Enhanced applications of the zebrafish (Danio rerio) embryo toxicity test as a model to mechanistically differentiate metal toxicity effects in fish.
Von der Fakultät für Mathematik, Informatik und Naturwissenschaften der RWTH Aachen University zur Erlangung des akademischen Grades einer Doktorin der Naturwissenschaften genehmigte Dissertation
vorgelegt von
Laura Sonnack, M. Eng.
aus Frankfurt am Main
Berichter: Univ.-Prof. Dr. rer. nat. Henner Hollert
Univ.-Prof. Dr. rer. nat. Andreas Schäffer
Tag der mündlichen Prüfung: 19. Februar 2018
Diese Dissertation ist auf den Internetseiten der Universitätsbibliothek online verfügbar.
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Contents
Contents
Summary ...... i Zusammenfassung ...... iv List of figures ...... viii List of tables ...... x
Chapter 1: General Introduction ...... 1 1.1. Metals in the environment ...... 2 1.1.1. Cadmium ...... 6 1.1.2. Cobalt ...... 6 1.1.3. Copper ...... 7 1.2. The test organism zebrafish and the embryo toxicity test as a test system ...... 8 1.2.1. Assessment of neurotoxic effects using defects of motor neuron development . 10 1.2.2. Assessment of neuromast damage as asensitive indicator of peripheral neurotoxicity ...... 12 1.2.3. Gene expression analyses...... 13 1.3. Objectives ...... 15
Chapter 2: Material & Methods ...... 17 2.1. Zebrafish husbandry ...... 18 2.2. Metals, chemicals and reagents ...... 18 2.3. Zebrafish embryo toxicity tests ...... 19 2.3.1. Assessment of exposure concentration dependent morphological effects ...... 19 2.3.2. Assessment of motor neuron impairment using immunofluorescence staining . 20 2.3.3. Assessment of neuromast damage using a vital dye staining ...... 22 2.3.4. Assessment of escape response ...... 23 2.3.5. Statistical analysis of the morphological and functional endpoints ...... 24 2.4. Gene transcription analysis ...... 24 2.4.1. RNA Extraction...... 24 2.4.2. Microarray experiments ...... 25 2.4.3. Functional analysis ...... 26 2.4.4. Real-time quantitative PCR ...... 27
Chapter 3 ...... 29 Effects of metal exposure on motor neuron development, neuromasts and the escape response of zebrafish embryos ...... 29
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Contents
3.1. Abstract ...... 30 3.2. Introduction ...... 31 3.3. Material and Methods ...... 33 3.3.1. Chemicals ...... 33 3.3.2. Analysis of metals ...... 34 3.3.3. Exposure of zebrafish embryos ...... 35 3.4. Results ...... 36 3.4.1. Morphological effects in zebrafish embryos ...... 36 3.4.2. Effects on motor neuron development ...... 39 3.4.3. Neuromast damage ...... 41 3.4.4. Behavioral effects ...... 42 3.5. Discussion ...... 43
Chapter 4 ...... 51 Comparative analysis of the transcriptome responses of zebrafish embryos after exposure to low concentrations of cadmium, cobalt and copper ...... 51 4.1. Abstract ...... 52 4.2. Introduction ...... 53 4.3. Materials and Methods ...... 54 4.3.1. Chemicals ...... 54 4.3.2. Analysis of metals ...... 55 4.4. Results ...... 56 4.4.1. Morphological effects ...... 56 4.4.2. Microarray analysis ...... 57 4.4.3. Real-time quantitative PCR ...... 62 4.5. Discussion ...... 64
Chapter 5 ...... 71 Concentration dependent transcriptome responses of zebrafish embryos after exposure to cadmium, cobalt and copper...... 71 5.1. Abstract ...... 72 5.2. Introduction ...... 73 5.3. Materials and Methods ...... 74 5.3.1. Analysis of metals ...... 74 5.4. Results ...... 75 5.4.1. Microarray-Analysis ...... 75 5.4.2. Real-time quantitative PCR ...... 83
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Contents
5.5. Discussion ...... 84
Chapter 6: General discussion & conclusion ...... 93 6.1. Addressing limitations of the zebrafish embryo toxicity test ...... 94 6.2. Special considerations regarding metals and toxicity ...... 98 6.3. General remark, conclusions and recommendations...... 101
Literature ...... 103 Erklärung ...... 119 Danksagung ...... 120 Curriculum Vitae ...... 121 Publication List ...... 123
Supplements ...... 125 A. List of chemicals, consumables and equipment ...... 125 A.1. Chemicals, reagents and antibodies used in this thesis ...... 125 A.2. Consumables used in this thesis ...... 126 A.3. Equipment used in this thesis ...... 127 B. Heat maps representing GO enrichment analysis ...... 128 C. List of significantly KEGG-Pathway of Gene Set Enrichment Analysis ...... 131 D. List of significant differentially expressed genes ...... 135 Cadmium (3.3 mg Cd/L) treated 48 hpf embryos ...... 135 Cadmium (3.3 mg Cd/L) treated 96 hpf embryos ...... 137 Cobalt (3.6 mg Co/L) treated 48 hpf embryos ...... 145 Cobalt (3.6 mg Co/L) treated 96 hpf embryos ...... 146 Copper (6.1 µg Cu/L) treated 48 hpf embryos ...... 147 Copper (6.1 µg Cu/L) treated 96 hpf embryos ...... 150
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Summary
Summary
The preservation of the environment and the containment of environmental pollution is one of the greatest challenges faced by our society. Metals as environmental pollutants, are a serious global problem. They are released in various forms during their extraction (mining), processing (chemical and metal industry) and, finally, due to improper disposal of metal-containing goods. Million tons of electronic waste materials containing metals such as cadmium, copper, chromium, silver, nickel and cobalt end up in the environment every year. Once metals have entered the environment, they persist because they are neither chemically nor biologically degradable.
Surface waters and their sediments are major sinks of metal pollution. They are directly contaminated by the discharge of industrial effluents, leaching and surface runoffs from storage or landfill sites or agricultural fields (sprayed with metal-containing pesticides). Therefore, aquatic organisms as fish are particularly affected by metal exposure. This exposure can lead to severe impairment of fish development, although the mechanistic action of which is not well understood. This PhD-thesis investigates the effects of the environmentally relevant metals cadmium, cobalt and copper on the embryonic development of the zebrafish (Danio rerio) at different biological levels. The zebrafish is an established model organism representative of vertebrates, and specifically aquatic vertebrates. Zebrafish early larval stages are increasingly endorsed as alternatives to animal testing using fish due to their many advantages. The uptake of heavy metals and metal ions in fish mainly takes place via the gills and the intestines and leads primarily to an imbalance of ion homeostasis, especially of Na+ and Ca2+. However, since the uptake of food and gills are absent in fish embryos, heavy metal uptake and effects in the early life stages are still largely unknown. In order to address some of the gaps in this knowledge, effects of metal exposure were studied morphologically (by fish embryo toxicity tests and microscopic imaging) molecularly (by transcriptome analysis) and functionally (by behavioural observations) on zebrafish embryos and eleutheroembryos. Specifically, the morphological development, the death of the hair cells of the lateral line organ’s neuromasts, the impairment of motor neuron development and the touch-evoked escape response were studied in wild-type zebrafish embryos, following exposure to different concentrations of either cadmium (CdCl2), cobalt (CoSO4) or copper (CuSO4). With this approach, it was intended to link cellular, morphological and functional aspects of adverse effects of a non-essential metal (cadmium) in comparison to essential metals (cobalt and copper). Motor neuron damage was ______i
Summary investigated by immunofluorescence staining of primary motor neurons (PMNs) and secondary motor neurons (SMNs). In vivo staining using the vital dye DASPEI were used to quantify neuromast damage. The consequences of metal exposure were also assessed functionally by testing the escape response behaviour following tactile stimulation. The median effective concentration (EC50) values for morphological effects at 72 hours post fertilization (hpf) were 14.6 mg/L for cadmium and 0.018 mg/L for copper, whereas no morphological effects were found in the cobalt exposed embryos up to 45.8 mg/L. All three metals caused a concentration- dependent reduction in the number of normal PMNs and SMNs, and in the fluorescence intensity of neuromasts (i.e. increase in hair cell death). Even the lowest metal concentrations (cadmium 2 mg/L, copper 0.01 mg/L and cobalt 0.8 mg/L) resulted in neuromast damage. The results demonstrate that the neuromast cells were more sensitive to metal exposure than morphological traits, or the response to tactile stimulation and motor neuron damage.
The molecular basis of metal toxicity in zebrafish embryo was also investigated on a broader scale by applying genome-wide transcriptomics analysis. This was aimed to improve the mechanistic understanding of adverse effects caused by different metals. This study was designed to compare exposure effects of three different exposure concentrations of the three metals at two different developmental stage (pre-hatch and post-hatch). Thus, embryos were exposed to low, sub-toxic concentrations of copper, cadmium and cobalt until 48 and 96 hpf and subsequently subjected to microarray analysis to determine the changes in the transcriptome profiles.
With regard to the effects seen at transcriptome level, the embryos reacted differently to the non-essential metal cadmium compared to the essential metals cobalt and copper. For example, gene specific transcription as well as GO terms hinted at detoxification processes in cadmium treated embryos only. Possible indicators of a detoxification response like glutathione-s- transferases and metallothionein2, were identified and heme oxygenase, another possible indicator of oxidative stress and detoxification, was significantly regulated after cadmium exposure. In contrast, no detoxification related gene transcripts or ontology terms were found regulated for essential metals cobalt and copper. Also in terms of the overall transcriptome response pattern and strength and pathway modulation. This thesis clearly showed a different reaction of the embryos to the essential compared to the non-essential metals.
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Summary
Furthermore, the results of this thesis point out the neuro- and ototoxic potential of cadmium, cobalt and copper. The additional study of the embryos’ escape response after tactile stimulation allowed a correlation with the effects on the motor neurons for all three metals. The findings suggested that the motor neuron damage may have caused to interrupt the innervation of the embryos’ tail muscles, which subsequently inhibited the essential muscle contraction required for the escape response. The transcriptome analysis at low concentration levels enabled us to relate GO terms of the nervours system development to the defect on the motor neurons for all three metals. Therefore, the transcriptional changes related to the nervous system development and the motor neuron damage, which resulted in the altered escape response, seemed to be connected by similar processes for all three metals. However, the no-hatch effect, which may have partly been caused by impaired tail muscle innervation due to an inhibited signal transduction in the nervous system (e.g. between the sensory neurons and motor neurons), was observed only in embryos exposed to copper. Based on the transcriptome level results, this assumption of signal transduction inhibition in the nervous system was strengthened since copper regulated Wnt and Notch signal transduction pathways. Further, additional GO terms of neuron development and differentiation associated with the deformation of the neurons for copper but not for cadmium and cobalt. Both molecular mechanisms seem to be related to both, the effect on the escape response and the no-hatch effect. Interestingly, Wnt signaling pathways were found regulated also in cobalt treated embryos, where a no-hatch effect was observed at higher carbonate hardness. In contrast, cadmium did not affect the hatching of the embryos, and also the Wnt signaling pathways were unaltered. However, the significant upregulation of cldnb mRNA may suggest an ototoxic potential of cadmium, which the embryos try to compensate by degeneration. The tight junction protein Claudin b is highly expressed in the neuromast.
Overall, this thesis demonstrates that a combination of fluorescence staining endpoints, gene expression analysis, behaviour assessment and zebrafish embryo toxicity tests can help to specify, quantify and elucidate mechanisms and connections defining the exposure effects of metals like copper, cadmium and cobalt. Moreover, it was shown that additional endpoint assessment procedures are available, which display higher sensitivity to detected metal toxicity in zebrafish embryos than current test procedures applied in the ecological risk assessment.
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Zusammenfassung
Zusammenfassung
Der Erhaltung der Umwelt und die Eingrenzung von Umweltverschmutzung ist eine der größten Herausforderungen unserer Gesellschaft. Metalle als Umweltschadstoffe sind ein ernstzunehmendes und globales Problem. Sie werden in verschiedenster Form bei ihrer Gewinnung (Abbau) und Verarbeitung (chemische und metallverarbeitende Industrie) und letztendlich bei der unsachgemäßen Entsorgung metallhaltiger Güter freigesetzt. Millionen Tonnen von Elektroschrott, der sämtliche Metalle wie Cadmium, Kupfer, Chrom, Silber, Nickel oder Kobalt enthält, landen jedes Jahr in der Umwelt. Einmal in die Umwelt eingetragene Metalle verbleiben dort, denn sie sind weder chemisch noch biologisch abbaubar.
Oberflächengewässer und ihre Sedimente sind bedeutende Schadstoffsenken für Metalle. Sie werden durch die Einleitung von Industrieabwässern, durch Gesteinsauswaschungen und Oberflächenabflüssen von Lager-, Mülldeponien oder durch die Landwirtschaft (metallhaltige Pestiziden) mit Metallen direkt belastet. Daher sind insbesondere Wasserorganismen, wie Fische, von Metallbelastungen betroffen. Die Exposition kann zu einer starken Beeinträchtigung der Fischentwicklung führen, wobei die mechanistischen Prozesse nicht völlig klar sind. Mit dieser Doktorarbeit werden nun die Wirkungen von den umweltrelevanten Metallen Cadmium, Kobalt und Kupfer auf die Embryonalentwicklung des Zebrabärblings (oder Zebrafisch, Danio rerio) auf verschiedenen biologischen Ebenen untersucht. Der Zebrafisch ist als ein repräsentativer Modellorganismus für Wirbeltiere etabliert, auch insbesondere für aquatische Wirbeltiere. Frühe Larvenstadien des Zebrafisches werden aufgrund ihrer vielen Vorteile zunehmend als Alternative zum Tierversuch gefördert. Die Aufnahme von Schwermetallen und Metallionen erfolgt bei Fischen allerdings hauptsächlich über die Kiemen und den Darm, wodurch es zu Störung des Ionen-Homöostase, besonders von Na+ und Ca2+ kommt. Bei den Fischembryonen fehlt diese Aufnahme über Futter und Kiemen, und die die Aufnahmewege und Wirkungen von Schwermetallen bei frühen Lebensstadien sind noch weitgehend unbekannt. Die Untersuchung von Effekten durch Metallbelastung bei Zebrafischembryonen auf morphologischer (durch Fisch-Embryotoxizitätstests und mikroskopische Bildgebung), molekularer (durch Transkriptomanalyse) und funktionaler (durch Verhaltensbeobachtungen) Ebene soll nun einige dieser Wissenslücken füllen. Untersucht wurden im Einzelnen die Entwicklung auf morphologischer Ebene, das Absterben der Haarzellen der Neuromasten des Seitenlinienorgans, die Schädigung der Motoneuronenentwicklung und die berührungsausgelöste Fluchtreaktion von Wildtyp- ______iv
Zusammenfassung
Zebrafischembryonen, nachdem sie an verschiedenen Konzentrationen von Cadmium (CdCl2),
Cobalt (CoSO4) oder Kupfer (CuSO4) exponiert waren. Die Absicht dieses Ansatzes war es, zelluläre, morphologische und funktionale Aspekte der adversen Effekte durch das nicht- essentielle Metall Cadmium im Vergleich zu den essentiellen Metallen Kobalt und Kupfer, zu verknüpfen. Die Schädigung der Motoneuronen wurde mittels Immunfluoreszenzfärbung der primären und sekundären Motoneuronen untersucht. Für die Quantifizierung der Neuromastschädigung wurde eine in vivo-Färbung mit dem Vitalfarbstoff DASPEI verwendet. Des Weiteren wurden die Ursachen der Metall-Exposition funktional anhand des
Fluchtverhaltens nach taktiler Stimulation bewertet. Die mediane Effektkonzentration (EC50) für morphologischen Effekte nach 72 Stunden nach der Befruchtung (hpf) wurde mit 14.6 mg/L für Cadmium und 0.018 mg/L für Kupfer bestimmt, wohingegen Embryonen, die bis zu einer Kobalt Konzentration von 45.8 mg/L exponiert wurden, keine morphologischen Effekte zeigten. Alle drei Metalle verursachten eine konzentrationsabhängige Abnahme der normal entwickelten primären und sekundären Motoneuronen sowie eine Abnahme der Fluoreszenzintensität in den Neuromasten (d.h. Zunahme der toten Haarzellen). Sogar bei den niedrigsten Metallkonzentrationen (Cadmium 2 mg/L, Kupfer 0.01 mg/L und Kobalt 0.8 mg/L) konnte eine Schädigung der Neuromasten detektiert werden. Die Ergebnisse zeigen, dass die Neuromastzellen sensitiverer auf die Metallbelastung reagierten als die morphologischen Eigenschaften, die Fluchtreaktion nach taktiler Stimulation oder die Schädigung an den Motoneuronen.
Die molekularen Grundlagen der Metall-Toxizität in Wildtyp-Zebrafischembryonen wurde in weiterem Umfang mittels Transkriptomanalysen untersucht. Dies sollte zu einem besseren mechanistischen Verständnis der von den verschiedenen Metallen verursachten schädlichen Effekte beitragen. Das Design der Studie war ausgelegt, um die Expositionseffekte der drei Metalle bei drei verschiedenen Expositionskonzentrationen zu vergleichen, und das bei zwei unterschiedlichen Entwicklungsstadien (vor und nach dem Schlüpfen). Folglich wurden die Embryonen an geringe, nicht-toxische Konzentrationen von Cadmium, Kobalt und Kupfer bis 48 und 96 hpf exponiert und anschließend einer Mikroarrayanalyse unterzogen, um Veränderungen in den Transkriptomprofilen zu bestimmen.
In Bezug auf die Effekte auf Transkriptomebene reagiert die Embryonen auf das nicht- essentielle Metall Cadmium deutlich unterschiedlich als auf die essentiellen Metalle Kobalt und Kupfer. Beispielsweise gab es nur bei den Cadmium exponierten Embryonen Hinweise auf ______v
Zusammenfassung
Detoxifikationsprozesse in der genspezifischen Transkription sowie in den Gen-Ontologie (GO) Termini. Mögliche Indikatoren für eine Entgiftungsreaktion, wie glutathion-s-transferase und metallothionein2 wurden zusammen mit heme oxygenase, ein weiterer möglicher Indikator für oxidativen Stress und Entgiftung, identifiziert und waren signifikant reguliert nach der Exposition an Cadmium. Im Gegensatz dazu waren bei den essentiellen Metallen Kobalt und Kupfer keine mit der Detoxifikation verwandten Gentranskripte oder GO-Termini reguliert. Auch in Bezug auf das gesamte Reaktionsmuster des Transkriptoms, die Reaktionsstärke und die Modulation der Pathway Regulierung zeigt diese Doktorarbeit sehr deutlich die unterschiedliche Reaktion der Fischembryonen auf essentielle im Vergleich zu nicht essentiellen Metallen.
Ferner heben die Ergebnisse das neuro- und ototoxische Potential von Cadmium, Kobalt und Kupfer hervor. Durch die zusätzlichen Untersuchungen zum Fluchtverhaltens der Embryonen nach taktiler Stimulation konnte eine Korrelation zu den Schädigungen der Motoneuronen für alle drei Metalle hegestellt werden. Demnach wäre es möglich, dass die Motoneuronschädigungen die Innervation von den Schwanzmuskeln unterbrochen haben könnten, was dann wiederum die für die Fluchtreaktion der Embryonen notwendige Muskelkontraktion verhindert hat. Die Transkriptomanalysen bei niedrigen Konzentrationsniveaus ermöglichte eine Zuordnung von GO Termini der Nervensystementwicklung zu den Schädigungen an den Motoneuronen für alle drei Metalle. Die transkriptionalen Änderungen mit Bezug zur Entwicklung des Nervensystems und die Motoneuronenschädigungen, die offensichtlich zu einer veränderten Fluchtreaktion führten, sind möglicherweise für alle drei Metalle über ähnliche Vorgänge verbunden. Allerdings wurde das Ausbleiben des Schlupfs, was zumindest teilweise auch mit einer beeinträchtigten Schwanzmuskelinnervation und einer inhibierenden Signaltransduktion im Nervensystem (z.B. zwischen den sensorischen Neuronen und den Motoneuronen) zusammenhängen könnte, nur bei den Kupfer exponierten Embryonen beobachtet. Basierend auf den Ergebnissen auf Transkriptomebene wurde diese Vermutung einer inhibierenden Signaltransduktion im Nervensystem verstärkt, da für Kupfer Wnt- und Notch-Signaltransduktionswege reguliert waren. Zudem konnten für Kupfer im Gegensatz zu Cadmium und Kobalt zusätzliche GO Termini, wie die Neuronenentwicklung und –differenzierung, mit der Deformation der Neuronen assoziiert werden. Beide molekularen Mechanismen schienen daher mit der fehlenden Fluchtreaktion und dem beeinträchtigten Schlupf der Embryonen verknüpfen zu sein.
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Zusammenfassung
Interessanterweise wurden Wnt-Signalwege auch in den Kobalt-behandelten Embryonen reguliert, wo bei einer höheren Carbonathärte auch ein beeinträchtigter Schlupf beobachtet wurde. Im Gegensatz dazu beeinflusste Cadmium nicht den Schlupf der Embryonen und zugleich wurden auch keine Wnt-Signalwege signifikant reguliert. Jedoch konnte die signifikante Expression von cldnb mRNA auf das ototoxische Potential von Cadmium hindeuten, welches die Embryonen durch Degeneration versuchen entgegenzuwirken. Das Tight-junction Protein Claudin b in den Neuromasten stark exprimiert wird.
Insgesamt demonstriert diese Dissertation, dass eine Kombination aus verschiedenen Fluoreszenzfärbungsendpunkte, Genexpressionsanalyse, Verhaltensbewertung und dem Zebrafischembryo-Toxizitätstest helfen kann, Mechanismen und Zusammenhänge zu präzisieren, quantifizieren und aufzuklären, die die Expositionseffekte von Metallen wie Cadmium, Kobalt und Kupfer bestimmen. Darüber hinaus konnte gezeigt werden, dass zusätzliche Endpunkten, Bewertungsverfahren zum Nachweis einer Metalltoxizität in Zebrabärblingembryonen zur Verfügung stehen, die eine deutlich höhere Sensitivität als herkömmliche Testverfahren in der ökologischen Risikobewertung aufweisen.
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List of figures
List of figures
Figure 1: Routes and interactions of trace metals in the environment (adopted from (Beijer and Jernelöv, 1986; Goyer and Clarkson, 1996)...... 3 Figure 2: Comparison of the dose-effect relationship between representative essential metals (a) and non-essential metals (b) (Fent, 2007)...... 5 Figure 3: Schematic illustration of the morphology and axonal direction of the three primary motor neurons, rostral (RoP) in red, medial (MiP) in green and caudal (CaP) in blue, of 48 hpf zebrafish embryo in lateral (left) and cross-sectional (right) view of a trunk somite. (Issa et al., 2012; Myers et al., 1986) ...... 11 Figure 4: Schematic illustration of a neuromast including the hair cells in green, the supporting cells in orange and the mantel cells in red (Chiu et al., 2008)...... 12 Figure 5: Schematic illustration of the key features of an adverse outcome pathway (AOP) (Ankley et al., 2010)...... 15 Figure 6: Inverted fluorescent full-focused images of the primary (left) and secondary (rigth) motor neurons of an untreated 48 hpf zebrafish embryo, stained with the specific antibodies znp1 and zn8. The green box comprises the area above the yolk sac extension where motor neurons were examined and classified...... 22 Figure 7: Inverted fluorescent full-focused image of the neuromasts of an untreated 72 hpf zebrafish embryo stained with DASPEI. The green boxes highlight the five neuromasts in the tail region which were measured per embryo...... 23 Figure 8: Proportion of 72-hpf embryos displaying morphological effects after exposure to different concentrations of (A) cobalt (Co), cadmium (Cd) and copper (Cu) and (B) control substances (neomycin, cisplatin and ethanol)...... 36 Figure 9: Proportion of 72-hpf embryos displaying morphological effects after exposure to cobalt at a concentration of 45.8 mg/L in different ISO-water...... 38 Figure 10: Representative inverted fluorescent images of stained (A) primary motor neurons (PMN) and (B) secondary motor neurons (SMN) in control embryos and embryos treated with cobalt (Co), cadmium (Cd) and copper (Cu)...... 40 Figure 11: (A) Representative inverted fluorescent images of stained neuromasts in control embryos and embryos treated with cobalt (Co), cadmium (Cd) and copper (Cu)...... 41 Figure 12: Tactile stimulation response assay at 72 hpf after exposure to cobalt (Co), cadmium (Cd) and copper (Cu)...... 42 Figure 13: (A) Effects of the control substance ethanol on primary motor neurons (PMN) and secondary motor neurons development (SMN) at 48 hpf; (B) relative fluorescence intensity (%) of stained neuromasts and (C) tactile stimulation response in 72-hpf embryos after exposure to neomycin and cisplatin...... 43 Figure 14: Venn diagrams representing zebrafish genes differentially expressed at 48 hpf (gray circle) and 96 hpf (green circle) after exposure to 3.3 mg Cd/L, 3.6 mg Co/L and 6.1 µg Cu/L compared to the control groups...... 57 Figure 15: Heat maps representing GO and KEGG enrichment analysis, showing the involvement of all differentially expressed genes in biological processes in (A) 48 hpf and (B) 96 hpf zebrafish embryos and (C) KEGG pathways...... 58 ______viii
List of figures
Figure 16: Functional relationships among significant GO terms identified in the transcriptomic response of 48 hpf zebrafish embryos to three different metals...... 60 Figure 17: The functional analysis of significant gene ontology (GO) terms for 48 hpf (A) and 96 hpf (B) zebrafish embryos exposed to cadmium, cobalt and copper...... 62 Figure 18: Comparison of the expression levels of mmp13a, hsp70.1, mmp9, mt2, cldnb, nkx2.2a, stat3 and atp2b1a, measured by qPCR in 48 hpf (A) and 96 hpf (B) zebrafish embryos exposed to cadmium (Cd), cobalt (Co) or copper (Cu)...... 63 Figure 19: Comparison of expression levels measured by microarray and qPCR in 48 hpf (A) and 96 hpf (B) zebrafish embryos exposed to cadmium...... 63 Figure 20: Bar diagrams representing differentially expressed genes after exposure to three different concentrations of cadmium, cobalt and copper in 48 hpf and 96 hpf zebrafish embryos: Total number of genes (A); concentration dependent transcript level changes of selected significant genes for cadmium (B), cobalt (C) and copper (D)...... 76 Figure 21: Functional comparison of the transcriptome response of cadmium treated 48 hpf (left) and 96 hpf (right) zebrafish embryos at different concentrations...... 78 Figure 22: Functional comparison of the transcriptome response of cobalt treated 48 hpf (left) and 96 hpf (right) zebrafish embryos at different concentrations...... 80 Figure 23: Functional comparison of the transcriptome response of copper treated 48 hpf (left) and 96 hpf (right) zebrafish embryos at different concentrations...... 82 Figure 24: mRNA expression levels of gene transcripts of mmp9, mt2, cldnb and nkx2.2a measured by RT-qPCR in 48 hpf and 96 hpf zebrafish embryos after exposure to cadmium (A), cobalt (B) or copper (C)...... 83 Figure 25: mRNA expression levels of gene transcripts of mmp9, mt2, cldnb and nkx2.2a measured by microarray in 48 hpf and 96 hpf zebrafish embryos after exposure to cadmium cobalt (B) or copper (C)...... 84
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List of tables
List of tables
Table 1: Morphological endpoints assessed in the fish embryo toxicity tests (FET). A detailed description of individual endpoints can be found in Nagel (2002) and Braunbeck and Lammer (2006) ...... 20 Table 2: Final concentrations of the antibody mixtures in the immunofluorescence stainings of motor neurons ...... 21 Table 3: Primers used for real-time qPCR validation of the microarray results ...... 28 Table 4: Concentrations of copper (Cu), cadmium (Cd) and cobalt (Co) determined by inductively coupled plasma mass spectrometry (ICP-MS). Concentrations are shown as mean values with the standard error of the mean...... 35 Table 5: Carbonate-hardness of the different ISO test media ...... 35 Table 6: Mean EC50 and LC50 values of cobalt, cadmium, copper, neomycin, cisplatin and ethanol with the corresponding 95% confidence intervals for sublethal and lethal morphological effects calculated using probit analysis (ToxRat Professional v2.10, ToxRat Germany)...... 37 Table 7: Concentrations of cadmium, cobalt and copper determined by inductively coupled plasma optical emission spectrometry (ICP-OES) ...... 56 Table 8: Metal concentrations determined by inductively coupled plasma-optical emission spectrometry (ICP-OES) ...... 74
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List of tables
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Chapter 1: General Introduction
Chapter 1: General Introduction
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Chapter 1: General Introduction
1.1. Metals in the environment
The preservation of the environment and the containment of environmental pollution is one of the greatest challenges of our society. With the constantly growing economy, the pollution of the environment by the production, usage and disposal of chemicals increases (Fent, 2007). Serious problems arise when harmful substances such as metals, accumulate in the environment and the food chain. The responsible handling and a risk-based evaluation of substances entering the environment is the basis for a sustainable use of natural resources.
Metals are among the oldest toxicants which can be found naturally in the environment, deriving from natural sources such as erosion, volcanic activity and forest fires (Nriagu, 1989). Extraction of metals from ore deposits and distribution in the environment by anthropogenic activity is the other main source, which probably accounts for the majority of metal dispersion nowadays. Unfavourably, metals can neither be synthesised nor destroyed, and once they have entered the environment they persist. With the beginning of the industrialisation, their use in industry and agriculture as well as in the development of new technologies increased (Bradl, 2005). Therefore, metals entered the environment increasingly from anthropogenic sources, mainly through mining, processing and manufacturing of metals, the disposal of metal- containing goods and chemical products (e.g. paints) (Bradl, 2005; Tchounwou et al., 2012). In recent times, particularly the global volume of electronics waste (e-waste) has grown rapidly and steadily. For example, the United Nations University Institute reported an increase from 33.8 million metric tonnes (Mt) in 2010 to 41.8 Mt in 2014 (Baldé et al., 2015). Industrial countries contribute the main part. In 2014, for example, most e-waste was generated in Asia with 16.0 Mt followed by America and Europe with 11.7 Mt and 11.6 Mt, respectively. While in Europe around 40% of the e-waste gets recycled, the global recycling rate is small with around 25-30% in Japan and China, 12% in America and Canada and only 1% in Australia (Baldé et al., 2015). Environmental damage is caused mainly by improper collection and disposal of e-waste, which contains several toxic metals such as mercury, cadmium, copper, chromium, silver, nickel, lead and cobalt. Metal contamination is a special environmental challenge due to the extreme persistency of metals.
There are many ways for metals to enter the environment and interact with the atmosphere and the terrestrial and aquatic system, as shown in Figure 1 (Beijer and Jernelöv, 1986). Most metals leach into the aquatic environment from landfills or become re-mobilised from sediments,
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Chapter 1: General Introduction
which largely act as metal sinks and source of other persistent pollutants (Bluhm et al., 2014, Kosmehl et al., 2012). The re-mobilisation of metals from sediments can happen during flooding events or by changes in other abiotic factors.
Figure 1: Routes and interactions of trace metals in the environment (adopted from (Beijer and Jernelöv, 1986; Goyer and Clarkson, 1996).
The aquatic environment with lakes, rivers, estuaries and oceans provides habitats for a large variety of different organisms and plants. As well as being the basis of all life, water is an important economic asset and indispensable to our daily life as drinking water. Therefore, the aquatic environment is particularly vulnerable against pollutions with metals and responsible handling of the resource water is crucial.
In Germany, the largest amount of heavy metals (around 70 %) enters the aquatic environment from diffuse sources such as erosion, rain or groundwater, followed by industrial direct discharges from local sewage treatment plants (20 %) and the chemical industry, which accounts for 10 %, according to the German Environment Agency (Umweltbundesamt UBA). Metals occur in the environment in various forms and speciation; in water mainly as free ions, as inorganic and organic complexes, adsorbed to particles or colloidally bonded. These forms are in equilibrium with each other and the amounts depend on the properties and the chemical composition of the medium. It is the free metal ions and the respective aqua complexes which cause most of the negative effect of metals relevant to ecotoxicology. The bioavailability of ______3
Chapter 1: General Introduction
heavy metals in the aquatic environment is heavily dependent on the pH, the water hardness, the dissolved organic carbon (DOC) content and to a lesser extent, temperature and salinity. In general, the concentration of free aquatic metal-ions and thus the toxicity, decreases with increasing water hardness, as metal ions complex with anionic ligands in the water. Therefore, a higher toxicity of heavy metals is generally reported for soft water but still dependent on the free metal ions (Fent, 2007).
With regard to adverse effects to aquatic organisms, many metals and metal-containing compounds are known to affect mainly cellular organelles like the mitochondria. They also cause cytotoxicity by apoptosis, neurotoxicity, carcinogenesis, cell cycle modifications or modulate enzymes involved in metabolism, detoxification and damage repair (Tchounwou et al., 2012; Wang and Shi, 2001). Further, many studies demonstrated that the production of reactive oxygen species (ROS) and oxidative stress play an important role in the toxicity and carcinogenicity of metals (Stohs and Bagchi, 1995; Valko et al., 2005). ROS are produced by many biological processes and contain oxygen radicals. They originate in organisms from normal metabolism processes, mitochondrial electron transport, or autoxidation processes of dissolved cell components (Fent, 2007). Oxidative stress is defined as a disturbance in the balance between the production of ROS and antioxidant defences, which causes detrimental effects on organisms (Betteridge, 2000). Further metals have the potential to bioaccumulate in the organisms. The bioaccumulation is highly dependent on the bioavailability of heavy metals in the aquatic environment.
In terms of biological function of metal ions in organisms, metals are divided into essential and non-essential metals. Essential metals are necessary for an organism to survive and must be supplied exogenously, because the organism cannot synthesize them. Non-essential metals have no biological function and are not necessary for an organism and an external supply is not required. Even if metals are essential for a living organism, they can still become toxic at higher concentrations. Figure 2 displays the comparison of the dose-effect relationship of representative essential versus non-essential metals. Essential metals like copper, zinc and cobalt can cause negative effects on living organisms by excess as well as deficiency. For example, deficiency of copper leads to anaemia in vertebrates (Fent, 2007). Contrary, non- essential metals like mercury or cadmium, increasingly exert negative effects with concentrations exceeding a threshold, causing reversible to irreversible damage to exitus.
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Chapter 1: General Introduction
Homoeostasis is the maintenance of the internal dose at optimal level, below the critical threshold, keeping excess and deficit of a metal in balance.
Figure 2: Comparison of the dose-effect relationship between representative essential metals (a) and non-essential metals (b) (Fent, 2007).
Other than with essential metals, organisms have very few mechanisms to rid the cell of an excess of non-essential metal ions. In terms of toxicity, essential and non-essential metals clearly differ, and this thesis particularly aims at addressing these differences by comparing exposure effects of the non-essential with the essential metals.
Nonetheless, environmental relevant metals like cadmium, mercury, zinc, copper, nickel, chromium, lead, cobalt, titanium, iron and silver can be harmful to the environment and the living organisms and have been studied intensively in recent years. However, many mechanistic and particularly molecular mechanisms underlying the toxic effect of those metals are still not fully understood. Therefore, this thesis focused on three environmentally relevant metals with one non-essential metal cadmium and two essential metals cobalt and copper. In terms of toxicity, cadmium and copper are certainly the major metal pollutants to impact the health and the survival of fish populations. However, potential adverse effects caused by an excess of essential metals like cobalt, in the aquatic environment may not be neglected, given that the use of diverse metals in consumer products is increasing rather than decreasing.
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Chapter 1: General Introduction
1.1.1. Cadmium
Cadmium is the chemical element with the symbol Cd and has an atomic weight of 112.4 u and the atomic number 48. It belongs to the transition metals and stands in group 12 of the periodic table of elements. It forms a solid silver grey metallic metal and appears in the environment mostly in an oxidative state of + 2. The amount of Cd in the earth's crust is 3 x 10-5 %. In freshwater, cadmium is mainly found as Cd2+ and Cd(OH)+.
Cadmium occurs naturally in the environment in a non-elementary form, arising from mineral ores. However, the majority derives form anthropogenic sources as a side product of the zinc and lead production. Cadmium is used in many industrial applications, for example in batteries, alloys, stabiliser for plastics, anticorrosive coatings, lightfast paint or electronic compounds. Besides mercury, cadmium is the heavy metal which causes the greatest damage to the environment and the human health. For example, cadmium contamination of Japanese rice fields in the middle and the end of the 19th century caused the itai-itai disease in humans (Fent, 2007).
In water, the cadmium toxicity is highly dependent on the concentration of the free hydrated 2+ 2+ Cd ions ([Cd(H2O)n] ). The speciation and thus the toxicity of cadmium changes with the pH, water hardness, alkalinity as well as the available organic and inorganic ligands, as seen for most of the metals. Additionally, the salinity of the medium is highly dependent on the cadmium toxicity. In water, a higher salinity increases the Cl- concentration and decreases the toxicity of cadmium, as the concentration of the free hydrated Cd2+ ions decreases with the formation of cadmium chloride (CdCl2) (Fent, 2007). Therefore, cadmium and their compounds are more toxic to freshwater organism.
1.1.2. Cobalt
Cobalt is a chemical element with the symbol Co, an atomic weight of 58.9 u and the atomic number 27. It belongs to the ferromagnetic transition metals and stands in group 9 of the periodic table of elements. It forms a solid metallic, bluish grey shaded metal and is the most stable in compounds at the oxidation states of + 2. In water, cobalt is mainly found dissolved 2+ as Co or as non-ionic CoCO3. The amount of Co in the earth's crust is 0.003 %.
Cobalt is an essential metal and an important component of vitamin B12, which is important for the growth of the red blood cells. In industry, cobalt has been used in the manufacturing of ______6
Chapter 1: General Introduction
pigments and paints, alloyed with cobalt or in batteries. Already in ancient times, cobalt was used to colour glass blue. Further, cobalt is a common component in electronic devices like cell phones. In order to cover the great demand of cobalt, cobalt needs still to be mined and extracted from the ore by aggressive toxic methods. Cobalt is mainly mined in Central Africa particularly in Congo, and causes severe environmental problems around the mines and it affects the health of workers and residents (Banza et al., 2009; Cheyns et al., 2014).
In the aquatic environment, the bioavailability of cobalt increases with a decreasing pH and increasing suspended solids (Moore, 1991). Further, the toxicity of cobalt to freshwater organisms is dependent on water hardness of the medium. Accordingly, Diamond et al. showed a decreasing toxicity with an increasing water hardness from 50 to 200 mg/L of CaCO3 (Diamond et al., 1992). There are otherwise few studies on the toxicity of cobalt, since cobalt is considered to be barely toxic. Despite its low general toxicity, the concern about cobalt has increased more recently because of suspected high carcinogenic properties.
1.1.3. Copper
Copper is a chemical element with the symbol Cu, an atomic weight of 63.5 u and the atomic number 29. It belongs to the transition metals and stands in the group 11 of periodic table of elements. It is a solid, metallic salmon pink metal which is most stable in aquatic solutions at oxidation states + 2. In the dissolved state copper is mainly found as CuOH+ or as non-ionic
CuCO3. The amount of Cu in the earth's crust is 0.01 %.
Copper is essential to living organisms and is important for many body functions, like the protection against free radicals, the electron transport and the formation of blood. Copper is a corrosion resistant, antibacterial, non-magnetic metal and has a very good electrical and thermal conductivity. Thus, copper is used in many different products for example in jewellery, coins, art products and as ingredient of many alloys. Further, copper is very often used in the electrical industry for example as a component of power cords and wiring. In Germany, copper water pipes are still common from which copper can directly leach into the drinking water. How much of the copper leaches depends highly on the pH, water hardness, the retention time in the pipes as well as the age of the pipe.
In water, copper toxicity is highly depending on the concentration of the free hydrated Cu2+ 2+ ions ([Cu(H2O)6] ). For example, copper causes highly toxic effects at lower pH-values as
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Chapter 1: General Introduction
copper is especially found as free hydrated Cu2+ ions. With an increasing pH, the amount of the free hydrated Cu2+ ions is decreased by the increasing amount of copper hydroxide and copper carbonate and therefore the toxicity of copper decreases with an increasing pH (Stumm and Morgan, 1996). In lakes, copper (Cu(II)) mainly binds to organic complexes and the concentration of free Cu2+-aqua-ions is very low. Copper is an environmentally important metal and has been studied extensively in recent years. Free Cu(II) ions are cytotoxic and affect especially the liver of vertebrates.
1.2. The test organism zebrafish and the embryo toxicity test as a test system
Fish are important indicators of metal pollution in fresh water (Öztürk et al., 2009; Rashed, 2001) since they accumulate metals which can be taken up by humans through the food chain. Also, many fish species are predators and are as such affected by bioamplification of metals or other bioaccumulative pollutants. Due to their standing at the top level of the trophic web and their role in aquatic ecosystems, fishes are the representative vertebrate models in ecotoxicology.
Adult fish take up metals either via food or by ventilation from the water and accumulate them in their tissues, mostly in the liver, kidney and gills and to a lesser extend in the muscles. In fish embryos and larvae, which are still sustained by the yolk and do not yet consume external food, the uptake of metal occurs only passively through the skin. The uptake and accumulation depends on various parameters, like metal speciation and concentration, fish species and age, exposure time, way of uptake and environmental conditions (Jezierska and Witeska, 2006). For example, a higher water temperature increased the uptake and bioaccumulation of metals like cadmium in different fish species (arctic char, stone loach and japanese eel) which could be explained by a higher metabolic rate (Douben, 1989; Köck et al., 1996; Yang and Chen, 1996). The pH influenced the accumulation of copper in tissues of Oreochromis niloticus (Cogun and Kargin, 2004). In zebrafish, metals have shown to reduce the Ca2+ and Na+ uptake. After cadmium and copper exposure of zebrafish, the Ca2+ uptake was particularly affect (Alsop and Wood, 2011).
In general, early developmental stages of fish are very sensitive to metal exposure (Fent, 2007; Jezierska et al., 2009). Metals can cause mortality and have negative effects on the development, with malformations and a smaller size of the fish embryos, and affect hatching. For example, copper as well as cobalt affected the hatching of zebrafish larvae (Cai et al., 2012; ______8
Chapter 1: General Introduction
Dave and Xiu, 1991; Johnson et al., 2007; Muller et al., 2015), which was also noticed in the studies of this thesis. Further, metal exposure can even induces endocrine disrupting effects in fish (Jezierska et al., 2009).
The fish species Danio rerio (formerly Brachydanio rerio) commonly known as zebrafish, was used for the studies of this PhD-thesis to improve the understanding of the toxic effects of environmentally relevant metals in early life fish. The zebrafish is a tropical benthopelagic species belonging to the carp and minnow family (Cyprinidae) and is native to Southeast Asia and the Ganges river system of Burma and Sumatra. They grow about 3-5 centimeters long. The females are a little paler and usually appear more round bodied, especially if the stomach is filled with eggs. The males are more slender and have a reddish-orange tint (Westerfield, 2000). The zebrafish has many characteristics which makes it a good test organism in ecotoxicology. They are hardy, undemanding and the husbandry is relatively low maintenance and inexpensive. The main advantages with respect to assays using the fish embryos are the rapid development and in particular the high number of year-round produced eggs per zebrafish female (200-300 per spawn), the small size of the eggs, and the observation facilitating transparency of the chorion and the embryos. Fish embryos are beneficial for studying toxic effects of pollutants like metals, because they enable fast and economical testing as well as they provide numerous methodological tools to study toxic effects at multiple biological levels in a whole organism. Additionally, the zebrafish embryo acute toxicity test (FET) according to the OECD test guideline 236 is a recognized animal alternative for the assessment of fish acute toxicity. The test was standardized already in 2000 as DIN standard (DIN 38415-6) and 2001 implemented for the wastewater assessment in Germany. The test complies with the principles of the 3Rs of replacement, reduction and refinement of animal tests (Russell et al., 1959) and helps reducing the number of adult fishes otherwise sacrificed in acute fish tests for either waste water or chemical assessments. The FET is a positive example of a successful validation and international adoption of an animal alternative non in-vitro test method.
The FET can easily be enhanced by additional sub-organism test endpoints, in order to improve the understanding of toxic effects. It was therefore a key objective of this PhD-thesis was to evaluate additional sensitive test endpoints for the zebrafish fish embryo toxicity test by including fluorescence based staining methods and gene transcription analysis. Fluorescent labels are great tools to visualize different cell types and tissues in vivo. They have demonstrated to facilitate the detection of e.g., cyto-, myo-, neuro-, vaso- or ototoxic effects of ______9
Chapter 1: General Introduction
environmentally relevant chemicals in zebrafish. Thus, different fluorescence based staining methods or transgenic fish lines have successfully been applied in this context (Delov et al., 2014; Muth-Köhne et al., 2012). Of great advantage are fluorescent endpoints which can be analysed and quantified electronically with the help of image analysis programs. Computer- based effect assessments are far more objective than human assessments which rely on individual judgment and can be very subjective. Moreover, the detection and measurement of e.g., fluorescence intensity can be automated. This thesis demonstrates how different fluorescence-based as well as molecular methods can gainfully be added to the FET to further elucidate the effects of metal exposure using early developmental stages of the zebrafish as a model.
1.2.1. Assessment of neurotoxic effects using defects of motor neuron development
Many studies have shown that metal exposure can cause neurological impairments in humans and other living organisms (Caito and Aschner, 2015; Du and Wang, 2009; Wennberg, 1994; Wright and Baccarelli, 2007). Metals can interfere with neurotransmission but can also damage cells of the nervous system. Motor neurons are part of the central nervous system and are required for muscular control. They transmit signals from the spinal cord through their axons to innervate the muscles. In zebrafish, motor neurons are distinguished into primary and secondary motor neurons. In general, the primary motor neurons innervate the fast muscle fibers while the secondary motor neurons innervate the slow muscle fibers (Babin et al., 2014). The development of the primary motor neurons (PMN) starts during the first day post-fertilization (dpf), while the secondary motor neurons (SMN) start to develop approximately six hours later (Kimmel et al., 1995; Myers et al., 1986). Every trunk somite contains three primary motor neurons on each side, a rostral (RoP), a medial (MiP) and a caudal (CaP) primary motor neuron and sometimes a fourth, a variable (VaP) primary is present (Fig. 3). Figure 3, right, illustrates how the CaP motor neurons innervate the ventral muscles, RoP the lateral and MiP the dorsal muscles (Eisen et al., 1986; Myers et al., 1986; Westerfield et al., 1986). In contrast to the primary motor neurons, the secondary motor neurons are located more ventrally and laterally in the spinal cord. The secondary motor neurons are categorized in ventral (vS), dorsal (dS) and dorso-ventral (dvS) projected secondary motor neurons (Babin et al., 2014; Menelaou and McLean, 2012).
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Figure 3: Schematic illustration of the morphology and axonal direction of the three primary motor neurons, rostral (RoP) in red, medial (MiP) in green and caudal (CaP) in blue, of 48 hpf zebrafish embryo in lateral (left) and cross-sectional (right) view of a trunk somite. (Issa et al., 2012; Myers et al., 1986)
To microscopically observe a damaging effect of chemicals on the motor neurons of zebrafish embryos, transgenic fish lines can be used. The transgenic zebrafish line Tg(gata2:GFP) (Meng et al., 1997) expresses green fluorescent protein (GFP) in the secondary motor neuron subtype vS (innervate in ventral myotome) while Tg(isl1:GFP) (Higashijima et al., 2000) zebrafish expresses GFP in subtype dS (innervate in dorsal myotome). In 2006, Carrel et al. described a classification of the axon defects in the Tg(gata2:GFP) zebrafish after smn MO knockout (Carrel et al., 2006). Both transgenic zebrafish lines were used in combination with a monoclonal antibody staining using the antibody zn5 against the antigen activated leukocyte cell adhesion molecule a (alcama), to characterize the toxic effect of nicotine on the motor neuron development (Menelaou and Svoboda, 2009). Additional to transgenic zebrafish lines, motor neuron defects can also be visualized by immunochemical staining. The disruption of primary and secondary motor neuron development in 3 dpf zebrafish embryos, for example, was visualized using specific monoclonal antibody stainings with znp1 (antigen: synaptotagmin IIb) for PMNs and zn8 (antigen: alcama) for SMNs (Sylvain et al., 2010). Accordingly, this approach has been used to assess the neurotoxic potential of several chemicals in 48 hpf zebrafish embryos, like thiocyclam, cartap and disulfiram (Muth-Köhne et al., 2012), and to demonstrate the damage of SMNs after exposure to silver nanoparticles (Muth-Köhne et al., 2013). The immunofluorescence staining of motor neurons had been established at the Fraunhofer IME Unifish lab and was applied in the course of this thesis to evaluate the neurotoxic potential of the three different metals.
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1.2.2. Assessment of neuromast damage as asensitive indicator of peripheral neurotoxicity
The lateral line is the main mechanosensory organ of fish and most important for rheotaxis and coordination in swimming behaviour, prey detection and predator avoidance (Gompel et al., 2001; Montgomery et al., 1997). It consists of the so called neuromasts which are formed of mantel, supporting and hair cells (Figure 4). The neural hair cells are directly exposed to the fish’ surrounding medium and potential toxicants dissolved therein. And likewise to the hair cells of the mammalian inner ear, the hair cells of the neuromasts are high susceptible to damage by ototoxins (Chiu et al., 2008). Damage or death of the neuromast cells can therefore be considered a very sensitive parameter of mechanosensory toxicity and disruption of the peripheral nervous system of the fish.
Figure 4: Schematic illustration of a neuromast including the hair cells in green, the supporting cells in orange and the mantel cells in red (Chiu et al., 2008).
Already in fish embryos a distinction can be made between the neuromasts of the anterior lateral line of the head region and the posterior lateral line (PLL) of the trunk and tail region. The neuromast development starts after 20 hpf while the PLL primordium migrates caudal towards the end of the tail and thereby evolve the neuromasts. This formation is completed at around 40 hpf (Kimmel et al., 1995). The hair cells of the neuromasts can regenerate by cellular proliferation (Warchol and Corwin, 1996) or trans-differentiation (Adler and Raphael, 1996) of supporting cells after damage by chemical exposure up to a specific threshold concentration (Monroe et al., 2015). ______12
Chapter 1: General Introduction
The imaging of the development of the lateral line can be achieved using the transgenic zebrafish line Tg(cldnb:lynGFP), in which GFP is expressed in the hair cells and the supporting cells of the neuromasts (Haas and Gilmour, 2006). This fish line was used for development studies on the primordium of the posterior lateral line in zebrafish embryos (Gallardo et al., 2010; Sarrazin et al., 2010). Alternatively, in vivo staining of neuromasts is possible with different vital dyes like FM® 4-64FX, FM1-43, 4-(4-(diethylamino)styryl)-N- methylpyridinium iodide (4-di-2-Asp) and 2-(4-(dimethylamino)styryl)-N-ethylpyridinium iodide (DASPEI). Both approaches are suitable to detect damaging developmental effects on the neuromast hair cells of zebrafish (Hernandez et al., 2006; Jorgensen, 1989; McDermott et al., 2010; Nagiel et al., 2008; Ton and Parng, 2005). However, the dye staining enables a more selective assessment of hair cell death than the transgenic line, in which the supporting cells are illuminated as well. Thus, the in vivo neuromast staining method with DASPEI was optimized and applied in this thesis to assess the toxic potential of cadmium, cobalt and copper to the neuromast cells.
1.2.3. Gene expression analyses
To investigate the molecular mechanism of toxic action of compounds, transcriptome analysis is a useful tool. Microarray technology, which had been developed in the 1990s, gained recognition in ecotoxicology from early 2000 onwards. The technology makes it possible to identify and measure the expression levels of thousands of gene transcripts of a given organism or tissue simultaneously (Babu, 2004). For the analysis, the RNA of samples gets extracted, if needed amplified and labeled with fluorescent Cyanine dyes like the green Cy3 and/or the red Cy5. Afterwards, the labeled RNA samples are hybridized for example to complementary oligonucleotides on glass slides and the slides are then scanned by a fluorescent reader and bound labeled RNA molecules can be quantified by the strength of the fluorescent signal. The expression of single gene transcripts can be measured by reverse transcription polymerase chain reaction (RT-PCR). Using quantitative real-time (rt) RT-PCR, the PCR amplicons can be quantified based on fluorescence measurement. Commonly, either intercalating dyes (like SYBR Green) or specific oligonucleotide probes labeled with dyes, are used for quantitative rt (RT-)PCR. In order to investigate effects of metal exposure on gene expression and signaling, microarray analysis with additional quantitative rt (RT-)PCR was applied in this thesis.
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Genetic, genomic and transcriptomic analyses of zebrafish are facilitated as the zebrafish genome is completely sequenced (Busch et al., 2011) and widely annotated. Gene expression analysis of zebrafish can help to determine the underlying mechanism of the toxic effect of chemicals. For instance, gene expression studies have been applied to describe the mechanism of endocrine disruption (Hawliczek et al., 2012; Schiller et al., 2013a; Schiller et al., 2013b). To provide mechanistic insight of metal toxicity, exposures to nickel, cobalt and chromium were studied by transcription profiling of whole adult male zebrafish (Hussainzada et al., 2014). For zebrafish embryos, microarray analyses were conducted after copper (Craig et al., 2009), cadmium (Sawle et al., 2010) or mercury (Ung et al., 2010) exposure to study molecular mechanisms of the tested metals.
The application of the fish embryo test with additional fluorescence endpoints and transcriptomics enables researchers to link toxic effects of substances across biological levels, from the molecular processes to the functional consequences. This appears to be the most promising approach to describe the mechanisms of toxicity. In terms of the application of such multi-level effect evaluations in the regulatory context, the concept of adverse outcome pathways (AOPs) is being implemented over recent years. AOPs combine molecular initiating events with an adverse outcome across several biological levels (Ankley et al., 2010). The AOP framework follows the same principle as the mechanism of action and mode of action concept. However, AOP more comprehensive and includes various key features as molecular, cellular, structural and functional changes in biological systems. Figure 5 illustrates the schematic representation of an adverse outcome pathway from the chemical exposure to macro-molecular interactions via the cellular, organ and organism responses to the resulting response of a population. The AOP framework can help to categorise and generalize toxicity-related knowledge and to improve the understanding of the ecological risk which benefits the assessment of chemicals (Groh, Ksenia J. et al., 2015). AOPs also identify possible knowledge gaps requiring further research studies.
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Chapter 1: General Introduction
Figure 5: Schematic illustration of the key features of an adverse outcome pathway (AOP) (Ankley et al., 2010).
1.3. Objectives
The overarching objective of this PhD-project was to improve the understanding of the toxic effects caused by environmentally relevant metals in early life-stage fish, by applying variations of the zebrafish (Danio rerio) embryo test. Metal toxicity is still a serious global problem, thus the project is of a great relevance in the context of the protection of wildlife populations and ultimately the health of people.
The goals of this thesis:
• To elucidate at least some of the mechanisms underlying toxicity of three environmentally relevant metals (essential and non-essential) at morphological, sub- morphological and molecular level in zebrafish embryos → to better understand adverse effects and the associated risks for the environment.
• To evaluate additional test methods such as vital and antibody stainings and gene transcription analysis, for the assessment of metal toxicity in zebrafish early life stages.
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Chapter 1: General Introduction
Aims and resulting tasks:
Extend the scope of the zebrafish embryo toxicity test specifically for metals
- by including morphological and functional (i.e. behavioural) endpoints:
o To investigate adverse effects of cadmium (CdCl2), cobalt (CoSO4) and copper
(CuSO4) on the morphological development, the escape response and the development of motor neurons and neuromasts of wild-type zebrafish embryos. (Chapter 3)
- by including transcriptome analysis endpoints:
o To investigate the transcriptome response to cadmium (CdCl2), cobalt (CoSO4)
and copper (CuSO4) exposure by applying microarray analysis to pre-hatch and post-hatch wild-type zebrafish embryos. → Comparison of the different metals (non-essential and essential) at two developmental stages (Chapter 4) o To investigate the concentration dependency of effects of three different
exposure concentrations of cadmium (CdCl2), cobalt (CoSO4) and copper
(CuSO4) on the transcriptome of wild-type zebrafish embryos at two developmental stages (pre-hatch and post-hatch). → Comparison of the different metals, the developmental stages and the exposure concentrations (Chapter 5)
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Chapter 2: Material & Methods
Chapter 2: Material & Methods
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In this chapter, the basic methods used for this thesis are described. To avoid repetition, only specific methods or modifications of the basic methods are described in the individual chapters.
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Chapter 2: Material & Methods
2.1. Zebrafish husbandry
Adult wild-type zebrafish from established breeding groups at the Fraunhofer IME (originally obtained from West Aquarium GmbH, Bad Lauterberg, Germany) were used for egg production. The zebrafish were cultured in large groups in 200–300-L tanks under flow-through conditions at 27 ± 1°C and with a 14-h photoperiod. The fish were fed twice daily on weekdays, once with Tetramin Flakes and once with live brine shrimp nauplii (Artemia salinas), and only with brine shrimps at the weekend. Water used for husbandry was charcoal- and particle filtered and UV-light sterilized before inflow in the zebrafish tanks. Water quality is checked weekly by measurements of temperature, pH, oxygen, water and carbonate hardness, nitrate, nitrite and ammonia. For egg collection, shallow glass spawning trays covered with metal mesh lids were placed into the tanks before illumination and were left for one hour at the beginning of the light phase. Subsequently, eggs were harvested by carefully removing the spawning trays from the tanks and collecting the eggs in a tea strainer. The collected eggs were cleaned from debris with a wash bottle and transferred to a glass dish with fresh aquarium water. The estimated number of eggs per tank was recorded for control.
2.2. Metals, chemicals and reagents
Cadmium, cobalt and copper were purchased from Sigma-Aldrich (Munich, Germany).
Cadmium was tested as cadmium chloride (CdCl2), cobalt as cobalt(II) sulfate heptahydrate
(CoSO4.7H2O) and copper as copper sulfate (CuSO4). All metal salts were well soluble in water and all metal test solutions were directly prepared in 1:5 diluted ISO-standard water (according to OECD guideline 203, Annex 2, and diluted 1:5). The stock solutions of all metals were prepared one day before test start and stirred for at least one hour at 27°C. Subsequently, the exposure test solutions were prepared from the stock solutions at corresponding dilutions with 1:5 diluted ISO water. Afterwards, all test and remaining stock solutions were strongly aerated overnight to agitate and oxygenate the solutions. The 1:5 diluted ISO-water is a soft water with an electric conductivity of about 150 µS/cm, a water hardness of 4°dH and a carbonate hardness of 1°dH. The pH in all tests remained between 7.5 and 8.5. Temperature, pH and oxygen of the test solutions were checked before test start and at the end of the tests.
The metals, used control substances as well as all important reagents and chemicals used are listed in Supplements A: List of chemicals, consumables and equipment.
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2.3. Zebrafish embryo toxicity tests
Zebrafish embryo toxicity tests were carried out following the SOP of the Fraunhofer IME, according to the principles of the DIN EN ISO 15088 and the Fish Embryo Toxicity Test OECD draft guideline (OECD 2006). Metal exposure experiments were carried out in 96-well U- bottom polystyrene microtiter test plates (Greiner Bio-one, Germany). The wells of the plates were saturated overnight by incubation with 200 µl of the corresponding metal or control solution. All solutions were renewed prior to the test start. After harvest of the eggs, the embryos were transferred to Petri dishes containing the test solutions as quickly as possible to ensure early exposure ( 1 hpf). The eggs were examined under a microscope, and those which were coagulated, unfertilized or younger than the four- cell respectively older than 16-cell stage, or which showed uneven cell division, were removed. Afterwards, the eggs were individually transferred from the Petri dishes to the wells (one embryo/well) of the plates and incubated for a maximum of 96 h at 27 ± 1°C with a 14-h photoperiod. All test solutions were renewed after 48 h.
2.3.1. Assessment of exposure concentration dependent morphological effects
Each test consisted of two replicate plates for each treatment (i.e., either one of the metal exposure concentrations or ISO-water control) as technical replicates to account for possible plate effects. Each plate contained 24 embryos for either controls or exposures, accounting for n=48 embryos per treatment and test. An internal plate control of 12 wells and embryos was also included on each plate. All tests were repeated three times to account for possible inter- assay variations. The total exposure time was in most cases 72 h, with assessments of morphological effects after 24, 48 and 72 h. The tests were terminated after 72 h since the neuromast staining (see 2.3.3) worked most efficient around 72 hpf and the method required therefore termination and fixation of the embryos at this time point. The 96 h assessment time point stipulated by the OECD guideline 236 was therefore omitted and the post-hatch mortality rate determined 24 h early at 72 hpf. For the microarray experiments, however, the total exposure time was 96 h.
The assessment time points were recorded as hpf based on the incubation time, disregarding the development stage of the embryos 1 hpf at the start of exposure. Twenty-one sublethal and lethal morphological effects were evaluated according to Nagel (2002) and Braunbeck and Lammer (2006), with minor modifications. “Teratome” and “Exitus” were added to the list to ______19
Chapter 2: Material & Methods
describe severly malformed embryos (i.e. embryos lacking most or all developmental structures, like somites or eyes) respectively deceased embryos ≥24h. A list of all morphological endpoints assessed can be found in Table 1.
Table 1: Morphological endpoints assessed in the fish embryo toxicity tests (FET). A detailed description of individual endpoints can be found in Nagel (2002) and Braunbeck and Lammer (2006) Developmental stage 24 hpf 48 hpf >72 hpf Lethal endpoints Coagulation * * * No detachment of tail * * * No somites * * * No heartbeat * * Teratome * * * Exitus * * * Sublethal endpoints Altered formation of somites * * * No formation of eyes * * * No spontaneous movement * Edema * * * Reduced Heart-beat/Blood circulation * * Pigmentation * * Not hatched * No response to tactile stimulation * Malformation of head * * * Malformation of sacculi/otoliths * * * Malformation of tail * * * Malformation of heart * * Modified chorda structure * * * Yolk deformation * * * General growth retardation * * *
2.3.2. Assessment of motor neuron impairment using immunofluorescence staining
Separate zebrafish embryo toxicity tests were carried out for the evaluation of motor neuron impairment of the three metals. Ethanol (ROTIPURAN® ≥99.8%, C2H6O, Carl Roth) was used in parallel as a positive control substance (conc. of 1 to 3%) for the staining method and as a reference for the effect expression. Embryos exposed for 48 h (and corresponding controls) were dechorionated manually and fixed in 4% (w/v) paraformaldehyde (Sigma Aldrich) in phosphate-buffered saline (PBS, Invitrogen) for 4 h at room temperature, then washed three times in PBS containing 0.1% (v/v) Triton X-100 (PBST) and stored at 4°C. Whole-mount ______20
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immunostaining was carried out according to Westerfield (2000) and as modified by Muth- Köhne et al. (2012), with the modification that permeabilization and blocking was achieved by incubation with 4% Triton X-100 plus 10% (v/v) normal goat serum in PBST (PBS/4TN) for 30 min. The embryos were then incubated in 96-well plates (10-12 embryo/well) with a primary antibody mixture of znp1, a mouse monoclonal antibody (IgG2a) specific for PMNs and zn8, a mouse monoclonal antibody (IgG1) specific for SMNs (Trevarrow et al., 1990), both obtained from the Developmental Hybridoma Bank, University of Iowa, USA. The secondary antibodies were DyLight 549-conjugated AffiniPure Goat Anti-Mouse IgG, specific for Fc subclass 1, and DyLight 649-conjugated AffiniPure Goat Anti-Mouse IgG, specific for Fc subclass 2a (Jackson ImmunoResearch Europe). The final concentrations of the primary and secondary antibody mixtures used for the immunofluorescence staining of the motor neurons were determined by titration and are shown in Table 2.
Table 2: Final concentrations of the antibody mixtures in the immunofluorescence stainings of motor neurons final concentration Standard volume Primary Znp1 (Concentration 25 µg/mL) 5 µg/mL 60 µL antibodies Zn8 (Concentration 50 µg/mL) 5 µg/mL 30 µL (300 µL) Normal goat serum 20 µL/mL 6 µL PBST 204 µL Secondary DyLight 549-conjugated 5 µL/mL 5 µL antibodies DyLight 649-conjugated 5 µL/mL 5 µL (1000 µL) Normal goat serum 20 µL/mL 20 µL PBST 970 µL
Antibody incubation, imaging and analysis were carried out as described by Muth-Köhne et al. (2013). Accordingly, the embryos were embedded in one drop of 3% methylcellulose and horizontally aligned on a microscope slide. The larvae were analyzed under the microscope using the Leica AF6000 inverted microscope system. Z-stack image series were acquired from each embryo and the images were processed by generating a so-called full-focus image with the ImageJ plugin “Stack Focuser”.
Primary and secondary motor neurons were examined individually at different wavelengths in the area above the yolk sac extension, as shown in Figure 6. Between 9 and 10 motor neurons were analysed per embryo. Motor neurons showing defects were classified (according to Carrel et al. (2006)) based on the severity of damage as mild (i.e. delayed development, axons lacking stereotyped morphology), moderate (i.e. axons with ectopic branches or innervating neighboring myotomes) or severe (e.g. truncated axons).
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Figure 6: Inverted fluorescent full-focused images of the primary (left) and secondary (rigth) motor neurons of an untreated 48 hpf zebrafish embryo, stained with the specific antibodies znp1 and zn8. The green box frames the area above the yolk sac extension where motor neurons were examined and classified.
This classification was applied to 5–6 individual embryos from each replicate and three independent test replications were conducted. Thus, 15 – 18 embryos were analysed for each exposure concentration, and the results were presented and statistically analysed as percentage values of each severity class in comparison to the proportion of normally-developed motor neurons.
2.3.3. Assessment of neuromast damage using a vital dye staining
Metal exposed and corresponding control 48 hpf and non-hatched 72 hpf zebrafish embryos were dechorionated manually. Neomycin (neomycin trisulfate salt hydrate;
C23H46N6O13.3H2SO4 x H2O, Sigma-Aldrich) and Cisplatin (cis-diamineplatinum(II) dichloride; H6Cl2N2Pt, Sigma-Aldrich) were used as positive control substances for the staining method and as a reference for the ototoxic effects. All embryos were transferred to 1.5-mL Eppendorf tubes (10-12 embryo/tube) filled with the vital dye solution (0.1 mg/mL DASPEI (2-[4-(Dimethylamino)styryl]-1-ethylpyridinium iodide) in ISO water) and stained in the dark for 20 min. DASPEI is a red fluorescent potentiometric mitochondrial dye (max. excitation/emission 460/590 nm), which stains mitochondria in living cells and tissue. As hair cells contain many mitochondria and are easily accessible, especially hair cells are intensly stained. In previous studies, in vivo staining of neuromast hair cells was already applied (Ton and Parng 2005; Harris et al. 2003; Williams and Holder 2000). The dye was removed carefully by repeated washing with 1:5 diluted ISO water. It was important to ensure the vitality of the larvae, otherwise selective staining of the neuromasts was impossible, because dead cells have a diminished mitochondrial membrane and therefore the whole fish would be stained.
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The embedding and imaging of the embryos was carried out analogous to the motor neuron staining in Section 2.3.2. The neuromasts of the embryos were analyzed by measuring the fluorescence intensity of the neuromasts versus the background fluorescence using ImageJ (Version 1.46, National Institutes of Health). The background intensity was subtracted from the neuromast intensity.
Figure 7: Inverted fluorescent full-focused image of the neuromasts of an untreated 72 hpf zebrafish embryo stained with DASPEI. The green boxes highlight the five neuromasts in the tail region which were measured per embryo.
The fluorescence intensity of five neuromasts in the region between the distal end of the yolk sac and the end of the tail were measured per embryo (Figure 7). Three independent test replications were analyzed, with 5–6 individual embryos in each replicate.
2.3.4. Assessment of escape response
In order to evaluate impairments of the escape response to tactile stimulation (basically the startle response), embryos were exposed to the metals in 24-well flat-bottom plates, with each well filled with 2 mL of either test solution or 1:5 diluted ISO water. 12 embryos were examined (72 hpf) for each test concentration. Each embryo was transferred to a single well. Unhatched embryos were dechorionated beforehand. After 5 minutes of acclimation, the embryos were nudged with a 10-μL pipette tip and the responses were recorded. To measure the embryo behavior, a scoring system was developed defining four different levels of escape behavior (Buck et al., 2012): the normal escape response (normal startle response or C-start), reduced escape response (1–2 cm movement), minimal escape response (1–5 mm movement) and no escape response (no movement). For each exposure concentration, the results were presented and statistically analysed as percentage values of each different levels of escape behavior in comparison to the proportion of normal escape response.
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2.3.5. Statistical analysis of the morphological and functional endpoints
For all tested metals and the control substances concentration-effect relationships were determined, and the ECx and LCx threshold values for sublethal and lethal morphological effects were calculated with the corresponding 95% confidence intervals (CIs) by probit analysis using ToxRat Professional v2.10.
Further statistical analysis for the morphological development, the escape response and the development of motor neurons and neuromasts was carried out using GraphPad Prism software v5.0. Data were tested for normality and homogeneity of variance. For all data, one-way ANOVA with Dunnett’s for post hoc testing for multiple comparisons (*p = 0.05; **p = 0.01; ***p = 0.001) was conducted to test for significant differences between the control and exposure groups for a respective test parameter.
2.4. Gene transcription analysis
The embryo tests for the microarray analysis were conducted according to the description of section 2.3.1. After 48 and 96 h of exposure, 20 embryos per replicate were sampled and pooled in 1.5 mL Eppendorf tubes, all liquid removed and snap-frozen over dry ice and then stored at –80°C for RNA extraction. For the microarray analysis, four biological replicates (i.e. four samples of pooled embryos) were used for each treatment.
2.4.1. RNA Extraction
Total RNA was extracted from the frozen, pooled embryos using the Trizol method and ® homogenization with motor-driven plastic micro-pistils. After addition of 500 μl of TRIzol (Invitrogen) or TRI Reagent (Sigma-Aldrich), each sample was homogenized and afterwards centrifuged at 12.000 g and 4°C for 10 min. The RNA-containing supernatant was incubated for 5 min at room temperature, then 100 μl of chloroform were added and the samples carefully vortexed, incubated another 10 min at room temperature and centrifuged again. The RNA- containing water phase was separated, ethanol was added in a 1:1 ratio, and samples were again carefully vortexed and transferred to RNeasy Mini Spin Columns (Qiagen, Hilden, Germany) for RNA purification. The RNA was cleaned-up according to the manufacturers’ protocol and was stored at -80 °C until further analysis.
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The quality and quantity of the total RNA was verified using a NanoDrop 1000 spectrophotometer (Thermo Fisher Scientific, Schwerte, Germany) and an Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, USA). For all RNA samples, the absorbance ratios 260/280 and 260/230 were greater than 2.0 and 1.8, respectively, and the RNA integrity number (RIN) was above 8.7.
2.4.2. Microarray experiments
The microarray experiments were generally in compliance with the MIAME (Minimum information about a microarray experiment; Brazma et al. 2001, Nature Genetics) principles. The microarrays were performed using the Zebrafish (V3) Gene Expression Microarray 4 x 44K Kit (Agilent Technologies), with 43,803 Danio rerio probes per array, representing ~18,350 genes. The samples were processed following Agilent’s One-Color Microarray-Based Gene Expression Analysis Protocol (Low Input Quick Amp Labeling, v6.6, September 2012). The starting amount of all samples was 100 ng of total RNA. Agilent One-Color RNA Spike- In Mix was added as internal positive controls for monitoring the microarray workflow for linearity, sensitivity and accuracy, from sample amplification and labelling trough to the microarray process. The total RNA samples with Spike-In were reverse transcribed into cDNA, amplified and synthesised into cRNA by T7 RNA Polymerase. The cRNA was labelled with Cyanine- 3 and purified on RNeasy Mini Spin Columns (Qiagen, Hilden, Germany). The amount of the amplified and labelled cRNA and the specific activity of the Cy3-fluorescence signal were quantified and then 1.65 μg cRNA of each sample were hybridized to the microarray slide overnight for 17 h at 65°C. All microarray slides were scanned with the Agilent Microarray Scanner (Agilent Technologies), and image information (raw data) extracted from the scans by Agilent Feature Extraction Software (Agilent Technologies). During this step, the pixels were identified and quantified as intensity signals in each feature, intensity signals were dye normalized with LOWESS intensity normalization and the fluorescence intensity of the background was subtracted. Further, outlier features were detected and flagged. Afterwards, datasets for each metal were filtered and percentile normalized separately using GeneSpring Software GX (Agilent Technologies) by setting the raw signal threshold to preset 1.0, which convert all values less than 1.0 to 1.0. This is necessary because a value less than 1.0 would give a large negative value after log transformation. Based on the common assumption that only half of the genes on the array are differentially expressed, the intensity values of all probes were shifted to the 75th percentile. The baseline transformation was set to the median, which means ______25
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that for each probe the median of the log summarized values from all samples are calculated and subtracted from each of the samples. Additional, the detected outliers were filtered by flags. To eliminate the background noise caused by non-regulated genes before the statistical analysis, a fold-change (FC) cut-off was selected. Hence, to filter obviously non-regulated genes and to identify differentially (from the controls) expressed gene transcripts, a fold-change threshold of
1.1 was applied. Due to the low exposure concentrations below the EC10-value for sub-lethal morphological effects and therefore on average subtle transcriptome changes, a fold-change cut-off >1.1 would have excluded the majority of small but significant changes from the analysis. On the normalized microarray data, analysis of variance (ANOVA) was carried out with a post hoc Tukey’s honestly significant difference (HSD) test, an asymptotic p-value computation and the multiple testing correction of Benjamini Hochberg false discovery rate (FDR). The p-value cut-off was set to the default value of 0.05 for the analysis of the significant genes, as 0.05 is a very popular cut-off value for rejecting the null hypothesis.
2.4.3. Functional analysis
The functional analysis approach was in principal described earlier (Schiller et al., 2013a) and aimed to find regulated Gene Ontology (GO) terms and KEGG pathways (Al-Shahrour et al., 2007). Gene set enrichment analysis was restricted to annotated genes ranked by their corrected p-value, using the logistic model available on the babelomics4 platform (http://v4.babelomics.org). In order to find functionally associated genes, the annotated ranked genes were tested against the zebrafish genome using the logistic model, with the p-value cut- off set to 0.05 analogous to the analysis of the significant genes. Significant Gene Ontology (GO) terms from babelomics4 were run through a SimRel similarity measurement algorithm with an allowed large similarity = 0.9 in REVIGO (http://revigo.irb.hr/revigo.jsp) (Supek et al., 2011), an open source tool that summarizes GO terms by removing redundant and concluding similar terms. In SimRel, the stringency of similarity measurements can be user defined, and in our case we allowed a large similarity for the comparison of different metals. For visualization, the network data were imported in Cytoscape v3.2.0 to modulate all scatterplots to a clustered structure by yFiles Organic Layout. A colour scheme was manually assigned to the network using Adobe Photoshop CS2.
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2.4.4. Real-time quantitative PCR
Real-time quantitative PCR (qPCR) in compliance with the MIQE (The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (Bustin et al., 2009)) guidelines, was used to confirm and validate the microarray data.
The gene transcripts used for the validation were selected from the list of significantly- modulated genes of the cadmium exposure, which showed the strongest overall transcriptome response. Common marker genes of metal and oxidative stress, like metallothionein 2 (mt2), heat shock cognate 70-kd protein, tandem duplicate 1 (hsp70.1) as well as matrix metallopeptidase 9 (mmp9) and matrix metallopeptidase 13a (mmp13a) were chosen. The genes claudin b (cldnb), NK2 homeobox 2a (nkx2.2a), signal transducer and activator of transcription 3 (stat3), ATPase, Ca++ transporting, plasma membrane 1a (atp2b1a) were added due to their involvement in the development of the neuromast cells and motor neurons. As reference genes β-actin 1 (actb1) and ef1-α, like 1 (eef1a1l1) were used, which were both found to be stably expressed across all metal exposures. Primers and the corresponding literature references (if appropriate) are listed in Table 3. Selected primers were screened using the NCBI PrimerBlast tool (http://www.ncbi.nlm.nih.gov/tools/primer-blast) and were analyzed by gradient PCR and qPCR. Microarray RNA samples were transcribed to cDNA and analyzed using an iQ5TM5 real-time PCR cycler (BioRad©, Hercules, USA) and SYBR®GreenER qPCR SuperMix (Invitrogen, Carlsbad, USA). The reference genes were independently of the exposure to the three metals stably expressed. For the PCR amplification, we used 2 min at 50°C and 10 min at 95°C for incubation followed by amplification for 15 s at 95°C and 60 s at 60°C (40 cycles). For each qPCR reaction, three replicate samples of each treatment, taken from the microarray experiments were analyzed, with three technical replicates of each samples run in parallel (n = 9).
The qPCR data were normalized using the two reference genes and analyzed by the comparative delta-delta Ct method (2∆∆Ct) (Livak and Schmittgen, 2001; Pfaffl, 2001; Vandesompele et al., 2002) for a relative quantification of the amplicons. For each metal, the results of the three biological replicates of each concentration were statistically compared to the three ISO control replicates by one-way ANOVA with a Dunnett’s post hoc test.
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Table 3: Primers used for real-time qPCR validation of the microarray results Gene name Accession Primer-Sequence (5'- 3') Size Publication number Bp mmp13a NM_201503 ATGGTGCAAGGCTATCCCAAGAGT 289 Nesan et al. (2012) GCCTGTTGTTGGAGCCAAACTCAA Hillegass et al. (2008) mmp9 NM_213123 AACCACCGCAGACTATGACAAGGA 89 Hillegass et al. GTGCTTCATTGCTGTTCCCGTCAA (2008) hsp70.1 NM_131397 CATCGACGCCAACGGG 191 Gonzalez et al. CCAGGGAGTTTTTAGCAGAAATCTT (2005) mt2 NM_001131053 GCCAAGACTGGAACTTGCAAC 124 Brammell and CGCAGCCAGAGGCACACT Wigginton (2010) Cldnb NM_131763 GAAGGAATTTGGATGAGCTGCGTGG 153 Gallardo et al. CGACAGCATGATTCCCATCAGTCCG (2010) nkx2.2a NM_131422 GGAGGGTTCTGAGGCGACTA 190 TGCGGACGTGTCTTGAGAGT stat3 NM_131479 AGTGAAAGCAGCAAAGAGGGAGGA 106 TGAGCTGCTGCTTAGTGTACGGTT atp2b1a NM_001044757 TTCCGCAGCTCGCTGT 182 Cambier et al. GGAGGTGTAGGGGTCGC (2012) ß-actin 1 NM_131031.1 CGAGCAGGAGATGGGAACC 102 (actb1) CAACGGAAACGCTCATTGC ef1-α, like 1 NM_131263.1 GTGCTGTGCTGATTGTTGCT 201 Craig et al. (2009) (eef1a1l1) TGTATGCGCTGACTTCCTTG
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Effects of metal exposure on motor neuron development, neuromasts and the escape response of zebrafish embryos
Laura Sonnack1,4, Sebastian Kampe2, Elke Muth-Köhne2, Lothar Erdinger3, Nicole Henny3, Henner Hollert4, Christoph Schäfers2, Martina Fenske1
1 Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany 2 Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Schmallenberg, Germany 3Department of Medical Microbiology and Hygiene, Heidelberg University Hospital, Heidelberg, Germany 4Department of Ecosystem Analysis, Institute for Environmental Research, RWTH Aachen University, Germany
This chapter is based on the paper of the same title published in Neurotoxicology & Teratology, Vol. 50, Page 33-42, Jul-Aug. 2015. ______29
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3.1. Abstract
Low level metal contaminations are a prevalent issue with often unknown consequences for health and the environment. Effect-based, multifactorial test systems with zebrafish embryos to assess in particular developmental toxicity are beneficial but rarely used in this context. We therefore exposed wild-type embryos to the metals copper (CuSO4), cadmium (CdCl2) and cobalt (CoSO4) for 72 hours to determine lethal as well as sublethal morphological effects. Motor neuron damage was investigated by immunofluorescence staining of primary motor neurons (PMNs) and secondary motor neurons (SMNs). In vivo stainings using the vital dye DASPEI were used to quantify neuromast development and damage. The consequences of metal toxicity were also assessed functionally, by testing fish behavior following tactile stimulation. The median effective concentration (EC50) values for morphological effects 72 hours post fertilization (hpf) were 14.6 mg/L for cadmium and 0.018 mg/L for copper, whereas embryos exposed up to 45.8 mg/L cobalt showed no morphological effects. All three metals caused a concentration-dependent reduction in the numbers of normal PMNs and SMNs, and in the fluorescence intensity of neuromasts. The results for motor neuron damage and behavior were coincident for all three metals. Even the lowest metal concentrations (cadmium 2 mg/L, copper 0.01 mg/L and cobalt 0.8 mg/L) resulted in neuromast damage. The results demonstrate that the neuromast cells were more sensitive to metal exposure than morphological traits or the response to tactile stimulation and motor neuron damage.
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3.2. Introduction
Metals in the environment arise from natural sources such as erosion, volcanic activity and forest fires (Nriagu, 1989), but also from anthropogenic sources, mainly the processing and manufacturing of metals, the disposal of metal-containing electronic devices (e-waste) and chemical products (e.g. paints), and from agriculture (AMAP, 1998). Metal contamination is a global environmental problem because metals are neither chemically nor biologically degradable and the use of electronic goods and nanomaterials is increasing. Cobalt derivatives are included in the REACH (Directive 1907/2006/EEC) “Candidate List of Substances of Very High Concern for Authorisation” due to their carcinogenic properties, and cadmium is a priority pollutant according to the European Water Framework Directive 2008/105/EC (EWFD). Although several metals are essential for humans and animals, including chromium, iron, cobalt, copper, nickel, vanadium and zinc, because they support vital cell functions, they can still become toxic at higher concentrations. For instance, copper has shown to be highly toxic to aquatic organisms. Juvenile rainbow trout showed an increase in mortality after ten days of exposure starting at 20 μg/L Cu (as CuSO4) as well as accumulation in the gills (Shaw et al., 2012). Daphnia magna as another example, showed at a copper concentration of 0.4 µg/L Cu that the reproduction after 21 days was inhibited (Dave, 1984). Effects like mortality, apoptosis and hair cell death occurred in zebrafish larvae after exposure to copper up to 76 hpf in a concentration range of 1 to 500 µM CuSO4 (0.06 to 31.77 mg/L Cu) (Hernandez et al., 2006; Hernandez et al., 2011; Luzio et al., 2013). In particular developing fish (Jezierska et al., 2009) may be affected by copper bioaccumulation. Cobalt and other metals accumulate in adult zebrafish tissues (Reinardy et al., 2011) and can induce effects like apoptosis and oxidative stress and affect the hatching of zebrafish (Danio rerio) larvae (Cai et al., 2012; Dave and Xiu, 1991).
Many metals have shown to be harmful to fish, and the underlying mechanisms initiating metal toxicity are complex and often not yet fully understood. However, the knowledge of the initiating events causing adverse metal effects is important for a realistic estimation of the hazards associated with exposure of fish to metals at different scenarios and conditions, from acute to chronic. Moreover, the contamination of the environment with diverse metals at trace concentrations, increasingly in nano particulate form, and with metal containing compounds is a growing problem while suitable test methods to effectively monitor and assess metal toxicity in aquatic systems are still scarce. The zebrafish embryo toxicity assay (FET) is a recognized ______31
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alternative for the assessment of fish acute toxicity (OECD test guideline 236). It is also a powerful tool to assess sub-acute effects, when morphological and sub-morphological parameters are combined and included in the assessment (Braunbeck and Lammer, 2006; Scholz et al., 2008; Strähle U. et al., 2012). The FET combines the benefits of a whole organism and vertebrate model system with in-vitro scale properties and animal protection advantages (Busch et al., 2011; Strähle U. et al., 2012). It has shown in numerous studies to be a highly versatile toxicity model which allows the assessment of effects at different levels, from the molecular to the physiological to the organism and even the behavioral in parallel, at short test durations and larger scale (Ali et al., 2011; Truong et al., 2014; Yang et al., 2009). With our study we aimed at exploring the suitability of additional cellular and behavioral endpoints to the FET to improve the evaluation of metal toxicity. Cell or molecule specific fluorescent labels are advantageous as test read-outs because the detection of the fluorescent signals can be computerized and quantified with the help of image processing programs such as ImageJ (Rasband). This reduces the subjectivity of manually assessed endpoints, which rely on variable perceptions and levels of experience of the person conducting the evaluation on the test. Another advantage is the visualization and identification of molecular and cellular targets of toxicants which can specifically be chosen to indicate mechanism of action. Different fluorescence endpoints, such as the staining of apoptotic cells with acridine orange or the TUNEL assay have already been used in zebrafish embryos to measure apoptosis caused by cadmium (Chan and Cheng, 2003; Yu et al., 2012), mercury (Yang et al., 2010), copper (Hernandez et al., 2011) and cobalt (Cai et al., 2012). Muscle fiber development and axon growth have been used as markers for the myotoxic and neurotoxic effects of cadmium (Hen Chow and Cheng, 2003). The disruption of primary motor neuron (PMN) and secondary motor neuron (SMN) development was visualized using specific antibody staining (Sylvain et al., 2010), and accordingly this approach has been used to assess the damage to SMNs in zebrafish embryos 48 h post-fertilization (hpf) following exposure to silver nanoparticles (Muth-Köhne et al., 2013). Another promising approach is the in vivo staining of neuromast hair cells (Froehlicher et al., 2009; Harris et al., 2003; Ton and Parng, 2005; Williams and Holder, 2000) to detect damaging effects to these hair cells as a developmental toxicity endpoint. For example, the light-sensitive fluorescent vital dye 2-(4-(dimethylamino)styryl)-N-ethylpyridinium iodide (DASPEI) can be used to stain mitochondria in living hair cells allowing the visualization of neuromasts and the lateral line organ (Jorgensen, 1989). The neuromasts, which contain mitochondrion-rich mechanosensory cells, reside on the outer surface of the skin and are easily
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accessible by the dye. The neural hair cells share many properties with the hair cells in the mammalian inner ear, including selective susceptibility to ototoxins. A recent study already showed effects of metal nanoparticles on the lateral line and the behavior in zebrafish embryos (McNeil et al., 2014). A combined analysis of motor neuron/neuromast damage and behavioral endpoints can therefore be instrumental in connecting cellular with organism effects because it has been shown that neurons, especially Mauthner cells, mediate specific reactions known as the escape response, startle response or C-start in the goldfish (Carassius auratus) and zebrafish (Eaton et al., 1984; Faber et al., 1989; Liu and Fetcho, 1999; Zottoli, 1977). The Mauthner cells receive information from the lateral line organ and excite motor neurons via the spinal cord, causing contractions of the muscles and thus, the escape reflex.
In this study, we investigated the effects of metal exposure on motor neurons and neuromasts, morphological development and the escape response of wild-type zebrafish embryos. With this approach, it was intended to link cellular, morphological and functional aspects of adverse effects of metal toxicity. Specifically, we examined the toxic effects of cobalt, cadmium and copper by using 72 h FETs in combination with these additional endpoints, to evaluate whether an improvement in the sensitivity to metal exposure can be achieved and to discuss the ecotoxicological significance of the effects observed.
3.3. Material and Methods
For detailed information see Chapter 2: Material & Methods, particularly 2.3 Zebrafish embryo toxicity tests.
3.3.1. Chemicals
Suitable exposure concentrations of copper and cadmium cobalt were selected based on the results of previous FET range-finding experiments. For cobalt, the test concentrations were chosen based on published data (Reinardy et al., 2011; Sylvain et al., 2010) since no concentration-response could be established for morphological effects within the water soluble concentration range. Copper was applied at concentrations of 0.011, 0.014, 0.024, 0.068, 0.152 and 0.364 mg Cu/L, and was chosen because of its known toxicity towards aquatic organisms, e.g. LC50 = 13.82 μM in zebrafish at 4 dpf (Hernandez et al., 2011). Cadmium was applied at concentrations of 2.0, 4.2, 8.9, 18.2 and 34.8 mg Cd/L. Cobalt was applied at concentrations of
0.8, 2.6, 6.4, 16.6 and 45.8 mg Co/L. Ethanol (ROTIPURAN® ≥99.8%, C2H6O, Carl Roth) was
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used as a positive control substance for neurotoxic effects. Concentrations of 1.0, 1.5, 2.0, 2.5 and 3.0% were chosen for the exposure according to the results of previous studies (Muth- Köhne et al. 2012; Sylvain et al. 2010). The antibiotic neomycin (neomycin trisulfate salt hydrate; C23H46N6O13.3H2SO4 x H2O, Sigma-Aldrich) was applied as a positive control for ototoxic effects and used at concentrations of 1.0, 3.16, 10, 31.62 and 100 mg/L. We also used the anti-cancer drug cisplatin (cis-diamineplatinum(II) dichloride; H6Cl2N2Pt, Sigma-Aldrich) at concentrations of 1.0, 2.66, 7.07, 18.8 and 50 mg/L to evaluate hair cell regeneration potential (Mackenzie and Raible, 2012). The exposure concentrations of neomycin and cisplatin were selected according to the results previously performed FET range-finding experiments (data not shown).
3.3.2. Analysis of metals
Metal concentrations in the ISO water solutions used for the tests were quantified by inductively coupled plasma mass spectrometry (ICP-MS) using a Perkin Elmer Elan 6000. All measurements were carried out according to DIN EN ISO 17294-2 (Chen et al., 2004). The instrument was calibrated using at least eight equidistant standard solutions (Merck, Germany). Generally, metals were quantified using the most abundant isotope without isobar or other interferences. All samples were analyzed without any further preparation using an instrument controlled auto sampler. However, samples were diluted if the measured concentrations were outside of the calibration range. The quality of the measurements was confirmed by the analysis of certified reference materials (surface water level 2; SPS, Norway).
To confirm that the concentrations were constant over time, the test solutions were measured at the test start and after 72 h. The total metal concentrations are shown as the means ± standard error of the mean (SEM) of two measurements.
Table 4 shows that the metal concentrations were in the same range at the beginning and end of the test for all three metals, indicating that the solutions were stable over time. The concentrations of copper, cadmium and cobalt were in the same range as the nominal concentrations for all test solutions. The variance between the nominal and empirical concentrations exceeded 20% in some cases, so the results refer to the measured copper, cadmium and cobalt concentrations and are depicted as mean empirical values.
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Table 4: Concentrations of copper (Cu), cadmium (Cd) and cobalt (Co) determined by inductively coupled plasma mass spectrometry (ICP-MS). Concentrations are shown as mean values with the standard error of the mean. Cu (mg/L) Cd (mg/L) Co (mg/L) nominal measured nominal measured nominal measured 0 h 72 h 0 h 72 h 0 h 72 h 0.000 ± 0.000 ± 0.00 ± 0.00 0.0 ± 0.0 ± 0.000 0.000 0.000 0.00 0.00 ± 0.00 0.00 0.00 0.00 0.011 ± 0.011 ± 2.05 ± 2.03 ± 0.78 ± 0.77 ± 0.010 0.000 0.000 2.04 0.01 0.02 0.76 0.02 0.01 0.014 ± 0.014 ± 4.19 ± 4.23 ± 2.43 ± 2.85 ± 0.020 0.002 0.002 3.72 0.04 0.03 2.02 0.03 0.04 0.024 ± 0.024 ± 8.88 ± 8.92 ± 6.52 ± 6.30 ± 0.044 0.001 0.001 6.78 0.14 0.06 5.38 0.03 0.00 0.068 ± 0.068 ± 17.80 ± 18.60 ± 16.20 ± 17.00 ± 0.088 0.001 0.001 12.35 0.70 0.80 14.30 0.40 0.40 0.152 ± 0.152 ± 35.45 ± 34.05 ± 45.75 ± 45.90 ± 0.187 0.000 0.000 22.49 0.45 0.05 38.02 0.45 0.10
3.3.3. Exposure of zebrafish embryos
Due to a lack of morphological effects in the zebrafish embryos after exposure to cobalt in 1:5 diluted ISO water, a supplementary test was performed to investigate a potential carbonate hardness dependent cause. To this end, embryos were exposed to the highest cobalt concentration of 45.8 mg/L using different dilutions of the ISO-standard water as test medium to simulate carbonate hardness conditions. The test solution prepared in 1:5 diluted, undiluted (1-times), 2-times and 4-times concentrated ISO-standard water, representing increasing carbonate hardness between 1° (17.85 mg/L) and 4°dH (89.25 mg/L) (Table 5). A selective increase in the carbonate hardness by an increase of the sodium hydrogen carbonate alone could not be achieved due the resulting intolerable change in the pH-value. The sublethal and lethal morphological effects of 45.8 mg/L cobalt in the different ISO-standard media were assessed after 24, 48 and 72 h.
Table 5: Carbonate-hardness of the different ISO test media Medium 1:5 ISO 1-times ISO 2-times ISO 4-times ISO Carbonate- <17.85 mg/L 53.55 mg/L 71.4 mg/L 89.25 mg/L hardness
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3.4. Results
3.4.1. Morphological effects in zebrafish embryos
The sublethal and lethal morphological effects of the three metals were assessed after 24, 48 and 72 h, as well as for ethanol (the control substance for motor neuron damage) and neomycin/cisplatin (control substances for ototoxicity).
Figure 8: Proportion of 72-hpf embryos displaying morphological effects after exposure to different concentrations of (A) cobalt (Co), cadmium (Cd) and copper (Cu) and (B) control substances (neomycin, cisplatin and ethanol). Bar charts show the concentration- dependent increase in embryos displaying any effect (white bars), and exemplary no hatch embryos (light gray), embryos with edema (darker gray) and coagulated eggs (black). The white bars depict the sum of all recorded effects according to table A1 (appendix), other bars show the predominant morphologic effects coagulation, no-hatch and edema; statistical significance versus control groups tested for “eggs with any effect” (white bars) only (One-way ANOVA with post hoc Dunnett´s test *= p < 0.05, **= p < 0.01, ***= p < 0.001).
Figure 8 shows the results at 72 hpf, whereas Table 6 lists the EC50/LC50 values for 24, 48 and 72 hpf, where these could be determined. The embryos exposed to cobalt (Figure 8 A, left) showed no morphological effects after 72 h at any of the tested concentrations in 1:5 diluted ISO water. Morphological effects after cobalt exposure occurred when in ISO water of higher carbonate hardness was used as test medium. These results can be found in the section 3.4.1.1 Cobalt toxicity related to carbonate hardness. However, exposure to cadmium resulted in a ______36
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concentration-dependent increase in coagulation, up to 90% at the highest concentration of 34.8 mg/L (Figure 8 A, middle). The calculated mean EC50 Cd values remained fairly constant (13.95 mg/L at 24 hpf, 14.68 mg/L at 48 hpf and 14.59 mg/L at 72 hpf), as did the LC50Cd values, which were approx. 1 mg higher (Table 6). Embryos exposed to copper also displayed a concentration-dependent increase in coagulation from 24 hpf (data not shown), but we also observed an additional no-hatch effect at 72 hpf. Exposure to copper at a concentration of 0.014 mg/L already suggested a no-hatch effect (Figure 8 A, right) although this was not significant due to the large deviation among the three biological replicates. The mean EC50Cu values were
0.118 mg/L at 48 hpf and 0.018 mg/L at 72 hpf, with the much lower EC50Cu value at 72 hpf reflecting the no-hatch effect (Table 6). When the metals were compared, copper was found to be the most toxic with the lowest EC50 value of 0.018 mg/L after 72 hpf.
Table 6: Mean EC50 and LC50 values of cobalt, cadmium, copper, neomycin, cisplatin and ethanol with the corresponding 95% confidence intervals for sublethal and lethal morphological effects calculated using probit analysis (ToxRat Professional v2.10, ToxRat Germany).
EC50 LC50 24 hpf 48 hpf 72 hpf 24 hpf 48 hpf 72 hpf Cobalt n.d. n.d. n.d. n.d. n.d. n.d. [mg/L] 13.95 14.68 14.69 15.27 15.58 15.84 Cadmium (Cl 7.25 - (Cl 7.10 - (Cl 6.33 - (Cl 6.79 - (Cl 6.21 - (Cl 5.94 - [mg/L] 36.32) 48.18) 69.16) 72.36) 129.06) 219.55) 0.115 0.118 0.018 0.121 0.124 0.125 Copper (Cl 0.05 - (Cl 0.05 - (Cl 0.01 - (Cl 0.048 - (Cl 0.047 - (Cl 0.050 - [mg/L] 0.53) 0.42) 0.04) 0.550) 0.519) 0.484) Neomycin n.d. n.d. n.d. n.d. n.d. n.d. [mg/L] 3.11 Cisplatin n.d. n.d. (Cl 2.80 - n.d. n.d. n.d. [mg/L] 3.45) 1.34 1.27 1.16 1.87 1.76 1.59 Ethanol (Cl 1.29 - (Cl 1.22 - (Cl 1.12 - (Cl 1.46 - (Cl 1.47 - (Cl 1.4 - [%] 1.39) 1.31) 1.20) 2.22) 2.01) 1.72)
The antibiotic control substance neomycin (Figure 7 B, left) showed no morphological effects after 72 h at all tested concentrations, as seen before for cobalt. Cisplatin-treated embryos also showed no significant morphological effects at 24 and 48 hpf, regardless of the concentration (data not shown). However, the 72 hpf embryos demonstrated a significant no-hatch effect at a concentration of 2.66 mg/L cisplatin (Figure 8 B, middle). At 24 and 48 hpf, an EC50Cis could not be determined because there were no morphological effects, but after 72 hpf the calculated ______37
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mean EC50Cis was 3.11 mg/L (Table 6). We were unable to determine the LCx because only sublethal morphological effects were observed. Zebrafish embryos exposed to ethanol showed a concentration-dependent increase in sublethal and lethal effects such as edema and coagulation from 24 hpf. Furthermore, many embryos did not hatch until 72 hpf, as was observed also for the copper and cisplatin exposure. Even at the lowest concentration of 1% ethanol was sufficient to induce a significant increase of morphological effects (Figure 8 B, right). The calculated mean EC50Ethanol values reduced over time, with 1.34% at 24 hpf and
1.16% at 72 hpf, and the LC50Ethanol value at 72 hpf was 1.59% (Table 6). Because there was 100% coagulation in embryos treated with the highest concentrations of copper (0.364 mg/L), cadmium (34 mg/L) and ethanol (2.5% and 3%), it was not possible to measure motor neuron/neuromast defects or behavior in these treatments.
3.4.1.1. Cobalt toxicity related to carbonate hardness
Figure 9: Proportion of 72-hpf embryos displaying morphological effects after exposure to cobalt at a concentration of 45.8 mg/L in different ISO-water. Bar charts displaying any effect (white bars) and no hatch embryos (light gray); statistical significance versus control groups tested for “eggs with any effect” (bars) only (One-way ANOVA with post hoc Dunnett´s test *= p < 0.05, **= p < 0.01, ***= p < 0.001).
Whereas the embryos exposed to cobalt in 1:5 diluted ISO showed no morphological effects after 72 h at any of the tested concentrations (see Figure 8 A, left), a significant increase in morphological effects were seen in 72 hpf zebrafish embryos exposed to cobalt in 2- and 4- times concentrated ISO (Figure 9). However, the significant increase in the overall effect rate
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was attributed to a no-hatch effect occurring from a carbonate hardness of 71.4 mg/L (2-times concentrated ISO).
3.4.2. Effects on motor neuron development
Zebrafish embryos exposed to all three metals were characterized by lower numbers of normally developing PMNs (Figure 10, A) and SMNs (Figure 10, B) at high concentrations. For cobalt-treated embryos, the reduction was significant for PMNs (Figure 10 A, left) and SMNs (Figure 10 B, left) at the highest concentration of 45.8 mg/l. For cadmium-treated embryos, the effects on both parameters were significant already at 8.9 mg/L (Figure 10, middle). PMNs were not significantly affected in copper-treated embryos, but an adverse effect on SMNs was already significant at a concentration of 0.024 mg/L (Figure 10 A and B, right). In the other treatments, significant effects on SMNs and PMNs were detected at the same exposure concentrations. The motor neuron effects of all three metals included moderate to severe defects, from excessively branched and truncated axons to axons innervating neighboring myotomes at the two highest concentrations (see images of Figure 10 A and B, orange arrows). Furthermore, weakly developed or missing SMNs were frequently observed towards the distal ends of the tail region. This effect was considered mild and suggests a delayed development of the motor neurons. Ethanol-treated embryos (positive controls) showed a significant reduction in the number of normal motor neurons at the lowest concentration of 1% (Figure 13), and certain severe effects were also observed, such as truncation of the axons.
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Figure 10: Representative inverted fluorescent images of stained (A) primary motor neurons (PMN) and (B) secondary motor neurons (SMN) in control embryos and embryos treated with cobalt (Co), cadmium (Cd) and copper (Cu). Arrows point to abnormal PMNs and SMNs which are branched, truncated or innervate into neighboring axons. Bar charts show the concentration-dependent reduction in the proportion of normally- developed motor neurons (white bars) and the increase in the proportion of motor neurons with minor (light gray), moderate (darker gray) and severe (black) defects; statistical significance versus control groups tested for “normally-developed motor neurons” (white bars): (One-way ANOVA with post hoc Dunnett´s test, 3 independent experiments with 5-6 individual embryos; 8-9 motor neurons per embryo *= p < 0.05, **= p < 0.01, ***= p < 0.001)
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3.4.3. Neuromast damage
Neuromast damage was analyzed to measure the disruption of the hair cells of the lateral line. Figure 11 shows fatal effects after 72 h.
Figure 11: (A) Representative inverted fluorescent images of stained neuromasts in control embryos and embryos treated with cobalt (Co), cadmium (Cd) and copper (Cu). The green arrows show five normally fluorescent neuromasts and the orange arrows affected neuromasts expressing weaker or no fluorescence. (B) Relative fluorescence intensity (%) of stained neuromasts in 72-hpf embryos after exposure to cobalt (Co), cadmium (Cd) and copper (Cu); statistical significance versus control groups: (One-way ANOVA with post hoc Dunnett´s test; n = 75 – 90 of 3 independent experiments with 5-6 individual embryos and 5 neuromasts measured per embryo *= p < 0.05, **= p < 0.01, ***= p < 0.001)
A concentration-dependent reduction in the fluorescence intensity was clearly observed for all three metals (Figure 11), and significant effects were observed already at the lowest treatment concentration of copper and cadmium respectively the second lowest of cobalt (2.6 mg/L). The highest reduction in fluorescence intensity was seen in the cadmium-treated embryos, where the intensity dropped to less than 30% across all concentrations (Figure 11 B, middle), although measurements were not possible at the highest concentration (34.8 mg/L) due to the extent of coagulation (>85%). In copper-treated embryos, the fluorescence intensity was significantly ______41
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reduced at the lowest concentration to ~70% compared to the control group (Figure 11 B, right). Between the lowest concentration (0.011 mg/L) and the next higher concentration (0.014 mg/L), there was no effect variation. The positive control substances neomycin and cisplatin induced a substantial and significant reduction in the fluorescence intensity of neuromasts, starting at 3.16 mg/L neomycin with 20% fluorescence intensity and 2.66 mg/L cisplatin with a fluorescence intensity of approximately 35% compared to the control (Figure 13).
3.4.4. Behavioral effects
In addition to the motor neuron and neuromast damage, we also considered the escape behavior of the embryos after tactile stimulation. The 72-hpf embryos exposed to cobalt displayed a slightly reduced escape response, which was significant at the highest concentration of 45.8 mg/L (Figure 12, left).
Figure 12: Tactile stimulation response assay at 72 hpf after exposure to cobalt (Co), cadmium (Cd) and copper (Cu). Bar charts show the concentration-dependent reduction in the normal escape response (white bars) and an increase in a reduced escape (light gray), nearly no escape (darker gray) and no escape (black) after touch; statistical significance versus the control groups was tested for “normally escape response” (white bars): (One-way ANOVA with post hoc Dunnett´s test; n = 36 per treatment of 3 independent experiments with 12 individual embryos *= p < 0.05, **= p < 0.01, ***= p < 0.001).
This effect threshold was consistent with the motor neuron damage (Figure 10), but lower than for the damage to neuromasts (Figure 11). In cadmium-treated 72-hpf embryos, exposure to concentrations of 18.2 mg/L affected the escape response which was indicated already at 8.9 mg/L. (Figure 12, middle). First effects of cadmium on motor neurons were seen at the same concentration whereas neuromast damage occurred only at 2.0 mg/L. The copper-treated embryos showed a significant reduction in the normal escape response at 0.024 mg/L (Figure 12, right). The lowest observed effect concentration (LOEC) of copper for the behavioral ______42
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endpoint did not differ from the morphological effects (Figure 8 A). Copper induced motor neuron (SMN) and neuromast damage instead became significant already at the lower concentration of 0.011 mg/L. Neomycin and cisplatin were used as positive control substances for the neuromast damage test, and these substances also induced a significant concentration- dependent reduction in the tactile stimulus response, starting at 10 mg/L neomycin and 2.66 mg/L cisplatin (Figure 13).
Figure 13: (A) Effects of the control substance ethanol on primary motor neurons (PMN) and secondary motor neurons development (SMN) at 48 hpf; (B) relative fluorescence intensity (%) of stained neuromasts and (C) tactile stimulation response in 72-hpf embryos after exposure to neomycin and cisplatin. Statistical significance versus the control groups was tested for normal-developed motor neurons (A), fluorescence intensity (B) and normal escape response (C): (One-way ANOVA with post hoc Dunnett´s test *= p < 0.05, **= p < 0.01, ***= p < 0.001)
3.5. Discussion
Since many mechanisms of metal toxicity in fish remain to be unraveled, it is difficult to fully evaluate the adverse outcome of metal exposure based on the read outs of conventional fish tests and existing knowledge. We used the zebrafish embryo toxicity test (zFET) to integrate mechanistic and functional aspects of subacute metal toxicity with teratogenicity. Hence, the scope of the existing test was extended by the phenotypic endpoints motor neuron and neuromast damage and behavioral impairment. Whether this approach could indicate adverse outcomes of metal toxicity and increase the explanatory power of the zFET was explored for copper, cadmium and cobalt.
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Cobalt did not induce any detectable morphological effects in 72-hpf zebrafish embryos even at the highest concentration of 45.8 mg/L (Figure 8 A, left). In comparison, cobalt at concentrations greater than 10.8 mg/L in water (100 mg/L CaCO3) was previously reported to inhibit hatching in 72-hpf zebrafish embryos (Dave and Xiu, 1991) and even 0.1 mg/L cobalt was sufficient to inhibit hatching when Hank’s solution was used as the medium (Cai et al., 2012). The absence of this effect in our investigation may therefore be medium-dependent because we used cobalt dissolved in 1:5 diluted ISO water (<17,85 mg/L CaCO3), which has a much lower carbonate hardness and ionic strength than the media used in the other studies. In a supplementary zebrafish embryo tests we were able to demonstrate a significant increase in the no-hatch effect at the highest cobalt concentration of 45.8 mg/L when a higher concentrated ISO water of a carbonate-hardness up to 89.25 mg/L was used (Chapter 3.4.1.1 Cobalt toxicity related to carbonate hardness; Table 5; Figure 9). These findings clearly strengthen the hypothesis of test medium-dependent cobalt toxicity. Nonetheless, cobalt affected the embryo´s escape response at 72 hpf when applied at the highest concentration of 45.8 mg/L in 1:5 diluted ISO water (Figure 12, left). This correlated with the effect on motor neurons, because both effects became significant starting at the same concentration. It is possible that the observed motor neuron damage reduced the innervation of tail muscles, and subsequently inhibited the essential muscle contraction required for the escape response. There have been no previous reports of motor neuron damage or escape response inhibition in zebrafish embryos or larvae caused by cobalt exposure, therefore no data were available for comparison. The reduction in fluorescence intensity of the neuromasts following cobalt exposure has not yet been reported either. This effect was seen at cobalt concentrations of ≥ 2.6 mg/L (Figure 11, left). A slight but non-significant reduction in fluorescence was observed already at 0.8 mg/L of cobalt, which we suggest implied at least partial damage to the neuromast hair cells. Regarding the significantly reduced fluorescence at higher concentrations, an almost complete destruction of the hair cells can be assumed. Cobalt exposure has been shown to inhibit rheotaxis in the African clawed frog (Xenopus laevis), suggesting the lateral line organ is affected and by extension the neuromasts which are its main functional units (Simmons et al., 2004). An adverse effect of cobalt on neuromasts was reported by Karlsen and Sand (1987), who demonstrated toxicity to neuromast cells in another freshwater fish species, the roach (Rutilis rutilis) starting at a concentration of 5.98 mg/L (0.1 mmol/L). In order to evaluate the potential environmental implications of the cobalt-specific effects on neuromasts, our results were compared to the predicted no effect concentration (PNEC) and EC50 values of the European Chemical Agency
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(ECHA). The PNEC for cobalt in aquatic freshwater organisms of 0.51 µg/L, reflects a higher sensitivity of other aquatic organisms than fish towards cobalt. The EC50 values of cobalt for different fish species range from 9.1 to 88.7 mg/L. Our results showed that cobalt causes neuromast damage already at 2.6 mg/L, with a tendency toward even lower concentrations since the mean fluorescence of the neuromast cells was 30 % lower than in the control fish even at 0.8 mg/L.
Cadmium-exposed embryos showed a concentration-dependent increase in coagulated eggs (Figure 8 A, middle), reaching a mortality rate of nearly 90% at the highest cadmium concentration of 34.8 mg/L (309 μM). This drastic effect was expected because cadmium toxicity is well-known in zebrafish. For example, Blechinger et al. (2007) (Blechinger et al., 2007) reported 100% mortality at a cadmium concentration of 125 μM in water (14.1 mg/L) during a 96-h acute test with 3-dpf zebrafish larvae. Fraysse et al. (2006) (Fraysse et al., 2006) reported a 20% no-hatch rate in 80-hpf zebrafish embryos exposed to cadmium at concentrations of 3.3 μM (0.37 mg/L) and 13.3 μM (1.5 mg/L). As previously also discussed for cobalt, we did not observe a cadmium-dependent effect on hatching in our test, nor did we see any other morphological effects besides coagulation. This deviation from the published data may have been caused by the different design of the exposure experiment, or occurred (as discussed for cobalt) due to the use of a medium with a lower ionic strength. An increase in apoptosis, which was shown by Chan and Chang (2003), may have contributed to the lethality, although Chan and Chang 2003 did not describe any mortality after 23 h exposure to 100 µM of cadmium (Chan and Cheng, 2003). Ectopic apoptosis mostly occurred in malformed tissues, what was not observed in the present study. Alsop and Wood (2011) studied the acute toxic mechanisms of cadmium in adult and larval zebrafish and found that mortality was related to a sharp decrease in whole body Na+ due to diffusive ion loss, and it may be speculated that this has also been the case for the cadmium exposed embryos of the present study (Alsop and Wood, 2011).
For cadmium exposure in water, we identified neuromast damage as the most sensitive endpoint as was the case for cobalt. Neuromast damage in 72-hpf zebrafish embryos was already statistically significant at the lowest test concentration of 2.0 mg/L (17.8 μM) (Figure 11, middle), and the hair cells were almost completely eliminated at higher cadmium concentrations. There have been no comparable studies testing the impact of cadmium on zebrafish neuromast cells, but the neuromasts and lateral line of juvenile sea bass ______45
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(Dicentrarchus labrax) were shown to be damaged at a cadmium concentration of 5 μg/L (Faucher et al., 2006). We also found that the escape response was only slightly less sensitive (18.2 mg/L) than the endpoints PMN and SMN (8.9 mg/L). As suggested earlier, this may indicate that motor neuron damage directly influences the swimming behavior of the larvae, although this remains to be confirmed. The calculated EC50 values of cadmium were in the same range as those reported for other fish species (0.75–6.47 mg/L, http://echa.europa.eu). The PNEC for cadmium in aquatic freshwater organisms is 0.19 µg/L and suggests a higher sensitivity of other aquatic organisms than fish also in the case of cadmium.
At 72 hpf, a no-hatch effect was also observed for copper, starting at a concentration of 0.014 mg/L (Figure 8 A, right) and becoming significant at concentrations of ≥ 0.024 mg/L. Reduced hatching success was similarly observed by Johnson et al. (2007) in embryos exposed to 0.050 mg/L copper for 72 h. One possible explanation for the no-hatch effect might be a missing hatch reflex due to neuronal defects. Hatching would normally occur between 48 and 72 hpf and results from a stroke of the tail of the embryo, which ruptures the chorion. Another reason could be damage to the hatching gland, which produces the enzyme chorionase required to digest the chorion. Subsequently, the weakened chorion can easily be ruptured by a blow from the embryo’s tail (Willemse and Denuce, 1973). It has been postulated that copper inhibits the secretion or activity of chorionase in rainbow trout (Hagenmaier, 1974). It is possible that metal ions directly interfere with the activity of chorionase because it is a metalloprotease or there may be a combination of enzymatic and mechanical mechanisms (Johnson et al., 2007). However, we observed thinning of the chorion during our manual dechorionation procedure suggesting that the activity of the enzyme was probably not affected in a significant manner. The more likely hypothesis is that copper exposure reduced the motility of the embryos by inhibiting signal transduction in the nervous system, e.g. between the sensory neurons (hair cells) and motor neurons innervating the myotome. Damage to the SMNs occurred at the same concentration than the no-hatch effect (0.024 mg/L), and suggests that the reduced hatching success might be related to a lower mobility of the embryo due to interrupted muscle innervation. This suggestion is supported by the observation of reduced movement of the 72- hpf embryos following tactile stimulation, starting at a copper concentration of 0.024 mg/L (Figure 12, right). It also corroborates our hypothesis that motor neuron damage may have interrupted the innervation of the myotome, reducing the escape response and likewise the hatch reflex. We also observed effects on neuromast hair cells at the lowest copper concentration of 0.011 mg/L, suggesting this as the most sensitive endpoint (Figure 11, right). This sensitive ______46
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response was anticipated because Johnson et al. (2007) reported a 50% reduction in the number of visible neuromasts in zebrafish embryos treated with 0.068 mg/L copper. Our results are in the same range of the PNEC for copper in aquatic freshwater organisms (7.8 µg/L). We observed a significant effect on neuromast development at a copper concentration of 11µg/L, which is the lowest concentration we tested.
In conclusion, the additional FET endpoints evaluated in this study revealed potential links between effects of waterborne metal exposure on gross development and motor neuron development, neuromast damage and escape response. The most evident coherence for all three metals was found between PMN/SMN damage and the reduced response to tactile stimulation. Both effects were also in agreement with the no-hatch effect in embryos exposed to copper. The absence of this effect in the cadmium or cobalt exposed embryos could have been medium- dependent because a no-hatch effect was previously observed for cobalt at comparable concentrations but in media of a higher ionic strength than the five-times diluted ISO medium used for all the tests of the present study. Even though this observation substantiates the hypothesis that the absence of the no-hatch effect may be medium-related, the reasons still need to be investigated. Our data indicate that the motility-related effects (i.e. hatch and tactile stimulus response) may reflect the consequences of neuronal damage to PMNs and SMNs. However, the tactile stimulation assay and the motor neuron damage could not verify the functional consequences of neuromast damage, because motor neurons are only indirectly connected to the lateral line organ, via neural circuits. The lateral line organ controls rheotaxis and therefore a rheotaxis assays with ≥ 5-dpf embryos would be more suitable to assess the functional consequences directly linked to neuromast damage. Tests on embryos ≥ 5-dpf, however, entail the use of protected animals which contradicts one of the main benefits of the FET. The consideration of alternative behavioral assays using younger developmental stages should be pursued, and modifications of already available locomotor test (Levin et al., 2004; Selderslaghs et al., 2010) appears to be a promising approach in this context.
For the three metals tested in this study, the results demonstrate that neuromast damage was the most sensitive endpoint of the zebrafish FET when compared to morphological effects, hatching, motor neuron damage and the escape response following tactile stimulation. However, by applying these different assessment methods in parallel, a more comprehensive understanding of metal toxicity was achieved. The motor neuron damage effect was coherent with the effects on hatching and the escape response, which suggests that the assumed loss of ______47
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muscle contraction in the tail as the potential cause of the no-hatch effect might at least be partly related to impaired tail muscle innervation. This effect was shown for all three metals, implying a similar mechanism of action on motor neuron development. Therefore, it would be important to test other metals to see whether these results can be confirmed and whether other metals also cause neuromast damage. Neuromast damage could be linked to an ototoxic effect of the corresponding metal and thus, the assay would potentially be suitable to also screen drugs for ototoxicity and otoprotection. In conclusion, we showed that neuromast damage is a sensitive and informative endpoint for metal toxicity in the FET. The fluorescent staining of the neuromast cells also enables an objective assessment method because the fluorescence intensity can be measured using automated imaging procedures rather than subjective judgment. The classification of the motor neuron defects based on a simple four level scoring, on the other hand, is prone to variation depending on the experience and subjectivity of the person conducting the assessment. We verified that the results of the motor neuron damage assessments were reproducible but this required the performance of the repeated assessments by the same person. Nevertheless, the immunofluorescent staining of motor neurons proved to be a simple hence sensitive method to visualize, locate and score neurodevelopmental damage at cell morphological level. The low objectivity of this method could be improved with the application of automated, computer based analysis programs and the inclusion of a measurable parameter like the axon length.
Overall, the integration of cellular and functional endpoints with developmental morphology in the context of the FET increased the informative value compared to the assessment of metal toxicity using the conventional FET endpoints only. However, even though the results of this study show that the fish embryo toxicity test has the potential to be used as an alternative screening assay for metal toxicity, it was also revealed that environmental parameters, like water hardness, affect the bioavailability of metals and require specific adjustments to the standard FET procedures. The variety of feasible molecular, cellular and organism endpoints which can potentially be integrated to enhance the FET for metal toxicity evaluations provide numerous possibilities for application in outcome pathway based approaches.
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Acknowledgement
This work was partially supported by the Fraunhofer Gesellschaft (FhG) internal programs by a research grant No. Attract 692 093 and by a PhD-Scholarship of Laura Sonnack (Doktorandinnenprogramm Fraunhofer). We would like to thank Dr. Richard Twyman for his support in editing the manuscript.
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Chapter 4
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Comparative analysis of the transcriptome responses of zebrafish embryos after exposure to low concentrations of cadmium, cobalt and copper
Laura Sonnack1,4, Thorsten Klawonn2, Ralf Kriehuber3, Henner Hollert4, Christoph Schäfers2, Martina Fenske1
1 Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany 2 Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Schmallenberg, Germany 3 Department of Safety and Radiation Protection, Forschungszentrum Jülich, Germany 4Department of Ecosystem Analysis, Institute for Environmental Research, RWTH Aachen University, Germany
This chapter is based on the paper of the same title published in Comparative Biochemistry and Physiology - Part D: Genomics and Proteomics, Vol. 25, Page 99-108, December 2017. ______51
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4.1. Abstract
Metal toxicity is a global environmental challenge. Fish are particularly prone to metal exposure, which can be lethal or can cause sublethal physiological impairments. The objective of this study was to improve our understanding on how adverse effects of essential and non- essential metals in early life stage zebrafish may be explained by changes in the transcriptome after exposure to non-toxic levels. We therefore studied the effects of three different metals at low concentrations in zebrafish embryos by transcriptomics analysis. The study design compared exposure effects caused by different metals at different developmental stages (pre- hatch and post-hatch). Wild-type embryos were exposed to solutions of low concentrations of copper (CuSO4), cadmium (CdCl2) and cobalt (CoSO4) until 96 h post-fertilization (hpf) and microarray experiments were carried out to determine transcriptome profiles at 48 and 96 hpf. We found that the toxic metal cadmium affected the expression of more genes at 96 hpf than 48 hpf. The opposite effect was observed for the essential metals cobalt and copper, which also resulted in the enrichment of different GO terms. Genes involved in neuromast and motor neuron development were significantly enriched, agreeing with our previous results showing motor neuron and neuromast damage in the embryos. Our data provide evidence that the response of the transcriptome of fish embryos to metal exposure differs for essential and non- essential metals.
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4.2. Introduction
Metal contamination is a global environmental challenge because metals are neither chemically nor biologically degradable so they persist once they have entered the environment. In addition to natural sources of metals, anthropogenic sources metal-containing consumer products and metal nanoparticles add to the burden (AMAP, 1998). Millions of tons of electronic waste materials containing metals such as cadmium, copper, chromium, silver, nickel and cobalt end up in the environment every year (Robinson, 2009). Metals leach from landfills and to a much larger degree, become remobilized from sediments, e.g., during flooding events (Redelstein et al., 2015) and enter the aquatic environment, where they harm aquatic organisms. Fish are prone to metal toxicity, which can be lethal or cause sublethal effects including developmental impairments. The molecular basis of these adverse effects is not yet understood in detail and few studies have been carried out to determine the mechanisms of metal toxicity in fish.
Environmentally important metals such as copper have been studied extensively due to the high toxicity to aquatic organisms like Daphnia spp. and fish. For example, hair cell death has been studied in the lateral line neuromasts of 76 hpf zebrafish embryos exposed to copper (George et al., 2006; Hernandez et al., 2011). The hsp70.1 promoter was shown to mediate a tissue- specific stress response in the presence of waterborne copper (Hernandez et al., 2011). Cadmium is also an environmental priority metal according to the European Water Framework Directive 2008/105/EC (EWFD) and has been shown to cause lethal effects in 48h zebrafish embryos (LC50 range of 5.5 to ~30 mg/) (Hallare et al., 2005; Weil et al., 2009) and to affect their hatching at < 0.2 µM (Fraysse et al., 2006). The commitment of neural progenitor cells is inhibited during brain development in zebrafish embryos concomitant with the regulation of the neurogenic genes ngn1 and neuroD (Chow et al., 2008). More recently, the importance of cobalt has increased because it is regarded as a potential carcinogen according to REACH (directive 1970/2006/EEC) despite its low general toxicity. In Chapter 3 “Effects of metal exposure on motor neuron development, neuromasts and the escape response of zebrafish embryos”, we found that exposure to cobalt, cadmium and copper affected the neuromast cells of the lateral line organ of zebrafish embryos (Sonnack et al., 2015). In order to improve our mechanistic understanding of the observed effects, we combined this analysis of toxicity with transcriptomics data. We have demonstrated in earlier studies that gene expression analysis can help determine underlying mechanisms of toxicity (Bluhm et al., 2014; Schiller et al., 2013b; Turner et al., 2012). Copper is known to affect neuromasts, and transcriptomics analysis of the ______53
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inner ear of one-year-old zebrafish showed that the stat3 and socs3 pathway is involved, and is important for hair cell regeneration (Liang et al., 2012).
Cadmium toxicity in common carp involves the beclin 1 gene (Gao et al., 2014). The effect of cadmium exposure on gene expression in different organs of adult zebrafish after 7 and 21 days revealed that mt1, mt2 and c-jun were upregulated in the brain after 21 days, and that the hsp70.1 gene, which is a marker of oxidative stress responses, was expressed in gills (Gonzalez et al., 2006).
Despite these numerous studies, there has been no comparative transcriptome-wide analysis of exposure to different metals at different time points. We therefore investigated the molecular basis of metal toxicity on a broader scale by applying transcriptomics analysis in wild-type zebrafish embryos at different developmental stages (pre-hatch and post-hatch) following exposure to three different metal solutions: copper (CuSO4), cadmium (CdCl2) and cobalt
(CoSO4). Specifically, we used the zebrafish embryo toxicity test to study metal toxicity during very early developmental stages and extended the scope of the assay by including transcriptome analysis endpoints. The zebrafish embryo toxicity test is used as a regulatory test for acute toxicity and complies with the principles of the 3Rs of replacement, reduction and refinement of animal tests (Russell et al., 1959). This approach has many advantages including its simplicity, convenience, and short duration, the small size of the eggs, the rapid embryonic development of zebrafish and the transparency of the chorion, to facilitate observation. The zebrafish genome is also completely sequenced, which facilitates genetic and genomic analysis (Busch et al., 2011).
4.3. Materials and Methods
For detailed information see Chapter 2: Material & Methods, particularly 2.4. Gene transcription analysis. The microarray data from this article have been deposited in the NCBI Gene Expression Omnibus under the accession number GSE80957.
4.3.1. Chemicals
The exposure concentrations of copper, cadmium and cobalt were selected based on the lowest observed effect concentration (LOEC) for neuromast damage and were below the EC10 value for sublethal morphological effects as determined in Chapter 3 “Effects of metal exposure on motor neuron development, neuromasts and the escape response of zebrafish embryos” ______54
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(Sonnack et al., 2015). Thus, cadmium was applied at a nominal concentration of 4.2 mg Cd/L (measured 3.3 mg Cd/L), cobalt at a nominal concentration of 6.4 mg Co/L (measured 3.6 mg Co/L) and copper at a nominal concentration of 11.0 µg Cu/L (measured 6.1 µg Cu/L).
4.3.2. Analysis of metals
Metal concentrations were analyzed by inductively coupled plasma optical emission spectrometry (ICP-OES) using an Agilent 720 instrument. Commercially available metal ICP standard solutions (Merck, Darmstadt, Germany) were used to prepare appropriate stock solutions and subsequently calibration solutions. All calibration standard solutions and samples were acidified (nitric acid, Rotipuran® quality, Carl Roth, Darmstadt) for stabilization (e.g. as suggested in ISO 11885:2007 and were diluted to a target concentration of approximately 0.5
M HNO3. The method was validated by the analysis of certified reference water TMDA-53.3 (certified for Cu, Cd and Co by Environment Canada) and the multi-element standard IV (Merck) alongside experimental samples. The recovery of recalibration samples was in the range of 100 ± 15%.
For the determination of dissolved metal concentrations in experimental samples, two series of measurements were taken at different wavelengths. The first series used 226.502 nm for Cd, 238.892 nm for Co and 324.754 nm for Cu, whereas the second series used 214.439 nm for Cd, 235.341 nm for Co and 327.395 nm for Cu. The limits of detection (LOD) and quantification (LOQ) were calculated for each series prior to the measurement of samples according to DIN 32645:2008-11 and Geiss and Einax (Geiss and Einax, 2001). The LODs were 0.010–0.031 µg Cd/L, 0.400–0.719 µg Co/L and 0.274–0.821 µg Cu/L. The corresponding LOQs were 0.031– 0.686 µg Cd/L, 1.200–2.156 µg Co/L and 0.821–1.255 µg Cu/L.
The concentrations of the stock and test solutions for cadmium, cobalt and copper were determined by ICP-OES and the results are shown in Table 7.
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Table 7: Concentrations of cadmium, cobalt and copper determined by inductively coupled plasma optical emission spectrometry (ICP-OES) Stock solution Nominal Measured Cadmium 306.6 mg/L 275.0 mg/L Cobalt 304.2 mg/L 216.4 mg/L Copper 19.91 mg/L 14.06 mg/L
Nominal Measured Test solution 0 h 48 h 96 h Cadmium 4.2 mg/L 3.3 mg/L 3.1 mg/L 3.3 mg/L Cobalt 6.4 mg/L 3.6 mg/L 3.6 mg/L 3.8 mg/L Copper 11.0 µg/L 6.1 µg/L 1.1 µg/L 7.9 µg/L
For cadmium, the measured concentration of the stock solution showed a deviation of 10% from nominal concentration. In the test solutions, the measured concentrations of 3.1 to 3.3 mg/L deviated by up to 26% from the nominal concentration. However, the test solution concentrations were stable over the exposure time of 96 h. For cobalt and copper, the nominal and measured concentrations of the stock solutions differed by up to 29%. The maximum deviation from nominal in the test solution concentrations at 96 h was 41% for cobalt and 28% for copper. As with cadmium, the cobalt test solution concentration was stable over time. For copper, the test solution concentration at the start of exposure (0 h) was 6.1 µg/L, which was 56% of nominal. We observed a further decrease in the concentration of the test solutions to 10% of nominal at 48 h. After renewing the test solution after 48 h, the concentration decreased less sharply to 72% of nominal at 96 h.
Overall, the deviation between the nominal and empirical concentrations exceeded 20% in some cases, in particular copper. All results are shown in relation to the measured concentrations at test start (0 h), i.e. 3.3 mg/L for cadmium, 3.6 mg/L for cobalt and 6.1 µg/L for copper.
4.4. Results
4.4.1. Morphological effects
A detailed description of the morphological effects after exposure to the different metals at different concentrations can be found in Chapter 3 “Effects of metal exposure on motor neuron development, neuromasts and the escape response of zebrafish embryos” especially 3.4.1 Morphological effects in zebrafish embryos Figure 8 and Table 4 (Sonnack et al., 2015). Briefly, cadmium-treated zebrafish embryos showed a concentration-dependent increase in mortality (coagulation) with a calculated mean EC10 at 72 hpf of 4.2 mg/L. Significant damage ______56
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to the neuromasts was observed at ≥ 2.0 mg/L (LOEC). Embryos exposed to copper displayed a concentration-dependent increase in coagulation from 24 hpf, but we also observed a no-hatch effect after 72 hpf. The calculated mean EC10 (morphology) for copper at 72 hpf was 12 µg/L and the LOEC for neuromast damage was 11 µg/L. Zebrafish embryos exposed to cobalt showed no morphological effects up to a concentration of 45.8 mg/L whereas neuromast defects were significant at 2.6 mg/L.
4.4.2. Microarray analysis
The Venn diagrams in Figure 14 show zebrafish genes with significant differences in expression levels at 48 hpf (gray circle) compared to 96 hpf (green circle) after exposure to 3.3 mg Cd/L, 3.6 mg Co/L or 6.1 µg Cu/L. Embryos exposed to cadmium also showed more genes differentially regulated at 96 hpf compared to 48 hpf, whereas the opposite effect was observed in embryos exposed to cobalt or copper.
Cadmium Cobalt Copper (non-essential) 48 hpf 96 hpf 48 hpf 96 hpf 48 hpf 96 hpf
100 11 357 30 1 17 165 0 9
Figure 14: Venn diagrams representing zebrafish genes differentially expressed at 48 hpf (gray circle) and 96 hpf (green circle) after exposure to 3.3 mg Cd/L, 3.6 mg Co/L and 6.1 µg Cu/L compared to the control groups. The fold change cutoff was set to 1.1 and statistical significances were determined by ANOVA with a post hoc Tukey’s test and Benjamini Hochberg multiple corrections (p-value cutoff 0.05).
For cadmium, 111 genes were differentially expressed in 48 hpf embryos (Figure 14, left), including 11 that were also differentially expressed at 96 hpf. The common set of differentially expressed genes comprised mt2, hsp70.1, hsp70.1l, cldnf, fkbp5, hsp90aa1.2, si:ch211-157c3.4, si:dkey-226m8.7 and si:dkey-92i15.4 (descriptions of all significant genes can be found in the Supplements D; List of significant differentially expressed genes). For cadmium, 357 genes were differentially expressed in 96 hpf embryos, more than threefold the number observed in 48 hpf embryos (Figure 14, left). In 48 hpf zebrafish embryos exposed to cobalt, 31 genes were differentially expressed (Figure 14, middle), whereas only 18 were differentially expressed at 96 hpf (Figure 14, middle). One gene involved in metal ion binding (ca15a, carbonic anhydrase ______57
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XV a), was differentially expressed at both time points. In 48 hpf zebrafish embryos exposed to copper, 165 genes were differentially expressed (Figure 14, right) but only nine were differentially expressed at 96 hpf and none of these were differentially expressed at both time points (Figure 14, right).
The results of the GO and KEGG enrichment analysis are displayed as heat maps (Figure 15), which represent all differentially expressed genes involved in biological processes in 48 hpf (Figure 15 A) and 96 hpf (Figure 15 B) zebrafish embryos.
Figure 15: Heat maps representing GO and KEGG enrichment analysis, showing the involvement of all differentially expressed genes in biological processes in (A) 48 hpf and (B) 96 hpf zebrafish embryos and (C) KEGG pathways. Pathways are shown and grouped if they were found to be regulated under two or more conditions (different time points and metals). Upregulation (yellow) and downregulation (blue) are indicated by shading representing log10 p-values. For this functional analysis, the fold change cutoff was set to 1.1 and gene set enrichment was performed using a logistic model (p-value cutoff = 0.05).
The maps only show the GO terms that were significant under at least two exposure conditions and metals. For zebrafish embryos exposed to cadmium and copper, genes related to biological process GO terms were mostly upregulated whereas for cobalt most GO terms indicated downregulation (Figure 15). In 48 hpf embryos, genes involved in processes related to central
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nervous system, eye, sensory organ and whole embryo development were differentially regulated by all three metals (upregulated by cadmium and copper but downregulated by cobalt). Furthermore, genes representing biological processes such as biosynthesis, response to xenobiotic stimuli and transcription were regulated by all three metals (Figure 15 A). In the 48 hpf embryos more concordant GO terms were found for cobalt and copper than for cadmium and cobalt or cadmium and copper. Cobalt and copper had opposing effects on genes related to nervous system and brain development, specifically those involved in forebrain, hindbrain and camera-type eye development, neuron fate, chordate embryonic development and Wnt pathway signaling. In 48 hpf embryos, cadmium and cobalt had opposing effects on genes involved in the regulation of growth and cell growth but similar effects on genes involved in ion transport and heat stress responses. Also in 48 hpf embryos, cadmium and copper showed mostly coherent effects on genes involved in biological processes such as cell, anatomical structure and eye morphogenesis, and heat stress responses (Figure 15 A). In contrast to the 48 hpf embryos, few GO terms showed significant gene enrichment under two or more exposure conditions at 96 hpf and none were affected by all three metals (Figure 15 B). For cobalt-treated embryos, the only significantly enriched biological process was the G-protein coupled receptor signaling pathway, which was also downregulated by copper exposure. Cadmium and copper had opposing effects on anatomical structure morphogenesis and response to chemicals, as also observed in the 48 hpf embryos. Notably, many enriched GO terms observed for cadmium- treated embryos at 48 hpf were also enriched in the 96 hpf embryos, e.g. the specific response to cadmium ions as well as sensory organ development (see Figure 17). KEGG pathway analysis (Figure 15 C) showed that only genes in the cell adhesion molecule pathway were mildly regulated by all three metals (upregulated by cadmium at 48 h, and downregulated by cobalt and copper at 96 h). Cell–cell adhesion is relevant for brain morphology as well as for the early development of the nervous system. In cadmium-exposed embryos, genes representing the mitogen-activated protein kinase (MAPK) signaling pathway, as well as genes involved in spliceosome assembly and endocytosis, were upregulated at 48 and 96 hpf. The MAPK signaling pathway regulates the cell cycle, apoptosis and neural cell death and is therefore important for the development of the nervous system (Dent et al., 2003; Harper and LoGrasso, 2001; Takeda and Ichijo, 2002). The spliceosome and endocytosis pathways were also mildly upregulated by copper in 48 hpf embryos. However, no pathway showed significant enrichment in response to cobalt at either 48 or 96 hpf. For copper, significant enrichment at 48 and 96 hpf was observed for the cell cycle, oocyte meiosis and notch signaling pathways, which were
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mostly upregulated, whereas oxidative phosphorylation was downregulated. Genes representing the notch signaling pathway, which is important during embryonic development, were more strongly regulated at 48 hpf than 96 hpf in zebrafish embryos exposed to copper.
A functional analysis comparing gene responses following exposure to the three different metals in 48 hpf zebrafish embryos is shown in Figure 16.
Figure 16: Functional relationships among significant GO terms identified in the transcriptomic response of 48 hpf zebrafish embryos to three different metals. Grey nodes show the gene ontology (GO) terms congruently found for cadmium, cobalt and copper exposure. Green nodes show congruent terms for cobalt and copper, orange for cadmium and copper, and blue for cadmium and cobalt. For functional analysis, significant GO terms generated in REVIGO through SimRel semantic similarity measurement algorithm were used with a large similarity allowance of 0.9. Cytoscape v3.2.0 and Adobe Photoshop CS2 were used for visualization.
The gray nodes (the largest group) represent the GO terms congruently found for cadmium, cobalt and copper exposure. These are followed by the green nodes indicating shared terms between cobalt and copper exposure, orange nodes indicating shared terms between cadmium and copper exposure, and blue nodes indicating shared terms between cadmium and cobalt exposure, each comprising only three GO terms each. Network connections among the GO ______60
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terms of all three metals spanned embryo development, multicellular organism development and organ morphogenesis, which also connected to eye, sensory organ and central nervous system development. Advanced branch connections for the two essential metals cobalt and copper were observed between central nervous system development and hindbrain, brain, and nervous system development, as well as neuronal fate commitment and cell fate specification. Furthermore, eye development was shown to be connected to embryonic camera-type eye and chordate embryonic development for cobalt and copper. None of these connections were found for the non-essential metal cadmium. Additionally, a connection between the regulation of biosynthesis and DNA-templated transcription, as well as DNA-templated transcription itself, was observed for all three metals. A connection between the regulation of growth and cell growth was found for cadmium and cobalt only.
Additional Figure 17 shows the results of functional analysis considering all significant GO terms for each of the different metals individually. This shows for 48 hpf zebrafish embryos a very similar arrangement of the GO terms for cobalt and copper, whereas the network representing the cadmium response is distinct (Figure 17 a). Embryos treated with cadmium showed a specific metal ion and cadmium response, which was not observed for cobalt or copper. These embryos exhibited a response to xenobiotic stimuli and Wnt signaling pathway regulation. Generally, more GO terms related to embryonic development, including central nervous system development, were found at 48 hpf than 96 hpf. The GO networks of the 96 hpf embryos (Figure 17 b) instead were clearly distinct for all three metals, potentially indicating different mechanisms of action. Nevertheless, cobalt and copper still share GO terms such as blood circulation and G-protein coupled receptor signaling pathway.
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Cadmium Cobalt Copper (non-essential) A
B
Figure 17: The functional analysis of significant gene ontology (GO) terms for 48 hpf (A) and 96 hpf (B) zebrafish embryos exposed to cadmium, cobalt and copper. Only significant GO terms generated in REVIGO using the SimRel semantic similarity measurement algorithm were used, with a large similarity allowance of 0.9. In the scatter plot, significant GO terms are represented by colored bubbles, which are arranged according to semantic similarities (i.e., the more similar the GO terms, the closer they are together); different colors of the bubbles indicate uniqueness (red indicates the highest uniqueness, yellow to green an intermediate uniqueness and blue the lowest uniqueness). The bubble size is linked to the p-value and increases with p-value increase).
4.4.3. Real-time quantitative PCR
The analysis of selected genes by qPCR following exposure to each of the three metals is shown in Figure 18. The transcripts representing mmp13a, hsp70.1, mmp9 and mt2 were significantly upregulated in cadmium-treated zebrafish embryos at 48 hpf (Figure 18 A), and by 96 hpf the abundance of transcripts representing mmp13a, mmp9 and mt2 more than doubled, with log2- transformed fold changes of >4 to 5 (Figure 18 B). In copper-treated embryos, mmp13a was slightly downregulated and hsp70.1 upregulated after 48 h, and mt2 was significantly upregulated after 96 hpf. In cobalt-treated embryos, only the hsp70.1 gene was significantly upregulated after 48 hpf. Genes involved in the development of the neuromasts and motor neurons (cldnb, nkx2.2a, stat3 and atp2b1a) were more weakly regulated in response to all three metals than the metal toxicity specific genes. After 48 hpf, only cldnb was significantly
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downregulated in copper-treated embryos, but cldnb and stat3 were significant upregulated and atp2b1a downregulated in cadmium-treated embryos at 96 hpf, and copper-treated embryos at 96 hpf showed a significant regulation of nkx2.2a.
Figure 18: Comparison of the expression levels of mmp13a, hsp70.1, mmp9, mt2, cldnb, nkx2.2a, stat3 and atp2b1a, measured by qPCR in 48 hpf (A) and 96 hpf (B) zebrafish embryos exposed to cadmium (Cd), cobalt (Co) or copper (Cu). Log2 transformed fold changes (FC) are plotted on the y-axis (one-way ANOVA with post hoc Dunnett’s test; *p < 0.05, **p < 0.01, ***p < 0.001).
Overall, the qPCR results agreed well with the microarray data for cadmium, cobalt and copper. Figure 19 compares the qPCR and microarray data for cadmium-treated zebrafish embryos as a representative example.
Figure 19: Comparison of expression levels measured by microarray and qPCR in 48 hpf (A) and 96 hpf (B) zebrafish embryos exposed to cadmium. Log2 transformed fold changes demonstrate good agreement between the microarray and qPCR results (one- way ANOVA with post hoc Dunnett’s test; *p < 0.05, **p < 0.01, ***p < 0.001).
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4.5. Discussion
Detailed mechanistic studies of metal toxicity in fish are scarce, and the particularly sensitive embryonic and larval developmental stages have been investigated less often than adults. The results of Chapter 3 “Effects of metal exposure on motor neuron development, neuromasts and the escape response of zebrafish embryos” demonstrated that motor neuron development and neuromast damage can serve as highly sensitive indicators of metal toxicity in zebrafish embryos (Sonnack et al., 2015). Here, we extended our investigation by including gene expression profiling to gain insight into potential mechanisms of metal toxicity affecting fish embryo development by considering two different developmental stages (pre-hatch and post- hatch) and comparing three different metals: copper (CuSO4), cadmium (CdCl2) and cobalt
(CoSO4).
Our microarray results indicated that the non-essential metal cadmium affected the embryonic transcriptome differently to cobalt and copper, which are considered essential metals. In cadmium treated embryos, more genes overall were differentially expressed than in embryos exposed to the other metals, and the number increased from 48 to 96 hpf. The opposite trend was seen for cobalt and copper exposed embryos, with fewer genes responding at 96 hpf. This observation suggests that the embryos pursued homeostasis when exposed to the essential metals cobalt and copper, and given that the exposure concentrations were low, they managed to achieve this status after hatch. The embryos appeared to have adapted to the additional extrinsic cobalt and copper ions because the differential gene expression observed at 48 hpf had ceased by 96 hpf. In contrast, embryos exposed to the non-essential metal cadmium experience adverse effects inducing detoxification (Wood et al., 2012a, b) and gene activity therefore increased over the longer exposure period of 96 h. However, the larger deviation from the nominal exposure concentrations of cobalt and copper in comparison to cadmium had almost certainly also an influence on the number of responding transcripts. The nominal concentrations of the three metals were chosen based on the corresponding EC10 values for morphological effects in Chapter 3.4.1 “Morphological effects in zebrafish embryos” (Sonnack et al., 2015), but the measured concentrations were all lower, with the lowest recovery for copper after the first 48 h of exposure. For cadmium, the actual exposure concentration was on average 23 % below the nominal concentration. For cobalt, the actual exposure concentration was on average 43 % below the nominal and the copper concentrations even decreased to 10 % of nominal after 48 h, while the exposure concentration during the post-hatch period (i.e., after test solution ______64
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renewal) only decreased to 71 % of the nominal concentration. Accordingly, the exposure condition may partly account for the weaker transcriptome response (in terms of numbers of transcripts; Figure 14) of cobalt (at 48 and 96 hpf) and copper (at 96 hpf) in comparison to cadmium. Yet the functional analysis (Figure 16) supported our hypothesis that the transcriptomic responses to the essential metals cobalt and copper were more similar to each other than either was to the response to cadmium.
In terms of the general mechanisms of metal toxicity, cadmium and copper may be taken up via epithelial Ca2+ pathways, although very little effect was shown on the total Ca2+ levels of zebrafish embryos exposed for up to 48 h, and toxicity was more related to general ion loss (Alsop and Wood, 2011). Cadmium and copper affect metallothionein production, and induce oxidative stress responses, apoptosis and compensatory reactions to ion imbalance in fish (Groh, K. J. et al., 2015) and specifically in zebrafish embryos (Craig et al., 2009; Craig et al., 2007). Metallothionein is required for heavy metal detoxification and homeostasis as well as protection against oxidative stress and neuroprotective mechanisms in aquatic vertebrates (Wang et al., 2014). Cadmium induced metallothionein expression more than copper in the fish species Hemibarbus mylodon (Cho et al., 2008) supporting our observations for metallothionein 2 (mt2) in 48 and 96 hpf zebrafish embryos described herein (Figure 18). This is consistent with other studies reporting mt2 expression in cadmium-exposed zebrafish larvae (Wu et al., 2008) and showing that cadmium is one of the most potent inducers of metallothionein expression (Chan et al., 2006; Cho et al., 2008; Wang et al., 2014). In addition to mt2, genes encoding matrix metalloproteinases 9 (mmp9) and 13a (mmp13a) were also strongly upregulated in cadmium-treated zebrafish embryos 48 and 96 hpf (Figure 18). Matrix metalloproteinases are needed to remodel the extracellular matrix during normal physiological, cellular and developmental processes, but they are also involved in wound healing and tumor growth (Vu and Werb, 2000). Specifically, mmp13a is involved in zebrafish craniofacial development, and mmp9 in fin and scale regeneration (de Vrieze et al., 2011; Hillegass et al., 2007; Pedersen et al., 2015). An increase in matrix metalloproteinase mRNA levels in zebrafish exposed to cadmium has not been reported before. However, the strong induction of mmp9 and mmp13a was observed in developing zebrafish embryo extracts following exposure to methyl mercury, linking these effects to tail impairments (Yang et al., 2010). Tail deformation was not observed in our assessment, but both cadmium and methyl mercury are non-essential metals so there is a potential for functional similarities involving the characteristic regulation of mmp9 and mmp13a in this context, although further studies would be required to confirm a general role in ______65
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response to non-essential metals. Nevertheless, the high-level expression of mmp9 and mmp13a could be linked through general developmental effects at the GO level following cadmium exposure (Figure 17).
For cobalt exposure, no metallothionein response has yet been described for zebrafish, although oxidative stress and apoptosis have been reported (Cai et al., 2012). We observed a non- significant increase in mt2 levels in 96 hpf embryos in response to cobalt (Figure 18). For copper exposure, we did not observe differentially expressed genes by microarray analysis in embryos at 48 or 96 hpf, but significant upregulation of mt2 mRNA was observed at 96 hpf by qPCR. The genes ATPase, Ca++ transporting, plasma membrane 1a (atp2b1a) and metallothionein 2 (mt2) were proposed as potential genetic markers in adult zebrafish exposed to copper (Craig et al., 2009), and accordingly we found that the atp1a1.5 gene was differentially expressed in 48 hpf zebrafish embryos exposed to copper. Our data show that atp1a1 and mt2 respond to copper exposure in zebrafish embryos and not solely in adults.
Oxidative stress is an important physiological response to metal exposure, and we observed that the heat shock cognate 70-kd protein, tandem duplicate 1 (hsp70.1) transcript was differentially expressed after 48 and 96 h in response to cadmium exposure. This agreed with a previous study showing hsp70.1 expression in adult zebrafish after 7 and 21 days of cadmium exposure (Gonzalez et al., 2006). Our qPCR data showed that hsp70.1 was also upregulated in 48 hpf zebrafish embryos exposed to cobalt and copper (Figure 18). Similarly, hsp70.1 was induced in 72 hpf transgenic zebrafish embryos in response to waterborne copper (Hernandez et al., 2011).
In zebrafish embryos exposed to cobalt, ca15a was the only gene to be differentially expressed at both 48 and 96 hpf. The product of this gene, carbonic anhydrase XVa, is associated with functional terms related to metal ion binding and is necessary for Na+ uptake via zebrafish skin and gills (Lin et al., 2008). The regulation of this gene by cobalt exposure has not been reported previously in zebrafish.
In 48 hpf zebrafish embryos exposed to copper, the GO term DNA methylation was significant (Figure 17) suggesting that copper may exert an epigenetic effect. Both copper and cadmium have previously been shown to significantly increase the level of total DNA methylation in goldfish (Carassius auratus) liver (Zhou et al., 2001). Epigenetic mechanisms of metal-induced neurotoxicity by microRNA expression have been described in adult AB strain zebrafish (Wang et al., 2013), but evidence of metal-induced epigenetic effects in zebrafish are otherwise scarce. ______66
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However, metal-induced DNA methylation and histone modification have been shown to affect gene expression in mammals, including humans (Cheng et al., 2012). Further studies to confirm metal-induced epigenetic mechanisms in zebrafish are therefore required, particularly because they may help to explain delayed and transgenerational effects in the context of metal resistance and tolerance.
The analysis of GO terms representing different biological processes showed that most GO terms were overrepresented by upregulated genes in embryos exposed to cadmium and copper, and the same was mostly true for downregulated genes in embryos exposed to cobalt (Figure 15). This differential transcriptomic response to cobalt and copper has not been described in zebrafish before, given that both metals are essential and the observed similarities in the significant functional terms (see results for 48 hpf embryos in Figure 17). The implied repression of the transcriptome by cobalt exposure (3.6 mg/L) is difficult to explain by linking this finding to the corresponding morphological effects. Cobalt was less toxic than copper and cadmium, and showed no morphological effects up to a concentration of 45.8 mg/L, where a no-hatch effect was observed only when a higher ionic strength ISO-water was used in the tests (Figure 9; Chapter Cobalt toxicity related to carbonate hardness) (Sonnack et al., 2015). Transcriptional repression could explain effects such as delayed growth, development and hatching, as reported for zebrafish embryos exposed to cobalt (Cai et al., 2012) but we saw no evidence of developmental delay in the cobalt-exposed embryos up to a concentration of 45.8 mg/L (Sonnack et al., 2015). The fact that 48 hpf embryos exposed to cobalt and copper showed similar sets of significant GO terms but opposing gene regulation profiles indicates that regulation may change with the exposure concentration and the associated increase in stress.
Cadmium-treated embryos showed a distinct set of GO term responses to copper/cobalt, including biological processes such as responses to metal ions or chemicals. These GO terms were not significant in cobalt or copper exposures, suggesting the latter (as essential metals) were perceived by the embryos as less noxious than non-essential cadmium.
A comparison of the two time points revealed that many GO terms were significantly overrepresented for all three metals in 48 hpf embryos but not in the corresponding 96 hpf embryos. Most GO terms were related to early embryonic development processes, from cellular differentiation to organ development, and were therefore more relevant in the 48 hpf embryos (undergoing embryogenesis) than the 96 hpf larval stage (Belanger et al., 2010). Additionally,
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fewer significant genes were shared by the three metals in 96 hpf embryos compared to the earlier stage, and no GO term was significant for all three metals at 96 hpf (Figure 15 B & C). One explanation for these data is that the differences between the 48 and 96 hpf embryos reflect the acclimation of the embryos to exposure in the case of cobalt and copper. In contrast, the number of genes responding to cadmium increased from 48 to 96 hpf, suggesting a time- dependent increase in the transcriptomic response, although this was not reflected by the overall number of functional terms.
Many metals that are essential for vertebrates are also developmental neurotoxins (Wright and Baccarelli, 2007). Our results show that cobalt and copper had opposing effects on gene expression profiles related to brain and nervous system development in 48 hpf embryos. Furthermore, genes involved in eye development in 48 hpf embryos were affected by cobalt, copper and cadmium (Figure 15 & Figure 16). Comparable studies in zebrafish embryos confirming or refuting such effects were not available at the time of this publication. At the morphological level, we observed no malformations of the brain or eyes that would link to the effects on the transcriptome, although our assessment only considered the gross morphology and shape of the organs. Behavioral deficits or eye malfunctions were not evaluated in our tests but may have revealed a potential translational link between gene modulation and physiological function. We have already demonstrated that copper, cadmium and cobalt affect the startle response of 72 hpf embryos, albeit at higher metal concentrations than we used herein (Sonnack et al., 2015). Although current evidence suggests that behavioral changes are sensitive and ecologically relevant endpoints of aquatic toxicity (Sloman and McNeil, 2012), the adverse behavioral effect of low metal concentrations tends to manifest only following long-term or chronic exposure scenarios (Barbee et al., 2014; Johnson et al., 2007; Kusch et al., 2008). The GO term central nervous system neuron differentiation was significantly overrepresented for cobalt and copper in 48 hpf zebrafish embryos, concordant with the damage to primary and secondary motor neurons reported in our previous study (Sonnack et al., 2015). We also observed damage to the mechanosensory hair cells of the neuromasts by DASPEI staining following exposure all three metals at concentrations below the EC10 value for morphological effects. Despite the absence of significant GO terms in the functional analysis, genes required for neuromast development were shown to be differentially expressed by microarray analysis in response to some of the metals. We confirmed the expression profiles of claudin b (cldnb), NK2 homeobox 2a (nkx2.2a), signal transducer and activator of transcription (stat3) and atp2b1a also by qPCR. Both methods showed that cldnb was significantly downregulated in 48 ______68
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hpf embryos exposed to copper and upregulated in 96 hpf embryos exposed to cadmium. The cldnb gene is necessary for neuromast development (Kollmar et al., 2001) and is expressed in zebrafish neuromast supporter cells (Chong et al., 2008; Hernandez et al., 2007). Although our previous study focused on damage to the neuromasts rather than cldnb-expressing supporting cells, the gene was also modulated by copper and cadmium. Interestingly, the GO terms for Wnt and Notch signaling were also significantly enriched for embryos exposed to cobalt and copper, suggesting that the regeneration of mechanosensory hair cells in the zebrafish lateral line relies on the interplay between Notch and Wnt signaling (Romero-Carvajal et al., 2015). The stat3 and atp2b1a genes are also required for the regeneration of mechanosensory hair cells and neuromasts (Cruz et al., 2009; Go et al., 2010; Liang et al., 2012), and atp2b1a knockdown reduced the number of hair cells in 5 dpf zebrafish larvae (Cruz et al., 2009). Here, we found that atp2b1a was significantly downregulated and stat3 upregulated by cadmium in 96 hpf embryos. Although genes involved in signaling pathways related to neuromast development and regeneration responded differently to the three metals, we nevertheless demonstrated both cellular (Sonnack et al., 2015) and transcriptomic effects. However, it is unclear whether damage to the neuromasts caused by different metals involves different molecular mechanisms.
The significant upregulation of stat3 by cadmium and nkx2.2a by copper in 96 hpf zebrafish embryos may be linked to the effects on motor neurons reported in our previous study (Sonnack et al., 2015). The role of the transcription factor Stat3 in motor neuron development and axon path-finding has been described in detail for 24 hpf AB strain zebrafish embryos (Conway, 2006). The regulation of stat3 transcription by metals was a novel finding for zebrafish embryos, but P-stat3 is upregulated in cadmium-treated mice (Kundu et al., 2009). The nkx2.2a gene is required for ventral spinal cord interneuron differentiation (Barth and Wilson, 1995) and is associated with many functional GO terms related to brain and CNS development, from motor neuron axon guidance to spinal cord oligodendrocyte differentiation. However, these GO terms were not overrepresented by significant genes in embryos exposed to copper and cadmium at 96 hpf (see Figure 17) which makes it more likely that the upregulation of nkx2.2a and stat3 reflects their involvement in signaling pathways representing other biological processes and cellular functions.
In conclusion, our results show that zebrafish embryos respond differently to essential compared and non-essential metals at the level of gene expression. Functional analysis revealed that the effects on the transcriptome were distinct for each metal, with little to no functional ______69
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coherence between cadmium and the essential metals. The molecular basis of the motor neuron and neuromast damage reported in our previous study appears to differ between the essential metals copper and cobalt and the non-essential metal cadmium.
Acknowledgements
This work was partially supported by the Fraunhofer Gesellschaft (FhG) internal programs via the Attract 692 093 research grant and by a PhD Scholarship for Laura Sonnack (Doktorandinnenprogramm Fraunhofer). Martina Fenske was also co-funded by the Landes- Offensive zur Entwicklung Wissenschaftlich-ökonomischer Exzellenz (LOEWE) of the Federal State of Hesse, Germany. We would like to thank Dr. Richard M. Twyman for editing the manuscript.
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Chapter 5
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Concentration dependent transcriptome responses of zebrafish embryos after exposure to cadmium, cobalt and copper.
Laura Sonnack1,4, Thorsten Klawonn2, Ralf Kriehuber3, Henner Hollert4, Christoph Schäfers2, Martina Fenske1
1 Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany 2 Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Schmallenberg, Germany 3 Department of Safety and Radiation Protection, Forschungszentrum Jülich, Germany 4Department of Ecosystem Analysis, Institute for Environmental Research, RWTH Aachen University, Germany
This chapter is based on the paper of the same title published in Comparative Biochemistry and Physiology - Part D: Genomics and Proteomics, Vol. 24, Page 29-40, July 2017. ______71
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5.1. Abstract
Environmental metals are known to cause harmful effects to fish of which many molecular mechanisms still require elucidation. Particularly concentration dependence of gene expression effects is unclear. Focusing on this matter, zebrafish embryo toxicity tests were used in combination with transcriptomics. Embryos were exposed to three concentrations of copper
(CuSO4), cadmium (CdCl2) and cobalt (CoSO4) from just after fertilization until the end of the 48 hpf pre- and 96 hpf post-hatch stage. The RNA was then analyzed on Agilent’s Zebrafish (V3, 4x44K) arrays. Enrichment for GO terms of biological processes illustrated for cadmium that most affected GO terms were represented in all three concentrations, while for cobalt and copper most GO terms were represented in the lowest test concentration only. This suggested a different response to the non-essential cadmium than cobalt and copper. In cobalt and copper treated embryos, many developmental and cellular processes as well as the Wnt and Notch signaling pathways were found significantly enriched. Also, different exposure concentrations affected varied functional networks. In contrast, the largest clusters of enriched GO terms for all three concentrations of cadmium included responses to cadmium ion, metal ion, xenobiotic stimulus, stress and chemicals. However, concentration dependence of mRNA levels was evident for several genes in all metal exposures. Some of these genes may be indicative of the mechanisms of action of the individual metals in zebrafish embryos. Real-time quantitative RT- PCR (qRT-PCR) verified the microarray data for mmp9, mt2, cldnb and nkx2.2a.
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5.2. Introduction
Metals belong to the oldest toxicants and anthropogenic metal contaminations of the environment are a common global issue. Large amounts of electronic waste in landfills, containing tons of metals are sad reality in many countries. From there and many other sources, high levels of metals are released and enter the aquatic environment. The toxicity of e.g., cadmium and copper has been studied intensively and both metals are known to accumulate in organs of aquatic organisms like fish (de Conto Cinier et al., 1999; Driessnack et al., 2016; Hollis et al., 2001; Kay et al., 1986; Kondera et al., 2014). In contrast, cobalt demonstrated low toxicity in aquatic organisms but has gained importance as an environmental contaminant in the context of REACH (Directive 1907/2006/EEC) due to suspected carcinogenicity.
Non-essential as well as essential metals can cause harmful effects to aquatic organisms. For zebrafish it was demonstrated that metals like cadmium, copper and cobalt impair the development and induce oxidative stress in adults (Arini et al., 2015; Craig et al., 2007; Gonzalez et al., 2006; Pereira et al., 2016) as well as larvae (Cai et al., 2012; Jin et al., 2015; Olivari et al., 2008; Pereira et al., 2016). Cadmium and copper additionally showed to affect metallothionein gene expression in adult zebrafish, which is important for detoxification of metals (Craig et al., 2009; Craig et al., 2007; Wang et al., 2014). However, many molecular mechanisms underlying these effects are still not fully understood. In particular concentration dependent effects and how these impacts on the transcription levels of genes, has yet to be explored in greater detail. In the present study, effects of the three metals on the transcriptome of zebrafish embryos were evaluated. Accordingly, zebrafish embryo toxicity tests were conducted with these metals and subsequent transcriptome changes analyzed to enlighten the mechanistic understanding of metal toxicity in sub-larval fish stages. Specifically, the study aimed at exploring the influence of different exposure concentrations on the transcript levels of genes expressed in the embryos. We have shown previously that the transcriptome responses to metal exposure were very different in pre- compared to post-hatch developmental stages, indicating that embryos cope differently with metal exposure than the hatched eleuthero embryos (see Chapter 4: Comparative analysis of the transcriptome responses of zebrafish embryos after exposure to low concentrations of cadmium, cobalt and copper). Here, particular emphasis was laid on the influence of different exposure concentrations on the transcript levels of genes in the embryos.
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To this end, wild-type zebrafish embryos were exposed to three different concentrations of copper (CuSO4), cadmium (CdCl2) and cobalt (CoSO4) from just after fertilization to 48 hours post fertilization (hpf) and 96 hpf, two different developmental stages pre-hatch and post-hatch. The RNA of these embryos was subjected to microarray analysis and significantly changed transcripts assigned to known molecular and biological functions and their connections to facilitate a mechanistic interpretation.
5.3. Materials and Methods
For detailed information see Chapter 2: Material & Methods, particularly 2.4. Gene transcription analysis. Microarray data in this article have been deposited in the NCBI Gene Expression Omnibus under the accession number GSE101058.
5.3.1. Analysis of metals
Nominal exposure concentrations of copper, cadmium and cobalt (see Table 8) were selected in the concentration range below the EC10- value for sub-lethal morphological effects and the lowest observed effect concentration for neuromast damage, as determined in Chapter 3 “Effects of metal exposure on motor neuron development, neuromasts and the escape response of zebrafish embryos” (Sonnack et al., 2015). Dissolved metal concentrations were determined in the stock and test solutions before, at the beginning, and after 48 h and 96 h (after test solution renewal at 48 h) of the exposures by using inductively coupled plasma optical emission spectrometry (ICP-OES) using an Agilent 720 ICP-OES system. The method was already described in detail in Chapter 4.3.2 Analysis of metals. For stabilization, the samples were acidified as recommended in ISO 11885:2007.
Table 8: Metal concentrations determined by inductively coupled plasma-optical emission spectrometry (ICP-OES) Cadmium Cobalt Copper test concentration [mg/L]: [mg/L]: [µg/L]: Nominal Measured nominal Measured nominal measured 0h 48h 96h 0h 48h 96h 0h 48h 96h 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.5 1.0 0.9 0.9 0.9 0.8 0.5 0.5 0.5 2.5 1.7 0.7 2.5 2.0 1.8 2.0 1.8 2.6 1.4 1.4 1.4 5.0 2.5 0.6 3.0 4.2 3.3 3.1 3.3 6.4 3.6 3.6 3.8 11.0 6.1 1.1 7.9
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The measured stock solution concentration of cadmium was 275.0 mg/L, thus 10.3 % less than the nominal concentration. For cobalt, the measured stock solution concentration of 216.4 mg/L was 28.9 % lower than the nominal concentration and for copper, the variance between the nominal and the measured stock solution concentrations of 14.06 mg/L was 29.4 %.
The test solution concentrations of cadmium (Table 8, left) at 0h (test start) were between 9 % and 21 % below nominal, ranging from 0.9 mg/L to 3.3 mg/L. During the test, the test concentrations remained stable over time. For cobalt (Table 8, center), the empirical test concentrations at 0h deviated further from the nominal concentrations than for cadmium, with 37.5 % of nominal at 0.8 mg/L and 43.8 % at 6.4 mg/L lower. However, the test concentrations remained stable over time. In comparison to cobalt, the test solution concentrations of copper (Table 8, right) at 0h were even lower with 32 % of nominal 2.5 mg/L and 50 % of 5.0 mg/L. All exposure concentrations decreased further over the first 48h to 90 - 72 % of nominal. In contrast, the test concentrations appeared not to have decreased between 48h and 96h after test solution renewal. Overall, the variance between the nominal and average (geometric means) measured concentrations of the test solutions over the 96h exposure period exceeded 20 % in most cases, except for the two lowest concentrations 1.0 and 2.0 mg/L of cadmium.
Due to the large deviations of the exposure concentrations from the nominal values, the results are presented and discussed in reference to the measured concentrations at test start (0h), i.e., 0.9, 1.8 and 3.3 mg/L for cadmium, 0.5, 1.4 and 3.6 mg/L for cobalt and 1.7, 2.5 and 6.1 µg/L for copper.
5.4. Results
5.4.1. Microarray-Analysis
Significant genes
Figure 20A shows the total number of differentially expressed gene transcripts in each treatment at both time points for all three metals. From these differential transcripts, those suggesting an exposure concentration dependent decrease or increase in the transcript levels were extracted and selected are depicted in the Figure 20B – D.
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Figure 20: Bar diagrams representing differentially expressed genes after exposure to three different concentrations of cadmium, cobalt and copper in 48 hpf and 96 hpf zebrafish embryos: Total number of genes (A); concentration dependent transcript level changes of selected significant genes for cadmium (B), cobalt (C) and copper (D). Fold change cut off was set to 1.1 and statistical significance tested by ANOVA with post hoc Tukey´s test and Benjamini-Hochberg multiple correction (adjusted p-value cut off 0.05; *= p < 0.05, **= p < 0.01, ***= p < 0.001).
For cadmium, 130 gene transcripts were differentially expressed in the lowest concentration of 0.9 mg/L (C1), 82 at 1.8 mg/L (C2) and 93 at 3.3 mg/L (C3) in 48 hpf zebrafish embryos (Figure 20A). Twenty-four of these transcripts were differentially expressed concordantly in all three concentrations, and among these were genes related to metal ion binding (mt2, klf11a, klf11b), calcium homeostasis (stc1l), xenobiotic detoxification (gstm3) and the response to cadmium ions and oxidative stress (hsp70.1, hsp70l, mt2). These genes showed a concentration dependent increase in their transcript level (Figure 20B) except for stc1l, which showed a fold-change decrease up to 10 at the highest cadmium concentration. In the 96 hpf zebrafish embryos exposed to cadmium, more gene transcripts were differentially expressed at the two highest ______76
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concentrations, fewer at the lowest concentration than at 48 hpf (Figure 20A). A concentration dependent increase in differentially expressed genes was observed, with 31 at the lowest concentration of 0.9 mg/L, and 352 at 3.3 mg/L. Concordant expression of transcripts at all three concentrations was found for 25 of these genes. Like in the 48 hpf embryos, some of these transcripts showed a pronounced concentration dependent response, e.g. of the matrix metalloproteinases mmp9 and mmp13, the heme oxygenase isoforms hmox1a and hmox1b, glutathione S-transferase pi genes gstp1 and gstp2 or the neuromast related claudin b (cldnb) (Figure 20B).
In the 48 hpf zebrafish embryos exposed to cobalt, 65 gene transcripts were differentially expressed at the lowest concentration of 0.5 mg/L, 26 at 3.6 mg/L, and only 8 at 1.4 mg/L (Figure 20A). A concentration dependent response was mostly seen for downregulated gene transcripts, like abcb4, agxtb, cmpk2, cygb2, cyp2p6, klf3, klf9, lpin1, slco2a1 and zgc:63602. Nonetheless, cygb2 and zgc:63602 were upregulated at the lowest concentration (Figure 20C). In 96 hpf zebrafish embryos, only a small number of differentially expressed genes could be observed for cobalt, with 10 at the lowest concentration of 0.5 mg/L, 13 at 1.4 mg/L and 18 at 3.6 mg/L (Figure 20A). Seven of these genes were differentially expressed at all three exposure concentrations. Five of these were related to metal and heme binding of which zgc:109934, zgc:173594, zgc:194125 and zgc:198419 were downregulated and zgc:92066 upregulated (Figure 20C). The carbonic anhydrase XVa (ca15a), which is related to ion binding, sodium transport and the regulation of pH, was found significantly reduced both in 48 hpf and 96 hpf cobalt treated embryos.
The zebrafish embryos exposed to copper showed a concentration dependent increase in differentially expressed genes at 48 hpf, with 52 at the lowest concentration of 1.7 µg/L, and 136 at the highest of 6.1 µg/L, but showed virtually no response at 96 hpf (Figure 20A). Twenty genes were differentially expressed concordantly in all three concentrations at 48 hpf. For genes like cyp19a1a, htr1b, lrit1a, opn1lw2, tcf7 and wnt10a a concentration dependent downregulation were observed (Figure 20D). Interestingly, the aromatase isoform 1a gene (cytochrome P450, family 19, subfamily A, polypeptide 1a, cyp19a1a) which is responsive to estrogen regulation, showed downregulation at 48 hpf, whereas the other isoform cyp19a1b showed upregulation in the 96 hpf embryos (Figure 20D). A concentration dependent pattern in the 96 hpf copper exposed embryos was otherwise only found for baiap2l2 and cyp19a1b and the uncharacterized genes si:ch211-197g15.6 and si:dkey-175g6.2. ______77
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Functional analysis based on overrepresented gene ontology terms
The transcriptome responses of 48 hpf and 96 hpf zebrafish embryos to each of the three metals at different concentrations are visualized in Figure 21 - Figure 23, based on overrepresented GO terms and their semantic relationships. Only gene ontology (GO) terms of the biological processes are used for this analysis. The grey nodes represent terms congruently found in all three concentrations.
Figure 21: Functional comparison of the transcriptome response of cadmium treated 48 hpf (left) and 96 hpf (right) zebrafish embryos at different concentrations. Grey nodes show the enriched gene ontology (GO) terms congruently found for all three tested cadmium concentration (C1 = 0.9 mg/L, C2 = 1.8 mg/L and C3 = 3.3 mg/L). Orange nodes depict congruent terms for C1 and C2, blue nodes for C2 and C3 and brown nodes depict terms for C2, and green nodes for C3. The scatterplots were generated by REVIGO (http://revigo.irb.hr) through a SimRel semantic similarity measurement algorithm with small similarity = 0.5. Cytoscape 3.2.0 and Adobe Photoshop CS2 were used for visualization.
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For cadmium treated embryos, the majority of significant GO terms were found to be represented by all three tested concentrations, both at 48 hpf and 96 hpf. For both time points, the largest clusters of connected terms include responses to cadmium, metal ion, xenobiotic stimulations, stress and chemicals (Figure 21). In the 48 hpf embryos, these terms are connected further to cell migration, chemotaxis, humoral immune response, locomotory behavior and remoter, to regulations of biosynthesis, pH and growth as well as otolith and embryo development (Figure 21, top). The two lowest cadmium concentrations of 0.9 mg/L (C1) and 1.8 mg/L (C2) connect the terms peptide metabolism and enterobactin biosynthesis with alcohol metabolism of the exposure to C2. Lipid catabolism and metabolism as well as chromatin assembly or disassembly were found significant exclusively to the highest concentration of 3.3 mg/L (C3). In 96 hpf cadmium treated zebrafish embryos, the lipid and potassium ion transport were significant only at the highest concentration (green node) and cellular protein metabolism and regulation of the transcription, DNA-templated for the two highest concentrations (blue node) (Figure 21, bottom). Besides, ion and cation transport were significant in the two lowest concentrations.
Cobalt demonstrated the largest network for the 48 hpf embryos, which reflects the varied transcriptome response pattern shown by the heat map (Figure S.2 in Supplements 128B Heat maps representing GO enrichment analysis). Most GO terms were found overrepresented in the lowest test concentration of 0.5 mg/L (yellow nodes in Figure 22, top). The network forms four to five clusters of closely linked terms. One cluster for example, represents biological developmental processes such as endoderm, pancreas, ventral midline, hindbrain and fin development and this cluster is mainly differently regulated at the highest concentration of 3.6 mg Co/L (green nodes). Other clusters related to metabolism processes, response to chemicals or DNA/RNA transcription are represented by terms enriched for different pairs of concentrations but mainly for the lowest concentration. Few GO terms like GPI anchor metabolic process, contraction, translation, lipoprotein and glutamine metabolism were significant in all three cobalt concentrations (grey nodes).
In cobalt treated 96 hpf embryos, fewer GO terms were found to be significantly overrepresented than in 48 hpf embryos (Figure 22, bottom). For the individual concentrations C1, C2 and C3 the numbers of terms enriched for regulated gene transcripts were similar. For example, endoderm and otolith development as well as lipid and phospholipid metabolism were significant at the lowest Co concentration of 0.5 mg/L, cation and potassium ion transport as ______79
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well as ceramide and amide metabolism were affected by the intermediate concentration of 1.4 mg/L and dorsal/ventral pattern formation, glial cell differentiation, convergent extension and regulation of signal transduction by the highest concentration 3.6 mg/L. Only the three GO terms cell surface receptor signaling pathway, G-protein coupled receptor signaling pathway and lipid transport were found significant at all three concentrations (grey nodes).
Figure 22: Functional comparison of the transcriptome response of cobalt treated 48 hpf (left) and 96 hpf (right) zebrafish embryos at different concentrations. Grey nodes show the enriched gene ontology (GO) terms congruently found for all three tested cobalt concentration (C1 = 0.5 mg/L, C2 = 1.4 mg/L and C3 = 3.6 mg/L). Orange nodes depict congruent terms, for C1 and C2, purple nodes for C1 and C3, and blue nodes for C2 and C3 and green nodes depict enriched terms for C3, brown node for C2 and yellow nodes for C1. The scatterplots were generated by REVIGO (http://revigo.irb.hr) through a SimRel semantic similarity measurement algorithm with small similarity = 0.5. Cytoscape 3.2.0 and Adobe Photoshop CS2 were used for visualization.
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For copper treated 48 hpf embryos, the majority of significant GO terms were found at all three copper exposure concentrations (grey nodes in Figure 23, top), and included cell differentiation, cell fate commitment and specification, developmental growth, notch signaling pathway, regulation of cell cycle and mitotic cell cycle. Fewer significant GO terms were found at the lowest copper concentration of 1.7 µg/L (yellow nodes) with terms such as cytoskeleton and actin cytoskeleton organization, neuron and cell migration, cellular metal ion homeostasis as well as muscle contraction. At the highest concentration of 6.1 µg/L (green nodes), significant GO terms like convergent extension, negative regulation of signal transduction, protein catabolism, potassium ion and dicarboxylic acid transport indicated regulation.
Compared to 48 hpf copper treated embryos, where most GO terms were enriched equally for all three concentrations, the majority of GO terms at 96 hpf were enriched only for the lowest concentration (yellow nodes in Figure 23, bottom). These GO terms comprise response to metal ion, cell migration and anion transport as well as lipid, sterol, peptide, cellular carbohydrate, glucose and glycogen metabolism. For copper treated 96 hpf embryos, five functional clusters of transport, chemical response, biological development processes, protein metabolism and glucose metabolism terms were identified. For all three concentrations of copper at 96 hpf (grey nodes), regulated genes associated with transport, notch signaling pathway and anatomical structure morphogenesis were enriched. Twelve GO terms including zinc ion transport, double- strand break repair, wound healing and ossification, were significantly enriched by the intermediate copper concentration of 2.5 µg/L (brown nodes). The highest concentration of 6.1 µg/L affected more GO terms (green nodes), including thymus and ectoderm development, muscle contraction, humoral immune response and cell redox homeostasis.
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Figure 23: Functional comparison of the transcriptome response of copper treated 48 hpf (left) and 96 hpf (right) zebrafish embryos at different concentrations. Grey nodes show the enriched gene ontology (GO) terms congruently found for all three tested copper concentration (C1 = 1.7 µg/L, C2 = 2.5 µg/L and C3 = 6.1 µg/L). Orange nodes depict congruent terms, for C1 and C2, purple nodes for C1 and C3, and blue nodes for C2 and C3 and green nodes depict enriched terms for C3, brown node for C2 and yellow nodes for C1. The scatterplots were generated by REVIGO (http://revigo.irb.hr) through a SimRel semantic similarity measurement algorithm with small similarity = 0.5. Cytoscape 3.2.0 and Adobe Photoshop CS2 were used for visualization.
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5.4.2. Real-time quantitative PCR
Results of the qPCR of selected genes measured in 48 hpf and 96 hpf embryos of all three exposure concentrations of cadmium, cobalt and copper are shown in Figure 24.
Figure 24: mRNA expression levels of gene transcripts of mmp9, mt2, cldnb and nkx2.2a measured by RT-qPCR in 48 hpf and 96 hpf zebrafish embryos after exposure to cadmium (A), cobalt (B) or copper (C). The concentrations were 0.9, 1.8 and 3.3 mg/L for cadmium, 0.5, 1.4 and 3.6 mg/L for cobalt and 1.7, 2.5 and 6.1 µg/L for copper. Log2 transformed fold changes (FC) on the y-axis were plotted against the genes, and significant differences between exposure groups and controls were tested by one-way ANOVA with post hoc Dunnett´s test (*= p < 0.05, **= p < 0.01, ***= p < 0.001).
In 48 hpf cadmium treated embryos, we found significant increases in mRNA for mmp9 at the highest exposure concentration. Upregulation of mt2 was significant even at all three cadmium concentrations, with a slightly higher upregulation in the lowest than in the intermediate concentration. The transcript of nkx2.2a was only significantly downregulated in the highest concentration. In 96 hpf zebrafish embryos, cadmium caused significant concentration dependent increases in mRNA of mmp9, mt2 and cldnb (Figure 24). For cobalt and copper, mt2 showed a less than two-fold concentration dependent upregulation at 96 hpf which became significant at 1.4 and 3.6 mg/L of cobalt and 2.5 and 6.1 µg/L of copper. At 48 hpf, mt2 was not altered but cldnb as well as nkx2.2a showed significant downregulation in the two lowest concentrations, and cldnb was also downregulated at the highest concentration of copper. After 96 hpf, nkx2.2a was downregulated for cobalt in the lowest concentration and significantly upregulated for copper only in the highest concentration.
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Figure 25: mRNA expression levels of gene transcripts of mmp9, mt2, cldnb and nkx2.2a measured by microarray in 48 hpf and 96 hpf zebrafish embryos after exposure to cadmium cobalt (B) or copper (C). The concentrations were 0.9, 1.8 and 3.3 mg/L for cadmium, 0.5, 1.4 and 3.6 mg/L for cobalt and 1.7, 2.5 and 6.1 µg/L for copper. Log2 transformed fold changes (FC) on the y-axis were plotted against the genes. Statistical significance tested by ANOVA with post hoc Tukey´s test and Benjamini-Hochberg multiple correction (adjusted p-value cut off 0.05; *= p < 0.05, **= p < 0.01, ***= p < 0.001)
In comparison to the microarray results, the log2 fold changes (log2FC) values of the gene transcripts measured by qPCR were found to be expressed at lower rates. Significant changes were seen for cadmium only; for cobalt and copper the transcript levels were insignificantly different from the controls (Figure 25).
Nevertheless, exposure concentration related upwards or downwards trends in transcript expression were coherent between the microarray and the qPCR data for these genes (Figure 24 & Figure 25).
5.5. Discussion
Many molecular mechanisms of metal toxicity in fish are still poorly understood. In particular exposure concentration dependent effects on gene transcript expression levels have not been well described. Here, we used 96h zebrafish embryo toxicity tests in combination with transcriptomics to elucidate at least some of these mechanisms. In Chapter 4: Comparative analysis of the transcriptome responses of zebrafish embryos after exposure to low concentrations of cadmium, cobalt and copper, we investigated the effects of cadmium, cobalt and copper on two different developmental stages pre- and post-hatch (48 hpf and 96 hpf). In
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the present study, we specifically explored exposure concentration dependent variations in gene transcription and tested three different concentrations for each metal and developmental stage.
As shown in our previous study, cadmium treated zebrafish embryos exhibited a stronger differential transcript expression at 96 hpf (total of 403 significant genes) than at 48 hpf (total of 239 significant genes). The opposite was shown for cobalt and copper treated embryos with a total of 93 (at 48 hpf) to 20 (at 96 hpf) significant genes for cobalt and 196 (at 48 hpf) to 21 (at 96 hpf) for copper. We assumed that with prolonged exposure to the essential metals cobalt and copper the zebrafish embryos managed to compensate for the excess metal and approached homeostasis, as suggested by the lowered transcriptome activity. Conversely, exposure to the non-essential metal cadmium induced adverse effects, leading to detoxification processes (Wood et al., 2012a, b). Thus, gene transcription activity was increased after a longer exposure time and particularly beyond hatch (Chapter 4). It was assumed that zebrafish were unable to compensate for the adverse effects of cadmium exposure with increasing exposure time. Therefore, gene transcription activity for cadmium, as a non-essential metal, was higher after the longer 96 h exposure time and for cobalt and copper, as essential metals, already earlier after the 48 h exposure. However, in order to corroborate this hypothesis, we suggest further experiments to study the changes in the metabolic activities of the embryos during pre- and post-hatch low-level metal exposures. A generally lower baseline gene activity at 96 hpf compared to 48 hpf was most likely not the reason for the lowered transcriptome activity we observed in the cobalt and copper exposed zebrafish embryos. There is good evidence that during zebrafish embryo and larval development, the baseline transcriptome activity steadily increases over time (Yang et al., 2013).
Concentration-response analyses are rarely found in whole transcriptome wide fish toxicity studies, mainly because they require complex hence expensive experiments. For the same reason, we were unable to study the entire concentration-response range and instead only compared three different concentrations of cadmium, cobalt and copper. Although three concentrations were statistically insufficient to identify different types of concentration response behaviors of individual gene transcripts or pathways, possible implications of using just one exposure concentration in transcriptomics based studies still became evident. Another aspect of our study to shed some light on was the importance of the exposure period during embryo-larval development of fish, which influences the transcriptome response considerably. For the zebrafish embryo toxicity test, where continuous exposure post-fertilization is ______85
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stipulated, we demonstrated that the transcriptome response to metal exposure is far more informative at the pre-hatch 48 hpf stage than at the post-hatch 96 hpf stage, which signifies the end of the OECD compliant standard test. A concentration related increase in the number of differentially expressed gene transcripts was observed at 48 hpf for copper and at 96 hpf for cadmium (Figure 20A). For cobalt, the number of genes did also increase with increasing exposure concentration at 96 hpf, but the overall number of genes (0, 2 and 4) was too low to exclude randomness. Regarding the transcription of selected significant genes, it was conspicuous that several genes assigned to the GO term “metal ion binding” were downregulated by cobalt and copper in 48 hpf and 96 hpf embryos but upregulated by cadmium. Although these genes were different for each metal and thus, were linked to different cellular and biological functions, it was an interesting observation to see the opposing regulation of genes of the same molecular function by essential versus non-essential metals. While in 48 hpf cadmium treated embryos only a weak concentration dependent increase could be observed for hsp70.1 and hsp70l and partly for mt2, a sharp concentration dependent increase was shown for hsp70.1, hsp70l, mt2, mmp13a, mmp9, cldnb, stat3 in 96 hpf embryos. As hypothesized before, this could partly be explained by the generally stronger transcriptome response at a later time point of 96 hpf, as observed for cadmium as a non-essential metal. The regulation of hsp70.1, hsp70l, mt2, mmp13a, mmp9, cldnb and stat3 has already been discussed in our previous study, and especially the regulation of the metallothionein expression corresponded with other studies. For example, metallothionein expression was highly induced in 24 hpf and 48 hpf zebrafish larvae after cadmium exposure (Chan et al., 2006; Wu et al., 2008). However, the metallothionein expression has been also reported after cadmium exposure in serval other aquatic vertebrates. For example, gene expression of metallothionein after exposure to cadmium is reported in liver, gill, olfactory and kidney tissues of coho salmon (Espinoza et al., 2012) and common carp (Cyprinus carpio) (De Smet et al., 2001; Hermesz et al., 2001). Furthermore, a higher metallothionein mRNA expression in cadmium than in copper treated fish was described for Hemibarbus mylodon (Cho et al., 2008). Therefore cadmium is reported as one of the powerful inducers for metallothionein transcription in fish (Wang et al., 2014). Additionally, glutathione-s-transferase (GSTs) genes like gstm3 in 48 hpf and gsto2, gstp1 and gstp2 in 96 hpf cadmium treated embryos showed a concentration dependent significant increases. GSTs play an important role in the detoxification of environmental toxicants like heavy metals and are included in the oxidative stress response. Even though GSTs are not named as a bio marker for cadmium exposure till now, the expression of GST mRNA has been
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reported for zebrafish embryos after cadmium exposure already in other studies (Jin et al., 2015; Kim et al., 2011; Wang and Gallagher, 2013). However, upregulation of several Gst transcripts after cadmium exposure was shown also in other fish species, like in juvenile coho salmon (Oncorhynchus kisutch) for gill, liver and olfactory tissues (Espinoza et al., 2012) as well as in river pufferfish (Takifugu obscurus) tissues (Kim et al., 2010). Further, the expression of heme oxygenase as hmox1a and hmox1b was significantly induced in 96 hpf cadmium treated embryos. The upregulation of hmox1 has been suggested as a potential marker of cadmium exposure in zebrafish embryos (Wang and Gallagher, 2013; Weil et al., 2009). More recently, the expression of hmox1a and hmox1b was found induced also in zebrafish eleutheroembryos and in adult zebrafish tissues (Holowiecki et al., 2016). Furthermore, an increased expression of hmox1 after cadmium exposure has been also reported in other fish species as juvenile coho salmon (Oncorhynchus kisutch) (Williams and Gallagher, 2013). Our findings on the transcript expression of glutathione-s-transferase and heme oxygenase after cadmium exposure agree with existing studies and overall, the regulation of the heat shock protein hsp70, glutathione-s- transferase gstm3, gsto2, gstp1 and gstp2 as well as heme oxygenase hmox1a and hmox1b reflect the oxidative stress response of cadmium. Another important finding was the strong downregulation of stanniocalcin 1 stc1l in 48 hpf zebrafish embryos after cadmium exposure. To our knowledge, the regulation of stc1l after cadmium exposure has not been reported for fish before. However, stc1l regulates the calcium uptake in zebrafish (Tseng et al., 2009) and a failure of the calcium-homeostasis after cadmium exposure was reported for other fish species like Atlantic salmon, Mozambique tilapia and goldfish (Berntssen et al., 2003; Pratap and Wendelaar Bonga, 2007; Suzuki et al., 2004).
In the essential metal copper and cobalt treated zebrafish embryos only few genes were found to be significant in all three concentrations and many of these genes had no annotation. Nonetheless, in 48 hpf embryos some cytochrome P450s (CYPs) indicated a concentration related decrease in mRNA with downregulation at the highest exposure concentration. These were cyp2p6 after cobalt and cyp19a1a after copper exposure. Several CYPs are important for the detoxification of metals, and the expression of CYP transcripts after for instance cobalt exposure has been reported also for other fish species. Cytochrome P450 1a (cyp1a) for example, was upregulated in rainbow trout after short exposure to cobalt (Ceyhun et al., 2011) or after hypoxia induced chemically by cobalt chloride in salmon hepatocytes (Olufsen and Arukwe, 2015). After exposure to 50 mg/L of copper oxide nanoparticles, however, cyp1a was significantly upregulated in 96 hpf zebrafish embryos (Sun et al., 2016). Here, we could observe ______87
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a significant regulation by copper (6.1 µg Cu/L) only for two CYP gene transcripts which are not involved in the phase I metabolism of xenobiotics. The gene transcript of the aromatase isoform cytochrome P450 19a1a (cyp19a1a) was downregulated at 48 hpf, the other isoform cytochrome P450 19a1b (cyp19a1b) upregulated at 96 hpf. Both genes encode for the two isoforms of the steroidogenic enzyme aromatase, which can be considered a target of endocrine, and more specifically estrogenic, disruption in zebrafish (Fenske and Segner, 2004; Muth- Köhne et al., 2016; Uchida et al., 2004). This observation is interesting because to our knowledge no zebrafish study has so far reported the regulation of cyp19a1a or cyp19a1b transcripts by copper or any other metal. In general, our array results suggest a concentration dependent phase II detoxification activity at gene transcription level for cadmium since the glutathione-s-transferase (GSTs) genes gstm3 (at 48 hpf) and gsto2, gstp1 and gstp2 (at 96 hpf) were found upregulated. Moreover, the upregulation of the metal binding protein metallothionein 2 gene transcript mt2 at all cadmium exposure concentrations at both time points may also hind at a protective response of the embryos towards toxic as well as oxidative stress. For the essential metals cobalt and copper, on the other hand, no gene transcripts related to detoxification were found upregulated in a concentration-dependent manner. The upregulation of the abcb4 by the highest cobalt concentration (3.6 mg Co/L) in the 48 hpf embryos, however, indicated that perhaps from a certain exposure concentration on the essential metals also induce a protective response in the embryos. Abcb4 acts like in mammals, as a xenobiotic efflux transporter in zebrafish, which has been shown for several toxicants (Fischer et al., 2013; Lu et al., 2015). Further for cobalt treated embryos, the kruppel-like factor genes klf3 and kfl9 were increasingly downregulated with increasing concentrations at 48 hpf (Figure 1C). The corresponding proteins play a decisive role in haematopoiesis, and a change in gene expression after cobalt exposure has not yet been reported. At 96 hpf, cobalt treated embryos showed that zgc:109934, zgc:173594, zgc:194125, zgc:198419 were concentration-related downregulated and zgc:92066 upregulated. These genes are not yet fully annotated but are all located on chromosome 3 and somehow related to the iron ion-homeostasis. The carbonic anhydrase transcript ca15a was found significantly downregulated both in 48 hpf and 96 hpf cobalt treated embryos, but showed a concentration-related trend only at 96 hpf. Ca15a plays an important role on the pH regulation. In copper treated 48 hpf embryos a concentration dependent downregulation was be observed for the genes transcription factor 7 (tfc7) and wingless-type MMTV integration site family, member 10a (wnt10a). The wnt10a gene plays an important role on the Wnt signaling pathway as well as the tfc7 gene, which is also involved in
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the fin development. The Wnt signaling pathway is crucial for many processes in the embryonic development. For copper oxide nanoparticles it was suggested that exposure can impair tissue extension during gastrulation of zebrafish embryos and that this is maybe due to a decrease in transcription of Wnt5 and Wnt11 (Xu et al., 2017).
The comparison of the three metals and the respective three exposure concentrations based on the enrichment for GO terms of biological processes illustrated the different responses of the non-essential metal cadmium versus the essential metals cobalt and copper. For cadmium almost all significant GO terms in the 48 hpf respectively 96 hpf embryos were found concordantly in all three concentrations. For cobalt and copper, on the other hand, a large proportion of the significant GO terms were only found to be represented in the lowest test concentration at 48 hpf respectively 96 hpf (Figure 22 & Figure 23). This observation may suggest that for essential metals obviously only low extrinsic concentrations disturb the homeostasis of the embryos whereas higher concentrations are compensated for by specific regulation. In the 48 hpf and 96 hpf cadmium exposed embryos the largest clusters of connected GO terms included responses to cadmium, metal ion, xenobiotic stimulations, stress and chemicals (Figure 21). This kind of response pattern was generally anticipated according to other fish studies on heavy metal exposure (Pierron et al., 2009; Redelstein et al., 2015;
Reynders et al., 2006). In 48 hpf cobalt exposed embryos the transcriptome response was very diverse with the functional GO terms forming five to six clusters. The 48 hpf zebrafish embryos responded at the lowest 0.5 mg/L cobalt concentration mainly with metabolism and DNA/RNA transcription related gene transcript changes whereas in the highest concentration of 3.6 mg Co/L mostly biological developmental processes such as endoderm, pancreas, ventral midline, hindbrain and fin development were affected. For copper treated 48 hpf embryos, one main GO cluster of cellular processes was identified with most GO terms as cell differentiation, cell fate commitment and specification, developmental growth, notch signaling pathway, regulation of cell cycle and mitotic cell cycle observed for all three exposure concentrations. While in copper treated 96 hpf embryos, five functional clusters of transport, chemical response, biological development processes, protein metabolism and glucose metabolism terms were identified mainly at the lowest concentration of 1.7 µg Cu/L. As already emphasized in Chapter 4, cadmium and copper upregulated the majority of gene transcripts related to GO terms of biological processes, especially in 48 hpf embryos, while cobalt mostly downregulated gene transcripts (Supplements B. Heat maps representing GO enrichment analysis Figure S.1, Figure S.2, Figure S.3). This observation of transcriptional repression may be associated with ______89
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morphological effects like delayed growth, development or hatching, which have been reported for zebrafish embryos exposed to cobalt (Cai et al., 2012). However, we did not observe any developmental delay in the cobalt-exposed embryos up to a concentration of 45.8 mg Co/L in 1:5 diluted ISO-standard water.
Validating the transcriptome results, we demonstrated that the qPCR results agreed well with the microarray data. The significant concentration dependent increases in gene transcripts observed for mmp9, mt2 and cldnb in the microarrays were confirmed by qPCR on 96 hpf cadmium treated embryos (Figure 20 & Figure 24). A significant increase in mmp9 and mt2 mRNAs could even be observed in 48 hpf embryos by qPCR. Especially in cobalt exposed 48 hpf and 96 hpf embryos, the PCR confirmed the downregulation of the cldnb and nkx2.2 transcripts, which in contrast to mmp9 and mt2 in cadmium decreased with increasing concentration. This finding corresponded with the functional analysis of the cobalt were most GO terms were significant at the lowest exposed cobalt concentration of 0.5 mg Co/L.
In conclusion, the results of this study clearly demonstrated exposure concentration related differences in the transcriptome responses of zebrafish embryos and eleutheroembryos to the non-essential metal cadmium compared to the essential metals cobalt and copper. The enrichment for GO terms of biological processes showed that each concentration of the essential metals altered the transcriptome of the embryos very differently. For cadmium, on the other hand, the responses of the transcriptome to the different concentrations were very similar and less diverse than for cobalt and copper, with most GO terms hinting at detoxification processes. Overall, concentration dependent effects on the transcriptome were more pronounced at 48 hpf than 96 hpf what was in line with the generally weaker transcriptome response at 96 hpf. As suggested previously in Chapter 4, the changes in the transcriptome response after prolonged exposure of 96 h of zebrafish embryos would imply adaptation to the exposure. However, after 48 h of exposure, the transcriptome patterns of the embryos rather indicate the response to toxic stress. In terms of individual gene transcripts commonly used as biomarkers of metal exposure (like mt2) or functional GO terms responding, only the effects of the non-essential cadmium resembled a metal exposure response. Copper instead activated the transcription of mainly developmental genes at 48 hpf and additionally metabolic and redox processes related genes at 96 hpf. In contrast, cobalt repressed the transcription of genes related to diverse metabolic processes at the lower concentrations and related to embryo developmental at the highest concentration. The exposure concentration as well as the exposure time clearly matters if the ______90
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molecular mechanisms of metal toxicity are to be elucidated in zebrafish embryos. The results of this study also provide transcriptome level evidence of the differences how zebrafish embryos cope with essential metal contamination versus non-essential metal contamination. This is important knowledge if such a fish embryo toxico-transcriptomics approach is applied to mechanistic as well as predictive environmental studies.
Acknowledgements
This work was partially supported by the Fraunhofer Gesellschaft (FhG) internal programs by a research grant No. Attract 692 093 and by a PhD-Scholarship of Laura Sonnack (Doktorandinnenprogramm Fraunhofer). Martina Fenske was also co-funded by the Landes- Offensive zur Entwicklung Wissenschaftlich-ökonomischer Exzellenz (LOEWE) of the Federal State of Hesse, Germany.
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6.1. Addressing limitations of the zebrafish embryo toxicity test
The FET is widely used for toxicity testing of substances and is based on the assessment of defined lethal and sub-lethal morphological endpoints. However, in order to identify the underlying mechanisms of a toxicant, the FET needs to be further refined e.g., by the addition of fluorescence endpoints which can visualise cyto-, myo-, neuro-, vaso- or ototoxic effects. This thesis specifically investigated additional test endpoints using in-vivo staining methods. One question to be addressed was if these endpoints are suitable to describe at least some underlying mechanism of metal toxicity. Furthermore, this thesis considered behavioural endpoints in addition to morphological assessments and fluorescence stainings (Chapter 3) and aimed at studying the molecular basis of metal exposure related effects using transcriptome analysis to gain mechanistic information (Chapter 4 and Chapter 5).
Chapter 3 demonstrated that the immunofluorescence staining of primary and secondary motor neurons is an appropriate tool to visualize the disruption of motor neuron development and motor neuron damage in 48 hpf zebrafish embryos. All three metals caused a concentration dependent increase in motor neuron damage and thus, verifying this additional endpoint as a sensitive indicator of metal toxicity in zebrafish embryos. However, the classification of the motor neuron defects according to Carrel et al. (2006) was only practical in 48 hpf zebrafish embryos and not applicable to 72 hpf zebrafish embryos, where defects appeared to be difficult to identify due to heavy branching of especially the primary motor neurons. This limited the immunofluorescence staining with the antibodies znp1 and zn8 and the detection of motor neuron effects to the 48 hpf time point, as shown previously (Muth-Köhne et al., 2013; Muth- Köhne et al., 2012). Sylvain et al. (2010) evaluated effects on the PMNs and SMNs after ethanol exposure in 3 dpf zebrafish embryos but used a modified categorisation of the motor neuron defects. The classification by Carrel et al. (2006) was used in this thesis because it provided a more descriptive evaluation of the defects than the Sylvain et. al method, which scores the degree of axon damage. Therefore, a new categorisation and classification would be suggested to determine the defects on motor neurons at various zebrafish life stages, but this task was not pursued in the context of this thesis.
Furthermore, the classification of the defects is carried out visually and thus highly dependent on the experience and subjectivity of the person conducting the assessment. The low objectivity of this method could be improved by the application of an automated, computer based analysis
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and the inclusion of a measurable (quantifiable) parameter like the axon length. An example of a more objective assessment method was the evaluation of the neuromast development and hair cell damage based on the quantification of the fluorescence intensity after in vivo fluorescent staining with the vital dye DASPEI. The fluorescence can be measured by automated imaging and does not depend on subjective judgments. The staining of the zebrafish embryos’ neuromasts with DASPEI is very simple, fast and inexpensive to perform (Chapter 3.4.3) and the defects of the hair cells of the neuromasts can easily be observed. Additional, hair cells of the neuromasts share most properties with the hair cells of the inner ear of mammals, which makes the assay very interesting also for hearing research. The neuromast damage assay is therefore potentially also suitable to screen drugs for ototoxicity and otoprotection. However, it needs to be considered that the neuromast hair cells of fish can regenerate to a certain level of damage after chemical exposure (Monroe et al., 2015) which was not taken into account during the evaluations conducted in this thesis. The regeneration of the neuromast hair cells depends on exposure and recovery time as well as on the exposure concentration. The regeneration potential of neuromast hair cells was investigated after waterborne copper exposure (Hernandez et al., 2006), and showed that PLL neuromasts of the trunk and tail recover concentration depended up to a copper concentration of 10 µM; at concentrations of 50 µM and higher the damage was irreversible, as also the supporting cells were destroyed. This demonstrated that a regeneration of destroyed supporting cells is not possible. With regard to the interpretation of the neuromast results of this thesis, a possible irreversible damage of the neuromasts was not assessed. To define the irreversible damage of the zebrafish embryo neuromasts caused by copper, cadmium or cobalt exposure, additional tests would be necessary to determine the regeneration. A direct assessment of an irreversible neuromast damage may be achieved by using the transgenic zebrafish line Tg(cldnb:lynGFP) in which GFP is expressed in the hair cells as well as in the supporting cells. However, the application of the Tg(cldnb:lynGFP) would required another assessment method than the measurement of the fluorescence intensity to indicate neuromast defects.
In general, acute and chronic fish tests are commonly used in the environmental risk assessment, but these standardized conventional tests provide only little to no information about the mechanisms of action of chemicals. However, in vivo fluorescent staining of developmentally relevant and physiologically indispensible cells or tissues can add sensitive and informative endpoints which can help to improve the understanding of the toxicity. The inclusion of such additional endpoints is therefore sensible to achieve more informative read-outs and can be ______95
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useful for a more realistic hazard assessment. For example, in context of the FET the use of the additional cellular and functional endpoints evaluated in Chapter 3 of this thesis, increased the informative value and improved the mechanistic understanding of the three tested metals. However, these additional endpoints could also be applied to improve the mechanistic understanding of other environmentally or health relevant chemicals and substances. The mechanisms of action can be an important parameter, to indicate potential subtle and long-term effects of substances and thereby provide necessary information for a better assessment of the toxicological effects on the ecosystem (Scholz et al., 2008). Therfore, in terms of environmental risk assessment, the fish embryos tests can help to identify the mechanisms of action of toxicants which may indicate possible adverse effects. Furthermore, studies applying adverse outcome pathways (AOPs), which combine molecular initiating events with adverse effects, become more and more important in this context (Ankley et al., 2010). AOPs are a very promising approach in ecotoxicology as well as in human and ecological risk assessments to improve the prediction of a potential hazard. In general, AOPs ought to simplify the complex mechanisms underlying toxicity by defining the chain of key perturbations leading to a known adverse effect. The AOP concept therefore aims at facilitating chemical risk assessments based on mechanistic reasoning.
This thesis further demonstrated that transcriptome analyses for the FET can be a suitable approach to describe the molecular basis of toxic effects (Chapter 4 and Chapter 5). In recent years, transcriptomics has become a recognized tool in ecotoxicology. Marker genes can serve as very sensitive biological indicators of chemical exposure and microarray studies enable the analysis of the molecular mechanisms of action based on exposure dependent transcriptome expression patterns. Especially fish biomarkers of exposure can be useful for environmental monitoring of pollutions, also with regard to the Water Framework Directive (Sanchez and Porcher, 2009). For example, metallothionein has long been known as an important biomarker for the monitoring of heavy metals such as cadmium, mercury, silver and copper in aquatic vertebrates and invertebrates (Amiard et al., 2006; Chan, 1995; Livingstone, 1993). Nonetheless, it has to be considered that transcriptomics using microarrays or more cutting- edge technologies like next generation RNA sequencing, are very expensive and require specialist expertise. However, the wealth of information that can be obtained simultaneously by these approaches are enormous. For the elucidation of some of the mechanisms underlying the toxicity of cadmium, cobalt and copper, the transcriptome analyses allowed e.g., to corroborate our hypothesis about neurotoxic and ototoxic effects. For copper treated 48 hpf ______96
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embryos, which showed a strong defect of the primary and secondary motor neurons, GO terms of nervous system development, central nervous system development, neural tube development, neuron development and differentiation were found significantly overrepresented. The agreement between the GO terms neuron development and differentiation and the motor neuron damage observed by fluorescence staining, substantiated the neurotoxic potency of copper. Cobalt demonstrated a weaker neurotoxic potential, since effects on the neural system were observed by staining only at higher exposure concentrations. At transcriptome level, few GO terms vaguely related to the nervous system development (e.g., synapse organization and neurotransmitter transport) were overrepresented at low concentration levels. In contrast to both essential metals, GO terms of the central nervous system development were found significantly overrepresented at all three tested concentrations of cadmium treated 48 hpf embryos, which also showed obvious defects of the motor neurons. The ototoxic potential of the metals was not clearly identifiable at transcriptome level since no GO terms related to neuromast or lateral line development were significant. However, there were indications that signaling pathways were affected, which were previously linked to the damage of the mechanosensory hair cells of the neuromasts. The GO terms Wnt signaling pathway were significantly enriched for the cobalt treated 48 hpf embryos and Wnt and Notch signaling pathway for the copper treated 48 hpf embryos. It was suggested that the regeneration of mechanosensory hair cells in the zebrafish lateral line relies on the interplay between Notch and Wnt signaling (Romero-Carvajal et al., 2015). Additionally, genes required for the neuromast development and regeneration were shown to be differentially expressed in the microarrays as well as the qPCR. Specifically, cadmium regulated the transcripts of the genes cldnb, atp2b1a, and stat3 in 96 hpf embryos. Nonetheless, it has to be considered that the expression of single genes cannot directly be correlated with the functionality of the proteins, as one single gene rarely encodes only one particular protein but rather one gene can encode different polypeptides as well as functional RNA. However, widely used gene ontology (GO) analyses and KEGG pathways help to characterize gene transcripts functionally and group them according to their known properties. Gene set enrichment based on ontology data derived from gene or protein resources and published literature is therefore a resourceful tool in the functional analysis of transcriptome data. It attaches relevance to the differentially expressed genes and groups and assigns them to signaling pathways which in turn, can be connected and linked to biological functions. In brief, gene (set) enrichment based on common annotations like GO and KEGG, can be instrumental when trying to make sense of transcriptomics data. However, especially the commonly used
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analyses of transcription patterns based on GO terms is not free of criticism. In particular, GO terms are relative general as the annotations and classifications of many genes are not very specific and is often based on assumptions about homology and orthology. Therefore, the additional use of KEGG analyses and other gene sets associated with certain pathways or mechanism, can provide even more reliable detailed mechanistic informations.
6.2. Special considerations regarding metals and toxicity
To accurately study effects of metal toxicity in the environment, factors such as exposure time and environmental parameters of the medium require far more attention than for other chemicals due to their physico-chemical characteristics. Abiotic parameters of the medium, like temperature, pH and water hardness, can affect the bioavailability and thus the toxicity of metals. It is therefore very important to measure and report these parameters of the test medium, otherwise a comparison with other studies is almost impossible. For cobalt it was demonstrated that the toxicity to freshwater organisms depends on the water hardness of the medium and can decrease with increasing water hardness (Diamond et al., 1992). These findings are contrary to our findings. This thesis shows that particularly the carbonate hardness of the media influenced the no-hatch effect of cobalt exposed zebrafish embryos which increased significantly with an increase in the carbonate-hardness of the standard ISO water (Chapter: 3.4.1.1 Cobalt toxicity related to carbonate hardness; Table 5; Figure 9). However, the study of Diamond et al. (Diamond et al., 1992) used daphnids (Ceriodaphnia dubia) and fathead minnow (Pimephales promelas) as freshwater species and they tested at a higher water hardness range than in this study. It may also be conceivable that the water hardness to toxicity correlation is not linear. Further studies would be necessary to confirm this assumption and to investigate the reasons for the opposing findings. Nonetheless, the question is raised whether the soft 1:5 ISO water is a good medium for testing metal toxicity in the FET. Most aquatic environments show much higher ionic strengths and carbonate hardness than the recommended ISO water and therefore ISO water is not the best and most representative medium to reflect the environmental relevance in this case.
Another important aspect focussed upon in this thesis was the difference between essential and non-essential metals. While the additional morphological and functional endpoints of the FET, as described in Chapter 3, showed no obvious difference between the essential and non-essential metals, it looked different at the transcriptome level. The zebrafish embryos responded
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differently to the non-essential metal cadmium than the essential metals cobalt and copper (Chapter 4 & Chapter 5). On the one hand, it was shown that the number of differentially expressed gene transcripts was higher for the non-essential metal and on the other hand, there was a difference between the two development stages of the embryos. The number of significant genes increased from 48 to 96 hpf for the non-essential cadmium and decreased for the essential metals copper and cobalt. These observations suggested that the embryos coped differently with the exposure to the metals. In case of the essential metals cobalt and copper, the embryos were presumably suitably equipped to deal with an excess of ions (thus, fewer genes were required overall) and consequently strived for homeostasis (what would explain the decrease in the transcriptome activity at 96 hpf). Contrary, in case of the non-essential metal cadmium, the ions caused adverse effects in the embryos and induced detoxification (Wood et al., 2012a, b). This would explain the overall stronger response and increase in the transcriptome activity over time. A different metabolic response to the non-essential metal cadmium in comparison to the essential metals cobalt and copper was indicated at gene transcription level also. In cadmium treated embryos, several transcripts of detoxification enzymes like glutathione-s-transferases (gsts) and metallothionein2 (mt2) were significantly regulated, while for copper and cobalt treated embryos this was not the case. Glutathione s-transferase and metallothioneins are well known biomarkers of oxidative stress and detoxification in fish and exposure of heavy metals to fish has been demonstrated many times to induce detoxification and oxidative stress response (Carvalho et al., 2012; Farombi et al., 2007; Schlenk et al., 2008; Sevcikova et al., 2011; Storey, 1996). Transcript expression of glutathione-s-transferase after cadmium exposure has been observed in different fish species such as European flounder (Sheader et al., 2006), pufferfish (Kim et al., 2010), in liver, gill and olfactory tissues of coho salmon (Espinoza et al., 2012) and in early life stage zebrafish (Jin et al., 2015). The findings suggest that gene transcripts of GST and metallothionein2 may be considered possible biomarkers of cadmium exposure also in zebrafish embryos. However, even if the presence of detoxification enzymes like GST are proven from the cleavage period (2-4 cell stage) in zebrafish embryos, the activity increases only after hatching (Wiegand et al., 2000). In addition to the fact that early life stages are particularly sensitive to chemical exposure, this would indicate a still incomplete detoxification system in non-hatched zebrafish embryos. The results of this thesis corroborate this assumption as a significant increase in the number and the expression of detoxification gene transcripts like gst was observed only in the hatched 96 hpf embryos and not the non-hatched 48 hpf embryos.
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Overall, this thesis could identify metallothionein2, glutathione-s-transferase gstm3, gsto2, gstp1 and gstp2, heat shock protein hsp70 and hsp70l as well as heme oxygenase hmox1a and hmox1b as possible indicators of detoxification or oxidative stress response after cadmium exposure of zebrafish embryos. Genes like hsp70l and homox1 were found regulated also in 5 dpf zebrafish embryos exposed to two Rhine River sediment extracts (Kosmehl et al., 2012). Sediments as pollutant reservoirs and sources are often strongly metal polluted. While in the study of Kosmehl et al. (2012) regulation of hsp70l was linked to the heavy metal cadmium, homox1 was not considerd a specific response. However, the regulation of homox1 gene only occurred in the sediment from Recklinghausen, were a slightly higher cadmium concentration was observed than in the other Rhine River sediment extracts. Furthermore, Wang and Gallagher (2013) reported increased glutathione S-transferase pi (gst pi), glutamate–cysteine ligase catalytic subunit (gclc), heme oxygenase 1 (hmox1) and peroxiredoxin 1 (prdx1) mRNA levels as indicative of Nrf2 (an oxidant-responsive nuclear transcription factor) activation in zebrafish larvae exposed for 3 h to cadmium. More recently, heme oxygenase enzymes were found significantly induced in adult zebrafish tissues (gill, brain and liver) as well as in zebrafish eleutheroembryos after cadmium exposure (Holowiecki et al., 2016). Altogether, this justifies a possible link of the heme oxygenase to the cadmium pollution, although most exposure effects are probably the result of interactions between the different pollutants of the sediment. To establish a direct causal connection between effect and only one particular pollutant of a sediment is difficult. Further, this thesis observed also few significantly regulated cytochrome P450s genes in 48 hpf zebrafish embryos exposed to the essential metals copper and cobalt, as cyp2p6 after cobalt and cyp19a1a and cyp19a1b after copper exposure. These results were unexpected. Both Cyp19 genes encode for the two isoforms of the steroidogenic enzyme aromatase, which are known to convert androgens to estrogens, thus the regulation of the two genes cyp19a1a and cyp19a1b could be associate with an endocrine disruption effect in copper treated zebrafish embryos. Some heavy metals are reported to induce endocrine disrupting effects in fish (Jezierska et al., 2009). With regard to the findings of this thesis, the results of a possible endocrine effect of copper corresponds with other studies in fish (Handy, 2003; Wang et al., 2015) and in toad larvae (Wang et al., 2016) were copper was suggested as an endocrine disrupting metal.
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6.3. General remark, conclusions and recommendations
In general, the results of the present thesis show that the additional test endpoints considered were more sensitive and informative than the standard morphological endpoints of the FET. In combination, these endpoints enabled a mechanistically enhanced metal toxicity evaluation. They can be instrumental for a better understanding of adverse effects of metals and the associated risks for the environment, and this certainly also for other aquatic toxicants. Other assets of the FET are that it is an easy and inexpensive tool, with possibilities for high- throughput applications. The neuromast and motor neuron damage assays are also suitable for ototoxicity and neurotoxicity drug screening. In combination with transcriptomics, the standard FET for acute toxicity can be transformed into an elucidating and versatile analysis tool. Specifically, this thesis demonstrates how to effectively enhance the FET to provide mechanistic information on the effects of essential and non-essential metals in fish early life stages. The gained mechanistic knowledge can e.g., feed into the refinement of adverse outcome pathways (AOPs) related to known adverse effects of metal exposure. The AOP framework can be useful to collect, organize and generalize existing toxicity-related knowledge (Groh, Ksenia J. et al., 2015). For example, Brix et al. (2017) recently observed mechanisms of nickel toxicity in aquatic environments by AOP analysis and identified knowledge gaps for further research.
An important aspect to be considered when describing the realistic impact of metals on the environment is the bioavailability. The toxicity of metals is highly dependent on abiotic parameters concerning the testing medium. We showed for instance, an increasing toxicity of cobalt with increasing water hardness, which was contrary to general assumptions about the metal toxicity to water hardness correlation. Comparable studies on the effect of cobalt in zebrafish embryos using ISO-water are missing, and only studies having used a different medium of a higher carbonate hardness and ionic strength reported also inhibition of hatching (Cai et al., 2012; Dave and Xiu, 1991). As outlined earlier, the results of FETs with metals have only very limited value for aquatic risk or hazard evaluations if the carbonate hardness and conductivity of the ISO are not adjusted to environmentally relevant levels.
In conclusion, this thesis point out the neuro- and ototoxic potential of cadmium, cobalt and copper in zebrafish embryos through the additional fluorescence staining endpoints as well as on transcriptome level. The gene transcription results revealed some of the molecular mechanisms behind those effects. This thesis could demonstrate that large scale transcriptomics
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can be a very useful approach when integrated with the FET, as it can provide an enormous amount of transcriptional information simultaneously.
Overall, this thesis evaluated additional test methods in terms of the FET and further, several mechanisms and connections of the metal exposure effects could be specified, quantified and elucidated. Thus, the initially defined objectives were successfully answered in the course of this thesis. Moreover, it was shown that the additional fluorescence staining endpoints as well as the gene expression analysis can be more sensitive indicators for metal toxicity in zebrafish embryos than current test methods applied in the ecological risk assessment. Therefore, the results of this thesis indicate that there is still potential and opportunity, to improve the standardized test methods (such as the FET) and to optimize their sensitivity and validity for testing the impact of substances on the environment. Although the effect evaluation for organisms in laboratory tests has already been improved in many ways over the years in compliance with the 3R principle, there is still a need to improve the existing tests and endpoints in their sensitivity in order to detect effects at low concentration ranges at an early stage. This is necessary to sustainably protect the aquatic communities because in the environment different stressors (such as the simultaneous exposure of several environmental toxicants at low concentrations) can result in multifactorial stress. Already low concentrations of a substance can have an enormous influence on the ecosystem, and it is indispensable to recognize these effects prematurely and to understand the mechanisms of toxicity of the substances in detail to apply the most appropriate protective measures. This thesis has been able to make an important contribution to this challenge.
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Erklärung
Erklärung
Ich versichere, dass ich diese Doktorarbeit selbständig und nur unter Verwendung der angegebenen Hilfsmittel angefertigt habe. Weiterhin versichere ich, die genutzten Quellen als solche kenntlich gemacht zu haben.
Laura Sonnack Aachen, am 31. August 2017
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Danksagung
Danksagung
An dieser Stelle möchte ich mich bei all denjenigen bedanken, die mich während meiner Doktorarbeit unterstützt haben. Mein ganz besonderer Dank gilt: Prof. Dr. Henner Hollert für die kompetente universitäre Betreung und Begutachtung der Arbeit. Vielen Dank für die Hilfe und Unterstützung auch bei den Veröffentlichungen. Prof. Dr. Andreas Schäffer für die bereitwillige Übernahme des Korreferats. Ein ausserordentliche Dank geht an Dr. Martina Fenske für super Betreuung und die Möglichkeit, mittels des Fraunhofer internen Doktoranndinen-Stipendium, meine Arbeit in ihrer Arbeitsgruppe am Fraunhofer IME anfertigen zu können. Ich danke dir ganz besonders für deine fachkundige Unterstützung in jeder Hinsicht! Dr. Thorsten Klawonn, Dr. Christoph Schäfers, PD Dr. Lothar Erdinger und Nicole Henny möchte ich besonders für die routinierte analytische Analyse der Metall-Lösungen danken. Dr. Ralf Kriehuber für die Möglichkeit die Microarray-Experimente im Labor der Abteilung für Sicherheit und Strahlenschutz des Forschungszentrums Jülich durchzuführen. Ohne diese Möglichkeit wäre ein großer Teil meiner Arbeit nicht Zustande gekommen. Ein besonderer Dank geht hier auch an Dominik Oskamp der mir während der Microarray-Versuche mit Rat und Tat zur Seite stand und so stets für eine äußerst kompetente Unterstützung sorgte. Herzlichen Dank dafür! Dr. Viktoria Schiller danke ich für die Hilfestellung bei der sehr umfangreiche Microarray- Auswertung, sowie ihr immer offenes Ohr und die schöne Zeit auch im privaten Umfeld. Danke! Tom Lingner für die erfahrene praxische Unterstützung bei dem qPCR Versuchen. Du hast so eine großen Teil zu der erfolgreichen Validierung meiner Microarray-Ergebnisse beigetragen. Vielen Dank auch für die vielen schönen Momente in den Pausen und zwischendurch! Allen weiteren Kolleginnen und Kollegen der Fischgruppe am Fraunhofer IME möchte ich für das immer nette Arbeitsklima danken. Namentlich möchte ich mich ganz besonders bei Vera Delov, Elke Muth-Köhne, Luisa Reiner und Jan Weckauf auch für die tolle Zeit außerhalb der Arbeit bedanken!
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Curriculum Vitae
Curriculum Vitae
Personal Information
First Name/ Surname: Laura Sonnack
Educations
2012 - 2018 PhD student RWTH-Aachen University (Department of Ecosystem Analysis) Topic: „Enhanced applications of the zebrafish (Danio rerio) embryo toxicity test as a model to mechanistically differentiate metal toxicity effects in fish “ at Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany (01.10.2012 - 31.03.2016)
2009 - 2012 Biological and environmental process engineering Master studies at University of Applied Sciences, Rüsselsheim Degree: Master of Engineering Topic of thesis: “The toxicity of silver nanoparticles to zebrafish embryos increases through sewage treatment processes “ at Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany
2003 - 2009 Biological process engineering Bachelor studies at University of Applied Sciences, Frankfurt Degree: Bachelor of Engineering Topic of thesis: „Biotechnological production of chitosan with the mucor fungus, Absidia coerulea (DSM 3018) after the addition of various surfactants “
Work Experience
2012 - 2016 Scientific assistant at Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany (PhD Thesis)
2012 6-month Work & Travel in New Zealand
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Curriculum Vitae
2011 Scientific assistant at Fraunhofer Institute for Molecular Biology and Applied Ecology IME, Aachen, Germany (Master Thesis)
2010 19-week internship in Fort Collins (USA) Department of Chemical & Biological Engineering Colorado State University Project: Microbial production of biofuels from lignin
2008 - 2009 Scientific assistant at laboratory Biological process engineering at University of Applied Sciences Frankfurt/Main (Bachelor Thesis)
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Publication List
Publication List
Research articles in international peer-reviewed journals
Sonnack L., Klawonn T., Kiehuber R., Hollert H., Schäfers C., Fenske M. (2017) Comparative analysis of the transcriptome responses of zebrafish embryos after exposure to low concentrations of essential and non-essential metals. Comparative Biochemistry and Physiology - Part D: Genomics and Proteomics; Vol. 25, Page 99-108, December 2017.
Sonnack L., Klawonn T., Kiehuber R., Hollert H., Schäfers C., Fenske M. (2017) Concentration-dependent gene expression in zebrafish embryos after exposure to cadmium, cobalt and copper. Comparative Biochemistry and Physiology - Part D: Genomics and Proteomics, Vol. 24, Page 29-40, July 2017.
Sonnack L., Kampe S., Muth-Köhne E., Erdinger L., Henny N., Hollert H., Schäfers C., Fenske M. (2015) Motor neuron development, neuromasts and the escape response as valuable endpoints to assess metal toxicity in zebrafish embryo tests. Neurotoxicology and Teratology, Vol. 50, Page 33-42, Jul-Aug. 2015.
Muth-Köhne E., Sonnack L., Schlich K., Hischen F., Baumgartner W., Hund-Rinke K., Schäfers C., Fenske M. (2013) The toxicity of silver nanoparticles to zebrafish embryos increases through sewage treatment processes. Ecotoxicology, Vol. 22, Issue 8, Page 1264–1277, October 2013
Platform presentations (Presenters are underlined)
Fenske M., Muth-Köhne E., Delov V., Sonnack L., Kampe S., Schäfers C. (2015) Detection and validation of molecular biomarkers for neurotoxicity in fish embryos (NTX31). 55th Annual Meeting of the Teratology Society, June 27-July1, Montréal, Canada
Sonnack L., Kampe S., Muth-Köhne E., Henny N., Erdinger L., Hollert H., Fenske M. (2014) Motor neuron and neuromast damage as new endpoints to explain metal toxicity in the zebrafish embryo toxicity test. SETAC Europe 24th Annual Meeting, May 11-15, Basel, Switzerland
Muth-Köhne E., Sonnack L., Schlich K., Hischen F., Baumgartner W., Hund-Rinke K., Schäfers C., Fenske M. (2012) Untersuchungen zur Wirkung von Silber- Nanopartikeln im Fischeitest unter Berücksichtigung von Klärprozessen. 5. Gemeinsame Jahrestagung von SETAC German Language Branch und GDCh, September 10-13, UFZ Leipzig, Germany
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Publication List
Poster presentations (Presenters are underlined)
Sonnack L., Muth-Köhne E., Kampe S., Schlich K., Hund-Rinke K., Hischen F., Baumgartner W., Hollert H., Fenske M. (2013) Investigating fundamental characteristic of metal toxicity in zebrafish (Danio rerio) embryos. SETAC Europe 23th Annual Meeting, May 12-16, Glasgow, United Kingdom
Sonnack L., Muth-Köhne E., Schlich K., Hund-Rinke K., Hollert H., Fenske M. (2013) Investigating fundamental characteristics of metal toxicity in zebrafish embryos. 3rd Young Environmental Scientists (YES) Meeting, February 11-13, Krakow, Poland
Sonnack L., Muth-Köhne E., Schlich K., Hund-Rinke K., Schäfers C., Debus R., Fenske M. (2012) Investigations on the effects of silver nanoparticles in the zebrafish embryo toxicity test, with consideration of sewage treatment processes. SETAC Europe 22th Annual Meeting, May 20-24, Berlin, Germany
Sonnack L., Muth-Köhne E., Schlich K., Hund-Rinke K., Debus R., Fenske M. (2011) Untersuchungen zur Wirkung von Silber-Nanopartikeln im Zebrafisch-Embryotest - unter Berücksichtigung von Kläranlagenprozessen. 16th SETAC German Language Branch Annual Meeting, September 18-20, Koblenz-Landau, Germany
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Supplements
Supplements
A. List of chemicals, consumables and equipment
A.1. Chemicals, reagents and antibodies used in this thesis
Metals, chemicals and other Use CAS Nr. Supplier Order number reagents Cadmium chloride Tested metal 10108-64-2 Sigma-Aldrich 655198 (CdCl2) Cobalt(II) sulfate Tested metal 10026-24-1 Sigma-Aldrich C6768 heptahydrate (CoSO4.7H2O) Copper sulfate Tested metal 7758-98-7 Sigma-Aldrich 61230 (CuSO4) Ethanol ROTIPURAN®, Positive control, 64-17-5 Carl Roth 9065 purity ≥ 99.8% RNA isolation Neomycin trisulfate salt Positive control 1405-10-3 Sigma-Aldrich N1876 hydrate Cis-Diamineplatinum(II) Positive control 15663-27-1 Sigma-Aldrich P4394 dichloride Calcium chloride Salt ISO water 10043-52-4 Carl Roth 5239 (CaCl2.2H2O) Magnesium sulphate Salt ISO water 22189-08-8 Carl Roth P027 (MgSO4.7H2O) Sodium hydrogen carbonate Salt ISO water 144-55-8 Carl Roth 6885 (NaHCO3) Potassium chloride Salt ISO water 7447-40-7 Carl Roth 6781 (KCl) Salt PBS Puffer Sodium chloride Salt PBS Puffer 7647-14-5 Carl Roth P029 (NaCl) di-Sodium hydrogen Salt PBS Puffer 7558-79-4 Carl Roth P030 phosphate dihydrate (Na2HPO4) Potassium hydrogen Salt PBS Puffer 7778-77-0 Carl Roth 3904 phosphate (KH2PO4) Triton X-100 Additive 9002-93-1 Sigma-Aldrich X100-5ML PBS-Triton Znp1, mouse monoclonal Primary Developmental antibody (IgG2a) antibody (staining) Hybridoma Bank for PMNs Zn8, mouse monoclonal Primary Developmental antibody (IgG1) antibody (staining) Hybridoma Bank for SMNs DyLight 549-conjugated Secondary Jackson Immuno AffiniPure Goat Anti-Mouse antibody (staining) Research Europe IgG, specific for Fc subclass 1 DyLight 649-conjugated Secondary Jackson Immuno AffiniPure Goat Anti-Mouse antibody (staining) Research Europe IgG, specific for Fc subclass 2a DASPEI Vital dye 3785-01-1 Life D-426 (2-(4-(dimethylamino)styryl)- (vital staining) Technologies N-ethylpyridinium) Paraformaldehyde Antibody staining 30525-89-4 Sigma Aldrich 0335
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Normal goat serum Antibody staining Sigma Aldrich G9023
Methylcellulose Embedding 9004-67-5 Sigma-Aldrich M0387 medium staining Chloroform, minimum 99% RNA-Isolations 67-66-3 Sigma-Aldrich C2432
TRIzol® reagent RNA-Isolations Sigma-Aldrich T9424
Qiagen RNeasy Mini Kit RNA-Isolations QIAGEN GmbH 74106 Microarray Agilent RNA 6000 Nano Kit Verification of Agilent 5067-1511 RNA Quality Technologies RNA Spike-In Kit, One- Microarray Agilent 5188-5282 Color Technologies Zebrafish (V3) Gene Microarray Agilent G2519F-026437 Expression Microarray 4 x Technologies 44K Kit One-Color Microarray (Low Microarray Agilent 5190-2305 Input Quick Amp Labeling; Technologies v6.6, September 2012) SYBR®GreenER qPCR qPCR Invitrogen 11761500 SuperMix SuperScript® IV Reverse Transcription Invitrogen 18090010 Transcriptase dNTPs Transcription Invitrogen 18427013
Random Hexamers Transcription Invitrogen N8080127
A.2. Consumables used in this thesis
Consumables Manufacturer Order number Barrier tips Nerbe Plus 10 µl 07-613-7300 100 µl 07-642-7300 200 µl 07-662-7300 100 - 1000 µl 07-692-7300 Cover glass Carl Roth H873.2
Cover sheeting (polystyrene well plates) Greiner Bio-One 676001
Disposable pasteur pipette (0.9 µl) Carl Roth EA57.1
Disposable weighing pan Carl Roth p652.1
Eppendorf reaction tubes (1.5 mL) VWR 525-0674
Glass pasteur pipette VWR 612-1702
Glass pipette VWR 5 mL 734-1691 10 mL 734-1693 25 mL 734-1695 Microscope slide Carl Roth H871.1
Parafilm M Brand 701606
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Supplements
Petri dishes VWR 90mm 391-0441 55mm 391-0866 Pipette tips VWR 200 µl 612-5755 1000 µl 613-0377 Polystyrene Greiner Bio-One 96 well plates 650101 24 well plates 662160
qPCR-plates VWR 211-0315
A.3. Equipment used in this thesis
Equipment Type Manufacturer Air pumps Tetratec ABS 300 Tetra
Analytical balance AB 104-S-A Mettler- Toledo Bioanalyzer Agilent 2100 Bioanalyzer Agilent Technologies Centrifuge Centrifuge Z2 16 MK Hermle Labortechnik Centrifuge Micro Centrifuge IR Carl Roth
Centrifuge Centrifuge 5415 R Eppendorf
Fluorescence microscope DMI 6000B /AF6000 Leica, system Germany Hot plate stirrer Stuart hotplate stirrer SB162 Bibby Scientific Limited, UK Hybridization oven (65 °C) Agilent Microarray Agilent Hybridization oven Technologies Incubator Model no.: 78532 W+C Binder, Germany Inverted bright field Labovert FS Leitz, microscope Germany Magnetic stirrer BIG squid IKA, Germany Magnetic stirrer HEI-MIX S Heidolph instruments, Germany Microarray Scanner Agilent G2565CA Agilent Microarray Scanner System Technologies Oxi-meter WTW 330i WTW GmbH, Germany pH-meter HI 221 Hama instruments, USA Pipette 2, 10, 20, 200, 1000 and 5000 μl Gilson, USA Pipette 10,20,200 μl Eppendorf, Germany Shaker MS3 digital IKA, Germany Spectrophotometer NanoDrop 1000 Thermo Fisher spectrophotometer Scientific Stereo microscope SZX2-ILLB Olympus Microscopy, Japan ______127
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Stereo microscope S6 Leica, Germany Vortex Lab dancer IKA, Germany
B. Heat maps representing GO enrichment analysis
Figure S.1: Heat maps representing GO enrichment analysis, showing the involvement of all differentially expressed GOs in biological processes in 48 hpf and 96 hpf zebrafish embryos after exposure to cadmium concentrations of C1 = 0.9, C2 = 1.8 and C3 = 3.3 mg/L. Upregulation (yellow) and downregulation (blue) are indicated by shading representing log10 p-values. For this functional analysis, the fold change cutoff was set to 1.1 and gene set enrichhment was performed using a logistic model (p-value cutoff = 0.05).
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Figure S.2: Heat maps representing GO enrichment analysis, showing the involvement of all differentially expressed GOs in biological processes in 48 hpf and 96 hpf zebrafish embryos after exposure to cobalt concentrations of C1 = 0.5, C2 = 1.4 and C3 = 3.6 mg/L. Upregulation (yellow) and downregulation (blue) are indicated by shading representing log10 p-values. For this functional analysis, the fold change cutoff was set to 1.1 and gene set enrichment was performed using a logistic model (p-value cutoff = 0.05).
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Figure S.3: Heat maps representing GO enrichment analysis, showing the involvement of all differentially expressed GOs in biological processes in 48 hpf and 96 hpf zebrafish embryos after exposure to copper concentrations of C1 = 1.7, C2 = 2.5 and C3 = 6.1 µg/L. Upregulation (yellow) and downregulation (blue) are indicated by shading representing log10 p-values. For this functional analysis, the fold change cutoff was set to 1.1 and gene set enrichment was performed using a logistic model (p-value cutoff = 0.05).
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C. List of significantly KEGG-Pathway of Gene Set Enrichment Analysis
"KEGG-Pathway" of Gene Set Enrichment Analysis. restricted to annotated genes ranked by their corrected p-value. using the logistic model available on the babelomics4 platform (http://v4.babelomics.org). The p-value cutoff was set to 0.05
KEGG-Pathway of Gene Set Enrichment Analysis Cadmium (3.3 mg Cd/L) treated 48 hpf embryos KEGG Description Log10 dre00010 Glycolysis / Gluconeogenesis 3.20290965 dre00030 Pentose phosphate pathway 1.53613096 dre00051 Fructose and mannose metabolism 2.53411368 dre00480 Glutathione metabolism 1.74753162 dre00512 Mucin type O-Glycan biosynthesis -2.01149371 dre00601 Glycosphingolipid biosynthesis - lacto and neolacto series -1.59305109 dre00980 Metabolism of xenobiotics by cytochrome P45 2.28363496 dre00982 Drug metabolism - cytochrome P450 2.57259034 dre03040 Spliceosome -8.80415081 dre04010 MAPK signaling pathway -2.70667271 dre04060 Cytokine-cytokine receptor interaction 2.61215666 dre04144 Endocytosis -1.43935532 dre04514 Cell adhesion molecules (CAMs) 1.34902878 dre04620 Toll-like receptor signaling pathway 2.19950866 dre04672 Intestinal immune network for IgA production 4.52588589 dre04910 Insulin signaling pathway 1.69779541
KEGG-Pathway of Gene Set Enrichment Analysis Cadmium (3.3 mg Cd/L) treated 96 hpf embryos KEGG Description Log10 dre00260 Glycine. serine and threonine metabolism 3.16245081 dre00600 Sphingolipid metabolism 2.1311753 dre02010 ABC transporters 2.87297422 dre03040 Spliceosome -8.2898383 dre04010 MAPK signaling pathway -8.93751161 dre04144 Endocytosis 5.49562348
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KEGG-Pathway of Gene Set Enrichment Analysis Cobalt (3.6 mg Co/L) treated 48 hpf embryos KEGG Description Log10 dre00062 Fatty acid elongation -2.18500679 dre00190 Oxidative phosphorylation -8.88550169 dre00240 Pyrimidine metabolism -1.76243702 dre00514 Other types of O-glycan biosynthesis -1.34964427 dre00563 Glycosylphosphatidylinositol(GPI)-anchor biosynthesis -1.7768847 dre00591 Linoleic acid metabolism -1.70364168 dre00830 Retinol metabolism -3.54141769 dre03010 Ribosome -1.53221599 dre03018 RNA degradation 3.35080166 dre03022 Basal transcription factors -1.37064043 dre03050 Proteasome 3.98170271 dre03410 Base excision repair -1.71720454 dre03420 Nucleotide excision repair -1.69424223 dre04142 Lysosome -1.327465 dre04260 Cardiac muscle contraction 3.58436779 dre04340 Hedgehog signaling pathway -2.56348039 dre04510 Focal adhesion 2.32643433 dre04810 Regulation of actin cytoskeleton 1.74483001 dre04920 Adipocytokine signaling pathway -3.01466005
KEGG-Pathway of Gene Set Enrichment Analysis Cobalt (3.6 mg Co/L) treated 96 hpf embryos KEGG Description Log10 dre04060 Cytokine-cytokine receptor interaction -1.39122969 dre04514 Cell adhesion molecules (CAMs) -1.40324788
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KEGG-Pathway of Gene Set Enrichment Analysis Copper (6.1 µg Cu/L) treated 48 hpf embryos KEGG Description Log10 dre00020 Citrate cycle (TCA cycle) -1.82758436 dre00071 Fatty acid degradation -1.75379783 dre00190 Oxidative phosphorylation -1.59223081 dre00330 Arginine and proline metabolism -1.39039943 dre00592 alpha-Linolenic acid metabolism -1.35563177 dre01100 Metabolic pathways -3.2427886 dre03010 Ribosome 2.30503885 dre03040 Spliceosome 2.38230748 dre04012 ErbB signaling pathway 1.92687293 dre04080 Neuroactive ligand-receptor interaction -1.55622159 dre04110 Cell cycle 3.49458471 dre04114 Oocyte meiosis 3.81129154 dre04115 p53 signaling pathway 4.85801585 dre04144 Endocytosis 2.01607697 dre04146 Peroxisome -1.31577719 dre04310 Wnt signaling pathway 3.51647208 dre04320 Dorso-ventral axis formation 1.65642329 dre04330 Notch signaling pathway -7.39141684 dre04350 TGF-beta signaling pathway 3.12431077 dre04520 Adherens junction 2.08331782 dre04914 Progesterone-mediated oocyte maturation 2.20077206 dre04916 Melanogenesis 2.88946683
KEGG-Pathway of Gene Set Enrichment Analysis Copper (6.1 µg Cu/L) treated 96 hpf embryos KEGG Description Log10 dre00010 Glycolysis / Gluconeogenesis -1.91887574 dre00190 Oxidative phosphorylation -2.29836934 dre00270 Cysteine and methionine metabolism 1.38641342 dre00480 Glutathione metabolism 2.16471318 dre00531 Glycosaminoglycan degradation 1.6936919 dre00970 Aminoacyl-tRNA biosynthesis 1.30765851 dre00982 Drug metabolism - cytochrome P450 1.41713859 dre03010 Ribosome -4.9010961 dre03410 Base excision repair 1.47860793 dre03440 Homologous recombination 1.37240642 dre04110 Cell cycle 1.58572954 dre04114 Oocyte meiosis 1.38047378 dre04140 Regulation of autophagy 1.62065389 dre04150 mTOR signaling pathway 2.42641781 dre04260 Cardiac muscle contraction -2.53948017 dre04330 Notch signaling pathway 1.51570197 dre04514 Cell adhesion molecules (CAMs) -2.4135347
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dre04620 Toll-like receptor signaling pathway 1.73012879 dre04914 Progesterone-mediated oocyte maturation 2.75516513
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D. List of significant differentially expressed genes
Significant Genes after analysis of variance (ANOVA) on normalized microarray data performed using GeneSpring Software GX (Agilent Technologies); Tukey’s Honestly Significant Difference (HSD) test was carried out as post hoc test, applying an asymptotic p- value computation; the p-value cut-off was set to 0.05. To adjust for multiple comparisons, the multiple testing correction of Benjamini Hochberg false discovery rate (FDR) was used.
Significant Genes of analysis of variance Cadmium (3.3 mg Cd/L) treated 48 hpf embryos Gene p-value Symbol Description (Corr) gem Danio rerio GTP binding protein overexpressed in skeletal muscle (gem), mRNA [NM_001045849] 2.79E-12 rom1a Danio rerio retinal outer segment membrane protein 1a (rom1a), mRNA [NM_200794] 3.26E-12 mt2 Danio rerio metallothionein 2 (mt2), mRNA [NM_001131053] 4.06E-12 LOC566865 Danio rerio hypothetical LOC566865, mRNA (cDNA clone IMAGE:7044508), partial cds. [BC134901] 4.39E-12 cx27.5 Danio rerio connexin 27.5 (cx27.5), mRNA [NM_131811] 7.17E-12 cyb5r2 Danio rerio cytochrome b5 reductase 2 (cyb5r2), mRNA [NM_001045360] 1.58E-11 klf9 Danio rerio Kruppel-like factor 9 (klf9), mRNA [NM_001128729] 9.29E-11 LOC1001502 20 Danio rerio uncharacterized LOC100150220 (LOC100150220), mRNA [NM_001128575] 9.69E-11 vip Danio rerio vasoactive intestinal peptide (vip), mRNA [NM_001114553] 1.14E-10 atp2b3b Danio rerio ATPase, Ca++ transporting, plasma membrane 3b (atp2b3b), mRNA [NM_001128242] 1.21E-10 calcium/calmodulin-dependent protein kinase (CaM kinase) II beta 2 [Source:ZFIN;Acc:ZDB-GENE- LOC798222 090312-34] [ENSDART00000133694] 1.44E-10 cell death-inducing DFFA-like effector a [Source:ZFIN;Acc:ZDB-GENE-091204-339] cidea [ENSDART00000087201] 3.02E-10 crygm5 Danio rerio crystallin, gamma M5 (crygm5), mRNA [NM_001007058] 7.47E-10 krtt1c19e Danio rerio si:dkeyp-113d7.4 (si:dkeyp-113d7.4), mRNA [NM_001114342] 1.19E-09 si:ch211- 214p13.3 si:ch211-214p13.3 [Source:ZFIN;Acc:ZDB-GENE-060503-779] [ENSDART00000129107] 1.89E-09 LOC1000058 79 Uncharacterized protein [Source:UniProtKB/TrEMBL;Acc:E7F4I5] [ENSDART00000111020] 2.52E-09 si:dkey- 7e14.7 si:dkey-7e14.7 [Source:ZFIN;Acc:ZDB-GENE-121214-164] [ENSDART00000112909] 3.02E-09 Danio rerio cytidine monophospho-N-acetylneuraminic acid hydroxylase (cmah), mRNA cmah [NM_001002192] 1.23E-08 ecrg4a Danio rerio esophageal cancer related gene 4a (ecrg4a), mRNA [NM_001017697] 1.25E-08 plac8.1 Danio rerio placenta-specific 8, tandem duplicate 1 (plac8.1), mRNA [NM_001033097] 1.73E-08 fkbp5 Danio rerio FK506 binding protein 5 (fkbp5), mRNA [NM_213149] 1.88E-08 stk35 Danio rerio serine/threonine kinase 35 (stk35), mRNA [NM_001077616] 1.96E-08 nck2b Danio rerio NCK adaptor protein 2b (nck2b), mRNA [NM_001003492] 2.12E-08 si:dkey- 226m8.7 Danio rerio si:dkey-226m8.7 (si:dkey-226m8.7), mRNA [NM_001110287] 3.03E-08 Danio rerio transient receptor potential cation channel, subfamily V, member 6 (trpv6), mRNA trpv6 [NM_001001849] 4.07E-08 zgc:73226 Danio rerio zgc:73226 (zgc:73226), mRNA [NM_205570] 5.21E-08 s100a11 Danio rerio S100 calcium binding protein A11 (s100a11), mRNA [NM_001282183] 6.60E-08 Danio rerio leucine-rich repeat, immunoglobulin-like and transmembrane domains 2 (lrit2), mRNA lrit2 [NM_001020536] 8.29E-08 foxq1b Danio rerio forkhead box Q1b (foxq1b), mRNA [NM_212907] 1.01E-07 agxtb Danio rerio alanine-glyoxylate aminotransferase b (agxtb), mRNA [NM_213162] 2.85E-07 evplb envoplakin b [Source:ZFIN;Acc:ZDB-GENE-030131-212] [ENSDART00000082000] 4.10E-07 ccdc85a Danio rerio coiled-coil domain containing 85A (ccdc85a), mRNA [NM_001114913] 7.20E-07 ______135
Supplements
hsp70l Danio rerio heat shock cognate 70-kd protein, like (hsp70l), mRNA [NM_001113589] 8.68E-07 cldn10l2 claudin 10-like 2 [Source:ZFIN;Acc:ZDB-GENE-030131-9598] [ENSDART00000062404] 1.17E-06 fam84b Danio rerio family with sequence similarity 84, member B (fam84b), mRNA [NM_001044880] 1.48E-06 hsp70 Danio rerio heat shock cognate 70-kd protein (hsp70), mRNA [NM_131397] 2.17E-06 gig2o Danio rerio grass carp reovirus (GCRV)-induced gene 2o (gig2o), mRNA [NM_001245983] 2.47E-06 LOC1000050 PREDICTED: Danio rerio hypothetical protein LOC100005016 (LOC100005016), mRNA 16 [XM_001344137] 2.49E-06 hsp70 Danio rerio heat shock cognate 70-kd protein (hsp70), mRNA [NM_131397] 3.35E-06 zgc:174938 Danio rerio zgc:174938 (zgc:174938), mRNA [NM_001105700] 4.81E-06 pdx1 Danio rerio pancreatic and duodenal homeobox 1 (pdx1), mRNA [NM_131443] 5.00E-06 cryba1b Danio rerio crystallin, beta A1b (cryba1b), mRNA [NM_001002586] 7.02E-06 gstm3 Danio rerio glutathione S-transferase M3 (brain) (gstm3), mRNA [NM_001162851] 1.50E-05 cldnf Danio rerio claudin f (cldnf), mRNA [NM_131766] 1.87E-05 fstl4 Danio rerio follistatin-like 4 (fstl4), mRNA [NM_001031843] 2.26E-05 hsp70 Danio rerio heat shock cognate 70-kd protein (hsp70), mRNA [NM_131397] 2.28E-05 Danio rerio heat shock protein 90, alpha (cytosolic), class A member 1, tandem duplicate 2 (hsp90aa1.2), hsp90aa1.2 mRNA [NM_001045073] 2.54E-05 ATP-binding cassette, sub-family B (MDR/TAP), member 5 [Source:ZFIN;Acc:ZDB-GENE-030131- abcb5 6414] [ENSDART00000079185] 2.97E-05 si:ch211- 157c3.4 Danio rerio si:ch211-157c3.4 (si:ch211-157c3.4), mRNA [NM_001164368] 3.36E-05 esr2a Danio rerio estrogen receptor 2a (esr2a), mRNA [NM_180966] 5.40E-05 hsp70l Danio rerio heat shock cognate 70-kd protein, like (hsp70l), mRNA [NM_001113589] 9.65E-05 si:dkey- 193b15.6 si:dkey-193b15.6 [Source:ZFIN;Acc:ZDB-GENE-070912-414] [ENSDART00000084859] 1.02E-04 si:dkey- AGENCOURT_69630133 NIH_ZGC_29 Danio rerio cDNA clone IMAGE:8353820 5', mRNA sequence 92i15.4 [DY557637] 2.04E-04 zgc:91985 Danio rerio zgc:91985 (zgc:91985), mRNA [NM_001003499] 2.58E-04 si:ch211- 79k12.1 Danio rerio si:ch211-79k12.1 (si:ch211-79k12.1), mRNA [NM_001083848] 5.20E-04 si:dkey- 61p9.6 Danio rerio si:dkey-61p9.6 (si:dkey-61p9.6), mRNA [NM_001044881] 5.53E-04 growth regulation by estrogen in breast cancer 1 [Source:ZFIN;Acc:ZDB-GENE-070112-332] greb1 [ENSDART00000076611] 5.98E-04 capns1b Danio rerio calpain, small subunit 1 b (capns1b), mRNA [NM_001109706] 7.23E-04 ints2 integrator complex subunit 2 [Source:ZFIN;Acc:ZDB-GENE-050522-148] [ENSDART00000023545] 8.92E-04 si:ch211- 157c3.4 Danio rerio si:ch211-157c3.4 (si:ch211-157c3.4), mRNA [NM_001164368] 9.48E-04 cth1 Danio rerio cth1 (cth1), mRNA [NM_130939] 1.17E-03 si:ch1073- 170o4.1 DR_ATE_NRM05_E07 adult testis normalized (TLL) Danio rerio cDNA, mRNA sequence [CO355144] 1.30E-03 znf366 zinc finger protein 366 [Source:ZFIN;Acc:ZDB-GENE-110408-46] [ENSDART00000058674] 1.75E-03 klf11b Danio rerio Kruppel-like factor 11b (klf11b), mRNA [NM_001077604] 1.82E-03 baiap2l2 Danio rerio BAI1-associated protein 2-like 2 (baiap2l2), mRNA [NM_001080804] 1.93E-03 stc1l Danio rerio stanniocalcin 1, like (stc1l), mRNA [NM_200539] 2.57E-03 zgc:154086 Danio rerio zgc:154086 (zgc:154086), mRNA [NM_001077327] 2.59E-03 hoxc13a Danio rerio homeo box C13a (hoxc13a), mRNA [NM_131543] 2.98E-03 paqr8 Danio rerio progestin and adipoQ receptor family member VIII (paqr8), mRNA [NM_183344] 5.35E-03 zgc:112994 Danio rerio zgc:112994 (zgc:112994), mRNA [NM_001020707] 5.37E-03 capn2b Danio rerio calpain 2, (m/II) large subunit b (capn2b), mRNA [NM_001018227] 8.22E-03 anxa1a Danio rerio annexin A1a (anxa1a), mRNA [NM_181758] 8.57E-03 zgc:85866 Danio rerio zgc:85866 (zgc:85866), mRNA [NM_001001826] 8.63E-03 jdp2 Danio rerio Jun dimerization protein 2 (jdp2), mRNA [NM_001002493] 9.12E-03 kif5ba kinesin family member 5B, a [Source:ZFIN;Acc:ZDB-GENE-070629-2] [ENSDART00000113849] 1.00E-02 ______136
Supplements
capn2b Danio rerio calpain 2, (m/II) large subunit b (capn2b), mRNA [NM_001018227] 1.06E-02 wu:fd44f01 Danio rerio wu:fd44f01 (wu:fd44f01), mRNA [NM_001201560] 1.19E-02 fos Danio rerio v-fos FBJ murine osteosarcoma viral oncogene homolog (fos), mRNA [NM_205569] 1.19E-02 Danio rerio potassium voltage-gated channel, Shaw-related subfamily, member 4 (kcnc4), mRNA kcnc4 [NM_001195196] 1.19E-02 LOC1000006 36 Danio rerio cDNA clone IMAGE:7148368. [BC091689] 1.21E-02 klf11a Danio rerio Kruppel-like factor 11a (klf11a), mRNA [NM_001044941] 1.35E-02 ugt5g2 Danio rerio UDP glucuronosyltransferase 5 family, polypeptide G2 (ugt5g2), mRNA [NM_001199376] 2.21E-02 odf3b Danio rerio outer dense fiber of sperm tails 3B (odf3b), mRNA [NM_199958] 2.40E-02 and3 Danio rerio actinodin3 (and3), mRNA [NM_001025511] 2.44E-02 diras1b Danio rerio DIRAS family, GTP-binding RAS-like 1b (diras1b), mRNA [NM_001126421] 2.53E-02 FDR306-P00011-DEPE-F_K17 FDR306 Danio rerio cDNA clone FDR306-P00011-BR_K17 5', mRNA wu:fj88f11 sequence [EH582267] 2.63E-02 and3 Danio rerio actinodin3 (and3), mRNA [NM_001025511] 2.72E-02 LOC1001486 88 Uncharacterized protein [Source:UniProtKB/TrEMBL;Acc:H9GX58] [ENSDART00000003955] 2.99E-02 AGENCOURT_16394323 NIH_ZGC_7 Danio rerio cDNA clone IMAGE:7036568 5', mRNA sequence wu:fb79b02 [CF996132] 3.39E-02 si:ch211- 281g13.5 Danio rerio si:ch211-281g13.5 (si:ch211-281g13.5), mRNA [NM_001145631] 3.52E-02 si:rp71- 15d4.1 leupaxin [Source:HGNC Symbol;Acc:14061] [ENSDART00000139647] 3.54E-02 LOC1003342 91 mucin 5B, oligomeric mucus/gel-forming [Source:HGNC Symbol;Acc:7516] [ENSDART00000127111] 4.15E-02 LOC1018830 17 si:ch211-51i16.3 [Source:ZFIN;Acc:ZDB-GENE-131127-411] [ENSDART00000074110] 4.23E-02 esrrd estrogen-related receptor delta [Source:ZFIN;Acc:ZDB-GENE-040616-3] [ENSDART00000125432] 4.58E-02
Significant Genes of analysis of variance Cadmium (3.3 mg Cd/L) treated 96 hpf embryos Gene p-value Symbol Description (Corr) rcor2 Danio rerio REST corepressor 2 (rcor2), mRNA [NM_205638] 6.75E-14 mybl2 Danio rerio myeloblastosis oncogene-like 2 (mybl2), mRNA [NM_001003867] 7.81E-13 lxn Danio rerio latexin (lxn), mRNA [NM_001008596] 1.30E-12 col10a1a Danio rerio collagen, type X, alpha 1a (col10a1a), mRNA [NM_001083827] 1.53E-12 ctsl.1 Danio rerio cathepsin L.1 (ctsl.1), mRNA [NM_001002368] 1.63E-12 stm Danio rerio starmaker (stm), mRNA [NM_198817] 1.76E-12 hif1an Danio rerio hypoxia-inducible factor 1, alpha subunit inhibitor (hif1an), mRNA [NM_201496] 1.81E-12 nr2e1 Danio rerio nuclear receptor subfamily 2, group E, member 1 (nr2e1), mRNA [NM_001003608] 1.97E-12 zgc:56197 Danio rerio zgc:56197 (zgc:56197), mRNA [NM_200207] 1.97E-12 nfil3-6 Danio rerio nuclear factor, interleukin 3 regulated, member 6 (nfil3-6), mRNA [NM_001002218] 2.78E-12 igfbp1b Danio rerio insulin-like growth factor binding protein 1b (igfbp1b), mRNA [NM_001098257] 3.06E-12 nkx2.2a Danio rerio NK2 transcription factor related 2a (nkx2.2a), mRNA [NM_131422] 3.37E-12 mt2 Danio rerio metallothionein 2 (mt2), mRNA [NM_001131053] 4.06E-12 ctsl.1 Danio rerio cathepsin L.1 (ctsl.1), mRNA [NM_001002368] 4.11E-12 Danio rerio solute carrier family 16 (monocarboxylic acid transporters), member 9a (slc16a9a), mRNA slc16a9a [NM_200410] 4.91E-12 rab18b Danio rerio RAB18B, member RAS oncogene family (rab18b), mRNA [NM_001003449] 6.12E-12 creg2 Danio rerio cellular repressor of E1A-stimulated genes 2 (creg2), mRNA [NM_001007305] 7.57E-12 nuf2 Danio rerio NUF2, NDC80 kinetochore complex component, homolog (nuf2), mRNA [NM_200310] 1.57E-11 LOC1000054 activating transcription factor 7 interacting protein 2 [Source:ZFIN;Acc:ZDB-GENE-131121-384] 85 [ENSDART00000155760] 1.58E-11 mks1 Danio rerio Meckel syndrome, type 1 (mks1), mRNA [NM_001077373] 2.16E-11 ______137
Supplements
mettl14 Danio rerio methyltransferase like 14 (mettl14), mRNA [NM_207071] 2.49E-11 suv39h1b Danio rerio suppressor of variegation 3-9 homolog 1b (suv39h1b), mRNA [NM_001126482] 2.95E-11 macrophage receptor with collagenous structure [Source:ZFIN;Acc:ZDB-GENE-120514-2] LOC571584 [ENSDART00000082368] 4.06E-11 Danio rerio mesoderm induction early response 1 homolog a (Xenopus laevis) (mier1a), mRNA mier1a [NM_199559] 4.55E-11 rtkn2a Danio rerio rhotekin 2a (rtkn2a), mRNA [NM_001005937] 6.50E-11 fstb Danio rerio follistatin b (fstb), transcript variant 1, mRNA [NM_001039631] 1.14E-10 hgd Danio rerio homogentisate 1,2-dioxygenase (hgd), mRNA [NM_152966] 1.21E-10 haus3 Danio rerio HAUS augmin-like complex, subunit 3 (haus3), mRNA [NM_001077171] 1.55E-10 dhrs13l1 Danio rerio dehydrogenase/reductase (SDR family) member 13 like 1 (dhrs13l1), mRNA [NM_205648] 1.75E-10 dgat1b Danio rerio diacylglycerol O-acyltransferase homolog 1b (mouse) (dgat1b), mRNA [NM_001002458] 2.35E-10 ddx20 Danio rerio DEAD (Asp-Glu-Ala-Asp) box polypeptide 20 (ddx20), mRNA [NM_001123323] 2.49E-10 mxra8b Danio rerio matrix-remodelling associated 8b (mxra8b), mRNA [NM_001079960] 2.67E-10 dpf1 Danio rerio D4, zinc and double PHD fingers family 1 (dpf1), mRNA [NM_001030204] 3.76E-10 fam98b Danio rerio family with sequence similarity 98, member B (fam98b), mRNA [NM_001079662] 4.66E-10 phax Danio rerio phosphorylated adaptor for RNA export (phax), mRNA [NM_001003995] 5.02E-10 gh1 Danio rerio growth hormone 1 (gh1), mRNA [NM_001020492] 5.10E-10 cbx7a Danio rerio chromobox homolog 7a (cbx7a), mRNA [NM_001017853] 5.63E-10 prim1 Danio rerio primase polypeptide 1 (prim1), mRNA [NM_201448] 6.96E-10 FDR103-P00048-DEPE-F_D16 FDR103 Danio rerio cDNA clone FDR103-P00048-BR_D16 5', mRNA sb:cb930 sequence [EH448781] 7.47E-10 nfil3-6 Danio rerio nuclear factor, interleukin 3 regulated, member 6 (nfil3-6), mRNA [NM_001002218] 7.65E-10 acer1 Danio rerio alkaline ceramidase 1 (acer1), mRNA [NM_001017603] 8.95E-10 tpmt.2 Danio rerio zgc:101684 (zgc:101684), mRNA [NM_001033586] 1.13E-09 ugt5a4 Danio rerio UDP glucuronosyltransferase 5 family, polypeptide A4 (ugt5a4), mRNA [NM_001177498] 1.71E-09 stm Danio rerio starmaker (stm), mRNA [NM_198817] 1.73E-09 Danio rerio ATP-binding cassette, sub-family C (CFTR/MRP), member 4 (abcc4), mRNA abcc4 [NM_001007038] 1.85E-09 tdg Danio rerio thymine-DNA glycosylase (tdg), mRNA [NM_001020751] 1.88E-09 nfil3-6 Danio rerio nuclear factor, interleukin 3 regulated, member 6 (nfil3-6), mRNA [NM_001002218] 2.10E-09 pfkfb3 Danio rerio 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (pfkfb3), mRNA [NM_213397] 2.15E-09 LOC798290 Danio rerio uncharacterized LOC798290 (LOC798290), mRNA [NM_001100061] 2.41E-09 cdkn3 Danio rerio cyclin-dependent kinase inhibitor 3 (cdkn3), mRNA [NM_001145681] 2.58E-09 zgc:113372 Danio rerio zgc:113372 (zgc:113372), mRNA [NM_001030234] 2.80E-09 si:ch211- 117l17.6 si:ch211-117l17.6 [Source:ZFIN;Acc:ZDB-GENE-110914-213] [ENSDART00000129260] 3.32E-09 zgc:114119 Danio rerio zgc:114119 (zgc:114119), mRNA [NM_001033754] 3.36E-09 sb:cb252 sb:cb252 [Source:ZFIN;Acc:ZDB-GENE-030131-9744] [ENSDART00000081039] 3.50E-09 fgf19 Danio rerio fibroblast growth factor 19 (fgf19), mRNA [NM_001012246] 4.54E-09 tmprss13a Danio rerio transmembrane protease, serine 13a (tmprss13a), mRNA [NM_001159512] 4.76E-09 LOC567822 si:ch211-14a17.10 [Source:ZFIN;Acc:ZDB-GENE-030616-581] [ENSDART00000113485] 5.19E-09 cbx7a Danio rerio chromobox homolog 7a (cbx7a), mRNA [NM_001017853] 5.27E-09 zic5 Danio rerio zic family member 5 (odd-paired homolog, Drosophila) (zic5), mRNA [NM_205727] 5.51E-09 zgc:172053 Danio rerio zgc:172053 (zgc:172053), mRNA [NM_001111242] 6.34E-09 sb:cb252 sb:cb252 [Source:ZFIN;Acc:ZDB-GENE-030131-9744] [ENSDART00000081039] 6.38E-09 CD44 molecule (Indian blood group) a [Source:ZFIN;Acc:ZDB-GENE-110429-1] cd44a [ENSDART00000126240] 6.49E-09 thraa Danio rerio thyroid hormone receptor alpha a (thraa), mRNA [NM_131396] 8.02E-09 si:ch211- 117l17.6 si:ch211-117l17.6 [Source:ZFIN;Acc:ZDB-GENE-110914-213] [ENSDART00000129260] 8.50E-09 ______138
Supplements
pole Danio rerio polymerase (DNA directed), epsilon (pole), mRNA [NM_001128523] 8.74E-09 CD44 molecule (Indian blood group) a [Source:ZFIN;Acc:ZDB-GENE-110429-1] cd44a [ENSDART00000126240] 9.89E-09 pir Danio rerio pirin (pir), mRNA [NM_001002550] 1.18E-08 ybey Danio rerio ybeY metallopeptidase (ybey), mRNA [NM_212594] 1.24E-08 smtlb Danio rerio somatolactin beta (smtlb), mRNA [NM_001037674] 1.32E-08 Danio rerio protein-kinase, interferon-inducible double stranded RNA dependent inhibitor, repressor of (P58 prkrira repressor) a (prkrira), mRNA [NM_213081] 1.39E-08 stm Danio rerio starmaker (stm), mRNA [NM_198817] 1.63E-08 si:dkeyp- lymphatic vessel endothelial hyaluronan receptor 1 [Source:HGNC Symbol;Acc:14687] 104h2.3 [ENSDART00000112109] 1.80E-08 fkbp5 Danio rerio FK506 binding protein 5 (fkbp5), mRNA [NM_213149] 1.88E-08 nck1a NCK adaptor protein 1a [Source:ZFIN;Acc:ZDB-GENE-070912-547] [ENSDART00000111212] 2.11E-08 centrosome and spindle pole associated protein 1 [Source:HGNC Symbol;Acc:26193] LOC569952 [ENSDART00000152028] 2.13E-08 Danio rerio metallothion mt2 ein 2 (mt2), mRNA [NM_001131053] 2.33E-08 sqstm1 Danio rerio sequestosome 1 (sqstm1), mRNA [NM_213173] 2.74E-08 zgc:172053 Danio rerio zgc:172053 (zgc:172053), mRNA [NM_001111242] 2.74E-08 si:dkey- 226m8.7 Danio rerio si:dkey-226m8.7 (si:dkey-226m8.7), mRNA [NM_001110287] 3.03E-08 cishb Danio rerio cytokine inducible SH2-containing protein b (cishb), mRNA [NM_001114554] 3.63E-08 crfb17 Danio rerio cytokine receptor family member B17 (crfb17), mRNA [NM_001135979] 3.69E-08 pvalb8 Danio rerio parvalbumin 8 (pvalb8), mRNA [NM_182937] 3.90E-08 zgc:153788 Danio rerio zgc:153788 (zgc:153788), mRNA [NM_001045347] 4.86E-08 zgc:174259 Danio rerio zgc:174259 (zgc:174259), mRNA [NM_001111208] 4.98E-08 glulc Danio rerio glutamate-ammonia ligase (glutamine synthase) c (glulc), mRNA [NM_001075114] 5.27E-08 fn1b Danio rerio fibronectin 1b (fn1b), mRNA [NM_001013261] 5.36E-08 dek Danio rerio DEK oncogene (dek), mRNA [NM_001045276] 5.55E-08 ucp1 Danio rerio uncoupling protein 1 (ucp1), mRNA [NM_199523] 5.73E-08 caspa Danio rerio caspase a (caspa), mRNA [NM_131505] 5.83E-08 tinagl1 Danio rerio tubulointerstitial nephritis antigen-like 1 (tinagl1), mRNA [NM_001044977] 6.09E-08 gstp2 Danio rerio glutathione S-transferase pi 2 (gstp2), mRNA [NM_001020513] 6.56E-08 gsto2 Danio rerio glutathione S-transferase omega 2 (gsto2), mRNA [NM_001007372] 7.76E-08 otomp Danio rerio otolith matrix protein (otomp), mRNA [NM_001045087] 8.85E-08 kera Danio rerio keratocan (kera), mRNA [NM_001025548] 8.87E-08 mpp1 Danio rerio membrane protein, palmitoylated 1 (mpp1), mRNA [NM_214692] 9.88E-08 fn1b Danio rerio fibronectin 1b (fn1b), mRNA [NM_001013261] 9.94E-08 igfbp1a Danio rerio insulin-like growth factor binding protein 1a (igfbp1a), mRNA [NM_173283] 1.03E-07 rab28 Danio rerio RAB28, member RAS oncogene family (rab28), mRNA [NM_199752] 1.07E-07 sult6b1 Danio rerio sulfotransferase family, cytosolic, 6b, member 1 (sult6b1), mRNA [NM_214686] 1.20E-07 igfbp1a Danio rerio insulin-like growth factor binding protein 1a (igfbp1a), mRNA [NM_173283] 1.21E-07 si:dkey- 22i16.3 Danio rerio si:dkey-22i16.3 (si:dkey-22i16.3), mRNA [NM_001145556] 1.35E-07 zgc:86764 Danio rerio zgc:86764 (zgc:86764), mRNA [NM_001002684] 1.40E-07 fbxo32 Danio rerio F-box protein 32 (fbxo32), mRNA [NM_200917] 1.46E-07 dbx1b Danio rerio developing brain homeobox 1b (dbx1b), mRNA [NM_131178] 1.78E-07 znf395a Danio rerio zinc finger protein 395a (znf395a), mRNA [NM_001080054] 1.81E-07 mapk11 Danio rerio mitogen-activated protein kinase 11 (mapk11), mRNA [NM_001002095] 1.85E-07 sult1st5 Danio rerio sulfotransferase family 1, cytosolic sulfotransferase 5 (sult1st5), mRNA [NM_001199903] 1.91E-07 zgc:171674 Danio rerio zgc:171674 (zgc:171674), mRNA [NM_001105106] 2.11E-07 ______139
Supplements
dnajb9b Danio rerio DnaJ (Hsp40) homolog, subfamily B, member 9b (dnajb9b), mRNA [NM_001024393] 2.13E-07 tmprss13a Danio rerio transmembrane protease, serine 13a (tmprss13a), mRNA [NM_001159512] 2.29E-07 gpx1a Danio rerio glutathione peroxidase 1a (gpx1a), mRNA [NM_001007281] 2.55E-07 dhrs13l1 Danio rerio dehydrogenase/reductase (SDR family) member 13 like 1 (dhrs13l1), mRNA [NM_205648] 2.62E-07 cbx3a Danio rerio chromobox homolog 3a (HP1 gamma homolog, Drosophila) (cbx3a), mRNA [NM_001045402] 2.97E-07 im:7142942 ring finger protein 4 [Source:HGNC Symbol;Acc:10067] [ENSDART00000123145] 3.37E-07 LOC1018860 93 si:ch211-264e16.1 [Source:ZFIN;Acc:ZDB-GENE-060503-226] [ENSDART00000099921] 3.39E-07 pvalb8 Danio rerio parvalbumin 8 (pvalb8), mRNA [NM_182937] 3.47E-07 LOC1000018 PREDICTED: Danio rerio solute carrier family 22 member 7-like (LOC100001838), mRNA 38 [XM_001337307] 3.59E-07 mmp9 Danio rerio matrix metalloproteinase 9 (mmp9), mRNA [NM_213123] 3.73E-07 il4r.1 Danio rerio interleukin 4 receptor, tandem duplicate 1 (il4r.1), mRNA [NM_001013282] 4.18E-07 Danio rerio solute carrier family 16 (monocarboxylic acid transporters), member 9a (slc16a9a), mRNA slc16a9a [NM_200410] 4.19E-07 LOC570015 si:dkey-66i24.8 [Source:ZFIN;Acc:ZDB-GENE-130531-72] [ENSDART00000156359] 4.44E-07 gstp1 Danio rerio glutathione S-transferase pi 1 (gstp1), mRNA [NM_131734] 5.69E-07 il4r.1 Danio rerio interleukin 4 receptor, tandem duplicate 1 (il4r.1), mRNA [NM_001013282] 5.71E-07 six6b Danio rerio sine oculis-related homeobox 6b (six6b), mRNA [NM_001020585] 6.13E-07 cx35.4 Danio rerio connexin 35.4 (cx35.4), mRNA [NM_001017685] 6.15E-07 zgc:153426 Danio rerio zgc:153426 (zgc:153426), mRNA [NM_001076715] 6.36E-07 sqstm1 Danio rerio sequestosome 1 (sqstm1), mRNA [NM_213173] 6.48E-07 zgc:123284 Danio rerio zgc:123284 (zgc:123284), mRNA [NM_001037411] 6.53E-07 gpx1a Danio rerio glutathione peroxidase 1a (gpx1a), mRNA [NM_001007281] 6.66E-07 gstp1 Danio rerio glutathione S-transferase pi 1 (gstp1), mRNA [NM_131734] 6.84E-07 tfap2b Danio rerio transcription factor AP-2 beta (tfap2b), transcript variant 2, mRNA [NM_001024665] 6.84E-07 LOC566996 prostaglandin reductase 1 [Source:HGNC Symbol;Acc:18429] [ENSDART00000125457] 6.89E-07 keap1a Danio rerio kelch-like ECH-associated protein 1a (keap1a), mRNA [NM_182864] 7.50E-07 pgd Danio rerio phosphogluconate hydrogenase (pgd), transcript variant 1, mRNA [NM_213453] 7.95E-07 pgd Danio rerio phosphogluconate hydrogenase (pgd), transcript variant 1, mRNA [NM_213453] 8.07E-07 hsp70l Danio rerio heat shock cognate 70-kd protein, like (hsp70l), mRNA [NM_001113589] 8.68E-07 ucp1 Danio rerio uncoupling protein 1 (ucp1), mRNA [NM_199523] 8.73E-07 sp9 Danio rerio sp9 transcription factor (sp9), mRNA [NM_212960] 9.60E-07 cmbl Danio rerio carboxymethylenebutenolidase-like (Pseudomonas) (cmbl), mRNA [NM_001109832] 9.66E-07 fn1b Danio rerio fibronectin 1b (fn1b), mRNA [NM_001013261] 1.02E-06 vtg7 Danio rerio vitellogenin 7 (vtg7), mRNA [NM_001102671] 1.03E-06 zgc:153911 Danio rerio zgc:153911 (zgc:153911), mRNA [NM_001077315] 1.04E-06 gldc Danio rerio glycine dehydrogenase (decarboxylating) (gldc), mRNA [NM_199554] 1.09E-06 zgc:194539 Danio rerio zgc:194539 (zgc:194539), mRNA [NM_001135984] 1.31E-06 zgc:158387 Danio rerio zgc:158387 (zgc:158387), mRNA [NM_001080034] 1.39E-06 gss Danio rerio glutathione synthetase (gss), mRNA [NM_001006104] 1.43E-06 hmox1a Danio rerio heme oxygenase (decycling) 1a (hmox1a), mRNA [NM_001127516] 1.44E-06 Danio rerio metallothionein 2, mRNA (cDNA clone MGC:56534 IMAGE:5914156), complete cds. mt2 [BC049475] 1.47E-06 ripk4 Danio rerio receptor-interacting serine-threonine kinase 4 (ripk4), mRNA [NM_213078] 1.47E-06 zgc:173729 Danio rerio zgc:173729 (zgc:173729), mRNA [NM_001109730] 1.57E-06 mknk2b Danio rerio MAP kinase-interacting serine/threonine kinase 2b (mknk2b), mRNA [NM_194402] 1.62E-06 pcp4a Danio rerio Purkinje cell protein 4a (pcp4a), mRNA [NM_001166122] 1.69E-06
______140
Supplements
Danio rerio phospholipase A2, group VII (platelet-activating factor acetylhydrolase, plasma) (pla2g7), pla2g7 mRNA [NM_213189] 1.78E-06 stat3 Danio rerio signal transduction and activation of transcription 3 (stat3), mRNA [NM_131479] 1.83E-06 vsig10 Danio rerio V-set and immunoglobulin domain containing 10 (vsig10), mRNA [NM_001100094] 1.88E-06 LOC1000050 PREDICTED: Danio rerio hypothetical protein LOC100005016 (LOC100005016), mRNA 16 [XM_001344137] 1.95E-06 hsp70 Danio rerio heat shock cognate 70-kd protein (hsp70), mRNA [NM_131397] 2.17E-06 mmp13a Danio rerio matrix metalloproteinase 13a (mmp13a), mRNA [NM_201503] 2.17E-06 hsd17b12a Danio rerio hydroxysteroid (17-beta) dehydrogenase 12a (hsd17b12a), mRNA [NM_200881] 2.49E-06 LOC1000050 PREDICTED: Danio rerio hypothetical protein LOC100005016 (LOC100005016), mRNA 16 [XM_001344137] 2.49E-06 grhl3 grainyhead-like 3 [Source:ZFIN;Acc:ZDB-GENE-030131-9854] [ENSDART00000114215] 2.70E-06 tpmt.1 Danio rerio zgc:109981 (zgc:109981), mRNA [NM_001002569] 2.72E-06 si:ch211- 95j8.2 claudin 23 [Source:HGNC Symbol;Acc:17591] [ENSDART00000155674] 2.81E-06 zgc:91849 Danio rerio zgc:91849 (zgc:91849), mRNA [NM_001002687] 2.83E-06 zgc:163083 Danio rerio zgc:163083 (zgc:163083), mRNA [NM_001083559] 3.03E-06 LOC560023 Uncharacterized protein [Source:UniProtKB/TrEMBL;Acc:E7F5N1] [ENSDART00000074385] 3.18E-06 cdk2 Danio rerio cyclin-dependent kinase 2 (cdk2), mRNA [NM_213406] 3.22E-06 hsp70 Danio rerio heat shock cognate 70-kd protein (hsp70), mRNA [NM_131397] 3.35E-06 stat1b Danio rerio signal transducer and activator of transcription 1b (stat1b), mRNA [NM_200091] 4.13E-06 pitpnaa Danio rerio phosphatidylinositol transfer protein, alpha a (pitpnaa), mRNA [NM_200935] 4.69E-06 gapdh Danio rerio glyceraldehyde-3-phosphate dehydrogenase (gapdh), mRNA [NM_001115114] 4.99E-06 LOC1000018 PREDICTED: Danio rerio solute carrier family 22 member 7-like (LOC100001838), mRNA 38 [XM_001337307] 5.80E-06 grhl3 grainyhead-like 3 [Source:ZFIN;Acc:ZDB-GENE-030131-9854] [ENSDART00000114215] 6.00E-06 Danio rerio solute carrier family 2 (facilitated glucose transporter), member 9-like 1 (slc2a9l1), mRNA slc2a9l1 [NM_001166117] 6.01E-06 scpp8 Danio rerio secretory calcium-binding phosphoprotein 8 (scpp8), mRNA [NM_001145244] 6.28E-06 sart3 Danio rerio squamous cell carcinoma antigen recognised by T cells 3 (sart3), mRNA [NM_001030118] 6.48E-06 Danio rerio membrane-spanning 4-domains, subfamily A, member 17A.4 (ms4a17a.4), mRNA ms4a17a.4 [NM_001102638] 6.69E-06 hpdb Danio rerio 4-hydroxyphenylpyruvate dioxygenase b (hpdb), mRNA [NM_001003742] 6.97E-06 zgc:172053 Danio rerio zgc:172053 (zgc:172053), mRNA [NM_001111242] 7.28E-06 moxd1 Danio rerio monooxygenase, DBH-like 1 (moxd1), mRNA [NM_001045206] 7.89E-06 si:ch211- 264f5.2 Danio rerio si:ch211-264f5.2 (si:ch211-264f5.2), mRNA [NM_001098253] 8.24E-06 spna2 Danio rerio spectrin alpha 2, mRNA (cDNA clone IMAGE:5409939), complete cds. [BC108293] 8.81E-06 glulc Danio rerio zgc:152741, mRNA (cDNA clone MGC:152741 IMAGE:8148536), complete cds. [BC124107] 1.00E-05 irf6 Danio rerio interferon regulatory factor 6 (irf6), mRNA [NM_200598] 1.07E-05 ift52 Danio rerio intraflagellar transport protein 52 (ift52), mRNA [NM_001001834] 1.11E-05 LOC793246 Uncharacterized protein [Source:UniProtKB/TrEMBL;Acc:E7F1W2] [ENSDART00000124159] 1.14E-05 zgc:153665 Danio rerio zgc:153665 (zgc:153665), mRNA [NM_001077463] 1.19E-05 tat Danio rerio tyrosine aminotransferase (tat), mRNA [NM_001077554] 1.20E-05 Danio rerio zgc:92903, mRNA (cDNA clone MGC:191620 IMAGE:100059929), complete cds. txn [BC164445] 1.25E-05 sqstm1 Danio rerio sequestosome 1 (sqstm1), mRNA [NM_213173] 1.26E-05 ehd1a Danio rerio EH-domain containing 1a (ehd1a), mRNA [NM_212874] 1.28E-05 cyp4f3 Danio rerio cytochrome P450, family 4, subfamily F, polypeptide 3 (cyp4f3), mRNA [NM_001089541] 1.41E-05 moxd1 monooxygenase, DBH-like 1 [Source:ZFIN;Acc:ZDB-GENE-030131-9320] [ENSDART00000127291] 1.60E-05 ctsc Danio rerio cathepsin C (ctsc), mRNA [NM_214722] 1.63E-05 LOC794425 Uncharacterized protein [Source:UniProtKB/TrEMBL;Acc:F1QKP1] [ENSDART00000126048] 1.64E-05 ______141
Supplements
zgc:109934 Danio rerio zgc:109934 (zgc:109934), mRNA [NM_001020531] 1.65E-05 cldn7b Danio rerio claudin 7b (cldn7b), mRNA [NM_131637] 1.65E-05 cth Danio rerio cystathionase (cystathionine gamma-lyase) (cth), mRNA [NM_212604] 1.70E-05 tmem176l.1 Danio rerio uo:ion001 mRNA, 3' UTR. [FJ392612] 1.70E-05 timp2b Danio rerio tissue inhibitor of metalloproteinase 2b (timp2b), mRNA [NM_213296] 1.71E-05 cldnf Danio rerio claudin f (cldnf), mRNA [NM_131766] 1.87E-05 zgc:173594 Danio rerio zgc:173594 (zgc:173594), mRNA [NM_001109854] 1.89E-05 slc30a1a Danio rerio solute carrier family 30 (zinc transporter), member 1a (slc30a1a), mRNA [NM_200879] 1.91E-05 lysine (K)-specific demethylase 6B, b [Source:ZFIN;Acc:ZDB-GENE-040724-166] kdm6bb [ENSDART00000079505] 2.08E-05 ATP-binding cassette, sub-family A (ABC1), member 1A [Source:ZFIN;Acc:ZDB-GENE-031006-12] abca1a [ENSDART00000142465] 2.12E-05 zgc:173594 Danio rerio zgc:173594 (zgc:173594), mRNA [NM_001109854] 2.21E-05 hsp70 Danio rerio heat shock cognate 70-kd protein (hsp70), mRNA [NM_131397] 2.28E-05 il4r.2 Danio rerio IL-4RA-like protein 2 soluble form mRNA, complete cds, alternatively spliced. [EF523378] 2.35E-05 si:ch211- 202h22.7 si:ch211-202h22.7 [Source:ZFIN;Acc:ZDB-GENE-090313-77] [ENSDART00000141207] 2.35E-05 vmhcl Danio rerio ventricular myosin heavy chain-like (vmhcl), mRNA [NM_001077464] 2.43E-05 zgc:194125 Danio rerio zgc:194125 (zgc:194125), mRNA [NM_001130667] 2.46E-05 Danio rerio heat shock protein 90, alpha (cytosolic), class A member 1, tandem duplicate 2 (hsp90aa1.2), hsp90aa1.2 mRNA [NM_001045073] 2.54E-05 lect2l Danio rerio leukocyte cell-derived chemotaxin 2 like (lect2l), mRNA [NM_001048055] 2.84E-05 ethe1 Danio rerio ethylmalonic encephalopathy 1 (ethe1), mRNA [NM_212929] 3.03E-05 Danio rerio HSPA (heat shock 70kDa) binding protein, cytoplasmic cochaperone 1 (hspbp1), mRNA hspbp1 [NM_200075] 3.22E-05 si:ch211- 157c3.4 Danio rerio si:ch211-157c3.4 (si:ch211-157c3.4), mRNA [NM_001164368] 3.36E-05 oclna Danio rerio occludin a (oclna), mRNA [NM_212832] 3.36E-05 myo1b myosin IB [Source:ZFIN;Acc:ZDB-GENE-030131-695] [ENSDART00000077187] 3.39E-05 timp2b Danio rerio tissue inhibitor of metalloproteinase 2b (timp2b), mRNA [NM_213296] 3.71E-05 prdx1 Danio rerio peroxiredoxin 1 (prdx1), mRNA [NM_001013471] 3.76E-05 gsr Danio rerio glutathione reductase (gsr), mRNA [NM_001020554] 3.83E-05 Danio rerio membrane-spanning 4-domains, subfamily A, member 17A.7 (ms4a17a.7), mRNA ms4a17a.7 [NM_001017714] 4.01E-05 cmbl Danio rerio carboxymethylenebutenolidase-like (Pseudomonas) (cmbl), mRNA [NM_001109832] 4.08E-05 nkx2.7 Danio rerio NK2 transcription factor related 7 (nkx2.7), mRNA [NM_131419] 4.50E-05 zgc:136929 Danio rerio zgc:136929 (zgc:136929), mRNA [NM_001040390] 4.64E-05 tagln2 Danio rerio transgelin 2 (tagln2), mRNA [NM_201576] 4.66E-05 zgc:158614 Danio rerio zgc:158614 (zgc:158614), mRNA [NM_001080700] 5.03E-05 il21r Danio rerio interleukin 21 receptor (il21r), mRNA [NM_001113510] 5.14E-05 Danio rerio elongation of very long chain fatty acids (FEN1/Elo2, SUR4/Elo3, yeast)-like 2 (elovl2), mRNA elovl2 [NM_001040362] 5.32E-05 cmlc1 Danio rerio cardiac myosin light chain-1 (cmlc1), mRNA [NM_131692] 6.25E-05 zgc:136572 Danio rerio zgc:136572 (zgc:136572), mRNA [NM_001045310] 7.08E-05 papss2b Danio rerio 3'-phosphoadenosine 5'-phosphosulfate synthase 2b (papss2b), mRNA [NM_212562] 7.28E-05 solute carrier family 4, anion exchanger, member 2a [Source:ZFIN;Acc:ZDB-GENE-051101-2] slc4a2a [ENSDART00000041319] 7.51E-05 anxa2a Danio rerio annexin A2a (anxa2a), mRNA [NM_181761] 7.52E-05 rpz3 Danio rerio rapunzel3 (rpz3), mRNA [NM_001146098] 7.60E-05 zgc:194839 Danio rerio zgc:194839 (zgc:194839), mRNA [NM_001123324] 7.72E-05 cd99l2 Danio rerio CD99 antigen-like 2 (cd99l2), mRNA [NM_194369] 9.16E-05 hsp70l Danio rerio heat shock cognate 70-kd protein, like (hsp70l), mRNA [NM_001113589] 9.65E-05 ______142
Supplements
gsr Danio rerio glutathione reductase (gsr), mRNA [NM_001020554] 1.15E-04 si:ch211- 166e11.5 si:ch211-166e11.5 [Source:ZFIN;Acc:ZDB-GENE-070912-142] [ENSDART00000112682] 1.16E-04 FDR202-P00027-DEPE-F_G13 FDR202 Danio rerio cDNA clone FDR202-P00027-BR_G13 5', mRNA zgc:92066 sequence [EH545747] 1.39E-04 zgc:114041 Danio rerio zgc:114041 (zgc:114041), mRNA [NM_001029972] 1.41E-04 ildr1a Danio rerio immunoglobulin-like domain containing receptor 1a (ildr1a), mRNA [NM_200393] 1.44E-04 zgc:123258 Danio rerio zgc:123258 (zgc:123258), mRNA [NM_001037439] 1.49E-04 prdx1 Danio rerio peroxiredoxin 1 (prdx1), mRNA [NM_001013471] 1.63E-04 rtn4b Danio rerio reticulon 4b (rtn4b), mRNA [NM_001040335] 1.65E-04 nots Danio rerio nothepsin (nots), mRNA [NM_131804] 1.65E-04 timp2b Danio rerio tissue inhibitor of metalloproteinase 2b (timp2b), mRNA [NM_213296] 1.68E-04 zgc:92481 Danio rerio zgc:92481 (zgc:92481), mRNA [NM_001004604] 1.72E-04 tnfaip8l2b Danio rerio tumor necrosis factor, alpha-induced protein 8, like 2b (tnfaip8l2b), mRNA [NM_200374] 1.85E-04 si:dkey- AGENCOURT_69630133 NIH_ZGC_29 Danio rerio cDNA clone IMAGE:8353820 5', mRNA sequence 92i15.4 [DY557637] 2.04E-04 ctssb.1 Danio rerio cathepsin Sb, tandem duplicate 1 (ctssb.1), mRNA [NM_001024409] 2.05E-04 Danio rerio parvalbumin 5, mRNA (cDNA clone MGC:192300 IMAGE:100060609), complete cds. pvalb5 [BC165125] 2.11E-04 zgc:113255 Danio rerio zgc:113255 (zgc:113255), mRNA [NM_001014327] 2.45E-04 epcam Danio rerio epithelial cell adhesion molecule (epcam), mRNA [NM_001017593] 2.50E-04 tnfrsf9a Danio rerio tumor necrosis factor receptor superfamily, member 9a (tnfrsf9a), mRNA [NM_001040369] 2.50E-04 cth Danio rerio cystathionase (cystathionine gamma-lyase) (cth), mRNA [NM_212604] 2.68E-04 pvalb5 Danio rerio parvalbumin 5 (pvalb5), mRNA [NM_207167] 2.89E-04 cebpb Danio rerio CCAAT/enhancer binding protein (C/EBP), beta (cebpb), mRNA [NM_131884] 2.91E-04 marveld2b Danio rerio MARVEL domain containing 2b (marveld2b), mRNA [NM_001126406] 3.06E-04 ptges Danio rerio prostaglandin E synthase (ptges), mRNA [NM_001014828] 3.11E-04 stx11a Danio rerio syntaxin 11a (stx11a), mRNA [NM_212910] 3.84E-04 rab42b Danio rerio RAB42, member RAS oncogene family (rab42b), mRNA [NM_001017683] 4.36E-04 ponzr4 Danio rerio cDNA clone IMAGE:7147948. [BC159225] 4.50E-04 or135-1 Danio rerio odorant receptor, family H, subfamily 135, member 1 (or135-1), mRNA [NM_001083869] 4.83E-04 cebpb Danio rerio CCAAT/enhancer binding protein (C/EBP), beta (cebpb), mRNA [NM_131884] 4.98E-04 FDR202-P00006-DEPE-R_H10 FDR202 Danio rerio cDNA clone FDR202-P00006-BR_H10 3', mRNA calml4b sequence [EH559267] 4.99E-04 LOC555317 Uncharacterized protein [Source:UniProtKB/TrEMBL;Acc:E7F2N2] [ENSDART00000128183] 5.00E-04 si:ch211- 264f5.2 Danio rerio si:ch211-264f5.2 (si:ch211-264f5.2), mRNA [NM_001098253] 5.31E-04 mvp Danio rerio major vault protein (mvp), mRNA [NM_201325] 5.32E-04 zgc:109934 Danio rerio zgc:109934 (zgc:109934), mRNA [NM_001020531] 5.41E-04 mvda Danio rerio mevalonate (diphospho) decarboxylase a (mvda), mRNA [NM_001007422] 5.53E-04 si:ch211- 122l24.4 Danio rerio si:ch211-122l24.4 (si:ch211-122l24.4), mRNA [NM_001130655] 5.59E-04 zgc:198419 Danio rerio zgc:198419 (zgc:198419), mRNA [NM_001113659] 5.73E-04 zgc:153665 Danio rerio zgc:153665 (zgc:153665), mRNA [NM_001077463] 6.46E-04 cab39l1 Danio rerio calcium binding protein 39, like 1 (cab39l1), mRNA [NM_213501] 7.84E-04 cdcp1a Danio rerio CUB domain containing protein 1a (cdcp1a), mRNA [NM_001014333] 9.31E-04 solute carrier family 30 (zinc transporter), member 8 [Source:ZFIN;Acc:ZDB-GENE-060315-10] LOC560642 [ENSDART00000080344] 9.45E-04 si:ch211- 157c3.4 Danio rerio si:ch211-157c3.4 (si:ch211-157c3.4), mRNA [NM_001164368] 9.48E-04 tmprss4a Danio rerio transmembrane protease, serine 4a (tmprss4a), mRNA [NM_001077738] 9.67E-04 rhov Danio rerio ras homolog gene family, member V (rhov), mRNA [NM_001012250] 1.04E-03 ______143
Supplements
gldc Danio rerio glycine dehydrogenase (decarboxylating) (gldc), mRNA [NM_199554] 1.08E-03 ankrd22 Danio rerio ankyrin repeat domain 22 (ankrd22), mRNA [NM_200274] 1.19E-03 Danio rerio membrane-spanning 4-domains, subfamily A, member 17A.4 (ms4a17a.4), mRNA ms4a17a.4 [NM_001102638] 1.36E-03 zgc:153118 Danio rerio zgc:153118 (zgc:153118), mRNA [NM_001076642] 1.43E-03 Danio rerio guanine nucleotide binding protein (G protein), alpha 15 (Gq class), tandem duplicate 1 gna15.1 (gna15.1), mRNA [NM_001003626] 1.43E-03 si:dkey- 228a15.1 Danio rerio si:dkey-228a15.1 (si:dkey-228a15.1), mRNA [NM_001045053] 1.45E-03 atp2b1a Danio rerio ATPase, Ca++ transporting, plasma membrane 1a (atp2b1a), mRNA [NM_001044757] 1.64E-03 tgm5l transglutaminase 5, like [Source:ZFIN;Acc:ZDB-GENE-110411-176] [ENSDART00000109821] 1.65E-03 f11r Danio rerio F11 receptor (f11r), mRNA [NM_001004667] 1.83E-03 si:ch211- 241b2.1 Danio rerio si:ch211-241b2.1 (si:ch211-241b2.1), mRNA [NM_001017868] 1.86E-03 npsn Danio rerio nephrosin (npsn), transcript variant 1, mRNA [NM_001077779] 1.87E-03 fgb Danio rerio fibrinogen, B beta polypeptide (fgb), mRNA [NM_212774] 2.09E-03 apoeb Danio rerio apolipoprotein Eb (apoeb), mRNA [NM_131098] 2.36E-03 cldne Danio rerio claudin e (cldne), mRNA [NM_131765] 2.61E-03 zgc:152857 Danio rerio zgc:152857 (zgc:152857), mRNA [NM_001076729] 3.16E-03 si:dkeyp- 46h3.2 Danio rerio si:dkeyp-46h3.2 (si:dkeyp-46h3.2), mRNA [NM_001114887] 3.39E-03 LOC1003343 63 sperm acrosome associated 4 like [Source:ZFIN;Acc:ZDB-GENE-101011-2] [ENSDART00000124071] 3.39E-03 Danio rerio membrane-spanning 4-domains, subfamily A, member 17A.1 (ms4a17a.1), mRNA ms4a17a.1 [NM_001017783] 3.40E-03 prdx1 Danio rerio peroxiredoxin 1 (prdx1), mRNA [NM_001013471] 3.50E-03 LOC567822 si:ch211-14a17.10 [Source:ZFIN;Acc:ZDB-GENE-030616-581] [ENSDART00000113485] 3.62E-03 zgc:91811 Danio rerio zgc:91811 (zgc:91811), mRNA [NM_001003481] 3.68E-03 keap1b Danio rerio kelch-like ECH-associated protein 1b (keap1b), mRNA [NM_001113477] 3.86E-03 si:ch1073- 263o8.2 si:ch1073-263o8.2 [Source:ZFIN;Acc:ZDB-GENE-030131-5362] [ENSDART00000151778] 3.97E-03 il15l Danio rerio interleukin 15, like (il15l), transcript variant 1, mRNA [NM_001009558] 4.37E-03 centrosome and spindle pole associated protein 1 [Source:HGNC Symbol;Acc:26193] LOC569952 [ENSDART00000081919] 4.97E-03 ccdc80 Danio rerio coiled-coil domain containing 80 (ccdc80), mRNA [NM_001007198] 5.26E-03 ftr83 finTRIM family, member 83 [Source:ZFIN;Acc:ZDB-GENE-031002-11] [ENSDART00000098239] 5.46E-03 AGENCOURT_30543644 NIH_ZGC_5 Danio rerio cDNA clone IMAGE:7412034 5', mRNA sequence dynll2b [CO918797] 5.50E-03 LOC567149 Uncharacterized protein [Source:UniProtKB/TrEMBL;Acc:E7EYZ0] [ENSDART00000124538] 5.62E-03 methionyl-tRNA synthetase 2, mitochondrial [Source:HGNC Symbol;Acc:25133] LOC566565 [ENSDART00000024604] 5.94E-03 ponzr3 plac8 onzin related protein 3 [Source:ZFIN;Acc:ZDB-GENE-050506-38] [ENSDART00000140378] 6.20E-03 pon1 Danio rerio paraoxonase 1 (pon1), mRNA [NM_001004542] 6.28E-03 cap1 Danio rerio Cap1 CAP, adenylate cyclase-associated protein 1 (cap1), mRNA [NM_199909] 7.33E-03 zgc:175135 Danio rerio zgc:175135 (zgc:175135), mRNA [NM_001114722] 8.03E-03 zgc:153911 Danio rerio zgc:153911 (zgc:153911), mRNA [NM_001077315] 1.05E-02 Danio rerio solute carrier family 12 (sodium/chloride transporters), member 3 (slc12a3), mRNA slc12a3 [NM_001045080] 1.06E-02 Danio rerio solute carrier family 2 (facilitated glucose transporter), member 9-like 1 (slc2a9l1), mRNA slc2a9l1 [NM_001166117] 1.13E-02 zgc:194686 Danio rerio zgc:194686 (zgc:194686), mRNA [NM_001130647] 1.15E-02 zgc:65788 Danio rerio zgc:65788 (zgc:65788), mRNA [NM_199603] 1.19E-02 zgc:123218 Danio rerio zgc:123218 (zgc:123218), mRNA [NM_001037117] 1.31E-02 s100a1 Danio rerio S100 calcium binding protein A1 (s100a1), mRNA [NM_001089351] 1.40E-02 zgc:92360 Danio rerio zgc:92360 (zgc:92360), mRNA [NM_001002715] 1.48E-02 ______144
Supplements
acer1 Danio rerio alkaline ceramidase 1 (acer1), mRNA [NM_001017603] 1.59E-02 si:ch211- 12e13.2 si:ch211-12e13.2 [Source:ZFIN;Acc:ZDB-GENE-060526-27] [ENSDART00000007453] 1.65E-02 zgc:113255 Danio rerio zgc:113255 (zgc:113255), mRNA [NM_001014327] 1.65E-02 dalrd3 Danio rerio DALR anticodon binding domain containing 3 (dalrd3), mRNA [NM_001123326] 1.71E-02 Danio rerio HSPA (heat shock 70kDa) binding protein, cytoplasmic cochaperone 1 (hspbp1), mRNA hspbp1 [NM_200075] 1.71E-02 slc39a3 Danio rerio solute carrier family 39 (zinc transporter), member 3 (slc39a3), mRNA [NM_001080619] 1.74E-02 LOC1000001 68 Danio rerio cDNA clone IMAGE:6896133. [BC090263] 1.87E-02 hmox1b Danio rerio heme oxygenase (decycling) 1b (hmox1b), mRNA [NM_205671] 2.02E-02 Danio rerio ELOVL family member 7, elongation of long chain fatty acids (yeast) b (elovl7b), mRNA elovl7b [NM_199778] 2.09E-02 arl8bb Danio rerio ADP-ribosylation factor-like 8Bb, mRNA (cDNA clone IMAGE:5604898). [BC052221] 2.18E-02 krt18 Danio rerio keratin 18 (krt18), mRNA [NM_178437] 2.25E-02 RAB, member of RAS oncogene family-like 3 [Source:ZFIN;Acc:ZDB-GENE-040808-11] rabl3 [ENSDART00000123466] 2.25E-02 zgc:109934 Danio rerio zgc:109934, mRNA (cDNA clone MGC:173595 IMAGE:8154848), complete cds. [BC154146] 2.26E-02 cldni Danio rerio claudin i (cldni), mRNA [NM_131768] 2.80E-02 fut9d Danio rerio fucosyltransferase 9d (fut9d), mRNA [NM_001077246] 2.85E-02 family with sequence similarity 26, member E [Source:HGNC Symbol;Acc:21568] LOC798204 [ENSDART00000023995] 2.90E-02 zgc:158403 Danio rerio zgc:158403 (zgc:158403), mRNA [NM_001080084] 3.11E-02 fut9d Danio rerio fucosyltransferase 9d (fut9d), mRNA [NM_001077246] 3.13E-02 cldnb Danio rerio claudin b (cldnb), mRNA [NM_131763] 3.19E-02 lrrfip1a Danio rerio cDNA clone IMAGE:2601228, containing frame-shift errors. [BC098883] 3.39E-02 si:dkey- 165i4.3 Danio rerio si:dkey-165i4.3 (si:dkey-165i4.3), mRNA [NM_001110525] 3.43E-02 zgc:63489 Danio rerio zgc:63489 (zgc:63489), mRNA [NM_200629] 3.55E-02 rab42b Danio rerio RAB42, member RAS oncogene family (rab42b), mRNA [NM_001017683] 3.69E-02 Danio rerio solute carrier family 16 (monocarboxylic acid transporters), member 9b (slc16a9b), mRNA slc16a9b [NM_001003552] 3.76E-02 pmt Danio rerio phosphoethanolamine methyltransferase (pmt), mRNA [NM_001076637] 3.98E-02 Danio rerio heat shock cognate 70-kd protein, mRNA (cDNA clone MGC:65778 IMAGE:6789418), hsp70 complete cds. [BC056709] 4.20E-02 si:ch211- 130m23.2 Danio rerio si:ch211-130m23.2 (si:ch211-130m23.2), mRNA [NM_001114689] 4.49E-02 Danio rerio ELOVL family member 7, elongation of long chain fatty acids (yeast) b (elovl7b), mRNA elovl7b [NM_199778] 4.65E-02 LOC567640 laminin, alpha 3 [Source:HGNC Symbol;Acc:6483] [ENSDART00000140540] 4.95E-02
Significant Genes of analysis of variance Cobalt (3.6 mg Co/L) treated 48 hpf embryos Gene p-value Symbol Description (Corr) sv2ba Danio rerio synaptic vesicle glycoprotein 2 ba (sv2ba), mRNA [NM_001082995] 2.30E-12 arid5b Danio rerio AT rich interactive domain 5B (MRF1-like) (arid5b), mRNA [NM_001080201] 3.50E-12 potassium channel tetramerisation domain containing 3 [Source:ZFIN;Acc:ZDB-GENE-060503-169] kctd3 [ENSDART00000086164] 4.97E-12 klf9 Danio rerio Kruppel-like factor 9 (klf9), mRNA [NM_001128729] 7.31E-12 FDR103-P00048-DEPE-F_D16 FDR103 Danio rerio cDNA clone FDR103-P00048-BR_D16 5', mRNA sb:cb930 sequence [EH448781] 2.46E-11 myosin light chain kinase family, member 4a [Source:ZFIN;Acc:ZDB-GENE-120824-2] LOC566845 [ENSDART00000122138] 3.61E-11 lpin1 Danio rerio lipin 1 (lpin1), mRNA [NM_001044353] 8.39E-10 tmprss13a Danio rerio transmembrane protease, serine 13a (tmprss13a), mRNA [NM_001159512] 3.88E-09 ______145
Supplements
lpin1 Danio rerio lipin 1 (lpin1), mRNA [NM_001044353] 7.60E-09 cyp2p6 Danio rerio cytochrome P450, family 2, subfamily P, polypeptide 6 (cyp2p6), mRNA [NM_200139] 1.59E-08 agxtb Danio rerio alanine-glyoxylate aminotransferase b (agxtb), mRNA [NM_213162] 3.08E-08 fkbp5 Danio rerio FK506 binding protein 5 (fkbp5), mRNA [NM_213149] 3.58E-08 etnk1 ethanolamine kinase 1 [Source:ZFIN;Acc:ZDB-GENE-030328-21] [ENSDART00000143208] 3.25E-07 cygb2 Danio rerio cytoglobin 2 (cygb2), mRNA [NM_001024224] 2.83E-06 klf3 Danio rerio Kruppel-like factor 3 (basic) (klf3), mRNA [NM_131859] 3.74E-06 neuronal guanine nucleotide exchange factor [Source:HGNC Symbol;Acc:7807] LOC569090 [ENSDART00000111018] 4.11E-05 solute carrier organic anion transporter family, member 2A1 [Source:ZFIN;Acc:ZDB-GENE-060606-3] slco2a1 [ENSDART00000147789] 3.54E-04 fhl2b Danio rerio four and a half LIM domains 2b (fhl2b), mRNA [NM_001006028] 4.79E-04 fgg Danio rerio fibrinogen, gamma polypeptide (fgg), mRNA [NM_213054] 6.44E-03 nao26g07.y1 Zebrafish Posterior segment. Unnormalized (nao) Danio rerio cDNA clone nao26g07 5', cmpk2 mRNA sequence [DN892697] 8.21E-03 Danio rerio solute carrier organic anion transporter family, member 2A1 (slco2a1), mRNA slco2a1 [NM_001089582] 1.17E-02 ca15a Danio rerio carbonic anhydrase XV a (ca15a), mRNA [NM_001081689] 2.07E-02 zgc:63602 Danio rerio zgc:63602 (zgc:63602), mRNA [NM_200461] 2.16E-02 Danio rerio ATP-binding cassette, sub-family B (MDR/TAP), member 4 (abcb4), mRNA abcb4 [NM_001114583] 2.31E-02 hs6st3b Danio rerio heparan sulfate 6-O-sulfotransferase 3b (hs6st3b), mRNA [NM_001080194] 2.90E-02 LOC100005 globoside alpha-1,3-N-acetylgalactosaminyltransferase 1 [Source:HGNC Symbol;Acc:20460] 704 [ENSDART00000137063] 3.95E-02
Significant Genes of analysis of variance Cobalt (3.6 mg Co/L) treated 96 hpf embryos Gene p-value Symbol Description (Corr) pvalb8 Danio rerio parvalbumin 8 (pvalb8), mRNA [NM_182937] 1.18E-10 zgc:198419 Danio rerio zgc:198419 (zgc:198419), mRNA [NM_001113659] 1.26E-05 zgc:112408 Danio rerio zgc:112408 (zgc:112408), mRNA [NM_001017597] 4.02E-04 ch25h Danio rerio cholesterol 25-hydroxylase (ch25h), mRNA [NM_001008652] 4.93E-04 mfsd4b Danio rerio major facilitator superfamily domain containing 4b (mfsd4b), mRNA [NM_001114416] 5.77E-04 zgc:112408 Danio rerio zgc:112408 (zgc:112408), mRNA [NM_001017597] 1.41E-03 zgc:194125 Danio rerio zgc:194125 (zgc:194125), mRNA [NM_001130667] 3.25E-03 foxf2b forkhead box F2b [Source:ZFIN;Acc:ZDB-GENE-041001-130] [ENSDART00000103232] 4.15E-03 FDR202-P00027-DEPE-F_G13 FDR202 Danio rerio cDNA clone FDR202-P00027-BR_G13 5', mRNA zgc:92066 sequence [EH545747] 4.17E-03 zgc:109934 Danio rerio zgc:109934 (zgc:109934), mRNA [NM_001020531] 4.45E-03 zgc:173594 Danio rerio zgc:173594 (zgc:173594), mRNA [NM_001109854] 5.87E-03 solute carrier family 4, anion exchanger, member 1b [Source:ZFIN;Acc:ZDB-GENE-110215-2] slc4a1b [ENSDART00000078497] 6.40E-03 zgc:109934 Danio rerio zgc:109934 (zgc:109934), mRNA [NM_001020531] 7.26E-03 zgc:173594 Danio rerio zgc:173594 (zgc:173594), mRNA [NM_001109854] 7.95E-03 zgc:113442 Danio rerio zgc:113442 (zgc:113442), mRNA [NM_001013280] 8.04E-03 ifit5 Danio rerio interferon-induced protein with tetratricopeptide repeats 5 (ifit5), mRNA [NM_001190465] 8.35E-03 ca15a Danio rerio carbonic anhydrase XV a (ca15a), mRNA [NM_001081689] 2.07E-02
______146
Supplements
Significant Genes of analysis of variance Copper (6.1 µg Cu/L) treated 48 hpf embryos Gene p-value Symbol Description (Corr) si:dkey- Danio rerio 94e7.2 si:dkey-94e7.2 (si:dkey-94e7.2), mRNA [NM_001114918] 1.12E-12 rho Danio rerio rhodopsin (rho), mRNA [NM_131084] 1.31E-12 hpdb Danio rerio 4-hydroxyphenylpyruvate dioxygenase b (hpdb), mRNA [NM_001003742] 2.62E-12 asb10 Danio rerio ankyrin repeat and SOCS box containing 10 (asb10), mRNA [NM_001077148] 7.17E-12 cart2 Danio rerio cocaine- and amphetamine-regulated transcript 2 (cart2), mRNA [NM_001017570] 1.38E-11 rgs5b Danio rerio regulator of G-protein signaling 5b (rgs5b), mRNA [NM_001017821] 1.46E-11 LOC566865 Danio rerio hypothetical LOC566865, mRNA (cDNA clone IMAGE:7044508), partial cds. [BC134901] 2.66E-11 cpa4 Danio rerio carboxypeptidase A4 (cpa4), mRNA [NM_001002217] 4.46E-11 Danio rerio calcium/calmodulin-dependent protein kinase (CaM kinase) II alpha (camk2a), mRNA camk2a [NM_001017741] 7.18E-11 opn1lw2 Danio rerio opsin 1 (cone pigments), long-wave-sensitive, 2 (opn1lw2), mRNA [NM_001002443] 9.80E-11 krtt1c19e Danio rerio si:dkeyp-113d7.4 (si:dkeyp-113d7.4), mRNA [NM_001114342] 1.03E-10 cldn15lb Danio rerio claudin 15-like b (cldn15lb), mRNA [NM_001002446] 1.07E-10 tnmd Danio rerio tenomodulin (tnmd), mRNA [NM_001114413] 1.46E-10 calcium/calmodulin-dependent protein kinase (CaM kinase) II beta 2 [Source:ZFIN;Acc:ZDB-GENE- LOC798222 090312-34] [ENSDART00000133694] 3.62E-10 cabp2a Danio rerio calcium binding protein 2a (cabp2a), mRNA [NM_001030268] 4.80E-10 si:dkey- 7k24.6 si:dkey-7k24.6 [Source:ZFIN;Acc:ZDB-GENE-131127-122] [ENSDART00000041177] 5.90E-10 stxbp1b Danio rerio syntaxin binding protein 1b (stxbp1b), mRNA [NM_001089376] 6.39E-10 LOC100331 105 Uncharacterized protein [Source:UniProtKB/TrEMBL;Acc:E7F0I3] [ENSDART00000129308] 7.46E-10 ugt5d1 Danio rerio UDP glucuronosyltransferase 5 family, polypeptide D1 (ugt5d1), mRNA [NM_001177496] 7.56E-10 zgc:163083 Danio rerio zgc:163083 (zgc:163083), mRNA [NM_001083559] 1.94E-09 si:dkey- 7k24.6 si:dkey-7k24.6 [Source:ZFIN;Acc:ZDB-GENE-131127-122] [ENSDART00000155761] 3.04E-09 im:7147977 Danio rerio cDNA clone IMAGE:7147977. [BC103484] 3.49E-09 si:ch211- 213d14.2 si:ch211-213d14.2 [Source:ZFIN;Acc:ZDB-GENE-030131-8357] [ENSDART00000155197] 4.34E-09 ndufs8b Danio rerio NADH dehydrogenase (ubiquinone) Fe-S protein 8b (ndufs8b), mRNA [NM_001024402] 6.83E-09 gabrr2a Danio rerio gamma-aminobutyric acid (GABA) A receptor, rho 2a (gabrr2a), mRNA [NM_001045376] 6.92E-09 cx32.3 Danio rerio connexin 32.3 (cx32.3), mRNA [NM_199612] 7.54E-09 FDR103-P00020-DEPE-F_P04 FDR103 Danio rerio cDNA clone FDR103-P00020-BR_P04 5', mRNA wu:fj19g03 sequence [EH438865] 1.05E-08 slc35g2b Danio rerio solute carrier family 35, member G2b (slc35g2b), mRNA [NM_001013563] 1.27E-08 sybu Danio rerio syntabulin (syntaxin-interacting) (sybu), mRNA [NM_001077173] 1.54E-08 ptk7a Danio rerio protein tyrosine kinase 7a (ptk7a), mRNA [NM_001020665] 2.81E-08 phox2bb Danio rerio paired-like homeobox 2bb (phox2bb), mRNA [NM_001014818] 4.70E-08 zgc:77938 Danio rerio zgc:77938 (zgc:77938), mRNA [NM_205642] 5.21E-08 ttll2 Danio rerio tubulin tyrosine ligase-like family, member 2 (ttll2), mRNA [NM_001111230] 5.51E-08 sc:d189 Danio rerio sc:d189 (sc:d189), mRNA [NM_001098260] 5.81E-08 zgc:194355 Danio rerio zgc:194355 (zgc:194355), mRNA [NM_001135971] 5.93E-08 prc1b Danio rerio protein regulator of cytokinesis 1b (prc1b), mRNA [NM_200234] 6.10E-08 cel.1 Danio rerio carboxyl ester lipase, tandem duplicate 1 (cel.1), mRNA [NM_199607] 7.73E-08 si:dkeyp- 113d7.1 si:dkeyp-113d7.10 [Source:ZFIN;Acc:ZDB-GENE-061207-80] [ENSDART00000141237] 7.87E-08 plscr3a Danio rerio phospholipid scramblase 3a (plscr3a), mRNA [NM_001105113] 9.28E-08 Danio rerio leucine-rich repeat, immunoglobulin-like and transmembrane domains 1a (lrit1a), mRNA lrit1a [NM_001018164] 9.85E-08 ______147
Supplements
axin2 Danio rerio axin 2 (conductin, axil) (axin2), mRNA [NM_131561] 1.02E-07 chrnb3a Danio rerio cholinergic receptor, nicotinic, beta polypeptide 3a (chrnb3a), mRNA [NM_201220] 1.19E-07 sphkap Danio rerio SPHK1 interactor, AKAP domain containing (sphkap), mRNA [NM_001083045] 1.22E-07 solute carrier family 39 (zinc transporter), member 5 [Source:ZFIN;Acc:ZDB-GENE-060608-1] slc39a5 [ENSDART00000149698] 1.70E-07 si:dkey- 104n9.1 PREDICTED: Danio rerio uncharacterized LOC560366 (LOC560366), misc_RNA [XR_223934] 2.18E-07 htr1b Danio rerio 5-hydroxytryptamine (serotonin) receptor 1B (htr1b), mRNA [NM_001128709] 2.59E-07 chia.4 Danio rerio chitinase, acidic.4 (chia.4), mRNA [NM_200446] 2.61E-07 cyp2ad2 Danio rerio cytochrome P450, family 2, subfamily AD, polypeptide 2 (cyp2ad2), mRNA [NM_152954] 3.49E-07 cyp51 Danio rerio cytochrome P450, family 51 (cyp51), mRNA [NM_001001730] 3.53E-07 mych Danio rerio myelocytomatosis oncogene homolog (mych), mRNA [NM_001126109] 3.56E-07 oprd1b Danio rerio opioid receptor, delta 1b (oprd1b), mRNA [NM_212755] 4.18E-07 si:dkey- 117i10.1 si:dkey-117i10.1 [Source:ZFIN;Acc:ZDB-GENE-091204-371] [ENSDART00000143715] 4.46E-07 nmrk2 nicotinamide riboside kinase 2 [Source:ZFIN;Acc:ZDB-GENE-040912-44] [ENSDART00000140440] 5.52E-07 LOC570508 C-reactive protein 1 [Source:ZFIN;Acc:ZDB-GENE-060503-314] [ENSDART00000105662] 5.74E-07 Danio rerio nuclear receptor subfamily 5, group A, member 5 (nr5a5), transcript variant 1, mRNA nr5a5 [NM_214779] 7.18E-07 ptgs2b Danio rerio prostaglandin-endoperoxide synthase 2b (ptgs2b), mRNA [NM_001025504] 8.46E-07 fam131a Danio rerio family with sequence similarity 131, member A (fam131a), mRNA [NM_001114579] 9.68E-07 sult2st1 Danio rerio sulfotransferase family 2, cytosolic sulfotransferase 1 (sult2st1), mRNA [NM_198914] 1.01E-06 zgc:171226 Danio rerio zgc:171226 (zgc:171226), mRNA [NM_001102641] 1.37E-06 srd5a2a Danio rerio steroid-5-alpha-reductase, alpha polypeptide 2a (srd5a2a), mRNA [NM_001017703] 1.65E-06 angptl1b Danio rerio wu:fi40b08 (wu:fi40b08), mRNA [NM_001199970] 1.73E-06 zgc:158258 Danio rerio zgc:158258 (zgc:158258), mRNA [NM_001080668] 2.21E-06 Danio rerio guanine nucleotide binding protein (G protein), beta polypeptide 3b (gnb3b), mRNA gnb3b [NM_213202] 2.35E-06 LOC559915 potassium channel, subfamily V, member 1 [Source:HGNC Symbol;Acc:18861] [ENSDART00000102591] 2.78E-06 LOC100330 861 Uncharacterized protein [Source:UniProtKB/TrEMBL;Acc:F1Q7H4] [ENSDART00000113499] 2.78E-06 cdh13 cadherin 13, H-cadherin (heart) [Source:ZFIN;Acc:ZDB-GENE-060503-286] [ENSDART00000136754] 3.19E-06 si:dkeyp- lymphatic vessel endothelial hyaluronan receptor 1 [Source:HGNC Symbol;Acc:14687] 104h2.3 [ENSDART00000112109] 3.74E-06 kdm5bb Danio rerio lysine (K)-specific demethylase 5Bb (kdm5bb), mRNA [NM_001002166] 3.78E-06 Danio rerio ATPase, Na+/K+ transporting, alpha 1a polypeptide, tandem duplicate 5 (atp1a1a.5), mRNA atp1a1a.5 [NM_178099] 3.95E-06 neurotensin receptor 1 (high affinity) [Source:ZFIN;Acc:ZDB-GENE-090313-372] LOC569344 [ENSDART00000112436] 4.89E-06 Danio rerio cocaine- and amphetamine-regulated transcript protein 1 (CART1) mRNA, complete cds. cart4 [GU057833] 1.08E-05 LOC100537 PREDICTED: Danio rerio multidrug and toxin extrusion protein 1-like (LOC100537389), mRNA 389 [XM_003201709] 1.12E-05 spondin 2b, extracellular matrix protein [Source:ZFIN;Acc:ZDB-GENE-990415-161] spon2b [ENSDART00000054588] 2.11E-05 cryabb Danio rerio crystallin, alpha B, b (cryabb), mRNA [NM_001002670] 2.41E-05 calca Danio rerio calcitonin/calcitonin-related polypeptide, alpha (calca), mRNA [NM_001002471] 3.09E-05 ccdc85a Danio rerio coiled-coil domain containing 85A (ccdc85a), mRNA [NM_001114913] 3.61E-05 LOC101884 293 G protein-coupled receptor 137B [Source:HGNC Symbol;Acc:11862] [ENSDART00000099568] 4.19E-05 pla1a Danio rerio phospholipase A1 member A (pla1a), mRNA [NM_207056] 6.37E-05 phosphodiesterase 6B, cGMP-specific, rod, beta [Source:ZFIN;Acc:ZDB-GENE-090421-2] pde6b [ENSDART00000135816] 6.83E-05 si:busm1- 266f07.1 Danio rerio si:busm1-266f07.1 (si:busm1-266f07.1), mRNA [NM_001007167] 1.34E-04 Danio rerio slc12a10.3 solute carrier family 12 (sodium/potassium/chloride transporters), member 10, tandem slc12a10.3 duplicate 3 (slc12a10.3), mRNA [NM_001135131] 1.67E-04
______148
Supplements
si:ch73- 14h1.2 ferric-chelate reductase 1 [Source:HGNC Symbol;Acc:27622] [ENSDART00000129585] 1.94E-04 ido1 Danio rerio indoleamine 2,3-dioxygenase 1 (ido1), mRNA [NM_001083854] 2.38E-04 rnf114 Danio rerio ring finger protein 114 (rnf114), mRNA [NM_001001828] 2.49E-04 kcnk1b Danio rerio potassium channel, subfamily K, member 1b (kcnk1b), mRNA [NM_001145575] 2.61E-04 tgm1l1 transglutaminase 1 like 1 [Source:ZFIN;Acc:ZDB-GENE-060503-139] [ENSDART00000027444] 3.50E-04 itln3 Danio rerio intelectin 3 (itln3), mRNA [NM_001159584] 3.56E-04 Danio rerio sema domain, transmembrane domain (TM), and cytoplasmic domain, (semaphorin) 6D, like sema6dl (sema6dl), mRNA [NM_001017682] 3.85E-04 rps6ka2 Ribosomal protein S6 kinase [Source:UniProtKB/TrEMBL;Acc:E7F164] [ENSDART00000044705] 4.21E-04 nkx3.2 Danio rerio NK3 homeobox 2 (nkx3.2), mRNA [NM_178132] 4.94E-04 alpi.1 Danio rerio alkaline phosphatase, intestinal, tandem duplicate 1 (alpi.1), mRNA [NM_001014353] 5.74E-04 cyp19a1a Danio rerio cytochrome P450, family 19, subfamily A, polypeptide 1a (cyp19a1a), mRNA [NM_131154] 7.23E-04 fam49ba Danio rerio family with sequence similarity 49, member Ba (fam49ba), mRNA [NM_200070] 1.06E-03 Danio rerio ubiquitin-conjugating enzyme E2W (putative), mRNA (cDNA clone IMAGE:7405075), partial ube2w cds. [BC095816] 1.42E-03 tmem8c Danio rerio transmembrane protein 8C (tmem8c), mRNA [NM_001002088] 1.46E-03 faa52c02.x1 Gong zebrafish testis Danio rerio cDNA clone IMAGE:5897450 3', mRNA sequence zgc:194246 [BQ419512] 2.64E-03 fc59c03.x1 Zebrafish WashU MPIMG EST Danio rerio cDNA clone IMAGE:3725668 3', mRNA sequence wu:fc59c03 [AI878472] 2.77E-03 LOC794656 Danio rerio novel NACHT domain containing protein (LOC794656), mRNA [NM_001128355] 3.17E-03 fah Danio rerio fumarylacetoacetate hydrolase (fumarylacetoacetase) (fah), mRNA [NM_199601] 3.29E-03 LOC559569 egl nine homolog 2 (C. elegans) [Source:ZFIN;Acc:ZDB-GENE-060503-757] [ENSDART00000090635] 3.42E-03 zgc:162060 Danio rerio zgc:162060 (zgc:162060), mRNA [NM_001089450] 3.60E-03 si:ch211- 282j17.3 Danio rerio si:ch211-282j17.3 (si:ch211-282j17.3), mRNA [NM_001030222] 3.61E-03 zgc:112531 Danio rerio zgc:112531 (zgc:112531), mRNA [NM_001017746] 4.06E-03 nitr6a Danio rerio novel immune-type receptor 6a (nitr6a), mRNA [NM_199130] 4.59E-03 LOC101886 414 si:ch211-193e5.3 [Source:ZFIN;Acc:ZDB-GENE-091116-7] [ENSDART00000153736] 4.71E-03 somatomedin B and thrombospondin, type 1 domain containing [Source:HGNC Symbol;Acc:30362] LOC796009 [ENSDART00000155596] 5.21E-03 kiss1ra Danio rerio KISS1 receptor a (kiss1ra), mRNA [NM_001105679] 6.24E-03 csrp3 Danio rerio cysteine and glycine-rich protein 3 (cardiac LIM protein) (csrp3), mRNA [NM_001006026] 6.87E-03 ATPase, Ca++ transporting, ubiquitous [Source:ZFIN;Acc:ZDB-GENE-060531-103] atp2a3 [ENSDART00000086443] 7.54E-03 thbs4a Danio rerio thrombospondin 4a (thbs4a), mRNA [NM_001114424] 7.60E-03 LOC101886 366 fibronectin type III domain containing 7 [Source:HGNC Symbol;Acc:26668] [ENSDART00000122432] 8.65E-03 cryabb Danio rerio crystallin, alpha B, b (cryabb), mRNA [NM_001002670] 9.77E-03 crp4 Danio rerio C-reactive protein 4 (crp4), mRNA [NM_001040297] 1.26E-02 Danio rerio similar to solute carrier family 6 (neurotransmitter transporter), member 14, mRNA (cDNA clone slc6a14 IMAGE:7216712), partial cds. [BC117616] 1.30E-02 si:dkey- 5-hydroxytryptamine (serotonin) receptor 2A, G protein-coupled [Source:HGNC Symbol;Acc:5293] 276l13.4 [ENSDART00000150982] 1.32E-02 zgc:91985 Danio rerio zgc:91985 (zgc:91985), mRNA [NM_001003499] 1.42E-02 si:ch211- 215c18.4 Danio rerio si:ch211-215c18.4 (si:ch211-215c18.4), mRNA [NM_001144790] 1.55E-02 LOC100537 238 trafficking protein, kinesin binding 1 [Source:HGNC Symbol;Acc:29947] [ENSDART00000085686] 1.75E-02 tekt2 Danio rerio tektin 2 (testicular) (tekt2), mRNA [NM_001017432] 1.85E-02 AGENCOURT_109125804 NIH_ZGC_30 Danio rerio cDNA clone IMAGE:9045538 5', mRNA sequence rpl21 [EV760012] 2.04E-02 wu:fk83g11 CT605696 ZF_mu Danio rerio cDNA clone ZF_mu_165o14 3', mRNA sequence [CT605696] 2.07E-02 acss2l Danio rerio acyl-CoA synthetase short-chain family member 2 like (acss2l), mRNA [NM_001277117] 2.09E-02 gpr1 G protein-coupled receptor 1 [Source:ZFIN;Acc:ZDB-GENE-091204-457] [ENSDART00000093341] 2.13E-02 ______149
Supplements
zgc:153913 Danio rerio zgc:153913 (zgc:153913), mRNA [NM_001079979] 2.26E-02 b4galnt1a Danio rerio beta-1,4-N-acetyl-galactosaminyl transferase 1a (b4galnt1a), mRNA [NM_001080570] 2.61E-02 rlf rearranged L-myc fusion [Source:ZFIN;Acc:ZDB-GENE-050208-257] [ENSDART00000092941] 2.63E-02 egr3 Danio rerio early growth response 3 (egr3), mRNA [NM_001002647] 2.71E-02 FDR103-P00002-DEPE-R_B17 FDR103 Danio rerio cDNA clone FDR103-P00002-BR_B17 3', mRNA agrp sequence [EH458154] 2.89E-02 fc46e01.x1 Zebrafish WashU MPIMG EST Danio rerio cDNA clone IMAGE:3724440 3', mRNA sequence wu:fc46e01 [AI883911] 3.52E-02 Danio rerio ELOVL family member 7, elongation of long chain fatty acids (yeast) b (elovl7b), mRNA elovl7b [NM_199778] 3.56E-02 pdlim2 Danio rerio PDZ and LIM domain 2 (mystique) (pdlim2), mRNA [NM_001042766] 3.97E-02 AGENCOURT_30564870 NIH_ZGC_19 Danio rerio cDNA clone IMAGE:7431121 5', mRNA sequence bricd5 [CO918642] 4.21E-02 LOC792623 dual specificity phosphatase 27 (putative) [Source:HGNC Symbol;Acc:25034] [ENSDART00000125062] 4.23E-02 tcf7 Danio rerio transcription factor 7 (T-cell specific, HMG-box) (tcf7), mRNA [NM_001012389] 4.50E-02 LOC568694 tripartite motif containing 29 [Source:HGNC Symbol;Acc:17274] [ENSDART00000082304] 4.51E-02 wnt10a Danio rerio wingless-type MMTV integration site family, member 10a (wnt10a), mRNA [NM_130980] 4.57E-02
Significant Genes of analysis of variance Copper (6.1 µg Cu/L) treated 96 hpf embryos p-value Gene Symbol Description (Corr) lin28a Danio rerio lin-28 homolog A (C. elegans) (lin28a), mRNA [NM_201091] 8.84E-08 fb39e08.x1 Zebrafish WashU MPIMG EST Danio rerio cDNA clone IMAGE:3714278 3', mRNA wu:fb39e08 sequence [AI444465] 1.12E-05 Danio rerio cytochrome P450, family 19, subfamily A, polypeptide 1b (cyp19a1b), mRNA cyp19a1b [NM_131642] 2.32E-05 ankef1a Danio rerio ankyrin repeat and EF-hand domain containing 1a (ankef1a), mRNA [NM_001025543] 4.64E-04 si:ch211- 197g15.6 Danio rerio si:ch211-197g15.6 (si:ch211-197g15.6), mRNA [NM_001045218] 3.47E-03 smim7 Danio rerio small integral membrane protein 7 (smim7), mRNA [NM_001198743] 5.60E-03 baiap2l2 Danio rerio BAI1-associated protein 2-like 2 (baiap2l2), mRNA [NM_001080804] 6.72E-03 si:dkey-175g6.2 fj49c03.x1 zebrafish adult brain Danio rerio cDNA 3', mRNA sequence [AW280086] 7.70E-03
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