NEUROBLASTOMA SH-SY5Y AND NEURAL PROGENITOR C17.2CELL LINES AS MODELS FOR NEUROTOXICOLOGICAL STUDIES

Jessica Lundqvist

Neuroblastoma SH-SY5Y and neuralprogenitor C17.2 cell lines as modelsfor neurotoxicological studies

Jessica Lundqvist

©Jessica Lundqvist, Stockholm University 2018 ISBN print 978-91-7797-108-5ISBN PDF 978-91-7797-109-2 Cover: Differentiated neural progenitor cells, photo taken by Jessica Lundqvist Printed in Sweden by Universitetsservice US-AB, Stockholm 2018Distributor: Department of Neurochemistry, Stockholm University

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List of Publications

I. Gustafsson H, Runesson J, Lundqvist J, Lindegren H, Axelsson V, Forsby A Neurofunctional endpoints assessed in human neuroblastoma SH-SY5Y cells for estimation of acute systemic toxicity Toxicology and Applied Pharmacology, 2010, 245(2), 191-202 II. Lundqvist J, El Andaloussi-Lilja J, Svensson C, Gustafsson Dorfh H, Forsby A Optimisation of culture conditions for differentiation of C17.2 neural stem cells to be used for in vitro toxicity tests Toxicology In Vitro, 2013, 27(5), 1565-1569 III. Lundqvist J, Svensson C Attoff K and Forsby A Altered mRNA expression and cell membrane potential in the differenti-ated C17.2 cell model as indicators of acute neurotoxicity Applied In Vitro Toxicology, 2016, 3(2), 154-162 IV. Attoff K., Gliga A., Lundqvist J., Norinder U. and Forsby A Whole genome microarray analysis of neural progenitor cells C17.2 dur-ing differentiation and selection of validation of mRNA biomarkers for developmental neurotoxicity PLoS One, 2017, 12(12), 1-29

Publications that are not included in this thesis Attoff K, Kertika D, Lundqvist J, Oredsson S and Forsby A. Acrylamide affects proliferation and differentiation of the neural progenitor cell line C17.2 and the neuroblastoma cell line SH-SY5Y Toxicology In Vitro, 2016, 35, 100-111 Forsby A, Norman KG, El Andaloussi-Lilja J, Lundqvist J, Walczak V, Curren R, Martin K, Tierney NK. Using novel in vitro NociOcular assay based on TRPV1 channel ac-tivation for prediction of eye sting potential of baby shampoos Toxicological Sciences, 2012, 129(2), 325-3 Lindegren H, Mogren H, El Andaloussi-Lilja J, Lundqvist J, Forsby A. Anionic linear aliphatic surfactants activate TRPV1: a possible endpoint for estimation of detergent induced eye nociception? Toxicology In Vitro, 2009, 23(8), 1472-1476 El Andaloussi-Lilja J, Lundqvist J, Forsby A. TRPV1 expression and activity during retinoic acid-induced neu-ronal differentiation Neurochemisty International, 2009, 55(8), 768-74. Edvinsson B, Lundqvist J, Ljungman P, Ringdén O, Evengård B. A prospective study of diagnosis of Toxoplasma gondii infection af-ter bone marrow transplantation Acta Pathologica, Microbiologica et Immunologica Scandinavica, 2008, 116 (5), 345-351

Abstract

We are surrounded by chemicals, thus understanding how exposure

to these chemicals affect us during our life is of great social importance. In order to predict human acute toxicity of chemicals, cosmetics or drugs, development of novel in vitro test strategies is required. The overall aim of this thesis was to evaluate whether two different cell line models could be used to predict acute neurotoxicity or developmental neurotoxicity. In paper one, we identified changes in cell membrane potential (CMP) as the most sensitive indicator of toxicity in neuroblas-toma SH-SY5Y cells.

In the following studies, we evaluated the capacity of the murine neu-ral progenitor cell line C17.2 to differentiate into mixed cell cultures. Upon differentiation of the C17.2 cells we could identify two morpho-logically distinguishable cell types; astrocytes and neurons (Paper II). We then investigated how differentiated C17.2 cells responded to non-cytotoxic concentrations of three known neurotoxic and three non-neu-rotoxic substances. The neurotoxicants induced depolarisation of CMP and alteration in the mRNA expression of at least one of the three bi-omarkers studied, i.e. βIII-tubulin, glial fibrillary acidic protein or heat shock protein-32. In contrast, no significant effects were observed when exposed to non-neurotoxic compounds (Paper III).

To further characterise the C17.2 cell model during differentiation, an mRNA microarray analysis of the whole genome was performed. The 30 most significantly altered biomarkers with association to neural development were identified. The mRNA expression of the 30 bi-omarkers were used as a panel to alert for developmental neurotoxicity by exposing C17.2 cells during differentiation to toxicants known to induce impaired nervous system development. All but two of the se-lected genes were significantly altered by at least one of the chemicals, but none of the 30 genes were affected when treated with the negative control (Paper IV).

In conclusion, the differentiated C17.2 neural progenitor cell line seems to be an attractive model for studying and predicting acute and developmental neurotoxicity.

Contents

Abstract .......................................................................................................... iii

Abbreviations ................................................................................................. ix

Introduction ..................................................................................................... 1 Predicting human risks from chemical exposures ......................................................... 1

General definition of toxicology ................................................................................ 1 Definition of acute and chronic toxicity ..................................................................... 1 Models to define acute toxicity ................................................................................. 2 The 3R principles ..................................................................................................... 2 Regulatory movements towards the use of non-animal based testing ..................... 3

Evaluation of in vitro models for assessment of acute toxicity ....................................... 3 MEIC ....................................................................................................................... 3 ACuteTox................................................................................................................. 5

Development of the AOP paradigm ............................................................................... 6 Definition of AOP ..................................................................................................... 7 The OECD AOPwiki ................................................................................................. 8

Neurotoxicology ............................................................................................................ 8 Well studied compounds that induce acute neurotoxicity ......................................... 8 Well studied compounds that induce chronic neurotoxicity ...................................... 9 Key target cell types for acute neurotoxicity ........................................................... 11

Blood-brain barrier ............................................................................................ 12 Astrocytes ........................................................................................................ 13 Neurons ............................................................................................................ 14

Key molecular targets in the nervous system ......................................................... 14 Neurotransmitter homeostasis .......................................................................... 14 Acetylcholine .................................................................................................... 15 Catecholamine neurotransmitter family ............................................................ 15 Glutamate ......................................................................................................... 17 GABA ............................................................................................................... 18 Neurotransmitter receptors ............................................................................... 18

The metabotropic receptor family ................................................................ 18 Ionotropic receptors .................................................................................... 21

Voltage operated ion channels ......................................................................... 23 Sodium channels......................................................................................... 23

Calcium channels ........................................................................................ 23 Subcellular systems ............................................................................................... 25 Primary cells .......................................................................................................... 25 Cell lines ................................................................................................................ 25

PC12 cells ........................................................................................................ 26 LUHMES .......................................................................................................... 26 SH-SY5Y .......................................................................................................... 27 Stem cells ......................................................................................................... 28 Embryonic stem cells........................................................................................ 28 Induced pluripotent stem cells .......................................................................... 29 The P19 cell line ............................................................................................... 29 C17.2 cell line ................................................................................................... 30

Hypotheses and Aims of the present studies ............................................... 31

Methodological considerations ...................................................................... 32 Chemicals ................................................................................................................... 32 Model systems ............................................................................................................ 38

SH-SY5Y (Paper I) ................................................................................................ 38 C17.2 (Paper II, III and IV) ..................................................................................... 38 Differentiation ........................................................................................................ 39

Analyses of mRNA expression .................................................................................... 40 Reverse Transcriptase Real-Time polymerase chain reaction (paper II) ................ 40 Reverse Transcriptase quantitative-PCR (paper III and IV) ................................... 41 Genome microarray (paper IV) .............................................................................. 42 Protein expression using western blot (paper II) .................................................... 42

Neurofunctional assays ............................................................................................... 42 Cell membrane potential (paper I, III) ..................................................................... 42 Noradrenaline uptake (paper I) .............................................................................. 43 Acetylcholine receptor activity and voltage operated Ca2+ channels (paper I) ........ 44 Acetylcholine esterase activity (paper I) ................................................................. 44

Cell viability tests (paper I and IV) ............................................................................... 45 Transcriptomics ........................................................................................................... 45

mRNA biomarkers ................................................................................................. 46

Results and Discussion ................................................................................. 47 Paper I ........................................................................................................................ 47 Paper II ....................................................................................................................... 51 Paper III ...................................................................................................................... 53 Paper IV ...................................................................................................................... 54

Conclusions and outlook ............................................................................... 57

Populärvetenskaplig sammanfattning ........................................................... 59

Acknowledgements ....................................................................................... 61

References .................................................................................................... 63

Abbreviations

3R Replacement, Reduction and Refinement ABC ATP-binding cassette (ABC) ACh Acetylcholine AChE Acetylcholine esterase AChR Acetylcholine receptor AGGR Aggregated embryonic rat brain cells AMPAR �-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor AOP Adverse Outcome Pathway ATRA All-trans retinoic acid BBB Blood-brain barrier BDNF Brain-derived neurotrophic factor cDNA Complementary DNA ChAT Choline acetyltransferase CMP Cell membrane potential CNS Central nervous system Ct Threshold cycle DA Dopamine DEG Differentially expressed genes DNT Developmental neurotoxicity ESCs Embryonic stem cells FBS Foetal bovine serum FMP FLIPR membrane potential G-protein Guanosine triphosphate-binding protein GABA �-aminobutyric acid GABAAR �-aminobutyric acid receptor, type A GAD Glutamic acid decarboxylase GAPDH Glyceraldehyde 3-phosphate dehydrogenase GFAP Glial fibrillary acidic protein GluR Glutamate receptors GPCRs G-protein coupled receptors hESC Human derived embryonic stem cells IC50 Concentration inducing 50% cytotoxicity/reduction in viable cells IP3 Inositol-1,4,5-trisphosphate iPSC Induced pluripotent stem cells KEs Key Events

KERs Key Event Relationships LD50 Lethal dose 50% LDH Lactate dehydrogenase L-dopa 3,4-dihydroxyphenylalanine LUHMES Lund University human mesencephalon cells mAChR Muscarinic acetylcholine receptors MDMA 3,4-methylenedioxymetamphetamine (Ecstasy) MeHg Methyl mercury MEIC Multicentre Evaluation of In Vitro Cytotoxicity MIE Molecular initiating effect mGluR Metabotropic glutamate receptor MOA Modes of action MPDP+ 1-methyl-4-phenyl-2,3-di hydropyridinium ion MPP+ 1-methyl-4-phenylpyridinium MPTP 1- methyl-4-phenyl-1,2,3,6-tetrahydropyridine mRNA Messenger ribonucleic acid MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide NA Noradrenalin nAChR Nicotinic acetylcholine receptor NADPH Nicotinamide adenine dinucleotide phosphate NGF Nerve growth factor NMDA N-methyl-D-aspartate NPCs Neural progenitor cells NRU Neutral red uptake NSCs Neural stem cells NT Neurotransmitter OECD Organisation of Economic Co-operation and Development OPs Organophosphates PC12 Pheochromocytoma cells PCR Polymerase chain reaction PD Parkinson’s disease PLC Phospholipase C PNS Peripheral nervous system RNA Ribonucleic acid RT-PCR Reverse transcriptase polymerase chain reaction TG Test guidelines TH Tyrosine hydroxylase TPA 12-O-tetradecanoylphorbol-13-acetate vGluT Vesicular glutamine transporters VOCC Voltage-operated calcium channels VOSC Voltage-operated sodium channels WP Work packages

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Introduction

Predicting human risks from chemical exposures

General definition of toxicology We are exposed to chemicals from our surroundings during our whole life and even before we are born. There is little we can do about it, but increasing the knowledge about the effects of exposure is a good start. Therefore, the field of toxicology is more important today than ever. The term toxicology derives from the Greek words toxicos (poisonous) and logos (word) and refers to the study of any adverse effect, i.e. any alteration from the normal cellular, biochemical or macromolecular fea-tures in a living organism or the environment. It also includes preven-tion and amelioration of such adverse effects. Toxic substances that are produced by living organisms are called toxins. Substances that are syn-thesized by man or naturally found in the environment are called toxi-cants. The father of toxicology, Paracelcus, stated “Sola dosis facit ven-enum” (which basically translates to “Poison is in everything and noth-ing is without poison. The dosage makes it a poison or a remedy”) when he discovered that mercury, which is extremely toxic, could also treat syphilis at low doses (Paracelsus, 1493-1541). There are toxins with extremely high potency e.g., botulinum toxin from bacteria Clostridium botulinum, one gram could kill more than one million people (Dhaked, et al. 2010).

Definition of acute and chronic toxicity Acute toxicity is defined as a general adverse effect, which can be de-tected within 24 hours and during an observation period of 2 weeks after exposure to a single dose or multiple doses within 24 hours of a toxicant (Duffus 1993). The compound can be administrated by using three dif-ferent routes i.e. orally, by inhalation or dermally (Alttox 2014). Chronic toxicity is defined as adverse effects after a long exposure time to toxicant. This exposure can be directly lethal, thus sub-lethal effects

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are more commonly seen e.g., impaired reproduction, proliferation, or behavioural changes.

Models to define acute toxicity Ever since the beginning of toxicological research, animals have been used to investigate the toxicity of substances. For estimation of acute toxicity, the lethal dose 50% (LD50) has been mostly used. LD50 is defined as the single dose, which kills 50% of the animals in a group and is estimated from dose-response curves ranging from non-toxic doses to high doses that generate 100% mortality (OECDa). This method of determining toxicity has been debated for several years be-cause of the many animals being sacrificed, the inhumane procedure itself and for its relevance (Balls and Clothier 1991; Zbinden and Flury-Roversi 1981). Hence, alternative methods that require fewer animals and lower doses were developed in the 1990´s. The fixed dose proce-dure was proposed as one alternative to the criticised LD50 method of toxicity testing and is now included in the Organisation of Economic Co-operation and Development (OECD) test guidelines (TGs) (OECDb).

The 3R principles Almost 60 years ago, William Russel and Rex Burch coined “the 3R principle” in order for scientific methods to be more humane for labor-atory animals in cancer research (The Principles of Humane Experi-mental Technique) (W.M.S. Russell and R.L. Burch). The OECD has considered the 3R concept in toxicity test guideline development since 1981, and the organisation has continuously implemented replacements or amendments of TGs with significant impact on the 3Rs (OECDc). The 3R abbreviation is defined as Replacement, Reduction and Refine-ment of experiments that involve animals in research. The first R, re-placement, means that the usage of animals should be avoided in toxi-cology testing, if possible. New, animal-free models and tools should be used together with the latest technologies and reports from science. The use of animal models is both time- and resource consuming and sometimes the data received from animal studies are not applicable to humans because of, e.g. different metabolism or different expression of receptors. The replacement section has been subdivided into two sec-tions; full- and partial- replacement (NC3R). Full replacement means that no animals are used, but human tissue, human primary cells, exist-ing cell lines or computer modelling (Prescott and Lidster 2017). In par-

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tial replacement, animals that are less developed in terms of pain sen-sation, e.g. nematodes and flies can be used as alternative full organism models. Primary cell cultures and tissues of animal origin are also con-sidered as partial replacement alternatives. The second R, reduction, means that if the usage of laboratory animals cannot be completely avoided, the number of animals should be minimised. More efforts should be made upon designing experiments to generate maximum in-formation of the received data, without losing the reproducibility and robustness of the model (Tornqvist, et al. 2014). The third R, refine-ment, stands for minimising the suffering and emphasising the wellbe-ing of the animal. This includes housing (Makowska and Weary 2016) and handling, which can also affect the results, hence contributing to reduction (NC3R).

Regulatory movements towards the use of non-animal based testing Hazard identification/characterisation, exposure assessment and risk assessment is the path of regulatory management (Tollefsen, et al. 2014). In regulatory toxicity testing and risk assessment, a paradigm shifts from using in vivo data to a more knowledge-based predictive risk assessment in humans have been suggested (Bal-Price, et al. 2017). The concept “modes of action” (MOA) was coined in the field of cancer by the Environmental Protective agency (EPA) (EPA 2005). However, in 2007, National Research Council stated the attempt to make toxicity testing for humans more relevant to the exposure of toxicants, less ex-pensive than in vivo tests and quicker due the huge amount of chemicals out in the market (NRC 2007).

Evaluation of in vitro models for assessment of acute toxicity Many animals have been sacrificed during the years in the predictions of lethal doses to humans. However, researchers have tried to solve the problems with assessing acute toxicity by using in vitro models. Here follow some examples of this work and efforts to make the science more animal-friendly but at the same time, not think less of the safety of chemical exposure to humans.

MEIC One of the pioneers in the field of in vitro toxicology, i.e. toxicity tests in cultured cells, was Björn Ekwall (Clemedson 2001). In the middle of

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1970´s, only 50 laboratories worldwide tested chemicals for general cy-totoxicity using cell cultures (Ekwall 1983). Screening of cytotoxicity was performed by using the metabolic inhibition test, “MIT-24”. HeLa cells were exposed to different compounds, pharmaceuticals, solvents and metals for 24 hours (Ekwall and Sandström 1978a; Ekwall and Sandström 1978b). The concentrations that induced 50% cytotoxicity (IC50) in HeLa cells were compared to the lethal blood concentrations in humans (Ekwall 1980). However, almost 40 years ago, it was stated that “One problem of in vitro cytotoxicology is the incomparability of results of different studies, due to the variation in tissue culture meth-ods”(Ekwall 1980b). This was also confirmed in the Multicentre Eval-uation of in Vitro Cytotoxicity (MEIC) study, which was started and organised by Ekwall and the Scandinavian Society of Cell Toxicology (Bondesson, et al. 1989). In the MEIC project, 50 compounds with sub-stantial human and in vivo toxicity data were tested in 67 in vitro assays (Clemedson, et al. 1998) and the cytotoxic concentrations were com-pared to human lethal peak concentration.

Human cell lines, primary cultures, animal cell lines and ecotoxico-logical test models were used in the MEIC study. To mention a few assays of interest, tetrazolium assay (MTT), neutral red uptake (NRU), lactate dehydrogenase (LDH) release, ATP content or release were used to assess cell viability (Clemedson, et al. 1996b). The main objective of the first part of the MEIC project was to broader the spectrum of cell models used for estimation of general toxicity, however organ-specific cell models were underrepresented (Clemedson, et al. 1996b). In part II, comparative analysis was performed on the received data (Clemed-son, et al. 1996a). The results from this study showed that the use of multiple cell lines for different cell growth- and viability tests did not really improve toxicity prediction from the cytotoxicity assays. Hence, moving forward in the project, the number of cell lines to be used for testing could be reduced, which would save both time and money. Fur-thermore, it was shown that animal derived cells did not predict human toxicity very well, which could lead to a shift using human derived cell lines instead. In part III, additional methods were used and a new anal-ysis was done (Clemedson 1998). The results from this study just con-firmed the results from part II. In part IV (Clemedson, et al. 1998), 20 additional chemicals were evaluated in 67 methods together with the previous 30 chemicals in eight new methods, which confirmed the basal cytotoxicity concept “all cell lines ought to have a similar response to chemicals” (Clemedson 1998).

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In part V, rodent (LD50) and human data (estimated mean lethal dose) were published (Ekwall, et al. 1998a). Information about human acute lethal doses, toxicokinetic monitoring of plasma concentration and post-mortem lethal blood concentrations were collected. It was stated that the outcome of any meaningful evaluation depends on many factors. The quality of the data being compared is one of the most im-portant factors for a successful validation, i.e. how true and reliable the raw data are (Ekwall, et al. 1998a). The data could in some cases be inconclusive, thus to report a “golden standard test” would be unrealis-tic. Nevertheless, multivariate partial least squares (PLS) analyses showed that a set of four endpoints, analysed in three human cell mod-els, correlated quite well to the human lethal blood concentration with R2=0.77 (Ekwall, et al. 1998; Clemedson, et al. 2000). However, the human toxicity was under-estimated for some compounds. These miss-predicted compounds were called outliers and the majority of these were known to be toxic because of a neuronal MOA.

ACuteTox Based on the findings in the MEIC project and a following validation study of two cytotoxicity tests (Anon 2006) the ACuteTox (Optimisa-tion and prevalidation of an in vitro test strategy for predicting human acute toxicity) project was initiated in 2005. The ACuteTox project was funded by the 6th EU framework programme as an attempt to optimise an alternative toxicity test strategy for estimation of acute systemic tox-icity (Clemedson, et al. 2007). One aim was to develop and identify test systems, i.e. cell models and assays, which could alert for chemicals possessing organ specific MOA. The ACuteTox project also considered toxicokinetic features such as absorption, distribution, metabolism and excretion together with computer-based prediction (in silico) models. Human lethal blood concentrations from intoxication cases (Sjostrom, et al. 2008b) and data derived from animal studies (LD50) (Hoffmann, et al. 2010) were used as reference values for evaluation of the in vitro-derived toxicity data.

The ACuteTox project was divided into 10 work packages (WPs) (Table 1.) (ACuteTox). General cytotoxicity data were collected in WP2 (Clothier, et al. 2008). The neutral red uptake assay using the 3T3 Balb/c mouse fibroblast cell line (3T3-NRU) was one of them. The aim for WP7 was to elucidate organ-specific toxicity in the liver, kidney and the nervous system. The neurotoxicity (WP7.1) assays were used on well-established models; aggregates of embryonic rat brain cells (AGGR), primary cell cultures and cell lines. Specific endpoints such

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as voltage-operated ion channel function, receptor signalling and neu-rotransmitter release, up-take and inactivation were studied. Less spe-cific endpoints were also examined, e.g. energy status, mRNA synthe-sis, cell membrane potential (CMP) and multi-endpoint mRNA expres-sion. The data obtained in the neuronal model systems were compared to the general cytotoxicity data generated in the 3T3-NRU assay and to the estimated human lethal blood concentration.

Table 1. Mission of each Work Package (WP) in the ACuteTox project

Work package Mission

WP1 List of chemicals to use in the project Create an “in vivo” data base

WP2 Create an “in vitro” data base

WP3 Iterative amendment of testing strategy, identification of outlier

WP4 New end-points, New cell systems

WP5 Alerts and correctors in toxicity screening: Role of ADE1

WP6 Alerts and correctors in toxicity screening: Role of metabolism

WP7 Alerts and correctors in toxicity screening: Role of target organ toxicity

WP7.1 Neurotoxicity

WP7.2 Nephrotoxicity

WP7.3 Hepatotoxcity

WP8 Technical optimisation of the amended test strategy

WP9 Pre-validation of the test system

WP10 Management, dissemination and exploitation of results

1ADE; Adsorption, distribution and excretion

One outcome of the ACuteTox project was that the multi-endpoint anal-yses (mRNA expression of cell-specific and stress genes, global glu-cose uptake and RNA synthesis) studied in the AGGR seemed to be the best performing neuronal assay. The AGGR assay generated most neu-rotoxicity alerts, i.e. was more sensitive that the cytotoxicity assay (Forsby, et al. 2009), and could perform the best prediction of toxic classes (Zurich, et al. 2013; Kinsner-Ovaskainen, et al. 2013).

Development of the AOP paradigm During the years, a substantial amount of data regarding toxicity has been produced. A new program was launched during 2012 by the OECD regarding Adverse outcome pathway (AOP) (OECDd) as an an-alytical method, which links toxic events together at different levels in

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The OECD AOPwiki The OECD (OECDe) has developed number of test guidelines regard-ing testing of chemicals in section 4 (health effects) (OECDf) e.g., for in vivo developmental toxicity (OECDg). Some of the developed AOPs in the database AOPwiki (AOPwiki a), have OECD status. One exam-ple of an AOP from AOPwiki is the MIE binding of agonist to the NMDA glutamate receptor (AOPwiki b), which leads to the AO impair-ment of learning and memory dysfunction.

Neurotoxicology Since the nervous system is complex with its many diverse types of cells and divergent functions, there is a high number of targets that may be involved in MIEs causing life-threatening acute adverse outcomes such as convulsions and respiratory arrest. Many of the targets are lig-and-gated or voltage-operated ion channels or G-protein coupled recep-tors (GPCRs). The effects and symptoms of neurotoxicity can be acute, however they can also appear after month or years after the exposure, or repeated exposures.

Well studied compounds that induce acute neurotoxicity Many plants synthesise natural toxins with neurotoxic properties such as Atropa belladonna (Chadwick, et al. 2015). The plant contains the tropane alkaloids atropine, scolpamine and hyoscyamine, toxins that are antagonists to the muscarinic acetylcholine receptors (mAChR) and cause symptoms after acute exposure such as impaired parasympathetic signalling resulting in symptoms such as dry mouth, urinary retention, flushing, papillary dilation, constipation, confusion and delirium (Demirhan, et al. 2012). The fatal dose of atropine for a human is 15 mg (Chadwick, et al. 2015).

Another example of a toxin with an acute neuronal MOA is nicotine from the Nicotiana tabacum plant, with a human fatal dose of 30-60 mg (Mayer 2014). Nicotine is a nicotinic acetylcholine receptor (nAChR) agonist. Intoxication is characterised by nausea, vomiting, hypersaliva-tion, increased pulse, increased blood pressure, bradycardia, tachycar-dia, dyspnea, convulsions, coma and respiratory arrest due to over stim-ulation of the peripheral and central nervous systems (PNS and CNS, respectively) (Schneider, et al. 2010; Thornton, et al. 2014).

Strychnine is a bitter-tasting alkaloid, found in the seeds of Strychnos nux-vomica, which is absorbed within minutes from the gastrointestinal

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tract after oral exposure (Sgaragli and Mannaioni 1973). The fatal dose in human of strychnine is 1.5 mg/kg (Flood 1999; Wood, et al. 2002). Strychnine is a competitive antagonist of glycine receptors. Upon ex-posure to strychnine, an over-excitation of inhibitory interneurons will occur. Loss of this inhibitory effect will result in muscle spasms, con-vulsions, exaggerated startle response and a painful death (Harvey, et al. 2008).

Organophosphates (OPs) consist of a group of synthetic chemicals, which are mostly used in agriculture as pesticides or insecticides. How-ever, OPs can also be used as chemical warfare nerve agents (Jacquet, et al. 2016). Chemical warfare nerve agents (e.g., tabun, sarin and soman) were developed in Germany before the 2nd world war. However, since then, several nations e.g., USA, Soviet Union and China, devel-oped other OP agents, e.g. “V”, “VX”, “RVX” and “CVX”. However most countries in the world have now agreed to follow the Chemical Weapons Convention and not use or produce chemical warfare nerve agents (Samuels 2005). The OP chemicals have a simple structure and their lethal MOA is irreversible inhibition of acetylcholine esterase (AChE). Therefore, the acetylcholine signalling is neither terminated in the neuromuscular junctions, nor in the nerve-gland junction (Colovic, et al. 2013b; Gupta, et al. 1986). The acute exposure to OPs leads to severe symptoms like salivation, lacrimation, urination, gastrointestinal upset, emesis (vomiting), diaphoresis, diarrhea, miosis (pupil contrac-tion), bradycardia, bronchospasm and bronchorrhea, all symptoms that are due to over-excitation of cholinergic neurons (Paudyal 2008). Atro-pine can used as an antidote. However, too high dose will induce delir-ium instead (Bowden and Krenzelok 1997) due to the action on the muscarinic acetylcholine receptor (see above) (Bardin and Van Eeden 1990).

Well studied compounds that induce chronic neurotoxicity Some chemicals are known to cause degeneration of the CNS or spe-cific areas of the brain after repeated/chronic exposure. One global pol-lutant of major concern is mercury. Once in the ecological system, it stays there and it is transformed by chemical reactions, i.e. oxidation, reduction and methylation, to biologically accumulating mercury deriv-atives (Driscoll, et al. 2013; Morel, et al. 1998). Special attention has been given to methylated mercury (MeHg). This compound is neuro-toxic due to its bioavailability e.g. translocation over the blood-brain barrier (BBB) by an amino acid carrier (Kerper, et al. 1992). Even low levels of MeHg are of great concern due to the possibility to cross the

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placenta barrier and thereby, can accumulate in the brain of the foetus (Ceccatelli, et al. 2013). As a matter of fact, MeHg is one of the most significant compounds that are known to generate developmental neu-rotoxicity (DNT) (Grandjean and Landrigan 2006; Radonjic, et al. 2013).

Meperidine (1- methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)) is an example of a neurotoxic compound, which induces symptoms like Parkinson’s disease (PD), i.e. impaired motor function due to specific degeneration of neurons in substatia nigra pars com-pacta (Langston, et al. 1984; Langston, et al. 1983; Markey, et al. 1984).

The MOA of MTPT was unknown until drug users started to develop parkinsonian symptoms e.g., impaired motor functions (Langston, et al. 1983). MPTP is lipophilic and can translocate over the BBB where it is taken up by astrocytes (Heikkila, et al. 1984; Ransom, et al. 1987). In the astrocytes, the conversion of the MPTP (Figure 2) occurs by mito-chondrial monoamine oxidase-B (MAO-B) (Chiba, et al. 1984) to the intermediate 1-methyl-4-phenyl-2,3-di hydropyridinium ion (MPDP+) and its conjugated base form 1-methyl-4-phenyl-2,3-dihydro-pyridinium (1,2-MPDP). The neurotoxic cation metabolite 1-methyl-4-phenylpyridinium (MPP+) forms by autoxidation and is translocated from astrocytes through the organic cation transporter 3 into dopamin-ergic neurons by the dopamine transporter (DAT).

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Figure 2. The metabolic conversion of MPTP to MPP+ via the intermediate MPDP+ and 1,2-MPDP.

Inside the neuron, MPP+ interferes with complex I (NADPH-dehydro-genase) in the electron transport chain, which results in a decrease of adenosine triphosphate (ATP) concomitantly with an increase of the of superoxide ion (O2

•–), which starts a process where cell death is the out-come (Schildknecht, et al. 2017).

Rotenone is a naturally occurring pesticide neurotoxin, which also possesses mitochondrial complex I inhibitory activity (Greenamyre, et al. 1999). An AOP for this target generating Parkinson-like symptoms has recently been proposed and is now presented in AOPwiki (AOPwiki c). As low as micromolar concentrations of rotenone induced neuronal degeneration of primary neuronal and hippocampal slice culture (Sherer, et al. 2003). However, curcumin has shown protective features of hippocampal rotenone-induced cell death (Darbinyan, et al. 2017).

Key target cell types for acute neurotoxicity All receptors, enzymes and molecules in the nervous system are poten-tial targets for any compound, which have the chemical properties to enter the brain. Due to the delicacy of the intracellular ion homeostasis, small alterations of the concentrations can have devastating and even

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lethal effects. Thus, any acute adverse effects on receptors, ion channels or changes of the protection shield of the brain, i.e. the BBB, may cause death.

Blood-brain barrier The knowledge of the existing barrier between the brain and the circu-latory system, i.e. the BBB, is just 110 years. The passage over the BBB membrane is strictly regulated in order to maintain a functional neu-ronal activity as well as to protect the CNS from intrinsic or extrinsic molecules, pathogens and toxins (Daneman and Prat 2015). The BBB is composed of three major cell types; endothelial cells, astrocytes and pericytes (Figure 3). The endothelial cells in the CNS are tightly at-tached to each other by tight junctions (Westergaard and Brightman 1973). Due to the composition of the BBB, transport proteins must be present to provide the CNS with nutrients. Small lipophilic substances can pass the BBB, however most transportation occurs via carrier-me-diated transport, receptor- mediated transport or active efflux transport. Examples of transport proteins are Na+-independent or Na+-dependent transporters and ATP-binding cassette (ABC) class transporters (Cor-reale and Villa 2009). The ABC is an active transporter (transport against the concentration gradient). Moving proteins and ions, e.g. in-sulin and Fe3+, across the BBB demands receptor-mediated transcyto-sis, e.g. transferrin receptor transports transferrin-bound Fe3+ into the parenchyma (Moos and Morgan 2002). The tightly regulated passage over the BBB is also an obstacle when it comes to the delivery of drugs to the CNS. In some neurodegenerative diseases the permeability of the BBB is altered (Zlokovic 2008). For example in PD (Westerlund, et al. 2009), where an altered BBB could indicate an early event in the progression of PD (Rite, et al. 2007). Al-teration of the BBB structure can also be induced by stress and hyper-thermia (Dvorska, et al. 1992; Sharma, et al. 1998).

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Figure 3. A schematic illustration of the blood-brain barrier showing endothelial cells, pericytes and astrocytes, which connect to the neurons

Astrocytes The astroglia, more commonly known as astrocytes, was first named “nervenkitt”, translated to nerve glue (Somjen 1988). This is to our knowledge not the complete truth nowadays. The astrocytes are divided into proplasmic and fibrous subtypes, which are found in the grey and white matter, respectively. The astrocytes’ main function is to maintain the extracellular environment of the neurons e.g., exchange ions and other molecules with the extracellular fluid, regulate osmotic pressure and inactivate neurotransmitters. With their processes, they also con-nect the capillaries of the blood circuit to the nervous system, where they create a thin protective membrane between the nervous tissue and the capillaries to form the BBB (Sofroniew and Vinters 2010).

Astrocytes are connected to each other via gap junctions, where small molecule can pass. Astrocytes express glial fibrillary acidic protein

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(GFAP), which often is used as an astrocytic biomarker. Two main glu-tamate transporter proteins are expressed in astrocytes, namely excita-tory amino acid transporter 1 and 2. These two transporters are ex-tremely important to maintain a healthy brain and loss of those make the brain more susceptible to seizures of epileptic kind (Coulter and Steinhauser 2015). The enzyme glutamine synthetase (GS) is present in the astrocytes and is responsible for the neurotransmitter glutamine syn-thesis from glutamate. GABAergic neurons are more dependent on this cycle to be functional (Liang, et al. 2006) compared to excitatory, glu-tamatergic neurons.

Neurons There are about 100 billion neurons and 1014 connections between them, i.e. synapses (Herculano‐Houzel 2014). The neurons can be sub-divided into subclasses based on location (i.e. sensory-, motor-, inter-, projection-, neuro-endocrine and neuro-vascular neurons), function (i.e. local inhibitory or excitatory neurons, distant inhibitory or excitatory neurons or neuromodulatory neurons) or chemistry (i.e. neurotransmit-ters).

Key molecular targets in the nervous system Neurons express a wide array of molecular components that may result in lethality if they, or their function, are adversely affected. The neuro-chemical features that are most prominent for this thesis are described below.

Neurotransmitter homeostasis In order to survive, a functional nervous system is crucial. Therefore, neurons, connection areas (synapses), signal molecules and a conductor (brain) are needed. The endogenous signal molecules in the nervous system are called neurotransmitters (NT) and their functions are (under controlled manner) to chemically induce or attenuate the activity of other neurons or other organs in the body (Patestas and Gartner 2016). Depending on which neurotransmitter, the synthesis occurs via precur-sors in the cytosol before transported into vesicles, or the precursor is transported to the vesicles where the synthesis occurs (Ognen 2002). The storage of NT in the vesicles has two main functions; to protect the NT from degradation and the fast release of the NT. The release (exo-cytosis) of NTs is dependent on two factors; action potential generating depolarisation of the cell membrane and intracellular calcium ions (Ca2+) (Williams and Smith 2018). The action potential triggers voltage operated Ca2+ channels (VOCC) to open and an influx of Ca2+ occurs.

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After release of the neurotransmitter, the vesicle must be recycled (en-docytosis) and filled with new transmitters in order to keep the terminal full of vesicles ready to be released. This is referred to as the exo-endo-cytic pathway (Xie, et al. 2017).

Acetylcholine Neuro-muscular transmission, parasympathetic signalling and choliner-gic signalling in the CNS are dependent on acetylcholine (ACh). Alter-ation of ACh signalling is lethal, as exemplified above by atropine, nic-otine and OPs. When an action potential is conducted along the axon and reaches the synapse, ACh is released into the synaptic cleft and binds to its receptors. The nicotinic actylcholine receptor (nAChR) is an ion channel, which is permeable to Na+, K+ and Ca2+ when activated (Hogg, et al. 2003). The muscarinic AChR (mAChR) is a G-protein coupled receptor (Haga 2013). The nAChR and mAChR will be dis-cussed in more detail later.

The synthesis of ACh occurs in the cytosol of the presynaptic neuron by the enzyme choline acetyltransferase (ChAT). ChAT catalyses the reaction between acetyl-CoA from the mitochondria and choline (recy-cled and translocated from the synaptic cleft via the high-affinity cho-line transporter) (Szutowicz, et al. 1999), yielding ACh. The newly syn-thesised ACh is translocated into vesicles by vesicular acetylcholine transporter (de Castro, et al. 2009). ACh cleared from the synaptic cleft by being enzymatically hydrolysed by AChE into acetic acid and cho-line (Colovic, et al. 2013a; Massoulie, et al. 1993). AChE is the most important enzyme in the body due to its function of terminating cholin-ergic signal transduction (Colovic, et al. 2013a).

Myasthenia gravis is an autoimmune disease connected to disruption of ACh induced signalling. Antibodies are produced against the nAChR located in the neuromuscular junctions (Makino, et al. 2017). Due to the inhibition of the receptor, symptoms like muscle weakness or re-peated contractions are seen in myasthenia gravis patients.

Catecholamine neurotransmitter family The catecholamine family of neurotransmitters contains dopamine (DA), noradrenaline (NA) and adrenaline. DA is synthesised in the ven-tral tegmental area and in the substantia nigra. It is the main NT regu-lating the reward system, but DA also associated with PD by the spe-cific degeneration of dopaminergic neurons in the substantia nigra pars compacta (see MOA of MPTP-induced neurotoxicity described above). NA is synthesised in Locus Coeruleus of the brainstem (Atzori, et al. 2016). Like adrenalin, NA is also synthesised in the chromaffin cells in

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the adrenal medulla, which is the site of its release (Alejandre-García, et al. 2018).

The catecholamines contain a benzene group with two adjacent hy-droxyl groups along with ethylamine sidechain with a single amine group, which can be substituted (Brady, et al. 2011). The synthesis of the catecholamines (Figure 4) begins with the amino acid L-tyrosine, which main source is through diet. L-tyrosine is hydroxylated by the enzyme tyrosine hydroxylase (TH) into 3,4-dihydroxyphenylalanine (L-dopa). L-dopa is further decarboxylated by L-aromatic amino acid decarboxylase to DA. This is the final step in neurons using dopamine as a neurotransmitter. However, if the neuron is noradrenergic or syn-thesises adrenaline, additional enzymes are present in the cytosol, i.e. dopamine β-hydroxylase and phenylethanolamine-N-methyltransfer-ase, respectively. After the synthesis, the NTs must be pumped into the synaptic vesicles against a concentration gradient.

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Figure 4. Synthesis of neurotransmitter catecholamine family, dopamine, noradrena-line and adrenaline.

Glutamate Glutamate is the main excitatory NT in the brain (Meldrum 2000a; Zhou and Danbolt 2014). In fact, most neurons in the brain are glutama-tergic. Glutamate is a product of the metabolism of glucose and one of

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the amino acids leucine, isoleucine or valine (Cole 2015). The synthesis of glutamate occurs in the synapse (Kvamme 2018).

Glutamate is stored in synaptic vesicles and is localised into these through the action of specialised transporter proteins called vesicular glutamine transporters (vGluT), which have three members (1, 2 and 3). vGluT1 and vGluT2 are expressed in glutamatergic neurons (Fremeau, et al. 2004), whilst vGluT3 is expressed in GABAergic, ser-otonergic and cholinergic neurons (Gras, et al. 2002; Schafer, et al. 2002). Glutamate is also the precursor molecule for the synthesis of the major inhibitory neurotransmitter in the brain, i.e. γ-aminobutyric acid (GABA). Glutamate has been shown to be involved in many conditions and diseases, e.g. pain (Kristensen, et al. 1992; Blandini, et al. 1996) schizophrenia (Moghaddam and Adams 1998) and PD (Blandini, et al. 1996)

GABA The main inhibitory NT is GABA. The metabolism was described for the first time in 1950 by Roberts and Frankel (Roberts and Frankel 1950). The synthesis occurs in the GABAergic neurons via decarboxy-lation of glutamate by glutamic acid decarboxylase (GAD).

Neurotransmitter receptors

The metabotropic receptor family The majority of pharmaceutical drugs have been developed to target metabotropic receptors and many toxins possess their MOA targeting these receptors.

Metabotropic receptors are the most diversified class of receptors in the nervous system. Metabotropic receptors are not channels but upon receptor activation, they are passing the signal transduction to a hetero-trimeric guanine nucleotide-binding protein (G-protein). Therefore, they are referred to as GPCRs. In general, the GCPRs contain seven transmembrane domains (TM), which are connected with three extra- and intra-cellular loops (Hilger, et al. 2018). The ligand binding do-main, is made up by TM2, TM3 and TM7 and the G-protein is con-nected to the third intracellular loop (Kristiansen et al., 2004).

The G-protein family can be divided into four major subfamilies; Gsα, G�i/o; Gq� and G�12. Gq�, activates the effector enzyme phospho-lipase C (PLC). When activated, PLC hydrolyses the phosphatidylino-sitol-4, 5-bisphosphate located in the membrane of the cell. This hy-

19

drolysis generates diacylglycerol, which activates protein kinase C at-tached to the membrane, and inositol-1,4,5-trisphosphate (IP3). IP3 is translocated to the endoplasmatic reticulum (ER) membrane, in which the IP3 receptor (IP3R) is located (Falkenburger, et al. 2010). When ac-tivating the IP3R, Ca2+ is released from intracellular deposits in the ER into the cytoplasm. The released Ca2+ activates an array of intracellular processes (Bootman, et al. 2001), through e.g. calmodulin, which af-fects cell signalling and function (Swulius and Waxham 2008). Gi/o pro-teins, inhibits the effector enzyme adenylate cyclase and thus, activa-tion results in a decrease in the intracellular cyclic AMP (cAMP) levels (Krejci, et al. 2004). cAMP is an activator of protein kinases (primarily protein kinase A) and thus, regulates protein function, e.g. ion channel permeability.

Muscarinic acetylcholine receptors mAChR regulates peripheral organ function via the parasympathetic NS. Over-activation of the parasympathetic NS results in overproduc-tion of tear and saliva (lacrimation), blurred vision (ciliary muscle con-trolling the lens is affected), constriction of the iris and, slower heart-beat (bradycardia). These are typical symptoms of toxicity that are in-duced by mAChR agonists or AChE inhibition, as described above. There are five subtypes of the metabotropic receptor family; M1 to M5. Among the mammalian species, mAChRs are highly conserved due to absence of introns in the gene (Hall, et al. 1993). The five subtypes are divided into two classes due to their different signalling mechanisms; M1, M3 and M5 activate PLC-mediated increase of intracellular cal-cium whilst M2 and M4 regulate inhibition of adenylyl cycalase. Hence, the M1, M3 and M5 receptors are associated with Gq/11 while M2 and M4 receptors are associated with the Gi/o –type of G-proteins (Shoykhet and Clark 2011).

Dopamine receptors DA receptors are divided in two main classes, D1 and D2, however there are five members of this receptor family (D1, D2L/S, D3, D4, D5). D1 and D5 have the same properties, referred to as D1-like receptor and D2L/S,3 and 4-like have the same properties, referred to as D2-like receptor (Mis-sale, et al. 1998). The D1 receptors family activates AC while the D2-like receptor family does not activate AC. The N-terminal has the same amino acids regardless family. However, the C-terminal is seven times

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longer in the D1-like receptors family than the D2-like receptors (Mis-sale, et al. 1998). In transmembrane helix 6 (TM6), phenylalanine is responsible for the interaction with the catecholamine aromatic residue. Schizophrenia is believed to be associated to changes in the D3R sig-nalling (Joyce and Millan 2005).

Adrenergic receptors Adrenergic receptors have affinity for NA and adrenaline. There are two main subclasses, � and �� where the �-subclass is further divided into two groups, �1 and �2. The �1 receptor is coupled to Gq/G11

whereas �2 is coupled to Gi/o and �-subclass is coupled to Gi/o (Strosberg 1993). When the NT activates Gq/G11, this in turn activates PLC which leads to an increase of intracellular Ca2+ and an activation of protein kinase C concomitantly with phospholipase D and mitogen-activated protein kinase. When �2 receptors are activated, the Gi/o-receptor is ac-tivated and AC is inhibited, however, phospholipase A2 is activated. When the ��� subunit is released, K+ channels are activated and as a consequence of cell membrane hyperpolarisation, Ca2+ channels (N-, P/Q-type) are inactivated. The �-subclass has three family members (i.e.������and���). The �-subtype is expressed on glia and regulate the release of glucose and is associated with inflammatory responses to-gether with the uptake of glutamate in the astrocytes (Werry, et al. 2003).

Glutamate receptors The metabotropic glutamate receptor (mGluR) family is subdivided into three main groups based on their sequence homology; mGluRI, II and III. In group I, the members are mGluR1 and mGluR5 and they are of the Gq-type and induce activation of PLC. In group II, members are mGluR2 and mGluR3 and in group III mGluR4, mGluR6, mGluR7, mGluR8. All mGluRII and III receptors are coupled to the Gi/Go, which inhibits the action of AC. Group I is found on the post-synaptic neurons (Lum, et al. 2017) while group II and III are more abundant in pre-syn-aptic neurons (Niswender and Conn 2010). All members have their own function. For instance, mGluR5 is of great importance for the prolifera-tion and survival of neural progenitor cells (NPC) (Jansson and Åker-man 2014).

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Ionotropic receptors The ionotropic receptor family is activated by ligand-binding activation of ion channels. They can be excitatory or inhibitory (Dingledine, et al. 1999b).

Nicotinic acetylcholine receptors One critical target for acute toxicity is the nAChR. This receptor family is a member of the cys-loop family and are localised on the neuromus-cular endplate, in chromaffin cells in the adrenal medulla (Sala, et al. 2008), in sympathetic and parasympathetic ganglia of the autonomous NS (Skok 2002), and in the CNS (Dani and Bertrand 2007). The nAChR is a 290 kDa large glyco-protein complex composed of five subunits forming three large domains, i.e. the ligand binding domain, a mem-brane spanning pore domain, and an intracellular domain. The neuronal pentamer is composed of specific combinations of subunits ��� �and ��� (Millar and Gotti 2009a). The specific assembly of the five subu-nits decide what property the receptor will have, i.e. ion conductivity. The water-filled poor connection between the intracellular and extra-cellular space, which is closed when not activated. Activation of the receptor and opening of the pore occur when two molecules of ACh, or the agonist nicotine, bind to the binding sites, located on the extracellu-lar part of the receptor (Kalamida, et al. 2007). The channel, which is permeable for Na+ (influx), Ca2+ (influx) and K+ (efflux), is a fast-act-ing, excitatory channel due to the subunit composition. The nAChR is competitively inhibited by the alkaloid curare (Naess 1952). When ad-ministrated in a toxic dose, asphyxiation occurs due to diaphragm pa-ralysis, which results in death (West 1984).

GABAA receptors The most important inhibitory NT in the CNS is GABA. One of the GABAergic receptor is the ligand gated ion channel GABAA (Sigel and Steinmann 2012). When activated, an influx of Cl- occurs through the channel. This renders up in a hyperpolarisation of the cell membrane, which in turn leads to an inhibitory effect on neurotransmission. The receptor has two binding sites for GABA and there are also orthosteric binding sites where many pharmaceuticals bind e.g. benzodiazepines, barbiturates and ethanol (Amin and Weiss 1993; Davies 2003; Pritchett, et al. 1989). If the function of the GABAA receptor is impaired, this renders up in a depolarisation and hyper-excitation of the neuron, which is seen in several conditions e.g. Huntington´s disease, PD and alcohol-ism. If the system is in imbalance, i.e. the GABAA receptor is blocked, the clinical symptoms is seizure (Treiman 2001).

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Glycine receptors One other important ligand gated ion channel is the glycine receptor. This receptor is also a member of the cys-loop receptor family. The re-ceptor protein is a 250 kDa protein constituted of����and ��subunits (Absalom, et al. 2009; Grudzinska, et al. 2005). This receptor, as the name implicates, binds the NT glycine (Betz and Laube 2006) and is located in the basal ganglia of brain (Waldvogel, et al. 2007), brain stem (Wenthold, et al. 1987), spinal cord (Alvarez, et al. 1997) and retinal neurons (Shen, et al. 2008). The central pore is water-filled (Absalom, et al. 2009) and binding of glycine to the N-terminal of the receptor induces permeability for Cl- (Absalom, et al. 2003). Depending on the cell’s resting potential, the flux of Cl- can induce either depolarisation or hyperpolarisation of the membrane (Albuquerque, et al. 2009). Deg-radation of glycine occurs with the action of the glycine cleavage sys-tem in the astrocytes (Verleysdonk, et al. 1999). Glycine is also a co-activator of the NMDA receptor (NMDAR) in an excitatory manner (Johnson and Ascher 1987).

Glutamate receptors There are three types of glutamate receptors in the CNS of the iono-tropic type i.e., 2-amino-3-(5-methyl-3-oxo-1,2-oxazol-4-yl) propanoic acid receptors (AMPAR), N-methyl-D-aspartate receptors (NMDAR) and Kainate receptors (Krieger, et al. 2015; Meldrum 2000b; Zhu and Gouaux 2017). All receptors are tetramers, which are involved in learn-ing, memory and in the mature neuron. Most abundant of the three re-ceptors are the AMPARs (Meldrum 2000b).

AMPA receptors AMPAR are tetrameric ion channels of different compositions of GluA1-GluA4, permeable to Na+ and K+ and to some extent Ca2+, de-pending on subunit composition and editing i.e., changes of the codons glutamine (Q) to arginine (R) (Sommer, et al. 1991). The GluA2 is al-most always present in the R form, which makes the channel imperme-able to Ca2+. The function of the non-selectivity for Ca2+ is suggested to be a protection against excitotoxicity (Lai, et al. 2014). The AMPARs are responsible for the fast synaptic transmission, i.e. they open and close rapidly when activated. Hence, AMPARs induce the initial excit-atory post-synaptic potential of the membrane in a glutamate-activated action potential. The channel becomes active when two out of four binding sites (Mayer 2005) for glutamate are occupied. However, the

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current is increased if the other two binding sites become occupied with glutamate because the channel will then be open for longer time (Her-guedas, et al. 2016). One way to distinguish AMPAR from the NMDAR functionally is that AMPAR is not Mg2+-sensitive. If termination of glu-tamate transmission is not functional, seizures will be generated by the activity of AMPARs (Rogawski 2013).

NMDA receptors The NMDAR are tetramers of different combinations of GluN1, GluN2A-D GluN3A and GluN3B. The NMDAR are Ca2+-channels that can be blocked by Mg2+. In order for NMDAR to be activated, both glutamate and glycine has to bind to the receptor (Furukawa and Gou-aux 2003). The NMDAR is responsible for the slow glutamatergic in-duced excitatory postsynaptic current, which is of great importance for the action potential (Dingledine, et al. 1999a).

Voltage operated ion channels

Sodium channels Voltage-operated sodium channels (VOSC) and potassium channels are crucial for the action potential of neurons and depolarisation of skeletal and heart muscle cells. The VOSC are composed of one large �-subunit and one or several ��subunits (Catterall 2000). The �-subunit is a 2000 amino acids long peptide (Catterall 1988), which forms a secondary structure consisting of 24 �-helical TM segments. These segments are arranged in four domains, which all four have voltage-sensing segments (S4) with positively charged amino residues every third residue. The most abundant VOSCs in the CNS are, Nav1.1, Nav1.2, Nav1.3, Nav1.6 whilst Nav1.7, Nav1.8 and Nav1.9 are expressed in the PNS (Catterall, et al. 2005).

Calcium channels The voltage-operated calcium channels (VOCC or CaV) main function is to allow Ca2+ to enter the cell in response to depolarisation of the cell membrane. Upon VOCC activation, a wide array of responses are initi-ated; action potential, release of hormones (Yang and Berggren 2006) and NT (Tsien, et al. 1988), excitation-contraction (Tsien 1983), rapid muscle contraction (Tanabe, et al. 1993), gene transcription and enzyme activity (Flavell and Greenberg 2008). There are ten members of this ion channel family (Ertel, et al. 2000), which are divided into two major classes based on activated threshold potentials, i.e. high- or low-voltage activated channels (Armstrong and Matteson 1986) (See Table 2).

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These channels are also possible to discriminate by studying the re-sponses to different toxins from snails (Tranberg, et al. 2012) or spider (tarantula) (Salari, et al. 2016). The termination of the signal through the calcium channels, occurs in two different ways; voltage and/or cal-cium dependent (Dolphin 1998).

Table 2. Voltage-operated Ca2+-channels Activa-

tion Thresh-

old

Type of Ca Cur-

rent Location Blocker Refer-ence

HVA1

L Cav1

Cav1.1 Muscle

Cav1.2 Heart/Neuron

Cav1.3 Neuron

Cav1.4 Neuron

P/Q

Cav2

Cav2.1 Neuron

�-agatoxin IVA

(American funnel web

spider)

(Adams 2004)

N Cav2.2 Neuron Pain �-cono-

toxin GVIA

(Tran-berg, et

al. 2012)

R Cav2.3 Neuron SNX��� (Tarantula)

(Salari, et al. 2016)

LVA2

T

Cav3

Cav3.1

T Cav3.2

T Cav3.3 1HVA; High-voltage activated channels, 2LVA; Low-voltage activated channels Existing neurotoxicological models and models under develop-ment There are several ways to generate models for testing neurotoxicity, e.g. subcellular systems, cell lines, primary cultures and induced pluripotent stem cells (iPSC).

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Subcellular systems Subcellular systems, e.g. isolated mitochondria (Li, et al. 2012) or syn-aptosomes (Colovic, et al. 2015) from different regions of the neuron, can be used for neurotoxicological studies. Isolated mitochondria can be used for investigations on the specific impact of a toxicant on the organelle itself. The procedure to obtain different types of mitochondria (i.e. light, heavy and non-synaptic) is quite easy but require animal sac-rificing. Despite the simple protocol, the membrane of the mitochondria may be disrupted, followed by loss of mitochondrial molecules together with their function. This model has, for instance, been used to detect reactive oxygen species (Franco, et al. 2007).

Primary cells Primary cell cultures can be isolated from most tissues of an animal of interest or from humans. The main advantage of primary cultures is their normal geno- and phenotypes (Pan, et al. 2009). Some of the major limitations in using primary cell cultures are the difficult access of hu-man material and the necessity of sacrificing animals. Since primary cells have a finite lifespan and limited expansion capacity, new cultures need to be prepared continuously. Primary cells are also very sensitive and require additional nutrients in their culture media that are not in-cluded in classical media. However, there is still a need for using pri-mary cells in some studies since they often maintain many of the im-portant markers and functions seen in vivo. For example, there are few (if any) alternative cell models expressing functional NMDA or GABAA receptors. Hence, isolated neuronal cultures of cerebellar gran-ule cells and cortical neurons are needed for these types of studies (Sunol, et al. 2008). Furthermore, primary astrocytes from new born rats are often used for studies on neuroinflammation (Moore, et al. 2013).

Cell lines Cell lines are, in comparison to primary cells, easy to handle and to culture. There are many published studies using cell lines and cell lines do not require the same continuous sacrifice of animals. There are two types of cell lines, i.e. finite or continuous/immortalized cell lines. An immortalized cell line can proliferate indefinitely, either because of ge-netic mutations or through artificial modifications. A finite cell line will reach senescence after a certain number of divisions (usually between 20-80 passages). One should keep in mind that the genotypic and phe-notypic profiles of the cells might differ from the tissue of origin and

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that the characteristics of the cells might changes over time with in-creasing passage numbers (Hughes, et al. 2007). Some established cell lines have been used for decades; the PC12 and SH-SY5Y being two of them. Others are more recently established like the LUHMES cell line.

PC12 cells The clonal cell line, pheochromocytoma cells (PC12) was established by Greene and Tischler back in 1976 (Greene and Tischler 1976b) from a rat adreanal medulla and have been used in numerous studies over the years in the field of neurotoxicity (Wang, et al. 2016). The PC12 cell line differentiates into a more neuronal-like phenotype upon treatment with nerve growth factor (NGF) (Das, et al. 2004). The differentiated PC12 cells express preferably, DA and NA but not adrenaline (Greene and Tischler 1976a). There are human derived pheochromocytoma cell lines, e.g. KNA cells, that in 1998 was the first continuous human phe-ochromocytoma cell line established (Pfragner, et al. 1998).

LUHMES The cells from the Lund University Human Mesencephalon (LUHMES) cell line was originally isolated from the ventral mesen-cephalon area from an 8-week female foetus. The original cells were used to generate the MESC2.10 cell line by using the LINX v-myc ret-roviral vector (Lotharius, et al. 2002). Upon differentiation, the cells differentiated into dopamine-like neurons, expressing TH and β-III tu-bulin (a marker for early and more mature neurons). At the same time, the differentiated cultures showed a down regulation of GFAP. The MESC2.10 cell line was further developed to the LUHMES subclone, which could be induced to differentiate into morphologically and bio-chemically mature dopamine-like neurons upon addition of tetracy-cline, glial cell line-derived neurotrophic factor and dibutyryl cAMP (Lotharius, et al. 2005). LUHMES cells have been used in several tox-icity studies. Tong et al., compared the sensitivity of three different cell models i.e. SH-SY5Y, LUHMES and isolated neural stem cells to 32 substances and found that LUHMES cells exhibited greater cytotoxic sensitivity to most of 32 substances (Tong, et al. 2017). The LUHMES cell can also be cultured in a 3-dimentional setting which is better mim-icking the natural niche and structural circumstances compared to 2-dimentional monolayer cultures (Harris, et al. 2017). The results from toxicological testing might better reflect the in vivo results by cultivat-ing the cells in a more natural setting. The LUHMES cell line has also

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been used to look at the differences in sensitivity to neurotoxic sub-stances between mature and immature cells (Delp, et al. 2017).

SH-SY5Y The SH-SY5Y cell line is a thrice clone from the neuroblastoma cell line SK-N-SH (Biedler, et al. 1973; Biedler, et al. 1978). The cells orig-inally derive from a bone marrow biopsy of a 4-year-old female neuro-blastoma patient. The neuroblastoma cancer form is one of the most common cancers amongst young children and is presumed to derive from the neural crest cells (Cohen-Kupiec, et al. 2011).

During several decades, the SH-SY5Y cell line has been used as an in vitro model system, detecting the impact of toxicants on mature and developing neurons (Attoff, et al. 2016a; Kölsch, et al. 1999). Also the SH-SY5Y has been used for detection of marine neurotoxins (Coccini, et al. 2017) and AChE inhibitors using a method called Amplex Red (Li, et al. 2017). The SH-SY5Y cell line is also one of the most com-monly used cell lines in the research of PD (Xicoy, et al. 2017).

The SH-SY5Y cells can be successfully differentiated to post-mitotic and more mature neuronal phenotypes, if such endpoints are needed for the experimental model. Differentiation can be induced by using all-trans retinoic acid (ATRA) (Pahlman, et al. 1984), the phorbol ester 12-O-tetradecanoylphorbol-13-acetate (TPA) (Åkerman, et al. 1984), a combination of these (Presgraves, et al. 2004) or by different neu-rotrophic factors (e.g. NGF, brain-derived neurotrophic factor (BDNF) and neurogulins) in combinations with ATRA and TPA (Agholme, et al. 2010). Depending on culture medium conditions and differentiation procedure, SH-SY5Y cells can be differentiated toward different neu-ronal phenotypes. For example, ATRA in combination with TPA gen-erates a highly differentiated dopaminergic neuronal phenotype (Lopes, et al. 2010; Presgraves, et al. 2004) and increased resting cell membrane potential (Adem, et al. 1987; Toselli, et al. 1996; Tosetti, et al. 1998). Differentiation with TPA generates a more noradrenergic phenotype, than differentiation with ATRA alone (Murphy, et al. 1991), with ele-vated noradrenaline content (Pahlman, et al. 1984), induced expression of neuropeptide Y and growth-associated protein-43 (Jalava, et al. 1992). Interestingly, staurosporine also induced the SH-SY5Y cells to differentiate into a noradrenergic phenotype with increased expression of TH and 30-fold increase in NA (Jalava, et al. 1993).

Native/undifferentiated SH-SY5Y cells express the P2X7 receptors, which upon activation open L-channel VOCC (Larsson, et al. 2002,; Sousa, et al. 2013). SH-SY5Y cells also express Nav1.2, Nav1.3 and

28

Nav1.7 (Vetter, et al. 2012; Zimmermann, et al. 2013), AChE and mRNA of M1 and M3 mAChR (Hicks, et al. 2013). Native SH-SY5Y cells also express opioid receptors, however, the mu (μ) subtype to a larger extent then the delta (δ) subtype (Kazmi and Mishra 1987; Yu and Sadee 1988). Upon differentiation, the expression levels are up-regulated (Yu and Sadee 1988) and SH-SY5Y cells have been used to study opioid receptor activity and desensitisation (Elliott, et al. 1994; Nowoczyn, et al. 2013). One should be aware that native and differen-tiated SH-SY5Y cells may respond differently to toxicants and should be regarded as different neuronal models (Cheung, et al. 2009).

Stem cells Pluripotent stem cells can differentiate and give rise to any type of cell within the body whereas nerve stem cells (NSCs) are multipotent cells. NSCs are different from more mature cells in three ways; have the abil-ity to self-renew, they can differentiate into all three neural lineages (neurons, oligodendrocytes and astrocytes) (Merkle and Alvarez-Buylla 2006; Temple 1989) and they can regenerate neural tissue (Ratajczak, et al. 2011). NSCs can be generated from pluripotent em-bryonic stem cells (ESCs), isolated from the blood of the umbilical cord (Divya, et al. 2012) or from the bone marrow (Sanchez-Ramos, et al. 2000). Hippocampus and some ventricular zones harbour multipotent neural progenitor cells (NPCs), which are precursors of neurons and astrocytes (Guo, et al. 2012). Both NSCs and NPCs can be used as mod-els for DNT, when exposed during differentiation or for neurotoxicity studies of the mature brain when exposed after differentiation.

Embryonic stem cells The origin of the pluripotent ESCs is the inner cell mass of the blasto-cysts. These cells are diploid and have the ability to differentiate into any of the three different germ layers i.e., endoderm, ectoderm and mes-oderm and to germ cells and gamets. There are several pluripotency markers including nanog, Oct-4, Gdf3 and DNMT3b (Sundberg, et al. 2011). ESCs have been used in the toxicology field for a quarter of a century, and one of the first in vitro models for identification of terato-genic compounds was the mouse embryonic stem cell test, so called EST. The test was developed by Spielmann and co-workers (Heuer, et al. 1993; Spielmann, et al. 1997), using the pluripotent embryonic stem cell line D3. The first documented isolation of human derived embry-onic stem cells (hESC) was described in 1994 (Bongso, et al. 1994). Since then, culturing of hESC have been refined and hESC lines have

29

been generated (Reubinoff, et al. 2000). However, isolation of hESC requires human embryos, which is highly controversial and ethical per-mits are needed for new isolation. Today there are 726 hESC clones registered on the Human Pluripotent Stem Cell Registry homepage (HPSC).

Induced pluripotent stem cells Due to the ethical issues when working with human embryonic cells, an alternative to the hESC is the induced pluripotent stem cells (iPSC). The origin of these cells are somatic cells which have been repro-grammed into pluripotent stem cells by overexpressing four pluripo-tency factors that have now been named “the Yamanaka factors”, i.e. Oct3/4, Sox2, Klf4, c-Myc (Takahashi and Yamanaka 2006). Yama-naka and colleagues were the first to transform fibroblasts from a fe-male face, back in development so they resemble the cells from the in-ner cell mass 30 days after retroviral transduction (Takahashi, et al. 2007). However, it has been shown that iPSCs are not identical to ESCs, as illustrated in a validation study of 80 different chemicals on neurite outgrowth in a high throughput screening assay for estimation of DNT (Ryan, et al. 2016). Nevertheless, today there are 1185 iPSC cell lines registered on the Human Pluripotent Stem Cell Registry homepage (HPSC).

The P19 cell line The P19 cell line is a pluripotent murine cell line derived from an em-bryo-derived teratocarcinoma in a C3H/He mouse that can be differen-tiated with ATRA into neurons, astrocytes and fibroblast-like cells (McBurney and Rogers 1982). The P19 cells develop functionally ac-tive synapses after differentiation with ATRA (Magnuson, et al. 1995; Morassutti, et al. 1994). The cells can also be differentiated and cultured in aggregates, which better resembles the normal embryonic develop-ment, compared to cells cultured in a 2-dimentional way (Popova, et al. 2016). The P19 cell line has been used to study the neurotoxicity of several different substances including MDMA (ecstasy), MeHg, oka-daic acid and acrylamide (Popova, et al. 2016; Popova, et al. 2017). The differentiated P19 cells were shown to be more sensitive to detecting cytotoxicity of MeHg, okadaic acid and acrylamide when compared to SH-SY5Y cells differentiated with ATRA and PC12 cells differentiated with NGF (Popova, et al. 2017).

30

C17.2 cell line The multipotent neural progenitor cell line, C17.2, was originally iso-lated from the cerebellum from a 4 days male old mouse of the K-strain. The cells were immortalised using avian v-myc transfection (Ryder, et al. 1990). The original intention of this cell line was to use it as engraft in degenerating brains (Snyder, et al. 1992). Since then, several trans-plantation studies have been performed in animal models, with the hope to find a treatment for PD (Wang, et al. 2007).

The C17.2 progenitor cells can be induced to differentiate by the nat-ural flaveniod, baicalin (Li, et al. 2011). Furthermore, since the melato-nin MT1 receptor was found to be expressed in the cell line, melatonin was used as an initiator of neuronal differentiation. However, no ex-pression of GFAP was detected indicating the lack of astrocytes in the cultures (Sharma, et al. 2008). Previous studies have shown that ATRA promotes astrocyte differentiation rather than neuronal development in C17.2 cells (Asano, et al. 2009; Bajinskis, et al. 2011a). It has also been shown that the C17.2 cells secrete neurotrophic factors such as NGF, BDNF and glia cell line-derived neurotrophic factor that promote an autocrine induction of differentiation (Lu, et al. 2003). In this thesis, an optimisation was generated in order to obtain mixed cultures with more equal distribution of neurons and astrocytes (Paper II).

The C17.2 cell line has been used in many different applications e.g., grafting (Liu, et al. 2007), toxicity ( Attoff, et al. 2016b; Dong, et al. 2016), radiation (Bajinskis, et al. 2011b), radiation (Luan, et al. 2012), virulence of parasite (Zhang, et al. 2017). The cell line has also been shown to be able to function as a delivery system of genes (Lynch, et al. 1999).

31

Hypotheses and Aims of the present studies

Due to the many difficulties in predicting neurotoxicity by using cell systems, my aims were to shed light on some important questions re-garding cell model systems and neurotoxicity testing:

• Is it possible to predict human acute toxicity in cell models without scarifying any animals?

• Is it possible to control differentiation of cloned, immortalised cells in order to receive organ-typical cultures containing more than one cell type?

• Could a murine neural progenitor cell line be as good as primary embryonic rat brain cell cultures or even better for prediction of acute systemic toxicity?

• What happens in a culture during differentiation in terms of gene ex-pression? • Can mRNA levels be used as biomarkers for acute neurotoxicity?

• Can mRNA levels be used as biomarkers for developmental neuro-toxicity? • Are there correlations between gene expression and functional end-points?

32

Methodological considerations

Chemicals Chemical used in this thesis are of three different categories of chemi-cals; industrial, pesticides, pharmaceuticals. These chemicals have dif-ferent modes of action and target organs e.g., liver, kidney and the nerv-ous system (Table 3). The chemicals used in paper I and IV were mainly chosen from the MEIC project which were industrial chemicals, bio-cides, pharmaceuticals, with different modes of action and target organs (Ekwall, et al. 1998a; Ekwall, et al. 1998b).

33

Ta

ble

3. C

ompo

unds

stud

ied

in th

is th

esis

and

thei

r mod

es o

f act

ion

Com

poun

ds p

aper

I U

sage

T

arge

t org

an1

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e of

act

ion

Ref

eren

ces

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hlor

vos

Bio

cide

C

NS

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bitio

n of

AC

hE

(Vas

conc

ello

s, et

al.

2002

)

Lith

ium

sulp

hate

In

dust

rial

CN

S H

eart

Kid

ney

Alte

rs p

hosp

holy

latio

n st

ate

of c

olla

psin

e re

-sp

onse

med

iato

r pro

tein

-2 (p

harm

acol

ogic

al)

(Tob

e, e

t al.

2017

)

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athi

on

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cide

C

NS

Mus

cle

Hea

rt In

hibi

tion

of A

ChE

(met

abol

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alao

xon)

(K

rstic

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l. 20

08)

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thio

n B

ioci

de

CN

S PN

S In

hibi

tion

of A

ChE

(met

abol

ite p

arao

xon)

(V

eron

esi a

nd P

ope

1990

)

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ostig

min

e D

rug

CN

S PN

S In

hibi

tion

of A

ChE

(E

yer 2

002)

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pine

sulp

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mon

ohy-

drat

e D

rug

CN

S H

eart

PNS

mA

ChR

ant

agon

ist

(Bha

ttach

arje

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t al.

2013

)

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fein

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rt C

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ne 2

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rone

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rug

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Han

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acca

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g C

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ishi

mur

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2017

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g C

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rt Li

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34

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poun

d U

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T

arge

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eren

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achl

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osph

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latio

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ach

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ni-B

uoni

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2017

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oxin

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ase

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atz,

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u, e

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2014

)

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um se

lena

te

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stria

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ung

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ney

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ds to

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-gro

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ano

1998

)

35

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poun

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T

arge

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e of

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ulke

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oura

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2010

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acet

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bind

s to

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luta

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gman

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201

2)

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toni

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dust

rial

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e m

etab

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nide

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bits

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ome

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plex

IV) i

n m

itoch

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ia

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vesl

ey, e

t al.

2007

; Mue

ller a

nd

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land

199

7)

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ylic

aci

d2 D

rug

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ney

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IT

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tor.

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oupl

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f oxi

dativ

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osph

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n (V

ane

and

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ting

2003

)

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enic

trio

xide

D

rug

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ney

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rt Li

ver

CN

S G

IT

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ds S

H-g

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s in

prot

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ause

s oxi

dativ

e st

ress

(E

rcal

, et a

l. 20

01; R

atna

ike

2003

)

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miu

m (I

I) ch

lorid

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dust

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s Kid

ney

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r B

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n pr

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omov

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elid

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2018

)

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2010

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2013

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36

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poun

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thyl

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datio

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met

abol

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ep, e

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2016

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84)

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olds

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l alc

ohol

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dust

rial

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IE u

nkno

wn

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NS

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essi

on

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outu

re, e

t al.

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)

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ne

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ons

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ae, e

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2013

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ner 2

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arek

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iech

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z, e

t al.

2017

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38

Model systems Throughout this thesis, two cell lines, the human neuroblastoma cell line SH-SY5Y (paper I) and the murine neural progenitor cell line C17.2 (paper II-IV) were used as a neural and neuronal model, respec-tively. Guidelines to test acute toxicity are based on data from human intoxication cases, animal studies and epidemiological studies. How-ever, new demands for determining toxicity data have been raised from both the EU and USA hence it is urgent to find models which fulfil these demands. Therefore, we wanted to explore if these two cell lines could be models of choice. There are several considerations when choosing in vitro model systems, both advantages and limitations and awareness of them both are of crucial knowledge.

SH-SY5Y (Paper I) In our study, we used both undifferentiated and differentiated cells. As routine medium for SH-SY5Y cell line, Earle´s minimum essential me-dium with Earle´s salts were used supplemented with 10% foetal bovine serum (FBS), L-glutamine [2 mM], 1% non-essential amino acids and the antibiotics, 100 U penicillin/ mL and 100 μg streptomycin/mL. The FBS contains factors, (i.e. growth factors, hormones, amino acids, vit-amins and trace elements), essential for the mitogenic effect, i.e. prolif-eration and cell growth. When testing a new batch of FBS, the new batch should be as close to the previous one in question of endotoxins, haemoglobin and other adverse factors.

C17.2 (Paper II, III and IV) The C17.2 neural progenitor cell line was used to mimic a more physi-ological neural cell model composed of a mixture of cells in the brain and not just a monoculture of neurons, since glia cells may modulate toxic responses of chemicals. The cells we routinely cultured in Dul-becco’s Minimal Essential Medium with the additions of 10% FBS, 5% horse serum, L-glutamine [2 mM], 100 U penicillin/mL and 100 μg streptomycin/mL.

39

Differentiation Both cell lines were differentiated in serum-free DMEM:F12 medium with N2 supplements (Apo-transferrin, progesterone, putrescine, so-dium selenite, insulin (Bottenstein and Sato 1979) and differentiation inducers; ATRA for the SH-SY5Y cells and NGF and BDNF for the C17.2 cells. A summary of differentiation and exposures for the end-points studied is presented in Table 4 for SH-SY5Y cells and Table 5 for C17.2 cells.

Table 4. Differentiation level, exposures and endpoints studied in SH-SY5Y cell mod-els (paper I)

Differentiation level

Exposure with chemicals

Endpoints

Native cells (3-4 days in culture)

� 15 +15 minutes

� 60 minutes � 30 minutes

� NA uptake

� AChE inhibition � LDH leakage

3 days in N2-medium with 1 μM ATRA

� During regis-tration (seconds)

� 15 minutes � 15 minutes � 30 minutes

� CMP

� VOCC function � AChR signalling � LDH leakage

40

Table 5. Differentiation level, exposures and endpoints studied in C17.2 cell models (paper II-IV)

Differentiation level

Exposure with chemicals

Endpoints

7 days in N2-medium with NGF and BDNF (10 ng/ml of each).

None � mRNA and protein expression of dif-ferentiation mark-ers nestin, �III-tu-bulin, GFAP

5 days in N2-medium with NGF and BDNF (10 ng/ml of each)

� During registration (seconds)

� 48 hrs

� During full

time of dif-ferentiation (5 days)

� CMP

� mRNA bio-mark-

ers (�III-tubulin, GFAP and HSP32)

� mRNA expression of 30 selected bi-omarkers for neu-ronal differentia-tion

10 days in N2-medium with NGF and BDNF (10 ng/ml of each)

� During full time of dif-ferentiation (5 or 10 days)

� mRNA expression of 30 selected bi-omarkers for neu-ronal differentia-tion

Analyses of mRNA expression

Reverse Transcriptase Real-Time polymerase chain reaction (paper II) In paper II, we used one of the most used techniques in modern molec-ular biology today, reverse transcriptase polymerase chain reaction

41

(RT-PCR). This method is a further development of the original poly-merase chain reaction (PCR) which use deoxyribonucleic acid (DNA) as template. However, RT-PCR uses ribonucleic acid (RNA) as a tem-plate, which in turn is made to first strand complementary DNA (cDNA). The RNA was extracted using RNeasy from Qiagen (Fer-menta). In each sample, the same amount of cDNA was added together with the specific primers of selected biomarkers of interest (nestin- pro-genitor cells; βIII-tubulin- neurons; GFAP-astrocytes and glyceralde-hyde 3-phosphate dehydrogenase (GAPDH) as a reference gene). For the actual PCR reaction, three different temperatures were used, due to the different optimal temperatures for different actions of the reaction. Denaturation of the cDNA template (94-98°C), annealing of the pri-mers, which is the most critical temperature step due to the specificity of the primers (50-65°C) and elongation (72°C) of the deoxynucleoside triphosphates (dNTPs) using the cDNA as a template. In our case, the cycle was repeated 22-26 times. The PCR product was separated on an agarose gel together with a ladder (showing the size of the PCR prod-ucts) and visualised with ethidium bromide and ultra violet light (UV-light). The intensity of the separated band corresponds to the amount of RNA expressed in the cell lysate from the beginning after differentia-tion. The intensity of the bands was quantified and analysed with an image program and normalised against a reference PCR product (GAPDH).

Reverse Transcriptase quantitative-PCR (paper III and IV) In paper III, we used the Reverse Transcriptase quantitative-PCR (RT-qPCR) in a small-scale setup, a method that is a further development of the RT-PCR technique. The template for this was also RNA from the harvested C17.2 cells. mRNA was converted to first strand cDNA, which functioned as a template for the RT-qPCR reaction. Before the RT-qPCR run, Maxima® SYBR® Green/fluorescein was added to-gether with the specific primers and the cDNA. Fluorescein served as an internal standard for the reaction, which incorporates into the cDNA during the thermal cycles, together with an intercalating dye in the mas-ter mix. The fluorescence will increase proportionally when the cDNA is amplified exponentially. There are several things to consider when preparing the RT-qPCR, just to mention a few; design of the primers (i.e. 30-60% GC content and no longer than 18-30 nucleotides) and lo-calisation of the primers (i.e. the amplicon should not be longer than 150 bp) (Bustin, et al. 2009).

42

Genome microarray (paper IV) In paper IV, we used an omic-method, i.e. transcriptomic analysis of altered gene expression. This has been shown to be an improved method to screen the whole genome in order to elucidate which of the genes in the C17.2 cell line were downregulated and which were upregulated during differentiation. Affymetrix is a “genome on a chip assay” where the whole transcribed genome is represented. The total RNA was ex-tracted using extraction kit from the undifferentiated and differentiated cells. The total RNA was used as a template for the synthesis of com-plementary DNA (cDNA) in the amplification and biotinylation reac-tion. The cDNA was then hybridised for 16 hours in 45°C washed stained, scanned and analysed.

Protein expression using western blot (paper II) The western blot method is a standard method to analyse protein ex-pression levels in modern research. It is a method based on proteins’ ability to separate according to their molecular size on a sodium do-decylsulphate polyacrylamide gel electrophoresis (SDS-PAGE) under the influence of an electric field. Prior to the separation, the protein mix was boiled in sodium dodecyl sulphate (SDS) to denature the proteins and give them a negative charge according to their size. Large proteins will be trapped in the upper part of the polyacrylamide mesh, while smaller proteins will run further down. The separated proteins were transferred from the polyacrylamide gel to a polyvinylidene fluoride (PVDF) or nitrocellulose membrane in an electric field. After transfer, the unwanted unspecific binding of the antibody was prevented by blocking the membrane with bovine serum albumin or milk powder. First, the primary antibody (directed to the protein of interest i.e. βIII -tubulin, GFAP and nestin) was applied to the membrane and after, the secondary antibody, was applied to the same membrane. The secondary antibody was conjugated with horseradish peroxidase to visualise band of interest by chemiluminescence.

Neurofunctional assays

Cell membrane potential (paper I, III) Patch-clamp recording using electrodes has been the principal method to study ion channel activity in the past. However, fluorescence probes such as bis-(1,3-dibarbituric acid)- trimethine oxanol (DiBAC4(3)) can also be used to study ion fluxes over the cell membrane (Yamada, et al.

43

2001). This method is a functional assay based on the feature that all cells possess a CMP. The fluorescence intensity increases upon depo-larisation of the cell membrane and decreases upon hyperpolarisation. Neurons and myocytes are two cell types in the body, which are de-pendent on the CMP in order to maintain their tissue specific function. Alterations in CMP are due to the change in ion homeostasis, which in turn is due the physical or chemical impact on ion channel and receptor function on the cell. However, in paper I and III we used the FLIPR membrane potential (FMP) probe (Baxter, et al. 2002) on differentiated SH-SY5Y and C17.2 cells. The sensitivity of the FMP probe makes it a nice tool to use, when studying ion flow over membranes. This probe translocates over the plasma membrane in a voltage-dependent manner. Upon depolarisation, the FMP probe is transferred over the membrane and binds to hydrophobic sites in the membrane and the fluorescence increases. Upon hyperpolarisation, the FMP probe is forced out from the cell and the fluorescence signal decreases (Molecular Devices). The plate can then be read in a Semi- HTS-fluorescence plate reader, e.g. Flexstation II. CMP is a global endpoint where effects of chemicals on neuronal MIEs are determined. However, some limitations with the as-say and the FMP probe are that the full structure and function of FMP is not available for the customers, detection of hyperpolarisation of the membrane is not optimised and some of the chemicals may interact with the FMP probe and thereby affect the fluorescence readout.

Noradrenaline uptake (paper I) Termination of NA-signalling occurs via receptors transporting NA back into the neuron. In the NA uptake assay, a pilot experiment showed that native cells were more susceptible than the ATRA-differ-entiated SH-SY5Y cells, hence the former was chosen for the experi-ments. The native cells were incubated with the reference chemical for 15 min, followed by addition of [3H]-NA with an incubation of 15 min. The protein content was determined in each sample, according to a modified Lowry protocol (Lowry, et al. 1951) developed by Forsby et al (Forsby, et al. 1995). The radioactivity was measured in each sample in a liquid scintillation counter and the [3H]-NA uptake (CPM/mg pro-tein) was normalised to untreated controls. As acceptance criteria for the tests, 50% of the reuptake of NA, induced by imipramine (a well-known noradrenaline reuptake inhibitor) was applied.

44

Acetylcholine receptor activity and voltage operated Ca2+ channels (paper I) In order to perform the ACh receptor signalling and VOCC, we used Fura 2 acetoxymethyl ester (Fura 2-AM), which is a fluorescent probe, which upon binding of Ca2+ changes it excitation peak to 340 nm from unbound 380 nm (Sato, et al. 1988). Translocation of Fura 2-AM over the plasma membrane occurs easily and inside the cell, esterase re-moves the acetoxylmethyl groups through hydrolysis. In this assay we used differentiated SH-SY5Y cells as model system due to more neu-ronal phenotype compared to undifferentiated cells. The cells were pre-incubated with Fura 2-AM for 30 min, followed by a quick wash and incubation in KRH-buffer in order to hydrolyse the Fura 2-AM. The chemicals were prepared in 5X concentration compared to the actual concentration on the cells, exposed and incubated with the test chemi-cal. After 15 min of incubation, baseline was recorded for 30 sec fol-lowed by carbachol-induced activation of the mAChR, or by KCl in-duced activation of the VOCCs in a semi-HTS fluorescence FlexStation II reader.

Acetylcholine esterase activity (paper I) The activity of AChE is crucial for nerve impulse termination in the neuromuscular junction. If impaired, cholinergic signalling will be overstimulated and death will occur due to respiratory failure. The pilot study for this assay, showed a higher readout in undifferentiated cells compared to differentiated cells so the undifferentiated cells were cho-sen. This method was developed by Ellman and co-workers in 1961 (Ellman, et al. 1961) where the substrate acetylthiocholine iodide (ASChI) is added to the cells, hydrolysed by the expressed AChE from the cells and the two products, thiocholine and acetate are formed. In turn, thiocholine reacts with the added substrate, 5,5´-dithio-bis-(2-ni-tro-benzoic acid) (DTNB) and the resulting yellow 5-thio-2-nitroben-zoate anion (TNB2-) is formed and thereafter the change was deter-mined spectrophotometrically at 420 nm. The cells were exposed to each of the reference chemicals in total of 60 min. Some of the reference chemicals needed bioactivation, e.g. oxidation, in order to block the AChE activity. A new fluorescence method, Amplex Red, has recently been developed to analyse AChE activity (Santillo and Liu 2015).

45

Cell viability tests (paper I and IV) Any effect of a compound on neuro-specific endpoints should be com-pared to general cytotoxicity. This can be done by using different as-says, e.g. trypan blue exclusion (Ryan, et al. 2016), MTT (Mosmann 1983) or resazurin reduction (O'Brien, et al. 2000), just to mention a few examples.

Trypan blue was one of the first methods that were used to detect cell viability; dead cells will take up the dye due to their disrupted cell mem-brane whilst alive cells will not. This can be useful when subcultivating cells to check for the presence of viable cells. MTT is another method used in the papers included in this thesis. MTT is a fast colorimetric assay, well suited for the 96-well format where the soluble yellow te-trazolium salt is converted by reduction by dehydrogenase to insoluble purple formazan crystals. One drawback of this assay is the dependence of NADH and NADPH for reductase activity. The levels of NADH and NADPH are dependent on glucose, thus lack of glucose lowers the read out of MTT. The confluence of the cells in culture is another issue, where over-confluent cells may lower their metabolic activity, which results in an underestimation of the number of cells due to less meta-bolic activity. Cell viability depends on an intact cell membrane. Any disturbance in the membrane may lead to leakage of intracellular fluid out in the extracellular space. Lactate dehydrogenase (LDH) leakage to the medium in relation to the total LDH activity in the cells can be mon-itored as an indication of acute membrane disruption and unspecific cy-totoxicity (Altman 1976). This assay was used for assessment of acute cytotoxicity in paper I.

Transcriptomics Transcriptomics, i.e. analyses of mRNA levels of specific genes, is a useful tool (Chin, et al. 2010) for examining the effect of a toxicant on the gene expression. This method can be used for characterisation of a cell model or toxicity studies due to the dynamic of the transcriptome (Joseph 2017). Microarrays are a type of transcriptomics where short probes i.e., small nucleotides, are attached to a solid plate e.g., glass. Fluorescently labelled transcripts are hybridised to the probes. When preforming a transcriptomic analysis, a separate quantitative validation is good laboratory practice.

46

mRNA biomarkers mRNA biomarkers were used to detect which mRNA levels were af-fected after exposure of C17.2 cells to the chemicals. As phenotypic biomarkers, nestin and βIII-tubulin were used to identify neural progen-itor cells and neurons, respectively and GFAP was used for astrocytes (paper II and IV). Heat-shock protein-32 (HSP-32) was used as a cell stress biomarker in Paper III. The biomarkers selected for validation of the whole genome array were genes involved in neurogenesis, axonal guidance, oligodendrocyte differentiation, astrocyte differentiation; Bone Morphogenic Protein 4 (BMP4), chordin-like protein 1, S100 cal-cium binding protein B (S100B), to mention a few of the 30 biomarkers (paper IV).

47

Results and Discussion

Paper I The aim in paper I was to evaluate five different in vitro assays, which were assumed to identify chemicals with neural MOAs and thereby in-dicate acute neurotoxicity. The assays were carefully chosen based upon their vital function for survival of humans; the CMP, activity of AChE, NA-uptake, AChR signalling and functionality of VOCCs. Lac-tate dehydrogenase leakage was analysed as an indication of acute cy-totoxicity. We used native or differentiated cells, depending on the fea-tures of the neurofunctional endpoints in the SH-SY5Y cells.

In the first phase, the effects of 23 chemicals were studied on the six endpoints. To evaluate the possibility to identify chemicals with neu-ronal MOA for acute toxicity, the results from these assays were com-pared to the general cytotoxicity, previously determined in the 3T3-NRU assay (Clothier, et al. 2008).

Chemicals, which show good correlation between cytotoxicity and in vivo toxicity are of no worries, it is the outlier chemicals, which show poor correlation between the in vitro and in vivo experiments that are of concern (Ekwall, et al. 1998b). In order to identify these chemicals, the logarithmic in vitro IC50 values from the 3T3-NRU assay (3T3-NRU, IC50) were compared with the logarithmic lethal blood concen-tration (LC50) values, i.e. the estimated lethal blood concentration, which would induce 50% lethality in humans (Sjostrom, et al. 2008a). If the difference was ≥ 0.7 log unit, then the chemical was considered an outlier chemical (Table 6). Of the 23 chemicals tested, 10 chemicals showed changes in the CMP i.e., depolarisation or hyperpolarisation. For eight of the 10 chemicals, this endpoint showed to be more sensitive than the general cytotoxicity i.e., the effects on CMP were seen at sig-nificantly lower concentrations than the reduced number of viable cells (IC50) determined in the 3T3-NRU assay. Four of the eight chemicals where previously identified as outlier chemicals in the in vitro-in vivo correlation (Table 6).

48

Nine of the tested chemicals attenuated NA uptake in native SH-SY5Y cells after 30 minutes of exposure. Of these nine chemicals, five were alerted as neurotoxic chemicals (amphetamine, caffeine, diaze-pam, methadone and verapamil). Other outlier chemicals, which did not affect the NA uptake were acetaminophen, digoxin, lindane, malathion nicotine and phenobarbital (Table 6).

The AChE activity was measured in native SH-SH5Y after exposure with the 23 phase I chemicals and with dichlorvos, parathion, and phy-sostigmine (phase II chemicals, used as positive controls for the end-point). Of the 26 chemicals, a reduction of activity was seen for nine of them; dichlorvos and physostigmine decreased the activity of AChE tremendously at low concentrations, followed in rank of activity by the OPs malathion and parathion. Furthermore, nicotine showed improved correlation when using the AChE activity assay as compared to the cy-totoxicity, determined by the 3T3-NRU assay. Dichlorvos toxicity was overpredicted and methadone toxicity was underpredicted when com-pared to the human LC50. Outlier chemicals not detected in the AChE assay were acetaminophen, atropine, diazepam, digoxin, lindane, phe-nobarbital and verapamil (Table 6).

Differentiated SH-SY5Y cells were incubated with each chemical 15

minutes before measurement of AChR signalling and VOCC function. The AChR agonist carbachol was used to elucidate if the chemicals im-paired AChR signalling. Extracellular KCl was used to induce CMP depolarisation and thereby activate VOCCs. Four reference chemicals (atropine, pentachlorophenol, sodium lauryl sulphate and verapamil) changed the activity of the AChR signalling and three in the VOCC function assay (pentachlorophenol, sodium lauryl sulphate and vera-pamil).

As a check for substance-induced acute cytotoxicity, the integrity of the membrane (cytotoxicity) was determined after 30 min exposure with native or differentiated SH-SY5Y cells. None of the 23 reference chemicals induced LDH activity except for two chemicals; sodium lau-ryl sulphate and mercury chloride.

The first set of chemicals showed that we were able to identify most neurotoxic alerts by using the CMP assay. This makes sense, since the CMP can be regarded as a central KE in an AOP for acute systemic toxicity that is induced by a neuronal MOA. Hence, this assay was se-lected for further chemical testing in phase II.

49

In the second phase set of chemicals, 14 of 36, changed the CMP (Table 6), however just five were identified as neurotoxic alert chemi-cals (i.e. affecting the CMP at significantly lower concentrations than the 3T3-NRU IC50). Three of the five alerted compounds were outlier chemicals and two chemicals were corrected when correlated to human lethal blood concentration (LC50). The result from phase II chemicals, indicated that chemicals were either under- or over- predicted compared to 3T3-NRU assay; the underpredicted chemicals were cadmium chlo-ride, diquat dibromide, methanol, sodium selenate and verapamil and the overpredicted chemicals were 2,4-dichlorophenoxyacetic acid, mer-cury chloride, pentachlorophenol, propranolol and sodium chloride. Some of the outlier chemicals in the 3T3-NRU vs. LC50 correlation were not detected by the CMP assay (acetaminophen, acetonitrile, cy-closporine A, diazepam, digoxin, dimethylformamide, ethylene glycol, malathion, parathion, phenobarbital, strychnine and warfarin). Amioda-rone, caffeine, rifampicine and tetracycline interacted with the FMP probe, which was shown as a technical limitation of the assay.

Table 6. The responses of 23 chemicals in phase I on five neurofunctional endpoints and responses of 36 phase II chemicals on the CMP, studied in SH-SY5Y cells.

Chemicals Outlier1 CMP AChE NA up-

take AChR VOCC Identified as neurotoxic2

7a-ethynylestradiol 2,4-dichlorophenoxyacetic acid Yes 5-fluorouracil Acetaminophen X Acetonitrile X Acetylsalicylic acid Acrylaldehyde Amiodarone hydrochloride Amitriptyline hydrochloride X Yes Amphetamine sulphate Yes Arsenic trioxide Atropine sulphate monohydrate X Yes Cadmium (II) chloride Caffeine Carbamazepine Chloral hydrate Cis-diamine platinum (II) dichloride Colchicine Cycloheximide Cyclosporine A X Diazepam X (Yes) Dichlorvos Yes Diethylene glycol Digoxin X Dimethylformamide X Diquat dibromide X Epinephrine bitartrate Ethanol Ethylene glycol X

50

Chemicals Outlier1 CMP AChE NA up-

take AChR VOCC Identified as neurotoxic2

Glufosinate-ammonium Hexachlorobenzene Isopropyl alcohol Lindane X Yes Lithium sulphate Malathion X Mercury (II) chloride Yes Methadone hydrochloride X Yes Methanol Nicotine X Yes Ochratoxin A Orphenadrine hydrochloride Yes Parathion X Pentachlorophenol Yes Phenobarbital X Physostigmine Yes Propranolol hydrochloride Yes Pyrene

Chemicals Outlier1 CMP AChE NA up-

take AChR VOCC Identified as neurotoxic2

Rifampicine Sodium chloride Sodium fluoride Sodium lauryl sulphate Sodium selenate X Sodium valproate Strychnine X Tert-butylhydroperoxide Tetracycline hydrochloride Thallium sulphate Warfarin X Verapamil hydrochloride X

1 Outlier chemicals showing an inadequate correlation between the estimated human lethal blood concentration (LC50 and the in vitro cytotoxicity data received in mouse fibroblast 3T3 model using the neutral red up take assay (3T3-NRU)). 2 Chemicals identified as neurotoxic by one or more of the endpoints studied in the SH-SY5Y cell models, i.e. toxic concentrations in neurofunctional endpoints < IC50 (3T3-NRU). Light blue boxes= phase I chemicals tested in all assays. Green= chemicals which affected the denoted assay, dark green= toxic concentrations in neu-rofunctional endpoints << IC50 (3T3-NRU), light green= toxic concentrations in neurofunc-tional endpoints >>IC50 (3T3-NRU)

Due to features of the SH-SY5Y cells, i.e. expression of receptors, phe-notype, metabolic systems etc, the cells were able to identify most, but not all, of the test substances. For instance, strychnine induces toxicity by inhibiting glycine receptors, but did not affect the CMP in the SH-SY5Y cells. This indicates that the SH-SY5Y cells may not express functional glycine receptors and thus, cannot be used for identification of chemicals that interfere with glycine receptor function. Also the choice of endpoints was of great importance. The CMP seemed to be a good choice, due to its function as a general key event that is affected by a wide array of MIEs. However, a test battery of the CMP assay, the

51

NA uptake assay and the AChE assay, might be useful for identification of most neurotoxic alerts in SH-SY5Y cells.

Paper II The hypothesis of paper II was to elucidate if the murine neural progen-itor C17.2 cell line had the capacity to differentiate into a mixed cell culture during controlled culture conditions. In order to elucidate this hypothesis, we used three different media i.e., 1) complete Dulbecco´s modified essential medium (DMEM) supplemented with 5% horse se-rum, 10% FBS, L-glutamine, penicillin and streptomycin, 2) complete DMEM without 10% FBS but supplemented with BDNF and NGF ([10ng/mL] of each neurotrophic factor) and, 3) serum free DMEM:F12 supplemented with N2, BDNF and NGF ([10ng/mL] of each neu-rotrophic factor).

Concomitantly, the cells were exposed in three different conditions, conditioned medium i.e., no change of differentiation medium for 8 days in culture (DIC), medium change after 3-4 days (8 DIC in total) and conditioned medium i.e., no medium change but addition of the neurotrophic factors every 3rd day. The control cells were cultured for 3 days in in complete DMEM (Figure 5).

52

Figure 5. Schematic overview over culture conditions and duration of differentiation

The initial experiments showed that the cells cultured in complete

DMEM for 3 days were in their native state with no neurite processes. Cells cultured for 8 days in complete DMEM medium, without or with medium change after 4 days (treatment 2 and 3, respectively), no sign of neurite outgrowth was seen. Cells cultured with FBS-deprived me-dium but with 5% HS, BDNF and NGF (treatment 4-6) showed similar phenotypes as the cells cultured in serum free DMEM:F12 medium

53

with N2-, BDNF- and NGF- supplements (treatment 7-9). These six treatments showed a mix of two distinctly different phenotypes in the cultures.

To further analyse the differentiation process, the cells were exam-

ined after 3, 7 and 10 of differentiation in medium of DMEM:F12 sup-plemented with N2, BDNF and NGF. After 3 days of differentiation, cells with a denser cell body and short processes were seen. However, when differentiated for 7 days, i.e. 8 DIC, the cells showed a total mixed phenotype culture i.e., denser cell bodies with long extrusions (assumed to be neurons) growing on top of cell with a “fried egg” shaped cell body with a larger nucleus (assumed to be astrocytes). When differen-tiated for 10 days (11 DIC), these cell phenotypes were even more sig-nificant. In order to confirm the phenotype changes not just by mor-phology, we analysed the mRNA expression of nestin, βIII-tubulin and GFAP after 7 days of differentiation (8 DIC). It was confirmed, using RT-PCR, that the differentiated cultures changed the expression pat-terns from a high nestin, low βIII-tubulin and GFAP to a culture with low expression of nestin and higher expression of βIII-tubulin and GFAP. This change of mRNA expression was also confirmed with ex-pression of the same proteins using western blot, where we saw an in-crease after 7 days of differentiation of the two proteins, βIII-tubulin and GFAP concomitantly a decrease of nestin protein.

Paper III The overall results from the AcuteTox project (paper I), together with the results from paper II, led to the hypothesis tested in paper III. The hypothesis was to clarify if the mixed cultures of neurons and astrocytes developed from the C17.2 murine neural progenitor cell line had the capacity and potential to alert for chemicals, known to induce acute tox-icity by a neural MOA. The aim was to see if the cell model could re-place the primary aggregating rat brain cell culture that showed to be the best neuronal model in the ACuteTox project (Zurich, et al. 2013).

We assessed the CMP and the mRNA expression of selected bi-omarkers; βIII-tubulin (neuronal biomarker), GFAP (astrocyte bi-omarker) and heat shock protein 32 (HSP32, also known as heme oxy-genase-1 (HO-1), a biomarker for cell stress/cell survival) as neurofunc-tional endpoints to see if the cells responded to the toxicants in a con-centration-dependent manner at non-cytotoxic concecntrations. Six

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compounds were chosen from the ACuteTox project; the neurotoxins atropine sulphate monohydrate, nicotine, strychnine, and the non-neu-rotoxic chemicals acetylsalicylic acid, digoxin and ethanol. Our study showed that both assays could discriminate between the neurotoxic or non-neurotoxic compounds. The CMP measurement showed that atro-pine sulphate monohydrate, nicotine and strychnine induced a depolar-isation of the membrane at lower concentration compared to the neutral red uptake in mouse fibroblast cell line (3T3/NRU) and in the same range as the estimated lethal blood concentration (Sjostrom, et al. 2008a). However, no effects were seen on the CMP when the cells were treated with the non-neurotoxic compounds.

By analysing the mRNA levels of the selected biomarkers i.e., βIII-tubulin, GFAP and HSP32, it was shown that at least one of the bi-omarkers were altered upon treatment with the neurotoxic chemicals at concentrations equal to 1/10 of the IC50, determined in the 3T3/NRU assay. The morphology and the fraction of neurons and astrocytes in the differentiated cell cultures were not altered after the exposure. No ef-fects were observed on the mRNA biomarker expression after exposure with the non-neurotoxic chemicals. The neurotoxic compounds affected both the CMP and the mRNA expression endpoints, which might indi-cate that an acute change in the CMP may alter the expression of one or more of the biomarkers used.

Paper IV The aim of paper IV was to elucidate if the murine neural progenitor cell line C17.2 could function as a model for DNT testing by selecting biomarkers that are crucial for development of the NS. The cells were differentiated under controlled conditions according to paper II for 5 or 10 days. The mRNA levels were analysed using microarray expression analysis. The results from the microarray were used to create a list over differentially expressed genes. From this list of differentially expressed genes involved in neural differentiation (determined by gene set enrich-ment analysis), the 30 genes with the highest log2(fold change) changes were chosen without bias. These 30 genes were further validated by RT-qPCR. The biomarker validation using RT-qPCR confirmed the results from the microarray, i.e. all 30 genes chosen were upregulated com-pared to undifferentiated cells. In order to validate the level of differen-tiation of the C17.2 cells, RT-qPCR was performed on biomarkers for different neuronal phenotypes. The results from the RT-qPCR showed,

55

upon differentiation, an up-regulation of GAD1 (a GABAergic neuron marker) together with vGluT1 (a glutamatergic neuron marker) whereas no expression of ChAT (cholinergic neuron marker), TH (dopaminergic or noradrenergic neuron marker) and tryptophan dehydroxylase 2 (ser-otonergic neuron marker) was noted. This indicates that the neuronal phenotypes in the differentiated C17.2 cell culture were mainly GA-BAergic and glutamatergic. Protein levels of the neuronal biomarker βIII-tubulin, the astrocytic biomarker GFAP and the neural progenitor biomarker nestin were analysed after 5 and 10 days of differentiation. The results showed an up-regulation of βIII-tubulin and GFAP during differentiation together with a down-regulation of nestin.

In order to visualise the robustness together with the reproducibility of the test model, a principal component analysis was performed on the different time points of differentiation. The comparison of the gene ex-pression in cultures at different differentiation stages, i.e.,10 days ver-sus 5 days of differentiation, 10 days versus undifferentiated and 5 days’ differentiation versus undifferentiated showed well defined sepa-ration of the different groups. The differentially expressed genes (DEGs) between 10 days of differentiation and undifferentiated was 2166 genes (1216 genes were upregulated and 950 genes were down-regulated). The DEGs for cells after 5 days of differentiation compared with undifferentiated cells were 1065 genes (665 genes were upregu-lated and 400 genes were downregulated) and only 283 genes were ei-ther up- or down-regulated (192 and 91 genes, respectively) when 10 days and 5 days differentiated cells were compared.

To detect the biological changes during differentiation of the C17.2 cells, ingenuity pathway analysis was performed in order to elucidate the changes of pathway activity and changes during the differentiation process. Level of significance and activation between the different dif-ferentiation scenarios showed that the (hepatic) fibrosis pathway was the top pathway in each scenario and the axonal guidance was second most significant pathway to be active during differentiation. Six genes that are specific for axonal guidance were selected to be included in the selection of the 30 biomarkers to be validated. Stress response pathway, cyclin and cell cycle regulation pathways were predicted to be inhibited, however G2/M DNA damage checkpoint regulation, acute phase re-sponse signalling and NF-κB pathway were predicted to be active dur-ing the differentiation process.

To further investigate the relevance of these 30 biomarkers for neural differentiation of the C17.2 cells, the differentiation process was stud-ied after the influence of three chemicals known to interfere with neural

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development; MeHg, valproic acid and acrylamide together with a neg-ative control, D-mannitol. The IC10 value, i.e. the concentration gener-ating 10% reduction in viable cells as determined by the AlamarBlue assay, was determined for each compound, and used as the exposing concentration for 10 days. The morphology of the differentiated C17.2 cells that were exposed to IC10 of each chemical was slightly changed and 28 of the 30 selected biomarkers showed significantly altered gene expression after exposure to at least one or two of the DNT inducing chemicals.

57

Conclusions and outlook

This thesis presents attempts to develop and evaluate cell models and methods that are sensitive enough to detect chemicals that induce tox-icity by neuronal MOAs. Molecular initiating events and early key events were studied to predict human toxicity. The conclusions from the hypotheses studied during seven years are as follows:

� It was possible to predict acute toxicity for neurotoxic com-

pounds by using cell models, e.g. the SH-SY5Y cells, instead of using animal models. However, the cell model must express functional targets.

� We found that the CMP assay was the most promising neuro-functional endpoint as shown by higher sensitivity than the 3T3-NRU cytotoxicity assay and the improved correlation to human lethal blood concentrations.

� Using SH-SY5Y as a cell model, a test battery of the cell mem-brane potential, noradrenaline uptake and acetylcholinesterase, might be useful for identification of most neurotoxic com-pounds.

� We obtained a mixed culture of neurons and astrocytes after dif-ferentiation of the neural progenitor C17.2 cell line by following a novel differentiation protocol that was developed in this study.

� The differentiation process of the C17.2 cells was robust and reproducible as shown by whole genome array analysis.

� When exposed to chemicals during differentiation, the C17.2 neural progenitor cells can be used for studies on DNT by mon-itoring gene expression of 30 carefully selected biomarkers in-volved in development the nervous system.

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� The differentiated C17.2 cells were more sensitive to strychnine than SH-SY5Y cells, which indicates that the C17.2 cell system is a more sensitive model system for some compounds, e.g. gly-cine receptor inhibitors.

� The differentiated C17.2 cell model could distinguish between neurotoxic and non-neurotoxic compounds by using either the CMP assay or the mRNA biomarker expression assay.

Our over-all conclusion is that the C17.2 cell model may be useful for estimation of acute neurotoxicity and developmental neurotoxicity. The cell model should be further validated for these purposes.

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Populärvetenskaplig sammanfattning

Hjärnan är vårt mest känsliga organ och minsta påverkan kan få för-

ödande konsekvenser då all signalering är strikt kontrollerad. Kemika-lier, bekämpningsmedel, läkemedel och kosmetika kan påverka hjärnan och nerverna på ett negativt sätt så som känselbortfall, svårigheter att lära sig saker eller ofrivilliga rörelser. För att kunna bedöma risken av kemikaliers toxicitet, behöver man testsystem som kan ta fram den in-formationen.

Det är idag nödvändigt att dokumentera toxiciteten för alla kemika-lier som produceras över 1 ton per år enligt EUs kemikalieförordning. Följden av denna förordning blev att många försöksdjur skulle behöva användas för att utreda toxiciteten för alla dessa kemikalier. Man hade tidigare sett att celler odlade i skålar reagerade på utvalda kemikalier men att vissa av dessa kemikalier, speciellt de som är toxiska för vår hjärna och nervsystemet, så kallat nervtoxiska, inte gav utslag i cellmo-dellerna. Syftet med min forskning var att utveckla och utvärdera cell-modeller som kan simulera skadliga effekter av kemikalier i hjärnans celler eller i nervsystemet.

Vi undersökte hur en etablerad nervcellmodell, så kallade SH-SY5Y, från människlig vävnad reagerade på 59 kemikalier. Olika nervcells-funktioner studerades och det visades att en kombination av flera meto-der skulle krävas för att kunna avgöra kemikaliernas toxicitet. Vi drog slutsatsen att denna cellmodell inte var tillräckligt komplex, då cellkul-turen enbart består av en typ av celler och inte som hjärnan, flera typer av celler (olika nervceller, astrocyter, med flera). Därför ville vi under-söka om en annan cellmodell, C17.2 som var av stamcellkaraktär från mushjärna, bättre kunde indikera om kemikalier är nervtoxiska. Stam-celler har en förmåga att utvecklas till olika mogna celltyper beroende av vilka signalämnen de exponeras för. Vi lyckades utveckla en metod där C17.2 celler mognade till två olika celltyper i cellodlingsskålen; nervceller och så kallade astrocyter. Vi fann att cellkulturen innehål-lande de två celltyperna kunde särskilja mellan substanser som var nervtoxiska och de som inte var det.

Med hjälp av stamcellinjer från hjärnan kan man studera utveckl-ingen från det omogna stadiet tills de utvecklas och blir nervceller och

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astrocyter. Detta kan efterlikna en mycket tidig utveckling av hjärnan. Vi såg att nivån av mRNA, vilket fungerar lite som proteinernas bygg-stenar, påverkades under cellmognaden av kemikalier som man vet ger hjärnskador om man exponeras under fosterutvecklingen.

Med bakgrund av våra resultat vågar vi vara hoppfulla om att man i framtiden kommer att, med hjälp av adekvata cellmodeller, kunna be-döma om hjärnans och nervsystemets funktioner påverkas av expone-ring för kemikalier som vuxen eller under fosterutvecklingen.

61

Acknowledgements

Efter år på institutionen för neurokemi (ja för mig blev det sammanlagt en lång tid) har det varit mycket skratt, ganska mycket gråt, mycket förtvivlan, en del lycka och lite sorg. Just i denna stund känns det ganska tomt och vemodigt men jag ska försöka skärpa mig. Så…

Mitt första tack vill jag rikta emot dig Anna, som i inledningen av vår tid tillsammans trodde på mig och lät mig komma in i din värld. Tänk vad mycket roligt vi har haft. Tack för allt! Det kommer inte sluta här, jag är som en fästing…. Tack, Ian, min andra handledare på Swetox, för alla goda råd i avhand-lingsarbetet och andra samtal, är så tacksam för all hjälp. Eftersom jag varit så länge på institutionen har det varit många männi-skor som jag träffat och lärt känna… Jag gör som ett CV…. Från nutid tillbaka i tiden… Kristina, bästaste bästa! Det är en ynnest att få ha en vän som du i mitt liv - så mycket skoj vi har haft och kommer att ha! Nina, vad vi tragg-lade i köket uppe på backen, något fastnade i alla fall. Heléne och He-lena, tack för all hjälp till en förvirrad nybörjare, Johan, du lärde mig gilla ”skånsk rapp” och sist men inte minst, Jojo, som var den som fick mig att börja på institutionen för många år sedan. Niina, vi gjorde det till slut - när denna bok är på tryck försvarar du din….. Och du, Veronica, är snart på andra sidan! Andrea, I have no doubt that you'll do just fine. Mina roomisar….. Dan and Helena good laughs are never far away. Tack alla ni som får detta ställe att gå runt. Anna-Lena, klippan som alltid ställer upp och man alltid kan komma till. Marie-Louise, för att du alltid finns där och tar hand om oss på bästa sätt. Vad skulle vi göra utan MLT!?!

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Sylvia, din dörr är alltid öppen (utom vid årsskiftet), både för öppna och slutna samtal. Einar, din knäckemacka går till historien. Anders för dina djupa samtal om allt mellan himmel och jord. Ülo, Tamas, Bengt, Hen-rietta, Mattias, Ricardo, Tom, Hakim, Kali, Birgitta och Balaje, ett stort tack för allt! Gamla doktorander som slutat men som gjorde det roligt att komma till jobbet. Till er doktorander som är kvar, ta hand om varandra; Anna E, Carmine, Cissi, Elena, Frida, Maxime, Mehedi, Moataz, Preeti, Tönis - tack för allt! Till mina vänner utanför universitetet; stallgänget som vi umgås mycket med, tack för att ni har bidragit till att jag grejade detta, familjen Åhl, Kleiman, Henriksson, Gyllenberg och Ask, för alla minnen vi skapat och skapar. Familjerna Arvidsson, Hesselgren/Standberg för att ni stått ut med mig. Pappa och Mamma, tack, för ni alltid ställer upp och hjälpte till när el-den är lös, ni gjorde det svåra lättare, tack! Mina syskon med familjer, för att ni finns. Farmor som alltid finns där för oss. Sist men inte minst Andreas och Clara, mina hjärtan!

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