acute toxicity test with chemical characterization. Danio rerio embryos were directly exposed to sieved sediment (≤ 63 μm) for 96 h. Sediment samples were collected from three polluted sites (Kramfors, Sundsvall and Örnsköldsvik) in the Gulf of Bothnia (Sweden) which are characterized by a long history of pulp and paper industry impact. Effect data were supported by chemical analyses of 237 organic pollutants and 30 trace elements.

Results

The results show that malformations and neurotoxic compounds are the main drivers of differentiation in chemical and effects analyses, respectively. Specific spinal cord malformations and delayed hatching were observed only in sediments from Kramfors while light hyperactivity was seen only after exposure to sediments from Sundsvall.

Conclusions

Our experiments demonstrate that specific chemical profiles lead to specific effect patterns in Danio rerio embryos. In fact, behavioral endpoints could help detect the exposure to neurotoxins, and the observation of body malformations seems to be a potential tool for the identification of site-specific pollutants as polychlorinated biphenyl (PCBs), brominated flame retardants (BFRs) and several pesticides. Overall, results show the suitability of Danio rerio embryos for the fast screening of sediment samples.

Background

Sediments are a well-known sink for a large variety of pollutants that may cause distress to benthic and pelagic species in case of their remobilization to the water-phase [1]. Risk assessment of complex mixtures may involve component-based approaches by applying chemical analysis together with measured or predicted toxicity data of individual components and mixture risk modeling or whole mixture approaches using bioassays. Both are complementary and thus their integration using chemical and bioanalytical tools for the characterization of sediment contamination should provide a more comprehensive picture of ecotoxicological risks to aquatic organisms [2]. In addition to effect concentrations, bioassays may provide information on modes of action (MoA) and may thus improve the diagnosis of risks in sediment samples [3,4,5,6,7,8,9,10]. In the last years, batteries of sensitive, rapid and cost-effective in vitro bioassays have been proposed as promising tools for the toxicological profiling of environmental samples and were also successfully applied for the characterization of aquatic sediments [11,12,13,14,15,16,17]. However, despite the undoubted advantages of cell-based assays for the analysis of toxicological patterns in sediments, in vitro results cannot directly predict the biological responses in more complex organisms and aquatic communities [18]. Moreover, only a minority of MoA covered by in vitro assays are suited to test complex environmental mixtures [19] including important toxic endpoints such as neurotoxicity [20]. Thus, in vitro tools need to be complemented with diagnostic in vivo monitoring. However, accepted and validated workflows for the in vivo toxicological profiling of complex mixtures including sediment contamination are still lacking.

One of the most promising organisms for diagnostic in vivo testing of sediment extracts is zebrafish (Danio rerio) embryos, which are a versatile model suitable for high-throughput analysis while keeping several advantages of in vitro approaches (i.e., low-cost, sensitivity, short duration of the test). The fish embryo toxicity test (FET) with Danio rerio has been considered as a good surrogate for the acute toxicity fish test [21] and was successfully used in several studies for the detection of toxicity and neurotoxicity in sediments samples [9, 22,23,24]. One of the major advantages of the FET with Danio rerio is the possibility to monitor several toxic endpoints including the modification of molecular processes and malformations which can be related to the exposure to specific pollutants [25,26,27,28]. Further, the FET with Danio rerio offers the possibility to monitor changes in behavioral patterns (i.e., swimming activity, early spontaneous movements), which may be relevant also for the population level [29, 30].

The present study provides a first attempt to integrate a diagnostic whole mixture assessment workflow based on in vivo toxicological profiling of Danio rerio after exposure to sediments for 4 days with a component-based approach applying chemical analysis of a wide target list of organic and inorganic chemicals. The objectives of the present study were (1) to validate this approach with sediments collected from the coast of Gulf of Bothnia (GoB, Baltic Sea, Sweden) (2) to identify effect patterns with multi-endpoint diagnosis in zebrafish embryos and support them with chemical analyses and (3) to offer a first in vivo ecotoxicological profile of sediment samples.

Methods

Sampling and sample preparation

Sediments were collected in GoB in an extensive sampling campaign in 2013 as part of the Swedish research project REACT. Three sites were selected in the bays of the city of Kramfors, Örnsköldsvik and Sundsvall, Sweden. With a grab sampler, samples from the top layers of the sediments with 5–10 cm thickness were taken. The three sites have a long history of pulp and paper industry, saw mills, as well as other industrial activities with possibly elevated levels of a series of legacy contaminants in the sediments, including polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyl (PCBs), organochlorine insecticides (OCPs), polychlorinated dibenzo-p-dioxins (PCDDs), polychlorinated dibenzofurans (PCDFs) and metals. The three sites are also characterized by the input of waste water treatment plants (WWTPs) and, thus, may receive additional micropollutants. After sampling, the samples were stored in triplicate in plastic containers, transported to the laboratory on ice and stored at − 20 °C until freeze-drying. The freeze-dried sediments were sieved to 63 µm and stored in brown glass bottles at − 20 °C until further treatment. Details about sampling sites, total organic carbon, total inorganic carbon and black carbon are provided in Additional file 1: Table S1.

Sediment extraction for chemical analyses

For LC- and GC-HRMS analyses for organic compounds, samples were extracted according to Massei et al. [31] with slight modifications. Extraction and analysis were based on the amount of total organic carbon (TOC) rather than on dry weight assuming TOC as the predominant phase for the accumulation of chemicals and to keep matrix effects in MS on a similar level. Further details of the pressurized liquid extraction (PLE) method and the preparation of the normal phase (NP) for clean-up are given in Additional file 1: S1.

For trace element analysis the sequential extraction procedure followed the three-steps sequential extraction of Rauret et al. [32]. Blanks and certified reference material (CRM) BCR-701 were used at every step of the extraction process to evaluate the instrumental method and for calibration. The element recovery rates from the CRM in each extraction solution were between 85 and 112% and similar to values published by Marguı et al. [33] and Tokalıoğlu and Kartal [34]. All samples were finally digested in aqua regia as follows. Aliquots of 250 mg of sample material were funneled into quartz microwave vessel with aqua regia (6 mL HCl; 37%, 2 mL HNO3; 65%) in a pressure- and temperature-controlled microwave. The elements in the soil extracts and digests were determined by inductively coupled plasma MS (ICP-MS/MS; Agilent 8800, Agilent Technologies, Germany) according to the norm for application of inductively coupled plasma MS (ICP-MS) EN ISO 17294-2:2017-01 [35].

Targeted chemical analysis of organic and inorganic pollutants

A list of 237 organic compounds likely to occur in sediments [i.e., pesticides, industrial chemicals, steroids, persistent organic pollutants (POPs)] and 30 trace elements including the main heavy metals were selected for chemical analysis covering a wide range of physico-chemical properties. Details on equipment, target compounds list, LC, GC, and MS conditions, quantification, method detection limits (MDLs), and internal standards are provided in Additional file 1: S2–S4, Tables S2–S6, S9; Additional file 2: Tables S7, S8. Additional methodological details on target chemical analyses are described in Massei et al. [31].

Fish culture, fish embryo production and selection

Adult zebrafish of the strain UFZ-OBI had been originally established from a wild type strain purchased from a local supplier (OBI hardware store, Leipzig) and had been bred at the UFZ for more than 13 generations. Fish were kept in 14-L aquaria with 25–30 fish each with a sex distribution between female to male of 1:2. The light–dark rhythm was 14:10 h and the water temperature was 26 ± 1 °C. Water parameters were measured frequently (pH 7–8; water hardness 2–3 mmol/L, conductivity 540–560 µS/cm, nitrate < 2.5 mg/L, nitrite < 0.025 mg/L, ammonia < 0.6 mg/L, oxygen saturation 87–91%). Within 30 min after spawning, eggs were collected using a grid covered dish and successively cleaned with aerated ISO standard dilution water (ISO-water) as specified in ISO 7346-3. Developmental stages were identified according to Kimmel (1995). The fish embryo acute toxicity test was conducted as described in the OECD TG 236 and in Bittner et al. [36], but additional endpoints were included.

Danio rerio multi-endpoints toxicity assay with sediments contact test

Twenty fertilized eggs were directly exposed to the freeze-dried sediments fine fraction (≤ 63 μm) in 40 mL of ISO-water (1 embryo/2 mL ISO-water) for 105 h at a temperature of 26 ± 1 °C and a photoperiod 12:12 light/dark according to the sediment contact protocol by Hollert et al. [22] with few modifications. Sediments were completely covering the bottom of the crystallization dish (total amount between 0.25 and 0.5 g) and agitated with 55 rpm. Negative control consisted in pure ISO-Water without adding inert particle or blank quartz powder. Table 1 gives an overview on the toxicological endpoints registered during exposure. Endpoints were selected according to their toxicological relevance, and their characterization in previous studies [37].

Table 1 The different endpoints observed along the 105-h exposure in Danio rerio embryos, their associated mode of action and major classes of contaminants associated

At 48-h post-fertilization (hpf) the heart is formed in two chambers and it is possible to count a regular heartbeat. The heartbeat rate was assessed by direct observation of the heart of the 5 randomly chosen embryos for 10 s. Heartbeat was counted manually and measurement time did not exceed 2 min to avoid temperature drops. From 72 hpf the hatching rate becomes stable for most of the larvae. The numbers of hatched embryos were counted at 24, 48, 72, and 96 hpf. An embryo was considered hatched when its body completely left the chorion. After 96-h embryos were selected for further locomotor activity (LA) determination [38]. For the evaluation of LA, 16 embryos for each sample and negative control were transferred to a 96 wheel plate with rectangular angles (one embryo per wheel, with 500 µL of clean ISO water). A randomized plate set-up was used to avoid interference in behavioral analyses. LA was only assessed for samples with mortality below 50% and a hatching rate above 50%. LA was registered over 50 min at a light/dark regime of 10-min dark, 20-min light and 20-min dark. Embryonic movement was tracked using the ZebraBox video tracking system (Viewpoint, Lyon, France) at a temperature of 28 ± 1 °C. Prior to the measurements, embryos were acclimated in the device for at least 10 min.

After LA evaluation, embryos were pooled together and used for acetylcholinesterase (AChE) analysis according to Küster [39]. Mortality and sublethal effects (i.e., yolk and pericardial edema, body deformations) were registered every 24 h and dead embryos were removed from the exposure media. The test media was not renewed during exposure.

One negative (ISO-Water) and one positive control (3,4-dichloroaniline, 3.4 mg/L) were tested in each experiment. The experiments were conducted in three independent replicates (n = 3). No fungal or biofilm growth was observed during or at the end of the exposure.

FET quality control

At the end of exposure, mortality of the negative control did not exceed 10%. Mortality of positive controls was in the expected toxicity range (between 30 and 80%). Oxygen concentration and pH were above the limits described by Andrade et al. [40] for developmental retardation and other sublethal effects (dissolved oxygen ≥ 6 mg/L; pH between 6 and 8). Thus, observed effects have to be considered effects of the exposure to sediment-bound chemicals and no other physical stressors.

Data treatment, multivariate, and statistical analysis

Multivariate statistical analyses and k-clustering were performed to group sites according to their chemical pattern. Data were log transformed, centered and normalized to avoid misclassification due to the differences in data dimensionality [41]. For k-means clustering, the Euclidean distance between sites was used to evaluate similarity and the Ward’s method was used in the linkage between sites and chemical patterns [41]. Statistical difference between control and treatments for lethality, heartbeat, hatching, and AchE inhibition were detected using a Tuckey multiple pairwise-comparisons test. For behavioral analysis, statistical differences between treatments and controls were detected by a non-parametric Kruskal–Wallis test with post-Bonferroni correction. All statistical analyses were performed using Microsoft Excel 2010®, Sigma Plot® (version 12.0.0.182), the software RStudio® (version 1.0.136) and the R packages drc, MASS, FactoMineR, factoextra, FitAR, chemometrics,ggplot2, dplyr, ggpubr, magrittr, and car.

Results

Occurrence and patterns of organic and inorganic pollutants

Organic pollutants

Out of the 237 selected target compounds analyzed (Additional file 2: Table S8), 71 compounds (27 PAHs, 10 PCBs, 14 pesticides and biocides (PEST), 7 compounds from industrial origin, 7 brominated flame retardants (BFR) and other brominated compounds (BC), and 6 more compounds from various groups were detected.

Among the three sites, the area of Kramfors showed the highest loads of chemicals with 53 identified compounds and a cumulative concentration of 3.6 μg/mg TOC. Native sediments from Örnsköldsvik and Sundsvall showed lower cumulative concentration with 160 and 163 ng/mg TOC, respectively.

The site of Kramfors showed higher cumulative concentrations of PAHs (3.3 μg/mg) with the 3- and 4-ringed phenanthrene and fluoranthene detected at concentrations of 830 and 535 ng/mg TOC. The sites of Sundsvall and Örnsköldsvik showed cumulative concentrations of PAHs of 133 and 146 ng/mg TOC, respectively. Additionally, BFRs were detected only in Kramfors with concentrations ranging from 0.02 to 1.1 ng/mg TOC.

The two fungicides irgarol and fenpropimorph (20 and 6 ng/g TOC), the herbicide chloridazon (0.03 ng/mg TOC) and the insecticide cyhalothrin (1.1 ng/mg TOC) were detected only in the area of Örnsköldsvik and not at other two sites of the GoB. Moreover, we identified in Örnsköldsvik the two herbicide transformations products, 2-hydroxyatrazine and 2-hydroxy-terbuthylazine- (both 0.1 ng/mg TOC).

Concentrations of organic pollutants for each site and compound are provided in Additional file 2: Table S10.

Trace elements

Overall, native sediments from the three sites of GoB showed similar total metal concentrations [from 50 up to 57 g/kg dry weight (d.w.)]. In particular, the pseudo total concentrations (aqua regia digested) of the seven priority elements proposed by the Swedish EPA monitoring list [42] (As, Cd, Cr, Cu, Ni, Pb and Zn) ranged from 0.33 to 165 mg/kg d.w. The metal concentrations (Additional file 2: Table S10) in the three fractions with different degrees of bioavailability F1 (weekly associated to carbonates, considered as readily bioavailable), F2 (reducible fraction and potentially bioavailable after perturbation) and F3 (bound to humic substances and sulfides and not bioavailable) are shown and discussed in Additional file 1: S5.

It may be summarized that metal concentrations at all three sites of GoBs were similar to background values at the river Elbe [43] as well as with the standard from Turekian and Wedepohl [44]. Total priority element concentrations detected in our study were in average 22 times lower than the one reported for contaminated surface sediments from Oskarshamn harbor (Sweden) [45] and are thus considered as unlikely to drive toxic effects.

K-means clustering of organic chemicals sediment contamination highlighted the presence of ubiquitous and site-specific pollutants (Fig. 1). We identified one cluster with compounds that are ubiquitous in all the sites of GoB (green cluster, UBI).

Fig. 1
figure1

K-means cluster of 71 detected organic chemicals (UBI: Ubiquitous; KR: Specific in Kramfors; SU&OR: Specific for Sundsvall and Örnsköldsvik). Data were log normalized and centered before analysis (Normal probability ≥ 0.99). No specific contamination patterns were highlighted for inorganic chemicals by k-means cluster analyses (data not shown)

The green cluster contains 23 PAHs and six additional compounds (2,6-diisopropylnaphthalene, dioctyldiphenylamine, diphenyl sulfone, m-Terphenyl, hexachlorobenzene and alpha-tocopherol acetate). A second cluster (red cluster, KR) is composed by compounds that were detected mostly in the area of Kramfors. The site was characterized by 5 BCs, 3-bromocarbazole, the two PCBs 118 and 52, the PAH indeno (1,2,3cd)fluoranthene and three sulfonated compounds. A third cluster (green cluster, SU&OR) contains chemicals which characterized the sites Sundsvall and Örnsköldsvik. The green cluster was characterized by the insecticide DDT and its metabolites, 8 PCBs congeners, 4 fungicides (carbendazim, fenpropimorph, irgarol and chloridazon), the biocide triclocarban, the transformation products of atrazine (2-hydroxyatrazine) and terbuthylazine (2-hydroxy-terbuthylazine), the PAHs 1-phenylnaphthalene, 9-vinylanthracene, cis-stilbene, o-terphenyl, hexachlorobenzene, and the pyrethroid cyhalothrin.

No specific contamination patterns were highlighted for inorganic chemicals by k-means cluster analyses due to similar trace element concentrations in the background range among the three sites (data not shown).

Sediments toxicological profiling with Danio rerio embryos

Lethal and sublethal effects

After 96 h, all tested sediments showed low lethality comparable to negative control (10%), see Fig. 2a.

Fig. 2
figure2

Embryo toxicity (a), heart beat (b) and cumulative hatching (c) of Danio rerio embryos after exposure to native sediments of Gulf of Bothnia. Experiment was performed in 3 independent replicates (20 embryos). ISO-Water was used as negative control and 3,4-dichloroaniline was used as positive control (3.4 mg/L). The symbol * indicates a statistical difference between treatments or between treatments and the control (p ≤ 0.01). The symbols a and b indicates a statistical difference between treatments (p ≤ 0.01). Error bars represent standard deviation

In all of the tested samples the embryos showed clear developmental retardation or yolk/pericardial edemas. All embryos exposed to sediments from Kramfors exhibited bent spines (Additional file 1: Fig. S3) and slow movements with twitching spasms. Embryos exposed to sediments from Sundsvall did not show clear sublethal effects while embryos exposed to sediments from Örnsköldsvik occasionally exhibited side swimming and slightly slower movements as compared to the control.

Heartbeat

After 48 h, native sediments from all sites caused a decrease of the embryos heart beat (average decrease 39%). The inhibition of the heartbeat was particularly strong in embryos exposed to sediments from Kramfors (47%). All three sites were statically different from the control (p ≤ 0.01). Results are shown in Fig. 2b.

Hatching rate

Embryos exposed to sediments from Örnsköldsvik and Sundsvall showed a hatching rate similar to the negative control. Embryos exposed to Kramfors had lower hatching rates at 48 (no hatching) and 72 (decrease of 84%) hours compared to those exposed to sediments from the other sites (p ≤ 0.01). After 96 h of exposure, the hatching rate of all exposed embryos was comparable in all samples. Results are shown in Fig. 2c.

LA

Negative controls showed low swimming activity during both light phases. However, the first 10 min of the dark phase were characterized by a peak of activity followed by a steady decrease of total LA in the next 10 min. This trend was already observed by other authors in previous studies [4648].Considering this trend, we analyzed the movement of fish embryos at four different phases: first light phase (L1), first 10 min of the dark phase (D1), second 10 min of the dark phase (D2) and second light phase (L2).

Embryos exposed to native sediments from GoB caused a general increase of the movement during L2. The increase was particularly strong for native sediments for Kramfors (3.1, p ≤ 0.001) and Sundsvall (3.7, p ≤ 0.001). Embryos exposed to native sediments from Sundsvall exhibited a general average increase of movement during D2 (2.6 times, p ≤ 0.001). Moreover, sediments from Sundsvall caused an increase of movements during L1 (2.4, p ≤ 0.001). Embryos exposed to sediments from Kramfors showed stronger inhibition of the movement (0.3 times, p ≤ 0.001) during D1 and increase during L1 (2.7, p ≤ 0.001). Lastly, native sediments from Örnsköldsvik exhibit values that are comparable with the controls and a slightly higher activity during D1 (1.4, p ≤ 0.001) and D2 (2.3, p ≤ 0.001). Results are shown in Fig. 3.

Fig. 3
figure3

Total distance (cm) of 96 hpf Danio rerio embryos during first light phase (L1), first 10 min of the dark phase (D1), second 10 min of the dark phase (D2) and second light phase (L2). Single dots represent the summed total distance of 16 embryos during each light/dark phase. The blue data sets market with * highlights statistical differences between control and treatments (p ≤ 0.001). Centre point show mean and error bars 95% confidence intervals

Inhibition of AChE

At 105 h, there was no statistical significance difference in the AChE activity in Danio rerio embryos exposed to native sediments from GoB and negative controls (Additional file 1: Figure S1).

An overview on the toxicological patterns in sediments from the three sites is given in Table 2.

Table 2 Toxicological pattern observed Danio rerio embryos after 96-h exposure to surface sediments from Gulf of Bothnia (fraction ≤ 63 µm)

Discussion

The major goal of this study was to validate a multi-endpoints in vivo assay to perform a fast identification of toxicological patterns in aquatic sediments. In this context, our results confirmed that different chemical mixtures lead to specific effects patterns in Danio rerio embryos. In particular, we found that the chemical mixture at site Kramfors mainly resulted in developmental malformation, while the ones detected in Sundsvall and Örnsköldsvik acted primarily on the swimming activity (Table 2).

Overall, the selected endpoints offered a comprehensive toxicological characterization of complex environmental mixtures. In particular, developmental malformations and delay in hatching were valid endpoints for the characterization of sediment pollution. In fact, abnormal spinal curvatures (i.e., kyphosis) and hatching problems were observed only in embryos exposed to sediments from Kramfors. However, it is important to underline that several chemicals that were detected in the three sites of GoB (i.e., PAHs, BDEs, heavy metals) were reported to cause spinal curvatures, general developmental toxicity, degeneration of myocytes, neural cell death and delayed hatching [4555]. Thus, it may be hypothesized that the higher concentrations of PAHs in Kramfors (24-fold higher compared to those measured in Sundsvall and Örnsköldsvik) may actually be responsible of the observed effect. In fact, it has been shown that teratogenic effects in early fish life stages are mainly caused by high PAHs concentrations [26, 56].

In this case, effect-directed analysis (EDA) or toxicity identification evaluation (TIE) could help to reduce complexity of the environmental mixture and allow for the identification of specific causative chemicals [57]. Moreover, additional non-destructive morphological endpoints (i.e., craniofacial, eyes malformations, tail and somite malformations) may be included in future studies to increase the screening power and specificity of the present workflow. As an example, innovative vertebrate automated screening technology (VAST) may be used to obtain high-content automatic imaging of Danio rerio embryos phenotypes [58].

Our workflow with Danio rerio embryos confirmed also the possibility to obtain a comprehensive neurotoxicological profile of environmental samples. As recently discussed by Legradi et al. [59] in a recent review, the identification of neuroactive chemicals in the environmental is an important emerging issue. In fact, more than 30,000 commercially used chemicals may have a neurotoxic potential and they could induce changes in the organism behavior leading to severe effects on the ecosystem [59].

In our study, sediments from Kramfors caused an inhibition of the movement during the dark phase, while sediments from Örnsköldsvik and Sundsvall induced an increase of the movement during the dark phases.

The higher swimming activity observed when the embryos were exposed to sediment extracts from Kramfors was probably influenced by spine malformations, occurring as visual impairments in the embryos. In fact, problems with the development of the retinal cells may lead to increased sensitivity to light and impaired behaviors [60]. In this case, the high concentrations of PAHs in Kramfors may also cause developmental defects of the retina, by up-regulating the aryl hydrocarbon receptor (AhR) [61]. Previous findings that environmental concentrations of phenanthrene caused the reduction of cell proliferation in the retina of zebrafish [61] support this hypothesis. It is also possible that the increase of activity during light phase may be related to a specific effect on the nervous system of the embryos. The hypothesis is confirmed by the similar chemical profiles of Örnsköldsvik and Sundsvall (Fig. 1), despite showing a slightly different effect patterns on the swimming behavior during the dark phase. As shown in previous studies, behavioral patterns were suggested to be a sensitive measure of ecotoxicological effects since they respond earlier than other endpoints [62]. Moreover, changes in behavior can be often linked to alteration at higher levels of biological organization [62]. Behavioral patterns were shown to be a robust, sensitive and reliable tool that can be used as early indicator of stress, and thus were used also to understand the effect at population and ecosystem level [29, 30]. Behavioral endpoints were also successfully applied for the identification of toxicity of several compound classes with neurotoxic MoA, including pesticides mixtures, pharmaceuticals and personal care products (PPCPs), metals and classical POPs [63,65,66,66]. However, it may be expected that neurotoxic effects are not restricted to these chemicals, but may be exhibited by many more. Thus, it will be hardly possible to identify individual drivers of neurotoxicity using effects on behavioral endpoints. In fact, many lipophilic neurotoxins accumulating in sediments primarily target membrane sodium channels and cause excitability of the nerves and muscles [67, 68]. Moreover, several anti-inflammatory drugs (steroidal glucocorticoids, nonsteroidal anti-inflammatory drugs, phosphodiesterase inhibitors), and dopaminergic antagonists may increase the waking activity during the light period [69]. However, the alteration of behavior may not only be related to the presence of neuroactive compounds. Since the development of the nervous system is influenced by several upstream molecular events (i.e., cellular replication, migration, differentiation, synaptogenesis), xenobiotics may influence processes that are not directly related to functional impairment, but interference with neurodevelopment [70]. Accordingly, potential effects on cardiac and muscle development could affect behavior as well [70]. The detection of these developmental effects would require appropriate detailed microscopical observations and markers that have not been considered in our screening.

Finally, our results highlight the fact that the heart beat rate may be considered a good marker of general stress, but not a good endpoint for the identification of specific toxicological patterns. It was shown that several PAHs (phenanthrene, naphthalene and benzo(k)fluoranthene) may induce a general bradycardia in zebrafish embryos and defects in the heart structure [71, 72], but also heavy metals for example may exhibit cardiovascular disturbance as heart underdevelopment and, in extreme cases, absence of cardiac muscles [53].

Conclusions

The present study highlights the added value of in vivo toxicological profiling with multi-endpoint FET with a specific focus on sublethal effects and neurotoxicity. This approach may integrate behavioral effects and malformations to discriminate toxic environmental mixtures (here sediment extracts) based on the symptoms they cause. Parallel chemical analysis may provide some insight into possible drivers. However, it is necessary to develop new methods and approaches to better link the observed effect to chemical drivers. The required efforts include testing of a broader range of chemicals and mixtures in multi-endpoints FET together with mechanistic research to better understand the development of the symptoms. An increasing number of mechanistically linked endpoints are needed including specific phenotypic endpoints and modified gene expression to target specific toxicity pathways. EDA and TIE studies may help unravel drivers of toxicity in environmental mixtures.

Abbreviations

AChE:

acetylcholisterase

BFR:

brominated flame retardants

BR:

brominated compounds

CRM:

certified reference material

EDA:

effect-directed analysis

FET:

fish embryo test

GC:

gas chromatography

GoB:

Gulf of Bothnia

Hpf:

hours post-fertilization

HR:

high resolution

ICP:

inductively coupled plasma

LC:

liquid chromatography

MDLs:

method detection limits

MoA:

mode of action

MS:

mass spectrometer

NP:

normal phase

OCPs:

organochlorine insecticides

PAHs:

polycyclic aromatic hydrocarbons

PCBs:

polychlorinated biphenyl

PCDDs:

polychlorinated dibenzo-p-dioxins

PCDFs:

polychlorinated dibenzofurans

PEST:

pesticides and biocides

PLE:

pressurized liquid extraction

POPs:

persistent organic pollutants

PPCPs:

pharmaceuticals and personal care products

TIE:

toxicity identification evaluation

TOC:

total organic carbon

VAST:

vertebrate automated screening technology

WWTPs:

waste water treatment plants

References

  1. 1.

    Schwarzenbach RP, Escher BI, Fenner K, Hofstetter TB, Johnson CA, von Gunten U, Wehrli B (2006) The challenge of micropollutants in aquatic systems. Science 313(5790):1072–1077

  2. 2.

    Brack W, Escher BI, Müller E, Schmitt-Jansen M, Schulze T, Slobodnik J, Hollert H (2018) Towards a holistic and solution-oriented monitoring of chemical status of European water bodies: how to support the EU strategy for a non-toxic environment? Environ Sci Eur 30(1):33

  3. 3.

    Warren SH, Claxton LD, Diliberto J, Hughes TJ, Swank A, Kusnierz DH, Marshall V, DeMarini DM (2015) Survey of the mutagenicity of surface water, sediments, and drinking water from the Penobscot Indian Nation. Chemosphere 120:690–696

  4. 4.

    Floehr T, Scholz-Starke B, Xiao H, Koch J, Wu L, Hou J, Wolf A, Bergmann A, Bluhm K, Yuan X (2015) Yangtze Three Gorges Reservoir, China: a holistic assessment of organic pollution, mutagenic effects of sediments and genotoxic impacts on fish. J Environ Sci 38:63–82

  5. 5.

    Garcia ALH, Matzenbacher CA, Santos MS, Prado L, Picada JN, Premoli SM, Corrêa DS, Niekraszewicz L, Dias JF, Grivicich I (2017) Genotoxicity induced by water and sediment samples from a river under the influence of brewery effluent. Chemosphere 169:239–248

  6. 6.

    Fetter E, Krauss M, Brion F, Kah O, Scholz S, Brack W (2014) Effect-directed analysis for estrogenic compounds in a fluvial sediment sample using transgenic cyp19a1b-GFP zebrafish embryos. Aquat Toxicol 154:221–229

  7. 7.

    Ke X, Wang C, Zhang H, Zhang Y, Gui S (2015) Characterization of estrogenic receptor agonists and evaluation of estrogenic activity in the sediments of Liaohe River protected areas. Mar Pollut Bull 100(1):176–181

  8. 8.

    Maranho L, Baena-Nogueras R, Lara-Martín P, DelValls T, Martín-Díaz M (2014) Bioavailability, oxidative stress, neurotoxicity and genotoxicity of pharmaceuticals bound to marine sediments. The use of the polychaete Hediste diversicolor as bioindicator species. Environ Res 134:353–365

  9. 9.

    Kais B, Stengel D, Batel A, Braunbeck T (2015) Acetylcholinesterase in zebrafish embryos as a tool to identify neurotoxic effects in sediments. Environ Sci Pollut Res 22(21):16329–16339

  10. 10.

    Wernersson A-S, Carere M, Maggi C, Tusil P, Soldan P, James A, Sanchez W, Dulio V, Broeg K, Reifferscheid G, Buchinger S, Maas H, Van Der Grinten E, O’Toole S, Ausili A, Manfra L, Marziali L, Polesello S, Lacchetti I, Mancini L, Lilja K, Linderoth M, Lundeberg T, Fjällborg B, Porsbring T, Larsson DJ, Bengtsson-Palme J, Förlin L, Kienle C, Kunz P, Vermeirssen E, Werner I, Robinson CD, Lyons B, Katsiadaki I, Whalley C, den Haan K, Messiaen M, Clayton H, Lettieri T, Carvalho RN, Gawlik BM, Hollert H, Di Paolo C, Brack W, Kammann U, Kase R (2015) The European technical report on aquatic effect-based monitoring tools under the water framework directive. Environ Sci Eur 27(1):7

  11. 11.

    Vethaak AD, Hamers T, Martínez-Gómez C, Kamstra JH, de Weert J, Leonards PE, Smedes F (2017) Toxicity profiling of marine surface sediments: a case study using rapid screening bioassays of exhaustive total extracts, elutriates and passive sampler extracts. Mar Environ Res 124:81–91

  12. 12.

    Nam S-H, Shin Y-J, Lee W-M, Kim SW, Kwak JI, Yoon S-J, An Y-J (2015) Conducting a battery of bioassays for gold nanoparticles to derive guideline value for the protection of aquatic ecosystems. Nanotoxicology 9(3):326–335

  13. 13.

    de Paiva Magalhães D, da Costa Marques MR, Baptista DF, Buss DF (2014) Selecting a sensitive battery of bioassays to detect toxic effects of metals in effluents. Ecotoxicol Environ Saf 110:73–81

  14. 14.

    Khan MI, Cheema SA, Tang X, Hashmi MZ, Shen C, Park J, Chen Y (2013) A battery of bioassays for the evaluation of phenanthrene biotoxicity in soil. Arch Environ Contam Toxicol 65(1):47–55

  15. 15.

    Neale PA, Altenburger R, Aït-Aïssa S, Brion F, Busch W, de Aragão Umbuzeiro G, Denison MS, Du Pasquier D, Hilscherová K, Hollert H, Morales DA, Novák J, Schlichting R, Seiler T-B, Serra H, Shao Y, Tindall AJ, Tollefsen KE, Williams TD, Escher BI (2017) Development of a bioanalytical test battery for water quality monitoring: fingerprinting identified micropollutants and their contribution to effects in surface water. Water Res 123:734–750

  16. 16.

    Di Paolo C, Ottermanns R, Keiter S, Ait-Aissa S, Bluhm K, Brack W, Breitholtz M, Buchinger S, Carere M, Chalon C, Cousin X, Dulio V, Escher BI, Hamers T, Hilscherová K, Jarque S, Jonas A, Maillot-Marechal E, Marneffe Y, Nguyen MT, Pandard P, Schifferli A, Schulze T, Seidensticker S, Seiler T-B, Tang J, van der Oost R, Vermeirssen E, Zounková R, Zwart N, Hollert H (2016) Bioassay battery interlaboratory investigation of emerging contaminants in spiked water extracts—towards the implementation of bioanalytical monitoring tools in water quality assessment and monitoring. Water Res 104:473–484

  17. 17.

    Välitalo P, Massei R, Heiskanena I, Behnische P, Brack W, Tindallf AJ, Pasquiere DD, Küster E, Mikola A, Schulze T, Sillanpää M (2017) Effect-based assessment of toxicity removal during wastewater treatment. Water Res 126:153–163

  18. 18.

    Tice RR, Austin CP, Kavlock RJ, Bucher JR (2013) Improving the human hazard characterization of chemicals: a Tox21 update. Environ Health Perspect 121(7):756

  19. 19.

    Hayers AW, Thomas JA, Gardner DE (1999) Neurotoxicology—Second Edition. Taylor & Francis, New York

  20. 20.

    Busch W, Schmidt S, Kühne R, Schulze T, Krauss M, Altenburger R (2016) Micropollutants in European rivers: a mode of action survey to support the development of effect-based tools for water monitoring. Environ Toxicol Chem 35(8):1887–1899

  21. 21.

    Lammer E, Carr GJ, Wendler K, Rawlings JM, Belanger SE, Braunbeck T (2009) Is the fish embryo toxicity test (FET) with the zebrafish (Danio rerio) a potential alternative for the fish acute toxicity test? Comp Biochem Physiol C Toxicol Pharmacol 149(2):196–209

  22. 22.

    Hollert H, Keiter S, König N, Rudolf M, Ulrich M, Braunbeck T (2003) A new sediment contact assay to assess particle-bound pollutants using zebrafish (Danio rerio) embryos. J Soils Sediments 3(3):197

  23. 23.

    Kammann U, Biselli S, Huhnerfuss H, Reineke N, Theobald N, Vobach M, Wosniok W (2004) Genotoxic and teratogenic potential of marine sediment extracts investigated with comet assay and zebrafish test. Environ Pollut 132(2):279–287

  24. 24.

    Keiter S, Peddinghaus S, Feiler U, Goltz B, Hafner C, Ho NY, Rastegar S, Otte JC, Ottermanns R, Reifferscheid G, Strähle U, Braunbeck T, Hammers-Wirtz M, Hollert H (2010) DanTox—a novel joint research project using zebrafish (Danio rerio) to identify specific toxicity and molecular modes of action of sediment-bound pollutants. J Soils Sediments 10(4):714–717

  25. 25.

    Fraysse B, Mons R, Garric J (2006) Development of a zebrafish 4-day embryo-larval bioassay to assess toxicity of chemicals. Ecotoxicol Environ Saf 63(2):253–267

  26. 26.

    Schiwy S, Bräunig J, Alert H, Hollert H, Keiter SH (2015) A novel contact assay for testing aryl hydrocarbon receptor (AhR)-mediated toxicity of chemicals and whole sediments in zebrafish (Danio rerio) embryos. Environ Sci Pollut Res 22(21):16305–16318

  27. 27.

    Di Paolo C, Seiler TB, Keiter S, Hu M, Muz M, Brack W, Hollert H (2015) The value of zebrafish as an integrative model in effect-directed analysis—a review. Environ Sci Eur 27(1):8

  28. 28.

    Gonzalez ST, Remick D, Creton R, Colwill RM (2016) Effects of embryonic exposure to polychlorinated biphenyls (PCBs) on anxiety-related behaviors in larval zebrafish. NeuroToxicology 53:93–101

  29. 29.

    Hellou J (2011) Behavioural ecotoxicology, an “early warning” signal to assess environmental quality. Environ Sci Pollut Res 18(1):1–11

  30. 30.

    Reinert KH, Giddings JM, Judd L (2002) Effects analysis of time-varying or repeated exposures in aquatic ecological risk assessment of agrochemicals. Environ Toxicol Chem 21(9):1977–1992

  31. 31.

    Massei R, Byers H, Beckers LM, Prothmann J, Brack W, Schulze T, Krauss M (2018) A sediment extraction and cleanup method for wide-scope multitarget screening by liquid chromatography–high-resolution mass spectrometry. Anal Bioanal Chem 410(1):177–188

  32. 32.

    Rauret G, Lopez-Sanchez J, Sahuquillo A, Rubio R, Davidson C, Ure A, Quevauviller P (1999) Improvement of the BCR three step sequential extraction procedure prior to the certification of new sediment and soil reference materials. J Environ Monit 1(1):57–61

  33. 33.

    Marguı E, Salvadó V, Queralt I, Hidalgo M (2004) Comparison of three-stage sequential extraction and toxicity characteristic leaching tests to evaluate metal mobility in mining wastes. Anal Chim Acta 524(1–2):151–159

  34. 34.

    Tokalıoğlu Ṣ, Kartal Ṣ (2006) Statistical evaluation of the bioavailability of heavy metals from contaminated soils to vegetables. Bull Environ Contam Toxicol 76(2):311–319

  35. 35.

    17294-2:2017-01, I., Water quality—application of inductively coupled plasma mass spectrometry (ICP-MS)—Part 2: determination of selected elements including uranium isotopes (ISO 17294-2:2016). 2017

  36. 36.

    Bittner L, Teixido E, Seiwert B, Escher BI, Klüver N (2018) Influence of pH on the uptake and toxicity of β-blockers in embryos of zebrafish, Danio rerio. Aquatic Toxicology 201:129–137

  37. 37.

    Hollert H, Keiter SH (2015) Danio rerio as a model in aquatic toxicology and sediment research. Environ Sci Pollut Res 22(21):16243–16246

  38. 38.

    Selderslaghs IW, Hooyberghs J, De Coen W, Witters HE (2010) Locomotor activity in zebrafish embryos: a new method to assess developmental neurotoxicity. Neurotoxicol Teratol 32(4):460–471

  39. 39.

    Küster E (2005) Cholin-and carboxylesterase activities in developing zebrafish embryos (Danio rerio) and their potential use for insecticide hazard assessment. Aquat Toxicol 75(1):76–85

  40. 40.

    Andrade TS, Henriques JF, Almeida AR, Soares AMVM, Scholz S, Domingues I (2017) Zebrafish embryo tolerance to environmental stress factors—concentration–dose response analysis of oxygen limitation, pH, and UV-light irradiation. Environ Toxicol Chem 36(3):682–690

  41. 41.

    Palma P, Ledo L, Soares S, Barbosa I, Alvarenga P (2014) Spatial and temporal variability of the water and sediments quality in the Alqueva reservoir (Guadiana Basin; southern Portugal). Sci Total Environ 470:780–790

  42. 42.

    Epa S (2000) Environmental quality criteria: coasts and seas. Swedish Environ Protect Agency Rep 5052:138

  43. 43.

    Prange A, Bössow E, Erbslöh B, Jablonski R, Jantzen E, Krause P, Krüger F, Leonhard P, Niedergesäß R, Pepelnik R (1997) Geogene Hintergrundwerte und zeitliche Belastungsentwicklung. Abschlussbericht, GKSS-Forschungszentrum Geesthacht GmbH 3:3

  44. 44.

    Turekian KK, Wedepohl KH (1961) Distribution of the elements in some major units of the earth’s crust. Geol Soc Am Bull 72(2):175–192

  45. 45.

    Fathollahzadeh H, Kaczala F, Bhatnagar A, Hogland W (2014) Speciation of metals in contaminated sediments from Oskarshamn Harbor, Oskarshamn, Sweden. Environ Sci Pollut Res 21(4):2455–2464

  46. 46.

    Liu Z, Wang Y, Zhu Z, Yang E, Feng X, Fu Z, Jin Y (2016) Atrazine and its main metabolites alter the locomotor activity of larval zebrafish (Danio rerio). Chemosphere 148:163–170

  47. 47.

    MacPhail R, Brooks J, Hunter D, Padnos B, Irons T, Padilla S (2009) Locomotion in larval zebrafish: influence of time of day, lighting and ethanol. Neurotoxicology 30(1):52–58

  48. 48.

    Zhao J (2014) Locomotor activity changes on zebrafish larvae with different 2,20,4,40-tetrabromodiphenyl ether (PBDE-47) embryonic exposure modes. Chemosphere 94:53–61

  49. 49.

    Wincent E, Jönsson ME, Bottai M, Lundstedt S, Dreij K (2015) Aryl hydrocarbon receptor activation and developmental toxicity in zebrafish in response to soil extracts containing unsubstituted and oxygenated PAHs. Environ Sci Technol 49(6):3869–3877

  50. 50.

    Barron MG, Carls MG, Heintz R, Rice SD (2004) Evaluation of fish early life-stage toxicity models of chronic embryonic exposures to complex polycyclic aromatic hydrocarbon mixtures. Toxicol Sci 78(1):60–67

  51. 51.

    Kim D-J, Seok S-H, Baek M-W, Lee H-Y, Na Y-R, Park S-H, Lee H-K, Dutta NK, Kawakami K, Park J-H (2009) Developmental toxicity and brain aromatase induction by high genistein concentrations in zebrafish embryos. Toxicol Mech Methods 19(3):251–256

  52. 52.

    Sfakianakis DG, Renieri E, Kentouri M, Tsatsakis AM (2015) Effect of heavy metals on fish larvae deformities: a review. Environ Res 137:246–255

  53. 53.

    Jezierska B, Ługowska K, Witeska M (2009) The effects of heavy metals on embryonic development of fish (a review). Fish Physiol Biochem 35(4):625–640

  54. 54.

    Magnusson-Olsson AL, Lager S, Jacobsson B, Jansson T, Powell TL (2007) Effect of maternal triglycerides and free fatty acids on placental LPL in cultured primary trophoblast cells and in a case of maternal LPL deficiency. Am J Physiol Endocrinol Metab 293(1):E24–E30

  55. 55.

    Westerlund L, Billsson K, Andersson PL, Tysklind M, Olsson PE (2000) Early life-stage mortality in zebrafish (Danio rerio) following maternal exposure to polychlorinated biphenyls and estrogen. Environ Toxicol Chem 19(6):1582–1588

  56. 56.

    Barron MG, Heintz R, Rice SD (2004) Relative potency of PAHs and heterocycles as aryl hydrocarbon receptor agonists in fish. Mar Environ Res 58(2–5):95–100

  57. 57.

    Burgess RM, Ho KT, Brack W, Lamoree M (2013) Effects-directed analysis (EDA) and toxicity identification evaluation (TIE): complementary but different approaches for diagnosing causes of environmental toxicity. Environ Toxicol Chem 32(9):1935–1945

  58. 58.

    Mathias JR, Saxena MT, Mumm JS (2012) Advances in zebrafish chemical screening technologies. Future Med Chem 4(14):1811–1822

  59. 59.

    Legradi JB, Di Paolo C, Kraak MHS, van der Geest HG, Schymanski EL, Williams AJ, Dingemans MML, Massei R, Brack W, Cousin X, Begout ML, van der Oost R, Carion A, Suarez-Ulloa V, Silvestre F, Escher BI, Engwall M, Nilén G, Keiter SH, Pollet D, Waldmann P, Kienle C, Werner I, Haigis AC, Knapen D, Vergauwen L, Spehr M, Schulz W, Busch W, Leuthold D, Scholz S, vom Berg CM, Basu N, Murphy CA, Lampert A, Kuckelkorn J, Grummt T, Hollert H (2018) An ecotoxicological view on neurotoxicity assessment. Environ Sci Eur 30(1):46

  60. 60.

    Anichtchik OV, Kaslin J, Peitsaro N, Scheinin M, Panula P (2004) Neurochemical and behavioural changes in zebrafish Danio rerio after systemic administration of 6-hydroxydopamine and 1-methyl-4-phenyl-1, 2, 3, 6-tetrahydropyridine. J Neurochem 88(2):443–453

  61. 61.

    Huang L, Wang C, Zhang Y, Wu M, Zuo Z (2013) Phenanthrene causes ocular developmental toxicity in zebrafish embryos and the possible mechanisms involved. J Hazard Mater 261:172–180

  62. 62.

    Rodrigues AC, Henriques JF, Domingues I, Golovko O, Žlábek V, Barata C, Soares AM, Pestana JL (2016) Behavioural responses of freshwater planarians after short-term exposure to the insecticide chlorantraniliprole. Aquat Toxicol 170:371–376

  63. 63.

    Pyle G, Ford A (2017) Behaviour revised: contaminant effects on aquatic animal behaviour. Aquat Toxicol 182:226–228

  64. 64.

    Oliveira R, Grisolia CK, Monteiro MS, Soares AM, Domingues I (2016) Multilevel assessment of ivermectin effects using different zebrafish life stages. Comp Biochem Physiol C Toxicol Pharmacol 187:50–61

  65. 65.

    Hasenbein S, Lawler SP, Geist J, Connon RE (2015) The use of growth and behavioral endpoints to assess the effects of pesticide mixtures upon aquatic organisms. Ecotoxicology 24(4):746–759

  66. 66.

    Monteiro LC, Van Butsel J, De Meester N, Traunspurger W, Derycke S, Moens T (2018) Differential heavy-metal sensitivity in two cryptic species of the marine nematode Litoditis marina as revealed by developmental and behavioural assays. J Exp Mar Biol Ecol 502:203–210

  67. 67.

    Wang S-Y, Wang GK (2003) Voltage-gated sodium channels as primary targets of diverse lipid-soluble neurotoxins. Cell Signal 15(2):151–159

  68. 68.

    Silver KS, Song W, Nomura Y, Salgado VL, Dong K (2010) Mechanism of action of sodium channel blocker insecticides (SCBIs) on insect sodium channels. Pestic Biochem Physiol 97(2):87–92

  69. 69.

    Irons TD, Kelly PE, Hunter DL, Macphail RC, Padilla S (2013) Acute administration of dopaminergic drugs has differential effects on locomotion in larval zebrafish. Pharmacol Biochem Behav 103(4):792–813

  70. 70.

    Dishaw LV, Hunter DL, Padnos B, Padilla S, Stapleton HM (2014) Developmental exposure to organophosphate flame retardants elicits overt toxicity and alters behavior in early life stage zebrafish (Danio rerio). Toxicol Sci 142(2):445–454

  71. 71.

    Incardona JP, Collier TK, Scholz NL (2004) Defects in cardiac function precede morphological abnormalities in fish embryos exposed to polycyclic aromatic hydrocarbons. Toxicol Appl Pharmacol 196(2):191–205

  72. 72.

    Incardona JP, Linbo TL, Scholz NL (2011) Cardiac toxicity of 5-ring polycyclic aromatic hydrocarbons is differentially dependent on the aryl hydrocarbon receptor 2 isoform during zebrafish development. Toxicol Appl Pharmacol 257(2):242–249

  73. 73.

    Carlsson G, Patring J, Kreuger J, Norrgren L, Oskarsson A (2013) Toxicity of 15 veterinary pharmaceuticals in zebrafish (Danio rerio) embryos. Aquat Toxicol 126:30–41

  74. 74.

    Jin M, Zhang X, Wang L, Huang C, Zhang Y, Zhao M (2009) Developmental toxicity of bifenthrin in embryo-larval stages of zebrafish. Aquat Toxicol 95(4):347–354

  75. 75.

    De Gaspar I, Blanquez MJ, Fraile B, Paniagua R, Arenas MI (1999) The hatching gland cells of trout embryos: characterisation of N-and O-linked oligosaccharides. J Anat 194(1):109–118

  76. 76.

    Irons TD, MacPhail RC, Hunter DL, Padilla S (2010) Acute neuroactive drug exposures alter locomotor activity in larval zebrafish. Neurotoxicol Teratol 32(1):84–90

  77. 77.

    Selderslaghs IW, Hooyberghs J, Blust R, Witters HE (2013) Assessment of the developmental neurotoxicity of compounds by measuring locomotor activity in zebrafish embryos and larvae. Neurotoxicol Teratol 37:44–56

  78. 78.

    Strmac M, Oberemm A, Braunbeck T (2002) Effects of sediment eluates and extracts from differently polluted small rivers on zebrafish embryos and larvae. J Fish Biol 61(1):24–38

  79. 79.

    Scholz S, Fischer S, Gundel U, Kuster E, Luckenbach T, Voelker D (2008) The zebrafish embryo model in environmental risk assessment–applications beyond acute toxicity testing. Environ Sci Pollut Res Int 15(5):394–404

Download references

Authors’ contributions

RM performed all experiments and been has involved in the whole process of analysis and interpretation of the data. HH has been involved in critically revising the FET section. MK contributed to the analysis and interpretation of the LC-HRMS data. WV contributed to the analysis and interpretation of the trace elements data. CW has been involved in the acquisition and analysis of GC-HRMS data. PH, CG and MT have been critically involved in revising the whole chemical analyses and sampling sections. They also gave an important contribution to the characterization of the sampling area. EK critically contributed to the understanding of the FET data in revising the FET section. WB made substantial contributions to the whole conception, design and interpretation of data. All authors read and approved the final manuscript.

Acknowledgements

We thank Umeå Marine Science Center, Umeå University, for performing the sampling campaigns organized. We thank also Nicole Schweiger and Margit Petre for the lab technical support. Chemaxon (Budapest, Hungary) is gratefully acknowledged for a free academic license of Marvin and JChem for Excel.

Competing interests

The authors declare that they have no competing interests.

Availability of data and materials

All data generated or analyzed during this study are included in this published article and its additional information files.

Consent for publication

Not applicable.

Ethics approval and consent to participate

Not applicable.

Funding

We acknowledge funding by the SOLUTIONS Project supported by the European Union Seventh Framework Programme (FP7-ENV-2013-two-stage Collaborative project) under grant no. 603437, the BmBF financed the NeuroBox project under the grant 02WRS1419E and 02WRS1419C) and the REACT research project funded by FORMAS (contract 2012-2090).

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Author information

Correspondence to Riccardo Massei.

Additional files

12302_2019_188_MOESM1_ESM.docx

Additional file 1: S1. Sediments extraction and clean-up. S2. GC-HRMS and LC-HRMS methods. S3. Trace Finder parameters. S4. Method detection limits. S5. Trace elements analyses. Table S1. Sediments characteristics and sampling spot information. Table S2. GC oven program. Table S3. Injection details for pulsed split less injection for GC-analysis. Table S4. Parameters of the GC-QExactive HRMS method. Table S5. LC gradient program. Table S6. Settings of the Trace Finder software. Table S9. Chemicals and Equipment. Figure S1. Sampling spot map. Figure S2. Acetylcholisterase inhibition in Danio rerio embryos exposed to sediments of Gulf of Bothnia. Figure S3. Zebrafish embryos after 96 hpf exposed to sediments of Kramfors and Örnsköldsvik.

12302_2019_188_MOESM2_ESM.xlsx

Additional file 2: Table S7 . Method detection limits (MDLs) for the detected compounds in sediment samples. Table S8. Target compounds list, their log D values at pH 7 and the internal standard used for quantification. Table S10. Concentrations of detected compounds in sediments of Gulf of Bothnia.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Keywords

  • Danio rerio embryos
  • Sediments
  • Monitoring
  • Neurotoxicity
  • Behavior
  • Mixtures