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ACTA UNIVERSITATIS UPSALIENSIS UPPSALA 2018 Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine 1481 Exposure to xenobiotic chemicals disrupts metabolism, rhythmicity and cell proliferation in Drosophila melanogaster HAO CAO ISSN 1651-6206 ISBN 978-91-513-0391-8 urn:nbn:se:uu:diva-356545

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Page 1: Exposure to xenobiotic chemicals disrupts metabolism ...uu.diva-portal.org/smash/get/diva2:1236178/FULLTEXT01.pdf · Cao, H. 2018. Exposure to xenobiotic chemicals disrupts metabolism,

ACTAUNIVERSITATIS

UPSALIENSISUPPSALA

2018

Digital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Medicine 1481

Exposure to xenobiotic chemicalsdisrupts metabolism, rhythmicityand cell proliferation in Drosophilamelanogaster

HAO CAO

ISSN 1651-6206ISBN 978-91-513-0391-8urn:nbn:se:uu:diva-356545

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Dissertation presented at Uppsala University to be publicly examined in B22, BMC,Husargatan 3, Uppsala, Friday, 21 September 2018 at 13:00 for the degree of Doctor ofPhilosophy (Faculty of Medicine). The examination will be conducted in English. Facultyexaminer: Professor Jan Larsson (Umeå University, Department of Molecular Biology).

AbstractCao, H. 2018. Exposure to xenobiotic chemicals disrupts metabolism, rhythmicity and cellproliferation in Drosophila melanogaster. Digital Comprehensive Summaries of UppsalaDissertations from the Faculty of Medicine 1481. 50 pp. Uppsala: Acta UniversitatisUpsaliensis. ISBN 978-91-513-0391-8.

Most species are constantly exposed to xenobiotic chemicals through multiple routes. Amongall categories of xenobiotics, phthalates and bisphenols are two of the most widely usedplasticizers and can be found in polyvinyl chloride (PVC) materials, medical devices and evendrinking water. In paper I, we found that bis-(2-ethylhexyl) phthalate (DEHP) exposure causeda significant decrease in circulating carbohydrates and insulin-related genes. The Multidrug-Resistance like Protein 1 (MRP1, MRP in Drosophila) belongs to the ATP-binding cassettetransporter family, and previous studies revealed the importance of MRP1 for transportingxenobiotics. However, the function of MRP1 in metabolism and other biological processesis still unclear. Therefore, in paper II, we showed that knocking down MRP expression inMalpighian tubules, the physiological equivalence of the vertebrate kidney, led to disruptedlipid homeostasis and oxidative resistance. In paper III and IV, we initially used wholetranscriptome sequencing to assess the genetic interferences of exposure to Dibutyl Phthalate(DBP) and Bisphenol A Diglycidyl Ether (BADGE). The reproductive and developmentaldisruptions of DBP had been reported in many studies. However, the mechanism is stillunclear. In paper III, we observed that DBP interfered with neuronal systems associatedcircadian genes, including in vrille (vri, human NFIL3), timeless (tim, human TIMELESS),period (per, human PER3) and Pigment-dispersing factor (Pdf). Furthermore, we demonstratedthat the evolutionarily conserved gene, Hormone receptor-like in 38 (Hr38, human NR4A2) wasinvolved in responding to DBP and regulated Pdf expression as a consequence. In paper IV,BADGE, a BPA-substitute, was tested for its disruptive effects on Drosophila. Based on thetranscriptome sequencing, we found that several mitotic genes, including string (stg, humanCDC25A), Cyclin B (CycB, human CCNB1), Cyclin E (CycE, human CCNE1), and pan gu (png,human NEK11), had detectable overexpression by BADGE exposure. Developmental exposureto BADGE induced a large increase of hemocytes in fly 3rd instar larvae, while it did not damagethe morphological structure of lymph gland and blood circulation. To summarize, our studiesdescribe the potential disruptions of the industrial xenobiotics and provide the mechanistic hintsfor future investigations.

Keywords: xenobiotics, metabolism, insulin signalling, circadian rhythm, carcinogen

Hao Cao, Department of Neuroscience, Functional Pharmacology, Box 593, UppsalaUniversity, SE-75124 Uppsala, Sweden.

© Hao Cao 2018

ISSN 1651-6206ISBN 978-91-513-0391-8urn:nbn:se:uu:diva-356545 (http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-356545)

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To my family and friends.

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List of Papers

This thesis is based on the following papers, which are referred to in the text by their Roman numerals.

I Cao H, Wiemerslage L, Marttila PS, Williams MJ, Schiöth HB,

Bis-(2-ethylhexyl) Phthalate Increases Insulin Expression and Lipid Levels in Drosophila melanogaster. Basic Clin Pharma-col Toxicol. 2016 Sep;119(3):309-16.

II Cao H, Kimari M, Maronitis G, Williams MJ, Schiöth HB, Multidrug-Resistance like Protein 1 activity in Malpighian tu-bules regulates lipid homeostasis in Drosophila. Manuscript.

III Cao H, Hosseini K, Siyahtiri MM, Maestri G, Shirazi M, Wil-liams MJ, Schiöth HB, Dibutyl phthalate exposure disrupts con-served circadian rhythm signaling systems in Drosophila. Man-uscript.

IV Cao H, Lindkvist T, Mothes TJ, Williams MJ, Schiöth HB, Developmental bisphenol A diglycidyl ether (BADGE) expo-sure causes cell over-proliferation in Drosophila. Manuscript.

Reprints were made with permission from the respective publishers.

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Additional publications

• Zheleznyakova GY, Cao H, Schiöth HB, BDNF DNA methylation changes as a biomarker of psychiatric disorders: literature review and open access database analysis. Behav Brain Funct. 2016 Jun 6;12(1):17.

• Wiemerslage L, Islam R, van der Kamp C, Cao H, Olivo G, Ence-Eriksson F, Castillo S, Larsen AL, Bandstein M, Dahlberg LS, Perland E, Gustavsson V, Nilsson J, Vogel H, Schurmann A, Larsson EM, Rask-Andersen M, Benedict C, Schiöth HB, A DNA methyla-tion site within the KLF13 gene is associated with orexigenic pro-cesses based on neural responses and ghrelin levels. Int J Obes (Lond). 2017 Jun;41(6):990-994.

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Contents

Introduction ................................................................................................... 11 Drosophila melanogaster in fundamental research .................................. 12

Conserved metabolic system ............................................................... 12 Tools in Drosophila research ............................................................... 13

Circadian rhythm and activity in Drosophila ........................................... 13 Endocrine Disruptors (EDCs) and Phthalates .......................................... 15

Bis-(2-ethylhexyl) Phthalate (DEHP) .................................................. 15 Di-butyl Phthalate (DBP) .................................................................... 16

BPA alternatives and Bisphenol A diglycidyl ether (BADGE) ............... 16 Non-monotonic dose-response curve (NMDRC) ..................................... 16 Xenobiotic metabolism and ABC transporters ......................................... 17

Aims .............................................................................................................. 19

Materials and methods .................................................................................. 20 Fly strains, maintenance, and toxin feeding pattern ................................. 20

Fly strains ............................................................................................ 20 Fly maintenance ................................................................................... 20 Toxin feeding pattern ........................................................................... 20

Library preparation, sequencing, and data analysis.................................. 21 Biochemical and molecular assays ........................................................... 22

RNA extraction and cDNA synthesis .................................................. 22 qRT-PCR ............................................................................................. 22 Carbohydrate assay .............................................................................. 23 Lipid measurement .............................................................................. 23 TAG assay ........................................................................................... 24 ROS detection ...................................................................................... 24 Larvae bleeding and hemocytes quantification ................................... 24 Confocal imaging ................................................................................ 25

Behavioral assays ..................................................................................... 25 Starvation assay ................................................................................... 25 Paraquat resistance............................................................................... 25 Circadian rhythm assay ........................................................................ 26 FlyPAD ................................................................................................ 26

Statistical analysis .................................................................................... 27

Results ........................................................................................................... 28

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Paper I ...................................................................................................... 28 Paper II ..................................................................................................... 29 Paper III .................................................................................................... 30 Paper IV ................................................................................................... 33

Conclusions and discussions ......................................................................... 35

Perspectives .................................................................................................. 38

Acknowledgements ....................................................................................... 39

References ..................................................................................................... 40

Appendix I- list of fly strains ........................................................................ 48

Appendix II- List of primer sets .................................................................... 49

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Abbreviations

DEHP- bis-(2-ethylhexyl) phthalate DAMS- Drosophila activity monitoring system CAFE- capillary feeding assay ABC transporter- ATP binding cassette transporters MRP- multidrug-resistance like protein PXR- pregnane X receptor TAG- triacylglyceride FlyPAD- Fly proboscis and activity detector ROS- reactive oxygen species DBP- di-butyl phthalate BPA- bisphenol A BADGE- bisphenol A diglycidyl ether NMDRC- non-monotonic dose-responding curve qRT-PCR- quantitative real-time PCR ZT- Zeitgeber time

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Introduction

Xenobiotics are defined as non-endogenous chemicals found in a living or-ganism. Plastic material is one of the most common xenobiotics humans are exposed to. In the nineteenth century, the Industrial Revolution prompted the development of industrial chemistry. Many materials were synthesized and introduced to manufactory. As plastics are portable, lightweight and durable materials, they were gradually applied in many fields. Plastics refer to a va-riety of synthetic or semi-synthetic organic materials which are elastic and malleable and can be used for making containers, packings and other indus-trial products. The first fully synthetic polymer, Bakelite, was produced in 1907 [1]. Due to advances in organic synthesis, numerous plastic materials have gradually developed. Nowadays, more than 300 million metric tons of plastics are produced annually [2]. However, like the two sides of a coin, the durability of plastics make them very difficult to fully degrade and will per-sist in nature for up to a century [3, 4]. Therefore, the trend of worldwide plastic contamination has attracted much attention from the public. Addi-tionally, the hazardous endocrinal disruption of bisphenol A (BPA) and bis-(2-ethylhexyl) phthalate (DEHP), which have been revealed in the past dec-ades [5-8], have caused great human health concerns. The human uptake of toxic compounds is not only from direct inhalation and ingestion, but also from bioaccumulation in the food chain, e.g., the phthalate residues of plastic film greenhouse vegetables [9], the plastic contamination from marine food products [4, 10], and migration from packings into food and water [11, 12]. Although, European countries have applied restriction on the industrial use of certain kinds of plastic compounds, the prevalent usage and ongoing in-vestiations of adverse effects of plastics are still threatening the public health. In this dissertation, I want to contribute to a better understanding of the xe-nobiotics, specifically the toxic plastic compounds. For this sake, three dif-ferent plasticizers, bis-(2-ethylhexyl) phthalate (DEHP, in Paper I), di-butyl phthalate (DBP, in Paper III), and bisphenol A digylcidyl ether (BADGE, in Paper IV) were assessed on Drosophila melanogaster, and a potential mo-lecular mechanism was raised (in Paper II). At last, I would like to empha-size some contents in this dissertation may share similar ideas and methods to my licentiate thesis which I defended in December, 2017 and titled as “A xenobiotic chemical and transporter regulates metabolism in Drosophila melanogaster”.

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Drosophila melanogaster in fundamental research Drosophila melanogaster, also known as common fruit flies, is one of the model animals used in many biological researches. Genetic studies with Drosophila were initiated in 1910 by Thomas Hunt Morgan. From 1910 to 1960, most Drosophila studies were focused on inheritance. Afterward, with the advantages of numerous tools and methods, investigations were not lim-ited to genetics and spread to immunology, neurology, and metabolism. Up to now, Drosophila melanogaster has been well documented and widely used in science. The first transgenic Drosophila model was constructed in 1987 and the genome was sequenced completely in 2000 [13]. There are thousands of genetic stocks available for deciphering molecular and cellular mechanisms underlying complicated biological processes. Moreover, the fruit flies are evolutionarily conserved. About 60% of genes are verified as a human homolog and over 75% of disease-related genes are also found in Drosophila melanogaster [14, 15] which enables the fruit fly as a useful tool in various aspects. Furthermore, owing to the rapid reproductive rate and short life cycle [16], research with Drosophila is always less time-consuming and more straightforward.

Conserved metabolic system On the metabolic aspect, enzymes and organs in Drosophila which regulate carbohydrate and lipid homeostasis are largely conserved and analogous to vertebrates [17]. The midgut of Drosophila acts as a stomach and intestine; the fat body is the functional equivalence of a liver and the main excretory organ Malpighian tubules are similar to a human kidney [18]. Maintenance of circulating sugar is crucial to organisms. In mammals, pancreatic α- and β- cells secrete glucagon and insulin respectively to stabilize blood sugar levels. The adipokinetic hormone (Akh) is known as the glucagon-like pep-tide in flies [19, 20]. Different from mammals, trehalose is the major circula-tion sugar in insects. A high level of trehalose induces Akh expression. Con-sequently, AKH forces trehalose to be stored in the form of glycogen. On the contrary, the insulin-insulin-growth-factor signaling (IIS) pathway modu-lates sugar level when it is below the threshold [21]. Eight Drosophila insu-lin-like peptides (Ilps) have been identified and expressed in varying tissues and patterns controlling growth, larval development, lifespan and metabo-lism [22-25]. In addition, the lipid homeostasis involves two conserved genes: the Drosophila perilipin-like protein Lsd2 (lipid storage droplet 2) promotes lipid storage [26] and the adipose triglyceride lipase (ATGL) hom-olog Brummer controls lipolysis [27]. The counterbalance between Lsd2 and Brummer generates the basic lipid homeostasis.

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Tools in Drosophila research The most used genetic tool in fruit flies is the GAL4-UAS binary system. It allows scientists to specifically overexpress or knockdown genes of interest in diverse tissues or cells [28]. The GAL4 protein is derived from a yeast transcription factor and can specifically target the Upstream Activation Se-quence (UAS). When a fly strain carries GAL4 expressed under the control of a native gene and then crosses to another UAS-strain, in the first genera-tion, specific GAL4 expression triggers the activation of UAS sequence. As a consequence, the fragment that the UAS carries can express and manipu-late the gene-of-interest spatially and/or temporally. This is a good tool to achieve genetic manipulations in fruit flies. In addition, most techniques used on rodents are available for Drosophila studies, such as optogenetics and CRISPR/Cas-9 genome editing [29-31]. Taken together, these powerful tools make fruit flies a suitable model organism in many scientific studies.

Circadian rhythm and activity in Drosophila Circadian rhythm, generally known as the biological clock, is a ubiquitous phenomenon driven by molecular clocks and found throughout species. A rhythmic animal is able to predict rhythmic changes in the environment, anticipate dawn and dusk, and behave regularly according to the time of the day [32]. Many physiological processes rely on circadian maintenance. And the maintenance of rhythmicity depends on self-sustaining molecular tran-scriptional/post-transcriptional feedback loops. The fundamental mechanism of circadian rhythm is well established, and the discoveries of Drosophila circadian genes period (per) and timeless (tim) were awarded the 2017 Noble Prize in Physiology and Medicine [33, 34]. In Drosophila, the central circa-dian genes, clock (clk) and cycle (cyc) are evolutionarily conserved. The oscillation of the proteins CLK-CYC regulates other circadian genes, such as per and tim, which can feedback to CLK-CYC transcription at night hours [35]. This feedback loop forms the foundation of day-night activity oscilla-tion. Additionally, the neuropeptide pigment dispersing factor (Pdf) has been extensively studied [36-42]. Pdf has diverse roles in controlling fruit fly rhythmicity. It is necessary for the maintenance of rhythm and setting or synchronizing the biological clock [36, 41]. Downstream activation of the PDF receptor (PDFR) activates G protein-coupled receptor (GPCR) to in-crease cAMP and PKA levels, leading to stabilization of TIM and PER [43]. One another circadian gene, cytochrome (cry) reacts to the light (basically the blue range of visible light) and degrades the dimerized PER/TIM com-plex [43]. This regulatory mechanism is schematically illustrated in Figure 1A.

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Figure 1. A schematic illustration of the molecular mechanism of circadian regulation in Drosophila melanogaster (A). CLK and CYC are the central genes which receive feedback from both PDF and PER/TIM. CRY responds to light and degrades PER/TIM complex. A mapping of circadian neurons in Drosophila brain (B). M cells are illustrated in blue and E cells in red. The s-LNv and l-LNv constitute the PDF-positive cells.

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The circadian neurons in Drosophila are fully mapped. In 1988, the circa-dian neurons were first identified by PER and TIM immunostaining [44]. According to the size, projections, and neurotransmitters, the circadian neu-rons are classified as the Dorsal Neurons (DN) 1, 2 and 3, the dorsal Lateral Neurons (LNd), the ventral Lateral Neurons (LNv), and Lateral Posterior Neurons (LPN) [32]. The LNvs, which can be divided into large and small LNvs (s- and l-LNvs) in term of the body size, are PDF positive neurons. The s-LNvs regulates the daytime activity and so are called Morning (M) cells or oscillators. On the contrary, the 5th s-LNv, three LNd and two DN1a neurons are more active in the nighttime and thus Evening (E) cells or oscil-lators. The cooperation of all these neurons forms a complex and elaborate network to reinforce the circadian rhythm (see Figure 2B).

Endocrine Disruptors (EDCs) and Phthalates Endocrine disrupting chemicals or endocrine disruptors (short as EDCs) are prevalent environmental pollutants, which can induce severe deficits in re-production, development and neural abnormalities. The definition of endo-crine disrupters was first coined in the 1990s [45]. However, the usage of EDCs can be retrospect to a century ago. Phthalate esters (PAEs) were intro-duced to industry in the 1930s and generally used in manufacturing plastic materials [46]. Due to the molecular properties, phthalates cannot form a covalent bond to plastics [47] which makes them easily leach from the plas-tic. To date, the annual global consumption of phthalates is over 470 million pounds [48]. Phthalates are the most prevalently used chemical in polyvinyl chloride (PVC) and medical devices manufacturing, plastics producing, cosmetics and food packaging [49]. The detrimental effects of two phthalates were assessed on Drosophila in this thesis, shown below.

Bis-(2-ethylhexyl) Phthalate (DEHP) DEHP is one of the most frequently used chemicals in the industry [50]. Human DEHP exposure routes include ingestion and inhalation [51, 52]. Although many restrictions on using DEHP have been applied, excessive DEHP levels are still found in human body fluid samples [53-55]. Both chronic and acute DEHP exposure has been reported to disrupt metabolism [56, 57], development [58, 59] and fertility [60-62]. Thus, investigating the mechanism of the disruptive effect of DEHP is important to human health and safety.

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Di-butyl Phthalate (DBP) DBP has widespread use in perfumes, cosmetics, and medical devices. In Europe, DBP has been banned since 2005. However, it is continuously de-tected in the environment which warns us of continued long-term exposure [63, 64] and calls for additional investigation.

BPA alternatives and Bisphenol A diglycidyl ether (BADGE) Bisphenols, which have been in commercial use since the 1950s, are a major type of plasticizer used in industry [65]. In the late 1990s, laboratory and epidemiological studies revealed the adverse effects of BPA exposure [66-69]. Due to the estrogenic property, BPA can cause metabolic disruption [70, 71], neurological impairment [72, 73], reproductive disturbance [74] and cancer [75]. Therefore, a group of BPA substitutions was derived during the twenty-first century. Bisphenol A diglycidyl ether (BADGE), which is one of these alternatives, is used in epoxy resin production. BADGE and its hydrolysis derivatives have been detected in human urine, plasma and adi-pose fat tissues [76, 77], indicating a prevalent exposure. Noteworthy, it can be easily hydrated in water and chlorinated in chlorine-containing solutions [78], and as a consequence, the concentration of BADGE and its derivatives cannot be accurately measured. Similar to BPA, BADGE also has estrogenic activity and its reproductive and developmental toxicity have been identified [79, 80]. Human are exposed to BADGE through multiple pathways. Many survey reports have detected BADGE and other BPA-substitutes in canned food [81], indoor air [82], and even in drinking water [83]. Nevertheless, BADGE does not attract too much concern. In paper IV, we demonstrated the carcinogenic property of BADGE.

Non-monotonic dose-response curve (NMDRC) Different from the typical toxins and drugs, most xenobiotics exhibit the non-monotonic dose-responding curves (NMDRC), i.e. a U- or inverted U-shape dose response [84]. Thus, it is very difficult to fully understand the adverse influences of these substrates. For instance, BPA was initially de-veloped as an estrogen mimic in pursuit of medical use in the 1890s [74]. Because of its low estrogenic efficacy, another structurally similar com-pound was synthesized called diethylstilbestrol (DES), which was also total-ly banned in 1979 [85]. BPA was then introduced in the manufacture of plas-tics until its reproductive and developmental toxicity had been widely no-

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ticed. This phenomenon happens and will possibly happen to other xenobiot-ics as well.

Xenobiotic metabolism and ABC transporters

Figure 2. A brief overview of xenobiotic metabolism which is modified from a recent review [86]. The phase I metabolism involves cytochrome P450 enzymes (CYPs) for the lipophilic activation of xenobiotics. In phase II, the UDP-glucuronosyltransferases (UGTs), sulfotransferases (SULTs) and glutathione-S- transferase bind to the xenobiotics and then transport them outwards from cells by phase III transporters, which are mainly multidrug-resistance like proteins (MRPs).

The xenobiotic control system consists of three phases and includes three xenobiotic metabolizing enzyme families [87]. In phase I, enzymes respond and activate the lipophilic components and expose the hydrophilic groups for phase II enzymes. The most known phase I molecules include cytochrome P450 enzymes, aryl hydrocarbon receptor (AHR) and pregnane X receptor (PXR) [88]. The phase II enzymes, such as nuclear factor (erythroid-derived 2)-like 2 (NRF2), can conjugate to the hydrophilic groups. At phase III, the enzymes/transporters then can transport xenobiotics out of the cell plasma. The ATP-binding cassette transporters (ABC transporters) are one of the largest transporter families in most species. They take part in both phase II and III clearance. In Drosophila, the two most investigated ABC transporter subfamilies are ABCB, which is also known as Multi Drug Resistance (MDR) and ABCC, which is also known as Multidrug Resistance-like Pro-

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tein (MRP). The schematic xenobiotic metabolism is illustrated in Figure 2. Cooperating with phase I and II enzymes, the ABC transporters contribute to toxin secretion and signal transduction [89, 90]. In this thesis, we focus on the ABCC transporters. As one of the major ABCC transporter, MRP1 is highly conserved and expressed in many metabolic and excretory tissues and also in both prokaryotic and eukaryotic organisms [91-93]. The roles of MRP1 as a lipophilic anion transporter in xenobiotics clearance and confer-ring resistance to anticancer agents are well documented [94-97]. In the met-abolic profile, MRP has also been reported potentially related to energy and drug metabolism [98, 99].

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Aims

In this work, we aim to investigate the undefined disruptions caused by xe-nobiotic exposures. Recently, society has realized the association between daily xenobiotic exposure and human endocrinal disease. As one major type of xenobiotics, plastic-related toxins raised great concern.

In paper I, we demonstrated that DEHP, a major additive in PVC materi-als, has metabolic impacts on Drosophila. Also, we aimed to identify the mechanism of how DEHP can disrupt metabolism.

In paper II, the tissue-specific functions of MRP were evaluated. It is well known that the ABC transporter family is much involved in xenobiotic me-tabolism. MRP belongs to the ABCC subfamily and takes part in xenobiotic clearance in many organs. Therefore, we conduct tissue-specific knockdown to isolate the metabolic role that MRP plays in different organs.

In paper III, we aimed to assess the influence of DBP exposure on Dro-sophila. DBP has been used in industry for decades and has been gradually banned in many developed countries because its small molecular mass can easily cause DBP leaching from plastics into food and water. However, the retention of DBP in the environment is long-lasting due to the extensive utilization of it. In this study, we found that DBP exposure led to a rhythmic disruption on Drosophila which has been rarely reported in previous studies.

In paper IV, the aim was to test the third xenobiotic compound, BADGE. Since the detrimental properties of BPA were uncovered, a group of BPA alternatives has developed and BADGE is one of these replacements. How-ever, knowledge about BADGE is insufficient. As a result, we further inves-tigated the carcinogenic nature of BADGE.

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Materials and methods

Fly strains, maintenance, and toxin feeding pattern Fly strains The laboratory wild-type fly CSORC was created by crossing CantonS and OregonR-C flies. All fly strains were obtained from Bloomington Stock center (Indiana, USA) unless otherwise stated. The transgenic fly strains are listed in Appendix I.

Fly maintenance Flies for experiments were maintained on Jazz-mix Drosophila food (Fisher Scientific, Göteborg, Sweden) and supplemented with yeast extract (Genesee Scientific, San Diego, California, USA) at 25°C and 60% humidity under 12/12h light:dark conditions. All of the UAS-TrpA1 fly crosses were main-tained at 20°C to inhibit TrpA1 activity. The F1 progeny were collected im-mediately after eclosion and aged for 5-7 days before the assays. Due to the fact that the frequent reproductive cycle of the female flies could potentially influence their behavior, we used only males in our experiments.

Toxin feeding pattern All the concentration mentioned in this dissertation refers to the final con-centration of certain toxins in fly food. All of the toxins were diluted in 99% ethanol and the control food was mixed with the same volume of 99% etha-nol without any toxins. In paper I, DEHP dilutions were ranged from 20 μM to 2 mM; in paper III, DBP dilutions were ranged from 45 nM to 450 nM and in paper IV, BADGE dilutions were ranged from 20 μM to 200 μM. The F0 flies were allowed to lay eggs in food bottles for 3-5 days. Then the F1 flies were raised on either normal food or toxin-containing food throughout the embryonic and larval stages. When the progenies eclosed, they were collected immediately and transferred to a vial with corresponding food for 5 days of aging before the experiments were conducted.

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Library preparation, sequencing, and data analysis The mRNA was isolated by Dynabeads mRNA purification kit (Invitrogen, 61006). The flies used for sequencing were fed on either control or 45nM DBP/60 μM BADGE food. Three biological replicates, which contained 10 whole flies in each replicate, were prepared for sequencing. RNA-Seq reads for whole transcriptome were obtained using SOLiD 5500xl paired-end se-quencing from Life Technologies (Uppsala, Sweden). This version produces read lengths of 75 bp for fragment libraries with the alternative to sequence an additional 35 bp in the reverse direction (paired-end sequencing). The samples were divided into six libraries and since the libraries were molecu-larly bar-coded the separation of libraries for control and experimental sam-ples was done effortlessly using respective barcodes. Further analysis was done using the 'Tuxedo suit' [100, 101] composed mainly of three tools: TopHat, Cufflinks, and CummRbund.

TopHat (v2.0.6) incorporates an ultra-high-throughput short read aligner with Bowtie (version 0.12.7) [102, 103] as the alignment engine. Based on the provided quality control information TopHat removes a portion of reads and maps the remaining reads to the reference genome. Reads were then aligned to the D. melanogaster reference genome (build dmel_r5.47_FB2012_05) obtained from Flybase using TopHat with the prebuilt Bowtie index downloaded from the TopHat homepage (http://TopHat.cbcb.umd.edu/igenomes.shtml). Transcript assembly and abundance estimation was performed with Cufflinks. The aligned reads were then processed by Cufflinks v2.0.2. Cufflinks tool estimates the relative abundances of transcripts based on how many reads support each transcript, taking into account biases in library preparation protocols and reports it in “fragments per kilobase of transcript per million fragments mapped” or FPKM. Cufflinks constructs a minimum set of transcripts describing the reads in the dataset rather than using existing gene annotation which allows Cufflinks to identify alternative transcriptions and splicing. However, it should be noted that Cufflinks is dependent on the provided genome annota-tion and therefore the reported FPKM values relate only to the genes de-scribed and genes missing in the annotation description file will not be re-ported.

Cuffcompare was used to produce combined General Transfer Format (GTF) files of the six libraries. The GTF files were then passed to cuffdiff along with original alignments obtained with TopHat. Cuffdiff reestimates the abundance of transcripts listed in GTF files using alignment files. The differential expression is checked for genes, transcripts, and isotopes. By tracking changes in the relative abundance of transcripts with a common transcription start site, cuffdiff can identify changes in splicing. Cuffdiff learns how read counts vary for each gene across the replicates and uses these variance estimates to calculate the significance of observed changes in

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expression. The calculated P value and q value (the FDR-adjusted P value of the test statistic) from Cuffdiff were used to determine the significance of differential expression. The significance depends on whether P is greater than the false discovery rate (FDR) after a Benjamini-Hochberg correction [104] for multiple testing.

Biochemical and molecular assays RNA extraction and cDNA synthesis The phenol chloroform method was used for RNA extraction from tissue samples [105]. At least twenty-five fly heads or ten fly bodies (or whole flies) were homogenized in 160 μL TRIzol (Invitrogen, Stockholm, Sweden) and added with 600 μL TRIzol afterwards, 200 μL chloroform (Sigma-Aldrich, Stockholm, Sweden), and samples mixed thoroughly followed by 12,000 g centrifugation for 15 min at 4 °C. The aqueous layer, which contained RNA, was separated and transferred into 500 μL isopropanol (Solveco AB, Rosersberg, Sweden). The precipitation of RNA was done at -32 °C for 1 hour or longer. Samples were centrifuged at 12,000 g for 10 min at 4 °C after precipitation. The RNA pellets were washed with 75% ice-cold ethanol for three times and then air dried for 15 min. RNase-free DEPC water was used to re-suspend the RNA samples. RNA concentration was measured using Multiscan GO spectrophotometer (Thermo Scientific). cDNA reverse transcription was performed using High-capacity RNA-to-cDNA kit (Ap-plied Biosystems, 4387406).

qRT-PCR Relative expression levels of the housekeeping gene, ribosomal protein 49 (Rp49, which is generally used in Drosophila [106] and other insect [107] studies) and of the genes of interest were determined with qRT-PCR. Each reaction, with a total volume of 20 μL, contained 20 mM Tris/HCl pH 9.0, 50 mM KCl, 4 mM MgCl2, 0.2 mM dNTP, DMSO (1:20) and SYBR Green (1: 50,000). Template concentration was 5 ng/μL, and the concentration of each primer was 2 pmol/L. Primers were designed with Beacon Designer (Premier Biosoft, Palo Alto, CA, USA) using the SYBR Green settings. All qPCR experiments were performed in triplicates; for each primer pair, a negative control with water was included on each plate. Amplifications were performed with 0.02 μg/mL Taq DNA polymerase (Biotools, Madrid, Spain) under the following conditions: initial denaturation at 95°C for 3 min, 50 cycles of denaturing at 95°C for 15 seconds, annealing at 52–63°C for 15 seconds, and extension at 72°C for 30 seconds. Analysis of qPCR data was performed using MyIQ 1.0 or Bio-IQ5 software (Bio-Rad, Solna, Sweden)

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as previously reported [108]. Primer efficiencies were calculated using LinRegPCR [109], and samples were corrected for differences in primer efficiencies. Double delta Ct was calculated and referred to as the relative expression level of each gene in different groups. All primers used were listed in Appendix II.

Carbohydrate assay To evaluate the sugar homeostasis, two circulating and two stored carbohy-drates in Drosophila were measured using a colorimetric method of Liquick Cor-Glucose diagnostic kit (Cormay, Marynin, Poland). At least 6 biological replicates for each group were prepared. For each replicate, 10 mg male (ap-proximately 14 to 16) flies were decapitated and centrifuged in 50 μL PBS solution (pH 7.4) at 5,600 g for 6 min to extract hemolymph. The aqueous layer was transferred to a new tube for measuring circulating glucose and trehalose and the remaining fly bodies were homogenized in 100 μL PBS buffer to extracts stored trehalose and glycogen. Both hemolymph and body samples were deproteinized at 70 °C for 5 min and following with incuba-tion on ice for 5 min. Solutions were then centrifuged at 12,900 g at 4 °C for 15 min. The supernatant was collected and 10 μL of both hemolymph and body supernatant was mixed separately with either 10 μL of 2 μL/mL por-cine kidney trehalase (Sigma-Aldrich, Stockholm, Sweden) to digest treha-lose to glucose. And another 10 μL of body supernatant was mixed with 10 μL of 1 mg/mL amyloglucosidase from Aspergillus niger (Sigma 10115) to digest glycogen to glucose. To measure the circulating glucose, 10 μL of hemolymph supernatant was directly mixed with 8 μL of deionized water. The trehalose samples were incubated at 37 °C and the glycogen samples were incubated at 25 °C overnight. After incubation, 10 μL of sample was diluted in 90 μL of deionized water and mixed with 650 μL of glucose reac-tion mixture (Cormay, Marynin, Poland) in a 96-well plate respectively. Absorbance was measured with a Multiscan GO spectrophotometer (Thermo Scientific) at 500 nm. For producing the standard curve, a serial dilution was made from a 10 μg/μL standard glucose solution. The concentration was calculated according to the produced standard curve.

Lipid measurement This experiment was performed as previously reported [110]. Flies were collected and aged for 5 days. Before the extraction, flies were either starved for 24 hours or normal fed. Thirty flies were transferred to a glass tube and dehydrated in 60°C for 1 hour. Ten replicates were prepared for each group. The body weight was measured. And then, the glass tubes were filled with diethyl ether (Sigma-Aldrich, Stockholm, Sweden) and incubated for 24 hours. The diethyl ether was discarded and the samples were incubated at

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60°C for 1 hour. The body weight was measured again. The lipid content was calculated as the subtraction of the second weighing from the first weighing.

TAG assay At least 5 flies were collected for each biological sample, and 6-8 replicates were prepared for all control and experimental groups. The flies were ho-mogenized in 100 μL of ice-cold PBST (pH=7.2, 0.05% of Tween 20). After 10 min incubation at 70 °C, 20 μL of the homogenized sample was separate-ly added to either 20 μL of PBST for measuring the free glycerol, or 20 μL of triglyceride reagent (Sigma; T2449) for measuring the total glycerol con-tent. All samples were then incubated at 37 °C for 60 min and followed with 3 min at 14,000 rpm. After incubation, 30 μL of each individual sample was transferred to a 96-well plate and mixed with 100 μL of free glycerol reagent (Sigma; F6428). The plate was incubated for 5 min at 37 °C. The absorbance of each sample was measured with Multiscan GO (Thermo Scientific) at 540 nm and calculated according to the standard curve. The standard curve was obtained from a serial dilution glycerol standard (Sigma triolein equivalent glycerol standard; G7793) and was produced along with the samples. The TAG concentration was determined as TAG concentration= total glycerol concentration- free glycerol concentration.

ROS detection In paper II, the reactive oxygen species was monitored by Amplex Red Hy-drogen Peroxide/Peroxidase Assay Kit, according to the instruction provided by the manufacturer (Molecular Probes, A22188). In brief, 6 fly bodies were homogenized in phosphate buffer (pH 7.4) and used as one replicate. The reaction mixture contained 50 μM Amplex Red reagent and 0.1 U/mL horse-radish peroxidase (HRP). The fluorescence was recorded at 530 nm excita-tion/587 nm emission. The results were normalized to Uro-GAL4>w1118 control flies.

Larvae bleeding and hemocytes quantification In paper IV, we tested the effect of BADGE exposure on cell replication. With the advantages of larval hematopoiesis system, the total number of larval hemocytes can reflect the cell proliferative profile. The 3rd instar lar-vae were collected and kept in 1x PBS solution for 5-10 minutes before bleeding. One drop of 1x PBS solution was placed on a glass slide. The larva was clamped at the anterior part with forceps and a needle was used to bleed the larva at the lymph gland. To get enough hemocytes, the larva was squeezed by another forceps. After 30 min, the cells were settled and at-

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tached to slide. For the CSORC larvae, the hemocytes were stained by DAPI for 20 min. For the Hml-GFP>UAS-RasV12 and genetic control cross, the flies were raised at 20 °C in order to inhibit the activity and lethal effect of Ras overexpression. The slides were then mounted and the images were tak-en by the Zeiss Axioplan 2 microscope. The number of hemocytes was counted using ImageJ software.

Confocal imaging In paper IV, the Hml-GFP larvae were used for live imaging and fed on 0, 60, 135, and 200μM BADGE food respectively. The 3rd instar larvae were anesthetized on ice and fixed by a drop transparent nail polish. The slides were immediately imaged using the Zeiss LSM 700 confocal microscope.

Behavioral assays Starvation assay Starvation resistance is a good preliminary parameter to evaluate the meta-bolic profile of Drosophila. To measure the resistance, the Drosophila Ac-tivity Monitoring System (DAMS) from TriKinetics was employed. The F1 progenies were collected after eclosion and aged in a vial containing corre-sponding food to their feeding pattern. After 5-7 days of aging, each individ-ual fly was placed in a 5 mm diameter tube and then monitored in the DAMS slots. The tubes were filled with 1% agarose (~2-3cm height) which provid-ed water and humidity, but not an energy source for the flies during the assay. Then a black cap was placed on the agarose side. Flies were transferred from the opening side and after they were put in the tubes, the opening was blocked with a cotton plug. Each genotype or feeding condition was moni-tored by one slot of 32 flies. As described, the alive/death status of the flies was measured by the beam-crossing numbers [111]. The flies were consid-ered as dead when the activity readouts became consecutive zero. The star-vation resistance was calculated as the average survival time under starva-tion.

Paraquat resistance Flies were collected and raised in a vial containing 8 mL of normal fly food at 25 °C for 5 post-eclosion days and then transferred to a vial containing 1% agarose for 6h starvation in order to eliminate all the remaining food. Para-quat was dissolved in 10% (w/v) sucrose solution at a final concentration of 20 mM. A round filter paper which soaked with paraquat solution was placed in a new agarose vial and 13-15 flies for each replicate were trans-

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ferred to this vial after starvation, and 6-8 biological replicates were pre-pared. To access the resistance to paraquat, the survival rate was recorded 3 times per day until they all died and both of the filter papers and the agarose vials were replaced daily.

Circadian rhythm assay In paper III, all the flies used in the circadian rhythm assay were continuous-ly raised on vials containing the corresponding DBP food after eclosion and aged for 5 days. For performing the circadian assay, the Drosophila Activity Monitoring System (DAMS) was employed. Each individual fly was placed in a capillary tube which was then monitored by the DAMS slot at 25°C, 60% humidity. The capillary tube had, on one end, the same DBP food as the feeding procedure, and on the other end, was blocked by a cotton plug after the fly was put into it. Thirty-two flies for each group were used. When the DAMS slot with the capillary tube was plugged in, the beam breakings of the fly were recorded per minute and referred to as the fly’s activity. For examining the rhythmicity, the flies were allowed to acclimate to the capil-lary overnight and then followed by five constant dark: dark cycles. After the constant dark period, the cycle returned back to 12/12h light:dark to assess if they were able to reset their rhythmicity. For the Pdf-GAL4>UAS-TrpA1 flies, the ambient temperature was 20°C to inhibit TrpA1 activity. Only for the rescue assay, the temperature was set at 30°C between ZT3 and ZT7 to activate TrpA1 channel and eventually trigger the activation of PDF neurons. All data, except the habituation period, were analyzed and plotted by DAM-FileScan and MATLAB based tool kit-S.C.A.M.P.

FlyPAD FlyPAD is the abbreviation of Fly Proboscis and Activity Detector. The assay was adapted from Itskov et al [112]. The male flies from both control and experimental crosses were collected after eclosion and aged for 5 days under the 12/12h light:dark cycle ad libitum at 25°C. The assay was con-ducted from 8 a.m. to 11 a.m in order to limit the influence of normal food intake. Before the experiment was performed, flies were transferred into the flyPAD arena. Each arena included two detective electrodes which had ei-ther a 150 mM sucrose (dissolved in 1% agarose) pellet or was blank. The blank electrode was carefully cleaned before the performance to eliminate any other influencing factors. During 1 hour of monitoring, all the interac-tions between the flies and the food pellet were recorded by Bonsai software. Thirty-two replicates were used for each group. Data were analyzed by using the MATLAB-based GUI (Graphic User Interface) program.

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Statistical analysis Unless otherwise stated, the data analysis and plotting were performed by Prism Graphpad 5. The data were plotted as mean ± SEM. All the significant differences were tested following one-way ANOVA with appropriate post hoc. The significances were represented as *p<0.05, **p<0.01, ***p<0.001 and also specified in the corresponding figure legend.

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Results

Paper I We employed the DAMS to screen how different doses of DEHP affect star-vation resistance. The concentrations we used for raising flies (from 20 to 2 mM) were chosen based on previous reports [113, 114]. Raising flies on 60, 200 and 600 μM DEHP food made them significantly more starvation re-sistant (p<0.001 for all the three groups) while the highest and lowest con-centrations were similar to the normal-fed flies. Then the most effective and relatively low concentration, 200 μM DEHP, was chosen for further experi-mentation. This concentration of DEHP was comparable to the levels found in dairy products [115]. Considering the potentially disruptive effects on the human metabolism of DEHP exposure [116], carbohydrate and lipid levels were analyzed. In ad libitum-fed flies, DEHP exposure significantly de-creased circulating glucose levels by 88% (1.02 ± 0.06 to 0.12 ± 0.01 mM, p<0.001) and decreased circulating trehalose levels by 37% (3.26 ± 0.08 to 2.06 ± 0.16 mM, p<0.001). However, no significant differences in stored carbohydrates were detected. Additionally, that no significance was detected in 24-hr starved flies implied DEHP has no effect on carbohydrate utilization. Thus, DEHP exposure led to a decrease of circulating carbohydrate levels under fed conditions. Lipid content of control and 200 M DEHP flies, before and after starvation, was also measured. In the fed group, 15% more total lipid was found in flies raised on 200 μM DEHP (70 ± 2 μg/fly) compared to control flies (61 ± 3 μg/fly, p=0.031).

The altered circulating carbohydrates and lipid content might result from either/both changing in feeding patterns and daily activity or metabolic dis-ruption. Therefore, food preference, food consumption, general activity and sleep of DEHP fed flies were assessed. No significances were found in any of the above behaviors, which can exclude the possibility of modified feed-ing and activity.

Previous data indicated that Drosophila insulin-like peptides genes (Ilp2, Ilp3 and Ilp5) produced in insulin-producing cells (IPCs) within the brain and adipokinetic hormone (Akh), which functions as glucagon in flies [19, 20, 117-120], act as key regulatory hormones in carbohydrate and lipid ho-meostasis [22, 23, 121, 122]. We examined the expression of these genes, as well as their receptors. According to the expression pattern of these genes, Ilp2, Ilp3, and Ilp5 were tested in fly heads cDNA samples; Ilp6, Akh and

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AkhR were tested in fly body cDNA samples, and InR was tested in both [51][52]. Ilp2 and Ilp3 were not affected while Ilp5 expression was increased by 81% in flies treated with 200 μM DEHP (p<0.001). The Drosophila orthologous protein of the insulin receptor (InR) also increased by 27% (p=0.041) in head and 44% (p=0.035) in body. No changes were observed in Ilp6, Akh and AkhR expression.

Paper II In Drosophila, MRP is highly expressed in the gut and Malpighian tubules and expressed at low levels in the fat body [89]. To study the function of the ABCC transporter MRP in different organs, we crossed UAS-MRP RNAi flies with four tissue-specific drivers, the mid-gut driver (48Y-GAL4), the hind-gut driver (c601-GAL4), the fat body driver (ppl-GAL4) and the Mal-pighian tubules driver (Uro-GAL4), and then performed a starvation assay using 5-7 days old male flies from the F1 generation. None of the 48Y-GAL4, c601-GAL4, and ppl-GAL4 crosses, compared to both of the genetic control flies, exhibited a starvation resistant phenotype. However, knocking down MRP in the Malpighian tubules (Uro-GAL4>UAS-MRP RNAi) significantly increased resistance to starvation when compared to control flies (61.57 hours ± 1.16 vs 56.66 hours ± 0.85, compared to Uro-GAL4>w1118, and 54.90 hours ± 1.47 compared to w1118> UAS-MRP RNAi, p<0.05 and p<0.001 respectively), revealed the important metabolic role of MRP in Malpighian tubules. Thus, we performed carbohydrate and triacylglyceride (TAG) assays with the F1 male flies. The level of circulating sugars and the stored sugars were assessed. None of the circulating glucose, circulating trehalose, stored trehalose or glycogen was notably affected. However, com-paring to both of the control groups (1.23 ± 0.08 mg/mL for Uro-GAL4>w1118 and 0.57 ± 0.08 mg/mL for w1118>UAS-MRP RNAi), the TAG content in the experimental group (2.44 ± 0.29 mg/mL, p<0.05) was significantly elevated and indicated that MRP in Malpighian tubules might be involved in lipid homeostasis. Noteworthy, as most of the presented stud-ies have shown, the abnormal lipid homeostasis was generally associated with deficiency of carbohydrate metabolism, such as obesity and diabetes. On the contrary, we have not noticed any effect on sugar levels in this study. We noticed that Sieber et al reported that the Drosophila homolog (Hr96) of the human pregnane X receptor (PXR), was involved in lipid but not the carbohydrate homeostasis in fruit flies [123]. As one of the phase II enzymes in xenobiotic transportation, PXR had been shown previously to interact with the ABC transporter family [124, 125]. Hr96 expression increased signifi-cantly in the Malpighian tubules MRP knockdown flies (an approximately 1.1-fold increase compared to w1118>UAS-MRP RNAi, p<0.001 and 0.5-fold increase comparing to Uro-GAL4>w1118 group, p<0.05), which could

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be a possible cause of lipid accumulation in the knockdown flies. Other than metabolic and genetic impact, knockdown MRP in Malpighian tubules also influenced the feeding behavior and food intake. Using FlyPAD, we ob-served that MRP knockdown in Malpighian tubules led to a reduction of total food intake, which was represented by the total number of sips (bites) (p < 0.001); interactions with the food pellet, which was represented by ac-tivity bouts (p < 0.01); and the number of meals during the monitoring, which was represented by feeding bursts (p < 0.001), were decreased, indi-cating the robust disruption of feeding behavior caused by insufficient MRP in the Malpighian tubules. Furthermore, MRP transporters are tightly related to oxidative responses and the reduction of oxidative resistance may contrib-ute to imbalanced homeostasis. Therefore, we performed a paraquat re-sistance assay by exposing the flies to paraquat-containing food. Paraquat is a commonly used herbicide that can induce oxidative stress when adminis-trated to flies. The surviving flies were counted and the survival rate was calculated daily; these data reflect how much the flies were resistant to oxi-dative stress. To our surprise, the Uro-GAL4>UAS-MRP RNAi flies showed increased resistance to oxidative stress. The experimental flies survived sig-nificantly longer than both of the control groups (the median survival was 110 hr for Uro-GAL4>w1118 and 68 hr for w1118>UAS-MRP RNAi while the value was 136 hr for Uro-GAL4>UAS-MRP RNAi, and the p-value was less than 0.01 and 0.001 respectively). We then conducted the Reactive Ox-ygen Species (ROS) detection assay. Consistent with the paraquat assay, the Uro-GAL4>UAS-MRP RNAi flies exhibited less ROS production than con-trols. To find out the reason, we examined the genes associated with both MRP and oxidative stress, including ss (spineless, the Drosophila homologue of AhR, aryl hydrocarbon receptor), cnc (cap-n-collar, the Dro-sophila homologue of NRF2, NF-E2-Related factor 2) and Keap1 (Kelch like ECH associated protein 1). The ss expression, but not cnc and Keap1, was remarkably increased in the MRP knockdowns (1.56 ± 0.16 fold change of Uro-GAL4>UAS-MRP RNAi, compared to 1.02 ± 0.07 fold change of Uro-GAL4>w1118 and 0.80 ± 0.05 fold change of w1118>UAS-MRP RNAi), which hinted that oxidative resistance might be the compensatory effects of lacking MRP in Malpighian tubules.

Paper III To gain a better understanding of how the xenobiotic DBP influences biolog-ical systems, we performed whole transcriptome sequencing using wild-type Drosophila raised on food containing 45 nM DBP until the adults were 5-7 days old. By mapping the Drosophila transcriptome to the reference genome obtained from Flybase (build dmel_r5.47_FB2012_05), 15147 transcripts were identified, including expressed genes (mRNA), miRNA, snRNA,

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snoRNA and tRNA and 215 genes were differentially expressed, taking into consideration the 'false discovery rate' and correcting for it using Benjamini-Hochberg correction. After performing pair-wise comparisons between all sequenced conditions, 171 differentially expressed genes remained signifi-cant. Next, using STRING we identified all interacting clusters using the genes. STRING identified 5 clusters of gene networks (Clusters 1a and 1b, 2, 3 and 4). Cluster 1A consisted of genes involved in light sensing and signal-ing, including Rhodopsin receptors (Rh3, Rh4, Rh5, and Rh6), as well as two Arrestins involved in Rhodopsin GPCR recycling (Arr1 and Arr2). Cluster 1b genes involved in the visual transduction process. This included G-proteins (Gaq, Gβ76C, Gγ30A and CG30054), most of which are known to signal downstream of Rhodopsin GPCRs in visual transduction. Cluster 2 contained four genes all involved in the regulation of circadian rhythm, in-cluding vrille (vri), tim, per and Pdf.Since there was no obvious morpholog-ical defect in eyes from males raised on DBP-containing food, we turned our attention to possible effects on circadian rhythm. To verify the genetic im-pacts that we observed in the transcript levels, we first tested the possible effects on circadian rhythm. Diverse concentrations of DBP feeding, as well as normal food, were used and the F1 flies were collected after eclosion. To test DBP effects on circadian rhythm, the DBP-fed adult male flies were first maintained in constant darkness for 72 hours, then switched to a normal 12/12h light:dark cycle for 72 hours. This experimental protocol can evalu-ate both rhythmic maintenance and circadian resetting. In this paper, the average activity of constant dark days was summarized in a 24-hour period to show the circadian pattern. Although, the circadian oscillation of control flies maintained in constant darkness were weakened, males raised on 45 nM, 135 nM or 450 nM DBP were not able to maintain any semblance of normal circadian rhythm when left in constant darkness. Especially, in flies maintained on 135 nM or 450 nM DBP the siesta were missing. Once the flies were switched to a normal 12/12h light:dark cycle, the circadian rhythm of all flies return to normal which indicated that DBP might not influence on the circadian reset. It is well known that the circadian genes oscillate in 24 hours. Our SOLiD hinted the potential circadian disruption by DBP. There-fore, understand how DBP disrupts the circadian rhythm we used quantita-tive RT-PCR (qPCR) to carefully look at the expression levels of the key circadian regulation genes influenced by DBP in our whole transcriptome sequencing. Flies were raised on varying amounts of DBP and collected at different times of the day to see how DBP affected the expression levels of the circadian regulatory genes. Interestingly, DBP had a strong effect on both Pdf and cry at Zeitgeber Time (ZT) 2. Other than ZT2, DBP exposure affected Pdf expression at ZT6 and ZT14 while cry expression was also in-hibited at ZT9. Expression levels of the other three genes tested (tim, per, and vri) were also significantly affected at varying ZT times. tim was upreg-ulated mainly at the late ZT times. At ZT15 and ZT 18, tim expression was

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significantly increased in most DBP concentrations. per expression was strongly influenced at ZT2 and 15. Specifically, per had elevated in 450nM DBP fed flies at ZT2 (p<0.05) and notably diminished at all concentrations at ZT15 (p<0.001). vri was strongly up-regulated at ZT 9 in males raised on food containing 45 nM DBP, but down-regulated in flies raised on higher concentrations of DBP. From these results we conclude that DBP has a strong effect on the expression levels of all circadian regulatory genes tested. Since the DBP exposed flies were able to reset their biological clock, we hypothesize the circadian disruption during the daytime may be resulted from Pdf-related signaling. To understand if DBP exposure disrupted circa-dian rhythm by affecting PDF neurons we expressed a temperature sensitive cation channel TrpA1 specifically in PDF neurons (Pdf-GAL4>UAS-TrpA1) and maintained the flies at 30oC during their siesta to activate the channel. For all crossed strains, flies were fed on either normal food or 135 nM DBP food. Because increasing in ambient temperature would elevate the general activity of flies, the circadian pattern from ZT0 to ZT3 was omitted. Obvi-ously, the average activity of all groups was increased from ZT4. Comparing normal fed and DBP fed control crosses, the circadian pattern was also shown to be influenced by DBP feeding. However, activation of PDF neu-rons during siesta period rescued the circadian arrhythmicity in Pdf-GAL>UAS-TrpA1, DBP fed flies. From these results we conclude that DBP caused circadian disruption may through the inhibition of PDF neurons dur-ing siesta hours. Phthalates have been shown to interact with nuclear hor-mone receptors [126-129] . Intriguingly, two nuclear hormone receptors are known to be involved in the regulation of circadian rhythm in Drosophila, Ecdysone-induced protein 75B (E75B, Human NR1D2) and Hormone recep-tor-like in 38 (Hr38, Human NR4A2). E75B is involved in regulating the expression of the vri gene, while it was reported that Hr38 is involved in a feedback loop that inhibits the expression of Pdf [130, 131]. To understand if DBP could be disrupting circadian rhythm via these two nuclear hormone receptors we first used qPCR to carefully look at the expression levels of Hr38 and E75B in males raised on food containing 135 nM DBP. Interest-ingly, DBP had a strong effect on Hr38 expression at ZT6 and 15, where Hr38 expression was significantly decreased compared to control males, but showed no significant influence on the expression levels of E75B when compared to controls. To understand if DBP exposure disrupted circadian rhythm by interacting with Hr38, we expressed Hr38 RNAi specifically in PDF neurons (Pdf-GAL4>UAS-Hr38 RNAi) and either raised the flies on normal food or food containing 135 nM DBP. Similar to what we observed with CSORC wild-type flies, when raised in constant darkness, unlike nor-mal fed controls, control flies (w1118>Pdf-GAL4 and w1118>UAS-Hr38 RNAi flies) raised on DBP-containing food were not able to maintain a prop-er circadian rhythm which was shown as the failure to anticipate daytime. Not surprisingly, loss of Hr38 in PDF neurons (Pdf-GAL4>UAS-Hr38

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RNAi) was sufficient to disrupt circadian rhythm, even in flies raised on normal food. Interestingly, raising these flies on DBP containing food did not disrupt circadian rhythm further, indicating DBP may be interacting with Hr38, either directly or indirectly, to disrupt circadian rhythm.

Paper IV BADGE is speculated to be mutagenic and teratogenic, but the laboratory and epidemiologic evidence is scarce. The whole mRNA transcriptome was sequenced and analyzed using developmental BADGE fed F1 flies. The 60 μM BADGE of feeding concentration which was used for sequencing was comparable to the human NOAEL (no observed adverse effect level). Sur-prisingly, even the flies fed on the NOAEL level of BADGE caused a mas-sive disruption of the expression of 351 genes. Most of the genes were high-ly correlated to cell proliferation and implied a strong relationship between BADGE and cell cycle regulation. To confirm the adverse effect of BADGE on cell replication, we selectively tested the transcriptional expression of some important cell cycle regulatory genes which were significantly overex-pressed in our transcriptome sequencing, including Cyclin-B (CycB), Cyclin-E (CycE), pan gu (png), giant nuclei (gnu) and string (stg). Flies were fed on three different BADGE dosages, 20 μM, 60 μM, and 200 μM, as well as control food. F1 flies were collected and aged five days before sampling. Consistent with the SOLiD sequencing data, CycB, png, and stg were signif-icantly up-regulated in flies maintained on food containing 200 μM BADGE (approximately 50% increase). CycE was also significantly increased in flies raised on both 60 μM and 200 μM BADGE. However, the expression of two components of the PNG-kinase complex, glu and gnu, was not changed. The inconsistency can result from the different sensitivities and procedures be-tween SOLiD sequencing and qRT-PCR. Furthermore, we tested if BADGE could result in phenotypic increasing of cell replication using larval hemato-poiesis system. In a Drosophila larva, the number of hemocytes is stable throughout different genetic backgrounds and can be easily visualized. We used the laboratory wild-type CSORC flies and fed the larvae on BADGE food. Third instar larvae were then bled on a glass slide and stained by DAPI to visualize the hemocyte nuclei. Compared to control flies, 200 μM BADGE significantly caused a 42% increase in the number of circulating hemocytes. Furthermore, we employed the GAL4-UAS system to modulate hematopoiesis. The Hml-GFP driver, which expresses both GFP and GAL4 in hemocytes, was crossed to UAS-RasV12 strain to overexpress constitutively active Ras GTPase in hemocytes which make the crossed flies more sensi-tive to carcinogens. When exposed to BADGE feeding, the Hml-GFP>UAS-RasV12 flies exhibited cell over-proliferation especially at the relatively lower concentrations (20 μM and 60 μM) with about 60% and 100% of increasing

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respectively. To exclude the possibility that BADGE influenced lymph gland morphology (hematopoietic tissue), we conducted the live imaging with Hml-GFP larvae. Since there is a GFP signal in hemocytes, the blood circu-lation is easily visible under fluorescent microscopy. The larvae used for imaging were raised on 0 μM, 60 μM, 135 μM, and 200 μM BADGE-containing food respectively. The results showed that BADGE did not dam-age the morphological structure of the lymph gland or epidermal hemocyte pools found in each larval segment, which meant hemocyte bands visible in each segment were intact. However, the fluorescent signaling of 135 μM and 200 μM was greater than the control larvae and indicated a potential increase in hemocytes.

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Conclusions and discussions

The main focus in this dissertation is on characterizing the disruptive effects of three xenobiotic chemicals, DEHP, DBP and BADGE. Specifically, after developmental exposure to DEHP, the fruit flies were more resistant to star-vation. This phenotypic evidence indicates the potential defects on the me-tabolism of the flies. In the further investigations, we found decreased levels of circulating sugars as well as increased lipid content. In addition, Ilp5 and InR transcripts were elevated in the DEHP-fed flies. In conclusion, chronic exposure to xenobiotic DEHP induced disturbances in the metabolic profile and the outcomes resembled metabolic syndrome-like dysfunctions. Re-markably, our dosage screening was comparable to previous rodents studies [132-134]. The reduction of circulating glucose and trehalose might result from alterations in insulin signaling. However, no stored sugars were notably affected, suggesting either diminished carbohydrate utilization or excessive carbohydrate storage. In line with this assumption, the total lipid content was increased after DEHP feeding and is consistent with a present study which revealed DEHP exposure induces obesity in mice [135]. Most studies on the function of Ilp5 focused on dietary restriction [21], however, the metabolic role of Ilp5 is not clear. Since we saw up-regulated Ilp5 and InR expression after DEHP feeding, we speculate the changes in these genes may also relate to physiological nutrient balance and should be studied further. Other than DEHP, DBP is one of the most common plasticizer in the indus-trial products. Although it was banned in European countries, residues and metabolites are still present in the environment. According to our transcrip-tome sequencing results, the data from flies raised on DBP food exhibited altered expression on hundreds of genes. Among these genes, the circadian-related transcripts were of interest. The main circadian regulatory genes, Pdf, tim, per, cry and vri, were more or less interfered by DBP in different ZT hours. Also, phenotypic arrhythmicity was observed after DBP diet. Due to these phenotypes, we suggest that the circadian neuropeptide Pdf might play a crucial role in responding to DBP. Further experiments using a thermo-sensitive ion channel to rescue the missed siesta could consolidate the exist-ence of DBP-Pdf interaction. Lastly, we determined the hormone receptor Hr38 expression is also affected by DBP and is necessary for DBP-induced circadian disruption in Drosophila. To our knowledge, this is the first study to show the association between an environmental xenobiotic chemical and

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the circadian rhythm. Strikingly, raising flies at a nano-molar level of DBP is sufficient to cause circadian problems. Since the circadian clock is consid-ered a fundamental physiological process throughout evolutionary back-grounds, the defects observed could generate severe consequences. Addi-tionally, we reported the human homologue of Hr38, known as NR4A2, is important in reacting to DBP uptake. Hr38 have been shown signal to inhibit the transcription of Pdf, and thus inhibit neural activity from the M cells [131]. DBP did not bypass Hr38 to further interfere with circadian behavior in the flies lacking of Hr38 in PDF neurons. This provided indirect evidence for the existence of a Hr38-Pdf-Pdfr pathway and needs more data to be fully understood. A third xenobiotic substrate, BADGE was examined. Surprisingly, BADGE-fed flies showed a trend of excessive cell proliferation both genetically and phenotypically. According to the SOLiD sequencing, 351 genes were affect-ed by BADGE. Within these genes, we noticed one group of cell replication related genes were significantly up-regulated. Using qRT-PCR method, we confirmed the up-regulations of most of these genes. Looking for phenotypic evidence, we employed the larval hematopoiesis system in Drosophila, and found significant increases of hemocytes in the fruit flies with different ge-netic background. Further, the tumorigenic potential of BPA has prompted investigational concerns. Although the clinical correlation between BPA and cancer is not specified, both of in vitro and in vivo studies have discovered the interaction [136, 137]. In accordance with BPA, BADGE can cause A-T base pair mutation in the E. coli tryptophan reverse mutation assay [138] and be genetically toxic in cultured human lymphocytes [139]. In conclusion, we suggest that all these findings demonstrate that BADGE is a possible carcin-ogen. Finally, we attempted to contribute a mechanistic understanding of xenobiot-ics. Noteworthy, the clearance of xenobiotics is one of the most important routes of removing exogenous chemicals. We evaluated the tissue-specific function of MRP, a major xenobiotic transporter, in fruit flies. Knockdown of MRP in Malpighian tubules increased the starvation resistance in wild-type flies and indicated the metabolic deficiency. As a crucial molecule, insufficient MRP in Malpighian tubules also influences lipid homeostasis, which might be a result from the up-regulation of Hr96. In fact, MRP-mediated lipid transportation has already been confirmed [140] and Hr96 has been characterized to control lipid metabolism in Drosophila [123]. As a xenobiotic-sensing receptor, Hr96 is also able to modulate energy utilization and lipid allocation. Hereby, we show that the tissue-specific MRP reduction is strong enough to alter global lipid metabolism. Additionally, we demon-strate that these flies show an increased oxidative resistance. The phenotype might be due to the increase in ss, the human AhR homolog, in the knock-

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down flies. AhR is a transcription receptor which is known to regulate the cytochrome P450 genes and participates in the phase I xenobiotic clearance [87, 141]. Hepatic treatment of AhR inducers caused an increased level of MRP [142, 143]. Therefore, we thought that reduction of phase III trans-porter MRP was likely to cause compensatory expression of phase II trans-porter AhR. Redundant AhR would eventually result in the oxidative re-sistance. In summarize, we demonstrated the tissue-specific function of an important xenobiotic transporter MRP. It was clear that MRP played multi-ple roles in physiological processes and might be a potential drug target in clinical treatments.

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Perspectives

Human exposure to xenobiotics and endocrine disrupting chemicals are im-portant public issues. An estimated 40% to 69% of obesity and diabetes may be related to these chemicals [144]. In reality, individuals are exposed to various xenobiotics actively and passively. They emerge in daily care prod-ucts, medical apparatus, containers and even food and water. More frustrat-ing, scientific research can hardly examine the combined outcomes of toxin mixtures and there is no specific method to evaluate or predict the influences in a long run. That is to say, xenobiotic research is facing two major issues. Firstly, human data is limited and lacking unified parameters. The predomi-nant source of human data comes from epidemiological surveys and clinical samplings. Researchers can only correlate xenobiotic levels to a certain type of disease. However, the mechanism remains obscure. Secondly, even though numerous laboratory animal studies are available, the genetic and anatomic differences will generate problems whenever the conclusion is going to be applied in practice. Therefore, a comprehensive understanding of each single xenobiotic needs greater attention. In paper I, III and IV, we put our efforts in demonstrating the adverse impacts of three commonly used xenobiotics. DEHP appears to be a metabolic disruptor and the endocrinal disruptions has been noticed by a number of present studies. Moreover, the level of DEHP in our environment cannot be neglected. The circadian dis-ruptions induced by DBP and possibly other toxins have yet to be fully elu-cidated. Once the rhythmicity is disrupted, it may consequently disturb other biological processes. And the interaction between nuclear receptors and en-vironmental toxins could be an interesting avenue to investigate further. Also, the less “popular” xenobiotics should be studied, such as BADGE and other substitutes. Finally, we suggest that the tissue-specific manner of ABC transporters may be relevant in clinical therapy. In paper II, tissue-specific knockdown of MRP produced diverse results. Specifically, in Malpighian tubules, lacking MRP lead to deficient homeostasis and feeding behavior. However, it is likely to be positive in reducing reactive oxygen species, which might be beneficial to clinical patients to some extent in the future.

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Acknowledgements

First of all, I would like to thank all the members and students in HelgiLab and the Neuroscience Department. The four years that I studied in the group has been very fantastic and memorable.

Especially, I would like to show my greatest thank to my supervisors, Professor Helgi Schiöth as my main supervisor and Dr. Michael Williams as my co-supervisor. Thank you for your patience and wisdom. I have learned a lot about scientific thinking from the lab meetings and discussions from you during my PhD period.

Also, I would like to thank to my office mates Misty Attwood and Chris-tina Zhukovsky for creating such a wonderful working atmosphere. They always consider the feeling of others.

Thanks to Lyle Wiemerslage for introducing me to a novel field when I just started in the lab. Also, I would like to thank to Giulia Maestri for your cooperation during the first two years of my PhD.

Thanks to Saurabh Patil, Eirini Kotsidou, Kimia Hosseini, Ahmed Mohammed Alsehli, Therese Lindkvist and all the other students that I have not mentioned in the FlyLab and HelgiLab. I can hardly finish my PhD without their help and inspiration.

My gratitude also goes to Xiaoting Zhang, Zhenhua Liu, Chengjun Wu, Weijia Yang, Keqiang Guo, Yanran Zhao and all the other friends out of the lab. Their encouragement and the time we spent together will be invalua-ble memory in my future life.

More importantly, I would like thank to my family very much. My par-ents, Xinchun Cao and Chunming Zhang, gave me the greatest support for the decision I made. A big thanks to my aunts Jinfang Zhang, Jinwen Zhang and my cousin Jiangbo Cao as well. Finally, I would like to thank my beloved wife, Linyu Zhang. I am sure that I can never finish this thesis if you are not standing behind me.

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Appendix I- list of fly strains

Table 1.

Strain name Genotype Strain descrription Used

in paper

Uro-GAL4 w*; P{w[+mC]=Uro-GAL4.T}2 Expresses GAL4 in princi-pal cells of the Malpighian tubules main segement

II

48Y-GAL4 w*; P{w[+mW.hs]=

GawB}48Y Expresses GAL4 in endo-derm

II

c601-GAL4 w*; P{w[+mW.hs]=GawB}c601[c601] Expresses GAL4 in hind-

gut, ureter, and proto-cerebrum

II

ppl-GAL4 w*; P{w[+mC]=ppl-GAL4.P}2 Expresses GAL4 in fat

body under the control of ppl regulatory sequences

II

UAS-MRP RNAi

y1 sc* v1; P{TRiP.HMS01780}attP2 Expresses dsRNA for MRP (FBgn0032456) under UAS control

II

Pdf-GAL4 y1 w*; P{Pdf-GAL4.P2.4}2, y1 w* Expresses GAL4 in LNvs

under Pdf regulatory sequence

III

UAS-TrpA1 P{w[mC] UAS-TrpA} Expresses TrA1 under

UAS control III

UAS-Hr38 RNAi

w*; P{UAS-Hr38.miRNA}attP16/CyO Expresses dsRNA for RNAi of Hr38 (FBgn0014859) under UAS control

III

Hml-GFP w*; P{w[+mC]=Hml-GAL4.Delta}2,

P{w[+mC]=UAS-2xEGFP}AH2w1118

Expresses GAL4 and GFP in lymph glands and circu-lating hemocytes

IV

UAS-RasV12 w*; P{w[+mC]=UAS-Ras85D.V12}2 Expresses Ras85D under

UAS control IV

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49

Appendix II- List of primer sets

Table 2.

Primer name Primer sequences Used in paper Rp49 Forward: 5’- CACACCAAATCTTACAAAATGTGTGA-3’

Reverse: 5’- AATCCGGCCTTGCACATG-3’ I, II, III and IV

Ilp2 Forward: 5’- TCTGCAGTGAAAAGCTCAACG-3’ Reverse: 5’- TCGGCACCGGGCATG-3’

I

Ilp3 Forward: 5’- TGAACCGAACTATCACTCAACA-3’ Reverse: 5’- AGAGAACTTTGGACCCCGTGAA-3’

I

Ilp5 Forward: 5’- GAGGCACCTTGGGCCTATTC-3’ Reverse: 5’- CATGTGGTGAGATTCGGAGCTA-3’

I

InR Forward: 5’- CCAAGAAGTTCGTCCATC-3’ Reverse: 5’- TCATTCCAAAGTCACCAA-3’

I

Akh Forward: 5’- TAGTGCTGTGTTAATTAC-3’ Reverse: 5’- TTCATTCTGAGTTCTATG-3’

I

AkhR Forward: 5’- AGGAGCGACTTTGATGAG-3’ Reverse: 5’- TCCGTAGCAGTAGATGAA-3’

I

Hr96 Forward: 5’-GATATGTTCCTCCAGGCCCTA-3’ Reverse: 5’- TGTGCGTGGCAAAGAAGACT-3’

II

Cnc Forward: 5’-CTGCATCGTCATGTCTTCCAGT-3’ Reverse: 5’-AGCAAGTAGACGGAGCCAT-3’

II

Keap1 Forward: 5’- AGGCCAATGTGTTTATTGAGCG-3’ Reverse: 5’- GCAATCAACTGATATGCCGAAAG-3’

II

ss Forward: 5’- GATATGTTCCTCCAGGCCCTA-3’ Reverse: 5’- TGTGCGTGGCAAAGAAGACT-3’

II

Pdf Forward: 5’- GCCACTCTCTGTCGCTATCC-3’ Reverse: 5’- CAGTGGTGGGTCGTCCTAAT-3’

III

tim Forward: 5’- CCAATGGACAAAAAGGAGCTTAGA-3’ Reverse: 5’- GTAACCCTTGAGGAGGAAATCCAC-3’

III

per Forward: 5’- CCAGATTCCCGAACGTCCGT-3’ Reverse: 5’- GCAGGAGTGGTGACCGAGTG-3’

III

vri Forward: 5’- ATGAACAACGTCCGGCTATC-3’ Reverse: 5’- CTGCGGACTTATGGATCCTC-3’

III

cry Forward: 5’- CCACCGCTGACCTACCAAAT-3’ Reverse: 5’- GGTGGCGTCTTCTAGTCGAG-3’

III

Hr38 Forward: 5’- GCAGCGGACAACTTCTACG-3’ Reverse: 5’- ACCGAAGGGGAGGAGACTG-3’

III

Eip75b Forward: 5’- CACCCAGGACGATAAGTTCAC-3’ Reverse: 5’- ACGAGTCAAACATGCAGATCAG-3’

III

cycB Forward: 5’-GTGAACGAGCCCACCTTAAAG -3’ Reverse: 5’-GAAACTCCCATCACGGGTTTG -3’

IV

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50

cycE Forward: 5’-AGCCTCCATCAGCTAAGCG -3’ Reverse: 5’-GCAACCGATGACAGATTGCC -3’

IV

stg Forward: 5’-CAGCAGTTCGAGTAGCATCAA -3’ Reverse: 5’-CTCCCATAGCTGGCAGAATTTT -3’

IV

png Forward: 5’-GCCAGGGCAAGGTGGATTT -3’ Reverse: 5’-CCACACGGGATCGTAGAGAC -3’

IV

gnu Forward: 5’-TAAATGGGGAGACCAGGCTAC -3’ Reverse: 5’-CGCACTTTTCAACTTGGATTCCT -3’

IV

plu Forward: 5’-GGAATACCGCCCTATTGAAGG -3’ Reverse: 5’-ATCTTCGCCTCAACAGTTCCT -3’

IV

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Acta Universitatis UpsaliensisDigital Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Medicine 1481

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