Fawaz Alasmari Dissertation Final.Pdf

A Dissertation

entitled

Chronic Exposure to Electronic Cigarette Vapor-Containing Nicotine and Co-Exposure to Alcohol and Nicotine: Effects on Glial Glutamate Transporters, Nicotinic Receptors and Neurotransmitters by

Fawaz Alasmari

Submitted to the Graduate Faculty as partial fulfillment of the requirements for the

Doctor of Philosophy Degree in

Experimental Therapeutics

______Dr. Youssef Sari, Committee Chair

______Dr. F. Scott Hall, Committee Member

______Dr. Isaac T. Schiefer, Committee Member

______Dr. Amit K. Tiwari, Committee Member

______Dr. Amanda Bryant-Friedrich, Dean College of Graduate Studies

The University of Toledo

May 2018

This document is copyrighted material. Under copyright law, no parts of this document may be reproduced without the expressed permission of the author.

An Abstract of

Chronic Exposure to Electronic Cigarette Vapor-Containing Nicotine and Co-Exposure to Alcohol and Nicotine: Effects on Glial Glutamate Transporters, Nicotinic Receptors and Neurotransmitters

Fawaz Alasmari

Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Doctor of Philosophy Degree in Experimental Therapeutics

The University of Toledo May 2018

Impairments in glutamatergic and dopaminergic systems have been suggested to mediate the development of drug dependence, including dependence to nicotine (NIC) and ethanol (EtOH). Several studies reported that chronic exposure to drugs of abuse decreased the expression of glutamate transporter-1 (GLT-1) as well as cystine/glutamate antiporter (xCT) but not glutamate/aspartate co-transporter (GLAST), which consequently increased extracellular glutamate concentrations in mesocorticolimbic brain regions. In the present studies, for the first time, we investigated the effects of chronic exposure to electronic (e)-cigarette vapor containing NIC, for one hour daily for three or six months, on GLT-1, xCT and GLAST expression in frontal cortex (FC), striatum (STR) and hippocampus (HIP) in mice. In these studies, we also investigated the effects of e-cigarettes on the expression of alpha-7 and alpha-4/beta2 nicotinic acetylcholine receptors (α-7 nAChR and α4/β2 nAChR), major pre-synaptic nicotinic receptors on the glutamatergic and dopaminergic terminals, respectively, which regulate glutamate and dopamine release. High Performance Liquid Chromatography (HPLC) was used to detect the concentrations of neurotransmitters in the FC and STR of mice exposed to e- cigarette vapor for six months. In these studies, we found that chronic exposure to e- cigarette vapor-containing NIC upregulated α-7 nAChR and α4/β2 nAChR in the FC, STR and HIP. However, the expression of α-7 nAChR in the HIP was not changed after three or six month’s inhalation of e-cigarette vapors. Additionally, e-cigarette vapors inhalation for three or six months induced downregulation on GLT-1 in the STR and xCT iii

in the STR and HIP. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) techniques detected concentrations of NIC and cotinine, a major metabolite of NIC, in central brain regions involved in drug reward and reinforcement. Alternatively, we found that STR dopamine tissue content was decreased in mice exposed to e-cigarette vapors for six months. The concentrations of glutamate in the STR and glutamine in the FC and STR were increased following six-month inhalation of e-cigarette vapor-containing NIC. GABA concentration was decreased in the FC of mice exposed to e-cigarette vapors. The obtained data provide novel evidence about the effects of chronic NIC inhalation on the expression of key astroglial glutamate transporters and nAChRs as well as the levels of neurotransmitters. Moreover, co-use of EtOH and tobacco cigarettes is common in United States and finding therapeutic compounds for the treatment of EtOH and NIC co- dependence is critical. Thus, the effects of co-exposure of NIC and EtOH on the expression of astroglial glutamate transporters and metabotropic glutamate receptor-1 (mGluR1) were determined in central brain regions involved in drug reward and reinforcement. We found that binge intake of EtOH increased the expression of mGluR1 in the nucleus accumbens (NAc) and did not affect the expression of astroglial glutamate transporters. However, NIC drinking reduced the expression of GLT-1 in the NAc and xCT in the NAc and HIP. Moreover, NIC drinking for four weeks upregulated on mGluR1 in the NAc. Co-exposure to NIC and EtOH reduced the expression of GLT-1 and xCT and increased the expression of mGluR1 in the NAc. Our results indicate that NIC and EtOH co-dependence might induce alterations in the glutamatergic systems through different pathways.

My dissertation is dedicated to my parents, Abu-Zuhair and Um-Zuhair, who have been praying for me, supporting me, thinking about me, and guiding me all the time since I was born.

Acknowledgements

I would like to thank God for giving me the ability and strength to achieve my goals. I would like to gratefully thank my advisor Dr. Youssef Sari for his help. Dr. Sari encourages me to work hard and publish my articles in high impact journals. Without Dr.

Sari’s guidance; I would not finish my PhD in optimal duration and quality. Thank you so much, Dr. Sari, for being a great help throughout my master and PhD studies. Dr. Sari has trained me very well to publish different type of articles (Research article, Short communication, Review article and Mini-review article) as a first author. I thank the committee members Dr. Scott Hall, Dr. Isaac Schiefer and Dr. Amit Tiwari for their advice, time, and critiques to improve the quality of my research. I thank Dr. Zahoor

Shah for being my graduate representative. I thank Dr. Richard Bell, Dr. Laura

Alexander, Dr. Isaac Schiefer, Dr. Salim Al-Rejaie, Dr. Shakir Alsharrari, Jessica Nelson,

Austin Horton, Dr. Shantanu Rao, Dr. Alaa Hammad and Sunil Goodwani for the great contribution. I thank Alqassem Hakami, Fahad Alshehri and Hasan Alhaddad for the support. Thanks to my friends, Abdulkareem Alanezi, Abdullah Alasmari, Qassem

Alhadidi, Ali Zarban, Rami alzhrani, Omer Fantoukh, and others for the support. I thank

King Saud University for the financial support. I extremely thank my parents, brothers and sisters for their support and encouragement. My parents pray without ceasing for me for my entire life including my studies. Thanks to my father, who is the leader that has inspired me and has impacted my life. I wish I can follow his steps in my remaining life.

Table of Contents

Abstract ...... iii

Acknowledgements ...... vi

Table of Contents ...... vii

List of Tables ...... xvi

List of Figures ...... xvii

List of Abbreviations ...... xxi

List of Symbols ...... xxiii

1 Overall Introduction……………...... 1

Introduction: Part I: Targeting Glutamate Homeostasis for Potential Treatment of

Nicotine Dependence……………..………………………………………………7

1.1 Role of nicotinic acetylcholine receptors in the modulation of glutamate

release……………………………………………………………………………13

1.2 Role of glutamate transporters in nicotine dependence ...... 15

1.3 Role of glutamate receptors in nicotine dependence ...... 18

Introduction: Part II: A Computerized Exposure System for Animal Models to

Optimize Nicotine Delivery into the Brain Through Inhalation of Electronic

Cigarette Vapors or Cigarette Smoke……………………………………………35

1.4 Comparisons of nicotine inhalation to other delivery routes ………………..39

1.5 Pharmacokinetic of nicotine inhalation compared to other routes of nicotine

exposure………………………………………………………………………….41 vii

1.6 Benefits of a computerized inhalation exposure system as a nicotine delivery method……………………………………………………………………………43

1.7 Comparisons of computerized inhalation (SciReq) system to other inhalation systems; validity and limitations………………………………………………....44

1.8 Comparisons of computerized inhalation (SciReq) system to other inhalation systems; system characteristics and exposure parameters……………………….47

Introduction: Part III: Role of glutamatergic system and mesocorticolimbic circuits in alcohol dependence…………...………………………………………60

1.9 Alcohol and Glutamate Receptors…………………………………………...65

1.10 Alcohol and Glutamate Transporters…………………………….…………69

1.11 Nucleus Accumbens (NAc)………………………………………………...71

1.11.1 Role of the glutamate receptors in the NAc in alcohol

dependence…………………………………………………………….…73

1.11.2 Role of the glutamate transporters in the NAc in alcohol

dependence…………………………………………………………….....77

1.12 Prefrontal Cortex (PFC)………………………………………………...... 79

1.12.1 Role of the glutamate receptors in the PFC in alcohol

dependence …………………………………………………………...…81

1.12.2 Role of the glutamate transporters in the PFC in alcohol

dependence…………………………………………………………….....82

1.13 Striatum…………………………………..…………………………….…...84

1.13.1 Role of the glutamate receptors in the striatum in alcohol

dependence ……………………………………………………………...85

viii

1.13.2 Role of the glutamate transporters in the striatum in alcohol

dependence……………………………………………………………... 86

1.14 Amygdala…………………………………………………………………...87

1.14.1Role of the glutamate receptors in the amygdala in alcohol

dependence……………………………………………………………….88

1.14.2 Role of the glutamate transporters in the amygdala in alcohol

dependence………………………………………………………………89

1.15 Hippocampus………………………………………………..……………...90

1.15.1 Role of the glutamate receptors in the hippocampus in alcohol

dependence…………………………………………………………….…91

1.15.2 Role of the glutamate transporters in the hippocampus in alcohol

dependence...... 93

1.16 Ventral Tegmental Area (VTA)…………………………………………....93

1.16.1 Role of the glutamate receptors in the VTA in alcohol

dependence…………………………………………………………….…95

1.16.2 Role of the glutamate transporters in the VTA in alcohol

dependence……………………………………………………………….96

1.17 Human Studies…………………………………………………….………..96

2 Chronic exposure to electronic cigarettes vapor-containing nicotine modulates nicotinic acetylcholine receptors and glial glutamate transporters in mesocorticolimbic brain regions of C57BL/6J mice ...... 127

2.1 Introduction………………………………………………………….….…..129

2.2 Materials and Methods…………………………………….……….……….132

2.2.1 E-cigarettes………………………………………………..……...132

2.2.2 Mouse inhalation of e-cigarette vapor……………………………132

2.2.3 Brain Tissue Harvesting…………………………………….…….133

2.2.4 Quantitative PCR (qPCR) assay for detection of GLT-1, and xCT

mRNA expression………………………………………………………133

2.2.5 Western blot assay for detection of α-4 nAChR, β-2 nAChR, α-7 nAChR,

GLT-1,GLT-1a, GLT-1b and xCT protein expression………………...………135

2.2.6 Ultra performance liquid chromatography- tandem mass spectrometry

(UPLC-MS/MS) for quantification of cotinine in the FC and STR …...……….136

2-2-7 Statistical Analyses…………………………………………...………….138 2.3 Results………………………………………………………….………...…139

2.3.1 Effects of exposure to e-cigarettes vapors on protein expression of α-4 nAChR in the FC, STR and HIP………………………………………………..139

2.3.2 Effects of exposure to e-cigarettes vapors on protein expression of β-2 nAChR in the FC, STR and HIP………………………………………...……...140

2.3.3 Effects of exposure to e-cigarettes vapors on protein expression of α-7 nAChR in the FC, STR and HIP………………………………………..………141

2.3.4 Effects of exposure to e-cigarettes vapors on mRNA and protein expression of GLT-1 in the FC, STR and HIP………………………………………….…..142

2.3.5 Effects of exposure to e-cigarettes vapors on protein expression of GLT-1 isoforms in the FC, STR and HIP………………………………………………143

2.3.6 Effects of exposure to e-cigarettes vapors on mRNA and protein expression of xCT in the FC, STR and HIP………….……………………………………..145

2.3.7 Determination of cotinine concentrations in the FC and STR……….…...146

2.4 Discussion………………………….………………………………….……147

2.5 Conclusion……………………………………………………...…………..150

3 Effects of chronic inhalation of electronic cigarettes containing nicotine on glial glutamate transporters and α-7 nicotinic acetylcholine receptor in female CD-1 mice...157

3.1 Introduction……………………………………………………………..….159

3.2 Materials and Methods…………………………………………….……….163

3.2.1 E-cigarettes………………………………………………..……...163

3.2.2 Mouse inhalation of e-cigarette vapor……………………………163

3.2.3 Brain Tissue Harvesting………………………………………….164

3.2.5 Western blot protocol for detection of α-7 nAChR, GLT-1, xCT and

GLAST …………………………………………………………………165

3.2.6 Quantitation of Cotinine via ultra-performance liquid

chromatography- tandem mass spectrometry (UPLC-MS/MS)…… … 166

3.2.7 Statistical Analyses………………………………….……..….….168 3.3 Results…………………………………………………………………....…168

3.3.1 Effects of e-cigarettes on α-7 nAChR expression in the FC, STR and

HIP…………………………………………………...…………………168

3.3.2 Effects of e-cigarettes on GLT-1 expression in the FC, STR and

HIP…………………………………………………………………..….169

3.3.3 Effects of e-cigarettes on xCT expression in the FC, STR and

HIP…………………………………………………………….………..170

3.3.4 Effects of e-cigarettes on GLAST expression in the FC, STR and

HIP………………………………………………………………...……171

3.3.5 Determination of nicotine and cotinine concentrations in the FC, and

cotinine in the plasma…………………………………………………..172

3.4 Dicussion…………………………………………...………….……………174

3.5 Conclusion………………………………………………………………….179

4 Effects of chronic inhalation of electronic cigarette vapor containing nicotine on

neurotransmitters in the frontal cortex and striatum of C57BL/6

mice………………………………………………………………...…………...189

4.6 Introduction………………………………………………………...…….…191

4.7 Materials and Methods…………………………..………..……….…….….193

4.7.1 E-cigarettes………………………………………………..……...193

4.7.2 Mouse inhalation of e-cigarette vapor……………………………194

4.7.3 Brain Tissue Harvesting…………………………….…………….195

4.7.4 High performance liquid chromatography (HPLC) with

electrochemical detection (EC)…………………………………………195

4.7.5 Statistical Analyses………………………………………….……196

4.8 Results……………………………………………………….…………...…197

4.8.1 Chronic inhalation of E-cigarette vapor decreased dopamine in the

STR………………………………………………………………..……197

4.8. 2 Chronic E-cigarette vapor exposure does not alter serotonin

concentrations in the FC or STR ……………...…………………..…....198

xii

4.8.3 Chronic inhalation of E-cigarette vapor for six-months increased

glutamate concentrations in the STR ……………………….……...…..199

4.8.4 Chronic nicotine-containing E-cigarette vapor inhalation increased

glutamine concentrations in the FC and STR …………………….……200

4.8.5 Inhalation of E-cigarette vapor for six-months decreased GABA in

the FC………………………………………….………………………..201

4.9 Dicussion…………………………………………...………………………202

4.10 Conclusion…………..…………………………………………………….205

5 Peri-adolescent drinking of ethanol with or without nicotine modulates glial glutamate transporters and metabotropic glutamate receptor-1 in female alcohol- preferring rats……………………………….………………………………….……….215

5.1 Introduction………………………………………………..………….…….217

5.2 Materials and Methods……………………………………...……………....220

5.2.1 Animals and drinking protocol………………..………………….220

5.2.2 Brain harvesting…………………………………….………….....222

5.2.3 Western Blot analyses……………………………………….……222

5.2.4 Glutathione peroxidase (GPx) activity…………………………...224

5.2.5 Statistical analyses………………………………………………..225

5.2.5.1 Drinking solution data……………………………….….225

5.2.5.1 Western Blot and glutathione peroxidase (GPx) data…..225

5-3 Results…………………………………………………………………...…226

5.3.1 Average intake of SUC, SUC-NIC, EtOH, or EtOH-NIC....……..226

xiii

5.3.2 Effects of binge-like drinking of SUC or SUC-NIC on GLT-1, xCT,

GLAST and mGluR1 expression in the NAc ………………………….227

5.3.3 Effects of binge-like drinking of EtOH or EtOH-NIC on GLT-1,

xCT, GLAST and mGluR1 expression in the NAc ……………..……..228

5.3.4 Effects of binge-like drinking of SUC or SUC-NIC on GLT-1, xCT,

GLAST and mGluR1 expression in the HIP …...………………...…….229

5.3.5 Effects of binge-like drinking of EtOH or EtOH-NIC on GLT-1,

xCT, GLAST and mGluR1 expression in the HIP ………...……..……231

5.3.6 Effects of binge-like drinking of SUC or SUC-NIC on GLT-1, xCT,

GLAST and mGluR1 expression in the HIP……………………………232

5.3.7 Effects of binge-like drinking of EtOH or EtOH-NIC on GLT-1,

xCT, GLAST and mGluR1 expression in the PFC……………………..233

5.3.8 Effects of SUC, SUC-NIC, EtOH, or EtOH-NIC drinking on GPx

activity in the HIP………………………………………………………235

5.4 Discussion………………………………………………………………..…235

6 Summary……………………………………………………………………..…251

6.1 Experimental Design……………………………………………………..…251

6.2 Outcomes…………………………………..……………………………….254 6.2.1 The effects of chronic exposure to e-cigarette vapors-containing

nicotine on nAChRs in the FC, STR and HIP…….……………………254

6.2.2 The effects of chronic exposure to e-cigarette vapors-containing

nicotine on glial glutamate transporters in the FC, STR and HIP…..….255

xiv

6.2.3 The effects of chronic exposure to e-cigarette vapors-containing

nicotine on the levels of neurotransmitters in the FC and STR………...256

6.2.4 The effects of chronic exposure to SUC, SUC-NIC, EtOH and

EtOH-NIC on glial glutamate transporters, mGluR1 and GPx in the NAc,

HIP and PFC……………………………………………………………257

References…………………………………………………...………………………….259

Appendix A…………………………………………………………………………..…262

List of Tables

2-1 Table shows primer sequence for each gene in mice animal model...... ………134

6-1 The effects of chronic exposure to e-cigarette vapors-containing nicotine on the

expression of nicotinic receptors and glial glutamate transporters in the FC, STR

and HIP………..………………………………………………………………..255

6-2 The effects of chronic exposure to SUC, SUC-NIC, EtOH, and EtOH-NIC on

glial glutamate transporters, mGluR1 and GPx in the NAc, HIP and PFC….…258

xvi

List of Figures

1-1 Schematic diagram shows the effect of nicotine on presynaptic α7-nAChRs in

glutamatergic terminals in the PFC...... 12

1-2 Schematic diagram shows the effect of nicotine on glutamatergic system.

Nicotine binds to nAChRs located at the glutamatergic terminal and elevates

extracellular glutamate concentration...... 18

1-3 Inhalation exposure system composes of six major components...... …50

1-4 Schematic diagram shows glutamatergic, dopaminergic and GABAergic

pathways involved in alcohol dependence in mesocorticolimbic areas...... 73

1-5 Schematic diagram shows the effects of alcohol on glutamatergic system ...... 79

1-6 Schematic diagram shows the effect of β-lactam antibiotics on major signaling

pathways involved in stimulation of glutamate transporter-1 (GLT-1) gene

expression ...... 83

1-7 Schematic diagram shows the effect of β-lactam antibiotics on cystine/glutamate

antiporter (xCT) expression as well as intracellular glutathione (GSH) content in

astrocyte ...... 84

2-1 Effects of three month inhalation of e-cigarette vapor containing nicotine on α-4

nAChR protein expression in the FC, STR and HIP ...... 139

2-2 Effects of three month inhalation of e-cigarette vapor containing nicotine on β-2

nAChR protein expression in the FC, STR and HIP ...... 140 xvii

2-3 Effects of three month inhalation of e-cigarette vapor containing nicotine on α-7

nAChR protein expression in the FC, STR and HIP ...... 141

2-4 Effects of three month inhalation of e-cigarette vapor containing nicotine on

GLT-1 mRNA and protein expression in the FC, STR and HIP ...... 143

2-51 Effects of three month inhalation of e-cigarette vapor containing nicotine on

GLT-1 isoforms protein expression in the FC, STR and HIP...... 144

2-6 Effects of three month inhalation of e-cigarette vapor containing nicotine on xCT

mRNA and protein expression in the FC, STR and HIP ...... 146

2-7 LC-MS/MS analysis of cotinine in the FC and STR tissue samples ...... 147

3-1 Effects of six months exposure to e-cigarette vapor (e-Cig) containing nicotine on

the relative (R) α-7 nAChR expression in the FC, STR and HIP in female CD-1

mice ...... 169

3-2 Effects of six months exposure to e-cigarette vapor (e-Cig) containing nicotine on

the relative (R) GLT-1 expression in the FC, STR and HIP in female CD-1

mice...... 170

3-3 Effects of six months exposure to e-cigarette vapor (e-Cig) containing nicotine on

the relative (R) xCT expression in the FC, STR and HIP in female CD-1

mice…… ...... 171

3-4 Effects of six months exposure to e-cigarette vapor (e-Cig) containing nicotine on

the relative (R) GLAST expression in the FC, STR and HIP in female CD-1

mice………………………………………………………….………………….172

xviii

3-5 LC-MS/MS was used to quantify levels of nicotine and cotinine based on the ratio

of the area under the curve of the MRM transitions for each analyte and a

corresponding isotope labeled internal standard (cotinine-d3 and nicotine-d4) ...173

4-1 Effects of six-month inhalation of e-cigarette vapor (E-Cig) containing nicotine

on dopamine concentrations in the FC and STR in male C57BL/6 mice ...... 197

4-2 Effects of six-month inhalation of e-cigarette vapor (E-Cig) containing nicotine

on serotonin concentrations in the FC and STR in male C57BL/6 mice ...... 198

4-3 Effects of six-month inhalation of e-cigarette vapor (E-Cig) containing nicotine

on glutamate concentrations in the FC and STR in male C57BL/6 mice ...... 199

4-4 Effects of six-month inhalation of e-cigarette vapor (E-Cig) containing nicotine

on glutamine concentrations in the FC and STR in male C57BL/6 mice ...... 200

4-5 Effects of six-month inhalation of e-cigarette vapor (E-Cig) containing nicotine

on GABA concentrations in the FC and STR in male C57BL/6 mice ...... 201

4-6 Schematic diagram summarizes the effects of inhalation of E-cigarette vapor-

containing nicotine for six months on the concentrations of neurotransmitters in

the FC and STR…………………………………………………………………206

5-1 Average last five sessions binge-like drinking of SUC, EtOH and NIC ...……..226

5-2 Effects of binge-like drinking of SUC and SUC-NIC on relative expression (R) of

GLT-1, xCT, GLAST, and mGluR1 in the NAc ...... 227

5-3 Effects of binge-like drinking of EtOH and EtOH-NIC on relative expression (R)

of GLT-1, xCT, GLAST, and mGluR1 in the NAc ...... 229

5-4 Effects of binge-like drinking of SUC and SUC-NIC on relative expression (R) of

GLT-1, xCT, GLAST, and mGluR1 in the HIP ...... 230

xix

5-5 Effects of binge-like drinking of EtOH and EtOH-NIC on relative expression (R)

of GLT-1, xCT, GLAST and mGluR1 in the HIP ...... 232

5-6 Effects of binge-like drinking of SUC and SUC-NIC on relative expression (R)

of GLT-1, xCT, GLAST, and mGluR1 in the PFC ...... 233

5-7 Effects of binge-like drinking of EtOH and EtOH-NIC on relative expression (R)

of GLT-1, xCT, GLAST, and mGluR1 in the PFC ...... 234

5-8 Effects of binge-like drinking of SUC, SUC-NIC EtOH, or EtOH-NIC on the

activity of GPx in the HIP (100% of water control group)...... 235

6-1 Experimental timeline for A) Three-month e-cigarette exposure paradigm. B)

Six-month e-cigarette exposure paradigm. C) Four-week EtOH and NIC co-

consumption paradigm………………...………………………………………..252

6-2 FC, STR and HIP express α7 nAChR and α4/β2 nAChR. B) The effects of

chronic exposure to e-cigarette vapors-containing nicotine on the expression of α7

nAChR and α4/β2 nAChR in the FC, STR and HIP………………………...….254

6-3 The effects of chronic exposure to e-cigarette vapors-containing nicotine on the

levels of neurotransmitters in the FC and STR……………………………...….256

List of Abbreviations

AC………….………. Air control alphaPKC …….……..Alpha protein kinase C AMPA……………….α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid ACC…………………Anterior cingulate cortex

DA…………………...Dopamine

CNS……………….... Central nervous system CPP…………...……..Conditional place preference

EAAT3……………....Glutamate transporter 3 e-cigarette………….. .Electronic cigarette ECN………………… E-cigarettes-containing nicotine ECV………………… E-cigarette vehicle control EtOH………………...Ethanol

FC……………………Frontal cortex

GABA………………. Gamma-Aminobutyric acid GLAST…………...... Glutamate/aspartate transporter GLT-1………………..Glutamate transporter-1 GSH…………...... Glutathione

HIP………………...…Hippocampus iGLURs……………....Ionotropic glutamate receptors mGluRs……………...Metabotropic glutamate receptors MS-153……………...(R)-(−)-5-methyl-1-nicotinoyl-2-pyrazoline MSN………………....Medium spiny neuron

NAc ...... Nucleus accumbens nAChRs ……….…….Nicotinic acetylcholine receptors NF-Κb…………….....Nuclear factor-kappa B NIC…………………..Nicotine NMDA…………….....N-methyl-D-aspartate

xxi

OFC…………………..Orbitofrontal cortex

P……………………...Alcohol-preferring pAKT………………...Phosphorylated-AKT PFC ...... Prefrontal cortex PI3K………………….Phosphatidylinositol-3-kinase

STR…………………..Striatum SUC…………………..Sucrose

VTA ...... Ventral tegmental area xCT…………………...Cystine/glutamate exchanger

xxii

List of Symbols

α ...... alpha β ...... beta n...... number of subjects

xxiii

Chapter 1

Overall Introduction

Recent evidence reports that electronic (e) cigarette use has increased significantly in

United States (U.S.) and other countries (McMillen et al., 2014, Schoenborn and Gindi,

2015). Although e-cigarette devices deliver only nicotine (NIC) without toxic constituents of conventional tobacco cigarettes (Margham et al., 2016), many toxicological effects have been found in animals exposed to e-cigarettes (Vardavas et al.,

2012, Hwang et al., 2016, Canistro et al., 2017). In addition, high e-cigarette dependence rate has been recently found in young and adults (Foulds et al., 2014, Etter and

Eissenberg, 2015). For instance, withdrawal symptoms as well as high desire to smoke e- cigarettes were reported with e-cigarette use (Dawkins et al., 2012). Thus, finding molecular pathways that are involved in the development of e-cigarette dependence is critical. Targeting these pathways might be an effective pharmacotherapy strategy to attenuate dependence to e-cigarettes.

Importantly, studies suggested that NIC dependence might be developed through alterations in neurotransmitters systems, including dopaminergic and glutamatergic systems (Knackstedt et al., 2009b, Okita et al., 2016). Other studies found that exposure 1

to NIC upregulated nicotinic acetylcholine receptors (nAChRs) and these receptors are localized on dopaminergic, glutamatergic and GABAergic neurons (Alsharari et al.,

2015, Alasmari et al., 2017b). It is important to note that nAChRs regulate the release of neurotransmitters from pre-synaptic neurons. For example, NIC increases glutamate and dopamine neurotransmission in part through activation of pre-synaptic nAChRs (Tizabi et al., 2002b, Tizabi et al., 2007, Konradsson‐Geuken et al., 2009). Moreover, NIC has been found to reduce the uptake of glutamate in the mescorticolimbic system (Knackstedt et al., 2009b). These studies delivered NIC through intraperitoneal or intracerebral administration. Since little is known about the effects of e-cigarettes on neurotransmitters systems, the present studies investigated the effects of chronic exposure to e-cigarette vapors on the expression of nAChRs and astroglial glutamate transporters as well as the tissue contents of neurotransmitters in central brain regions involved in drug reward and reinforcement.

Alternatively, it has been reported that more than thirty percent of the population in the U.S. consume tobacco and more than sixty percent of individuals consume ethanol

(EtOH) (Falk et al., 2006). In addition, the latter epidemiological study reported that around twenty seven percent of population in U.S. has been found to use both tobacco and EtOH. Importantly, EtOH consumers are more likely to smoke tobacco. In addition,

EtOH drinking has been found to increase tobacco consumption, while tobacco products use has a critical role in augmentation of EtOH intake (Bobo and Husten, 2000, Grant et al., 2004b, Falk et al., 2006). Several pre-clinical studies demonstrated the effects of NIC on EtOH seeking in animals exposed to EtOH. Pharmacologically, EtOH and NIC 2

stimulates glutamate and dopamine release in mesocorticolimbic brain regions (Tizabi et al., 2002b, Tizabi et al., 2007, Das et al., 2015). It has been suggested that glutamate transport is altered in animals exposed to both EtOH and NIC (Saellstroem Baum et al.,

2006b, Deehan et al., 2015, Hakami et al., 2016b). Glutamatergic projections in different parts of the mesocorticolimbic system have been shown to be involved in drug dependence. For instance, glutamatergic inputs from the PFC and HIP to the NAc have been found to be involved in drug seeking [For review see (Kalivas and Volkow, 2005)].

In addition, the PFC sends and receives glutamatergic inputs from the HIP, which might have a critical role in drug dependence (Hyman et al., 1987, Gigg et al., 1994, Parent et al., 2010a). Thus, studies are warranted to explore molecular mechanisms in glutamatergic systems for the treatment of EtOH and NIC co-dependence.

Studies have found that chronic exposure to EtOH or NIC reduces the expression of GLT-1 and xCT in the NAc (Knackstedt et al., 2009, Das et al., 2015). However, less is known about the effects of EtOH and NIC co-exposure on GLT-1 and xCT expression.

Thus, in the present study, for the first time, we investigated the effects of binge-like intake of EtOH-NIC on the astroglial glutamate transporters in the NAc, PFC and HIP.

Additionally, metabotropic glutamate receptor-1 (mGluR1) has been found to regulate

EtOH intake in animals in a limited access paradigm (Lum et al., 2014). Thus, we here investigated the effects of binge intake of EtOH-NIC on mGluR1 in the NAc, PFC and

HIP.

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Introduction: Part I

Targeting Glutamate Homeostasis for Potential Treatment of Nicotine Dependence

Fawaz Alasmari 1, Salim S. Al-Rejaie 2, Shakir D. AlSharari 2,3, and Youssef Sari 1,*

1Department of Pharmacology and Experimental Therapeutics, University of Toledo, College of Pharmacy and Pharmaceutical Sciences, Toledo, OH, USA.

2Department of Pharmacology and Toxicology, King Saud University, College of Pharmacy, Riyadh, Saudi Arabia.

3Department of Pharmacology and Toxicology, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA, USA

Abbreviations

Glutamate transporter 1 (GLT-1); nucleus accumbens (NAc) and prefrontal cortex (PFC); ventral tegmental area (VTA); nicotinic acetylcholine receptors (nAChRs); ionotropic glutamate receptors (iGLURs); N-methyl-D-aspartate (NMDA); α-amino-3-hydroxy-5- methyl-4-isoxazolepropionic acid (AMPA); Medium spiny neuron (MSN); Dopamine (DA); Glutamate transporter 3 (EAAT3); phosphatidylinositol-3-kinase (PI3K); alpha protein kinase C (alphaPKC); cystine/glutamate exchanger (xCT); metabotropic glutamate receptors (mGluRs).

*Send correspondence to: Youssef Sari, Ph.D. University of Toledo, College of Pharmacy and Pharmaceutical Sciences Department of Pharmacology and Experimental Therapeutics Health Science Campus, 3000 Arlington Avenue, HEB282G Toledo, OH 43614. USA E-mail: [email protected] Tel: 419-383-1507 (Office)

Note: This article was published in Brain research bulletin: Volume: 121 (Year: 2016): Pages: 1-8.

Abstract

Several studies demonstrated that impairment in glutamatergic neurotransmission is linked to drug dependence and drug-seeking behavior. Increased extracellular glutamate concentration in mesocorticolimbic regions has been observed in animals developing nicotine dependence. Changes in glutamate release might be associated with stimulatory effect of nicotinic acetylcholine receptors (nAChRs) via nicotine exposure. We and others have shown increased extracellular glutamate concentration, which was associated with downregulation of the major glutamate transporter, glutamate transporter 1 (GLT-1), in brain reward regions of animals exposed to drug abuse, including nicotine and ethanol.

Importantly, studies from our laboratory and others showed that upregulation of GLT-1 expression in the mesocorticolimbic brain regions may have potential therapeutic effects in drug dependence. In this review article, we discussed the effect of antagonizing presynaptic nAChRs in glutamate release, the upregulatory effect in GLT-1 expression and the role of glutamate receptors antagonists in the treatment of nicotine dependence.

Key words: Nicotine, nAChRs, GLT-1, xCT, iGLURs, mGluRs

Introduction

Nicotine dependence is one of the most preventable causes of death in the world (Jacobs et al., 1999, Doll et al., 2004). Consumption of tobacco, a product containing nicotine, leads to premature death in developing countries and in the USA (Cosin-Aguilar et al.,

1995, Holford et al., 2014). It is well known that chronic nicotine consumption increases the mortality and morbidity rates in the world (Perry et al., 1984, Slotkin et al., 1997,

Thun et al., 2000). Nicotine acts on nicotinic receptors, which are distributed at both pre- and post-synaptic terminals in neurons of various brain regions (Albuquerque et al.,

2009), and it regulates different signaling pathways, including reward system (Watkins et al., 2000). The role of nicotine in the brain’s reward neurocircuitry has been investigated extensively (Pontieri et al., 1996, Reid et al., 2000, Saellstroem Baum et al.,

2006a, Goriounova and Mansvelder, 2012). It has been shown that nicotine exposure is linked to dopamine and glutamate neurotransmission (Fu et al., 2000, Lambe et al., 2003,

Saellstroem Baum et al., 2006a, Kleijn et al., 2011). Nicotine stimulates dopaminergic neurons in the ventral tegmental area (VTA) via activation of nicotinic acetylcholine receptors (nAChRs) (Tizabi et al., 2002a, Li et al., 2014). It is important to note that dopaminergic neurotransmission plays an important role in drug dependence (Fu et al.,

2000, Tizabi et al., 2002a, Dani, 2003). However, several studies demonstrated that glutamatergic neurotransmission is also involved in drug dependence (Cornish and

Kalivas, 2000, Giorgetti et al., 2001, Christian et al., 2013b). It has been reported that neuroadaptation of the glutamatergic system occurs in drug dependence (McFarland et al., 2003a). 9

Glutamatergic projections from the prefrontal cortex (PFC) into nucleus accumbens

(NAc) and ventral tegmental area (VTA) are very critical in drug dependence (Parsegian and See, 2014). In addition, dopaminergic inputs from NAc into VTA have been found to play an important role in drug dependence (Yun et al., 2004). Additionally, changes in glutamate release may affect dopamine release in the PFC and NAc (Markou, 2008)

(Figure 1-1).

Both dopamine and glutamate release are increased by nicotine via stimulation of presynaptic nicotinic acetylcholine receptors (nAChRs) in dopaminergic and glutamatergic neurons in the mesocorticolimbic brain regions (Markou, 2008, Parikh et al., 2010) (Figure 1-1). Varenicline, an nAChRs partial agonist, attenuated nicotine and ethanol interactions in the mesocorticolimbic dopaminergic system in rat models (Ericson et al., 2009, Bito‐Onon et al., 2011). This compound was also found to have an analgesic effect in a mouse pain model (AlSharari et al., 2012). It has been shown that α4β2 nAChRs are present in two distinct stoichiometric arrangements, (α4) 2(β2) 3 nAChRs and (α4) 3 (β2) 3 nAChRs (Moroni et al., 2006). However, it has been found that exposure to nicotine can alter the stoichiometry of α4β2 nAChRs and consequently increase its expression (Nelson et al., 2003, Vallejo et al., 2005). Furthermore, stimulation of α4β2 nAChRs has been suggested to be the mechanism of nicotine - stimulated glutamate release (Garduno et al., 2012). Additionally, several studies found that nicotine has been found to bind to α7 nAChRs and increased glutamate and calcium release (Gray et al., 1996, Wang et al., 2006). Thus, modulation of glutamate release following exposure to nicotine might be mediated through stimulation ofnAChRs 10

expressed in glutamatergic neurons. Moreover, it has been reported that nicotine applied on medial prefrontal pyramidal cells can lead to increased extracellular glutamate concentration in rats (Lambe et al., 2003), which might be also a result of the downregulatory effect of nicotine on glutamate transporters.

Importantly, studies have demonstrated the important role of the major glutamate transporter, glutamate transporter 1 (GLT-1, its human homolog, excitatory amino acid transporter 2, EAAT2), in nicotine self-administration, nicotine dependence, nicotine withdrawal and nicotine-induced reinstatement of preference (Knackstedt et al., 2009a,

Alajaji et al., 2013). GLT-1 is known to regulate the majority of glutamate uptake

(Danbolt, 2001). Glutamate transmission is also regulated by another glial transporter, cystine/glutamate exchanger (xCT). This transporter was also shown to play a critical role in nicotine dependence in rats and humans (Knackstedt et al., 2009a). GLT-1 and xCT have suggested as targets for treatment of drug dependence, including nicotine and alcohol (Knackstedt et al., 2009a, Alhaddad et al., 2014a). Therefore, it is important to find potential therapeutic compounds that upregulate GLT-1 and xCT, and consequently attenuate nicotine and drug dependence.

Additionally, several studies demonstrated the important role of glutamate receptors in attenuating nicotine dependence (Kenny et al., 2003b, Kenny et al., 2009). It is important to note that blocking glutamate receptors has been found to reduce nicotine self- administration (Kenny et al., 2003b, Sidique et al., 2012). Moreover, inhibiting

glutamate receptors has been found to decrease nicotine-induced dopamine release in mesocorticolimbic area(Fu et al., 2000, Tronci and Balfour, 2011).

It has been discussed extensively about the potential role of nicotine in glutamatergic system, particularly glutamate receptors (Li et al., 2014). In addition, effects of glutamate following exposure to nicotine on both dopaminergic system and medium spiny neuron

(MSN) have been investigated recently (Pistillo et al., 2015). In this review article, we discussed the literature on the modulatory effect of nAChRs in glutamate release on nicotine dependence. Importantly, we further discussed the important role of GLT-1 and xCT, as well as the implications of glutamate receptors and their potential therapeutic role for the treatment of nicotine dependence.

Figure 1-1. Schematic diagram shows the effect of nicotine on presynaptic α7-nAChRs in glutamatergic terminals in the PFC. Glutamate released from glutamateregic neurons, binds to iGLURs in both striatal medium spiny neuron (MSN) in the NAc and dopaminergic terminals in the VTA. Glutamate activates dopamine release through stimulation of iGLURs in dopaminergic neurons. Dopamine then binds to dopamine receptor 1 (DAR1) or dopamine receptor 2 (DAR2) in the MSN, inducing dopamine actions.

1.1 Role of nicotinic acetylcholine receptors in the modulation of glutamate release

Several studies were conducted to demonstrate the role of presynaptic nAChRs in the release of glutamate following exposure to nicotine (Gray et al., 1996, Wang et al., 2006,

Garduno et al., 2012). Glutamatergic terminals express presynaptic α7 nAChRs in the rat

VTA and PFC (Jones and Wonnacott, 2004, Huang et al., 2014). As shown in Figure 1-

1, glutamate release via stimulating presynaptic α7 nAChRs in glutamate terminals may have an indirect action in dopamine release by activating ionotropic glutamate receptors

(iGLURs) in dopaminergic terminals (Desce et al., 1992, Fu et al., 2000, Kaiser and

Wonnacott, 2000).

Studies have shown that chronic nicotine administration modulated glutamate concentration in the VTA (Changeux, 2010) and PFC (Shameem and Patel, 2012, Falasca et al., 2014). Additionally, it has been suggested that calcium influx is the main signal pathway for releasing glutamate after acute and chronic nicotine administration at different concentrations (McGehee et al., 1995, Gray et al., 1996, Wang et al., 2006,

Dougherty et al., 2008). An influx of intracellular calcium in the PFC and hippocampus in presynaptic glutamate terminals, expressing α7 nAChRs, enhanced glutamate release after both acute and chronic exposure to nicotine (McGehee et al., 1995, Gray et al.,

1996, Wang et al., 2006, Dougherty et al., 2008). Furthermore, it has been reported that the association of glutamate release and calcium influx might be blocked by methyllycaconitine, α7 nicotinic receptor antagonist (Wang et al., 2006). Moreover, α- bungarotoxin irreversibly binds to α7 nAChRs and inhibits nicotine-induced increased 13

presynaptic calcium signaling in the central nervous system (McGehee et al., 1995).

Additionally, pretreatment with α-bungarotoxin blocked choline-induced glutamate release in the PFC through inhibitory binding of choline to α7 -nAChRs (Konradsson-

Geuken et al., 2009). Together, these findings suggest that presynaptic α7 nAChRs in glutamatergic terminals play an important role in the release of glutamate, and consequently release of dopamine following administration of nicotine.

Several studies demonstrated the role of α4β2 nAChRs in glutamate release after exposure to nicotine (Lambe et al., 2003, Parikh et al., 2010, Garduno et al., 2012). It has been demonstrated that acute nicotine administration activated glutamatergic synaptic transmission through stimulation of presynaptic α4β2 nAChRs in the dorsal raphe nucleus (Garduno et al., 2012). Moreover, chronic nicotine exposure has been found to upregulate α4β2 nAChRs in humans (Buisson and Bertrand, 2001). A lower dose of nicotine has been able to upregulate α4β2 nAChRs as compared to either α6β2 nAChRs or α3β2 nAChRs (Walsh et al., 2008). Moreover, amplitude of glutamate release induced by nicotine or α4β2 nAChRs agonists has been revealed to be decreased in β2 nAChRs knockout animal model (Lambe et al., 2003, Parikh et al., 2010). A study was performed to determine the morphological effects of nicotine on dendritic spines of α4β2 nAChRs showed that nicotine-induced lateral enlargement in the spine heads of α4β2 nAChRs can lead to glutamatergic synaptic plasticity, since glutamate receptors antagonists blocked the nicotine-induced spine remolding effect (Oda et al., 2014). It is important to note that

α4β2 nAChRs antagonist also abolished this effect, which suggests the potential role of this receptor in glutamate release. The stoichiometry of α4β2 nAChRs was found to be 14

altered after short and long term exposure to nicotine (Nelson et al., 2003, Vallejo et al.,

2005, Srinivasan et al., 2011). It is well known that the increase in assembly of α4β2 nAChRs stoichiometry can be developed by acute and chronic nicotine administrations

(Nelson et al., 2003, Kuryatov et al., 2005, Vallejo et al., 2005). This effect can lead to an increase in the expression of α4β2 nAChRs. Additionally, it has been shown that the stoichiometry of α4β2 nAChRs is an important mechanism of nicotine-induced upregulation of α4β2 nAChRs (Vallejo et al., 2005, Srinivasan et al., 2011). We suggest here that the upregulatory effects of nicotine on α4β2 nAChRs may induce the release of glutamate in the mesocorticolimbic regions. Moreover, presynaptic nAChRs antagonist in the glutamatergic terminals could be effective in reducing both nicotine-induced glutamate and dopamine releases.

1.2 Role of glutamate transporters in nicotine dependence Several studies found that exposure to drugs of abuse induced a marked increase in extracellular glutamate concentration in the mesocorticolimbic regions (Smith et al.,

1995, Del Arco et al., 1998, Reid et al., 2000, Williams and Steketee, 2004, Ward et al.,

2009a, Ding et al., 2012, Ding et al., 2013, Das et al., 2015). It has been reported that this effect can be associated with downregulation of glutamate transporters(Knackstedt et al., 2009a, Knackstedt et al., 2010, Alhaddad et al., 2014a, Alhaddad et al., 2014c).

Several glutamate transporters regulate glutamate uptake in astrocytes (Su et al., 2003,

Holtje et al., 2008). GLT-1 is responsible for the removal of the majority of extracellular glutamate concentration into astrocytes (Danbolt, 2001, Jensen et al., 2015).

Additionally, xCT is co-expressed with GLT-1 in astrocytes regulating glutamate

homeostasis [For review see (Reissner and Kalivas, 2010a)]. Studies have demonstrated the potential implications of GLT-1 and xCT expression in central reward brain regions in cocaine-seeking behavior (Sari et al., 2009, Knackstedt et al., 2010). It has been revealed that GLT-1 and xCT are downregulated in NAc after cocaine exposure

(Knackstedt et al., 2010). Similarly, GLT-1 and xCT were found downregulated in the

NAc , amygdala and hippocampus but not in PFC in P rats exposed to ethanol as compared to ethanol naïve group (Alhaddad et al., 2014c, Aal-Aaboda et al., 2015b).

Importantly, it has been shown that chronic nicotine exposure can lead to downregulation of GLT-1 (Knackstedt et al., 2009a). Acute exposure to nicotine increased extracellular glutamate concentration in NAc (Reid et al., 2000, Saellstroem Baum et al., 2006a). A study was performed to determine the neuropharmacological cause of high extracellular glutamate concentration induced by acute nicotine administration (Reid et al., 2000).

This study found that mecamylamine and L-trans-pyrolidine-2,4 dicarboxylic acid, a non- selective glutamate transporter blocker, inhibited nicotine-induced increases in extracellular glutamate concentration in the NAc. In addition, denervation of dopamine by local injection of 6-hydroxydopamine enhanced nicotine-induced glutamate release in

NAc (Reid et al., 2000). Moreover, local perfusion of artificial cerebrospinal fluid- calcium free did not affect nicotine-increased glutamate release (Reid et al., 2000).

Together, this study found that nicotine-induced glutamate release in the NAc may not be calcium or dopamine dependent-related mechanisms, which suggest that glutamate transporters may have a critical role in nicotine-induced glutamate release in mesocorticolimbic regions (Reid et al., 2000).

Importantly, nicotine self-administration decreased GLT-1 and xCT expression in the

NAc and VTA but not in PFC (Knackstedt et al., 2009a) (Figure 1-2). Furthermore, reinstatement of nicotine-seeking behavior was found associated with increased extracellular glutamate concentration, decreased GLT-1 expression and increased behavioral reactions, suggesting the potential role of glutamate transporters in relapse- like nicotine seeking (Gipson et al., 2013). Recent studies from our lab and others have demonstrated the important role of glutamate transporters. GLT-1 and xCT have been suggested as key players in ethanol intake (Aal-Aaboda et al., 2015b, Alasmari et al.,

2015a). Thus, upregulation of these transporters by ceftriaxone, a β-lactam antibiotic known to upregulate GLT-1, was associated with attenuation of relapse to ethanol and cocaine seeking (Knackstedt et al., 2010, Qrunfleh et al., 2013, Alhaddad et al., 2014a).

Additionally, ceftriaxone reduced reinstatement of conditioned place preference induced by nicotine (Alajaji et al., 2013). It has been shown that ceftriaxone attenuated also tolerance developed by the analgesic effects of morphine and nicotine dependence

(Rawls et al., 2010, Schroeder et al., 2011). These effects have been associated in part through upregulation of both GLT-1 and xCT expression. In clinics, it has been shown that N-acetylcysteine, a prodrug of L-cysteine involving xCT activation, can attenuate dependence to nicotine (Knackstedt et al., 2009a, Schmaal et al., 2011). Additionally, glutamate transporter 3 type (excitatory amino acid transporter 3, EAAT3) transports glutamate at post-synaptic neurons. It has been reported that EAAT3 was found to be regulated through neuronal activity, mediating other signaling pathways like phosphatidylinositol-3-kinase (PI3K) and protein kinase C (PKC) (Nieoullon et al.,

2006b, Yoon et al., 2014). Moreover, P13K inhibitor, and PKC inhibitor have been 17

found to decrease EAAT3 activity (Yoon et al., 2014). Importantly, it has been found that chronic exposure to nicotine- reduced EAAT3 activity, and this effect was found to be P13K- and PKC-dependent, since P13K- and PKC activators blocked the nicotine- induced decrease in EAAT3 activity (Yoon et al., 2014). Taken together, we suggest that GLT-1, xCT and EAAT3 may play an important role in nicotine dependence.

Figure 1-2. Schematic diagram shows the effect of nicotine on glutamatergic system. Nicotine binds to nAChRs located at the glutamatergic terminal and elevates extracellular glutamate concentration. Moreover, decreased GLT-1 and xCT expression were associated with chronic exposure to nicotine. Glutamate is converted to glutamine by glutamine synthetase enzyme in glial cells. Extracellular glutamate binds to iGLURs (NMDA and AMPA receptors) located in postsynaptic neurons. Negative feedback mechanism can occur due to binding of extracellular glutamate to mGlu2/3 receptor in presynaptic neurons of glutamatergic terminals, and consequently decreases extracellular glutamate concentration.

1.3 Role of glutamate receptors in nicotine dependence

It has been shown extensively that ionotropic glutamate receptors (iGLURs) and metabotropic glutamate receptors (mGluRs) have a critical role in nicotine and drug

dependence (Moran et al., 2005, Terry et al., 2012, Gipson et al., 2013). It is important to note that iGLURs such as N-methyl-D-aspartate (NMDA) and α-amino-3-hydroxy-5- methyl-4-isoxazolepropionic acid (AMPA) receptors are found in dopamine neurons in the VTA (Wang and French, 1993, Gao and Wolf, 2007). Interestingly, NMDA receptor was found to be involved in nicotine-induced dopamine release in the NAc and VTA (Fu et al., 2000, Wang et al., 2010b, Salamone et al., 2014) (Figure 1-1). Competitive

NMDA receptor antagonist, CGS 19755, administration in the VTA blocked nicotine- induced dopamine release in the NAc (Fu et al., 2000). Furthermore, it has been found that glutamate release in the VTA mediated with high doses of nicotine increased the release of dopamine in the NAc (Fu et al., 2000). Alternatively, glycine may potentiate glutamate-activated NMDA receptors and consequently stimulate (Desce et al.) dopamine release in the striatum (Desce et al., 1992). It has been shown that using conditioned place preference, nicotine dependence was attenuated in mice lacking NMDA receptors in the dopaminergic axon terminals in the VTA (Wang et al., 2010b). Furthermore, administration of NMDA receptor antagonists directly into the VTA inhibited nicotine- stimulated release of dopamine in the NAc (Schilstrom et al., 1998, Fu et al., 2000).

Moreover, systemic administration of NMDA receptor antagonist also blocked nicotine- induced release of dopamine (Kosowski and Liljequist, 2004). It has been reported that

2-amino-5-phosphonopentanoic acid (AP-5), a competitive NMDA receptor antagonist, blocked nicotine-activated NMDA receptor and consequently reduced (Desce et al.) dopamine release in rat VTA(Jin and Fredholm, 1997).

Alternatively, chronic nicotine self-administration increased NMDA receptor NR2A and

NR2B subunits’ expression in the PFC and increased AMPA receptor GluR2/GluR3 subunits’ expression in the VTA (Wang et al., 2007b). Moreover, the NMDA receptor

NR2A subunit expression in the VTA, PFC and amygdala was found to be increased after nicotine self-administration in rat models (Liechti and Markou, 2008, Kenny et al., 2009).

Studies showed that chronic nicotine self-administration upregulated NMDA receptor

NR2B subunit as well as AMPA receptor GluR2 subunit in the PFC and in the amygdala as compared to control group (Kenny et al., 2009). NMDA-increased release of glutamate has been found in cerebellar granule cells exposed to a sub-acute nicotine concentration (Lim et al., 2000). Furthermore, studies have shown that systemic administration or direct application of NMDA antagonists into the VTA reduced self- administration of nicotine in rats (Blokhina et al., 2005, Liechti and Markou, 2008,

Kenny et al., 2009). Reinstatement to nicotine-seeking behavior can be inhibited by the

NMDA receptor subunit antagonist, suggesting that glutamate neurotransmission has a crucial role in relapse to nicotine seeking (Gipson et al., 2013). Interestingly, cotinine, a metabolite of nicotine, attenuated the effects of NMDA receptor antagonist, MK-801, in rats (Terry et al., 2012).

In regards to AMPA receptors, studies demonstrated that these receptor antagonists blocked nicotine-increased dopamine release (Sziraki et al., 2002, Kosowski et al., 2004).

Topiramate, a non-selective AMPA/kainate receptor antagonist, decreased the release of monoamine that is induced by nicotine in the NAc (Schiffer et al., 2001). In addition, it has been reported that the head diameter of the dendritic spine of the NAc core and 20

AMPA to NMDA receptors ratio currents were increased within two weeks after starting nicotine self-administration in the NAc in rat model (Gipson et al., 2013). Moreover, microinjection of AMPA receptor antagonists directly into the VTA were reported to attenuate chronic nicotine and sucrose self-administration (Wang et al., 2008). However, conflicting data have been shown regarding the effects of AMPA receptor antagonists on nicotine self-administration (Wang et al., 2008, Kenny et al., 2009). Alternatively, several studies demonstrated that withdrawal from chronic exposure to nicotine self- administration decreased glutamate receptors expression in the PFC, leading to reduced glutamate neurotransmission in early withdrawal period of time [For review see (Li et al.,

2014)]. Moreover, nicotine withdrawal effects have been shown to be increased precipitately in animal models injected with AMPA/kainate receptor antagonist (Kenny et al., 2003a). Altogether, downregulation of glutamate receptors may be a compensatory mechanism for decreasing extracellular glutamate concentration induced by nicotine withdrawal.

In addition to iGLURs, mGluRs have been also demonstrated to be involved in nicotine dependence (Bespalov et al., 2005, Dravolina et al., 2007, Liechti et al., 2007, Palmatier et al., 2008, Tronci et al., 2010, Tronci and Balfour, 2011, Akkus et al., 2013).

Alternatively, it has been shown that mGluR5 antagonist, 6-methyl-2-(phenylethynyl)- pyridine (MPEP), decreased nicotine self-administration in rats and mice (Kenny et al.,

2003b, Paterson et al., 2003, Tronci and Balfour, 2011). Additionally, mGluR5 antagonist prevented relapse to nicotine-seeking behavior in rats (Tessari et al., 2004).

Moreover, MPEP reduced nicotine-induced dopamine release into the NAc (Tronci and 21

Balfour, 2011). Another study demonstrated that MPEP decreased nicotine seeking in rats (Palmatier et al., 2008). It is important to note that long-term use ex-smokers had higher mGluR5 binding as compared to recent use ex-smokers in thalamus and frontal cortex suggesting that mGluR5 is an important biomarker for nicotine dependence

(Akkus et al., 2015). Furthermore, studies have demonstrated that mGluR5 or mGluR1 antagonists are able to reduce cue-induced reinstatement of nicotine self-administration in rats (Bespalov et al., 2005, Dravolina et al., 2007). In addition, nicotine self- administration decreased mGlu2/3 receptors’ function in the mesocorticolimbic area

(Liechti et al., 2007). It has been suggested that presynaptic inhibitory mGluR2/3 regulates extracellular glutamate concentration (Moran et al., 2005) (Figure 1-2). Thus, blocking mGluR2/3 inhibits the efficacy of N-acetylcystine to reduce reinstatement of cocaine self-administration in rats, suggesting that mGluR2/3 has a role in the decrease of extracellular glutamate concentration in drug dependence (Moran et al., 2005). It has been reported that systemic or microinjection of mGluR2/3 agonist, LY379268, reduced nicotine-seeking behavior (Liechti et al., 2007). Moreover, stimulation of mGluR2 by positive receptor modulator reduced nicotine self-administration (Sidique et al., 2012).

We suggest here that both iGLURs and mGluRs play a critical role in nicotine dependence. For example, iGLURs and mGluR1/5 antagonists attenuated nicotine seeking (Bespalov et al., 2005, Dravolina et al., 2007). However, mGluR2/3 functions as a negative regulatory role in glutamate neurotransmission, since mGluR2/3 agonists are able to attenuate nicotine-self-administration behavior (Liechti et al., 2007, Sidique et al.,

2012).

Conclusion

Nicotine may be able to affect excitatory and inhibitory neurotransmitters in mesocorticolimbic brain regions. Dopamine has been long standing target for the treatment of nicotine dependence through the use of bupropion as an FDA approved drug, which is a dopamine transporter blocker. In addition to dopamine as a target, nicotine has been studied to have modulatory effects on glutamatergic system through multiple mechanisms in the mesocorticolimbic area. Nicotine dependence may result on changes in glutamatergic transmission mediated by smoking or tobacco use. Thus, studies clearly demonstrated that chronic exposure to nicotine has been linked to increase in the release of glutamate through stimulatory effect in presynaptic nAChRs located in dopaminergic and glutamatergic axon terminals. Accordingly, upregulating GLT-1 expression, antagonizing certain glutamate receptor or antagonizing presynaptic nAChRs may have modulatory effects in glutamate transmission and consequently lead to attenuation of nicotine dependence. These suggest that targeting glutamatergic neurotransmission through different key proteins may have potential therapeutic effect in the treatment of nicotine dependence.

Acknowledgments

The review article was written during the period of fund supported by Award Number

R01AA019458 (Y.S.) from the National Institutes on Alcohol Abuse and Alcoholism.

Conflict of Interest

The authors declare no conflict of interest. 23

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Introduction: Part II

A Computerized Exposure System for Animal Models to Optimize Nicotine Delivery into the Brain Through Inhalation of Electronic Cigarette Vapors or Cigarette Smoke

Fawaz Alasmari1, Laura E. Crotty Alexander2,3, Christopher A. Drummond4, and Youssef Sari1,* 1Department of Pharmacology and Experimental Therapeutics, College of Pharmacy and Pharmaceutical Sciences, University of Toledo, Toledo, OH, USA.

2 Pulmonary and Critical Care Section, VA San Diego Healthcare System, 3350 La Jolla Village Dr, MC 111J, San Diego, CA 92161, USA. 3 Department of Medicine, Division of Pulmonary and Critical Care, University of California at San Diego (UCSD), La Jolla, CA 92093, USA. 4Surgery and Efficacy Studies Department, MPI Research, Mattawan, MI, USA.

Abbreviations: α-7nAChR, alpha-7 nicotinic acetylcholine receptor; CNS, central nervous system; e-cigarette, electronic cigarette; GLT-1, Glutamate transporter-1; xCT, cystine/glutamate exchanger.

*Send correspondence to: Dr. Youssef Sari University of Toledo, College of Pharmacy and Pharmaceutical Sciences Department of Pharmacology and Experimental Therapeutics Health Science Campus, 3000 Arlington Avenue, HEB282G Toledo, OH 43614 E-mail: [email protected] Tel: 419-383-1507 (Office)

Note: this paper was published in Saudi Pharmaceutical Journal: Volume: in press (Year: 2018): Pages: in press.

Abstract

Pre-clinical studies investigated the effects of chronic exposure to nicotine on lungs, kidneys and brains using animal models. Most of these studies delivered nicotine into the circulatory and central nervous systems (CNS) through intraperitoneal injection or oral consumption methods. Few studies used inhalation machine system for nicotine delivery into brains in rodents to mimic human exposure to cigarettes. However, finding a more accurate and clinically relevant method of nicotine delivery is critical. A computerized inhalation machine has been designed (SciReq) and is currently employed in several institutions. The computerized machine delivers electronic (e)-cigarette vapor as well as tobacco smoke to rodents using marketed e-cigarette devices or tobacco cigarettes. This provides evidence about clinical effects of nicotine delivery by traditional methods

(combustible cigarettes) and new methodologies (e-cigarettes) in physiological systems.

Potential neurobiological mechanisms for the development of nicotine dependence have been determined recently in mice exposed to e-cigarette vapors in our laboratory using

SciReq system. In this review article, the discussion focuses on the efficiency and practical applicability of using this computerized inhalation exposure system in inducing significant changes in brain protein expression and function as compared to other nicotine delivery methods. The SciReq inhalation system utilized in our laboratory and others is a method of nicotine delivery to the CNS, which has physiological relevance and mimics human inhalant exposures. Translation of the effects of inhaled nicotine on the CNS into clinical settings could provide important health considerations.

Keywords: electronic cigarette; tobacco cigarette; cigarette inhalation; nicotine; combustible cigarette. 36

Introduction

Parenteral routes of nicotine administration have been the standard methods used in preclinical nicotine delivery methods for decades (Nadal et al., 1998, Tizabi et al., 2002b,

Knackstedt et al., 2009a, Fowler and Kenny, 2011, Wang et al., 2014). These parenteral routes include intraperitoneal, intravenous and intracerebral injections. Oral nicotine consumption is a method utilized in several studies to examine the behavioral effects of nicotine in animals (Sparks and Pauly, 1999, Adriani et al., 2002, Sari et al., 2016).

However, these delivery methods have less desirable clinical and pharmacokinetic properties as compared to inhalation of nicotine (For review see (Le Houezec, 2003)).

Laboratories have designed a computerized system for nicotine or tobacco smoke inhalation to investigate their effects in the body organs, including the brain.

The use of inhalation system for nicotine or tobacco cigarette smoke delivery in an animal model can provide novel evidence about the long-term effects of these chemicals on several neurotransmitters. It is important to note that exposure to nicotine through intra-striatal or subcutaneous routes of nicotine administration upregulated nicotinic acetylcholine receptors (nAChRs) in the mesocorticolimbic areas (Auta et al., 2000,

Buisson and Bertrand, 2001, Alsharari et al., 2015). In addition, intravenous self- administration of nicotine via base/infusion for 21 days reduced one of the major glial glutamate transporters such as glutamate transporter 1 (GLT-1) in central reward brain regions (Knackstedt et al., 2009a). These effects on the central nervous system (CNS) induced by nicotine exposure using non-clinical nicotine exposure methods may or may 37

not be clinically relevant. Thus, using a nicotine delivery system reflective of human exposure routes is important to confirm or refute these findings. Thus, this will define addictive behavioral and neurobiological effects that may be induced by inhaled nicotine, which may mediate alterations in the function and expression of certain brain proteins. In this review article, we compared and contrasted the inhalation route with other routes of nicotine exposure on mediation of addictive effects.

Inhalation has been associated with a fast rate of nicotine absorption as compared to other routes of delivery of nicotine (For review see (Le Houezec, 2003)). In addition, bioavailability of nicotine in the brain has been reported to be higher after inhalation of cigarettes as compared to parenteral routes of nicotine delivery (Benowitz, 1990).

Alterations in pharmacokinetic parameters occurred in subjects exposed to chronic inhalation of cigarette smoke-containing nicotine compared to other methods of nicotine delivery (Benowitz, 1990, Le Houezec, 2003). These differences in pharmacokinetics provide evidence that chronic nicotine inhalation may mediate alterations in key proteins involved in the development of nicotine dependence to a different extent, and in a different pattern than other routes of nicotine administration

The inhalation exposure system (computerized inExpose machine) of nicotine has been found to be associated with several modifiable characteristics. Different electronic cigarette (e-cigarette) and tobacco cigarette brands can be used in the system (Hwang et al., 2016), and this could be clinically relevant when testing the most marketed e-cigarette and tobacco cigarette products (Figure 1-3). In addition, the exposure period and 38

duration to cigarettes can be controlled by the experimenters to mimic the actual human exposure duration and frequency to cigarettes (Hwang et al., 2016) (Figure 1-3).

Interestingly, other drugs of abuse can also be applied using the inhalation exposure machine, which may provide potential evidence about the effects of inhaled drugs of abuse on the body. We here shed light on the main characteristics of using the computerized inhalation exposure system in animal models compared to other routes of nicotine delivery.

1.4 Comparisons of nicotine inhalation to other delivery routes

Several studies investigated the effects of nicotine on nicotinic receptors, dopaminergic and glutamatergic systems in the CNS. These studies found that nicotine exposure was able to upregulate subtypes of nAChRs in mesocorticolimbic brain regions (Buisson and

Bertrand, 2001, Alsharari et al., 2015). In addition, intraperitoneal injection of nicotine increased dopamine release in part by stimulation of nAChRs (Tizabi et al., 2002b, Tizabi et al., 2007). Moreover, nicotine self-administration upregulated ionotropic glutamate receptors (Wang et al., 2007a, Kenny et al., 2009, Alasmari et al., 2016a). In addition, intravenous self-administration of nicotine was found to reduce the expression of GLT-1 in the nucleus accumbens (Knackstedt et al., 2009a). The alterations in dopaminergic and glutamatergic systems as well as nicotinic receptors following different nicotine exposure methods have been suggested to mediate the development of nicotine dependence.

However, little is known about the effects of chronic exposure to nicotine exposure using inhalation of e-cigarette vapor or tobacco smoke-containing nicotine on dopaminergic system, glutamatergic system and nicotinic receptors. 39

A recent study from our laboratory reported that chronic inhalation of e-cigarettes vapor containing-nicotine induced alterations in the glutamatergic system in the brain of female

CD1 mice (Alasmari et al., 2017a). This study found that inhalation of e-cigarette vapor containing-nicotine for six months upregulated alpha 7 nAChR (α-7 nAChR) in frontal cortex and striatum in CD1 mice (Alasmari et al., 2017a). It is important to note that α-7 nAChR regulates glutamate release from pre-synaptic glutamatergic neurons

(Konradsson-Geuken et al., 2009). In addition, chronic inhalation of e-cigarette vapor induced downregulation of cystine/glutamate exchanger (xCT) in striatum and hippocampus as compared to a group exposed to air (Alasmari et al., 2017a). xCT is an important glial protein that regulates glutamate homeostasis (Baker et al., 2002).

Moreover, chronic exposure to e-cigarette vapor induced significant decrease in GLT-1 expression in the striatum. GLT-1 is glial glutamate transporter that clears the majority of extracellular glutamate (Danbolt, 2001). The reduction in the expression of GLT-1 and xCT is suggested to be associated with increase in extracellular glutamate concentration as it was found in animal model of alcohol dependence (Nemmar et al.,

2013). Alterations of these proteins have been suggested previously to be involved in part in the development of nicotine dependence (For review see (Alasmari et al., 2016a)).

Additionally, certain strains of animals prefer to consume nicotine orally only with additive appetizers such as sucrose or saccharin (Hauser et al., 2012, Sari et al., 2016).

These additives are able to help with the bitter taste of nicotine (Hauser et al., 2012, Nesil et al., 2015, Sari et al., 2016). However, addition of other ingredients that are not found in cigarettes may lead to changes in neurobiological systems. Sucrose and saccharin have 40

been found to induce alterations in the dopaminergic, glutamatergic and GABAergic systems (Khvotchev et al., 2000, Rada et al., 2005, Mitra et al., 2014). Thus, inhalation system might be a valid method to investigate the effects of chronic exposure to nicotine on key target proteins in the brain.

1.5 Pharmacokinetic of nicotine inhalation compared to other routes of nicotine exposure

Inhalation route can lead to high rate of absorption of nicotine through pulmonary system

(Benowitz, 1990, Le Houezec, 2003). Importantly, alveolar capillaries in the lungs have large surface areas, which facilitate and enhance the rate and extent of nicotine absorption

(Hirsch et al., 2005). These kinetic properties indicate the potential effects of nicotine inhalation delivery on the rate and extent of nicotine absorption, which may lead to high bioavailability of nicotine in the brain. Moreover, oral ingestion of nicotine has a lower systemic bioavailability since nicotine is metabolized pre-systemically in the liver (Le

Houezec, 2003). This suggests that absorption of nicotine might be higher with inhalation method. In addition, inhalation of nicotine has been associated with a fast rate of distribution in the brain (Le Houezec, 2003). Distribution of nicotine into different tissues after smoking a cigarette has been detected in previous studies (Le Houezec,

2003, Nides, 2008, Berridge et al., 2010). Nicotine distribution in the brain and arterial blood was found immediately after smoking a cigarette (Nides, 2008, Berridge et al.,

2010), and the concentration of nicotine was found to be decreased within twenty to thirty minutes in plasma (Le Houezec, 2003). Data suggest faster brain bioavailability of 41

nicotine, which may then induce neurobiological alterations in the function of certain proteins that mediate the development of nicotine dependence (Ponzoni et al., 2015,

Alasmari et al., 2017a). It is important to note that the ratio of nicotine in the brain to plasma has been reported to be elevated during inhalation exposure (Ghosheh et al.,

2001), and this ratio was decreased during the elimination period (Ghosheh et al., 2001).

We suggest here that the brain distribution of nicotine after smoking is rapid, which indicate that the pulmonary system plays a crucial role in rapid onset of nicotine distribution into the brain.

A study from our laboratory found that inhalation of e-cigarette vapors containing nicotine for six months showed high concentration of nicotine and cotinine, a major metabolite and biomarker of nicotine, in the frontal cortex of female CD-1 mice

(Alasmari et al., 2017a). We suggest that nicotine is absorbed and metabolized rapidly in the body and that nicotine and its metabolites are transported into the brain. These data indicate that the computerized inhalation machine is efficient and can deliver high concentrations of nicotine into the brain. Further results from this study demonstrated that nicotine inhalation induced alterations in the expression of several target proteins, including GLT-1, xCT and α-7 nAChR, which may have a role in the development of nicotine dependence.

1.6 Benefits of a computerized inhalation exposure system as a nicotine delivery method

Several clinically desirable properties are controlled using the digitized inhalation exposure system (Wong, 2007, Hwang et al., 2016). Preparation of cigarette compositions is possible using the computerized system, and this applies to most brands of combustible cigarettes and e-cigarettes (Hwang et al., 2016). In addition, different concentrations of nicotine can be loaded into this system to determine potential dose- effects on vital organs. Exposure time and exposure duration to cigarettes as well as atmospheric and humidity conditions have been controlled by researchers using the computerized inhalation exposure system in animal models (Wong, 2007, Hwang et al.,

2016) (Figure 1-3). These factors can be modified to make identical condition to particular human exposure condition that can be investigated. For example, new e- cigarette users have puff topography more similar to conventional cigarette smokers (puff time ~1-2 seconds long).

In addition to nicotine, other drugs of abuse such as marijuana, methamphetamine and cocaine can be applied in the inhalation system. This will provide clinical evidence about the neurobiological mechanisms that mediate the development of drug dependence.

Importantly, alcohol consumers are more likely to smoke tobacco cigarettes (Bierut et al.,

2000, Falk et al., 2008), and alcohol drinking has been suggested to increase tobacco consumption (Falk et al., 2006). As a corollary, tobacco use has a critical role in augmentation of alcohol intake (Grant et al., 2004a). This suggests that there are factors

that may lead to the reinforcing effects of co-abuse of alcohol and nicotine. However, in contrast to clinical studies, pre-clinical studies reported conflicting data showing that nicotine exposure can reduce or increase alcohol seeking behavior and blood alcohol concentrations (Parnell et al., 2006, Bito‐Onon et al., 2011, Sari et al., 2016). One of the possible reasons for the conflicting results is that parental or oral administration of nicotine may induce pharmacokinetic interactions with ingested alcohol (Parnell et al.,

2006). The methodology of nicotine exposure such as limited or continuous access is another factor that might affect the effects of nicotine exposure on alcohol intake. Thus, applying an accurate physiological nicotine delivery method through e-cigarette vapor/cigarette smoke inhalation in animal models of alcohol drinking may provide stronger clinical evidence about the effects of cigarette smoking on alcohol consumption.

These may provide information about whether there are synergistic, additive or antagonizing effects of alcohol and nicotine co-exposure on neurobiological proteins that mediate polysubstance uses.

1.7 Comparisons of computerized inhalation (SciReq) system to other inhalation systems; validity and limitations

Cotinine has been detected in plasma and brain of female CD1 mice exposed to e- cigarette for six months using SciReq system (Alasmari et al., 2017a). The study by

Alsamari et al. found that plasma cotinine concentration was similar in mice exposed to e-cigarette vapor as that found in human active smokers (Hukkanen et al., 2005). This indicates that the computerized inhalation system is a valid method for nicotine delivery 44

into the circulatory system. However, other studies found that another exposure system, a mouse pie cage Aerosol Medication Nebulizer, was also able to deliver nicotine containing e-cigarette vapors to mice such that cotinine was found in measureable concentrations in mouse plasma (Garcia-Arcos et al., 2016). Moreover, cotinine has been detected in mouse urine and brain following chronic exposure to tobacco smoke using mechanical ventilator delivery system (Ponzoni et al., 2015). However, the uses of both systems, computerized and non-computerized, have been associated with very low increase in plasma or urine cotinine level in air-control groups (Drummond et al., 2016,

Alasmari et al., 2017a). This effect is due to the inhalation of the environmental levels of tobacco smoke or e-cigarette vapor within the exposure area. Thus, using an efficient vacuum in both systems to clean all environmental smoke after each run is highly important. Studies found that inhalation of e-cigarette vapor using SciReq system induced reduction in the host defense as well as alterations in inflammatory cytokines and neurobiological proteins in mice (Hwang et al., 2016, Alasmari et al., 2017a). These data are consistent with previous studies reporting similar effects of tobacco smoke in humans

(Staley et al., 2006, Garlichs et al., 2009, Herr et al., 2009, Knackstedt et al., 2009a).

Reported literature showed conflicting findings demonstrating the efficiency of using other inhalation systems to investigate the effects of tobacco smoke in rodents

(Matulionis, 1984, Bowles et al., 2005, Moreno-Gonzalez et al., 2013). Importantly, chronic exposure to tobacco smoke failed to induce alterations in the pulmonary manifestations in mice and rats using different smoking inhalation machines (Matulionis,

1984). This indicates that the methodology of smoke inhalation should be validated and monitored carefully. 45

To the best of our knowledge, few studies have investigated the effects of passive exposure to tobacco smoke in pre-clinical models (Khan et al., 2008) and finding a new protocol for passive exposure to e-cigarette or tobacco smoke is critical. It is important to consider that the rate of passive exposure to smoke is increasing recently worldwide and the long-term effect of second-hand exposure to smoke in humans is a significant health concern. Alternatively, SciReq system is flexible depending on desired exposure method, it offers eight separated champers for the whole body exposure, or more than ten restraints mesh holders for nose only exposure, which enable the researchers to run groups of animals at the same time with controlled procedures. However, non-software inhalation systems use smoke inlets connected to one or two cages for smoke exposure and each cage can handle more than one animal (Kaisar et al., 2017). This method is less accurate as compared to the SciReq system since the amount of inhaled smoke would not be similar between animals in each cage. In addition, this method is associated with increased cage-change frequency and the environmental parameters, including the humidity, temperature and the puff volume, which should be controlled and tested in each exposure run. Interestingly, SciReq system can be used for both in vivo and in vitro applications and so far there is no well-established method to investigate the effects of e- cigarette vapors on the cell lines.

1.8 Comparisons of computerized inhalation (SciReq) system to other inhalation systems; system characteristics and exposure parameters

Although studies reported that inhalation of nicotine induced changes in the rodent biological systems using computerized and non-computerized inhalation methods

(Talukder et al., 2011, Drummond et al., 2016, Hwang et al., 2016, Alasmari et al.,

2017a, Franck et al., 2017, Ma et al., 2018), the use of computerized system is more convenient and accurate. Unlike other non-software inhalation systems, the computerized system, SciReq, composes of several parts that work together on a continuous and cooperative manner (Alasmari et al., 2017a). The base unit is controlled by software and this unit can handle up to four pumps. The base unit provides precise exposure parameters (temperature, humidity and exposure duration) sent from the software. Additionally, each system pump is connected to a smoking generating apparatus, and this indicates that different experimental groups can run in the system at the same time. These pumps produce time-flow pattern of smoke and in the same time it can test the atmosphere of the smoke generation machine. The atmosphere is monitored by a filter chamber that grabs the particulates, which are then analyzed chemically or gravimetrically. The capacity of atmosphere (0-100%) can be measured by qualitative particulate transducers. The Flexiware software is Windows-based software in which the users can save, monitor and modify the input data. The software enables the researchers to create their own profiles and the input data in each profile can be exported and stored in a Microsoft Excel style. In addition, the computerized software provides options for the type smoke delivery (constant/random) per unit of time. The software measures the 47

lung elastane and resistance to the smoke as well as carbon monoxide (CO) and puff volume precisely (Fahmy et al., 2010, Robichaud et al., 2015). In addition, the Flexiware software analyzes lung functions, including the ventilation rate and alveolar pressure as well as the lung volume (Herrmann et al., 2017). In contrast, non-computerized inhalation method requires a soap bubble flow meter and CO monitor to measure puff volume and CO, respectively (Tsuji et al., 2013). Additionally, non-digitalized smoke inhalation system measures the particle size of the substances via a cascade impactor

(Tsuji et al., 2013). However, the computerized system composes several nebulizers that produce different particle sizes of aerosols of prepared mixture solutions (Phillips et al.,

2017). The nebulizer generates minimal heat or force to the solutions and delivers different types of substances such as nanoparticle suspensions or solutions, ovalbumin and DNA fragments (Novali et al., 2015). One type of nebulizer produces a standard particle size (4 - 6 microns), while the other nebulizer produces fine particle sizes (2.5 – 4 microns) of aerosols (Devos et al., 2017). Custom-mesh nebulizer can be used to produce large particle sizes. Nanoparticles can be aerosolized by the Aerogen nebulizer

(Phillips et al., 2017).

Alternatively, non-software apparatus can handle only one cigarette and the researchers should change the cigarette after each run (Kaisar et al., 2017). SCIREQ system offers two different champers for smoking generations, single cigarette apparatus and cigarette smoking robot (CSR) (Ogunwale et al., 2017). The CSR can handle up to 24 cigarettes with automatic smoke ejection for several hours without human intervention. The smoking generation apparatus is supplied with a special adaptor for e-cigarette solutions. 48

Two different ways, nose-only or whole body exposure, can be applied in the machine to expose animals to e-cigarette vapor or tobacco smoke (Figure 1-3). The nose-only exposure method reduces the systemic effects of nicotine or other substances that penetrate into the body through skin or eye (Oyabu et al., 2016). This is also associated with fast changeover of the atmosphere mimicking human smoking exposure (Pauluhn and Thiel, 2007). However, the nose-only method of exposure requires restraining the animals in soft-mesh restraints, which is stressful for the animals. Alternatively, whole body exposure method allows animals to move freely throughout the chambers, which minimizes the stress. Moreover, desired concentrations of nicotine can be generated using whole body exposure supplied with aerosol generation devices. But the whole body exposure method can lead to deposition of the inhalant on the eyes and fur

(Nemmar et al., 2013, Oyabu et al., 2016). Additionally, gastrointestinal delivery of the nicotine and other chemicals has been reported in animals exposed to cigarettes in whole- body exposure apparatus (Oyabu et al., 2016). In this apparatus, rodents huddle and hide their noses from the inhalants. Thus, it is harder to measure the exact amount of e- cigarette vapor/tobacco smoke that are inhaled by the rodents compared to nose-only exposure. Finally, SCIREQ system offers a new method to expose the tobacco smoke to cell lines. Cell plates can be placed in the whole body champers and the tobacco smoke or e-cigarette vapor is driven across the liquid phase of air-liquid interface where the cells grow. Two different ways, main-stream smoke and side-stream smoke can be used in this system to expose the cells to tobacco smoke. Main-stream smoke requires a buffer chamber that distributes the puffs on all sides and the pump pulls the smoke outside the system. Side-stream smoke provides more constant delivery of smoke. 49

Figure 1-3. Inhalation exposure system composes of six major components. A) Cigarette smoke generation: multiple type of cigarettes such as combustible and electronic-cigarettes can be used in the apparatus to generate smoking. B) Nose-only exposure: animals can be placed in mask holders to provide only nose exposure to cigarettes. C) InExpose pumps: these pumps are designed to generate smoking. D) InExpose base unit: the base unit is connected to the software to control the exposure parameters such as exposure time and exposure duration. E) Whole body chamber: whole body animals can be placed in chambers to expose the whole body to cigarettes. F) Flexiware software: the exposure temperature, patterns of smoking and humidity as well as the exposure time and duration can be modified practically by the software. The image is adopted with permission from SCIREQ Scientific Respiratory Equipment Inc. (http://www.scireq.com/inexpose)

Conclusion

Establishment of a physiological exposure method of nicotine delivery in animal models through inhalation of cigarette vapor/smoke may lead to new clinical considerations.

Other non-inhalation methods of nicotine delivery have been historically used to evaluate nicotinic effects on CNS pathways and physiologic changes throughout the body.

However, these methods may have less desirable clinical pharmacokinetics of nicotine as compared to inhalation of e-cigarette vapor/cigarette smoke-containing nicotine. The computerized inhalation machine may allow investigators to modify the exposure dose of 50

nicotine and the exposure duration to the cigarettes/e-cigarettes. Moreover, investigators can use any type of cigarettes/e-cigarettes, which can provide information about the effects of marketed e-cigarette devices or tobacco cigarettes in relevant animal models.

The machine may be used to determine the neurobiological effects of other abused drugs that are given through inhalation such as marijuana, methamphetamine and cocaine. The favorable characteristics of this system make it highly that pre-clinical data obtained from using the inhalation system will be translatable to clinical stages of investigation. The computerized inhalation system controls several factors involved in the laboratory experiments and this system monitors the exposure parameters automatically with less users’ interventions as compared to non-computerized inhalation systems.

Acknowledgments

The authors would like to thank SCIREQ Scientific Respiratory Equipment Inc. for providing us with inExpose machine image used in Figure 1-3.

Funding

The review article was written during the period of funding supported by Award Number

R01AA019458 (Y.S.) from the National Institutes on Alcohol Abuse and Alcoholism,

R01HL137052-01 (L.C.A. PI) from the NIH NHLBI, Beginning Grant-in-Aid

16BGIA27790079 (L.C.A. PI) from the American Heart Association, Daniel O’Connor

Scholar Award P30DK079337 (L.C.A. PI) from the UAB-UCSD O’Brien Center, ATS

Foundation Award (L.C.A. PI), High Impact Award 26IP-0040 from the California TRDRP

(L.C.A. Co-I), with additional salary support from the VA San Diego Healthcare System

(L.C.A.). Fawaz Alasmari is supported by a scholarship from King Saud University.

Conflict of Interest

The authors have no conflicts of interest.

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Introduction: Part III

Role of glutamatergic system and mesocorticolimbic circuits in alcohol dependence

Fawaz Alasmari1, #, Sunil Goodwani2, #, Youssef Sari1,*

1Department of Pharmacology and Experimental Therapeutics, University of Toledo, College of Pharmacy and Pharmaceutical Sciences, Toledo, OH, USA.

2The Neurodegeneration Consortium, Institute for Applied Cancer Science, The University of Texas MD Anderson Cancer Center, Houston, TX, 77054, USA.

#, Authors equally contributed to the work.

Abbreviations Glutamate transporter 1 (GLT-1); cystine-glutamate antiporter (xCT); glutamate/aspartate transporter (GLAST); metabotropic glutamate receptors (mGluRs); ionotropic glutamate receptor (iGluRs); N-methyl-D-aspartate (NMDA); α-amino-3-hydroxy-5-methyl-4- isoxazolepropionic acid (AMPA); nucleus accumbens (NAc); prefrontal cortex (PFC); ventral tegmental area (VTA); anterior cingulate cortex (ACC); orbitofrontal cotrx (OFC); phosphorylated-AKT (pAKT); nuclear factor-kappa B (NF-κB); (R)-(−)-5- methyl-1-nicotinoyl-2-pyrazoline (MS-153); alcohol-preferring (P) rats; glutathione (GSH); conditioned place preference (CPP); Excitatory amino-acid transporters (EAAT).

Note: This paper will be submitted to a scientific journal. 60

Abstract

Emerging evidence demonstrates that alcohol dependence is associated with dysregulation of several neurotransmitters. Alterations in dopamine, glutamate and gamma-aminobutyric acid release are linked to chronic alcohol exposure. The effects of alcohol on the glutamatergic system in the mesocorticolimbic areas have been investigated extensively. Several studies have demonstrated dysregulation in the glutamatergic systems in animal models exposed to alcohol. Alcohol exposure can lead to increase in extracellular glutamate concentrations in the mesocorticolimbic brain regions. In addition, alcohol exposure affects the expression and functions of several glutamate receptors and glutamate transporters in these brain regions. In this review, we discussed the effects of alcohol exposure on glutamate receptors and certain glutamate transporters in each brain region of the mesocorticolimbic system. We also discussed the potential therapeutic role of glutamate receptors and glutamate transporters in each brain region for the treatment of alcohol dependence.

Key words: Alcohol Dependence; Glutamate; Glutamate Receptors; Glutamate

Transporters; NAc; PFC; Striatum; Amygdala; Hippocampus; VTA.

Introduction

Alcohol use disorders (AUD) are chronic relapsing disorders with profound implications on the socioeconomic status as well as morbidity and mortality of the addict. Ranked as third leading cause of preventable death, AUDs costs over $200 billion per year to the US economy according to National Institute of Alcohol Abuse and Alcoholism. Increased tendency to consume high amounts of alcohol with limited control on the consumption, despite the detrimental health outcomes associated with it, is a characteristic of the progression from an acute social drinking pattern to the state of alcohol dependence. The clinical aspect of the person occasionally consuming alcohol is distinct from escalated intake leading to emergence of chronic compulsive alcohol seeking behavior (Koob and

Volkow, 2010).

Corticostriatal circuitry involving both dopaminergic and glutamatergic projections play a critical role in the initiation and progression of dependence to most drugs of abuse

(Wise, 1987, Kalivas et al., 2009). There are at least two subcircuits: the limbic subcircuit and motor subcircuit are interconnected with nucleus accumbens (NAc) acting as a gateway between the two subcircuits, and collectively form the larger corticostriatal circuitry. The limbic subcircuit involves the prefrontal cortex (PFC), amygdala, NAc and ventral tegmental area (VTA); and the motor subcircuit encompasses the motor cortex, dorsal striatum and substantia nigra. Interestingly, both subcircuits play a critical role in drug dependence processes, with limbic system being the key center for processing the

new information based on the motivational cues and developing new behavioral response to those cues, while the motor subcircuit acts when the behavioral pattern to that motivational cue is already developed (Kalivas et al., 2009).

Ample evidence suggests that the positive reinforcing effects of acute alcohol exposure are associated with increased dopaminergic transmission in mesocorticolimbic brain regions (Weiss and Porrino, 2002, Gonzales et al., 2004). An increase in dopaminergic neuronal firing in the VTA has been reported following exposure to alcohol (Gessa et al.,

1985, Diana et al., 1993, Morzorati et al., 2010). Concomitantly, alcohol also increases dopamine release in the pathway projecting to the NAc (Clarke et al., 2014). In accordance, several studies have reported that increase in dopamine release in the NAc mediates the initial positive reinforcing effects of alcohol [For review see (Wise and

Rompre, 1989, Koob and Le Moal, 2001)],(Yoshimoto et al., 1992a, Bainton et al.,

2000). Similarly, the increase in dopamine release in the NAc was observed in humans consuming alcohol, as compared to those consuming non-alcoholic beverage, using PET scanning technique (Boileau et al., 2003). It is noteworthy to note that the NAc, PFC and amygdala receive dopaminergic inputs from the VTA (Kalivas and O'Brien, 2008). In addition, repeated alcohol intake also increases dopamine release into PFC and amygdala, which facilitates learning behavior associated with drug dependence (Trantham-Davidson and Chandler, 2015). It has been suggested that the glutamatergic projections from PFC to NAc play a crucial role in retrieving and integrating drug-associated memories

(Kalivas and Volkow, 2005, Kalivas and O'Brien, 2008). These glutamatergic projections from the PFC to NAc have therefore been suggested to be implicated in the 63

initiation and learning of drug seeking behaviors and are essential for reinstituting this behavior (Kalivas and Volkow, 2005, Moussawi and Kalivas, 2010). Glutamatergic projections from the amygdala and hippocampus to the NAc and PFC are involved in the behavioral response to the stimuli (craving) from previously established associations with motivational and neutral cues (Kalivas and Volkow, 2005). Several studies have reported an elevation of extracellular glutamate concentrations in the NAc during and after - alcohol exposure (Melendez et al., 2005, Saellstroem Baum et al., 2006, Szumlinski et al., 2007, Hinton et al., 2012, Ding et al., 2013, Das et al., 2015, Pati et al., 2016).

Importantly, rats during alcohol withdrawal showed a marked increase in extracellular glutamate concentration in the NAc (Saellstroem Baum et al., 2006). These studies indicate that repeated exposure to alcohol and withdrawal from chronic alcohol exposure increase extracellular glutamate concentrations in the NAc. Therefore, targeting the glutamatergic neurocircuitry to normalize the extracellular glutamate concentrations has been an appealing pharmacological strategy to attenuate alcohol seeking.

In the present review, we discussed the available evidence documenting the effects of alcohol on glutamatergic system. More specifically, we discussed the effects of alcohol exposure on the expression and function of glutamate receptors and transporters in mesocorticolimbic brain regions. We further discussed the potential therapeutic effects of pharmacological modulators of glutamate receptors and transporters, microinjected directly into specific mesocorticolimbic brain regions, on the attenuation of alcohol dependence. 64

1.9 Alcohol and Glutamate Receptors

Glutamate receptors have been categorized into two different categories based on the structure and function: metabotropic glutamate receptors (mGluRs) and ionotropic glutamate receptors (iGluRs). mGluRs are G-protein coupled receptors (GPCR), mediate the slow excitatory and inhibitory glutamatergic transmission through intracellular second messenger systems. On the contrary, iGluRs are ligand-gated ion channels, which regulate the rapid glutamatergic neurotransmission in the brain

(Meldrum, 2000). Dysregulated glutamatergic neurotransmission has been found after acute or chronic alcohol exposure. Not surprisingly, glutamate receptors (both presynaptic and postsynaptic) have been extensively implicated in the development and progression of alcohol dependence [For review see (Goodwani et al., 2017)]. There have been inconsistent reports of the effect of alcohol exposure on N-methyl-D- aspartate receptor (NMDAR) expression. For example studies reported a reversible upregulation of NMDARs in preclinical models exposed to alcohol (Ron, 2004, Kroener et al., 2012) while others have reported a decrease in NMDAR expression after alcohol exposure (Abrahao et al., 2013). Specifically, chronic exposure to alcohol increases the expression of NR2B mRNA as well as protein expression in both in-vitro and in-vivo models (Snell et al., 1996, Roberto et al., 2006, Kash et al., 2008, Kash et al., 2009,

Obara et al., 2009). In addition, increase in the expression of NR1 subunit of NMDAR has also been reported following chronic alcohol exposure (Trevisan et al., 1994, Roberto et al., 2006).

Despite the inconsistency in reports examined the effects of alcohol on NMDAR expression, there has been a consensus regarding its effect on NMDAR function.

Generally, acute alcohol exposure has an inhibitory effect while chronic exposure leads to increase in NMDAR function as well as NMDAR-mediated glutamatergic synaptic transmission [For review see (Goodwani et al., 2017)]. Interestingly, another study reported that exposure and withdrawal from alcohol induced a long-lasting increase in

NR2B NMDAR activity which facilitate alcohol consumption (Chen et al., 2011).

Conversely, inhibiting the NR2B-NMDAR using an antagonist, ifendropil, resulted in a significant decrease in alcohol consumption in rats (Wang et al., 2010). This indicates that NR2B-NMDAR plays a critical role in excessive alcohol intake. In addition to altering NMDAR expression, alcohol also increases α-amino-3-hydroxy-5-methyl-4- isoxazolepropionic acid receptor (AMPAR) expression as well as its synaptic localization in several in vitro and in vivo models (Brückner et al., 1997, Chandler et al., 1999,

Christian et al., 2012, Wang et al., 2012). The increase in AMPAR expression is accompanied by an increase in neuronal activity dependent pentraxin (NARP) levels, which further facilitates synaptic distribution of AMPAR, and this is critical for regulating neuroplasticity (Ary et al., 2012). Long-term exposure to chronic alcohol has been specifically found to upregulate GluR1 subunit of AMPAR (Ortiz et al., 1995). In addition, chronic alcohol exposure also led to upregulation of GluR2/3 subunit (Brückner et al., 1997, Chandler et al., 1999). Acute alcohol exposure also inhibits AMPAR functionally, but this inhibition is attained at much higher alcohol concentrations than that required for NMDAR inhibition (Lovinger et al., 1989, Dildy-Mayfield and Harris,

1992, Akinshola et al., 2003, Möykkynen et al., 2003). Interestingly, chronic exposure to 66

alcohol has been reported to enhance AMPAR-mediated currents in several brain regions

(Läck et al., 2007, Heikkinen et al., 2009, Ary et al., 2012, Christian et al., 2012). In addition, chronic alcohol exposure also enhanced AMPAR-evoked Ca2+ influx in developing neurons (Netzeband et al., 1999). As with AMPAR, increase in kainate receptor (KAR) expression has been found following exposure and withdrawal from alcohol in vitro (Carta et al., 2002). However, another study reported that there was no change in the KAR expression following exposure to alcohol (Chandler et al., 1999).

Functional inhibition of KAR following exposure to alcohol has been reported in several studies (Dildy-Mayfield and Harris, 1995, Martin et al., 1995, Valenzuela and Cardoso,

1999, Weiner et al., 1999). Pharmacological inhibition of AMPAR/KAR with mixed antagonists, CNQX and NBQX, attenuated alcohol seeking behavior as well as cue- induced reinstatement to alcohol (Stephens and Brown, 1999, Bäckström and Hyytiä,

2004, Czachowski et al., 2012). However, this effect may not necessarily to be specific to alcohol (Roberto and Varodayan, 2017). Contrarily, a AMPAR positive allosteric modulator, aniracetam, increased alcohol seeking-behavior determined by alcohol self- administration and cue-induced reinstatement of alcohol animal models (Cannady et al.,

2013). Although a general inhibition in the neuronal excitability is observed with acute alcohol exposure, chronic alcohol exposure increased iGluRs functioning [For review see

(Roberto and Varodayan, 2017)]. Therefore, counteracting these iGluRs mediated alterations in neuronal excitability and synaptic activity appears to be promising therapeutic approach in treating acute and chronic effects of alcohol exposure.

Although, unlike iGluRs, alcohol exposure has only modest effect on mGluRs. Group I

(mGluR1 and mGluR5) mGluRs and Group II (mGluR2/3) mGluRs are widely studied for their roles in alcohol dependence process. Group I mGluRs are predominantly localized in the post-synaptic neurons regulating slow excitatory neurotransmission while group II mGluRs are mainly located in pre-synaptic neurons, with limited post-synaptic and glial localization, and involved in slow inhibitory neurotransmission [For review see

(Goodwani et al., 2017)]. Upregulation of group I mGluRs (mGluR1 and mGluR5) following prolonged exposure to alcohol has been extensively reported (Szumlinski et al.,

2008, Obara et al., 2009, Cozzoli et al., 2012, Cozzoli et al., 2014). Increase in mGluR5 expression following alcohol exposure has also been associated with activation of its intracellular pathways (Cozzoli et al., 2009, Cozzoli et al., 2012). On the contrary, excessive alcohol exposure resulted in mGluR2 deficit which eventually led to an increase in alcohol seeking. This effect was abolished after restoring mGluR2 expression in the infralimbic cortex (Meinhardt et al., 2013). This has been pharmacologically substantiated in several preclinical studies. For example, pharmacological blockade of mGluR1 (by JNJ16259685, EMQMCM, CPCCOEt) resulted in a decrease in alcohol self-administration, condition place preference (CPP) and withdrawal associated seizures

(Besheer et al., 2008a, Kotlinska et al., 2011). Similarly, 3-((2-Methyl-4- thiazolyl)ethynyl) pyridine (MTEP) and 2-Methyl-6-(phenylethynyl) pyridine (MPEP), mGluR5 antagonists, have been demonstrated to diminish alcohol self-administration, cue-induced alcohol seeking, relapse, withdrawal and CPP (Backstrom et al., 2004,

Cowen et al., 2005, Olive et al., 2005, Schroeder et al., 2005, Backstrom and Hyytia,

2006, Hodge et al., 2006, Lominac et al., 2006, Cowen et al., 2007, Adams et al., 2008, 68

Besheer et al., 2008b, Bird et al., 2008, Blednov and Adron Harris, 2008, Gupta et al.,

2008, Schroeder et al., 2008, Besheer et al., 2010, Sidhpura et al., 2010, Kotlinska et al.,

2011). On the contrary, mGluR2/3 agonists, LY379268 and LY404039, have been found to attenuate alcohol self-administration, cue-induced alcohol seeking as well as behaviors associated with relapse to alcohol (Bäckström and Hyytiä, 2005, Rodd et al., 2006, Zhao et al., 2006, Sidhpura et al., 2010). Interestingly, a study compared alcohol-preferring (P) versus non-preferring (NP) rats reported that mGluR2/3 expression was lower in alcohol- naïve P rats compared to NP rats. In addition, there was also a decrease in group III mGluR (mGluR4, mGluR7 and mGluR8) expression in alcohol-naïve P rats as compared to NP rats (McBride et al., 2012, McBride et al., 2013). Alcohol exposure also decreased mGluR7 mRNA expression in rats without affecting mGluR4 and mGluR8 (Simonyi et al., 2004). The literature suggests that antagonism of post-synaptic group I mGluRs and/or agonism of group II mGluRs restores the glutamatergic imbalance, which attenuates alcohol seeking behavior in several preclinical models (Backstrom et al., 2004,

Kufahl et al., 2011, Lum et al., 2014).

1.10 Alcohol and Glutamate Transporters

Glutamate transporters are high-affinity transporters belonging to solute carrier 1 family.

These transporters co-transport three Na+ and one H+ along with counter-transport of K+ which creates a concentration gradient to transport glutamate out of the synapse into the glial cells (mainly astrocytes). Thereby, these glutamate transporters regulate synaptic glutamate concentrations to maintain extracellular glutamate concentration. There are five known glutamate transporters (also known as excitatory amino acid transporters; 69

EAATs) which have been characterized based on their expression and functions. The

EAAT1 (also known as glutamate/aspartate transporter, GLAST) is largely expressed in the cerebellum while the expression of EAAT2 (also known as glutamate transporter 1,

GLT-1) is predominantly localized in the forebrain (Danbolt, 2001). Due to their limited expression into specific sub-regions of the brain, these transporters share the load of maintaining the glutamate homeostasis by regulating the uptake of synaptic glutamate

(Lehre and Danbolt, 1998, Danbolt, 2001, Mitani and Tanaka, 2003). Unlike GLAST and GLT-1, which are expressed mainly in the astrocytes, EAAT3 is known as a neuronal glutamate transporter with more homogeneous but limited expression in the astrocytes.

This transporter was found to show highly expression level during the brain development.

This suggests that EAAT3 plays an important role during early neuronal development

(Torp et al., 1994, Haugeto et al., 1996, Furuta et al., 1997, Nieoullon et al., 2006).

Additionally, like EAAT2, EAAT4 is expressed in cerebellum (Bar-Peled et al., 1997,

Dehnes et al., 1998). However, EAAT5 is mainly expressed in the retinal bipolar cells and rod photoreceptor (Wersinger et al., 2006). Cystine-glutamate antiporter (xCT), another glial glutamate transporter, plays an important role in glutamate homeostasis

(Moran et al., 2005). xCT regulates extra-synaptic glutamate concentrations by exchanging extracellular cystine for intracellular glutamate in astrocytes (Baker et al.,

2002).

There is plethora of evidence demonstrates the effects of alcohol exposure on the expression as well as functions of the glutamate transporters. For example, acute alcohol exposure increased EAAT3 (Kim et al., 2003, Kim et al., 2005) as well as EAAT4 (Park 70

et al., 2008) activity; however, EAAT3 activity is reduced by chronic exposure to alcohol

(Kim et al., 2003, Kim et al., 2005). Alternatively, we have shown that chronic alcohol intake, in a five-weeks continuous two-bottles free-choice paradigm, results in a significant decrease in GLT-1 and xCT, but not GLAST, expression in central reward brain regions in male alcohol preferring (P) rats (Alhaddad et al., 2014a, Alhaddad et al.,

2014b, Aal-Aaboda et al., 2015, Rao et al., 2015a, Hakami et al., 2016b), (Figure 1-5B).

Moreover, studies from our laboratory also found that GLT-1 and xCT upregulators were able to attenuate chronic and relapse-like alcohol drinking behavior (Sari and

Sreemantula, 2012, Qrunfleh et al., 2013, Alhaddad et al., 2014a, Alhaddad et al., 2014b,

Aal-Aaboda et al., 2015, Alasmari et al., 2015a, Rao et al., 2015a, Rao et al., 2015b).

These studies have further fortified the importance of glutamate transporters in the alcohol addiction process.

1.11 Nucleus Accumbens (NAc)

Nucleus accumbens, NAc, also known as the central reward brain region, receives glutamatergic inputs from the amygdala, hippocampus and PFC (McFarland et al., 2003,

LaLumiere and Kalivas, 2008) (Figure 1-4). It is important to note that NAc is anatomically divided into two sub-compartments: the core and the shell, which are thought to be organized in a specific pattern to serve different functions (Zahm and Brog,

1992). The VTA dopaminergic innervation into the NAc shell is critical in establishing and maintaining learning and motivation events associated with alcohol dependence.

With distinct interconnection with anterior cingulate cortex (ACC) and orbital frontal cortex (OFC) , the glutamatergic projections into the NAc core mediate motivational 71

impulse which induce learned behaviors-associated with alcohol dependence (Kalivas and Volkow, 2005). Therefore, the effects of alcohol in NAc are not limited to an increase in glutamatergic neurotransmission, but also extend to an enhancement in other neurotransmitters such as dopamine and serotonin (Yoshimoto et al., 1992b, Olive et al.,

2001, Boileau et al., 2003, Melendez et al., 2005). Interestingly, studies that investigated the effects of voluntary alcohol intake (acute and chronic) on the extracellular glutamate concentrations reported an elevation in the extracellular glutamate concentrations in the

NAc (Melendez et al., 2005, Szumlinski et al., 2007, Ding et al., 2013, Das et al., 2015,

Pati et al., 2016). These findings were also in agreement with an increase in extracellular glutamate concentrations in the NAc following forced alcohol administration in rodent models of alcoholism (Melendez et al., 2005, Kapasova and Szumlinski, 2008, Carrara-

Nascimento et al., 2011, Ding et al., 2012). Additionally, there is an increase in extracellular glutamate concentrations in the NAc during cue-induced reinstatement of alcohol-seeking behavior compared to food-seeking behavior (Gass et al., 2011). This drug-induced increase in extracellular glutamate concentrations can be a result of either an increase in glutamate release into the synaptic cleft (Pierce et al., 1996) or decrease in glutamate uptake from the synaptic cleft (Melendez et al., 2005). In summary, alcohol induces an increase in extracellular glutamate concentrations in the NAc thereby dysregulating the glutamate homeostasis.

Figure 1-4. Schematic diagram shows glutamatergic, dopaminergic and GABAergic pathways involved in alcohol dependence in mesocorticolimbic areas. The mesocorticolimbic brain regions are composed of six major components – nucleus accumbens (NAc), prefrontal cortex (PFC), amygdala (Amg), hippocampus (Hpc), striatum (Stm) and ventral tegmental area (VTA). PFC, Amy and HIPP send glutamatergic projections into NAc. In addition, PFC and Amy as well as PFC and HIPP send and receive glutamatergic inputs from and into each other. Glutamatergic pathways from PFC into VTA have been found to be critical in alcohol dependence.

1.11.1 Role of the glutamate receptors in the NAc in alcohol dependence

High abundance of mGluRs has been reported in the NAc (Testa et al., 1994).

Specifically group I and group II mGluRs (mGluR5, mGluR2/3) in NAc have been very well studied in the context of alcohol dependence. The presynaptic mGluR2/3, when activated by glutamate, provides a negative feedback to decrease the glutamate release leading to a decrease in the glutamatergic neurotransmission (Moran et al., 2005).

Several studies have targeted the negative feedback loop to decrease the extracellular glutamate concentrations by stimulating the presynaptic mGluR2/3, which could

attenuate alcohol-seeking behavior. For example, microinjections of mGluR2/3 agonist,

LY379268, directly into the NAc attenuated alcohol self-administration in P rats (Besheer et al., 2010). Another study found that pre-treatment with mGluR2/3 agonist,

LY404039, reduced alcohol-seeking and relapse-like behavior without affecting the maintenance of operant alcohol self-administration in P rats (Rodd et al., 2006), as well as alcohol intake in both dependent and non-dependent mice (Kapasova and Szumlinski,

2008). In contrast, mGluR2/3 agonist, LY379268, attenuated alcohol self-administration and reinstatement, however, the effective doses also had motor-suppressant side effects in animals (Bäckström and Hyytiä, 2005). Alternatively, treatment with mGluR2/3 antagonist, LY341495 did not affect operant responses to alcohol in P rats (Schroeder et al., 2005). Although the available literature provides compelling evidence of the role of mGluR2/3 in alcohol dependence, there is less known about the effects of alcohol exposure on the expression and function of mGluR2/3 in the NAc, or the role of mGluR2/3 agonists in restoring glutamate homeostasis by decreasing glutamate release into the synaptic cleft. Therefore further studies are warranted to investigate the extent of contribution of NAc mGluR2/3 in context of AUD. Another avenue in practice to target mGluRs in context of alcohol dependence is by antagonizing group I mGluRs in the

NAc. Withdrawal following binge-alcohol consumption in adult mice led to an increase in mGluR1 and mGluR5 expression in the NAc shell (Lee et al., 2016). Additionally, the latter study reported that binge alcohol consumption also led to an increase in protein kinase C epsilon type (PKCε) level in the NAc core. It is noteworthy that activation (by phosphorylation) and translocation of PKCε is critical in regulating the cellular localization of mGluR5 in the NAc (Schwendt and Olive, 2017). Moreover, binge 74

alcohol consumption was associated with an increase in the NAc levels of phospho-

Ser729-PKCε (Cozzoli et al., 2016). Furthermore, inhibition of PKCε translocation decreased binge alcohol consumption in mGluR1/5 dependent manner (Cozzoli et al.,

2016). Therefore, it has been concluded that chronic alcohol intake resulted in functional increase in mGluR5-Homer2-PI3K signaling pathway in the NAc and this was inhibited by intra-NAc infusions of mGluR5 antagonist, MPEP (Cozzoli et al., 2009). PKCε is a critical downstream of PI3K-mGluR5 signaling pathway and this cascade in NAc is required for attenuation of alcohol consumption by mGluR5 antagonism (Olive et al.,

2005, Gass and Olive, 2009). Interestingly, systemic administration of mGluR5 antagonist MPEP decreased cue-induced reinstatement of alcohol-seeking behavior and

ERK1/2 phosphorylation in the NAc (Schroeder et al., 2008). It is important to note that this study reported an increase in ERK1/2 phosphorylation in the NAc shell, which was associated with a reinstatement of alcohol-seeking behavior in rats. In a different study

MPEP administered locally into the NAc showed ability to attenuate alcohol self- administration, without affecting the response to sucrose or water, in P rats (Besheer et al., 2010). Furthermore, blocking mGluR5 in the NAc also reduced cue-induced reinstatement of alcohol seeking behavior in rats (Sinclair et al., 2012). Upregulation of mGluR1 in the NAc shell was also reported following stress-alcohol cross-sensitization in mice (Quadir et al., 2016). Intra-NAc infusion of JNJ-16259685, a negative-allosteric modulator of mGluR1, has been shown to decrease alcohol consumption in C57BL/6J mice. The same study demonstrated the ability of mGluR1 negative allosteric modulators in decreasing alcohol consumption was associated with modulation of mGluR1-Homer2-

PLC signaling in the NAc shell (Lum et al., 2014). 75

Like mGluRs, iGluRs are also expressed in the NAc (Nie et al., 1994). NMDAR- dependent long-term depression (LTD) in the NAc is associated with neuronal plasticity.

Disruption of NMDAR dependent LTD in the NAc has been found to be a compensatory neuroadaptation in response to chronic alcohol consumption (Jeanes et al., 2011, Abrahao et al., 2013, Jeanes et al., 2014). Alcohol locomotor sensitization is associated with altered NMDAR synaptic plasticity in the NAc, which lead to an increase in alcohol consumption (Abrahao et al., 2013). Several studies have also reported an inhibition in

NMDAR function following acute alcohol exposure (Maldve et al., 2002, Zhang et al.,

2005, Zhang et al., 2006). Another study found that alterations in NMDAR functions in the NAc mediated excessive alcohol intake in mice exposed to chronic intermittent alcohol exposure paradigm (Renteria et al., 2017). Moreover, microinjection of a competitive NMDAR antagonist directly into the NAc reduced alcohol self- administration in rats (Rassnick et al., 1992) as well as alcohol conditional place preference (CPP) (Gremel and Cunningham, 2009). Withdrawal following 2-week period of binge alcohol drinking in mice resulted in alcohol-seeking behaviors and this was associated with increase in the expression of GluN2b subunit of NMDAR in the NAc shell (Lee et al., 2016). Interestingly, the same study also reported an increase in expression of Ca2+/calmodulin-dependent protein kinase II (CAMKII). Upon phosphorylation and activation, CAMKII mediates NMDAR-dependent long term potentiation (LTP), which lead to forward trafficking of AMPAR to the synaptic membrane [For review see (Morisot and Ron, 2017)]. Additionally, CAMKII has been directly linked to establishment of alcohol-drinking behaviors (Easton et al., 2013).

Importantly, stress-alcohol cross-sensitization displays an increase in GluN2b expression 76

in the NAc shell, however GluN2b expression was decreased in the NAc core in mice

(Quadir et al., 2016). A study reported that chronic alcohol exposure increased the expression of NR2A and NR1 subunits of NMDAR in the NAc of low-sensitized mice compared to high-sensitized mice. The study classified these mice into low and high sensitization based on locomotor activity indicating that NR2A and NR1 subunits of

NMDAR are implicated in mediating locomotion following repeated-alcohol exposure

(Nona et al., 2014). Alcohol exposure also has been reported to increase phosphorylation

(activation) of GluA1 S831 subtype of AMPAR (pGluA1 S831) in the NAc, however the contribution of activated NAc AMPAR in escalating alcohol consumption appeared to be limited in this study (Cannady et al., 2017). Following chronic intermittent alcohol exposure, there is a marked decrease in GluA2-containing AMPAR and this was associated with an increase in GluA2-lacking AMPAR. This alteration in AMPAR subunit composition is implicated in the loss of NMDAR-induced LTD in the NAc, which increased alcohol intake (Renteria et al., 2018).

1.11.2 Role of the glutamate transporters in the NAc in alcohol dependence

Increase in synaptic glutamate in the NAc has been found extensively in animals exposed to alcohol exposure (Szumlinski et al., 2005, Szumlinski et al., 2007, Kapasova and

Szumlinski, 2008, Ding et al., 2013). Studies have reported that alcohol-induced increase in extracellular glutamate is associated with a decrease in glutamate uptake in the NAc

(Melendez et al., 2005, Das et al., 2015). The increase in glutamate concentrations in the

NAc has been shown to enhance alcohol drinking in mice (Griffin et al., 2014).

Moreover, we have shown that GLT-1 and xCT but not GLAST are downregulated in 77

the NAc in P rats exposed to alcohol for five weeks as compared to alcohol naïve group

(Alhaddad et al., 2014a, Alhaddad et al., 2014b, Hakami et al., 2016b). This effect was associated with an increase in extracellular glutamate concentrations in the NAc (Das et al., 2015) (see Figure 1-5A and 2B). Moreover, pharmacological upregulation of GLT-1,

GLT-1 isoforms and/or xCT in the NAc has been reported to attenuate both alcohol consumption and relapse to alcohol (Sari and Sreemantula, 2012, Qrunfleh et al., 2013,

Alhaddad et al., 2014a, Alhaddad et al., 2014b, Alasmari et al., 2015b, Rao et al., 2015a,

Rao et al., 2015b, Alasmari et al., 2016). We also reported that this alcohol-induced downregulation of GLT-1 and xCT in NAc are regulated at least in part, by phosphorylated-AKT (pAKT) and nuclear factor-kappa B (NF-κB) (Alhaddad et al.,

2014b, Rao et al., 2015a) (Figure 1-6). This indicates that these signaling pathways are critical in downregulatory effects of alcohol on the glial glutamate transporters. On the contrary, β-lactam antibiotics and MS-153 induced reversal of GLT-1 and xCT downregulation following alcohol exposure also increased pAKT and NF-κB levels in the

NAc (Alhaddad et al., 2014b, Rao et al., 2015a, Rao et al., 2015b) (Figure 1-6). downregulation following alcohol exposure also increased pAKT and NF-κB levels in the

NAc (Alhaddad et al., 2014b, Rao et al., 2015a, Rao et al., 2015b) (Figure 1-6).

Figure 1-5. Schematic diagram shows the effects of alcohol on glutamatergic system. A) Normal release of glutamate neurotransmitter from presynaptic glutamatergic neurons in the central nervous system. In addition, normal expression of glutamate transporter-1 (GLT-1), glutamate aspartate transporter (GLAST) and cystine/glutamate antiporter (xCT) in water naïve model. B) Chronic exposure to alcohol decreased GLT-1 and xCT expression but not GLAST in the mesocorticolimbic areas. This effect is associated with marked increased in extracellular glutamate concentrations.

1.12 Prefrontal Cortex (PFC)

PFC is connected to NAc and VTA by both dopaminergic as well as glutamatergic projections. The dopaminergic neurons originating from the VTA project dopaminergic inputs to the PFC and these projections have been known to mediate the initial rewarding effects associated with drugs of abuse (Geisler and Zahm, 2005, Watabe-Uchida et al.,

2012, D'Souza, 2015). On the contrary, VTA and NAc receive glutamatergic projections originating from the PFC (Filip and Cunningham, 2003, Kalivas et al., 2009). The glutamatergic projections from PFC to VTA regulate the dopaminergic transmission in 79

the VTA and therefore can regulate rewarding effects associated with drugs of abuse

(Overton and Clark, 1997). However, the glutamatergic projections from the PFC into the NAc have been implicated in the initiation of drug dependence as well as learning associated with drug-seeking behavior (Kalivas and Volkow, 2005, Moussawi and

Kalivas, 2010, Goodwani et al., 2017). Apart from its interconnections with VTA and

NAc, PFC also is innervated by glutamatergic projections from the hippocampus and amygdala ,which are critical in the development of behavioral responses of learning- associated with drug use (McDonald, 1996, Kalivas and Volkow, 2005, Parent et al.,

2010).

It has been found that exposure to alcohol decreased the neuronal activity in PFC in vivo and in neuronal slice cultures. This decrease in neuronal activity was further characterized by alcohol’s effect on decreasing the amplitude and duration of the spontaneous membrane depolarizations in the PFC (Tu et al., 2007). In humans, alcohol exposure has been found to be associated with decrease in prefrontal cortical excitability

(Kahkonen et al., 2003). In addition to its effect on glutamatergic system, chronic exposure to alcohol also led to loss of dopamine receptors (D2 and D4) signaling in the medial PFC (Trantham-Davidson et al., 2014). Interestingly, glutamate release dysregulation has also been observed in the medial PFC of adult rats following acute intraperitoneal alcohol injection (1 g/kg) (Mishra et al., 2015). Moreover, a study found that alcohol craving is associated with significant increase in glutamate concentrations in the dorsolateral PFC (Frye et al., 2016b). Importantly, pyramidal glutamatergic neurons

in the medial PFC have been suggested to be involved in the development of alcohol withdrawal (George et al., 2012).

1.12.1 Role of the glutamate receptors in the PFC in alcohol dependence

Several studies have reported compelling evidence confirming involvement of glutamatergic receptors in the PFC in maintenance of dependence to alcohol (Pickering et al., 2007, Gass et al., 2014). Thus, a study demonstrated that infusion of mGluR5 antagonist, 3-((2-methyl-4-thiazolyl)ethynyl) pyridine, inhibited CDPPB, a mGluR5 a positive allosteric modulator, in the infralimbic (subregion of PFC) mediated-alcohol seeking during extinction period in rats (Gass et al., 2014). Moreover, this study reported an increase in amplitude of NMDA currents in the PFC during the extinction period of alcohol seeking, which was partially abolished after administration of mGluR5 positive allosteric modulator. Additionally, long-term alcohol exposure increases ratio of

NMDAR to AMPAR current as well as NMDAR subunits expression without affecting

AMPAR subunit in the PFC (Kroener et al., 2012).

Moreover, alcohol exposure dampens NMDAR-mediated excitatory postsynaptic currents reversibly at toxic concentrations. These data indicate that NMDAR-mediated excitatory postsynaptic responses in the PFC maybe susceptible to acute with high dose exposure to alcohol. Interestingly, there was no notable effect of alcohol on the AMPAR-mediated electrical activity in the PFC (Weitlauf and Woodward, 2008). In addition, a positive correlation between alcohol consumption and AMPA GluR1 receptor subunit mRNA expression in the PFC has been determined in rat models (Pickering et al., 2007). 81

1.12.2Role of the glutamate transporters in the PFC in alcohol dependence

It is suggested that motivational effects of chronic exposure to drug of abuse may lead to a significant decrease in GLT-1 expression in the NAc but not in the PFC (Reissner and Kalivas, 2010). In line with this, we reported that exposure to alcohol for five weeks did not downregulate GLT-1 levels in the PFC (Sari and Sreemantula, 2012, Alhaddad et al., 2014a, Alhaddad et al., 2014b). However, several studies from our laboratory showed that β-lactam antibiotics (e.g. ceftriaxone) attenuated chronic and relapse-like alcohol drinking in part by upregulatory effects on GLT-1 and xCT expression in the PFC

(Qrunfleh et al., 2013, Alhaddad et al., 2014a, Alasmari et al., 2015a, Rao et al., 2015a,

Rao et al., 2015b, Alasmari et al., 2016, Hakami et al., 2016a). Our laboratory also reported that β-lactam antibiotics increased levels of pAKT and NF-κB in PFC and consequently reduced alcohol consumption (Rao et al., 2015a, Rao et al., 2015b) (Figure

1-6). Furthermore, ceftriaxone, a β-lactam antibiotic, was able to reduce the level of

IκBα, an inhibitor of NF-κB, in the PFC (Rao et al., 2015b) (Figure 1-6).

Figure 1-6. Schematic diagram shows the effect of β-lactam antibiotics on major signaling pathways involved in stimulation of glutamate transporter-1 (GLT-1) gene expression. β-lactam antibiotics stimulate phosphorylated-AKT (pAKT) signaling directly or indirectly. Moreover, pAKT increases both nuclear factor-kappas B (NF-κB) functioning and IκBα (Inhibitor of NF-κB) degradations. Furthermore, stimulated NF-κB is able to increase glutamate transporter-1 (GLT-1) gene transcription and consequently GLT-1 synthesis. Furthermore, increased GLT-1 expression removes extracellular glutamate concentration into astrocyte.

Importantly, stimulation of xCT antiporter can increase intracellular cystine level, which is further involved in the biosynthesis of glutathione (GSH) via γ-GlutamylCysteine synthetase and glutathione synthetase enzymes sequentially (Lewerenz et al., 2009). It is important to note that ceftriaxone treatment for seven days increased GSH contents in the brain (Amin et al., 2014). Moreover, GSH induces neuroprotective and antioxidant effects through inhibitory effects on reactive oxygen species (Lewerenz et al., 2009)

(Figure 1-7).

Figure 1-7. Schematic diagram shows the effect of β-lactam antibiotics on cystine/glutamate antiporter (xCT) expression as well as intracellular glutathione (GSH) content in astrocyte. β-lactam antibiotics increase xCT expression and consequently stimulate exchange of extracellular cystine for intracellular glutamate. Cystine, inside astrocyte, is normally converted to cysteine, which is further converted into γ-GlutamylCysteine by γ-GlutamylCysteine synthetase enzyme with contribution of intracellular glutamate. Glutathione synthetase enzyme and glycine are able to convert γ- GlutamylCysteine to GSH. Increased intracellular glutathione content induces neuroprotection as well as decrease in oxidative stress effects. Glutathione peroxidase is responsible for oxidation of GSH into oxidized GSH, while glutathione reductase is able to reduce oxidized GSH into reduced GSH.

1.13 Striatum

Several studies have investigated the effects of alcohol exposure on the dysregulation of glutamate homeostasis in the striatum. For example, first study reported that withdrawal from chronic alcohol exposure resulted in a marked increase in extracellular glutamate levels in the striatum and this effect was found to be a consequence of increased glutamate release (Rossetti and Carboni, 1995). In addition, NT69L, an analog 84

of neurotensin (NT) (8–13), reduced alcohol consumption and preference and induced alterations in glutamatergic and dopaminergic systems in mouse striatum (Li et al., 2011).

The latter study reported that this compound was able to reduce alcohol-increased dopamine and glutamate extracellular concentrations in mice striatum.

1.13.1 Role of the glutamate receptors in the striatum in alcohol

dependence

One of the earlier studies examining the effect of alcohol withdrawal on glutamatergic neurotransmission reported an increase in the extracellular glutamate levels in the striatum after withdrawal from chronic alcohol and this effect was associated with activation of NMDAR (Rossetti and Carboni, 1995, Rossetti et al., 1999). This increase in the activity of NMDAR led to the stimulation of positive feedback process, and consequently resulted in the increase in glutamate release (Rossetti et al., 1999). These findings were further substantiated by use of NMDAR antagonist, dizocilpine, which counteracted the effect of alcohol withdrawal on the extracellular glutamate concentrations (Rossetti et al., 1999). Furthermore, alcohol inhibits NMDAR-dependent

LTP while facilitating LTD thereby modifying the corticostriatal circuitry involved in habit-learning process (Yin et al., 2007). Interestingly, acute ex-vivo exposure of the dorsal striatum to alcohol resulted in an increase in NR2B, a NMDAR subunit, phosphorylation and this effect was associated with long-term facilitation of the NR2B- containing NMDARs in the dorsal striatum (Wang et al., 2007). Conversely, operant self-administration of alcohol was attenuated by NR2B NMDAR antagonist infused directly into the dorsal striatum (Wang et al., 2007). In another study from the same 85

laboratory, it was reported that repeated alcohol exposure induced long-lasting increase in phosphorylation and membrane localization of NR2B NMDAR in the dorsomedial striatum (DMS) and this effect was confirmed with the electrophysiological and biochemical findings observed in DMS (Wang et al., 2010). In the next study, the authors examined the role of GluR1 and GluR2 in alcohol-facilitated LTP in the DMS

(Wang et al., 2012). Not surprisingly, this study reported that ex-vivo and systemic exposure to alcohol led to facilitation of LTP in the DMS. Interestingly, this LTP induction was accompanied by increased synaptic localization of GluR1 and GluR2,

AMPAR subunits, in the DMS. Furthermore, microinjection of AMPAR blocker in the striatum attenuated alcohol self-administration but not sucrose (Wang et al., 2012).

1.13.2 Role of the glutamate transporters in the striatum in alcohol

dependence

A study reported that withdrawal from alcohol resulted in downregulation of GLT-1 in striatum (Abulseoud et al., 2014). Conversely, ceftriaxone restored alcohol- downregulated GLT-1 expression in the striatum and this elevation in GLT-1 levels after ceftriaxone treatment last 7-days after ceftriaxone treatments (Abulseoud et al., 2014). In another study, ceftriaxone-induced upregulation of GLT-1 in striatum also led to reduced alcohol drinking in mice (Lee et al., 2013). This latter study suggested that the modulatory role of GLT-1 in alcohol drinking behavior is mediated by type 1 equilibrative nucleoside transporter (ENT1) in the striatum. Another study from our laboratory showed that repeated oral high dose of alcohol induced a significant decrease in striatal GLT-1 but not xCT or GLAST in Wistar rats (Alshehri et al., 2017). However, 86

there is little known about the role of striatal glutamate transporters on the development of alcohol withdrawal symptoms as well as reinstatement of alcohol seeking. Further studies are warranted to evaluate the effects of upregulation of striatal glutamate transporters in the attenuation of alcohol seeking.

1.14 Amygdala

Substantial preclinical evidence confirms the role of amygdala in the development of drugs of abuse dependence, including alcohol (Caine et al., 1995, Di Ciano and Everitt,

2004, Schroeder et al., 2008, Sinclair et al., 2012, Aal-Aaboda et al., 2015). The glutamatergic projections from the amygdala innervating the NAc regulate alcohol- seeking behavior (Gass et al., 2011, Keistler et al., 2017). Glutamate released from the amygdala into the NAc has been found to play a key role in sensitization and seeking behaviors associated with exposure to drugs of abuse (Kalivas et al., 2009) (Figure 1-4).

Interestingly, amygdala has been shown to receive glutamate inputs from PFC(Hubner et al., 2014). A microdialysis study reported a significant increase in the glutamate release in the amygdala after chronic alcohol treatment (Roberto et al., 2004). Moreover, a significant increase in glutamate neurotransmission in basolateral amygdala has been detected in rats exhibited high rate of alcohol self-administration (Gass et al., 2011).

Furthermore, synaptic glutamate concentration and presynaptic glutamate function in the amygdala are increased in rats withdrawal from chronic alcohol exposure (Christian et al., 2013). A study found that acute and chronic exposure to alcohol alters glutamate homeostasis in part through cannabinoid receptor-1 in the amygdala (Robinson et al.,

2016). Thus, reports suggest that glutamate neurotransmission in the amygdala after 87

alcohol exposure has a critical role in the development of alcohol dependence as well as reinstatement of alcohol.

1.14.1 Role of the glutamate receptors in the amygdala in alcohol

dependence

Direct inhibition of mGluR5 in the basolateral amygdala reduced cue-induced reinstatement of alcohol-seeking behavior (Sinclair et al., 2012). Several studies reported that chronic alcohol exposure increased the mRNA and protein expression of NMDAR as well protein expression of group 1 mGluRs in the amygdala (Roberto et al., 2006, Obara et al., 2009). Furthermore, stimulating mGluR2 has been found to attenuate cue-induced alcohol-seeking behavior and this was associated with alteration in c-fos expression levels in the amygdala (Zhao et al., 2006). In addition, LY379268, mGluR2/3 agonist, attenuated conditioned reinstatement of alcohol and this was associated by a significant increase in GTPγS binding in the amygdala following treatment with mGluR2/3 agonist

(Kufahl et al., 2011). Another study showed that binge alcohol consumption was able to increase the expression of mGluR1 and mGluR5as well as their signaling as a neuroadaptive changes to maintain excessive alcohol consumption. The effect of alcohol on group I mGluRs was further substantiated by using intra-amygdala infusion of mGluR1 and mGluR5 blockers, which decreased binge alcohol consumption (Cozzoli et al., 2014). Chronic alcohol exposure increased the expression levels of group 1 mGluRs as well as NMDAR in the amygdala (Cozzoli et al., 2014). Thus, presynaptic mGluR2/3 agonist or post-synaptic mGluR5 antagonist in the basolateral amygdala might provide a fruitful avenue to inhibit binge-alcohol intake as well as relapse to alcohol. Additionally, 88

chronic alcohol exposure has been found to increase iGluRs (AMPA and NMDA receptors) functions and expression in the amygdala (Floyd et al., 2003, Roberto et al.,

2006, Christian et al., 2012). Moreover, microinjection of AMPA/kainate receptor antagonist, CNQX, in the amygdala reduced alcohol induced-CPP in rats (Zhu et al.,

2007). These data provide strong evidence about the potential implication of amygdala igluRs and mGluRs in the development of alcohol dependence.

1.14.2 Role of the glutamate transporters in the amygdala in alcohol

dependence

A study from our laboratory investigated the effects of alcohol consumption for five weeks on the expression of GLT-1 and xCT in amygdala (Aal-Aaboda et al., 2015). As highlighted in Figure 1-5A and 1-5B, the study found that GLT-1 and xCT in the amygdala are downregulated in male P rats exposed to alcohol for five weeks as compared to alcohol naïve group (Aal-Aaboda et al., 2015). Moreover, MS-153 has been found to upregulate both GLT-1 and xCT in amygdala and consequently reduced alcohol drinking and preference (Aal-Aaboda et al., 2015). Another study from our laboratory reported that ceftriaxone was able to reduce alcohol consumption in part by upregulating xCT and GLT-1 in the amygdala (Rao and Sari, 2014). Together, these studies demonstrated that targeting GLT-1 and xCT in the amygdala might provide promising therapeutic effect for potential attenuation of alcohol seeking behavior.

1.15 Hippocampus

The important role of memory formation on manifesting alcohol-seeking behavior has been found to be a critical in alcohol dependence. The contribution of hippocampus, the memory center, in promoting dependence to alcohol and other drugs of abuse is discussed across the literature (Adcock et al., 2006, Delgado and Dickerson, 2012, Aal-Aaboda et al., 2015). It is important to note that hippocampus is anatomically connected by its glutamatergic projections into NAc, PFC and amygdala, which suggest it role in drugs of abuse, including alcohol (Britt et al., 2012) (Figure 1-4). Moreover, several studies have reported that exposure to alcohol was associated with increased extracellular glutamate concentrations in the hippocampus (Moghaddam and Bolinao, 1994, Ward et al., 2009).

Interestingly, study suggest that lower doses of alcohol increase extracellular glutamate concentrations while the exposure to higher doses of alcohol leads to a decrease in extracellular glutamate concentrations (Moghaddam and Bolinao, 1994). There have been consistent reports of elevated extracellular glutamate concentrations in hippocampus following withdrawal from chronic alcohol exposure (Dahchour and Witte, 1999,

Dahchour and De Witte, 2003). Another study examined the effect of alcohol on the hippocampus reported death of newly formed neurons in the dentate gyrus (a subregion of hippocampus) of the adult rats after six weeks of moderate doses of alcohol (Herrera et al., 2003). In the same study, authors reported a relationship between decreased neurogenesis following alcohol exposure and impaired hippocampal-dependent cognitive functions. Similar findings were also reported in another study where chronic alcohol exposure disrupted hippocampal neurogenesis by decreasing neural progenitor cell proliferation, inhibiting cell survival and altering morphological maturation of newborn 90

neurons (He et al., 2005). In line with these reports, a reversible reduction in hippocampal volumes has also been demonstrated in human alcoholics using magnetic resonance imaging (MRI) (White et al., 2000).

1.15.1 Role of the glutamate receptors in the hippocampus in alcohol

dependence

Hippocampus widely expresses mGluRs and iGluRs (Khakpai et al., 2013, Pomierny-

Chamioło et al., 2014). Importantly, chronic exposure to alcohol induced upregulation of

NMDAR subunits (NR1, NR2A and NR2B) expression as well as function in rat hippocampus (Trevisan et al., 1994, Smothers et al., 1997). Moreover, a non-competitive

NMDAR antagonist, memantine, which has been widely reported to attenuate alcohol seeking, also prevented alcohol-associated increase in NMDAR expression in the hippocampus (Maler et al., 2005). However, the exact order of sequence is unknown whether the NMDAR normalization led to attenuation of alcohol seeking or vice-a-versa.

There has been consistent reports in the literature emonstrated that hippocampal NMDAR are sensitive to inhibitory effects of alcohol (Randoll et al., 1996, Yang et al., 1996,

Criswell et al., 2003), which eventually leads to attenuation of hippocampus-mediated

LTP (Blitzer et al., 1990, Morrisett and Swartzwelder, 1993, Givens and McMahon,

1995). Another study revealed that alcohol significantly reduced hippocampal LTP at concentrations required to inhibit response to NMDA (Blitzer et al., 1990). In addition to NMDAR, alcohol exposure can also affect AMPA and KA receptors in the hippocampus. Studies have revealed, that alcohol also has inhibitory effect on AMPA and KA receptors in the hippocampus (Martin et al., 1995, Weiner et al., 1999, Costa et 91

al., 2000, Crowder et al., 2002, Carta et al., 2003). In hippocampus, chronic alcohol exposure has been shown to increase the expression of AMPAR GluR-C subunit, without any changes in GluR-A and GluR2 subunits, in an in-situ hybridization study

(Brückner et al., 1997). In addition, deletion of GluR-C AMPAR subunit in the mesocorticolimbic areas including hippocampus has been shown to reduce cue-induced reinstatement of alcohol seeking behavior as well as alcohol deprivation effect in mice

(Sanchis-Segura et al., 2006). Although most of the studies on the effects of alcohol on hippocampus have been focused on iGluRs, there is substantial evidence demonstrating that alcohol also affects mGluRs signaling in the hippocampus. For example, examining the effect of chronic alcohol exposure on hippocampus in rats revealed a sub-region and sub-type specific changes in mGluR mRNA expression (Simonyi et al., 2004). This study reported that chronic alcohol led to a decrease in mGluR3 and mGluR5 mRNA expression in dentate gyrus sub-region of hippocampus. However, the same study found that chronic alcohol exposure reduced mGluR1, mGluR5 and mGluR7 mRNA expression with no effects on mGluR2, nGluR4 and mGluR8 in the CA3 sub-region of hippocampus. It is important to note that stimulation of mGluR2 has been found to reduce cue-induced reinstatement of alcohol-seeking behavior and that is mediated in part by increased c-fos gene expression in the hippocampus (Zhao et al., 2006). Moreover, it has been reported an increase in phosphoinositide hydrolysis through activating mGluR in hippocampal membranes isolated from offspring of rats treated with alcohol and this effect was associated with reduced binding activity of 3H-MK-801 to NMDAR (Valles et al., 1995). We suggest here that alcohol consumption as well as the reinstatement of alcohol exposure alter glutamate receptors expression and function in the hippocampus. 92

1.15.2 Role of the glutamate transporters in the hippocampus in alcohol

dependence

As mentioned earlier, studies reported an increase in the extracellular glutamate levels in the hippocampus following exposure to alcohol (Moghaddam and Bolinao, 1994, Ward et al., 2009). However, this effect could be attributed to either its diminished clearance of glutamate by the synaptic glutamate transporters or due to heightened release from the presynaptic glutamatergic terminals. Interestingly, a recent study from our laboratory reported that chronic exposure to alcohol decreased the expression of GLT-1 and xCT in the hippocampus (Aal-Aaboda et al., 2015) (Figure 1-5B). Accordingly, MS-153 has been found to reduce alcohol drinking and preference at least in part by increasing both

GLT-1 and xCT expression in the hippocampus (Aal-Aaboda et al., 2015). In another study, repeated high dose of alcohol, given orally, reduced the expression of hippocampal

GLT-1 but not xCT in the Wistar rats (Alshehri et al., 2017). Although these evidences point towards diminished glutamatergic clearance in the hippocampus is associated with chronic alcohol exposure, further studies are warranted to unravel the mechanisms involved in downregulatory effects of chronic alcohol exposure on hippocampal glutamate transporters.

1.16 Ventral Tegmental Area (VTA)

Dopaminergic connections between VTA and the other brain regions such as NAc and

PFC indicate the involvement of the VTA in the process of alcohol dependence (Brodie et al., 1990, Gatto et al., 1994, Ding et al., 2012). Additionally, VTA is innervated by the glutamatergic projections from the PFC, amygdala, pedunculopontine tegmentum, and 93

laterodorsal tegmentum (Geisler et al., 2007, Omelchenko and Sesack, 2007) (Figure1-4).

Importantly, glutamatergic neurons are also found in the VTA (Yamaguchi et al., 2007).

There has been controversial reporting on the effect of alcohol on the extracellular glutamate concentrations in the VTA. For examples in the first study, alcohol administration in naïve alcohol-preferring rats had no effect on extracellular glutamate concentrations in the VTA (Kemppainen et al., 2010). In a second study, a biphasic response of extracellular glutamate concentrations in the VTA after alcohol exposure was observed in rats. For example, lower dose of alcohol (0.5 g/kg) resulted in an increase in the extracellular glutamate concentrations in the VTA (Ding et al., 2012). This effect was not observed with moderate dose (1 g/kg) of alcohol in drug-naïve rats. However, higher doses of alcohol (2 g/kg) led to a significant decrease in the extracellular glutamate concentrations in the VTA in both alcohol-naïve as well as alcohol experienced rats (Ding et al., 2012). In the third study, a challenge dose of alcohol in rats repeatedly treated with morphine had no effect on extracellular glutamate concentrations (Ojanen et al., 2007). In the fourth study, alcohol at clinically relevant doses increased extracellular glutamate concentrations in the VTA. This effect was attributed due to the increase in the glutamatergic neurotransmission into the dopaminergic neurons in the VTA (Xiao et al.,

2009). Importantly, alcohol self-administration directly into the VTA has been found to be higher in P rats as compared to NP rats (Gatto et al., 1994). Taken together, alcohol exposure is associated with significant alterations of glutamate neurotransmission in the

VTA.

1.16.1 Role of the glutamate receptors in the VTA in alcohol dependence

Alcohol administration or voluntary consumption has been reported to increase the ratios of AMPA to NMDA currents in the VTA. This effect on the AMPA to NMDA ratio was associated either with an increase in AMPAR mediated excitatory synaptic transmission or a decrease in NMDAR mediated currents due to changes in their expression or functions (Stuber et al., 2008). Moreover, long-term alcohol exposure induced upregulation of NR1 subunit of NMDAR as well as GluR1 subunit of the AMPAR in the

VTA (Ortiz et al., 1995). This effect was not observed with the short-term alcohol exposure. These results were in agreement with a previous study showed that long-term alcohol exposure activated VTA neurons (Ortiz et al., 1995). In addition, exposure to alcohol has been shown to enhance NMDA plasticity in the VTA (Bernier et al., 2011).

Furthermore, alcohol’s inhibitory effect on synaptic transmission in the VTA is attributed to its inhibitory effect on NMDAR-mediated excitation (Stobbs et al., 2004).

Alternatively, pharmacologically blocking AMPA/KA receptors by intra-VTA microinjections with CNQX, an AMPA/KA receptor antagonist, attenuated alcohol seeking without affecting sucrose-intake in rats (Czachowski et al., 2012). This indicates that glutamatergic neurotransmission in the VTA is implicated in the development of alcohol-seeking behavior. Despite the important role of iGluRs in the VTA on the alcohol dependence process, little is known about the role of VTA mGluRs in alcohol dependence.

1.16.2 Role of the glutamate transporters in the VTA in alcohol dependence

It has been reported that alcohol during maintenance as well as deprivation reduced

GLAST expression but not xCT and GLT-1 in posterior VTA of female P rats (Ding et al., 2013). Since most studies reported a significant reduction in GLT-1 and xCT expression in other brain regions, studies are needed to verify the effect of alcohol on

GLT-1 and xCT in the VTA.

1.17 Human Studies

One of the most critical aspects in the field of alcohol addiction has been the learnings behaviors-associated with alcohol-dependent and alcohol-abstinent humans. Despite the high predictability of the neurobiological changes in human alcoholics from animal models of alcoholism, translating the effects of alcohol on the brains of animals into humans still remains debatable. Magnetic resonance spectroscopic (MRS) analysis in humans revealed that acute alcohol withdrawal increased extracellular glutamate concentrations in the prefrontocortical regions compared to the healthy control subjects

(Hermann et al., 2012). In another study employing Proton-MRS to examine the glutamate levels in the NAc, a significant higher glutamate concentration was found in alcohol-dependent subjects compared to controls. More interestingly, the combined glutamate and glutamine concentrations in the NAc and ACC exhibited a positive correlation with craving, measured using the Obsessive Compulsive Drinking Scale

(Bauer et al., 2013). However, the ACC glutamate concentrations are known to bounce back to normal during post-withdrawal period (Mon et al., 2012). Intriguingly, a study comparing heavy-drinking with light-drinking subjects found a negative correlation 96

between glutamate contents in the frontal white matter and the severity of alcohol dependence and loss of control over alcohol intake, suggesting that glutamate plays a critical role during transition from non-dependent heavy drinking to the state of dependence (Ende et al., 2013). It is important to note that glutamate-glutamine cycling in the brain has been suggested to be disrupted in alcohol dependent group compared to the control group (Thoma et al., 2011). In addition to the increase in the glutamate concentrations in the brain, an elevation in glutamate concentrations was also documented in the cerebrospinal fluid (CSF) of patients abstinence from alcohol for four weeks and this elevation was strongly correlated with the severity of alcohol dependence

(Umhau et al., 2010, Frye et al., 2016a). Acamprosate, a NMDAR antagonist, treatments reduced this alcohol-induced increase in CSF glutamate concentrations (Frye et al.,

2016a). However, another study reported that there is no change in glutamate concentrations in CSF of alcohol-dependent subjects as compared to control subjects

(Tsai et al., 1998). In another study examining the alcohol use pattern in humans diagnosed with depression concluded a positive association between glutamate concentrations in hippocampus and alcohol use (Hermens et al., 2015). These studies provide compelling evidence of dysregulated glutamatergic homeostasis, as demonstrated by altered glutamate concentrations in brain regions, during and post-withdrawal from

AUD.

Changes in glutamatergic receptors have also been found in humans with AUDs (Kryger and Wilce, 2010, Enoch et al., 2014, Laukkanen et al., 2014). Post-mortem whole- hemisphere autoradiographic analysis in Cloninger type 2 alcoholics, as compared to 97

control subjects, revealed an increase in AMPAR expression in the ACC (Kärkkäinen et al., 2013). Another study also reported a decrease in the mRNA as well as protein expression of GluR2 subunit of AMPAR in amygdala of alcoholics compared to controls

(Kryger and Wilce, 2010). An increase in GRIA4 (encoding GluA4) gene expression in alcoholics has also been reported (Enoch et al., 2014). Moreover, a single nucleotide polymorphism (SNP) in NMDAR-2B subunit (GRIN2B) was found to be critical in genetic susceptibility to earlier age of withdrawal in alcohol dependent patients (Paul et al., 2017). Human alcoholics also showed upregulation of GRIN2B (encoding GluN2B) and GRIN2D (encoding for GluN2D) compared to controls (Enoch et al., 2014).

Moreover, abstinent alcoholics with SNPs in the GRIN2C subunit of NMDAR demonstrated an increase in alcohol-stimulated neuronal activity in the ACC (which positively correlated with alcohol craving) and PFC (negatively associated with alcohol craving) (Bach et al., 2015). This was further confirmed in another study performed on over 1000 humans which revealed a strong association between genetic variations of

NR2B with development of alcohol dependence (Schumann et al., 2008). Similarly, abstinent alcoholics with SNPs in GIRK1, gene encoding for KARs, exhibited an increase in the neuronal activity in the PFC and OFC (Bach et al., 2015). Another study reported a decrease in the relative mRNA expression of NR1, NR2A and NR2B subunit in superior frontal and primary motor cortex in cirrhotic alcoholics compared to non- cirrhotic alcoholics, suggesting the involvement of NMDAR in alcohol-induced cirrhosis

(Ridge et al., 2008). A significant increase in GRIK3 (GluR7) gene expression has also been reported in alcoholics compared to controls (Enoch et al., 2014). This study concluded that NMDAR is implicated significantly in the development of alcohol 98

addiction. Like preclinical studies, increase in mGluR1/5 expression has been documented in hippocampus of type 1 alcoholics (non-genetic) as compared to either type 2 alcoholics (genetic) or healthy subjects (Kupila et al., 2013). Interestingly, post- mortem analysis of ACC from alcoholics also revealed a reduction in mGluR2 transcript levels (aminMeinhardt et al., 2013), and this decrease in mGluR2-mediated neurotransmission is thought to be critical in relapse to alcohol. Interestingly, in another study where the alcoholic subjects were sub-divided into type 1 and type 2, revealed an increase in mGluR2/3 in type 2 alcoholics as compared to controls assessed by radioligand binding technique (Laukkanen et al., 2014). Human alcoholics also have been found to have upregulation in the GRM3 (mGluR3) and GRM4 (mGluR4) (Enoch et al., 2014).

We and others have investigated extensively the effects of alcohol exposure on the glutamate transporters in animals. Not surprisingly, several studies have reported similar alterations in the glutamate transporters in humans as well. For example, microarray analysis of post-term basolateral amygdala from human alcoholics, compared to controls, revealed a significant downregulation of GLT-1 and GLAST (Kryger and Wilce, 2010).

On the contrary, upregulation of GLT-1 and EAAT3 was observed in white blood cells, during early and late withdrawal from alcohol in humans (Ozsoy et al., 2016). Another study reported a marked increase in GLAST expression in the PFC of chronic alcoholics, suggesting that this increase in GLAST protein levels is a compensatory mechanism to combat the increase of glutamate levels (Flatscher‐Bader and Wilce, 2006, 2008).

Additionally, a genetic variant of GLT-1 in humans, G603A, has been linked with risk- tasking behaviors and cirrhosis associated AUD (Sander et al., 2000, Foley et al., 2004).

Concluding remarks and future directions

Several studies have demonstrated alterations in glutamate neurotransmission in the mesocorticolimbic brain regions following alcohol exposure. It is well known that NAc receives glutamatergic inputs from PFC, amygdala and hippocampus. It is also reported that PFC sends as well as receives glutamatergic projections into VTA and from the hippocampus and amygdala. Amygdala and hippocampus also send glutamatergic projections into the PFC. The glutamatergic interactions between different central reward brain regions have been predominant focus in alcohol dependence research.

Importantly, significant alterations in mGluRs and iGluRs expression, and function have been reported in the mesocorticolimbic areas in animals exposed to alcohol. Moreover, studies have found that blocking or deleting specific glutamate receptors in the NAc,

PFC, striatum, amygdala, and hippocampus attenuated alcohol seeking behavior.

However, further studies are warranted to verify the role of AMPA and NMDA receptors as well as each subtype of mGluRs in each brain region for attenuating alcohol dependence, tolerance, relapse, withdrawal, and craving.

Additionally, chronic exposure to alcohol has been reported to reduce expression of major astroglial glutamate transporters (GLT-1 and xCT) in the NAc, amygdala and hippocampus but not in PFC. Moreover, attenuation of chronic and relapse-like alcohol 100

drinking has been associated with upregulation of GLT-1 and xCT expression in the

NAc, PFC, amygdala, and hippocampus. This indicates that stimulating these transporters in mesocorticolimbic area is critical for attenuating alcohol seeking behavior.

However, more studies are needed in the near future to evaluate the effects of long-term exposure to alcohol on the expression of GLT-1 and xCT in the striatum and VTA. This is important to provide evidence about the potential therapeutic effects of glutamate transporters upregulators in striatum and VTA for managing alcohol dependence.

Acknowledgments

The review article was written during the period of fund supported by Award Number

R01AA019458 (Y.S.) from the National Institutes on Alcohol Abuse and Alcoholism.

Authors would like to thank Rami M. Alzhrani for his technical assistance.

101

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Chapter 2

Chronic exposure to electronic cigarettes vapor-containing nicotine modulates nicotinic acetylcholine receptors and glial glutamate transporters in mesocorticolimbic brain regions of C57BL/6J mice

Fawaz Alasmari1, Laura Crotty E. Alexander2,3, Alaa M. Hammad1, Austin Horton4, Isaac T. Schiefer4, Christopher A. Drummond5, and Youssef Sari1,*

1Department of Pharmacology and Experimental Therapeutics, College of Pharmacy and Pharmaceutical Sciences, the University of Toledo, Toledo, OH 43614, USA. 2 Pulmonary and Critical Care Section, VA San Diego Healthcare System, 3350 La Jolla Village Dr, MC 111J, San Diego, CA 92161, USA. 3Department of Medicine, Division of Pulmonary and Critical Care, University of California at San Diego (UCSD), La Jolla, CA 92093, USA. 4Department of Medicinal and Biological Chemistry, College of Pharmacy and Pharmaceutical Sciences, the University of Toledo, Toledo, OH 43614, USA 5Department of Medicine, Division of Cardiovascular Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH 43614, USA.

Abbreviations: AC, air control; α-7 nAChR, alpha-7 nicotinic acetylcholine receptor; α4/β2 nAChR , alpha 4/ beta 2 nAChR; e-cigarettes, electronic cigarette; ECV, e- cigarette vehicle control; ECN, e-cigarettes-containing nicotine; FC, frontal cortex; GLAST, glutamate/aspartate transporter; GLT-1, Glutamate transporter-1; HIP, hippocampus; NAc, nucleus accumbens; PFC, prefrontal cortex; STR, striatum; VTA, ventral tegmental area; xCT, cystine/glutamate antiporter . * Corresponding authors: Dr. Youssef Sari University of Toledo, College of Pharmacy & Pharmaceutical Sciences Department of Pharmacology and Experimental Therapeutics Health Science Campus, 3000 Arlington Avenue, Toledo, OH 43614, USA E-mail: [email protected] Tel: 419-383-1507 Note: This paper will be submitted to a scientific journal.

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Abstract

Alterations in glutamate and dopamine neurotransmissions have been suggested to be involved in the development of nicotine dependence. Nicotine exposure increases the release of glutamate and dopamine in part through stimulatory effects on pre-synaptic nicotinic acetylcholine receptors (nAChRs). In addition, chronic exposure to nicotine reduced the expression of glutamate transporter 1 (GLT-1) and cystine/glutamate antiporter (xCT) in the nucleus accumbens (NAc). In the present study, we grouped female C57BL/6J mice into three groups; 1) Group 1 was exposed to electronic (e) cigarettes vapor-containing nicotine

(ECN); 2) Group 2 was exposed to e-cigarettes vehicle vapor (ECV); and 3) Control group 3 exposed to air only (AC). We investigated the effects of three months exposure to e-cigarettes vapor-containing nicotine on the protein expression of α7 nAChR, α4/β2 nAChR as well as the level of mRNA and protein of astroglial glutamate transporters, including GLT-1 and xCT in the frontal cortex (FC), striatum (STR), and hippocampus (HIP), as compared to AC and

ECV groups. We found that chronic inhalation of e-cigarette vapor-containing nicotine increased the protein expression of α7 nAChR and α4/β2 nAChR in the FC and STR. We also found that e-cigarettes vapor-containing nicotine increased α4/β2 nAChR but not α7 nAChR expression in the HIP. Additionally, the total GLT-1 relative mRNA and protein expression was decreased only in the STR. Moreover, GLT-1 isoform (GLT-1a and GLT-1b) expression was downregulated in the STR of mice exposed to ECN. However, inhalation of e-cigarettes vapor induced downregulatory effects on xCT in both STR and HIP compared to AC and

ECV groups. Finally, mass spectrometry detected high concentrations of cotinine in the FC and STR in ECN group. Our work provides information about the changes in the expression

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of nAChRs and astroglial glutamate transporters in specific mesocorticolimbic brain regions after three months exposure to nicotine-containing e-cigarette vapor.

Key words: E-cigarettes; Nicotine Dependence; α4/β2 nAChR; α-7 nAChR; GLT-1; xCT

2.1 Introduction

Emerging evidence indicates that the use of electronic (e) cigarettes is becoming common worldwide (Dockrell et al., 2013, Brown et al., 2014, McMillen et al., 2014).

Although tobacco companies and cigarettes users claim that e-cigarettes are a safe alternative to tobacco cigarettes, harmful effects have been observed with e-cigarettes exposure (Vardavas et al., 2012, Hwang et al., 2016, Yu et al., 2016). Recent studies found that e-cigarettes exposure induced initiating effects of cancer as well as DNA damage (Yu et al., 2016, Canistro et al., 2017). In addition, addictive behavioral effects have been found in subjects exposed to e-cigarettes for chronic period of time (Foulds et al., 2014, King et al., 2014, Etter and Eissenberg, 2015). E-cigarette dependence is found following long-term use of e-cigarettes (Foulds et al., 2014, Etter and Eissenberg,

2015). Passive exposure to e-cigarettes has been found to increase the desire to consume e-cigarettes or conventional cigarettes in smokers (King et al., 2014). Thus, finding molecular mechanisms or pathways that could be pharmacologically targeted to attenuate the use of e-cigarettes is critical. In this study, we determined the expression of three subtypes of nicotinic acetylcholine receptors (nAChRs) as well as the astroglial glutamate transporters in the frontal cortex (FC), striatum (STR) and hippocampus (HIP) in C57BL/6J mice exposed to e-cigarette vapor for three months.

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The release of glutamate and dopamine after exposure to nicotine is modulated by nAChRs in mesocorticolimbic areas (Tizabi et al., 2002, Tizabi et al., 2007,

Konradsson‐Geuken et al., 2009, Bortz et al., 2013). It is important to note that α7 nAChR and α4/β2 nAChR are mainly expressed in glutamatergic and dopaminergic neurons, respectively (Azam et al., 2002, Jones and Wonnacott, 2004). In addition, targeting α7 nAChR or α4/β2 nAChR has been found to reduce the effects of nicotine on glutamate or dopamine release (Cohen et al., 2003, Konradsson‐Geuken et al., 2009).

Recently, we found that six months exposure to e-cigarettes upregulated α7 nAChR in the FC and STR of female CD1 mice (Alasmari et al., 2017). Thus, changes in function or protein expression of these subtypes of nAChRs might affect glutamate/dopamine homeostasis after chronic exposure to e-cigarettes. This effect might contribute to the development or initiation of nicotine dependence. In this study, we investigated the effects of three months inhalation of e-cigarette vapor-containing nicotine on the protein expression of α7, α4 and β2 subtypes of nAChR in the FC, STR and HIP.

Studies have shown that glutamatergic systems are involved in the reinforcing effects of nicotine. Glutamate transporter-1 (GLT-1) was found to remove the majority of extracellular levels of glutamate into astrocytes (Tanaka et al., 1997, Danbolt, 2001).

Downregulation of GLT-1 and increases in the total extracellular concentration of glutamate have been observed in animals exposed to drugs of abuse (Melendez et al.,

2005, Das et al., 2015). GLT-1 is present in different isoforms in the brain; GLT-1a is expressed in neurons and astrocytes, while GLT-1b is localized in astrocytes (Berger et al., 2005, Holmseth et al., 2009). Although six-month inhalation of e-cigarette vapor- 130

containing nicotine reduced GLT-1 expression in the STR (Alasmari et al., 2017), little is known about the effects of chronic use of e-cigarettes-containing nicotine on GLT-1 isoforms in the mesocorticolimbic system. Thus, in the present study, we determined whether e-cigarettes vapor-containing nicotine has differential downregulatory effects on GLT-1 isoforms in the astrocytes and neurons of the FC, STR and HIP. In addition, xCT, another astroglial glutamate transporter, regulates the homeostasis of glutamate through exchange of intracellular glutamate for extracellular cystine (Moran et al.,

2005). Six month exposure to e-cigarette vapor reduced xCT expression in the STR and

HIP (Alasmari et al., 2017). However, the mRNA expression of GLT-1 and xCT following exposure to nicotine is not well elucidated. Thus, in this study, we investigated the effects of three-month exposure to e-cigarettes vapor-containing nicotine (ECN) on the mRNA and protein expression of astroglial glutamate transporters following chronic exposure to e-cigarette vapor.

Cotinine, a major metabolite of nicotine, is widely used as an indicator of smoking in humans (Wall et al., 1988, Acosta et al., 2004). Cotinine has longer half-life compared to nicotine, which suggests that cotinine is a potential biomarker that can be found in urine, plasma and the brain in subjects exposed to nicotine (Acosta et al., 2004, Chang et al., 2005, Katner et al., 2015, Alasmari et al., 2017). In the present study, we used liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantify the concentrations of cotinine in two critical brain areas, FC and STR, in mice exposed to e-cigarette vapor- containing nicotine for three months. This confirms whether our inhalation exposure was effective to deliver nicotine to the exposed mice. 131

2.2 Materials and Methods

2.2.1 E-cigarettes

E-cigarette cartomizers (tanks; 2.4 ohm, plastic, refillable) as well as the ingredients of e-liquids, including nicotine, propylene glycol and vegetable glycerin were acquired online from Xtreme Vaping. Preparation of -liquids were performed in our laboratory by adding 24 mg/mL nicotine to a mixture of 50% propylene glycol and 50% vegetable glycerin. This ratio is used in multiple marketed e-cigarettes devices. Specific batteries for e-cigarettes (280 mAh fixed, automatic, rechargeable, stainless steel) were bought online from FastTech. Briefly, the heating coil in e-liquid was applied by a voltage for 4 seconds every 20 seconds. E-cigarette vapor was generated by heating this coil using

2L/min negative pressure to draw the e-liquid from the atomizer.

2.2.2 Mouse inhalation of e-cigarette vapor

Female C57BL/6J mice at six-week old were purchased from Jackson Laboratories and were exposed to the SciReq inExpose system as recently described (Alasmari et al.,

2017). Nose-only e-cigarette vapor exposure was used in this study. Mice, at the age of

7–8 weeks, were divided into three groups; 1) Mice were exposed to e-cigarette vapor containing nicotine; 2) Mice were exposed to e-cigarette vehicle; and 3) Air control group. All groups were placed in the same restraints for 12 seconds/minute, for 60 132

minutes/day, five days/week, for three months. There was a 30 minute-recovery period in pre-warmed cages for all mice after restraint in the apparatus. Two hours after the last exposure, mice were euthanized by exsanguination, under general anesthesia (ketamine and xylazine). Note all animals were used in accordance with the NIH guidelines for animal use under protocols approved by the IACUC committee at the University of

California, San Diego and San Diego VA health system.

2.2.3 Brain Tissue Harvesting

Brains were extracted, immediately frozen, and kept at -80 °C until later analysis.

Stereotaxic coordinates from the Mouse Brain Atlas (Paxinos, 2007) were used to identify and dissect brain tissue samples (FC, STR and HIP). The isolated brain regions were stored in liquid nitrogen at -80°C for protein and mRNA expression testing assays, as well as LC-MS/MS analysis.

2.2.4 Quantitative PCR (qPCR) assay for detection of GLT-1,and xCT mRNA

expression

The mRNA expression of astroglial glutamate transporters for all tissue samples was investigated using a real-time quantitative PCR (RT-PCR) assay as described previously

(Hammad et al., 2017b). TRizol reagent (Invitrogen# 15596-018) was used to isolate total RNA from the portions of FC, STR, and HIP tissues. Reverse transcription (RT)

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was performed using a commercially available cDNA synthesis kit (Thermo Scientific, cat#AB-1453/A). Appropriate forward and reverse primers for the genes of interest were purchased from Invitrogen (Table 1.). A reaction mixture-containing primers,

SYBR Green (BIORAD, #170-8882) and cDNA samples were used with an iCycler real time PCR testing system (Bio-Rad laboratories, München, Germany). As described in a previous study (Livak and Schmittgen, 2001), the 2−ΔΔCT method was used to calculate and analyze the amount of mRNA for each sample based on threshold cycle number

(CT). This relative amount of mRNA for the genes of interest was compared between each group. The values of ΔCT were calculated by subtracting the average values of CT for the control gene (GAPDH) from the average values of CT for the nicotinic receptors and astroglial glutamate transporter genes. To calculate ΔΔCT, the mean ΔCT value of the AC group was subtracted from the mean values of ΔCT for the ECV and ECN groups. The ΔΔCT values for each group were further analyzed by 2−ΔΔCT to obtain the relative fold change from control for each gene of interest. The values of fold change were shown as mean ± SEM.

Table 2-1: shows primer sequences for each gene analyzed. These primer sequences are the GLT-1 primer sequence from (Tortarolo et al., 2004), The xCT primer sequence from (Gnana-Prakasam et al., 2009), and the GAPDH primer sequence from (Jiao et al., 2011). Gene Primer Sequence Forward primer 5′-AGCCGTGGCAGCCATCTTCATAGC-3′ GLT-1 Reverse primer 5′-ATGTCTTCGTGCATTCGGTGTTGGG-3′ Forward primer 5′-AAGTGGTTCAGACGATTATCAG-3′ xCT Reverse primer 5′-AAGAAACGTGGTAGAGGAATG-3′ Forward primer 5′-GGGTGGAGCCAAACGGGTC-3′ GAPDH Reverse primer 5′-GGAGTTGCTGTTGAAGTCGCA-3′ 134

2.2.5 Western blot assay for detection of α-4 nAChR, β-2 nAChR, α-7 nAChR,

GLT-1,GLT-1a, GLT-1b, and xCT protein expression

The changes in protein expression of α-4 nAChR, β-2 nAChR, α-7 nAChR, GLT-1, and xCT in the FC, STR, and HIP tissues were investigated using Western blot assay as described previously (Alasmari et al., 2015, Alasmari et al., 2016). Homogenization of brain samples from FC, STR, and HIP tissues were performed using a specific lysis buffer containing protease inhibitors. The Bio-rad DC (detergent compatible) protein assay (Bio-Rad, Hercules, CA, USA) was used to detect the total protein in each brain sample. After protein quantification, 10-20% polyacrylamide gels were loaded with similar amounts of protein from each tissue sample for electrophoretic separation. The transfer of protein into PVDF membranes was performed using transfer apparatus equipment. Different concentrations of 5% non-fat dry milk (for α -4/ β -2 /α -7 nAChRs) and 3% (for GLT-1, GLT-1 isoforms, xCT and GAPDH) in Tris-buffered saline with Tween-20 (TBST) were used to block PVDF membranes at room temperature for 30 minutes. Subsequently, the primary antibodies: rabbit anti-α-4 nAChR (1:1000,

Abcam), rabbit anti-β-2 nAChR (1:1000,Thermo Fisher Scientific), rabbit anti- α-7 nAChR (1:500,Abcam), guinea pig anti-GLT-1 (1:5000, Millipore), rabbit anti-GLT-1a

(1:5000, gift from Dr. Jeffery Rothstein at Johns Hopkins University), rabbit anti-GLT-1b

(1:5000, gift from Dr. Paul Rosenberg at Harvard Medical School) and rabbit anti-xCT

(1:1000, Abcam) were incubated with the membranes at 4̊C overnight. To control for the quantity of loading of proteins, mouse anti-GAPDH (1:5000, Millipore) was used. On

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the second day, membranes were washed five times with TBST followed by 30 minutes- blocking with 3% non-fat dry milk in TBST at room temperature. Horseradish peroxidase

(HRP) -labeled secondary antibodies (anti-rabbit IgG, anti-guinea pig IgG, or anti-mouse

IgG) at ratio of 1:3000 were incubated with the membranes for 90 minutes. Membranes were then further washed with TBST followed by drying on Whatman filter paper.

Commercial available chemiluminescence kits (Super Signal West Pico, Pierce Inc.) were used and applied to the membranes to detect the proteins of interest. Radiographic films

(HyBlot CL Film Thermo Fisher Scientific) were exposed to the membranes and these films were developed using an SRX-101A processor. MCID software was used to express the digitized image bands of proteins (α-4 nAChR, β-2 nAChR, α-7 nAChR,

GLT-1, GLT-1a, GLT-1b, xCT, and GAPDH). The values obtained from AC animals were represented as 100% to determine whether ECN or ECV induced changes in the expression for the proteins of interest in the FC, STR, and HIP as described in previous studies. One percent agarose gel was used to separate the bands of the mRNA data.

Images of the bands were taken using a digital camera (Canon) connected to a UV light apparatus (PhotoDoc-It UVP 50 Imaging System).

2.2.6 Ultra performance liquid chromatography- tandem mass spectrometry

(UPLC-MS/MS) for quantification of cotinine in the FC and STR

Brain samples, FC and STR, were spiked with an acidic solution containing a mixture of deuterated internal standards, homogenized, extracted using a solid phase resin, and analyzed using LC-MS/MS via multiple reactions monitoring (MRM) to quantitate 136

cotinine. Treatment duration, route, conditions, and identity of samples were blinded to the LC-MS experimenter. Briefly, FC and STR tissue (1-30 mg [n = 5-7]) was weighed and transferred to a 1.5 mL RINO tube (Next Advance Inc.) followed by addition of dH2O (200 µL, 0.05% formic acid [FA]) containing cotinine-d3 (250 nM) and diluted in ammonium acetate (200 µL at 10 mM). The solution was homogenized with The Bullet

Blender Storm (Next Advance Inc.) for 1 min (speed 8) followed by centrifugation at

14,000 rpm for 1 min. The supernatant was collected and applied to a solid phase extraction resin (Evolute Express WCX cartridge; size = 30 mg/1 mL [Biotage]) using a

Vacmaster manifold (Biotage). Cartridges were washed with ammonium acetate (500

µL at 50 mM), gravity flow for 5 min followed by application of vacuum for 1 min.

Cartridges were then washed with isopropyl ethanol (IPA) (125 µL), gravity flow for 5 min followed by application of vacuum for 1 min. Cartridges were then washed with dichloromethane (DCM) (500 µL), gravity flow for 5 min followed by application of vacuum for 5 min. Analytes were eluted with dH2O:IPA (85:15) +0.1 % FA (125 µL).

A 50 µL of the elutant was spiked with 20 µL of the IPA wash (cotinine elutes in IPA wash). Samples were then analyzed by LC-MS/MS via a Shimadzu Nexera XR UPLC coupled with a Shimadzu 8050 triple quadrupole mass spectrometer. The instrument was optimized for MRM transitions using analytical grade standards of dopamine, dopamine [1-13C], serotonin, serotonin-d4, nicotine, nicotine-d4, cotinine, cotinine-d3

(Sigma Aldrich and Cambridge Isotopes). UPLC utilized a Kinetex-core column

(Phenomenex): 2.6 µm HILIC 100 Å, 100 x 4.6 mm. UPLC Method: aqueous ammonium formate (5 mM, solvent A); acetonitrile:dH2O (9:1) (solvent B); flow rate

0.4 mL/min; Gradient: t = 0 min, 50 % B; t = 1.5 min, 50 % B; t = 2 min, 5 % B; t = 6 137

min, 5 % B; t = 6.1 min, 50 % B. Stop time 10 min. The resulting total ion chromatograms (TIC) for each MRM event demonstrated parent ion transition with two or three authentic fragment ions and were integrated to determine the area under the curve (AUC) of each analyte in each sample. Quantitation was carried out using a calibration curve and the ratio of the AUC of each analyte peak with the corresponding internal standard (AUCCot/ AUCCotd3). The calibration curve was prepared in blank sample of matrix (homogenized brain tissue) spiked with varying concentrations of each analyte (0.02 µM, 0.08 µM, 0.2 µM, 0.8 µM, 2 µM) and a fixed concentration of internal standard (0.25 µM for all except dopamine [750 µM]) with solid phase extraction as described above.

2.2.7 Statistical analyses

One-way ANOVA followed by Newman–Keuls post hoc tests were used to analyze mRNA, Western blot, and LC-MS/MS data between AC, ECV, and ECN groups. The expression of immunoblot bands were represented as 100% of AC group as done previously (Li et al., 2003, Raval et al., 2003, Miller et al., 2008, Zhang and Tan, 2011,

Simões et al., 2012, Hammad et al., 2017a). All statistical analysis tests used a p<0.05 level of significance.

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2.3 Results

2.3.1 Effects of exposure to e-cigarettes vapors on protein expression of α-4

nAChR in the FC, STR and HIP

One way ANOVA showed significant differences in the expression of α-4 nAChR among AC, ECV and ECN groups in the FC [F (2, 12) = 4.309 (p = 0.0389)], STR [F (2,

12) = 5.268 (p = 0.0228)] and HIP [F (2, 12) = 8.072 (p = 0.0060)]. As compared to

ECV group, Newman Keuls post-hoc multiple comparisons test revealed a significant increase in α-4 nAChR protein expression in all studied brain areas in ECN group (Fig.

2-1B).

Fig. 2-1. Effects of three month inhalation of e-cigarette vapor containing nicotine on relative (R) α-4 nAChR protein expression in the FC, STR and HIP. A) Expression of α-4 nAChR and GAPDH (loading control) blots in the FC, STR and HIP. B) Statistical analysis revealed a significant increase in α-4 nAChR protein expression in ECN as compared to AC in all studied brain areas as well as ECV groups in the STR and HIP. Values are represented as mean ± SEM (*p<0.05, **p<0.01), (n=5 for each group).

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2.3.2 Effects of exposure to e-cigarettes vapors on protein expression of β-2

nAChR in the FC, STR and HIP

We further investigated the protein expression of β-2 nAChR after three months of exposure to e-cigarette vapor. One way ANOVA analysis showed significant differences in β-2 nAChR mRNA and protein expression among AC, ECV and ECN groups in the

FC [F (2, 12) = 5.188 (p = 0.0238)], STR [F (2, 12) = 9.879 (p = 0.0029)] and HIP [F (2,

12) = 4.276 (p = 0.0396)]. Newman–Keuls multiple comparison test revealed that three- month inhalation of e-cigarette vapor increased β-2 nAChR protein expression in the

ECN group compared to the AC group in all studied brain areas (Fig. 2-2B).

Fig. 2-2. Effects of three month inhalation of e-cigarette vapor containing nicotine on relative (R) β-2 nAChR protein expression in the FC, STR and HIP. A) Expression of β-2 nAChR and GAPDH (loading control) blots in the FC, STR and HIP. B) Statistical analysis revealed a significant increase in β-2 nAChR protein expression in ECN as compared to AC in all studied brain areas as well as ECV groups in the STR. Values are represented as mean ± SEM (*p<0.05, **p<0.01), (n=5 for each group).

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2.3.3 Effects of exposure to e-cigarette vapors on protein expression of α-7

nAChR in the FC, STR and HIP

One-way ANOVA analysis revealed significant changes in the protein expression of α-7 nAChR among AC, ECV and ECN groups in the FC [F (2, 12) = 8.975 (p = 0.0041)] and STR [F (2, 12) = 6.288 (p = 0.0136)] but not in the HIP [F (2, 12) = 0.7276 (p =

0.5032)]. Newman–Keuls analysis showed that α-7 nAChR protein expression was significantly increased in the ECN group compared to the AC and ECV groups in both

FC and STR (Fig. 2-3B).

Fig. 2-3. Effects of three month inhalation of e-cigarette vapor containing nicotine on relative (R) α-7 nAChR protein expression in the FC, STR and HIP. A) Expression of α-7 nAChR and GAPDH (loading control) blots in the FC, STR and HIP. B) Statistical analysis revealed a significant increase in α-7 nAChR protein expression in ECN as compared to AC and ECV groups in the FC and STR but not in the HIP. Values are represented as mean ± SEM (*p<0.05, **p<0.01), (n=5 for each group).

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2.3.4 Effects of exposure to e-cigarette vapors on mRNA and protein expression

of GLT-1 in the FC, STR and HIP

The effects of nicotine-containing e-cigarette vapor exposure on GLT-1 mRNA and protein expression in the FC, STR and HIP were investigated. One-way ANOVA followed by Newman–Keuls analysis did not show any significant changes in GLT-1 mRNA expression in the FC [F (2, 12) = 0.4825 (p = 0.6287)] or HIP [F (2, 12) =

0.38941 (p = 0.6857)] (Fig. 2-4B&J) or GLT-1 protein expression in either FC [F (2, 12)

= 0.4556 (p = 0.6446)] or HIP [F (2, 12) = 0.208 (p = 0.8152)] (Fig. 2-4D&L). However, one way ANOVA indicated a significant difference in the striatal GLT-1 mRNA [F (2,

12) = 4.523 (p = 0.0344)] and protein [F (2, 12) = 5.462 (p = 0.0206)] expression in the

STR. Newman–Keuls test showed that three-month exposure to e-cigarette vapor- containing nicotine reduced striatal GLT-1 mRNA and protein expression compared to

AC and ECV groups (Fig. 2-4F&H).

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Fig. 2-4. Effects of three month inhalation of e-cigarette vapor containing nicotine on relative (R) GLT-1 mRNA and protein expression in the FC, STR and HIP. A) Expression of GLT-1 and GAPDH (loading control) transcript (RT-PCR) in the A) FC, E) STR and I) HIP. B) There were no significant changes in GLT-1 mRNA expression in ECN as compared to the control groups in the FC. F) A significant decrease in GLT-1 mRNA expression in ECN as compared to the control groups in the STR. J) There were no significant changes in GLT-1 mRNA expression in ECN as compared to the control groups in the HIP. Western blot bands for GLT-1 and GAPDH (loading control) in the C) FC, G) STR and K) HIP. D) There were no significant changes in GLT-1 protein expression in ECN as compared the control groups in the FC. H) A significant decrease in GLT-1 protein expression in ECN as compared to the control groups in the STR. L) There were no significant changes in GLT-1 protein expression in ECN as compared to the control groups in the HIP. Values are represented as mean ± SEM (*p<0.05), (n=5 for each group).

2.3.5 Effects of exposure to e-cigarette vapors on protein expression of GLT-1

isoforms in the FC, STR and HIP

We further determined the expression of GLT-1 isoforms in the FC, STR and HIP in

AC, ECV and ECN groups. One-way ANOVA analysis found no significant differences in GLT-1a expression in the FC [F (2, 12) = 1.024 (p = 0.3884)] or HIP [F (2, 12) =

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0.691 (p = 0.5200)] or GLT-1b expression in the FC [F (2, 12) = 0.00713 (p = 0.9929)] and HIP [F (2, 12) = 0.432 (p = 0.6591)] between the three groups. However, statistical analysis showed significant changes in the expression of GLT-1a [F (2, 12) = 7.536 (p =

0.0076)] and GLT-1b [F (2, 12) = 6.247 (p = 0.0138)] among AC, ECV and ECN groups in the STR. Newman–Keuls multiple comparisons showed a significant reduction in

GLT-1a and GLT-1b expression in ECN compared to the control groups in the STR

(Fig. 2-5F&H) but not in the FC (Fig. 2-5B&D) or HIP(Fig. 2-5J&L).

Fig. 2-5. Effects of three month inhalation of e-cigarette vapor containing nicotine on relative (R) GLT-1 isoforms protein expression in the FC, STR and HIP. A) Western blot bands for GLT-1a and GAPDH (loading control) in A) FC, E) STR and I) HIP. B) There were no significant changes in GLT-1a protein expression in ECN as compared to control groups in the FC. F) A significant decrease in GLT-1a protein expression in ECN as compared to the control groups in the STR. J) There were no significant changes in GLT-1a protein expression in ECN as compared to the control groups in the HIP. Western blot bands for GLT-1b and GAPDH (loading control) in C) FC, G) STR and K) HIP. D) There were no significant changes in GLT-1b protein expression in ECN as compared the control groups in the FC. H) A significant decrease in GLT-1b protein expression in ECN as compared to the control groups in the STR. L) There were no significant changes in GLT-1b protein expression in ECN as compared to the control groups in the HIP. Values are represented as mean ± SEM (*p<0.05, **p<0.01), (n=5 for each group).

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2.3.6 Effects of exposure to e-cigarette vapors on mRNA and protein expression

of xCT in the FC, STR and HIP xCT mRNA and protein expression following three-month inhalation of e-cigarette vapor-containing nicotine have been determined in the FC, STR and HIP. One way

ANOVA revealed that there were significant differences in xCT mRNA and protein expression among AC, ECV and ECN groups in the STR [F (2, 12) = 4.646 (p = 0.0321) for mRNA expression] and [F (2, 12) = 5.097 (p = 0.0250) for protein expression] and

HIP [F (2, 12) = 7.914 (p = 0.0064) for mRNA expression] and [F (2, 12) = 7.479 (p =

0.0078) for protein expression] but not in the FC [F (2, 12) = 0.0983 (p = 0.9071) for mRNA expression] and [F (2, 12) = 1.140 (p = 0.3520) for protein expression].

Newman–Keuls multiple comparison tests showed significant decreases in xCT mRNA expression in the ECN in the STR compared to both AC and ECV groups (Fig. 2-6F) as well as in the HIP (Fig. 2-6J) compared to ECV group. Statistical analysis also revealed a significant reduction in xCT protein expression in the STR and HIP in the ECN group compared to ECV and AC groups (Fig. 6H&I). There were significant changes in xCT mRNA and protein expression in the FC between all groups (Fig. 2-6B&D).

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Fig. 2-6. Effects of three month inhalation of e-cigarette vapor containing nicotine on relative (R) xCT mRNA and protein expression in the FC, STR and HIP. A) Expression of xCT and GAPDH (loading control) transcript (RT-PCR) in A) FC, E) STR and I) HIP. B) There were no significant changes in xCT mRNA expression in ECN as compared to the control groups in the FC. F) A significant decrease in xCT mRNA expression in ECN as compared to the control groups in the STR. J) A significant decrease in xCT mRNA expression in ECN as compared to the control groups in the HIP. Western blot bands for xCT and GAPDH (loading control) in the C) FC, G) STR and K) HIP. D) There were significant changes in xCT protein expression in ECN as compared the control groups in the FC. H) A significant decrease in xCT protein expression in ECN as compared to the control groups in the STR. L) A significant decrease in xCT protein expression in ECN as compared to the control groups in the HIP. Values are represented as mean ± SEM (*p<0.05), (n=5 for each group).

2.3.7 Determination of cotinine concentrations in the FC and STR

Quantitative LC-MS was used to detect cotinine concentrations in the FC and STR based on a standard calibration curve, which represents the area under the curve relationship of the labeled isotope of cotinine analytical standard (Cotinne-d3) at a specific concentration. One way ANOVA showed significant differences in the cotinine 146

concentrations among AC, ECV and ECN groups in the FC [F (2, 12) = 8.756, p =

0.0039] and STR [F (2, 12) = 5.074, p = 0.0220]. Newman–Keuls multiple comparison tests revealed that chronic exposure to e-cigarette vapor-containing nicotine was associated with significant cotinine concentrations in both FC and STR as compared to both AC and ECV groups (Fig. 2-7C).

Fig. 2-7. LC-MS/MS analysis of cotinine in the FC and STR tissue samples. A) Representative chromatograms of each group for FC brain samples. B) Representative chromatograms for each group for STR brain samples. C) Quantitation based on the ratio of the AUC of the MRM transitions of cotinine and cotinine-d3 relative to a calibration curve. Concentrations were calculated after normalizing for tissue weight (assuming tissue/plasma density = 1). Values of ECN group are represented as mean ± SEM and compared to AC and ECV groups. Values are represented as mean ± SEM (*p<0.05, **p<0.01), (n=5 for each group).

2-4 Discussion

In the present study, the effects of three-month exposure to e-cigarette vapor containing nicotine on the expression of nicotinic receptor and astroglial glutamate transporters were investigated in the FC, STR, and HIP. We found that nicotine-containing e-cigarette vapor exposure induced upregulatory effects on nicotinic receptors in mesocorticolimbic 147

brain areas. Additionally, we report here that chronic inhalation of e-cigarette vapor reduced astroglial glutamate transporter mRNA and protein expression in specific brain areas. The cotinine data indicate that our inhalation machine system delivers e-cigarette vapor that results in nicotine reaching mesocorticolimbic brain regions.

Nicotinic receptors are distributed in pre- and post-synaptic neurons in the brain and the stimulation of these receptors has been found to induce dopamine and glutamate release

(Tizabi et al., 2002, Tizabi et al., 2007, Bortz et al., 2013). Studies found that chronic subcutaneous administration of nicotine, as well as intravenous infusion of nicotine, increased α4/β2 nAChR expression in the central limbic areas (Alsharari et al., 2015,

Fasoli et al., 2016). In this study, we found that three-month inhalation of e-cigarette vapor containing nicotine upregulated α4/β2 nAChR in the FC, STR, and HIP as well as

α7 nAChR in the FC and STR. It is important to note that chronic exposure to e-cigarette vapor and tobacco smoke increased the binding sites of α4/β2 nAChR in the cortex, nucleus accumbens (NAc), and hippocampus of mice (Ponzoni et al., 2015). Moreover, six month exposure to e-cigarette vapor induced upregulatory effects on α7 nAChR in the

FC and STR in female CD1 mice (Alasmari et al., 2017). These findings indicate that nicotine-containing e-cigarette vapor has upregulatory effects on the nicotinic receptors in mesocorticolimbic areas.

Glutamate homeostasis is regulated by astroglial glutamate transporters, including GLT-1 and xCT (Danbolt, 2001) and the expression of these transporters are decreased in the

NAc following exposure to ethanol, cocaine, and nicotine (Knackstedt et al., 2009, 148

Goodwani et al., 2015, Hakami et al., 2016, Hammad et al., 2017b). Chronic inhalation, or intravenous self-administration, of nicotine reduced GLT-1 and xCT expression in the brain areas in the mesocorticolimbic system (Knackstedt et al., 2009, Alasmari et al.,

2017). A recent study from our laboratory reported that e-cigarette vapor exposure for six months reduced GLT-1 in the STR and xCT in the STR and HIP (Alasmari et al.,

2017). We report here that e-cigarette vapor exposure reduced mRNA and protein expression of GLT-1 in the STR, and xCT in the STR and HIP. Our data suggest that nicotine affects the mRNA level of these transporters and consequently the number of astroglial transporters. A previous study from our laboratory reported that chronic exposure to drugs of abuse, such as cocaine, decreased the relative mRNA level of GLT-

1 and xCT in the NAc (Hammad et al., 2017b). These data indicate that chronic exposure to nicotine suppresses mRNA of glial glutamate transporters and consequently reduces the expression of these proteins on the surface of astrocytes. Thus, nicotine-containing e- cigarette vapor exposure might reduce the expression of astroglial glutamate transporters in the STR and HIP through transcription mechanisms. Additionally, we found that inhalation of vapor containing nicotine induced downregulatory effects in GLT-1 isoforms (GLT-1a and GLT-1b) only in the STR. This suggests that chronic exposure to nicotine reduces GLT-1 and its isoforms in astrocytes.

In our study, LC-MS/MS showed significant concentrations of cotinine in the FC and

STR, which indicates the effectiveness of our computerized inhalation exposure system for nicotine delivery, absorption, and transport into the brains of animals through inhalation of e-cigarette vapor [For review see (Alasmari et al., 2018)]. This also 149

indicates that nicotine is metabolized into cotinine and the metabolite is accumulated in the mesocorticolimbic brain regions. Since the same mesh restraints were used with AC,

ECV, and ECN groups, the exposure to the vapor of e-cigarettes in the environment

(fume hood) might lead to very low concentrations of cotinine in the STR of both control groups.

2.5 Conclusion

Our work reveals that a clinically and physiologically relevant exposure to nicotine through e-cigarette vapor exposure induced changes in the expression of nicotinic receptors and glial glutamate transporters in the brain. These alterations might mediate the initiation and development of nicotine dependence. Further research is required to study the relationship between the alterations in nicotinic receptors and glutamate transporters with glutamate/dopamine homeostasis in the mesocorticolimbic brain reward regions.

Acknowledgements/Funding

This work was supported in part by the National Institutes of Health (R01AA019458 to

Y.S.), (1F32DK104615-01 to CAD), Veterans Affairs BLR&D Career Development

Award (1IK2BX001313 to LCA), a UAB-UCSD O’Brien Center Daniel O’Connor

Scholar Award (P30DK079337 to LCA), AHA Beginning Grant-in-aid

(16BGIA27790079 to LCA), and an ATS Foundation Award to LCA. Authors thank the

Shimadzu Laboratory for Pharmaceutical Research Excellence at The University of

Toledo for Mass spectrometry instrumentation used in this study. The authors thank Dr. 150

J. Rothstein and Dr. P. Rosenberg for providing us with GLT-1a and GLT-1b antibodies, respectively. Authors would like to thank Dr. F. Scott Hall for allowing us to use the gel imaging system for our agarose gel images. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of

Health.

Conflict of Interest

The authors declare no conflict of interest.

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Chapter 3

Effects of Chronic Inhalation of Electronic Cigarettes Containing Nicotine on Glial Glutamate Transporters and α-7 Nicotinic Acetylcholine Receptor in Female CD-1 Mice Fawaz Alasmaria,#, Laura E. Crotty Alexanderb, c#, Jessica A. Nelsond, Isaac T. Schieferd, Ellen Breene, Christopher A. Drummondf, Youssef Saria,* # Equal contribution to the experiments aDepartment of Pharmacology and Experimental Therapeutics, College of Pharmacy and Pharmaceutical Sciences, the University of Toledo, Toledo, OH 43614, USA. b Pulmonary and Critical Care Section, VA San Diego Healthcare System, 3350 La Jolla Village Dr, MC 111J, San Diego, CA 92161, USA. c Department of Medicine, Division of Pulmonary and Critical Care, University of California at San Diego (UCSD), La Jolla, CA 92093, USA. d Department of Medicinal and Biological Chemistry, College of Pharmacy and Pharmaceutical Sciences, the University of Toledo, Toledo, OH 43614, USA. eDepartment of Medicine, Division of Physiology, UCSD, La Jolla, CA 92093, USA. fDepartment of Medicine, Division of Cardiovascular Medicine, College of Medicine and Life Sciences, University of Toledo, Toledo, OH 43614, USA.

Abbreviations: α-7 nAChR, alpha-7 nicotinic acetylcholine receptor; e-cigarettes, electronic cigarette; FC, frontal cortex; GLAST, glutamate/aspartate transporter; GLT-1, Glutamate transporter-1; HIP, hippocampus; NAc, nucleus accumbens; PFC, prefrontal cortex; STR, striatum; VTA, ventral tegmental area; xCT, cystine/glutamate antiporter . * Corresponding authors: Dr. Youssef Sari University of Toledo, College of Pharmacy & Pharmaceutical Sciences Department of Pharmacology and Experimental Therapeutics Health Science Campus, 3000 Arlington Avenue, Toledo, OH 43614, USA E-mail: [email protected] Tel: 419-383-1507

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Note: This article was published in Progress in Neuro-Psychopharmacology and Biological Psychiatry: Volume: 77 (Year: 2017): Pages 1-8.

Abstract

Alteration in glutamate neurotransmission has been found to mediate the development of drug dependence, including nicotine. We and others, through using western blotting, have reported that exposure to drugs of abuse reduced the expression of glutamate transporter-1 (GLT-1) as well as cystine/glutamate antiporter (xCT), which consequently increased extracellular glutamate concentrations in the mesocorticolimbic area. However, our previous studies did not reveal any changes in glutamate/aspartate transporter (GLAST) following exposure to drugs of abuse. In the present study, for the first time, we investigated the effect of chronic exposure to electronic (e)-cigarette vapor containing nicotine, for one hour daily for six months, on GLT-1, xCT, and GLAST expression in frontal cortex (FC), striatum (STR), and hippocampus (HIP) in outbred female CD1 mice. In this study, we also investigated the expression of alpha-7 nicotinic acetylcholine receptor (α-7 nAChR), a major pre-synaptic nicotinic receptor in the glutamatergic neurons, which regulates glutamate release. We found that inhalation of e-cigarette vapor for six months increased α-7 nAChR expression in both FC and STR, but not in the HIP. In addition, chronic e-cigarette exposure reduced GLT-1 expression only in STR. Moreover, e-cigarette vapor inhalation induced downregulation of xCT in both the STR and HIP. We did not find any significant changes in GLAST expression in any brain region. Finally, using liquid chromatography-tandem mass spectrometry (LC-

MS/MS) techniques, we detected high concentrations of nicotine and cotinine, a major metabolite of nicotine, in the FC tissues of e-cigarette exposed mice. These data provide

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novel evidence about the effects of chronic nicotine inhalation on the expression of key glial glutamate transporters as well as α-7 nAChR. Our work may suggest that nicotine exposure via chronic inhalation of e-cigarette vapor may be mediated in part by alterations in the glutamatergic system.

Key words: E-cigarettes; α-7 nAChR; GLT-1; xCT; Cotinine.

3.1 Introduction

Electronic (e)-cigarettes are battery operated nicotine delivery devices that heat and aerosolize e-liquid, creating vapor [For review (Hahn et al., 2014)]. Most e-liquid on the market contains nicotine, thus users who are inhaling e-cigarette vapor are also inhaling nicotine (Crotty Alexander et al., 2015). Recently, e-cigarette use has increased globally as an alternative or supplement to conventional tobacco cigarette use (Yamin et al.,

2010, Crotty Alexander et al., 2015, Schoenborn and Gindi, 2015). Emerging evidence demonstrates that exposure to e-cigarettes may induce several toxicological effects, including inflammation, decreased host defenses and DNA damage that is a precursor to neoplastic transformation (Vardavas et al., 2012, Hwang et al., 2016, Yu et al., 2016).

Although e-cigarettes were invented as a smoking cessation tool, they have been demonstrated to confer similar urges to smoke, as compared to conventional smoking

(King et al., 2014). Withdrawal symptoms and high desire to smoke were associated with withholding of e-cigarettes (Dawkins et al., 2012). E-cigarettes deliver smaller amounts of nicotine per puff as compared to tobacco cigarettes, however, similar

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systemic nicotine and cotinine concentrations to combustible cigarettes have been achieved after exposure (Schroeder and Hoffman, 2014). It has been reported that some brands of e-cigarettes can deliver higher nicotine levels as compared to combustible cigarettes (Ramôa et al., 2015). Exposure to nicotine containing e-cigarette vapor during late prenatal and early postnatal life induced significant persistent behavioral alterations during adulthood compared to vehicle control (e-cigarettes without nicotine) and air-control mice (Smith et al., 2015).

In the present study, we investigated the effects of chronic exposure to e-cigarette vapor containing nicotine, using a well-established, clinically relevant mouse exposure system, on the glutamatergic system in female CD-1 mice. The rationale for using female, not male, mice in this study is that previous studies found that female animal models showed higher nicotine seeking behavior compared to male models (Donny et al., 2000,

Torres et al., 2009). In addition, a prior study found that female rats exhibited higher motivation to consume nicotine as compared to male and female ovariectomized rats

(Donny et al., 2000). This suggests that hormones, including estradiol, play a crucial role in nicotine seeking behavior. Moreover, nicotine rewarding effects have been enhanced in female rats as compared to male rats (Torres et al., 2009).

Nicotinic acetylcholine receptors (nAChRs), including alpha-7 nAChR (α-7 nAChR), have been found to be upregulated or stimulated following exposure to nicotine (Auta et al., 2000, Buisson and Bertrand, 2001, Konradsson‐Geuken et al., 2009, Alsharari et al.,

2015). Importantly, α-7 nAChR is localized mainly in pre-synaptic glutamatergic 160

neurons in the mesocorticolimbic areas (Marchi et al., 2002, Jones and Wonnacott,

2004, Feduccia et al., 2012) and this receptor has been found to modulate the majority of glutamate release in prefrontal cortex (PFC) and other brain regions following nicotine exposure (Konradsson‐Geuken et al., 2009, Feduccia et al., 2012, Bortz et al., 2013).

However, there is little known about the effects of chronic nicotine exposure on α-7 nAChR expression. We here, for the first time, determined the expression of α-7 nAChR in frontal cortex (FC), striatum (STR) and hippocampus (HIP) following six months of inhalation of e-cigarette vapor containing nicotine in female CD-1 mice.

Additionally, we and others have shown that chronic exposure to drugs of abuse reduced the expression of glutamate transporter-1 (GLT-1,) as well as cystine/glutamate antiporter (xCT) in the nucleus accumbens (NAc), HIP and amygdala (Knackstedt et al.,

2009, Knackstedt et al., 2010, Alhaddad et al., 2014a, Alhaddad et al., 2014b, Aal‐

Aaboda et al., 2015). It is important to note that GLT-1 is responsible for clearance of a majority of the extracellular glutamate concentration into astrocytes (Tanaka et al., 1997,

Danbolt, 2001). Decreased GLT-1expression was associated with significantly increased extracellular glutamate concentrations in the NAc in animals exposed to alcohol or heroin (Melendez et al., 2005, LaLumiere and Kalivas, 2008, Shen et al.,

2014, Das et al., 2015). In addition, xCT plays a crucial role in glutamate homeostasis by exchanging extracellular cystine for intracellular glutamate (Baker et al., 2002, Shih et al., 2006). Moreover, the xCT system was found to be involved in attenuation of nicotine seeking (Knackstedt et al., 2009). Glutamate/aspartate transporter (GLAST) is another glutamate transporter, co-localized with GLT-1 in astrocytes, and is mainly 161

expressed in the cerebellum and retina (Lehre and Danbolt, 1998, Danbolt, 2001).

Although we did not observe any downregulation in GLAST expression following alcohol drinking for five weeks (Alhaddad et al., 2014b, Hakami et al., 2016), we aimed in this study to determine whether chronic nicotine exposure may affect the expression of this glial glutamate transporter in the central reward brain regions. In the present study, the expression of GLT-1, xCT, and GLAST after six months of exposure to e- cigarette vapor containing nicotine was investigated in the FC, STR and HIP.

Several studies have detected nicotine and cotinine (the major metabolite and biomarker of nicotine) in plasma and urine (Hengen and Hengen, 1978, Curvall et al., 1982,

Horstmann, 1985, Degen and Schneider, 1991, Mercelina-Roumans et al., 1996, Acosta et al., 2004, Chang et al., 2005, Levine et al., 2013). Few studies have assessed the concentration of nicotine and cotinine in specific brain regions, such as NAc and STR

(Chang et al., 2005, Katner et al., 2015). However, there is little known about the bioavailability of nicotine in the brain following six months of inhalation of e-cigarettes vapor. As compared to other routes of administration, nicotine inhalation has a fast and high rate of absorption as well as high rate of brain distribution [For review see (Le

Houezec, 2003)]. Detection of high concentrations of nicotine and cotinine in the brain during chronic nicotine inhalation might suggest the degree of nicotine exposure associated with any changes in the glutamatergic system. In this study, Western blotting was used to quantify changes in the amount of proteins that are expressed in neurons and glia in different brain regions for air control and e-cigarette vapor containing nicotine

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groups. In addition, we determined nicotine and cotinine concentrations in the FC following six months of exposure to e-cigarette vapor.

3.2 Materials and Methods

3.2.1 E-cigarettes

All e-cigarette atomizers (tanks; 2.4 ohm, plastic, refillable) and e-liquids (propylene glycol, vegetable glycerin, nicotine, with no additives) used in the study were bought online from Xtreme Vaping. E-liquids were prepared in the lab by mixing 50% propylene glycol, 50% vegetable glycerin, and 24 mg/mL nicotine. This composition is commonly used in multiple brands of e-cigarettes as well as with users who make their own e-cigarettes. E-cigarette batteries (280 mAh fixed, automatic, rechargeable, stainless steel) were purchased online from FastTech. Fresh e-cigarette vapor was used for all murine exposures, as described previously (Hwang et al., 2016). Briefly, voltage was applied to the heating coil in the e-liquid for 4 seconds every 20 seconds, and at the same time 2L/min negative pressure was applied to draw the e-liquid through the atomizer, creating the e-cigarette vapor.

3.2.2 Mouse inhalation of e-cigarette vapor

Six week old, female CD-1 mice were obtained from Jackson Labs. CD-1 mice are outbred, and thus have higher genetic diversity than most mouse lines. Significant findings in this mouse line are thought to have more clinical relevance, as their genetic diversity leads to more heterogeneity in the results, requiring a more powerful signal to reach significance. The inExpose system (SciReq) was used as previously described 163

(Hwang et al., 2016) to provide nose-only e-cigarette vapor for inhalation, thus limiting the exposure to the respiratory system. Both e-cigarette and control mice are placed into the soft-mesh inExpose restraints for 60 minutes per day, five days per week, but the control mice breath room air only. At the age of 7–8 weeks, e-cigarette mice were exposed to e-cigarette vapor containing 24 mg/mL nicotine for 12 seconds per minute, for 60 minutes per day, five days per week, for six months.(Smith et al., 2015,

Drummond et al., 2016, Hwang et al., 2016)Control mice were placed in the same restraints, but breathed room air only (Air control group). To create appropriate experimental controls, air control and e-cigarette exposed mice were placed into identical, individual mesh restraints. Although the air control group was intended to only breathe air, they were placed into the same hood as the e-cigarette mice attached to the

InExpose device, to ensure similar temperature, light and sound exposures. Mice were allowed to recover for 30 minutes in pre-warmed cages following restraint. Mice were euthanized 1-2 hours after the last treatment with terminal intracardiac bleeding, under general anesthesia [100mg/kg ketamine (Zoetis) and 10mg/kg xylazine (Vedco)]. Note all animals were used in accord with the NIH guidelines for animal use under protocols approved by the IACUC committee at the University of California, San Diego and San

Diego VA health system.

3.2.3 Brain Tissue Harvesting

Brains were gently removed from the skull. Specific brain regions, including FC, STR and HIP, were dissected according to stereotaxic coordinates from the Mouse Brain

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Atlas (Paxinos, 2007). Brain sections were immediately snap frozen in liquid nitrogen and stored at -80°C for immunoblot testing.

3.2.4 Western blot protocol for detection of α-7 nAChR, GLT-1, xCT and GLAST

Western blotting was used to quantify changes in the expression of α-7 nAChR, GLT-1, xCT, GLAST and GAPDH in FC, STR and HIP tissues between e-cigarette and air control groups, as described previously (Alasmari et al., 2015, Alasmari et al., 2016a,

Hakami et al., 2016). Brain tissues (FC, STR and HIP) were homogenized in lysis buffer-containing protease inhibitors. Total protein in each homogenized brain sample was quantified using Bio-Rad quantification reagents, DC™ (detergent compatible) protein assay (Bio-Rad, Hercules, CA, USA). Equal amounts of protein from FC, STR, and HIP tissue samples were loaded on 10-20% polyacrylamide gels for electrophoretic separation. Proteins were transferred to PVDF membranes, which were blocked using

5% (α -7 nAChR) or 3% (GLT-1, xCT, GLAST and GAPDH) milk in Tris-buffered saline with Tween-20 (TBST) for 30 minutes at room temperature. Membranes were incubated at 4°C overnight with one of the following primary antibodies: rat anti- α-7 nAChR (1:500 Abcam), guinea pig anti-GLT-1 (1:5000 Millipore), rabbit anti-xCT

(1:1000 Abcam), and rabbit anti-GLAST (1:5000 Abcam). Mouse anti-GAPDH (1:5000

Millipore) was used as the loading control. On the following day, the membranes were washed with TBST and blocked with 3% milk in TBST for 30 minutes at room temperature, followed by incubation with horseradish peroxidase-labeled (HRP)

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secondary antibodies (anti-rat IgG, anti-guinea pig IgG, anti-rabbit IgG or anti-mouse

IgG) at 1:3000 for 90 minutes. The membranes were washed five times with TBST and dried. Chemiluminescence was detected using a commercially available kit (Super

Signal West Pico, Pierce Inc.) applied to the dried membranes for one minute prior to exposure. An SRX-101A processor was used to develop the radiographic films (HyBlot

CL Film Thermo Fisher Scientific) that were exposed to membranes incubated with chemiluminescence reagent. The digitized images of the α-7 nAChR, GLT-1, xCT,

GLAST and GAPDH bands were quantified and assessed using MCID software. The data obtained from air control animals were used as 100% to focus on changes in the expression of studied proteins in brain regions of animals exposed to e-cigarette vapor containing nicotine.

3.2.5 Quantitation of Nicotine and Cotinine via ultra-performance liquid

chromatography- tandem mass spectrometry (UPLC-MS/MS).

As described below, a portion of the FC was spiked with extraction buffer containing

LC-MS internal standards, homogenized, extracted using a solid phase resin, and analyzed using LC-MS/MS via multiple reaction monitoring (MRM) to quantitate nicotine and cotinine. Treatment duration, route, conditions, and identity of samples were blinded to the LC-MS experimenter. Briefly, FC tissue (10-30 mg [n = 12]) was weighed and transferred to a 1.5 mL RINO tube (Next Advance Inc.) followed by addition of tissue extraction reagent (100 µL [Invitrogen] containing a protease inhibitor cocktail [Sigma]) and a solution of ammonium acetate (200 µL at 50 mM) containing two internal standards at a fixed concentration, Cotinine-d3 (5 µM) and Nicotine-d4 (5

166

µM). The solution was homogenized with The Bullet Blender Storm (Next Advance

Inc.) for 1 min (speed 8) followed by centrifugation at 13,500 rpm for 2 min. The supernatant was collected, the remaining pellet washed with ammonium acetate (200 µL at 50 mM), centrifuged at 13,500 rpm for 2 min, and the combined supernatants applied to a solid phase extraction resin (Evolute Express WCX cartridge; size = 30 mg/1 mL

[Biotage]) using a Vacmaster manifold (Biotage). Cartridges were washed with ammonium acetate (1 mL at 50 mM), analytes eluted with methanol (1 mL) and evaporated to dryness via high flow purge with argon. Samples were reconstituted in

100 μL of 95:5 (ammonium acetate/methanol) for LC-MS analysis via a Shimadzu

Nexera XR UPLC coupled with a Shimadzu 8050 triple quadrupole mass spectrometer.

The instrument was optimized for MRM transitions using analytical grade standards of

Cotinine, Nicotine, Cotinine-d3, and Nicotine-d4 (Sigma Aldrich and Cambridge

Isotopes). UPLC utilized a Kinetex-core column (Phenomenex): 2.6 um C18 100 Å,

100 x 4.6 mm. UPLC Method: aqueous ammonium acetate (10mM, solvent A); methanolic Ammonium Acetate (10mM, solvent B); flow rate 1.0 mL/min (utilized post-column T-split, MS effective flow-rate = 0.3 mL/min). Gradient: t = 0 min, 0% B; t

= 4 min, 95% B; t = 5.50 min, 95% B; t = 5.51, 0% B. Stop time 10 min. The resulting total ion chromatograms (TIC) for each MRM event demonstrated parent ion transition to three qualified fragment ions and were integrated to determine the area under the curve (AUC) of each analyte in each sample. Quantitation was carried out using a calibration curve and the ratio of the AUC of each analyte peak with the corresponding internal standard (AUCNic/AUCNicd4 and AUCCot/ AUCCotd3).

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Forebrain tissue was spiked with varying concentrations of each analyte (Nicotine and

Cotinine at 0.05, 0.1, 1, 5, and 10 µM) and processed as described for experimental samples above. A calibration curve was generated and extraction efficiency calculated based on the ratio of the AUC of the analyte peak to the AUC of the corresponding internal standard peak. The calibration curve was used to calculate concentration of analytes after normalization according to the weight of FC tissue used in each instance.

Cotinine levels in serum were assessed via cotinine ELISA (Calbiochem), following the standard protocol and using a standard curve.

3.2.6 Statistical analyses:

Western blot data obtained for proteins of interest in FC, STR and HIP tissues between e-cigarette and air control groups were analyzed using an independent unpaired t-test.

The densities of immunoblot bands from the air control group were defined as 100%.

LC-MS data analysis used one-way ANOVA with Tukey’s post-test. All statistical analyses were represented as a p<0.05 level of significance.

3.3 Results

3.3.1 Effects of e-cigarettes on α-7 nAChR expression in the FC, STR and HIP

We determined the expression of α-7 nAChR following six months of e-cigarette vapor inhalation in the FC, STR and HIP. Unpaired t-test analyses showed an increase in the expression of α-7 nAChR in both FC (p<0.01; Fig. 3-1) and STR (p< 0.05; Fig. 3-1) in the e-cigarette group as compared to air controls. However, unpaired t-test analyses did not show any changes in α-7 nAChR in HIP (p> 0.05; Fig. 3-1). 168

Fig. 3-1. Effects of six months exposure to e-cigarette vapor (e-Cig) containing nicotine on the relative (R) α-7 nAChR expression in the FC, STR and HIP in female CD-1 mice. A) Immunoblot bands for α-7 nAChR and GAPDH (loading control) expression in the FC, STR and HIP. B) Unpaired t-test analysis of immunoblots showed a significant increase in the ratio of α-7 nAChR / GAPDH in FC and STR, but not in HIP, in e-cigarette exposed mice as compared with air controls (control value set to 100%). Data are shown as mean ± SEM (**p<0.01; *p<0.05), (n=4-5 for each group).

3.3.2 Effects of e-cigarettes on GLT-1 expression in the FC, STR and HIP

We investigated the effects of chronic e-cigarette use on the expression of GLT-1 in FC,

STR and HIP brain regions. E-cigarette vapor inhalation reduced GLT-1 expression in

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the STR significantly, as compared to air controls (p< 0.05; Fig. 3-2). However, six months of exposure to e-cigarettes did not induce significant alterations in GLT-1 expression in either the FC or HIP (p> 0.05; Fig.3- 2).

Fig. 3-2. Effects of six months of inhalation of e-cigarette vapor containing nicotine (e- Cig) on the relative (R) GLT-1 expression in the FC, STR and HIP in female CD-1 mice. A) Immunoblot bands for GLT-1 and GAPDH (loading control) expression in the FC, STR and HIP. B) Unpaired t-test analysis of immunoblots showed a significant decrease in the ratio of GLT-1 / GAPDH in STR, and not significant in FC and HIP, in e- cigarette exposed mice compared with air controls (control value set to 100%). Data are shown as mean ± SEM (*p<0.05), (n=4-5 for each group).

3.3.3 Effects of e-cigarettes on xCT expression in the FC, STR and HIP

We further investigated the expression of xCT after six months of exposure to e- cigarettes. As compared to the air control group, unpaired t-test analyses showed

170

significantly decrease in the expression of xCT in the STR (p<0.05; Fig. 3-3) and HIP

(p< 0.01; Fig. 3-3) in e-cigarette vapor exposed mice. However, e-cigarette vapor inhalation for six months did not cause any changes in xCT expression in the FC (p>

0.05; Fig. 3-3).

Fig. 3-3. Effects of six months e-cigarette vapor containing nicotine inhalation (e-Cig) on the relative (R) xCT expression in the FC, STR and HIP of female CD-1 mice. A) Immunoblot bands for xCT and GAPDH (loading control) expression in FC, STR and HIP tissues. B) Unpaired t-test analysis of immunoblots showed a significant decrease in the ratio of xCT / GAPDH in STR and HIP, but not significant in FC, in e-cigarette mice as compared with air controls (control value set to 100%). Data are shown as mean ± SEM (**p<0.01; *p<0.05), (n=4-5 for each group).

3.3.4 Effects of e-cigarettes on GLAST expression in the FC, STR and HIP

The effects of nicotine containing e-cigarette vapor inhalation for six months on GLAST expression in the FC, STR and HIP were determined. Independent t-test analyses did not

171

reveal any changes in GLAST expression in any of the three brain regions (p> 0.05; Fig.

3-4).

Fig. 3-4. Effects of six months e-cigarette vapor containing nicotine inhalation (e-Cig) on the relative (R) GLAST expression in the FC, STR and HIP. A) Immunoblot bands for GLAST and GAPDH (loading control) expression in FC, STR and HIP tissues. B) Unpaired t-test analysis of immunoblots showed non-significant changes in the ratio of GLAST / GAPDH in FC, STR and HIP in e-cigarette exposed mice as compared with air controls (control value set to 100%). Data are shown as mean ± SEM, (n=4-5 for each group). 3.3.5 Determination of nicotine and cotinine concentrations in the FC, and

cotinine in the plasma

Nicotine and cotinine concentrations were determined quantitatively using LC-MS based on a calibration curve correlating the area under the curve relationship of isotope labeled analytical standards (Nicotine-d4 and Cotinne-d3) at fixed concentrations with varying concentrations of nicotine and cotinine. Nicotine and cotinine were both found in the FC at significant levels in e-cigarette exposed mice, 18.82 μM (± 3.7) and 16.65

μM (± 9.2), respectively. The relatively short biological half-life of nicotine (reported at

~10-30 min), makes our finding of significant interest. It suggests that chronic e- cigarette use could result in accumulation of nicotine and its chief metabolite, cotinine, 172

in the FC. Cotinine has a 16 hour half-life in vivo, therefore it has more stable levels over time as compared to nicotine, making it an ideal biomarker for daily nicotine intake via smoking and vaping (Hukkanen et al., 2005). Cotinine in mouse plasma immediately after e-cigarette vapor exposure was 243 +/- 14 ng/mL. Human cotinine levels are typically between 250-300 ng/mL in cigarette smokers (Benowitz et al., 1983,

Gori and Lynch, 1985). Nonsmokers exposed to secondhand smoke have serum cotinine levels of less than 1 ng/mL, but heavy exposure can lead to levels of 1–10 ng/mL. Active smokers consistently have serum levels higher than 10 ng/mL, averaging in the 250-300 ng/mL range, and sometimes higher than 500-800 ng/mL in heavy tobacco users (Hukkanen et al., 2005). Thus, our mouse e-cigarette exposure protocol leads to blood cotinine levels similar to that of smokers.

Fig. 3-5. LC-MS/MS was used to quantify levels of nicotine and cotinine based on the ratio of the area under the curve of the MRM transitions for each analyte and a corresponding isotope labeled internal standard (cotinine-d3 and nicotine-d4). A) calibration curve for extracted blank brain samples spiked with varying concentrations of nicotine and cotinine with fixed concentration of nicotine-d4 and cotinine-d3. LC-MS/MS total ion chromatograms (TIC) for each analyte within each sample of B) Air-control group and C) e-cigarettes (e-Cig) group. D) calculated concentrations of each analyte based on TIC shown in A-C. Data analyzed using one-way ANOVA and shown as mean ± SEM (***= p<0.001), (n=5 for each group). 173

3.4 Discussion

Several studies have investigated the effects of nicotine on the glutamatergic system in different brain regions in the mesocorticolimbic areas (Wang et al., 2007, Kenny et al.,

2009, Knackstedt et al., 2009, Konradsson‐Geuken et al., 2009). Nicotine increases glutamate neurotransmission as well as upregulates post-synaptic glutamate receptor in these areas (Neff et al., 1998, Wang et al., 2007, Kenny et al., 2009, Konradsson‐Geuken et al., 2009). It has been reported that the PFC sends glutamatergic inputs into NAc, a major brain region in the ventral STR (Kalivas and Volkow, 2005). In addition, the PFC sends as well as receives glutamatergic projections into and from the HIP (Hyman et al.,

1987, Gigg et al., 1994, Parent et al., 2010). Moreover, the HIP has been shown to send glutamatergic inputs into the NAc (Britt et al., 2012). This glutamatergic interaction between different brain regions indicates the important role of the glutamatergic system following exposure to nicotine. In these studies, we investigated changes in the glutamatergic system, including nicotinic receptors, glutamate transporters and glutamate antiporters in FC, STR and HIP brain regions following six months of nicotine- containing e-cigarette vapor inhalation by female CD-1 mice. We designed our mouse e- cigarette vapor exposure system based on the most common conventional cigarette smoke exposure, which entails 1 second of cigarette smoke every 60 seconds for 1 hour daily (1 minute total of cigarette smoke). Users take longer drags from e-cigarettes (3-4 seconds) as compared to conventional cigarettes (1 second), and have been found to consume more e-cigarette vapor daily when directly compared to cigarettes, thus our system activates the e-cigarette for 4 seconds, three times per minute. The total e- 174

cigarette vapor exposure of one hour per day, 5 days per week, is modest compared to what heavy e-cigarette users are reporting. Alternatively, vapor inhalation for drug delivery has been well used in several drugs of abuse animal models. However, it is important to consider that vapor inhalation delivery may or not induce hormonal changes in animals as compared to animals exposed to drugs of abuse using different delivery routes. Studies are warranted to determine whether cigarette vapor inhalation can lead to hormonal changes in female and male animal models.

The effects of nicotine exposure on α-7 nAChR have been studied extensively (McGehee et al., 1995, Auta et al., 2000, Alkondon and Albuquerque, 2005, Konradsson‐Geuken et al., 2009). However, there is little known about the effects of chronic nicotine exposure on α-7 nAChR expression. Gutamatergic synaptic transmission has been enhanced at least in part by stimulatory effects of nicotine on pre-synaptic α-7 nAChR (Cheng and

Yakel, 2014). Stimulating α-7 nAChR by nicotine has been suggested to be one of the main mechanisms for nicotine-induced high extracellular glutamate concentrations in the mesocorticolimbic areas (Konradsson‐Geuken et al., 2009, Cheng and Yakel, 2014).

Chronic exposure to nicotine was found to be associated with upregulation of post- synaptic glutamate receptors (Wang et al., 2007, Kenny et al., 2009, Alasmari et al.,

2016a) and that the effect has been suggested to be associated with altered glutamate neurotransmission in the mesocorticolimbic brain regions (Wang et al., 2007).

Importantly, α-7 nAChR is expressed in glutamatergic projections from PFC to central brain reward regions such as NAc and ventral tegmental area (VTA) [For review see

(Feduccia et al., 2012)]. This indicates that α-7 nAChR, expressed in the PFC, mediates 175

glutamatergic projections into NAc and VTA. In this study, we determined a significant increase in α-7 nAChR expression in the FC in e-cigarette exposed mice as compared to air controls (Fig. 3-1). Moreover, we found that six months exposure to e-cigarettes upregulated α-7 nAChR in the STR as compared to air controls. It is important to note that, in a previous study, one minute local perfusion of nicotine (10 nmol/minute) into the

STR was able to upregulate α-7 nAChR significantly in Flinders Sensitive rats as compared to Flinders Resistant rats, which was associated with significant increases in dopamine concentrations (Auta et al., 2000). Stimulation of α-7 nAChR in STR by a receptor agonist, through a microdialysis probe, induced glutamate release and, consequently, dopamine release (Campos et al., 2010). These and our findings suggest that α-7 nAChR in STR may be critical in the development of nicotine dependence through stimulation of glutamate and dopamine release.

A prior study reported that two subcutaneous nicotine injections in male rat pups at postnatal days 14 or 15 did not induce any upregulatory effects on α-7 nAChR expression in HIP slices (Alkondon and Albuquerque, 2005). Our results also showed that α-7 nAChR expression in the HIP region is not changed following chronic (six month) inhalation of nicotine within e-cigarette vapor. It is important to note that α-7 nAChR is highly expressed in HIP (Clarke et al., 1985, Seguela et al., 1993, Marks et al., 1996), which may suggest that neuroadaptation mediating α-7 nAChR expression in the HIP is a key factor that may reduce the effects of chronic nicotine exposure on the changes of the expression of this receptor.

176

The effects of drugs of abuse on GLT-1 and xCT have been investigated extensively

(Knackstedt et al., 2009, Knackstedt et al., 2010, Alhaddad et al., 2014a, Alhaddad et al.,

2014b, Hakami et al., 2016). Our lab showed that chronic exposure to ethanol for five weeks reduced the expression of GLT-1 and xCT in NAc, HIP, and amygdala in male rats (Alhaddad et al., 2014b, Aal‐Aaboda et al., 2015, Hakami et al., 2016). In addition,

β-lactam antibiotics and (R)-(−)-5-methyl-1-nicotinoyl-2-pyrazoline (MS-153) upregulated GLT-1 and xCT in these brain regions and consequently attenuated ethanol drinking behavior (Alhaddad et al., 2014b, Aal‐Aaboda et al., 2015, Alasmari et al., 2015,

Alasmari et al., 2016b). Moreover, ceftriaxone, a β-lactam antibiotic, and N- acetylcysteine restored the expression of both GLT-1 and xCT in rats exposed to cocaine and consequently reduced relapse-like cocaine seeking behavior (Knackstedt et al.,

2010). GLT-1 and xCT have been suggested to play a crucial role in nicotine-seeking behavior such as nicotine-self administration and reinstatement of nicotine, as well as nicotine tolerance (Knackstedt et al., 2009, Schroeder et al., 2011, Alajaji et al., 2013,

Gipson et al., 2013, Ramirez-Niño et al., 2013). A recent study from our lab showed that ceftriaxone attenuated ethanol-, nicotine-, and a mixed solution of ethanol and nicotine- drinking behavior at least in part by upregulating GLT-1 in both NAc and PFC (Sari et al., 2016). Importantly, self-administration of nicotine (0.03 mg/kg) base/infusion for 21 days induced down-regulatory effects on GLT-1 in NAc but not in other brain regions, including VTA, amygdala and PFC (Knackstedt et al., 2009). The same study found that nicotine self-administration for 21 days reduced the expression of xCT in both NAc and

VTA (Knackstedt et al., 2009). In the present study, we used a model of nicotine intake with high physiological relevance to human e-cigarette users. We found that inhalation 177

of e-cigarette vapor-containing nicotine for six months reduced GLT-1 expression in the

STR but not in the FC and HIP. This suggests that GLT-1 protein in the STR is reduced following chronic nicotine exposure, and that this reduction may be due to the motivational effects of drugs of abuse, including nicotine (Knackstedt et al., 2009,

Reissner and Kalivas, 2010).

We report here a significant reduction in xCT expression in the STR and HIP but not in

FC tissues in e-cigarette exposed mice as compared to air controls. It is important to note that in contrast to continuous exposure to nicotine (such as via in-dwelling pumps), phasic exposure to nicotine, which was applied in our study, has been shown to decrease xCT expression (Knackstedt et al., 2009). Alternatively, we did not find any significant changes in GLAST, which is primarily located in the cerebellum and retina, expression level in any brain region studied between e-cigarette and air control groups. This is consistent with prior findings which showed that ethanol ingestion for five weeks did not induce any changes in GLAST expression in NAc and PFC in male rats (Alhaddad et al.,

2014b, Hakami et al., 2016).

Previous studies found that inhalation of e-cigarettes as well as combustible cigarettes induced significant increase in cotinine concentrations in the plasma and urine (Brazell et al., 1984, Xu et al., 2014, Ha et al., 2015, Ponzoni et al., 2015, Smith et al., 2015,

Drummond et al., 2016). In this study, we further detected nicotine and cotinine concentrations in FC tissues, which provide novel evidence about the distribution of nicotine in e-cigarette vapor into the brain. We found significant nicotine and cotinine 178

concentrations in the brain of animals exposed to nicotine containing e-cigarette vapor, as compared to air control groups. This indicates the ability of inhaled nicotine to cross the blood brain barrier. Previous and our findings may indicate that inhaled nicotine of cigarettes is absorbed into the circulatory system and distributed into central nervous system. Since e-cigarettes and air-control groups were placed into the same mesh restraints, the environmental levels of e-cigarette vapor within the fume hood led to very low concentrations of cotinine in the FC of the air control mice.

3.5 Conclusion

We conclude here that nicotine delivery via e-cigarette vapor inhalation, using a physiological and clinically relevant exposure method, induced changes in the expression of glial glutamate transporters and nicotinic receptors. Chronic exposure to nicotine through inhalation of e-cigarette vapor containing nicotine increased α-7 nAChR expression in the mesocorticolimbic area. Moreover, e-cigarette exposure also reduced the expression of GLT-1 and xCT, which may lead to high extracellular glutamate concentrations in central reward brain regions. These data demonstrated that nicotine exposure alters glial glutamate transporters as well as nicotinic receptors, which might be key proteins in the development of nicotine dependence.

Acknowledgements/Funding

This work was supported in part by the National Institutes of Health (R01AA019458 to

Y.S.), (1F32DK104615-01 to CAD), Veterans Affairs BLR&D Career Development

Award (1IK2BX001313 to LCA), AHA Beginning Grant-in-aid (16BGIA27790079 to 179

LCA), and O’Brien Center Daniel O’Connor Memorial Pilot Award to LCA. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Authors thank the Shimadzu Laboratory for

Pharmaceutical Research Excellence at The University of Toledo for Mass spectrometry instrumentation used in this study.

180

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Chapter 4

Effects of Chronic Inhalation of Electronic Cigarette Vapor Containing Nicotine on Neurotransmitters in the Frontal Cortex and Striatum of C57BL/6 Mice

Fawaz Alasmari1, Laura E. Crotty Alexander2, 3, Alaa M. Hammad1, #, Christine M. Bojanowski2,3, Alex Moshensky2,3, Youssef Sari1,*

Abbreviations: α-7 nAChR, alpha-7 nicotinic acetylcholine receptor; e-cigarettes, electronic cigarette; FC, frontal cortex; GABA, gamma-Aminobutyric acid; GLT-1, Glutamate transporter-1; NAc, nucleus accumbens; PFC, prefrontal cortex; STR, striatum; VTA, ventral tegmental area; xCT, cystine/glutamate antiporter .

# Current address: Department of Pharmacy, College of Pharmacy, Al-Zaytoonah University of Jordan, Amman, Jordan

* Corresponding authors:

Dr. Youssef Sari University of Toledo, College of Pharmacy & Pharmaceutical Sciences Department of Pharmacology and Experimental Therapeutics Health Science Campus, 3000 Arlington Avenue, Toledo, OH 43614, USA E-mail: [email protected] Tel: 419-383-1507

Note: This paper will be submitted to a scientific journal.

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Abstract

Electronic (E)-cigarettes are the latest form of nicotine delivery device, and are highly popular in the general population. It is currently unknown whether vaping E-cigarettes leads to nicotine addiction. Alterations in the levels of the neurotransmitters in the mesocorticolimbic areas have been reported to mediate the initiation and development of nicotine dependence. Therefore, to determine whether E-cigarettes activate the same addiction pathways as conventional cigarettes, we investigated the effects of daily inhalation of E-cigarette vapor-containing nicotine for six- months on the concentrations of these neurotransmitters in the frontal cortex (FC) and striatum

(STR) of male C57BL/6 mice. We found that chronic inhalation of E-cigarette vapor- containing nicotine reduced dopamine concentration only in the STR. There were no changes in serotonin concentrations in the FC or STR. Chronic E-cigarette exposure also increased glutamate concentration in the FC alone, while glutamine concentrations were increased in both the FC and STR. We found that E-cigarette exposure also decreased GABA concentration only in the FC. These data suggest that chronic E-cigarette use alters homeostasis of several neurotransmitters in the mesocorticolimbic areas, which may result in the development of nicotine dependence in E-cigarettes users.

Key words: E-cigarettes; Dopamine; Glutamate; Glutamine; GABA; Serotonin.

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4.6 Introduction

The use of electronic (E)-cigarettes worldwide is substantial, with use ranging from 1% to 25% across populations (Delnevo et al., 2015, Palipudi et al., 2015, Singh, 2016, Zhong et al.,

2016). Although E-cigarette devices produce a nicotine containing aerosol, commonly referred to as vapor, with fewer toxic constituents as compared to conventional tobacco cigarette smoke (Margham et al., 2016), research studies have found that E-cigarette vapor induces inflammation, impairs host defense and has other notable toxicological effects

(Vardavas et al., 2012, Hwang et al., 2016, Yu et al., 2016, Canistro et al., 2017, Crotty

Alexander et al., 2018). In addition, there is a high dependence rate reported for E-cigarettes, and clinical studies have reported addictive behavioral effects such as a high urge to smoke and withdrawal symptoms (Dawkins et al., 2012, Foulds et al., 2014, Etter and Eissenberg,

2015). It has been suggested that these addictive effects develop due to alterations in the homeostasis of neurotransmitters in the mesocorticolimbic brain areas (Mifsud et al., 1989,

Caillé and Parsons, 2004, Deehan et al., 2015). In the present study, for the first time, we investigated the effects of six-months of E-cigarette vapor inhalation on the tissue contents of several neurotransmitters in the frontal cortex (FC) and striatum (STR) in male C57BL/6 mice.

Exposure to nicotine stimulates nicotinic acetylcholine receptors (nAChRs) and causes changes in dopamine neurotransmission (Tizabi et al., 2002, Tizabi et al., 2007). Additionally, dopamine receptor antagonists have been found to attenuate nicotine self-administration in rats while increases in extracellular dopamine concentrations in the nucleus accumbens (NAc) shell have been observed in animals with a preference for nicotine (Corrigall and Coen, 1991,

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Scherma et al., 2012). A recent clinical study reported that smoking tobacco cigarettes also affected dopamine biosynthesis in the mesocorticolimbic system (Rademacher et al., 2016).

Nicotine exposure has also been shown to have effects of serotonin neurotransmission. Acute and chronic systemic injection of nicotine increased serotonin release in the frontocortical area and STR (Ribeiro et al., 1993, Takahashi et al., 1998). Chronic, but not acute, exposure to nicotine increases the re-uptake of serotonin in the prefrontal cortex (PFC) and hippocampus

(Awtry and Werling, 2003). Chronic nicotine exposure also reduces the synthesis of serotonin transporters in humans, suggesting alterations in the concentrations of serotonin within the mesocorticolimbic system (Semba and Wakuta, 2008). Long-term exposure to nicotine also has been shown to reduce mRNA expression of the serotonin transporter (Ishikawa et al.,

1999, Watanabe et al., 2011). Little is known about the effect of chronic E-cigarette exposure on the dopaminergic and serotonin systems. Here we investigated dopamine and serotonin levels in both the FC and STR of mice exposed to E-cigarette vapor for six months.

A recent study from our laboratory demonstrated that inhalation of E-cigarette vapor for six months led to down-regulation of glutamate transporter-1 (GLT-1) and cystine/glutamate exchanger (xCT) in the STR of female CD1 mice (Alasmari et al., 2017). Decreases in the expression of these glial glutamate transporters is associated with a significant elevation in extracellular glutamate concentrations (Melendez et al., 2005, LaLumiere and Kalivas, 2008,

Shen et al., 2014, Das et al., 2015). Moreover, our laboratory recently reported that upregulation of GLT-1 in the NAc and PFC reduced nicotine consuming behavior (Sari et al.,

2016). Studies have shown that nicotine exposure stimulates α7-nAChR in presynaptic glutamatergic neurons and consequently increases glutamate release (Konradsson‐Geuken et 192

al., 2009, Cheng and Yakel, 2014). The biosynthesis of glutamate and glutamine is also increased in animals exposed to nicotine for a long period of time (Shameem and Patel, 2012).

In this study, we determined whether E-cigarette vapor exposure causes alterations on the concentrations of glutamate and glutamine in the FC and STR.

Previous studies have shown that short-term exposure to nicotine increased GABA neurotransmission (Fu et al., 2011, DuBois et al., 2013, Taylor et al., 2013). GABA, an inhibitory neurotransmitter, blocks the effects of the excitatory neurotransmitter, dopamine, in the brain (Dewey et al., 1999, Polosa and Benowitz, 2011) and GABA receptor agonists attenuate nicotine seeking behaviors in rats (Paterson et al., 2004, 2005). Several studies have shown that GABA receptor desensitization develops following chronic exposure to nicotine

(Mansvelder et al., 2002, Pidoplichko et al., 2004). This desensitization effect reduces the inhibitory effects of GABA leading to excitability of the dopamine reward system (D’Souza and Markou, 2013). In this study, we evaluated the concentrations of GABA in the FC and STR of mice after long-term exposure to E-cigarette vapors to investigate whether E-cigarette use induces any alterations in the inhibitory neurotransmitter, GABA, and the excitatory neurotransmitter such as glutamate.

4.7 Materials and Methods

4.7.1 E-cigarettes

E-liquid mixtures of 50% glycerin, 50% propylene glycol and 24 mg/mL nicotine (purchased from Xtreme Vaping) were prepared in our laboratory as described in our recent study

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(Alasmari et al., 2017). No flavors or other additives were used. E-cigarette cartomizers

(tanks; 2.4 ohm, plastic, refillable) and batteries (280 mAh fixed, automatic, rechargeable, stainless steel) were purchased from FastTech. Fresh E-cigarette vapor was created by activating the battery via application of negative pressure, 2L/min for 1 second, by the

InExpose system (SciReq), followed by continuous negative pressure of 1L/min for 3 additional seconds. By activating the battery and applying pneumatic pressure, the e-liquid was heated and drawn through the internal atomizer, creating E-cigarette vapor.

4.7.2 Mouse inhalation of e-cigarette vapor

Male C57BL/6 mice, 6-8 weeks old, were purchased from Harlan Labs. The SciReq inExpose inhalation system was used as described in our previous studies (Alasmari et al., 2017, Crotty

Alexander et al., 2018). Soft-mesh restraints, such that only the noses of mice are introduced into the central channel through which the E-cigarette vapor flows, were used in this study to focus the E-cigarette vapor exposure to the respiratory system, creating a physiologic exposure model of E-cigarette use. Mice inhaled E-cigarette vapor for 4 seconds every 20 seconds, for one hour per day, for five days per week, for six months (E-Cig group). Using the same restraints, control mice were exposed to room air only (Air control group) for the same amount of time. Pre-warmed cages were used to recover mice for 30 minutes post-exposure. At the end of six months, animals were anesthetized with 100 mg/kg ketamine and 10 mg/kg xylazine, administered in PBS intraperitoneally, 30-60 minutes after the final exposure. Mice also received 200 units of heparin in 200uL PBS i.p. during induction of anesthesia. Terminal intra-aortic bleed was performed, followed by opening the right and left cardiac ventricles. All animal protocols were in accordance with the NIH guidelines for animal use and approved by 194

the IACUC committee at the University of California, San Diego and San Diego VA

Healthcare System.

4.7.3 Brain Tissue Harvesting

Brains were isolated and brain areas, FC and STR, were dissected according to stereotaxic coordinates of the Mouse Brain Atlas (Paxinos, 2007). Brain tissues were immediately snapfrozen in liquid nitrogen and stored at -80°C for neurotransmitter assays.

4.7.4 High performance liquid chromatography (HPLC) with electrochemical detection

(EC)

The levels of dopamine and serotonin in the FC and the STR were detected using HPLC-EC system as described previously (Das et al., 2016). Briefly, brain tissue samples were lysed and sonicated in 0.25N perchloric acid followed by centrifugation for 20 min at 4°C at 14000 × g.

A specific 0.22 μm filter was used to filter the supernatants and the filtrates were injected into a

C18 column (3.2 × 150 mm, 3μm particle size, Thermo Scientific). The mobile phase contained 54.3 mM sodium phosphate, 0.215 mM octyl sodium sulphate, 0.32 mM citric acid and 11% methanol (pH~ 4.4). To detect dopamine and serotonin concentrations, the CoulArray coulometric detector (model 5600A, ESA, Inc.) was used and connected to CoulArray software for which the chromatograms are shown. The external standards of dopamine and serotonin were purchased from Sigma-Aldrich and analyzed by calculating the peak area to generate a standard calibration curve. The concentrations of the dopamine and serotonin of the tissue samples were then detected. Tissue pellets were resuspended with 1N NaOH for protein

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quantification, using DC (detergent compatible) protein assay, to normalize the concentrations of neurotransmitters to the relative protein contents.

An HPLC-EC system was used to quantify the concentrations of glutamate, glutamine, and

GABA in the FC and the STR following a six-month exposure to E-cigarette vapor. As described previously (Das et al., 2016), homogenized FC and STR tissues millipore water were heated at 98°C for 5 min and centrifuged for 5 minutes at 4°C at 10,000 rpm. Supernatants were collected and filtered using 0.22 μm filters, while the pellets were collected for protein quantification. Pre-column derivatization of [C18 column (3.0 × 50 mm, 2.5 μm particle size,

Waters, Inc.)] of supernatants was performed with mixture of sodium sulfite and o- phthalaldehyde in a solution containing ethanol, sodium sulfite, and 0.1 M sodium tertraborate using 540 autosampler and ESA model. The mobile phase contained 0.1 mM EDTA, 0.1 M

Na2HPO4 and 7.5% Methanol (pH~ 2.8-3). To detect glutamate, glutamine, and GABA, the

CoulArray coulometric detector (model 5600A, ESA, Inc.) was used and connected to

CoulArray software for which the chromatograms are shown. The external standards of glutamate, glutamine, and GABA were purchased from SigmaAldrich and analyzed by calculating peak area to generate a standard calibration curve. The concentrations of glutamate, glutamine, and GABA of the tissue samples were then detected. Tissue pellets were resuspended with 1N NaOH for protein quantification, using DC (detergent compatible) protein assay, to normalize the concentrations of neurotransmitters to the relative protein contents.

4.7.5 Statistical analyses

Unpaired independent t-test was used to analyze tissue content data obtained for

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neurotransmitters of interest in the FC and STR brain tissues between E-cigarette and Air- control groups. The statistical analyses data were shown as p<0.05 level of significance.

4.8 Results

4.8.1 Chronic inhalation of E-cigarette vapor decreased dopamine in the STR

We determined the concentrations of dopamine in the FC and STR in mice exposed to air or E- cigarette vapor-containing nicotine for six months. There was a significant decrease in the concentration of dopamine in the STR in E-cig mice compared to Air-control mice (p =

0.0266; Fig. 4-6C and 4-6D). However, chronic E-cigarette vapor inhalation did not alter dopamine concentrations in the FC (p = 0.1792; Fig. 4-6A and 4-6B).

Fig. 4-6. Effects of six-month inhalation of e-cigarette vapor (E-Cig) containing nicotine on dopamine concentrations in the FC and STR in male C57BL/6 mice. A) Peaks of dopamine in the FC in Air and E-Cig groups. B) Independent t-test analysis did not show any significant changes in dopamine concentration in the FC between e-cigarette and air control groups. C) Peaks of dopamine in the STR in Air and E-Cig groups. D) Independent t-test analysis showed a significant decrease in dopamine concentration in the STR in mice exposed to e-cigarette vapor compared to air controls. Data are reported as mean ± SEM (*p<0.05, ns; not significant), (n=5 for each group), [X-axis, retention time (minutes), Y-axis, response].

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4.8.2 Chronic E-cigarette vapor exposure does not alter serotonin concentrations in the FC or STR We further detected the concentations of serotonin in the FC and STR after six-months of E- cigarette vapor inhalation. There were no significant changes in serotonin concentrations in the FC (p = 0.8462; Fig. 4-7A and 4-7B) and the STR (p = 0.8114; Fig. 4-7C and 4-7D) following six-months of E-cigarette vapor-containing nicotine inhalation as compared to Air- controls.

Fig. 4-7. Effects of six-months inhalation of e-cigarette vapor (E-Cig) containing nicotine on serotonin concentrations in the FC and STR in male C57BL/6 mice. A) Peaks of serotonin in the FC in Air-controls and E-Cig groups. B) Independent t-test analysis did not show any significant changes in serotonin concentration in the FC between e-cigarette and air controls. C) Peaks of serotonin in the STR in Air-controls and E-Cig groups. D) Independent t- test analysis did not show any significant changes in serotonin concentration in the STR between e-cigarette and air control groups. Data are reported as mean ± SEM (ns; not significant), (n=5 for each group), [X-axis, retention time (minutes), Y-axis, response].

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3.8.3 Chronic inhalation of E-cigarette vapor for six-months increased glutamate concentrations in the STR

We quantified glutamate concentrations in the FC and STR after six-months of E-cigarette vapor inhalation. As compared to Air controls, E-cig exposed mice had a significant increase in glutamate concentration in the STR (p = 0.0366; Fig. 4-8C and 4-8D) but not in the FC (p =

0.1995; Fig. 4-8A and 4-8B). We next investigated the effects of chronic exposure to E- cigarette vapor on the levels of glutamine in both FC and STR.

Fig. 4-8. Effects of six-months inhalation of e-cigarette vapor (E-Cig) containing nicotine on glutamate concentrations in the FC and STR in male C57BL/6 mice. A) Peaks of glutamate in the FC in Air-controls and E-Cig groups. B) Independent t-test analysis did not show any significant changes in glutamate concentration in the FC between e-cigarette and air control groups. C) Peaks of glutamate in the STR in air-control and E-Cig groups. D) Independent t-test analysis showed a significant increase in glutamate concentration in the STR in mice exposed to e-cigarette vapor compared to air controls. Data are reported as mean ± SEM (*p<0.05, ns; not significant), (n=5 for each group), [X-axis, retention time (minutes), Y- axis, response].

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4.8.4 Chronic nicotine-containing E-cigarette vapor inhalation increased glutamine concentrations in the FC and STR

Since inhalation of E-cigarette vapor for six months increased glutamate concentrations in the

STR, we evaluated concentrations of glutamine in both the FC and the STR in mice exposed to

E-cigarette vapor versus Air controls for six months. Glutamine concentrations were significantly increased in the FC (p = 0.0481; Fig. 4-9A and 4-9B) and STR (p = 0.0017; Fig. 4-

9C and 4-9D) in mice exposed to nicotine containing E-cigarette vapor compared to Air controls.

Fig. 4-9. Effects of six-months inhalation of e-cigarette vapor (E-Cig) containing nicotine on glutamine concentrations in the FC and STR in male C57BL/6 mice. A) Peaks of glutamine in the FC in air-control and E-Cig groups. B) Independent t-test analysis showed a significant increase in glutamine concentration in the FC in mice exposed to e-cigarette vapor compared to air control groups. C) Peaks of glutamine in the STR in air-control and E-Cig groups. D) Independent t-test analysis showed a significant increase in glutamine concentration in the STR in mice exposed to e-cigarette vapor compared to air controls. Data are reported as mean ± SEM (**p<0.01,*p<0.05, ns; not significant), (n=5 for each group), [X-axis, retention time (minutes), Y-axis, response].

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4.8.5 Inhalation of E-cigarette vapor for six-months decreased GABA in the FC

The effects of six months exposure to nicotine containing E-cigarette vapors on the concentrations of GABA in the FC and STR were investigated. Chronic daily exposure to E- cigarette vapor induced a significant decrease in the levels of GABA in the FC (p = 0.0415; Fig.

4-10A and 4-10B) compared to Air controls. However, no significant change in GABA concentration in the STR of mice exposed to E-cigarette vapor was found (p = 0.3941; Fig. 4-

10C and 4-10D).

Fig. 4-10. Effects of six-months inhalation of e-cigarette vapor (E-Cig) containing nicotine on GABA concentrations in the FC and STR in male C57BL/6 mice. A) Peaks of GABA in the FC in air-control and E-Cig groups. B) Independent t-test analysis showed a significant decrease in GABA concentration in the FC in mice exposed to e-cigarette vapor compared to air control groups. C) Peaks of GABA in the STR in air-control and E-Cig groups. D) Independent t-test analysis did not show any significant changes in GABA concentration in the STR between e-cigarette and air control groups. Data are reported as mean ± SEM (**p<0.01,*p<0.05, ns; not significant), (n=5 for each group), [X-axis, retention time (minutes), Y-axis, response].

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4.9 Discussion

Dopamine and glutamate projections from the ventral tegmental area (VTA) and the FC, respectively, into the NAc, are necessary for the development of drug dependence, including nicotine (Kalivas and Volkow, 2005, LaLumiere and Kalivas, 2008, Feduccia et al., 2012,

Pistillo et al., 2015, Subramaniyan and Dani, 2015). Additionally, glutamatergic projections have been found to be released from the amygdala and hippocampus into the NAc (Britt et al.,

2012, Goodwani et al., 2017). The FC receives GABAergic inputs from the VTA and basal ganglia (Carr and Sesack, 2000, Saunders et al., 2015), and GABA can inhibit dopamine release from the VTA into the NAc and FC. This effect has been suggested to attenuate nicotine and cocaine seeking behavior (D’Souza and Markou, 2013, Vella and Di Giovanni, 2013, Edwards et al., 2017). Alternatively, serotonergic inputs from raphe nucleus have been found to stimulate serotonin receptors in the STR, NAc and hippocampus (Nakamura, 2013). In the present work, we studied the concentrations of these neurotransmitters in two critical brain areas, FC and

STR, in mice exposed daily to nicotine within E-cigarette vapor for six-months. Our data provide evidence that chronic E-cigarette use induces changes in neurochemical levels in the

FC and STR and activates nicotine dependence pathways (Figure 6).

Nicotine exposure has been found to induce the release of neurotransmitters including dopamine and glutamate through stimulatory effects on nAChRs in the mesocorticolimbic areas

(Tizabi et al., 2002, Tizabi et al., 2007, Konradsson‐Geuken et al., 2009). Exposure to nicotine for two weeks increased the concentrations of dopamine in the mesocorticolimbic areas (Fuxe et al., 1990). Interestingly, other studies reported that several month-long exposure to nicotine significantly decreased dopamine synthesis and release in humans and monkeys, respectively 202

(Perez et al., 2012, Rademacher et al., 2016). In this study, with a several month-long exposure to nicotine via E-cigarette vapor inhalation, we found reduced dopamine concentrations in the

STR, but not in the FC. This consistency between previous data and our own suggests that chronic inhalation of tobacco smoke or nicotine containing E-cigarette vapor reduces dopamine synthesis and content, specifically in the STR (Figure 6).

Previous studies have shown conflicting results regarding the effects of nicotine exposure on serotonin expression, uptake and functions (Awtry and Werling, 2003, Semba and Wakuta,

2008). In rats, nicotine exposure has been shown to increase the extracellular concentrations and release of serotonin in the FC and STR, respectively (Ribeiro et al., 1993, Takahashi et al.,

1998). We did not find significant alterations in the concentrations of serotonin in the FC and

STR of mice exposed to E-cigarette vapor for six months. These data suggest that while nicotine might affect the release as well as the uptake of serotonin, there is no effect on the serotonin content within the FC and STR.

Several studies have investigated the effects of nicotine on the glutamatergic system in multiple mesocorticolimbic brain regions (Konradsson‐Geuken et al., 2009, Alasmari et al., 2016,

Alasmari et al., 2017). Studies have reported that nicotine stimulates nAChRs and also reduces glutamate uptake, leading to increased extracellular glutamate concentrations (Knackstedt et al.,

2009, Gipson et al., 2013, Cheng and Yakel, 2014). Importantly, we found recently that E- cigarette vapor inhalation does not alter the expression of GLT-1 in the FC (Alasmari et al.,

2017). In the present study, chronic daily inhalation of E-cigarette vapor for six months did not affect the concentrations of glutamate in the FC. This data suggests that extracellular glutamate 203

in the FC is transported into astrocytes mainly by GLT-1 and is then converted to glutamine.

Additionally, FC sends and receives glutamatergic inputs to and from multiple brain regions in the mesocorticolimbic area. Thus, most of glutamate in the FC innervates other brain areas such as NAc (Britt et al., 2012). We found here that E-cigarette vapor-containing nicotine exposure increased the concentration of glutamate in the STR (Figure 3C, 3D and 6). It is noteworthy that the ventral STR area receives glutamate inputs from FC, amygdala and hippocampus (Kalivas and Volkow, 2005, Britt et al., 2012). Moreover, a previous study from our laboratory found that six-month daily inhalation of E-cigarette vapor-containing nicotine reduced the expression of GLT-1 and xCT in the STR (Alasmari et al., 2017). The increase in glutamatergic projections to the STR (Mori et al., 1994) and the decrease of striatal glial glutamate transporters expression (Alasmari et al., 2017) may lead to high concentrations of glutamate. Elevation of glutamate concentrations in the STR may be involved in the development of nicotine dependence.

Nicotine dependence has been suggested to be associated with significant increases in glutamine biosynthesis and concentrations in astrocytes. We demonstrate here that E-cigarette exposure increases glutamine concentrations in both FC and STR (Figure 4A-D and 6). These data are consistent with a prior study showing that glutamine synthesis was increased significantly in the mesocorticolimbic brain regions of rats injected with nicotine for four weeks

(Shameem and Patel, 2012), and confirms that inhalation of nicotine induces the same alterations.

The GABAergic system has been investigated extensively as a major inhibitory 204

neurotransmitter system strongly associated with drug dependence (Negus et al., 2000,

Paterson et al., 2004, Jayaram and Steketee, 2005, Miranda et al., 2009). A previous study reported that chronic exposure to environmental tobacco smoke or nicotine reduced the expression of GABA(B1) receptor in rats (Li et al., 2002). Therapeutic compounds that stimulate the GABA receptor have been reported to attenuate nicotine seeking behavior

(Fattore et al., 2002, Paterson et al., 2004, Paterson et al., 2008). The inhibitory role of GABA on dopamine release is suggested to be the mechanism for the attenuating effects of GABA receptors agonists on nicotine seeking behavior (D’Souza and Markou, 2013). It has been shown that exposure to 500 nM of nicotine for 25 minutes increased GABA transmission measured by inhibitory postsynaptic currents and this effect was followed by a long-term inhibition on the GABA neurons in the VTA (Pidoplichko et al., 2004). This indicates that chronic nicotine exposure desensitizes GABA receptors and reduces GABA transmission

(Mansvelder et al., 2002). In the present study, we found that daily E-cigarette vapor inhalation for six months reduced GABA concentrations in the FC, but not in the STR (Figure

5A-D and 6). The decrease of GABA level in the FC in our study suggests that persistent nicotine exposure results in further stimulation of excitatory neurotransmission in central reward areas which may facilitate nicotine-seeking behavior.

4.10 Conclusion

Our data indicate that chronic, daily exposure to nicotine-containing E-cigarette vapor alters the concentrations of neurotransmitters within mesocorticolimbic brain regions (Figure 6).

The changes in neurotransmitter levels in our murine model suggest that daily, persistent use of E-cigarettes may lead to nicotine addiction. This raises a public health concern as it 205

suggests that the younger generations of users, which have the highest rates of E-cigarette use, might become addicted to these devices despite unknown long-term physiologic and pathologic consequences (Crotty Alexander et al., 2015). Furthermore, existing data suggest that young users of E-cigarettes are more likely to start smoking conventional tobacco, which may have serious deleterious effects on human health (Leventhal et al., 2015, Goldenson et al.,

2017). Further studies are warranted to investigate the withdrawal and relapse effects of exposure to nicotine-containing E-cigarette vapor on neurotransmitter concentrations in the mesocorticolimbic brain areas.

Fig. 4-11. Schematic diagram summarizes the effects of inhalation of E-cigarette vapor- containing nicotine for six months on the concentrations of neurotransmitters in the FC and STR.

Acknowledgements/Funding

This work was supported in part by the National Institutes of Health (R01AA019458 to Y.S.;

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R01HL137052-01 to L.C.A.). This work was also funded by an American Heart Association

Beginning Grant-in-Aid (16BGIA27790079 to L.C.A.), a UAB-UCSD O’Brien Center Daniel

O’Connor Scholar Award (NIH P30-DK079337 to L.C.A.), and an ATS Foundation K to R

Transition Award (L.C.A.). Authors would like to thank Dr. Bruce S. Levison for all his valuable guidance and suggestions with HPLC troubleshooting.

Conflict of interest

The authors declare no conflict of interest.

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Chapter 5

Peri-Adolescent Drinking of Ethanol and/or Nicotine Modulate Glial Glutamate Transporters and Metabotropic Glutamate Receptor-1 in Female Alcohol-Preferring Rats

Fawaz Alasmaria, Richard L. Bellb,*, P.S.S. Raoc, Alaa M. Hammada,#, Youssef Saria,*

aUniversity of Toledo, College of Pharmacy and Pharmaceutical Sciences, Department of Pharmacology and Experimental Therapeutics, Toledo, OH 43614, USA. bDepartment of Psychiatry and Institute of Psychiatric Research, Indiana University School of Medicine, Indianapolis, IN 46202, USA. c Department of Pharmaceutical Sciences, College of Pharmacy, The University of Findlay, Findlay, OH 45840, USA. #Current address: Department of Pharmacy, College of Pharmacy, Al-Zaytoonah University of Jordan, Amman, Jordan

* Corresponding authors: Dr. Youssef Sari University of Toledo, College of Pharmacy & Pharmaceutical Sciences Department of Pharmacology and Experimental Therapeutics Health Science Campus, 3000 Arlington Avenue, Toledo, OH 43614, USA E-mail: [email protected] Tel: 419-383-1507

Dr. Richard L. Bell Department of Psychiatry & Institute of Psychiatric Research Indiana University School of Medicine 791 Union Drive Indianapolis, IN 46202, USA E-mail: [email protected] Tel: 317-278-8407 Note: This paper was re-submitted to pharmacology, biochemistry and behavior journal.

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Abstract

Impairment in glutamate neurotransmission mediates the development of dependence upon nicotine (NIC) and ethanol (EtOH). Previous work indicated that continuous access to EtOH or phasic exposure to NIC reduces expression of the glutamate transporter-1

(GLT-1) and cystine/glutamate antiporter (xCT) but not the glutamate/aspartate transporter (GLAST). Additionally, metabotropic glutamate receptors (mGluRs) expression was affected following exposure to EtOH or NIC. However, little is known about the effects of EtOH and NIC co-consumption on GLT-1, xCT, GLAST, and mGluR1 expression. In this study, peri-adolescent female alcohol preferring (P) rats were given binge-like access to water, sucrose (SUC), SUC-NIC, EtOH, or EtOH-NIC for 4 weeks. The present study determined the effects of NIC and/or EtOH consumption on GLT-1, xCT, GLAST, and mGluR1 expression in the nucleus accumbens (NAc), hippocampus (HIP) and prefrontal cortex (PFC). GLT-1 and xCT expression were decreased in the NAc following both SUC-NIC and EtOH-NIC. In addition, only xCT expression was downregulated in the HIP in both these later groups. Also, glutathione peroxidase (GPx) activity in the HIP was reduced following SUC, SUC-NIC, EtOH, and

EtOH-NIC consumption. Similar to previous work, GLAST expression was not altered in any brain regions. However, mGluR1 expression was increased in the NAc in the

SUC-NIC, EtOH, and EtOH-NIC groups. These results indicate that peri-adolescent binge-like drinking of EtOH or SUC with/without NIC may exert differential effects on glial glutamate transporters and receptors relative to those observed in previous studies using adult rats.

Key words: Co-Abuse; ethanol; nicotine; GLT-1; xCT; mGluR1. 216

5.1 Introduction

Recent evidence indicates a significant increase in alcohol and tobacco consumption in adolescents worldwide (Johnston et al., 2015, Primack et al., 2015, Esser, 2017, Lim et al., 2017, Miech et al., 2017, Wang et al., 2017). Additionally, alcohol consumption has been shown to increase pleasure from cigarettes smoking in young adults (Gubner et al.,

2017). Moreover, several clinical studies indicate that alcohol abusers are more likely to abuse tobacco (Bierut et al., 2000, Falk et al., 2008). Similarly, studies have reported that ethanol (EtOH) drinking increased tobacco use, while tobacco use increased EtOH intake

(Bobo and Husten, 2000, Grant et al., 2004, Falk et al., 2006, Falk et al., 2008). Thus, it appears that EtOH and nicotine (NIC) have mutual reinforcing/rewarding properties, which result in increased intake when both co-exposed simultaneously (Griffiths et al.,

1976, Bito-Onon et al., 2011). Delineating the pharmacological mechanisms involved in the development of EtOH and NIC co-dependence could lead to the discovery of molecular targets for pharmacotherapy intervention, in particular targets within the central glutamatergic reward neurocircuitry.

Within the mesocorticolimbic reward pathway, the nucleus accumbens (NAc) receives glutamatergic inputs from different brain regions, including the prefrontal cortex (PFC) and hippocampus (HIP) (Floresco et al., 2001, Kalivas and Volkow, 2005). These glutamatergic projections to the NAc have been implicated in the development of drug- seeking and drug-taking behavior (LaLumiere and Kalivas, 2008). The HIP also receives input from and sends glutamatergic projections to the PFC, which appears to mediate the 217

development of drug dependence as well [For review see (Feduccia et al., 2012)]. Thus, it is important to clarify the effects of binge-like drinking of EtOH or SUC with/without

NIC on the glutamatergic system in these three brain areas. Importantly, exposure to

EtOH or NIC has been associated with significant increases in total extracellular glutamate concentrations in these critical brain regions (Floresco et al., 2001, Lambe et al., 2003, Saellstroem Baum et al., 2006, Bancila et al., 2009). The Deehan and colleagues study (2015) reported that female P rats exposed to EtOH-NIC showed significant increases in extracellular glutamate concentrations as compared with EtOH, saccharin-NIC or saccharin self-administered groups. However, the effects of co- exposure of NIC and EtOH on glial glutamate transporter and metabotropic glutamate receptor-1 (mGluR1) expression in the mesocorticolimbic neurocircuit have not been studied directly.

Glutamate uptake is primarily regulated by the glutamate transporter-1 (GLT-1), of which the excitatory amino acid transporter 2 (EAAT2) is the human homolog (Danbolt, 2001).

Previous work indicates that EtOH drinking for five weeks or intravenous NIC self- administration for 21 days reduced the expression of GLT-1 (Knackstedt et al., 2009,

Goodwani et al., 2015) suggesting that long-term exposure to EtOH or NIC may induce a marked increase in total extracellular glutamate concentrations. However, less is known about the effects of EtOH and NIC co-consumption on GLT-1 expression in the mesocorticolimbic system. Additionally, cystine/glutamate antiporter (xCT) has an important role in regulating glutamate homeostasis [For review see (Bridges et al., 2012)] through the xCT antiporter, extracellular glutamate is exchanged for intracellular cystine 218

(Baker et al., 2002, Shih et al., 2006). The glutamate/aspartate transporter (GLAST) is another glutamate transporter co-localized with GLT-1 and xCT in astrocytes. However,

GLAST appears to be minimally expressed in the central nervous system (CNS) (Takumi et al., 1997, Lehre and Danbolt, 1998b). Nevertheless, a recent study reported that

GLAST expression was present in the NAc and PFC but this expression was not changed following free-choice access exposure to EtOH for five weeks in male P rats (Hakami et al., 2016). Regarding Group I metabotropic glutamate receptors (mGluRs), mGluR1 is upregulated in animals exposed to EtOH or NIC (Kane et al., 2005, Obara et al., 2009).

Moreover, mGluR1 antagonists significantly attenuated both EtOH and NIC seeking behavior in animals (Dravolina et al., 2007, Besheer et al., 2008, Lum et al., 2014,

Goodwani et al., 2017) suggesting a potential role for mGluR1 in regulating the reinforcing effects of EtOH and NIC. However, the effect of EtOH-NIC co-exposure on the expression of GLAST or mGluR1 has not been directly investigated.

Interestingly, xCT is neuroprotective and through antioxidant effects in part by stimulating the biosynthesis of glutathione (Shih et al., 2006, Albrecht et al., 2010).

Intracellular cystine is converted to cysteine, which is involved in glutathione synthesis and oxidative stress inhibition (Shih et al., 2003, Amin et al., 2014). Importantly, oxidized glutathione is formed by the oxidation of glutathione via glutathione peroxidase

(GPx), which is widely used as a biomarker for neuroprotection (Deponte, 2013). A correlation between GPx activity and xCT expression, however, has not been directly evaluated in the context of co-consumption of NIC and EtOH.

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In the present study, we investigated changes in the expression of glutamate transporters

(GLT-1, xCT, GLAST, and mGluR1 in the NAc, HIP and PFC in female P rats exposed to a binge-like drinking protocol with free-choice access to sucrose (SUC), SUC-NIC,

EtOH, or EtOH-NIC. Additionally, GPx activity in the HIP was assessed. The rationale for using female, rather than male, P rats in this study is based on reported literature, which demonstrated a heightened EtOH and NIC seeking behavior in female as compared to male animals and humans (Donny et al., 2000, Torres et al., 2014, Frydenberg et al.,

2015). A positive correlation has been associated between levels of estrogen and EtOH consumption in female humans (Frydenberg et al., 2015). In addition, female rats showed higher motivation to consume NIC or EtOH compared to female ovariectomized or male rats (Torres et al., 2014, Flores et al., 2016). Owing to the clinically and physiologically relevance to human exposure, a multiple scheduled binge-like drinking of

EtOH or SUC with/without NICparadigm was used in this study to simulate binge-like drinking (Bell et al., 2011). Overall, this study was designed to provide evidence regarding the differential or synergistic effects of binge-like EtOH with/without consumption on the CNS glutamatergic system relative to the findings observed in studies using adult rodents.

5.2 Materials and methods

5.2.1 Animals and drinking protocol

Female P rats used in this study were maintained in a facility fully accredited by the

Association for the Assessment and Accreditation of Laboratory Animal Care

(AAALAC). All research protocols were approved by the Institutional Animal Care and 220

Use Committee (IACUC) of the Indiana University School of Medicine (IUSM,

Indianapolis, IN) and were in accordance with the guidelines of the IACUC of the

National Institutes of Health (NIH) and the Guide for the Care and Use of Laboratory

Animals (Institute of Laboratory Animal Resources, Commission on Life Sciences,

National Research Council 1996). Animals were weaned at 21 days old [post-natal day

(PND) 21] and group housed by sex. At PND 25, animals were transferred to a vivarium room maintained on a 12/12h reverse dark/light cycle with light offset at 10:00 a.m.

At PND 30+/-2, animals were transferred to hanging stainless steel wire-mesh cages and given ad lib access to food and water until tissue harvesting. On the third day that the rats were housed in hanging stainless steel wire-mesh cages, each animal was randomly assigned to one of the five different treatment groups. All groups experienced a binge- like drinking-in-the-dark—multiple-scheduled-access procedure (Bell et al., 2011) of two 1hr sessions separated with two hrs and the first session occurring during the first hr of the dark cycle. Access to the respective solutions occurred five days a week (Monday through Friday) for four weeks. Rats were divided into five groups and were given free- choice access to three bottles [three bottle-choice (3BC)] as follows: a water bottle and concurrent access to (1) two bottles of water, (2) a bottle of 15% as well as a bottle of

30% EtOH, (3) a bottle of 15% EtOH and 0.07 mg/ml NIC as well as a bottle of 30%

EtOH and 0.14 mg/ml NIC, (4) a bottle of 10% SUC and 0.07 mg/ml NIC as well as a bottle of 10% SUC and 0.14 mg/ml NIC, and finally (5) a bottle of 10% SUC as well as a bottle of 10% SUC. NIC was mixed with either EtOH or SUC to stimulate NIC 221

drinking in P rats and avoid unpleasant taste of NIC. The NIC concentrations (0.07 mg/mL and 0.14 mg/mL) were chosen based on studies showed that the intake of NIC

(mg/kg/day) using these concentrations was comparable to NIC intake per cigarette of low level smokers (Benowitz, 1984, Hauser et al., 2012).

5.2.2 Brain harvesting

Approximately 2 hrs after the last binge-like access period, rats were euthanized and brains were immediately extracted and immediately kept at -80°C for immunoblotting assay. Brain regions (NAc, PFC and HIP) were dissected using a Cryostat machine maintained at -20°C. The Paxinos and Watson Atlas was used to determine the boundaries of these brain regions (Paxinos and Watson, 1998). All isolated brain tissue regions were stored at -80°C for testing the expression of GLT-1, xCT, GLAST and mGluR1. Random samples were chosen from each group (n=6, for each group) for

Western Blotting.

5.2.3 Western Blot analyses

Western Blot assay was performed to determine changes in expression of GLT-1, xCT,

GLAST, mGluR1, and GAPDH in the NAc, HIP and PFC as described previously

(Alasmari et al., 2016b, Hammad et al., 2017). Briefly, brain tissue samples were homogenized gently using lysis buffer-containing protease inhibitor. For protein quantification, Bio-Rad quantification reagents (Bio-Rad, Hercules, CA, USA) were 222

used to determine the total protein in each tissue sample. Specific volume from each sample of tissue was mixed with laemmli dye and then loaded on polyacrylamide gel

(10-20%). Subsequently, a transfer apparatus system was used to transfer proteins from each gel onto a PVDF membrane. Subsequently, membranes were blocked using 3% free fat milk in Tris-buffered saline Tween-20 (TBST) for 30 minutes to one hr at room temperature. The PVDF membranes were incubated with the desired primary antibodies

(overnight) at 4°C. The primary antibodies used in this study included guinea pig anti-

GLT-1 (1:5000, Millipore), rabbit anti-xCT antibody (1: 1000; Abcam), rabbit anti-

GLAST antibody (1: 5000; Abcam), and rabbit anti-mGluR1 (1: 3000; Millipore

Bioscience Research Reagents). These antibodies have been used in our previous study

(Hammad et al., 2017). The control loading protein used in this study was mouse anti-

GAPDH (1:5000, Millipore). On the second day, all membranes were washed five times with TBST followed by 30-minute blocking in 3% free fat milk. Subsequently, membranes were incubated with the appropriate secondary antibody [anti-rat IgG, anti- guinea pig IgG, anti-rabbit IgG or anti-mouse IgG, respectively] at a dilution of 1:3000 for 90 minutes. This was followed by five washes with TBST and drying. To detect proteins, the dried membranes were incubated with the developing Chemiluminescent kit (Super Signal West Pico, Pierce Inc.). Membranes exposed to HyBlot CL Film

(Thermo Fisher Scientific) were then developed using SRX-101A processor. An MCID machine was used to quantify and analyze the expression of GLT-1, xCT, GLAST, mGluR1, and GAPDH on digitized blot images. In each run of the gels, we load the gels as follows: 1) Water, SUC and SUC-NIC; and 2) Water, EtOH and EtOH-NIC. Thus, each group will be compared for changes in the expression of GLT-1, xCT, GLAST and 223

mGluR1 in the NAc, PFC, and HIP. The data for the water-control group were expressed as 100% to determine significant changes in expression of these proteins

(relative to water control group) in these mesocorticolimbic brain regions of animals exposed to binge-like access to different drinking solutions as performed previously (Li et al., 2003, Raval et al., 2003, Miller et al., 2008, Zhang and Tan, 2011, Simões et al.,

2012, Devoto et al., 2013, Alasmari et al., 2015).

5.2.4 Glutathione peroxidase activity (GPx)

Glutathione peroxidase (GPx) activity in the HIP region of the treated rats was determined using the commercially available glutathione peroxidase kit (Cayman

Chemical, Ann Arbor, USA). To examine GPx activity, brain tissue samples were homogenized in ice-cold PBS (pH 7.4) supplemented with 1 mM EDTA. The homogenate was centrifuged at 21,952 g for 30 mins at 4°C and the supernatant was assessed immediately for GPx activity using the kit protocol. Briefly, the rate of change in absorbance at 340 nm (A340) over 1 to 6 minutes was determined for the background wells, positive control and the collected brain tissue samples in duplicate. The GPx activity was then determined using the rate change of A340 and the NADPH extinction coefficient. Protein concentration of samples was determined using a Pierce BCA

Protein Assay Kit (ThermoFisher Scientific, Waltham, USA).

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5.2.5 Statistical Analyses

5.2.5.1 Drinking-solution data

The average intake of SUC, EtOH and NIC for the last five sessions of the four-week binge-like scheduled drinking procedure was calculated and analyzed using unpaired t test. We used here, unpaired t test, to compare between SUC (g/kg) or EtOH (g/kg) drinking with and without addition of NIC. In addition, we used unpaired t test to determine the effects of EtOH and SUC on NIC intake (mg/kg). It is important to consider that SUC or EtOH and NIC were used with different concentrations and the drinking was measured with different units of amount.

5.2.5.2 Western blot and glutathione peroxidase (GPx) data

Data obtained from the Western Blot assays, for the proteins of interest, were analyzed as a percentage ratio relative to the control loading protein (GAPDH) using one-way

ANOVA followed by Newman Keuls post-hoc multiple comparison tests. The percentage of GPx activity was also analyzed using a one-way ANOVA followed by

Newman Keuls multiple comparisons. The densities of immunoblot bands and GPx activity obtained from the water control group served as the 100% bench-mark. All data are shown for a p<0.05 level of significance. We used larger sample size for behavioral studies (n = 9) compared to laboratory studies (n = 6) to make the confounding factors constant as described previously.

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5.3 Results

5.3.1 Average intake of SUC, SUC-NIC, EtOH, or EtOH-NIC

Independent t test analysis revealed that addition of NIC significantly reduced SUC intake [p < 0.0001, (Figure 5-1A)]. An unpaired t test showed that the average intake of

NIC (mg/kg) was significantly lower in animals exposed to the binge-like schedule of

EtOH-NIC drinking compared with the SUC-NIC group [p < 0.0001, (Figure 5-1B)].

However, no significant differences were observed for the average intake of EtOH relative to EtOH-NIC [p >0.05, (Figure 5-1C)].

Figure 5-1. Average last five sessions binge-like drinking of; (A) SUC (g/kg of average body weight) and SUC-NIC (g/kg of body weight), (B) NIC (SUC) (mg/kg of body weight) and NIC (EtOH) (mg/kg of body weight) NIC (mg/kg of body weight) in female P rats, and (C) EtOH (g/kg of body weight) and EtOH-NIC (g/kg of body weight). Unpaired t test revealed that addition of NIC reduced SUC consumption, however, the analysis did not show any change in EtOH consumption following addition of NIC. Unpaired t test revealed that NIC consumption was higher in SUC-NIC group compared to EtOH-NIC group. Data are represented as mean ± SEM (n = 9 for each group), (# p < 0.0001).

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5.3.2 Effects of binge-like drinking of SUC or SUC-NIC on GLT-1, xCT, GLAST and mGluR1 expression in the NAc

One-way ANOVA showed a significant difference among water control, SUC and SUC-

NIC groups in GLT-1 expression [F (2, 15) = 10.99, p = 0.0011, (Figure 5-2A)], xCT expression [F (2, 15) = 6.911304, p = 0.0075, (Figure 5-2B)] and mGluR1 expression [F

(2, 15) = 4.536, p = 0.0288, (Figure 5-2D)] but not in GLAST expression [F (2, 15) =

0.6335, p = 0.5444, (Figure 5-2C)] in the NAc. Newman-Keuls multiple comparison post-hoc test revealed that while there was no significant changes in GLT-1 expression between SUC and water groups in the NAc, SUC-NIC drinking reduced GLT-1 and xCT expression and increased mGluR1 expression in the NAc compared to water control and

SUC groups.

Figure 5-2. Effects of binge-like drinking of SUC and SUC-NIC on relative expression (R) of (A) GLT-1, (B) xCT, (C) GLAST, and (D) mGluR1 in the NAc (100% of water control group). One way ANOVA followed by Newman-Keuls analysis revealed that SUC-NIC but not SUC exposure reduced GLT-1/GAPDH and xCT/GAPDH ratios in the NAc. The analysis did not show any significant reduction in GLAST/GAPDH ratio in the NAc. One way ANOVA followed by Newman-Keuls analysis revealed that SUC-NIC but not SUC exposure increased mGluR1/ratio in the NAc. Data are represented as mean ± SEM (n = 6 for each group), (* p < 0.05 and ** p < 0.01). 227

5.3.3 Effects of binge-like drinking of EtOH, or EtOH-NIC on GLT-1, xCT, GLAST and mGluR1 expression in the NAc

We further determined the effects of four-week binge-like access drinking of EtOH and

EtOH-NIC on the expression of GLT-1, xCT, GLAST and mGluR1 in the NAc. One- way ANOVA showed a significant difference among these groups in the NAc in GLT-1 expression [F (2,15) = 5.288, p = 0.0183, (Figure 5-3A)], xCT expression [F (2, 15) =

7.261, p = 0.0062, (Figure 5-3B)] and mGluR1 expression [F (2,15) = 4.581, p = 0.0280,

(Figure 5-3D)] but not in GLAST expression [F (2, 15) = 0.5534, p = 0.5863, (Figure 5-

3C)]. Newman-Keuls multiple comparisons showed that while there were no significant changes in GLT-1 and xCT expression between water control and EtOH groups in the

NAc, EtOH-NIC exposure reduced GLT-1 and xCT expression expression compared to water control and EtOH groups in the NAc. In addition, EtOH and EtOH-NIC exposure increased mGluR1 expression in the NAc compared to water group and there were significant changes in mGluR1 expression in the NAc between EtOH and EtOH-NIC groups.

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Figure 5-3. Effects of binge-like drinking of EtOH and EtOH-NIC on relative expression (R) of (A) GLT-1, (B) xCT, (C) GLAST, and (D) mGluR1 in the NAc. One way ANOVA followed by Newman-Keuls analysis revealed that EtOH-NIC but not EtOH exposure reduced GLT-1/GAPDH and xCT/GAPDH ratios in the NAc (100% of water control group). The analysis did not show any significant reduction in GLAST/GAPDH ratio between the groups in the NAc. One way ANOVA followed by Newman-Keuls analysis revealed that EtOH-NIC and EtOH exposure increased mGluR1/GAPDH ratio in the NAc. Data are represented as mean ± SEM (n = 6 for each group), (* p < 0.05 and ** p < 0.01).

5.3.4 Effects of binge-like drinking of SUC or SUC-NIC on GLT-1, xCT, GLAST and mGluR1 expression in the HIP One-way ANOVA demonstrated a significant difference in xCT expression among water control, SUC and SUC-NIC groups in the HIP [F (2, 15)

= 9.056169, p = 0.0026, (Figure 5-4B)]. The statistical analysis did not show any significant differences among water control, SUC and SUC-NIC groups in GLT-1 expression [F (2, 15) = 0.7020627, p = 0.5111, (Figure 5-4A)], GLAST expression [F (2,

15) = 0.9834759, p = 0.3969, (Figure 5-4C)] and mGluR1 expression [F (2, 15) =

229

0.6596258, p = 0.5314, (Figure 5-4D)]. Newman-Keuls analysis revealed that SUC-NIC drinking reduced xCT expression significantly in the HIP compared to SUC and water groups. No significant changes in xCT expression were observed between the SUC- alone and water groups in the HIP.

Figure 5-4. Effects of binge-like drinking of SUC and SUC-NIC on relative expression (R) of (A) GLT-1, (B) xCT, (C) GLAST, and (D) mGluR1 in the HIP (100% of water control group). One way ANOVA followed by Newman-Keuls analysis revealed that SUC-NIC but not SUC exposure reduced xCT/GAPDH ratio in the HIP. The analysis did not show any significant reduction in GLT-1/GAPDH, GLAST/GAPDH and mGluR1/GAPDH ratios between all groups in the HIP. Data are represented as mean ± SEM (n = 6 for each group), (* p < 0.05 and ** p < 0.01).

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5.3.5 Effects of binge-like drinking of EtOH or EtOH-NIC on GLT-1, xCT, GLAST and mGluR1 expression in the HIP

We further investigated expression of GLT-1, xCT, GLAST and mGluR1 between water,

EtOH and EtOH–NIC groups. One-way ANOVA revealed a significant change in xCT expression among these groups in the HIP [F (2, 15) = 5.081380, p = 0.0207, (Figure 5-

5B)] but not in GLT-1 expression [F (2, 15) = 0.3785, p = 0.6912, (Figure 5-5A)],

GLAST expression [F (2, 15) = 0.111438, p = 0.8953, (Figure 5-5C)] and mGluR1 expression [F (2, 15) = 0.2522296, p = 0.7803, (Figure 5-5D)]. Newman-Keuls multiple comparisons revealed that there was no significant changes in xCT expression in the HIP following binge-like EtOH drinking as compared to water control group. However,

EtOH–NIC drinking decreased xCT expression significantly in the HIP compared to

EtOH and water control groups.

231

Figure 5-5. Effects of binge-like drinking of EtOH and EtOH-NIC on relative expression (R) of (A) GLT-1, (B) xCT, (C) GLAST and (D) mGluR1 in the HIP (100% of water control group). One way ANOVA followed by Newman-Keuls analysis revealed that EtOH-NIC but not EtOH exposure reduced xCT/GAPDH ratio in the HIP. The analysis did not show any significant reduction in GLT-1/GAPDH, GLAST/GAPDH and mGluR1/GAPDH ratios between the groups in the HIP. Data are represented as mean ± SEM (n = 6 for each group), (* p < 0.05).

5.3.6 Effects of binge-like drinking of SUC or SUC-NICon GLT-1, xCT, GLAST and mGluR1 expression in the PFC

One-way ANOVA did not revealed any significant differences in GLT-1 expression [F

(2, 15) = 0.1418, p = 0.8689, (Figure 5-6A)], xCT expression [F (2, 15) = 0.4836, p =

0.6259, (Figure 5-6B)], GLAST expression [F (2, 15) = 0.2063, p = 0.8159, (Figure 5-

6C)] and mGluR1 expression [F (2, 15) = 0.372983, p = 0.6949, (Figure 5-6D)] among water control, SUC and SUC-NIC groups expression in the PFC.

232

Figure 5-6. Effects of binge-like drinking of SUC and SUC-NIC on relative expression (R) of (A) GLT-1, (B) xCT, (C) GLAST, and (D) mGluR1 in the PFC (100% of water control group). One way ANOVA followed by Newman-Keuls analysis did not show any significant reduction in GLT-1/GAPDH, xCT/GAPDH GLAST/GAPDH and mGluR1/GAPDH ratios between all groups in the PFC. Data are represented as mean ± SEM (n = 6 for each group).

5.3.7 Effects of binge-like drinking of EtOH, or EtOH-NIC on GLT-1, xCT, GLAST and mGluR1 expression in the PFC

We further determined the expression of GLT-1, xCT, GLAST and mGluR1 between water control, EtOH and EtOH–NIC groups in all studied brain regions. One-way

ANOVA did not demonstrate any significant differences in GLT-1 expression [F (2, 15)

= 0.4153, p = 0.6675, (Figure 5-7A)], xCT expression [F (2, 15) = 0.3513, p = 0.7094,

(Figure 5-7B)], GLAST expression [F (2, 15) = 0.1540, p = 0.8586, (Figure 5-7C)] and

233

mGluR1 expression [F (2, 15) = 0.2625593, p = 0.7725, (Figure 5-7D)] among these groups in the PFC.

Figure 5-7. Effects of binge-like drinking of EtOH and EtOH-NIC on relative expression (R) of (A) GLT-1, (B) xCT, (C) GLAST, and (D) mGluR1 in the PFC (100% of water control group). One way ANOVA followed by Newman-Keuls analysis did not show any significant reduction in GLT-1/GAPDH, xCT/GAPDH GLAST/GAPDH and mGluR1/GAPDH ratios between all groups in the PFC. Data are represented as mean ± SEM (n = 6 for each group).

234

5.3.8 Effects of SUC, SUC-NIC, EtOH, or EtOH-NIC drinking on GPx activity in the HIP

One-way ANOVA followed by Newman-Keuls analysis indicated a significant reduction in GPx activity in the HIP of SUC and SUC-NIC groups as compared to the water control group [F (2,15) = 5.065, p = 0.0209, (Figure 5-8A)]. In addition, one-way

ANOVA followed by Newman-Keuls multiple comparisons showed that % of GPx activity was also significantly reduced in EtOH and EtOH-NIC groups compared to the water control group in the HIP [F (2,15) = 4.194, p = 0.0357, (Figure 5-8B)].

Figure 5-8. Effects of binge-like drinking of SUC, SUC-NIC EtOH, or EtOH-NIC on the activity of GPx in the HIP (100% of water control group). A) One way ANOVA followed by Newman-Keuls analysis revealed that SUC and SUC-NIC exposure reduced GPx activity the HIP. B) One way ANOVA followed by Newman-Keuls analysis revealed that EtOH and EtOH-NIC exposure reduced GPx activity in the HIP. Data are represented as mean ± SEM (n = 6 for each group), (* p < 0.05).

5.4 Discussion

The present study examined the effects of binge-like drinking of EtOH with/without NIC on glial glutamate transporters and mGluR1 expression in three brain regions of female P rats. In addition, the study investigated the effects of SUC on GLT-1, xCT, GLAST and 235

mGluR1 expression to determine whether there is interaction between SUC and NIC on glutamatergic transporters and receptor. The findings indicate that binge-like SUC-NIC drinking decreased GLT-1 expression in the NAc and xCT expression in both the NAc and HIP, while increasing mGluR1 expression in the NAc as well as compared to water control and SUC groups. In addition, binge-like EtOH drinking did not affect glial glutamate transporters in the brain regions examined but did increase mGluR1 expression in the NAc compared to water control groups. Moreover, binge like EtOH-NIC drinking reduced GLT-1 in the NAc and xCT in both the NAc and HIP and increased mGluR1 in the NAc as compared to water control group.

In the present study, the addition of NIC in the SUC solution resulted in a significant reduction in SUC consumption. However, EtOH intake was not significantly changed by the addition of NIC. This indicates that the bitter taste of NIC may reduce SUC consumption but not necessarily EtOH intake. It should be noted that the present study used a binge-like drinking in peri-adolescent P rats, whereas previous work has generally been done in adult rats given continuous access to EtOH and/or NIC. In addition, the present findings indicate that NIC intake was significantly higher in the group given binge-like scheduled access to SUC-NIC compared to those given access to EtOH-NIC.

This effect was probably due to the significantly higher consumption of SUC relative to

EtOH (Fig. 1). Previous work has revealed conflicting results for the effects of NIC exposure on SUC and EtOH consumption (Bito-Onon et al., 2011, Grimm et al., 2012,

Sari et al., 2016). One reason for these inconsistent findings may be the route of NIC administration. For instance, oral NIC self-administration reduced SUC and EtOH intake 236

(Sari et al., 2016) in one study, while others have reported that EtOH and SUC consumption are increased following i.p injections of NIC (Bito-Onon et al., 2011,

Grimm et al., 2012).

A prior study from our group reported that upregulating GLT-1 in the NAc and PFC by ceftriaxone led to attenuation of EtOH and/or NIC drinking behavior in female P rats

(Sari et al., 2016). This indicates that glial glutamate transporters, mainly GLT-1, play critical role in regulating EtOH or NIC seeking [For review see (Alasmari et al., 2016a,

Goodwani et al., 2017)]. In the present work, for the first time, we found that peri- adolescent binge-like scheduled access to SUC-NIC downregulated GLT-1 in the NAc compared to water control and SUC groups, while peri-adolescent EtOH-NIC reduced

GLT-1 expression in the NAc compared to water control and EtOH groups. However, neither SUC nor EtOH binge-like scheduled drinking altered the expression of GLT-1 in the NAc. Previously, continuous exposure to EtOH for five weeks and phasic exposure to NIC for 21 days reduced GLT-1 expression in the NAc of adult rats (Knackstedt et al.,

2009, Alhaddad et al., 2014b, Goodwani et al., 2015). However, chronic limited access to EtOH did not induce any changes in GLT-1 or xCT expression in adult animals

(Griffin et al., 2015, Pati et al., 2016, Stennett et al., 2017). Together these indicate that continuous not-scheduled exposure to EtOH reduces the expression of GLT-1 in the

NAc. Our data also suggest that multiple scheduled NIC self-administrations are able to decrease the expression of GLT-1 in the NAc. Additionally, we did not observe any changes in GLT-1 expression in the HIP following binge-like drinking of EtOH with/without NIC. A previous study reported that phasic exposure to electronic cigarettes 237

vapors-containing NIC for six months did not reduce GLT-1 in the HIP (Alasmari et al.,

2017). Our present data are in agreement with previous findings using adult rats wherein

EtOH or NIC exposure did not cause any changes in GLT-1 expression in the PFC

(Knackstedt et al., 2009, Goodwani et al., 2015). In addition, a recent study found that blocking GLT-1 in the NAc did not attenuate reinstatement of SUC seeking (Bobadilla et al., 2017). Moreover, for the first time, we found that chronic exposure to SUC did not affect GLT-1 expression in the NAc, HIP and PFC.

Several studies, using adult rats, have reported that chronic exposure to EtOH or NIC led to reduction in xCT expression in specific brain regions, including the NAc, HIP and ventral tegmental area (Knackstedt et al., 2009, Alhaddad et al., 2014b, Aal-Aaboda et al., 2015, Alasmari et al., 2017). In this study, for the first time, we investigated the effects of peri-adolescent binge-like drinking of EtOH, SUC, SUC-NIC and EtOH-NIC on xCT expression in the NAc, PFC and HIP. We found that SUC-NIC and EtOH-NIC intakes induced a significant downregulation of xCT expression in the NAc and HIP.

This effect was not observed in the group exposed to EtOH drinking. Previous work showed that xCT expression was reduced after scheduled phasic exposure to NIC but not

EtOH in the NAc, the striatum and HIP (Knackstedt et al., 2009, Griffin III et al., 2014,

Alasmari et al., 2017, Stennett et al., 2017). This suggests that adult and peri-adolescent scheduled EtOH exposure might not cause significant changes in expression of glial glutamate transporters compared to continuous exposure to EtOH. Additionally, previously reported studies and our data have not demonstrated any significant reduction in the expression of xCT following chronic exposure to NIC in the PFC (Knackstedt et 238

al., 2009, Alasmari et al., 2017). Although continuous consumption of EtOH reduced xCT expression in the PFC (Alhaddad et al., 2014a), our data indicate that scheduled binge-intake of EtOH did not affect the expression of xCT in the PFC.

In this study, we did not observe any changes in GLAST expression following binge-like scheduled drinking of EtOH, SUC-NIC or EtOH-NIC for four weeks. Although GLAST is localized throughout the brain, GLAST is highly expressed in the cerebellum rather than forebrain (Lehre and Danbolt, 1998a, Danbolt, 2001). Moreover, GLAST was found highly expressed in the retina (Lehre and Danbolt, 1998a). Continuous EtOH drinking for five weeks or chronic NIC inhalation did not alter the expression of GLAST in the NAc, striatum and PFC (Hakami et al., 2016, Alasmari et al., 2017). Overall, the data indicate that NIC might have a selective downregulatory effect on the expression of

GLT-1 and xCT transporters in NAc or HIP.

The expression of mGluR1 was also determined in the NAc, HIP and PFC following peri-adolescent multiple scheduled binge-like intakes of EtOH with/without NIC. We report that limited access to EtOH and/or NIC upregulated mGluR1 expression in the

NAc. This is in agreement with a previous study that revealed that exposure to EtOH for six months increased mGluR1 expression in the NAc core (Obara et al., 2009). In addition, mGluR1 expression in the amygdala was found to be increased in animals exposed to binge-like scheduled drinking of EtOH (Cozzoli et al., 2014). Other findings reported that offspring of strains that were bred to consume high amount of EtOH, in a limited access paradigm, showed a significant increase in mGluR1 expression in the NAc 239

(Cozzoli et al., 2009, Cozzoli et al., 2012). However, less is known about the effects of

EtOH and NIC co-exposure on the expression of mGluR1 in central reward brain areas.

We found here that co-exposure to EtOH and NIC induced upregulatory effects on mGlurR1 in the NAc. Studies found that phasic exposure to EtOH or NIC resulted in a marked increase in the total extracellular concentrations of glutamate which might indicate increased firing of medium spiny neurons (Griffin III et al., 2014, Griffin et al.,

2015, Ryu et al., 2017). We suggest here that this effect might increase the expression of post-synaptic glutamate receptors such as mGluR1 as a compensatory mechanism.

However, we did not observe any changes in the expression of mGluR1 in the HIP or the

PFC regions. Since little is known about the effects of intermittent exposure to EtOH or

NIC on the mGluR1 expression and synaptic glutamate concentrations in the HIP and

PFC, further studies are required to delineate the relationship between extracellular glutamate concentrations and the expression of post-synaptic glutamate receptors, including mGluR1 in these brain regions.

Several drugs of abuse, including EtOH, are well-known inducers of oxidative stress in the HIP (Pant et al., 2017). Since the activity of GPx has a direct impact on the ability of cells to defend against oxidative stress, recent studies have focused on examining the impact of drug abuse on GPx activity (Biala et al., 2017, Gong et al., 2017). Exposure to water pipe smoke, for instance, was found to reduce the activity of GPx in the HIP

(Alzoubi et al., 2015). This effect was also associated with a significant impairment in the memory and learning of male Wistar rats. Intuitively, an increase in GPx activity has been associated with protective effects against oxidative stress in animals (Miyamoto et 240

al., 2003). A prior study reported that ceftriaxone, a GLT-1 and xCT upregulator, was able to normalize glutathione contents (Amin et al., 2014) suggesting strong association between glutathione system and glial glutamate transporters expression. In this study, we found that SUC-NIC and EtOH-NIC drinking decreased both xCT and GPx activity in the HIP compared to the water control group suggesting a possible correlation between reduction of xCT expression and attenuation of GPx activity in NIC treated rats.

Interestingly, exposure to SUC or EtOH reduced GPx activity but had no effect on xCT expression compared to the water control group. This indicates that SUC and EtOH might affect the activity of GPx through other mechanisms, including the generation of free radicals (Oh et al., 1998, Rosas-Villegas et al., 2017). Overall, our data do not provide conclusive evidence suggesting a direct link between expression of xCT and the activity of GPx in the HIP following exposure to NIC and/or EtOH.

In summary, our work indicates that peri-adolescent co-access to EtOH and NIC in animals exposed to limited access paradigm induced significant changes in the expression of glial glutamate transporters and mGluR1 in the NAc and HIP. Future research is needed to investigate the effects of these drugs of abuse on the glutamatergic system in

NAc subregions including NAc shell and core. These data further confirmed previous findings observed in studies using adult animals. It is important to note that young generation has high rate of EtOH-NIC co-addiction and the long-term biological and physiological effects of these drugs are highly concerned. Thus, the glutamatergic system might be an effective pharmacotherapeutic target to attenuate NIC and EtOH co-

241

addiction. Further studies are warranted in the near future to investigate the specific effect of NIC on oxidative stress parameters in the mesocorticolimbic areas.

Acknowledgements

The presented research was supported in part by AA019458 (Y. Sari) and AA13522

(R.L. Bell) from the National Institutes on Alcohol Abuse and Alcoholism.

Conflict of interest

The authors declare no conflict of interest.

242

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Chapter 6

Summary

6.1 Experimental Design

In our studies, we used different experimental designs to study the expression of astroglial glutamate transporters and nicotinic receptors in the mesocorticolimbic system following the exposure to e-cigarette vapor for six (Figure 5-1A) and three (Figure5-1B) months as described previously (Hwang et al., 2016, Alasmari et al., 2017, Crotty

Alexander et al., 2018). In these studies, we used an inhalation exposure system to expose the mice to e-cigarette vapor-containing nicotine. The beneficial characteristics of using this system are described in our review article (Alasmari et al., 2018). In addition, another design was used to study the effects of EtOH and NIC co-consumption on astroglial glutamate transporters and mGluR1 in the mesocorticolimbic brain areas

(Figure 5-1C).

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Figure 6-1. Experimental timeline for A) Three-month e-cigarette exposure paradigm. B) Six-month e-cigarette exposure paradigm. C) Four-week EtOH and NIC co-consumption paradigm.

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6.2 Outcomes

6.2.1 The effects of chronic exposure to e-cigarette vapors-containing nicotine on nAChRs in the FC, STR and HIP

In these studies, we showed that chronic inhalation of e-cigarette vapors-containing nicotine increased the expression of α7 nAChR and α4/β2 nAChR in central brain regions involved in drug reward and reinforcement (Figure 5-2). It is important to note that previous studies found that chronic exposure to NIC upregulated nAChRs in the brain

(Yates et al., 1995, Sallette et al., 2005, Alsharari et al., 2015, Fasoli et al., 2016).

However, we did not find any changes in HIP α7 nAChR following chronic exposure to e-cigarette vapors-containing nicotine.

Figure 6-2. A) FC, STR and HIP express α7 nAChR and α4/β2 nAChR. B) The effects of chronic exposure to e-cigarette vapors-containing nicotine on the expression of α7 nAChR and α4/β2 nAChR in the FC, STR and HIP. Note the number of nAChRs in the diagram is just an assumption and it does not reveal the real number of these receptors in the brain.

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6.2.2 The effects of chronic exposure to e-cigarette vapors-containing nicotine on glial glutamate transporters in the FC, STR and HIP

In these studies, we showed that chronic inhalation of e-cigarette vapors-containing nicotine reduced the expression of GLT-1 and GLT-1 isoforms (GLT-1a and GLT-1b) in the STR. This effect was associated with reduced xCT expression in the STR and HIP.

However, GLAST expression was not changed following chronic exposure to e-cigarette vapors-containing nicotine (Table 5-1).

Table 6-1. Summary of the effects of chronic exposure to e-cigarette vapors- containing nicotine on the expression of nicotinic receptors and astroglial glutamate transporters in the FC, STR and HIP.

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6.2.3 The effects of chronic exposure to e-cigarette vapors-containing nicotine on the tissue contents of neurotransmitters in the FC and STR

In these studies, we showed that chronic inhalation of e-cigarette vapors-containing nicotine reduced tissue contents of dopamine and GABA in the STR and FC, respectively. Glutamate tissue content in the STR was increased, while glutamine tissue contents were increased in both FC and STR. We did not find any significant changes in serotonin tissue contents in the FC and STR following chronic exposure to e-cigarette vapors-containing nicotine (Figure 5-3). These and others findings suggest that NIC- containing e-cigarette vapors alters the homeostasis of neurotransmitters (Fuxe et al.,

1990, Tizabi et al., 2002, Pidoplichko et al., 2004, Konradsson‐Geuken et al., 2009, Perez et al., 2012, Rademacher et al., 2016)

Figure 6-3. The effects of chronic exposure to e-cigarette vapors-containing nicotine on the tissue contents of neurotransmitters in the FC and STR.

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6.2.4 The effects of chronic exposure to SUC, SUC-NIC, EtOH and EtOH-NIC on astroglial glutamate transporters, mGluR1 and GPx in the NAc, HIP and PFC

In these studies, we showed that chronic intake of NIC reduced the expression of GLT-1 in the NAc and xCT in the NAc and HIP. In addition, chronic NIC exposure increased the expression of mGluR1 in the NAc. Binge intake of EtOH did not affect the expression of astroglial glutamate transporters in central brain regions involved in drug reward and reinforcement. However, mGluR1 expression was increased only in the NAc of rats espoused to four-week limited access of EtOH drinking (Table 5-2). Previous studies from our laboratory found that continuous EtOH drinking downregulated GLT-1 and xCT in the mesocorticolimbic area (Alhaddad et al., 2014, Aal-Aaboda et al., 2015,

Goodwani et al., 2015, Hakami et al., 2016), while scheduled access to EtOH did not affect the expression of astroglial glutamate transporter in the brain (Griffin et al., 2015,

Pati et al., 2016, Stennett et al., 2017). However, phasic exposure to NIC reduced the expression of GLT-1 and xCT in mesocorticolimbic brain regions (Knackstedt et al.,

2009, Alasmari et al., 2017).

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Table 6-2. Summary of the effects of chronic exposure to SUC, SUC-NIC, EtOH, and EtOH-NIC on astroglial glutamate transporters, mGluR1 and GPx in the NAc, HIP and PFC.

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Appendix A

This Dissertation contains the following published and submitted articles:

1. Alasmari, F., Bell R.L, P.S.S.Rao, Hammad A.M, & Sari, Y. (Submitted). Peri- adolescent drinking of ethanol and/or nicotine modulates astroglial glutamate transporters and metabotropic glutamate receptor-1 in female alcohol-preferring rats. Pharmacology Biochemistry and Behavior

2. Alasmari, F., Alexander, L. E. C., Drummond, C. A., & Sari, Y. (2018). A computerized exposure system for animal models to optimize nicotine delivery into the brain through inhalation of electronic cigarette vapors or cigarette smoke. Saudi Pharmaceutical Journal. In press

3. Alasmari, F., Alexander, L. E. C., Nelson, J. A., Schiefer, I. T., Breen, E., Drummond, C. A., & Sari, Y. (2017). Effects of chronic inhalation of electronic cigarettes containing nicotine on glial glutamate transporters and α-7 nicotinic acetylcholine receptor in female CD-1 mice. Progress in Neuro- Psychopharmacology and Biological Psychiatry 77: 1-8.

4. Alasmari, F., Al-Rejaie, S. S., AlSharari, S. D., & Sari, Y. (2016). Targeting glutamate homeostasis for potential treatment of nicotine dependence. Brain research bulletin. 121: 1-8.

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