A Dissertation Submitted to the Temple University Graduate Board

In Partial Fulfillment of the Requirements for the Degree

by

Examining Committee Members:

©

2015

by

Patrick M. Regan

All Rights Reserved

ii ABSTRACT

Multiple classes of pharmaceuticals, including acetaminophen, aspirin, and other nonsteroidal anti-inflammatory drugs (NSAIDs), are used to relieve mild to moderate pain; however, one of the oldest classes of pharmaceuticals, opioids, remains the primary class of drugs used in the management of severe pain. For decades, the unique pharmacological profiles of opioid compounds have suggested the existence of multiple opioid receptor subtypes and, accordingly, four opioid receptors have been cloned to date; the mu (µ)-opioid receptor, the kappa (κ)-opioid receptor, the delta (δ)-opioid receptor, and the nociceptin/orphanin FQ receptor. Additionally, each receptor is encoded by its own distinct gene; the OPRM1, OPRK1, OPRD1, and OPRL1, respectively.

Despite the identification and characterization of these four opioid receptor subtypes, pharmacological data, particularly from opioid receptor knockout mice, does not conform to the predications of a four opioid receptor model and instead suggests the existence of additional receptor subtypes. Additional opioid receptors have since been proposed but corresponding genes have either been unidentified or found to be genetically unrelated. Interestingly, this problem is not unique to opioid receptors, as there is a large discrepancy between the number of protein encoding genes and the repertoire of mRNA transcripts and encoded proteins they produce, with gene products far more numerous than estimates would predict. It is now understood that this discrepancy is due to the generation of multiple RNA transcripts from a single gene. Several mechanisms are utilized in order to generate mRNA transcript variants, or isoforms, from a single gene; iii however, the primary mechanism, known as alternative splicing, involves a complex macromolecular machine, referred to as the spliceosome, through which specific portions of the precursor mRNA (pre-mRNA) sequence are selectively removed and the remaining nucleotide sequences are ligated to form a unique mRNA transcript. Recently, multiple opioid receptor isoforms, particularly for the

µ-opioid receptor, have been identified; however, both their regulation and their functional significance are poorly characterized. As such, multiple studies are needed to more precisely describe alternatively spliced µ-opioid receptor isoforms, particularly the regulation of spliceosome components that determine the splicing specificity of particular isoforms as well as the distinct signaling pathways utilized by particular isoforms both constitutively and following agonist binding. Using a model of dopaminergic neurons, this study sought to examine these questions and found that expression of a particular splice variant, MOR-1X, was up-regulated by morphine through a mechanism involving the essential splicing factor ASF/SF2. Structural comparison of this isoform to the prototypical variant MOR-1 found that the unique distal portion of C-terminal domain contains two additional PKA phosphorylation sites as well as a second agonist-induced phosphorylation motif highly conserved among opioid receptors. Functional comparison of MOR-1 and MOR-1X found distinct signaling differences, both constitutively and following morphine treatment, in MAPK signaling cascades, particularly ERK1/2. While the pharmacological significance of MOR-1X expression and signaling remains unclear, the clinical importance of this finding extends beyond a mechanism of opioid analgesic variability, as the physiological iv roles of opioids also include immunomodulation and have been implicated specifically in the exacerbation of HIV viral replication and pathology, particularly neurocognitive dysfunction. Accordingly, the HIV viral protein Tat was found to block morphine-mediated increases in MOR-1X expression by similarly blocking morphine-mediated increases in ASF/SF2 expression. Consequently, MOR-1X and HIV viral proteins were found to have a unique and synergistic role in the regulation of intrinsic apoptotic signaling cascades, specifically Bax expression, and in cell proliferation. Therefore, the regulation of alternative splicing events by both opioids and HIV viral proteins involves, in part, the inverse regulation of

ASF/SF2 protein expression, through which the expression of the MOR-1X isoform is subsequently and significantly altered. This, in turn, may lead to functional consequences in opioid pharmacokinetics as well as in opioid-related pathology, such as the exacerbation of HIV associated neurocognitive dysfunction, as MOR-1X contains unique functional regions which may be responsible for the observed differences in MAPK and intrinsic apoptotic signaling and cellular proliferation. Collectively, these findings support previous studies that suggest alternative splicing of the MOR is altered by exogenous factors, such as morphine and HIV, identify unique signaling pathways for various opioid receptor isoforms, and are the first to suggest a potential mechanism through which pharmacological interventions could be utilized to alter opioid receptor isoform expression, thereby altering the pharmacological and physiological effects of opioids.

v

DEDICATION

Dedicated to my family and friends

vi TABLE OF CONTENTS

ABSTRACT ...... iii

DEDICATION ...... vi

LIST OF TABLES ...... xii

LIST OF FIGURES ...... xiii

LIST OF ABBREVIATIONS ...... xv

CHAPTER 1 – INTRODUCTION ...... 1

1.1 Identification and Classification of Opioids ...... 1

1.2 Physiological Effects of Opioids ...... 6

1.3 Identification and Classification of Multiple Opioid Receptor

Subtypes ...... 8

1.3.1 Characterization of the δ-opioid receptor ...... 10

1.3.2 Characterization of the κ-opioid receptor ...... 12

1.3.3 Characterization of the µ-opioid receptor ...... 13

1.3.4 Characterization of the nociceptin/orphanin FQ receptor ...... 16

1.4 Hypothesis and Specific Aims ...... 17

CHAPTER 2 – MATERIALS AND METHODS ...... 21

2.1 Cell Culture ...... 21

2.2 Plasmid Constructs & Transfection ...... 21

2.3 Morphine, Recombinant Tat Protein, and Stress Inducer Treatments .. 23

2.4 Extraction and Purification of Cytoplasmic RNA ...... 24

2.5 Primers, Semi-Quantitative Two-Step RT-PCR, and Gel

Electrophoresis ...... 25 vii 2.6 Extraction and Purification of Whole Cell Proteins ...... 28

2.7 Discontinuous Electrophoresis and Li-Cor Western Blotting ...... 29

2.8 MAPK Array Analysis ...... 30

2.9 CAT Reporter Gene Analysis ...... 31

2.10 MTT and Viability Assays ...... 32

CHAPTER 3 – TRANSCRIPTIONAL AND POST-TRANSCRIPTIONAL

REGULATION OF OPIOID RECEPTOR ISOFORMS ...... 33

3.1 Transcriptional and Post-Transcriptional Regulation of Opioid

Receptors ...... 33

3.1.1 Epigenetic regulation ...... 34

3.1.2 Alternative splicing ...... 38

3.1.3 Single nucleotide polymorphisms ...... 45

3.1.4 MicroRNAs ...... 48

3.1.5 Polyadenylation ...... 50

3.2 Regulation of OPRM1 Expression by Opioids and HIV ...... 52

3.2.1 Autoregulation of opioid receptor expression by opioids ...... 54

3.2.2 Regulation of opioid receptor expression by HIV ...... 55

3.3 Results ...... 57

3.3.1 Morphine increases MOR-1X mRNA expression in SH-SY5Y ...... 57

3.3.2 HIV Tat attenuates morphine-mediated increases of MOR-1X mRNA ...... 59

3.4 Discussion ...... 61

CHAPTER 4 – REGULATION OF ALTERNATIVE SPLICING MECHANISMS

BY MORPHINE AND HIV ...... 68

viii 4.1 Mechanisms of Constitutive and Alternative Splicing ...... 68

4.2 Auxiliary Splicing Proteins ...... 76

4.2.1 Heterogeneous nuclear ribonucleoproteins (hnRNPs) ...... 77

4.2.2 SR proteins ...... 78

4.3 Regulation of Alternative Splicing by Modification of Auxiliary Splicing

Proteins ...... 84

4.3.1 Spatial and temporal regulation of auxiliary splicing proteins ...... 85

4.3.2 Phosphorylation of SR proteins ...... 88

4.3.3 Splice site consensus sequences for auxiliary splicing proteins ...... 94

4.3.4 Concentration-dependent activity and antagonism ...... 102

4.4 Autoregulation of HIV viral genome constitutive and alternative

splicing ...... 106

4.5 Results ...... 113

4.5.1 Morphine-mediated increases in ASF/SF2 protein is attenuated by Tat ...... 113

4.5.2 Overexpression of ASF/SF2 increases MOR-1X mRNA expression ...... 114

4.5.3 Absence of SFRS1 transcriptional regulation by morphine and Tat ...... 116

4.6 Discussion ...... 119

CHAPTER 5 – STRUCTURAL AND FUNCTIONAL VARIABILITY OF MOR

ISOFORMS ...... 123

5.1 Structural Organization of Opioid Receptors ...... 123

5.1.1 The G protein-coupled receptor family ...... 124

5.1.2 The opioid receptor family ...... 128

5.2 Mechanisms of GPCR and Opioid Receptor Signal Transduction ...... 132

5.2.1 G protein-dependent signaling mechanisms ...... 133 ix 5.2.2 G protein-independent signaling mechanisms ...... 139

5.2.3 Activation of MAPK pathways ...... 142

5.2.4 Agonist-independent signaling mechanisms ...... 155

5.2.5 Opioid receptor-independent signaling mechanisms ...... 158

5.3 Modulation of GPCR and Opioid Receptor Signaling ...... 162

5.3.1 Regulators of G protein signaling ...... 163

5.3.2 Receptor phosphorylation, desensitization, and internalization ...... 165

5.3.3 Receptor oligomerization ...... 174

5.3.4 Divergent signaling of opioid receptor isoforms ...... 179

5.4 Results ...... 188

5.4.1 Comparison of MOR-1 and MOR-1X amino acid sequences and predicted

functional motifs ...... 188

5.4.2 Activation of MAPK cascades by MOR-1X is distinct from MOR-1 ...... 190

5.5 Discussion ...... 197

CHAPTER 6 – OPIOIDS AND HIV-ASSOCIATED

NEUROPATHOGENESIS ...... 203

6.1 Mechanisms of Programmed Cell Death ...... 203

6.1.1 Modulation of cell viability by opioids ...... 213

6.2 Opioids & HIV Pathogenesis ...... 218

6.2.1 Opioid-mediated immunomodulation ...... 220

6.2.2 Modulation of HIV infectivity by opioids ...... 225

6.2.3 HIV-associated neurocognitive dysfunction ...... 229

6.2.4 Opioid synergism in HIV-associated neurocognitive dysfunction ...... 237

6.3 Results ...... 245

x 6.3.1 MOR-1X uniquely regulates apoptotic, but not autophagic, proteins ...... 246

6.3.2 MOR-1X signaling reduces mitochondrial dehydrogenase activity but not

viability ...... 253

Table 6.1: Viability of MOR-1 and MOR-1X expressing HEK293 cells...... 258

6.4 Discussion ...... 258

CHAPTER 7 – CONCLUSIONS AND FUTURE DIRECTIONS ...... 264

7.1 Conclusions ...... 264

7.1.1 Alternative splicing of the MOR is inversely regulated by morphine and Tat

through modulation of ASF/SF2 expression ...... 264

7.1.2 Unique MAPK signaling of MOR-1X is attributed to additional phosphorylation

motifs of the C-terminal domain ...... 265

7.1.3 MOR-1X constitutively decreases Bax expression and decreases cellular

metabolism upon chronic, high dose morphine treatment ...... 266

7.2 Future Studies ...... 268

7.2.1 Cell-type specificity in opioid pharmacology ...... 268

7.2.2 Complexity of alternative splicing mechanisms ...... 271

7.2.3 In vitro models of HIV-associated neurocognitive dysfunction ...... 272

REFERENCES ...... 275

xi LIST OF TABLES

Table

2.1 MOR-1 isoform specific primers and annealing temperatures ...... 28

6.1 Viability of MOR-1 and MOR-1X expressing HEK293 cells ...... 258

xii LIST OF FIGURES

FIGURE

3.1 Schematic representation of human OPRM1 alternative

splicing ...... 44

3.2 Increased expression of MOR-1X mRNA in SH-SY5Y following

morphine treatment ...... 58

3.3 HIV viral protein Tat attenuates morphine-mediated increases in

MOR-1X mRNA ...... 60

3.4 Endogenous SH-SY5Y expression of several MOR isoforms is not

significantly affected by morphine or HIV Tat ...... 61

4.1 ASF/SF2 protein expression in SH-SY5Y following opioid and Tat

treatments ...... 114

4.2 Overexpression of ASF/SF2 protein increases MOR-1X mRNA ...... 116

4.3 Morphine and Tat do not alter SFRS1 promoter activity or ASF/SF2

RNA expression ...... 118

5.1 Comparison of MOR-1 and MOR-1X amino acid sequences and

predicted functional motifs ...... 190

5.2 Divergent ERK/RSK signaling in MOR-1- and MOR-1X-transfected

HEK293 cells constitutively and following morphine treatment .... 193

5.3 Divergent MAPK signaling in MOR-1- and MOR-1X-transfected

HEK293 cells constitutively and following morphine treatment .... 195

6.1 Morphine does not affect Beclin-1 expression or LC-3 conversion in

either MOR-1 and MOR-1X expressing HEK293 cells ...... 245 xiii 6.2 Constitutive reduction in Bax by MOR-1X is not synergistic with HIV

viral protein signaling ...... 251

6.3 Morphine-mediated reduction in cellular metabolism by MOR-1X is

not synergistic with HIV viral protein signaling ...... 256

xiv LIST OF ABBREVIATIONS

7TM 7 transmembrane

ACTH adrenocorticotropic hormone

ADP adenosine diphosphate

Ago Argonaute

AIDS acquired immunodeficiency syndrome

AIF apoptosis inducing factor

ASF/SF2 alternative splicing factor/splicing factor 2

ANI asymptomatic neurocognitive impairment

ANT adenine nucleotide translocator

AP activator protein

ASK apoptosis signal-regulating kinase

ATCC American Type Culture Collection

ATP adenosine triphosphate

Baf bafilomycin

BBP branch point binding protein

CAD caspase-activated DNase

CaM calmodulin

CaMK calmodulin-dependent protein kinase

CaMKII calmodulin-dependent protein kinase II

cAMP cyclic adenosine monophosphate

cART combination antiretroviral therapy

xv CDK cyclin-dependent kinase

cDNA complementary DNA

CF cleavage factor

CLK CDC-like kinase

CMV cytomegalovirus

CNS central nervous system

CPSF cleavage-polyadenylation specificity factor

CREB cAMP response element-binding protein

CRF corticotropin-releasing factor

CstF cleavage-stimulation factor

CTX cholera toxin

DAMGO [D-Ala2,MePhe4,Gly(ol)5]enkephalin

DISC death-inducing signaling complex

DMEM Dulbecco's Modified Eagle's Medium

DNMT DNA methyltransferase

Dnmt1 DNA (cytosine-5-)-methyltransferase 1

DOR delta (δ)-opioid receptor

DPDPE [D-Pen2,D-Pen5]enkephalin

DR death receptor

EAAT2 excitatory amino acid transporter-2

EBV Epstein-Barr virus

eIF4F eukaryotic initiation factor 4F

xvi ER endoplasmic reticulum

ERK extracellular signal-regulated kinase

ESE exonic splicing enhancer

ESS exonic splicing silencer

FADD Fas-associated death domain protein

FasL Fas ligand

FasR Fas receptor

FBS fetal bovine serum

GDP guanosine-diphosphate

GPCR G protein-coupled receptor

GRKs G protein-coupled receptor kinases

GSK-3 glycogen synthase kinase-3

GTP guanosine-triphosphate

HAART highly active antiretroviral therapy

HAD HIV-associated dementia

HAND HIV-associated neurocognitive disorder

HBSS Hank's Balanced Salt Solution

HDAC histone deacetylase

HIV human immunodeficiency virus

HIVE HIV encephalitis

hnRNP heterogeneous nuclear ribonucleoprotein

HPA hypothalamic-pituitary-adrenal

xvii IAP inhibitors of apoptosis proteins

ICAD inhibitor of caspase-activated DNase

IDT Integrated DNA Technologies

IDUs injection drug users

IFN interferon

IGC interchromatin granule cluster

IHC immunohistochemistry

IL interleukin

INBtxA 3-Iodobenzoylnaltrexamide 1

iNOS inducible nitric oxide synthase

IP-10 INF-γ-inducible protein 10

IP3 inositol 1,4,5-triphosphate

IRES internal ribosome entry segment

ISE intronic splicing enhancer

ISH in situ hybridization

ISS intronic silencing silencer

JCV JC virus

JNK c-Jun amino-terminal kinase

KEPI kinase-enhanced PP1 inhibitor

KOR kappa (κ)-opioid receptor

LC3 light chain 3

LPS lipopolysaccharide

xviii LRP low density lipoprotein receptor-related protein

LTP long-term potentiation

LTR long terminal repeat

M-CSF macrophage-colony stimulating factor

M6G morphine-6β-glucuronide

MAPK mitogen-activated protein kinase

MAPKK MAPK kinase

MAPKKK MAPK kinase kinase

MBP methyl-CpG-binding protein

MCMD minor cognitive motor disorder

MCP-1 monocyte chemoattractant protein-1

MeCP2 methyl CpG binding protein 2

miRISC RNA-induced silencing complex

miRNA microRNA

MK MAPK-activated protein kinase

MND mild neurocognitive disorder

MNK MAPK-interacting kinase

MOR mu (µ)-opioid receptor

MPT mitochondrial permeability transition

MSK mitogen- and stress-activated kinase

MTT 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide

NCBI National Center for Biotechnology Information

xix NK natural killer

NMD nonsense-mediated decay

NMDA N-methyl-d-aspartate

NMDAR N-methyl-d-aspartate receptor

NO nitric oxide

NRSF neuron-restrictive silencer factor

NSAIDs nonsteroidal anti-inflammatory drugs

OFQ/N orphanin FQ/nociception

OLR1 opioid receptor-like receptor

ORF open reading frame

PDGF platelet-derived growth factor

PE phosphatidylethanolamine

PLC phospholipase C

PNS peripheral nervous system

POMC proopiomelanocortin

PP1 protein phosphatase 1

PP2A protein phosphatase 2A

PPT polypyrimidine tract

pre-miRNA precursor miRNA

pre-mRNA precursor mRNA

PTX pertussis toxin

REST RE1-silencing transcription factor

xx RGS regulator of G protein signaling

RISC RNA-induced silencing complex

ROS reactive oxygen species

RSK 90kDa ribosomal S6 kinase

RT reverse transcriptase

RT-PCR reverse transcription polymerase chain reaction

rTat recombinant Tat

SAPK stress-activated protein kinase

SF1 splicing factor 1

snoRNA small nucleolar RNA

SNP single nucleotide polymorphism

snRNP small nuclear ribonucleoprotein

SO superoxide

SP specificity protein

SR serine-arginine

SRPK SR-specific protein kinase

SRSF serine/arginine-rich splicing factor

ssDNA single-stranded DNA

STAT signal transducer and activator of transcription

TAR trans-activation response

TIAR TIA-1-related

TLR toll-like receptor

xxi TM transmembrane

TNF tumor necrosis factor

TNFR1 tumor necrosis factor receptor 1

Tra2β Transformer-2 protein homolog β

TRADD TNFR1-associated death domain protein

U2AF U2 snRNP auxiliary factor

USF upstream stimulatory factor

UTR untranslated region

UVC ultraviolet-C

VTA ventral tegmental area

YY1 Yin Yang 1

xxii CHAPTER 1 – INTRODUCTION

1.1 Identification and Classification of Opioids

Opioids represent one of the oldest classes of clinically important pharmaceuticals and their use, typically as a tincture of opium extracted from the opium poppy, has been around for over a millennia (Trescot, Datta et al. 2008).

Traditionally, the term “opiate” is used to refer to compounds derived from the opium poppy (Papaver somniferum) and their synthetic analogues, whereas

“opioid” is a more general term referring to all compounds, isolated naturally or created synthetically, that have opiate-like actions (Reisine and Bell 1993,

Somogyi, Barratt et al. 2007). In an attempt to understand the mechanisms through which isolated and synthesized opioids exerted their effects, it was discovered that exogenous opioid compounds mimick endogenous opioid peptides (Reisine and Bell 1993, Abbadie and Pasternak 2002). These endogenous peptides are synthesized from larger precursor proteins, which are cleaved at basic residues to produce the active opioid peptide. In following, endogenous opioids are classified according to their precursor peptide and generally fall into one of three families, endorphins or enkephalins, both characterized in 1975, or dynorphins, identified later in 1979.

Proopiomelanocortin (POMC) serves as the precursor peptide for the endorphin family of opioid peptides (α- and β-endorphin), as well as for multiple other peptides, including adrenocorticotropic hormone (ACTH), also known as corticotrophin, and for α-MSH, which compose the non-opioid peptide family of

1 melanocortins (Przewlocki 2004). The enkephalins represent a family of pentapeptides (YGGFM and YGGFL) derived from pre-proenkephalin through a complex process that generates both long and short peptides. Pre-prodynorphin, the precursor peptide for the dynorphin family of endogenous opioid peptides, generates multiple opioid peptides, including dynorphin A, dynorphin B, and α- and β-neoendorphin. Additional, uncategorized opioid peptides with unidentified precursors have also been isolated and do not belong in any of these 3 families

(Singh, Bajpai et al. 1997, Zadina, Martin-Schild et al. 1999, Abbadie and

Pasternak 2002). Overall, endogenous opioid peptides also show heterogeneity in their neuroanatomical localization, which may simply be the result of the variable distribution of their corresponding precursor proteins or processing enzymes. Additionally, the selective neuroanatomical distribution of opioid peptides may reflect their individual functional roles in disparate biological processes (Fichna, Janecka et al. 2007).

Most non-peptide opioids are categorized into one six chemical classes, generated by the systematic manipulation of the chemical structure of morphine.

The most well-known opioids, such as morphine and heroin, belong to the 4,5α- epoxymorphinan opiate class. This class is characterized by a benzene ring with a phenolic, stereospecific hydroxyl group at position 3, essential for activity in only the natural levorotatory (-) enantiomers, as well as an alcohol hydroxyl group at both position 6 and the nitrogen atom. Within this class, manipulations at the 6-position have been shown to alter potency of the given drug. This was identified in the natural metabolites of morphine, morphine-6β-glucuronide (M6G) 2 and morphine-6-sulfate, which are glucuronidated and sulfonated, respectively, at the 6-position, causing increased potency. Likewise, heroin, which is acetylated at both the 3- and 6-positions, is more potent than morphine. This is most likely due to the fact that acetylation enhances the ability of the drug to pass through the blood-brain barrier, resulting in greater penetration into the brain from an equivalent dose. Using this principle, alterations of the 6-position, by converting the hydroxyl group to a ketone, have been used to synthesize potent analgesics, including hydromorphone and hydrocodone. Modifications of the 6- position, as well as the tertiary nitrogen, have also been used to generate clinically important opioid antagonists, such as naloxone and naltrexone (Raynor,

Kong et al. 1994, Pasternak and Pan 2013). A second class of opioid compounds, the morphinans, are structurally similar to the 4,5α- epoxymorphinans but lack the 4,5-epoxy bridge, C7–C8 double bond, and the 6- hydroxyl group. Despite these missing chemical structures, morphinans still show rigid stereoselectivity similar to 4,5α-epoxymorphinans, with only the levorotatory

(-) enantiomer being active. Benzomorphans, a third class of opioids, are generated by removing the “C ring” of the 4,5α-epoxymorphinan structure. These opioids typically have prominent psychotomimetic properties and, unlike 4,5α- epoxymorphinans and morphinans, do not always show stereoselectivity, with the dextrorotatory (+) enantiomer of some benzomorphans having off target effects. Additional classes of opioids, including oripavines, phenylpiperidines, and acyclic analgesics, represent more complex manipulations of the 4,5α- epoxymorphinan chemical structure but are still clinically useful both as 3 analgesics and as treatments for opioid addiction. Completely synthetic opioids, which do not use opium for synthesis and are not represented in any opioid class, have also been manufactured. The most notable, methadone, is of great clinical importance due to its prolonged half-life and its efficacy as an opioid addiction therapy. Stereoselectivity is not always characteristic of unclassified opioids, as is seen with methadone, of which the dextrorotatory (+) enantiomer is thought to have antagonistic properties on N-methyl-d-aspartate (NMDA) receptors (NMDARs). Additional, uncharacterized opioids, such as a 4-phenyl- piperidine analogue of codeine commonly known as tramadol, [D-

Ala2,MePhe4,Gly(ol)5]enkephalin (DAMGO), and [D-Pen2,D-Pen5]enkephalin

(DPDPE) are of great value to researchers since they are enzymatically stable and highly selective for a single opioid receptor subtype (discussed in section

1.3). Since their initial discovery, thousands of opioid compounds, with a great variety of chemical structures, stability, potency, and metabolites, have been synthesized and have been of great use both clinically and in researching opioid pharmacology (Reisine and Bell 1993, Somogyi, Barratt et al. 2007, Trescot,

Datta et al. 2008, Pasternak and Pan 2013).

Although originally identified as the active agent in opium produced from

Papaver somniferum, it is now recognized that morphine synthesis is not restricted to plants but is also present in animal tissues, including the mammalian brain. Endogenous morphine in mammals is identical in structure to that isolated from Papaver somniferum and its synthesis is associated with that of dopamine and catecholamines, as shown in the human neuronal catecholamine-producing

4 cell line SH-SY5Y. Endogenous morphine is released from SH-SY5Y cells via a

Ca2+-dependent mechanism following stimulation or physical trauma. The

UGT2B7 enzyme, responsible for metabolizing morphine into inactive morphine-

3-glucuronide (M3G) and highly active M6G, is also expressed in SH-SY5Y and, as such, M6G has been found in secretory granules. This suggests a role for both endogenous morphine and its metabolites in brain physiology, possibly in brain plasticity and development, by serving as a neurotransmitter and/or a neuroendocrine factor. Criteria for neurotransmitters include localization in nerve terminals within secretory vesicles, the presence of specific pre- and postsynaptic receptors able to induce specific effects, secretion upon depolarizing stimulation via a Ca2+-dependent mechanism, and regulation of expression by an extra- or intracellular mechanism. While endorphins are primarily cited as the endogenous opioid neuromodulators in mammals, a strong case can be made for endogenous morphine also serving in this role as a neurotransmitter. Multiple studies have collectively shown that morphine meets all four criteria; however, a comprehensive study identifying endogenous morphine as a true neurotransmitter by meeting all four criteria, within the same system, has not yet been published (Stefano, Goumon et al. 2000, Muller,

Glattard et al. 2008). Therefore, examination of the physiological effects of opioids are typically reserved to either endogenous opioid peptides or exogenous opioid compounds.

5 1.2 Physiological Effects of Opioids

While multiple classes of drugs, including acetaminophen, aspirin, and other nonsteroidal anti-inflammatory drugs (NSAIDs), are used to relieve mild to moderate pain, opioids remain the primary class of drugs used in the management of severe pain. Additionally, while the use of opioid derivatives eliminate the sensation of pain, they are differentiated from local anesthetics as they do so without interfering with primary sensations, such as light touch, temperature, sharp/dull sensations and position sense (Abbadie and Pasternak

2002, Pasternak and Pan 2013). Opioid mediated analgesia is the result of selective inhibition of nociceptive C-fibers and A delta fibers by indirectly altering the membrane potential of these fibers. Inhibition of C- and A delta fiber activity blocks the synaptic release of neurotransmitters associated with pain signaling, including substance P and glutamate. Opioids also mediate the inhibition of

GABAergic interneurons in the ventral tegmental area, blocking GABA release, thus indirectly increasing dopaminergic neuron activity in the nucleus accumbens. The extra dopamine released in the nucleus accumbens mediates a sensation of intense pleasure and represents the reward response characteristic of opioids. As such, this axis is thought to contribute greatly to opioid addiction.

(Przewlocki 2004, Trescot, Datta et al. 2008). Opioids also modulate the activity of adrenergic and other peptidergic neurons, including systemic motor neurons and corticotropin-releasing factor (CRF) neurons within the hypothalamus, the latter of which is implicated in opioid mediated anxiety and the adversive effects of opioid withdrawal (Carmody 1987, Przewlocki 2004).

6 While they are primarily used in the modulation of pain sensation, opioids are able to regulate a number of physiological processes. Within the central nervous system (CNS) and peripheral nervous system (PNS), the broad distribution of the opioid peptides suggests that they play an important role as neurotransmitters and neuromodulators and, as such, have been shown to affect neural growth, differentiation, synaptic plasticity, neurotransmitter release of dopamine, noradrenaline, serotonin, and acetylcholine, and cognitive functions, including learning, memory, affective behaviors, locomotion, endocrine functions such as water balance, limbic homeostasis, hunger, sexual behavior, stress responses, and complex functions such as reward, arousal, vigilance, and social defeat. Given this broad modulation of CNS and PNS functions, opioids have been implicated in the pathophysiology of many nervous system disorders, including Parkinson’s, Tourette syndrome, Alzheimer’s, schizophrenia, epilepsy, and depression (Reisine and Bell 1993, Reisine 1995, Peckys and

Landwehrmeyer 1999, Waldhoer, Bartlett et al. 2004, Fichna, Janecka et al.

2007, Georganta, Agalou et al. 2010, Cuellar-Herrera, Velasco et al. 2012). In addition to the nervous system, opioids are known to modulate multiple peripheral organ systems. The use of opioids is known to inhibit gastrointestinal motility and can therefore be used clinically to treat disorders such as diarrhea.

Another, but more dangerous, clinical application is the use of opioid analogs to cause respiratory depression. When used in an outpatient setting, opioid-induced respiratory depression rarely presents a risk, although it can become problematic in patients with an underlying pulmonary disorder and is the primary cause of

7 death in opioid abuse. Severe clinical complications may also arise due to the profound immunosuppression exerted by prolonged opioid treatment (discussed in section 6.2.1). Other clinically relevant actions of opioid compounds include their ability to stimulate either tachycardia or bradycardia in addition to promoting either hypertension or hypotension. (Carmody 1987, Reisine and Bell 1993,

Chao, Gekker et al. 1996, Abbadie and Pasternak 2002, Pasternak and Pan

2013).

1.3 Identification and Classification of Multiple Opioid Receptor Subtypes

There is a vast amount of pharmacological evidence that suggests the existence of multiple opioid receptor subtypes, such as the unique pharmacological profiles of individual opioids as well as the more recent inconsistencies seen in genetic knockout models. Indeed, multiple binding sites, through which various opioids exert their physiological effects, had been proposed as early as the 1950s and 1960s based on rigid structure-activity relationships of opioids and were eventually identified in mammalian brain tissue in 1973 (Standifer and Pasternak 1997, Snyder and Pasternak 2003, Dietis,

Rowbotham et al. 2011, Pasternak and Pan 2013). Since then, opioid receptors have been identified in a wide range of vertebrates. To date, four opioid receptors have been cloned; the mu (µ)-opioid receptor (named for its affinity for morphine), the kappa (κ)-opioid receptor (named for its affinity for ketocyclazocine), the delta (δ)-opioid (named for the mouse vas deferens where it was first isolated), and the nociceptin/orphanin FQ receptor. The three classical

8 opioid receptors, µ, κ, and δ, display nearly 60% homology with one another, while the newly discovered nociceptin/orphanin FQ receptor displays nearly 50% homology. Following the identification of these four opioid receptors by selective ligand binding, it was found that each receptor is encoded by its own distinct gene. These genes, named OPRM1, OPRK1, OPRD1, and OPRL1 as they encode the µ, κ, δ, and nociceptin/orphanin FQ receptors, respectively, display a similar genomic structure, suggesting a single, common ancestral gene. This shared evolutionary history was later confirmed using a combination of positional and phylogenetic data. Additional opioid receptors have been proposed based off pharmacological data, including the sigma (σ)-receptor (named for its affinity for

SKF10047), responsible for psychomimetic effects, dysphoria, and stress- induced depression. However, once this receptor was cloned in 1996, it was identified to be single transmembrane-spanning protein targeted by other drugs of abuse, such as PCP, and is no longer classified as an opioid receptor.

Likewise, the proposed zeta (ζ)-opioid receptor was cloned and showed no homology to the classical opioid receptors. Other proposed receptors, including the lambda (λ)-opioid receptor and epsilon (ε)-opioid receptor are poorly characterized and their corresponding genes have not been identified (Wei and

Loh 2002, Waldhoer, Bartlett et al. 2004, Dreborg, Sundstrom et al. 2008,

Trescot, Datta et al. 2008, Wei and Loh 2011). An additional protein receptor which is highly homologous to both opioid and somatostatin receptors, has also been characterized. This receptor, named C3, shares many structural features with opioid receptors (discussed in section 5.1.2), including conserved 9 glycosylation sites, a cyclic AMP-dependent kinase phosphorylation site in the third cytoplasmic loop, and a palmitoylation site on the intracellular C-terminal domain. Receptors that exhibit homologies significantly greater than 50%, particularly within their transmembrane domains, are often regarded as comprising subfamilies of a receptor type; however, despite almost 70% homology with opioid receptors, the C3 receptor does not bind any known opioids and is therefore not considered a member of the opioid receptor family

(Lachowicz, Shen et al. 1995). This receptor highlights the difficulty in characterizing opioid receptor subtypes, as homology alone is not sufficient.

Therefore, multiple criteria must be used to classify opioid receptor subtypes, including selective binding of opioid compounds, induction of opioid-like systemic effects, and the identification of a corresponding gene that is phylogenetically related to accepted opioid receptor genes.

1.3.1 Characterization of the δ-opioid receptor

The δ-opioid receptor (DOR) was the first opioid receptor successfully cloned and was initially identified by its selective binding of enkephalins. Like most opioids, δ-selective agonists induce analgesia; however, δ-selective agonists do not induce respiratory depression or inhibit gastrointestinal motility, making them favorable therapeutic agents. Multiple studies utilizing immunohistochemistry (IHC), in situ hybridization (ISH), radiolabeled ligand binding, reverse transcription polymerase chain reaction (RT-PCR), and retrograde labeling have allowed for the characterization of opioid receptor localization, which collectively exhibits regional-specific differences among 10 subtypes. DORs can be found abundantly throughout the brain with various densities, with the highest densities being found in the cerebral cortex (Abbadie and Pasternak 2002, Wang and Wessendorf 2002, Mrkusich, Kivell et al. 2004).

Outside the CNS, DORs are found within multiple physiological systems (Gray,

Coupar et al. 2006). Subcellular localization of opioid receptors, in general, is less defined. Limited expression of DORs on both the cell membrane and within the cytoplasm of both presynaptic and postsynaptic terminals has been identified, with a greater proportion of presynaptic DORs localized to neuronal axons. This subcellular distribution of DORs suggests a predominantly presynaptic function

(Arvidsson, Riedl et al. 1995, Peckys and Landwehrmeyer 1999, Abbadie,

Lombard et al. 2002, Abbadie and Pasternak 2002, Kivell, Day et al. 2004,

Pennock and Hentges 2011).

As stated earlier, the δ-opioid receptor is encoded by the OPRD1 gene, located on chromosome 1 in humans (Zaki, Bilsky et al. 1996). This gene utilizes a minimal promoter sequence that lacks a TATA sequence but contains an E box sequence, which is activated by the binding of upstream stimulatory factor (USF), and a GC box, which is activated by the binding of SP proteins. Additional regulatory elements include an Ets-binding site, which overlaps with the E box, as well as regulatory sites for AP-1 and AP-2 binding. While the identification of these regulatory sites has helped to understand the regulation of OPRD1 activity, additional regulatory sites remain to be elucidated, particularly those responding to the action of growth factors and cytokines (Wei and Loh 2002).

11 1.3.2 Characterization of the κ-opioid receptor

Although originally identified by their high affinity for benzomorphans, the

κ-opioid receptor (KOR) selectively binds the dynorphin family of endogenous opioid peptides. Clinically, multiple κ-selective agonists have been used for their ability to induce potent analgesia. Similar to δ-selective agonists, κ-selective agonists do not induce respiratory depression and have limited effects on gastrointestinal motility. A unique aspect of κ-selective agonists is that they do not stimulate tolerance or physiological dependence, making them ideal for clinical use. Unfortunately, many κ-selective agonists elicit unpleasant psychomimetic effects, dysphoria, and diuresis, limiting their therapeutic potential

(van Der Houven Van Oordt, Newton et al. 2000, Abbadie and Pasternak 2002,

Wang, Sun et al. 2010). Relative to other opioid receptors, KORs are found in low abundance in mice and rats. The greatest density of KORs occurs within striatum, thalamus, hypothalamus, cerebral cortex, cerebellum, brainstem, and spinal cord; however, as with most opioid receptor subtypes, localization and density is highly variable between species. For example, the terminal field of the mossy fiber system in the hilus of guinea pigs contains a high density of KORs while this same region is devoid of KORs in rats (Fowler and Fraser 1994,

Peckys and Landwehrmeyer 1999, Abbadie and Pasternak 2002, Wang, Sun et al. 2010). Additionally, there is limited expression of KORs within physiological systems outside the CNS (Gray, Coupar et al. 2006, Wang, Sun et al. 2010).

Subcellular localization of KORs is relatively unknown, although evidence suggests a function on presynaptic terminals (Pennock and Hentges 2011). 12 The gene encoding κ-opioid receptors, OPRK1, is located on human chromosome 8 (Zaki, Bilsky et al. 1996). It is unique in that it utilizes two promoters separated by a non-coding exon. Transcription initiation by the first promoter region within OPRK1 utilizes two TATA boxes, although this is not well conserved between species. Transcription initiation by the second promoter region is localized to an intronic region of OPRK1 and utilizes a CAAT box and a

NF-κB transcription factor binding site. This intronic sequence is also involved in the suppression of both OPRK1 promoters as it contains an Ikaros binding site.

At least two types of transcripts are produced from the OPRK1 gene, depending on the promoter utilized, with transcription of the classical transcript being initiated downstream from one of two TATA boxes while transcription of an alternative transcript begins within intron 1, resulting in its retention in the mature mRNA (Yakovlev, Krueger et al. 1995, Wei and Loh 2002). As with OPRD1, characterization of transcription regulatory sites within OPRK1 is lacking and, as such, additional studies are needed to fully characterize the OPRK1 gene.

1.3.3 Characterization of the µ-opioid receptor

The µ-opioid receptor (MOR) was cloned shortly after the δ-opioid receptor and, clinically, represents the most relevant opioid receptor as it has a high affinity for classical opioid agonists, such as morphine and heroin, and antagonists, such as naloxone. Endogenously, the MOR is the target receptor for endorphins, although MORs may also interact with opioids belonging to other families, such as dynorphins. Its biological significance can be inferred from the

13 fact that it is highly conserved across species, with more than 95% homology between the human and rat receptors. Activation of MORs by µ-selective agonists causes analgesia, respiratory depression, immunosuppression, and inhibition of gastrointestinal motility in addition to stimulating hormone and neurotransmitter release. Various densities of MORs can be found in multiple structures throughout the CNS, including the cerebral cortex, striatum, thalamus, hypothalamus, cerebellum, brain stem and spinal chord, with expression seen more so in neurons than glial cells (Carmody 1987, Wang, Johnson et al. 1994,

Arvidsson, Riedl et al. 1995, Kaufman, Keith et al. 1995, Peckys and

Landwehrmeyer 1999, Abbadie and Pasternak 2002, Wang and Wessendorf

2002, Kivell, Day et al. 2004, Volkow and Normand 2013). Likewise, many peripheral physiological systems also express MORs in great abundance (Gray,

Coupar et al. 2006). The subcellular localization of MORs is highly diverse, with

MORs being functionally identified within the cell membrane and cytoplasm of pre- and postsynaptic terminals. Expression is predominantly postsynaptic, being localized to the somatodendritic region; however, axonal expression of both MOR protein and mRNA has also been identified in discrete neuronal populations

(Arvidsson, Riedl et al. 1995, Abbadie and Pasternak 2002, Kivell, Day et al.

2004, Pennock and Hentges 2011). Therefore, MORs may have both a presynaptic and postsynaptic function.

The MOR is encoded by the OPRM1 gene, which is located on chromosome 6 in humans (Kaufman, Keith et al. 1995, Wei and Loh 2011).

Mechanisms of OPRM1 expression have largely been studied in mouse, with the

14 conservation of homologous sequences exhibiting similar functions and mechanisms assumed to occur across closely related species; however, this assumption is not entirely accurate as a wide disparity in regulatory regions between closely related species has been characterized (Choe, Dong et al.

2011). Within humans, two promoter regions, designated as proximal and distal, can be found and lack both TATA and CCAAT sequences. While these promoter regions can function independently from each other to promote transcription, transcription initiation by the proximal promoter region appears to be favored

(Liang, Mestek et al. 1995, Ko, Minnerath et al. 1997, Pan 2005, Pasternak and

Pan 2013), accounting for almost 95% of OPRM1 activity (Wei and Loh 2002,

Law, Loh et al. 2004). Regardless, multiple transcription initiation sites in the 5’ regulatory region of the distal promoter region have also been reported (Andria and Simon 1999, Xu and Carr 2001) and, as such, both the proximal and distal promoter regions are subject to regulation. Several DNA elements homologous to known transcription factor binding sites have been identified within this region, including multiple sites for activator protein (AP) 1 and 2, specificity protein (SP)

1 and 3, cAMP response element-binding protein (CREB), Yin Yang 1 (YY1),

E2F1, signal transducer and activator of transcription (STAT) 1, 3, and 6, and neuron-restrictive silencer factor (NRSF), also known as RE1-silencing transcription factor (REST) (Liang, Mestek et al. 1995, Wendel and Hoehe 1998,

Bedini, Baiula et al. 2008, Choi, Hwang et al. 2008, Kim, Hwang et al. 2008, Liu,

Li et al. 2010, Pasternak and Pan 2013). In addition to these proximal and distal promoter regions, a third, TATA-containing promoter region has been identified

15 upstream of exon 11 (Pan 2005, Malik, Flock et al. 2006, Pasternak and Pan

2013). Therefore, similar to OPRK1, at least three types of transcripts are produced from the OPRM1 gene depending on whether the proximal, distal, or exon 11 promoter is utilized.

1.3.4 Characterization of the nociceptin/orphanin FQ receptor

The nociceptin/orphanin FQ receptor, also called the opioid receptor-like receptor (OLR1), is the most recently identified opioid receptor. The gene that encodes OLR1, designated OPRL1, is located on human chromosome 20 and has nearly 70% sequence homology to other opioid receptor genes (Przewlocki

2004, Waldhoer, Bartlett et al. 2004, Levran, Yuferov et al. 2012). While being a weak target for classical opioids, ORL1 selectively binds the newly identified neuropeptide orphanin FQ/nociception (OFQ/N), an endogenous 17-amino acid peptide that is similar to dynorphin A. Activation of ORL1 by OFQ/N blocks morphine induced dopamine release, resulting in a decrease in opioid reward signaling (Chevlen 2003, Waldhoer, Bartlett et al. 2004, Ammon-Treiber and Hollt

2005). As such, OPRL1 activity is suggested to mediate addiction responses by negatively regulating the mesolimbic dopaminergic system (Levran, Yuferov et al.

2012). ORL1 is localized to the cerebral cortex, thalamus, hypothalamus, periaqueductal gray, dorsal raphe and locus coeruleus nuclei, and the spinal cord dorsal horn as well as in peripheral sensory and sympathetic ganglia, (Xie,

Meuser et al. 1999). Despite the physiological and pharmacological significance of ORL1, little is known about the exact function and regulation of this receptor.

16 As such, further experiments are needed to characterize this new member of the opioid receptor family.

1.4 Hypothesis and Specific Aims

Despite the identification of multiple opioid receptors, as well as the classification of innumerable opioid compounds, a four opioid receptor model does not readily predict the clinical observations of opioid pharmacology. For example, gene knockouts targeting exon 1 of the OPRM1 gene are sufficient to abolish analgesia mediated by the µ-selective agonist morphine; however, they are not sufficient to abolish analgesia mediated by its metabolite M6G or by its diacetylated form, heroin (Kieffer 1999, Schuller, King et al. 1999). Multiple studies investigating opioid pharmacology have suggested the existence of additional opioid receptors and, as previously stated, additional receptors have been proposed; however, evidence in support of the existence of additional opioid receptor types is lacking given that no additional opioid-receptor genes have been identified. Instead, studies have shown that transcriptional and post- translational modifications of opioid receptors are involved in the diverse pharmacology observed with opioid agonists. Among these regulatory mechanisms, the most intriguing is constitutive and alternative splicing. As will be discussed in detail throughout this manuscript, constitutive and alternative splicing generates multiple alternatively spliced variants, or isoforms, of opioid receptors. This is particularly true for the MOR, which exhibits the most complex and extensive splicing patterns among classical opioid receptors (Pasternak and

Standifer 1995, Mayer, Schulzeck et al. 1996, Pan, Xu et al. 1998, Xie, Meuser et 17 al. 1999, Pan, Xu et al. 2001, Xin and Wang 2002, Chevlen 2003, Mizoguchi, Wu et al. 2003, Pan 2003, Pan, Xu et al. 2003, Kvam, Baar et al. 2004, Schnell and

Wessendorf 2004, Doyle, Sheng et al. 2007, Li, Lee et al. 2007, Schnell and

Wessendorf 2009, Barrie, Smith et al. 2012, Dever, Xu et al. 2012, Levran,

Yuferov et al. 2012, Pasternak and Pan 2013, Pasternak 2014, Xu, Xu et al.

2014).

Characterization of MOR isoforms is lacking; however, limited studies suggest that these receptors exhibit unique cellular and subcellular localization, ligand binding, cell signaling, desensitization, internalization, and recycling characteristics. As such, each MOR isoform must be regarded as a separate receptor subtype that collectively contributes to the overall cellular and physiological effects of opioids. Alterations in the MOR isoform profile may therefore alter the balance within this collective signaling, thereby altering opioid pharmacology. Although it is well-known that the physiological and cellular response to opioids is altered by numerous factors, most notably prolonged clinical use and abuse of opioids, through the modulation of opioid receptor expression and the establishment of opioid tolerance, mechanisms that regulate

MOR splicing specificity are poorly understood, as are any extracellular factors that alter MOR splicing specificity. Recently, it has been suggested that opioid use may also promote changes in MOR splicing patterns, in addition to regulating opioid tolerance and receptor expression, as individuals maintained on methadone exhibit altered expression of certain splice variants (Vousooghi,

Goodarzi et al. 2009). Whether this is a direct result of methadone treatment,

18 prior substance abuse, or represents a genetic predisposition for the development of opioid addiction is still unknown; however, limited studies have suggested that chronic morphine treatment can alter MOR splicing through a yet unknown mechanism (Verzillo, Madia et al. 2014, Xu, Faskowitz et al. 2015).

Therefore, this study set out to first establish whether opioid treatment, specifically acute and chronic morphine exposure, directly impacts the alternative splicing of the MOR and the mechanism through which this is mediated. Second, this study sought to determine the unique signaling cascades activated by those

MOR isoforms identified to be regulated by morphine in order to assess the cellular consequences of morphine-mediated changes in MOR alternative splicing patterns in opioid pharmacology.

While opioids are primarily recognized and studied for their analgesic properties their role in immunomodulation is becoming increasingly important.

This is particularly true for HIV infection, as opioid abuse not only serves as a risk factor for viral transmission through the sharing of contaminated syringes but also actively enhances HIV replication and infectivity through direct and indirect mechanisms, thereby accelerating disease progression. Opioid-mediated exacerbation of HIV infection has since been offset by the development of anti- retroviral therapy that suppresses HIV viral replication systemically; however, current anti-retroviral therapy compounds have poor penetration into the CNS and, as a result, do not effectively treat the CNS HIV reservoir or the subsequent neurocognitive deficits, collectively known as HIV-associated neurocognitive dysfunction (HAND). Given that opioids primarily target the CNS, it is not

19 surprising that opioid abuse has also been found to exacerbate HAND through direct and indirect mechanisms (Gurwell, Nath et al. 2001, Nath, Hauser et al.

2002, Hauser, El-Hage et al. 2005, Berman, Carson et al. 2006, Hauser, El-Hage et al. 2006, Hauser, El-Hage et al. 2007, Hauser, Fitting et al. 2012). This is often broadly attributed to opioid signaling mediated by the MOR without distinguishing specific MOR isoform activity. Furthermore, HIV viral replication is, itself, dependent on host alternative splicing mechanisms and HIV viral proteins may, therefore, favorably alter the host splicing machinery. Whether this impacts the splicing specificity of the MOR is still unclear; however, limited studies suggest that HIV infection alters MOR splicing due to increased inflammatory signaling, although a direct mechanism has not been established (Dever, Xu et al. 2012,

Dever, Costin et al. 2014). As such, this study sought to determine whether HIV viral proteins, independently or concomitantly with opioids, directly alter MOR splicing specificity and the mechanism through which this is mediated in addition to determining whether the unique signaling cascades activated by MOR isoforms, identified to be regulated by morphine, intersect with HIV viral protein signaling to exacerbate HIV neuropathology.

20 CHAPTER 2 – MATERIALS AND METHODS

2.1 Cell Culture

The human neuroblastoma cell line SH-SY5Y was obtained from the

American Type Culture Collection (ATCC) and was maintained in Neurobasal media supplemented with B-27 supplement (Invitrogen), 2mM GlutaMAX

(Invitrogen), and 50µg/mL gentamicin (Invitrogen) in a humidified incubator at

o 37 C with 7% CO2. Cells were split and subcultured using 0.25% Trypsin-EDTA solution and subcultures were not maintained after 20 passages. The human embryonic kidney cell line HEK293 was also obtained from the ATCC and was maintained in Dulbecco's Modified Eagle's Medium (DMEM) and supplemented with 2% heat-inactivated fetal bovine serum (FBS) and 50µg/mL gentamicin in a

o humidified incubator at 37 C with 7% CO2. For experiments, SH-SY5Y cells were plated in uncoated 6-well plates at a confluence of 5x105 cells/well and incubated for 24 hours to allow for attachment before treatment. HEK293 cells were serum starved for 24 hours using DMEM supplemented with 0.2% FBS and 50µg/mL gentamicin prior to experiment. Cells were then plated on poly-d-lysine coated 6- well or 12-well plates at a confluence of 2x105 cells/well or 1x105 cells/well, respectively, and were incubated for 36 hours to allow for attachment before treatment.

2.2 Plasmid Constructs & Transfection

The pCMV6-MOR-1 and pCMV6-MOR-1X expression plasmids, which transcribe Myc/DDK-tagged, full-length MOR-1 and MOR-1X, respectively, were

21 purchased from OriGene. The CAT expression constructs pBLCAT3-pSF2 (-400 to +47) and pBLCAT3-pSF2 (-200 to +47) were generated previously by our lab

(Sariyer 2010). The pCGT7-SF2/ASF-FL expression plasmid, which transcribes

T7-tagged, full length ASF/SF2, was previously described (Cazalla, Zhu et al.

2002) and kindly provided by Dr. Javier F. Cáceres, Ph.D. (Medical Research

Council Human Genetics Unit, Western General Hospital, Edinburgh EH4 2XU,

Scotland, United Kingdom) for use previous studies (Cazalla, Zhu et al. 2002,

Sariyer 2010, Uleri, Beltrami et al. 2011, Uleri, Regan et al. 2013). HIV viral protein expressing plasmids pCDNA3-Vpr-WT and pCMV-Tat86 were obtained previously by our lab (Amini, Mameli et al. 2005, Saunders, Eldeen et al. 2005,

Mukerjee, Sawaya et al. 2007, Deshmane, Amini et al. 2011, Barrero, Datta et al.

2013). The pCGT7-empty vector plasmid was used as a control for transfection conditions. Plasmid stocks of all constructs were generated by transforming competent E. Coli DH5α cells and purifying plasmids constructs using the

MaxiPrep kit purchased from Qiagen. Purified plasmid constructs were

o resuspended in DNase/RNase-free dH2O and stored at -20 C.

For experiments, SH-SY5Y and HEK293 cells were transfected with 3µg plasmid DNA using Fugene 6 transfection reagent in a 1:3 and 1:2 ratio, respectively. Briefly, transfection samples were mixed in 100µL of OptiMEM and incubated for 45 minutes at room temperature. Culture media was then aspirated from plated cells and replaced with 100µL transfection sample and 900µL of additional OptiMEM. Following a 4 hour incubation, fresh culture media was

22 added directly to transfection samples and cells were incubated for 48 hours to allow for vector expression.

2.3 Morphine, Recombinant Tat Protein, and Stress Inducer Treatments

Purified, recombinant, full-length Tat protein was purchased from

ImmunoDiagnostics, resuspended in dH2O to create a 0.1mM stock solution, and aliquots were stored at -70oC. Purified morphine sulfate salt pentahydrate was purchased from Sigma-Aldrich, resuspended in dH2O to generate a 0.1mM stock solution, and stored at room temperature. Control conditions consisted of serum starvation using HBSS, serum starvation using HBSS with concomitant bafilomycin (Baf) treatment, and treatment with CdCl2. Stock solutions for Baf and CdCl2 were created by diluting each into dH2O to a concentration of 1.5µM and 600mM, respectively. Bafilomycin stock solution aliquots were stored at -

o o 20 C, while the CdCl2 stock solution was stored at 4 C. For final treatment concentrations, morphine (final concentration of 0.1µM, 1µM, or 10µM), rTat

(final concentration of 1nM, 50nM, or 100nM) and CdCl2 (final concentration of

1mM) stock solutions were diluted into culture media directly, whereas bafilomycin was diluted into Hank's Balanced Salt Solution (HBSS) to a final concentration of 5nM and added to cells following the removal of culture media.

Treatment courses were conducted in such a way that all experimental conditions were harvested at the same time point. For 24 hour morphine, rTat, and combination treatments, stock solutions were added simultaneously and, following 23 hours, morphine alone was added to the 1 hour time point condition

23 so that all samples were collected at the 24 hour time point. For chronic morphine treatments, the morphine stock solution was diluted directly into culture media every 2 hours for 24 hours. At the 20 hour time point, bafilomycin and

HBSS was added to create a 4 hour starvation condition. At 23 hours, the CdCl2 stock solution was added to create a 1 hour apoptotic condition. All treatments were harvested at 24 hours.

2.4 Extraction and Purification of Cytoplasmic RNA

Cytoplasmic RNA was extracted from treated cells using the RNEasy Mini

Kit (Qiagen) following the manufacturer’s protocol adjusted for purification of cytoplasmic RNA fractions only. Briefly, treated cells were trypsinized, transferred to RNase-free micro-centrifuge tubes, and centrifuged at 8,000rpm for 5 minutes.

Media was aspirated and the cell pellet was washed with 1mL ice-cold PBS.

Washed cells were centrifuged again then lysed in complete RLN buffer (50mM

Tris-HCl pH 8, 140mM NaCl, 1.5mM MgCl2, 0.5% NP-40, 1U/µL RNase Inhibitor

(Invitrogen), and 1mM DTT) for 5 minutes on ice. The cytoplasmic RNA- containing fraction was then separated from the nuclear and plasma membrane fractions by centrifugation at 8,000rpm for 5 minutes and the cytoplasmic RNA- containing supernatant was transferred to fresh, RNase-free micro-centrifuge tubes. Cytoplasmic RNA samples continued to be processed following the

Qiagen RNEasy protocol and purified cytoplasmic RNA was resuspended in

RNase-free dH2O.

DNA contamination was removed by treating cytoplasmic RNA samples with RNase-free recombinant DNase I (Roche) following an optimized protocol. 24 Briefly, cytoplasmic RNA samples were resuspended to a volume 50µL with

RNase-free dH2O. DNase treatment samples were prepared by adding 5.5µL 10x

DNase Buffer and 2µL recombinant DNase I and incubated at room temperature for 15 minutes. Samples were then treated with 25mM ETDA, incubated at 65oC for 10 minutes, and placed immediately on ice. Prior to conducting two-step RT-

PCR experiments, cytoplasmic RNA needed to be repurifed in order to remove

DNase enzymes and buffer salts. DNase treated samples were therefore increased to a volume of 200µL using RNase-free dH2O, subjected to purification via phenol/chloroform extraction, and precipitated using ethanol. Precipitated

DNase-treated, cytoplasmic RNA was then resuspended in RNase-free dH2O to a concentration of 300ng/µL and stored at -70oC.

2.5 Primers, Semi-Quantitative Two-Step RT-PCR, and Gel Electrophoresis

Semi-quantitative, two-step RT-PCR was conducted using High Fidelity

Platinum Taq and either Superscript III Reverse Transcriptase (RT) or MLV-V RT enzymes following optimized protocols. For two-step RT-PCR using the

Superscript III RT enzyme, initial RNA denaturation and priming samples (100ng sample RNA, 0.5µg/µL OligodT12-18 Primer, and 2x reaction mix) were added to thin walled, RNase-free PCR tube and incubated at 65oC for 5 minutes then placed immediately on ice. Samples were then transferred to fresh, thin walled,

RNase-free PCR tubes containing additional 2x reaction buffer and 1U/µL

Superscript III RT. Synthesis of complementary DNA (cDNA) was then initiated by incubating the samples at 50oC for 50 minutes, then 85oC for 5 minutes before

25 being placed on ice. cDNA samples were transferred to fresh, thin-walled,

RNase-free PCR tubes containing an equal volume of PCR master mix (1x High

Fidelity Buffer, 0.4mM dNTP mix, 2mM MgSO4, 1.5U/µL High Fidelity Platinum

Taq, RNase-free dH2O) and 0.2µM of both forward and reverse primers (Table

2.1). Samples were then placed in a PCR cycler, initially denatured at 94oC for 2 minutes, then run for 35 cycles of 30 seconds at 94oC, 30 seconds at an optimized annealing/extension temperature (Table 2.1), and 3 minutes at 68oC.

Following PCR cycling, a final extension was conducted at 68oC for 10 minutes then samples were cooled to 4oC.

For two-step RT-PCR using the MLV-V RT enzyme, initial cDNA synthesis samples were generated in thin walled, RNase-free PCR tube by mixing 2.25µg purified, cytoplasmic RNA, 0.5µg/µL OligodT12-18, and 0.7mM dNTP mix.

Samples were heated at 65oC for 5 minutes then placed immediately on ice, where 10x complete MLV-V RT reaction buffer (250mM Tris-HCl pH, 375mM

KCl, 15mM MgCl2, 1mM DTT, 3U/µL RNase Inhibitor) was added. Samples were incubated at 37oC for 2 minutes, then 10U/µL MLV-V was directly added and samples were incubated at 37oC for 50 minutes then at 70oC for 15 minutes. The cytoplasmic RNA template strands were then specifically degraded by adding

0.2U/µL of RNase H to each sample then incubating at 37oC for an additional 20 minutes. Phenol/chloroform purification and ethanol precipitation was used to purify cDNA, which was resuspended in DNase/RNase-free dH2O at a concentration of 200ng/µL and stored at 4oC until use in a PCR analysis. High

26 Fidelity Platinum Taq PCR samples were made by adding 1.6µg MLV-V RT- generated cDNAs into equal volumes of an alternative PCR master mix (1x High

Fidelity Buffer, 0.8mM dNTP mix, 2mM MgSO4, 2.25U/µL High Fidelity Platinum

Taq, RNase-free dH2O) with 0.2µM of both forward and reverse primers. Primers were ASF/SF2 forward 5’-ACCTTCCATCTAGATCGGGAGGTGGTGTGATTCGT

-3’ and reverse 5’-TTCCAGGATCCTTAGTCGCGACCATACACCGCGTCTT-3’ and GAPDH ReadyMade forward and reverse primers purchased from Integrated

DNA Technologies (IDT). Samples were placed in a PCR cycler and amplified under the same conditions as Superscript III RT-generated two-step RT-PCR samples using an optimized annealing/extension temperature of 65oC.

Gel electrophoresis was used to determine PCR amplification.

Electrophoresis-grade agarose powder was dissolved in 1x TAE buffer (40mM

Tris, 20mM acetic acid, 1mM EDTA) with 50ng/mL ethidium bromide to create a

2% agarose gel. Electrophoresis samples were prepared by adding 25µL of PCR samples to 5µl 6x DNA loading buffer (30% glycerol, 0.25% bromophenol blue in

1x TAE buffer). Samples were loaded and run at 75V for 1 hour and visualized using the Kodiak Gel Logic Imaging System. Semi-quantitative analysis was performed using the ImageJ imaging software (Schneider, Rasband et al. 2012).

27 Table 2.1: MOR-1 isoform specific primers and annealing temperatures

Transcript Primer Sequence PCR Annealing/Extension Temperature

Forward TGC TCA GCT CGG TCC CCT CC

MOR-1 Reverse GCA GAG CAG AGT GGC CAG AGA G 65oC

Forward GGT GCT GGT GGT GGT GGC TG

MOR-1A Reverse AGT GGG CAA GGC ACT CAC CCT 68oC

Forward CCC CCA CGA ACG CCA GCA AT

MOR-1B2 Reverse GCC GTG GAG GGG TGG TCT CT 65oC

Forward TGC TCA GCT CGG TCC CCT CC

MOR-1B4 Reverse AGG CTG TCT CTC CCG CCC AG 68oC

Forward TGC TCA GCT CGG TCC CCT CC

MOR-1B5 Reverse ATT GCT GCC GTT CGT GGG GG 68oC

Forward CTC GGC GGG AGA GAC AGC CT

MOR-1I Reverse CAG CCA CCA CCA CCA GCA CC 65oC

Forward GGT GCT GGT GGT GGT GGC TG

OPRM1 Exon 6 Reverse GCCGTG GAG GGG TGG TCT CT 60oC

Forward GCC TGG CTT CAG GTG TGG GG

MOR-1K Reverse GCG GAC ACT CTT GAG GCG CA 65oC

Forward CGA CCT GGG CGG GAG AGA CA

MOR-1V Reverse ATT GGC CGT GGA GGG GTG GT 60oC

Forward AGA GAC CAC CCC TCC ACG GC

MOR-1W Reverse AGT GGG CAA GGC ACT CAC CCT 60oC

Forward TGC GCC TCA AGA GTG TCC GC

MOR-1X Reverse CTC CAC CAG ACG GGC TGG GA 65oC

2.6 Extraction and Purification of Whole Cell Proteins

Whole cell protein lysates were extracted following an optimized protocol from Abcam. Briefly, treatment media was aspirated from culture wells and plated cells were washed once with ice-cold PBS. Cells were then lysed directly in culture wells using ice-cold RIPA lysis buffer (150mM NaCl, 50mM Tris-HCL pH

8, 1% NP-40, 0.5% Na Deoxycholate, 0.1% SDS) supplemented with respective serine/threonine and tyrosine phosphatase inhibitors NaF (10mM) and Na3VO4

(1mM) as well as a 1x mammalian protease inhibitor cocktail purchased from

Sigma-Aldrich. Cells were rocked in complete RIPA lysis buffer for 5 minutes at

4oC before being scraped from the well, transferred to micro-centrifuge tubes, 28 and rotated at 4oC for an additional 30 minutes. Protein lysates were centrifuged at 13,000rpm for 5 minutes and supernatant was transferred to fresh micro- centrifuge tubes. Protein concentrations were determined using the Bio-Rad

Bradford Reagent and a 96-well plate reader. Purified protein lysates were stored at -20oC.

2.7 Discontinuous Electrophoresis and Li-Cor Western Blotting

Equal concentrations of protein lysates were mixed with 6x Laemmli Buffer

(12% SDS, 30% β-mercaptoethanol, 60% glycerol, 375mM Tris HCl pH 6.8) and

RIPA lysis buffer to bring all samples to a total volume of 50µL. Bromophenol blue was not added to the loading buffer as it interferes with fluorescent analysis using the Li-Cor imaging system. Sample were then denatured at 100oC for 5 minutes, vortexed, centrifuged at 13,000rpm, and loaded into wells of a 12%

SDS-polyacrylamide gel for separation by SDS-PAGE. Discontinuous electrophoresis was performed at 200V for 1 hour using a Tris-Glycine-SDS

(TGS) buffer (25mM Tris-Base, 250M Glycine, 3.5mM SDS). Proteins were transferred onto methanol-activated, Li-Cor-specific PVDF membranes using a wet transfer system containing Tris-Glycine transfer buffer (26.5mM Tris-Base,

192mM Glycine, 1% methanol) and run at 250mA for 3 hours. Membranes were dried at room temperature and stored protected from light.

Quantitative analysis using the Li-Cor Odyssey CLx Infrared Imaging

System was performed following an optimized protocol. Briefly, dried PVDF membranes were reactivated in methanol and washed in PBS. Membranes were

29 then blocked for 1 hour, with shaking, in a 5% milk:PBS solution. Primary monoclonal and polyclonal antibodies against ASF/SF2, T7, β-tubulin, Beclin-1,

LC3, and Bax were diluted 1:1000 in a 5% milk:PBS solution as well. For fluorescence analysis of proteins, primary antibodies were added to membranes and probed, with shaking, for either 1-2 hours at room temperature or overnight at 4oC. The primary antibody solutions were then removed and membranes were extensively washed with PBS containing 0.1% Tween-20 three separate times consecutively for 5 minutes each, removing wash buffer between washes, with a final wash of PBS without Tween-20 for 5 minutes. Secondary antibody dilutions of 1:5,000 were prepared in a 5% milk:PBS solution by adding Li-Cor-specific

IRDye 800CW goat anti-mouse IgG and/or IRDye 680CW goat anti-rabbit IgG.

Membranes were probed with secondary antibodies for 1 hour at room temperature, protected from light, then extensively washed with PBS containing

0.1% Tween-20 as before, followed by a final wash of PBS to remove residual

Tween-20. Membranes were then scanned and analyzed using the Li-Cor

Odyssey CLx Infrared Imager (LI-COR; Millennium Science, Surrey Hills,

Australia).

2.8 MAPK Array Analysis

Total cell lysates were prepared from HEK293 cells transfected with plasmids expressing either MOR-1 or MOR-1X, which were left untreated or treated with morphine, using Human Phospho-MAPK Array Kit (R&D Systems,

Minneapolis, MN) lysis buffer following the manufacturer’s protocol. Protein concentrations were determined using the Bio-Rad Bradford Reagent and a 96- 30 well plate reader. Manufacturer-supplied membranes were blocked with Array buffer 5 for 1 hour at room temperature. Array buffer 5 was then aspirated and membranes were rocked overnight at 4oC in a mixture of the manufacturer- supplied antibody mix and 200µg fresh protein lysates adjusted to a final volume of 1.5 mL with Array Buffer 1. The membranes were then processed using a manufacturer-supplied chemo-luminescent solution according to the manufacturer’s protocol. Probed dot blots were exposed on radiographic film, which were developed and scanned for semi-quantitative analysis using ImageJ software.

2.9 CAT Reporter Gene Analysis

Activity of the ASF/SF2 encoding gene, SFRS1, was determined using a

CAT reporter gene assay following an optimized protocol. Briefly, treated pBLCAT3-pSF2 (-400 to +47) or pBLCAT3-pSF2 (-200 to +47) expressing SH-

SY5Y cells were washed twice with PBS then incubated in TEN Buffer (40mM

Tris HCl pH 7.5, 1mM EDTA pH 8, 150mM NaCl) for 5 minutes at room temperature with shaking. Cells were removed by scraping, transferred to micro- centrifuge tubes, and centrifuged at 13,000rpm and 4oC for 1 minute. TEN buffer supernatant was aspirated from samples and pelleted cells were resuspended in ice-cold 0.25M Tris HCL pH 7.5. Lysis of resuspended cells was performed using three freeze/thaw cycles and lysates were allowed to cool for 10 minutes on ice.

Samples were centrifuged at 13,000rpm and 4oC for 5 minutes and the protein- containing supernatants were transferred to fresh micro-centrifuge tubes. CAT reporter gene assay samples were prepared using 30µg protein and incubated at 31 37oC for 1 hour. Samples were then mixed with ethyl acetate, lyophilized, resuspended in a low volume of ethyl acetate, and placed drop-wise onto chromatography paper. Liquid chromatography was then performed using a 19:1 chloroform/methanol running buffer. Exposures of chromatography paper were conducted at -70oC for 12 hours protected from light. Liquid scintillation counting was used to quantitate CAT reporter gene expression.

2.10 MTT and Viability Assays

Mitochondrial dehydrogenase activity was determined using a 3-(4,5- dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) colorimetric assay following an optimized protocol. Briefly, MTT solution (5mg/mL MTT in PBS) was added directly to the culture media of treated HEK293 cells plated in 12-well culture plates. Cells were incubated at 37oC for 1 hour before the MTT-containing culture media was aspirated. The resulting formazan within MTT-treated cells was solubilized by the addition of an MTT solvent (4mM HCl, 0.1% NP-40 in 2- propanol). Solubilized formazan samples were then transferred to a 96-well plate and absorbance was measured at 590nm, using absorbance at 620nm as a reference. Early and late apoptosis was determined by Annexin/7-AAD staining and cell sorting using a Guava flow cytometer and Guava Nexin Kit following the manufacture’s protocol and associated software (Millipore).

32 CHAPTER 3 – TRANSCRIPTIONAL AND POST-TRANSCRIPTIONAL

REGULATION OF OPIOID RECEPTOR ISOFORMS

3.1 Transcriptional and Post-Transcriptional Regulation of Opioid

Receptors

The existence of multiple opioid receptor subtypes and their unique patterns of expression in various tissues and species suggest that multiple regulatory mechanisms exist in order to maintain proper localization and density of receptor expression. For example, opioid receptors are temporally regulated during differentiation of embryonic cells. In undifferentiated embryonic cells,

OPRM1 is transcriptionally silent, while OPRD1 and OPRK1 are constitutively active. During the early phase of differentiation, the activity of OPRD1 and

OPRK1 is diminished, while OPRM1 remains silent. Conversely, by the late stages of differentiation, all three opioid genes are transcriptionally active (Wei and Loh 2002, Chevlen 2003). Additionally, cellular expression and subcellular localization of KORs and MORs, but not DORs, fluctuates during the maturation of human oocytes (Agirregoitia, Peralta et al. 2012). Multiple theories have been suggested to explain spatial and temporal regulation of opioid receptor expression as well as for pharmacological data that suggests the existence of additional opioid receptor subtypes. These include polymorphisms of the opioid receptor genes, epigenetic regulation of transcription, and post-transcriptional regulatory mechanisms, such as alternative splicing, microRNA, and differential polyadenylation of the mRNA transcript.

33 3.1.1 Epigenetic regulation

Within diploid cells, the human genome consists of a nearly 6 billion base pair nucleotide sequence. Considering that the average base pair is approximately 0.34 nanometers long, an individual diploid cell contains a staggering length of DNA, nearly 2 meters. Therefore, it is necessary for cells to have mechanisms for compacting the genome into a more manageable size. The packaging of chromosomal DNA is facilitated by a family of proteins known as histones. These small, positively charged proteins bind to negatively charged

DNA nucleotide sequences, forming a DNA-protein complex known as a chromatin, which is further packaged into the recognizable 46 chromosomes of human diploid cells. The histone family consists of 5 protein members. Formation of the basic, repeating chromatin unit, a nucleosome, involves binding of histone proteins H2A, H2B, H3, and H4 (two of each) to a short nucleotide sequence to form an octomer, followed by the addition of histone protein H1 to fully compact the DNA sequence (Annunziato 2008). While packaging of DNA into nucleosome structures is beneficial for the conservation of space within the cell, it poses a challenge for functional processes, such as transcription, that require the separation of DNA strands and the binding of proteins and enzyme complexes to target nucleotide sequences. As such, reversible cellular mechanisms are in place to regulate chromatin accessibility. These mechanisms can be broadly categorized into one of two categories; the enzymatic modification of the histone

N-terminal by acetylation, methylation, ubiquitination, sumoylation, and/or

34 phosphorylation, or the displacement of histones by chromatin remodeling complexes (Annunziato 2008, Yang, Lay et al. 2010).

Epigenetic regulation refers to modifications in gene transcription unrelated to variations in the DNA sequence. While histone modulation of chromatin accessibility represents one form of epigenetic regulation, the primary mechanism of epigenetic regulation for several eukaryotic genes involves methylation of a DNA cytosine located on the 5’ side of a DNA guanosine, collectively referred to as CpGs. CpG dinucleotide sequences are constitutively methylated with the exception of those found in what are referred to as CpG islands, DNA regions >500bp characterized by a GC content >55% with a CpG ratio >0.65. Interestingly, nearly 60% of mammalian gene promoters are located within CpG islands, suggesting that CpG methylation is a highly conserved mechanism for regulating promoter activity (Chevlen 2003, Meaney and

Ferguson-Smith 2010, Yang, Lay et al. 2010). In mammalian cells, CpG methylation is mediated by DNA methyltransferases (DNMTs) and represses gene expression either by inhibiting the binding of transcription factors to promoter regions or by recruiting specialized proteins, known as methyl-CpG- binding proteins (MBPs), that directly repress transcription, sterically inhibit transcription factor binding, modify the DNA structure, and/or recruit co-repressor complexes (Hwang, Song et al. 2007, Yang, Lay et al. 2010). Recruited MBPs may also include histone deacetylases (HDACs), which, as the name implies, remove acetyl groups from the histone N-terminal. Histone deactlyation results in a tighter binding of histones to DNA, compacting the chromatin and reducing

35 accessibility. This establishes a multi-tier system of transcriptional repression, in which histones mediate accessibility of DNA nucleotides to DNA binding factors, such as DNMTs, which methylate CpG island regions, promoting the recruitment of MBPs, including HDACs, which feed back to deactylate histones and promote further repression. Therefore, it is no surprise that several transcriptional cofactors that promote DNA activity are able to modulate histone activity by post- translational modifications. Collectively, epigenetic regulation, at its core, involves a complex relationship between DNA nucleotides, packaging proteins such as histones, DNA binding proteins, and transcription factors and cofactors (Meaney and Ferguson-Smith 2010).

Epigenetic mechanisms have been found to regulate the expression of most opioid receptor genes. Histones within the chromatin region associated with

OPRM1 are mostly deacetylated. As such, two classes of HDACs, HDAC1 and

HDAC2, were shown to be recruited to the OPRM1 promoter region. Likewise,

HDAC inhibitors were shown to increase OPRM1 promoter activity, particularly at the proximal promoter region (Lin, Flock et al. 2008, Park, He et al. 2008).

Similarly, OPRK1 is known to be tightly bound within a chromatin structure while

HDAC binding and histone modifications where shown to regulate activity of both promoter regions (Park, He et al. 2008, Flaisher-Grinberg, Persaud et al. 2012).

Histone deacetylation has also been implicated in the regulation of OPRD1 activity (Park, He et al. 2008, Wei 2008). In addition to histone modifications,

DNA methylation of specific CpG sites is heavily implicated in opioid gene regulation, particularly of OPRM1. CpG methylation within the proximal promoter

36 region of OPRM1 facilitates methyl CpG binding protein 2 (MeCP2) binding, which subsequently recruits HDACs and additional repressor proteins, including the chromatin-remodeling factor Brg1 and DNA (cytosine-5-)-methyltransferase 1

(Dnmt1), to drive histone modifications and chromatin condensation (Hwang,

Song et al. 2007, Wei 2008, Hwang, Song et al. 2009, Hwang, Kim et al. 2010,

Pasternak and Pan 2013). Collectively, these findings demonstrate the extent to which opioid receptors are epigenetically regulated. Furthermore, epigenetic regulation is particularly important in the temporal and spatial regulation of opioid receptor expression during differentiation of neuronal and non-neuronal cell types

(Andria and Simon 1999, Wei 2008).

Considering the significant role epigenetic regulation has in opioid receptor expression, hereditary and environmental factors that impact epigenetic mechanisms are of particular importance. Ethnic differences in CpG methylation of OPRM1 have been shown, with increased methylation seen in African

Americans compared to Hispanics or Caucasians, suggesting some level of heritability. This is not unexpected, as ethnic differences in overall DNA methylation have been reported and may be an indirect result of ethnic differences in the frequency of variants in regulatory proteins, for example methyltransferases (Nielsen, Hamon et al. 2010). What is of particular interest, however, is the effect of opioids on epigenetic mechanisms. Increased methylation of CpG sites in OPRM1 promoter regions is seen in heroin addicts as well as former heroin addicts stabilized on methadone as a therapeutic. Reduced gene expression is observed in this population, possibly as a result of reduced

37 binding affinity for transcription factors, specifically SP1. Exactly how opioid treatment leads to epigenetic modifications is still the subject of investigation, as increased methylation states might be the indirect result of genetic inheritance or prior environmental factors that serve as risk factors for future heroin addiction, or a direct result of chronic heroin abuse or long-term methadone maintenance.

Therefore, longitudinal studies following heroin addicts before and throughout treatment would be beneficial (Wei 2008, Nielsen, Yuferov et al. 2009, Nielsen,

Hamon et al. 2010, Nestler 2014).

3.1.2 Alternative splicing

The human genome consists of roughly 25,000 protein encoding genes; however, there is a large discrepancy between the number of protein encoding genes and the repertoire of mRNA transcripts and encoded proteins they produce, with gene products far more numerous than estimates would predict. It is now understood that this discrepancy is due to the generation of multiple RNA isoforms from a single gene by several mechanisms, including alternative transcription initiation and polyadenylation site usage. The primary mechanism for the generation of multiple mRNA transcripts from a single gene is alternative splicing and, in addition to 5′ capping and 3′ polyadenylation, constitutes an important step of pre-mRNA processing. General splicing, often referred to as constitutive splicing, is a complex process through which specific portions of the precursor mRNA (pre-mRNA) sequence, referred to as introns, are removed and the remaining nucleotide sequences, referred to as exons, are ligated to form a mature mRNA transcript. Alternative splicing involves the differential inclusion 38 and exclusion of exons, and sometimes introns, into the pre-mRNA sequence, resulting in multiple, mature mRNA variants (Kim, Goren et al. 2008, Hui 2009,

Markovic and Challiss 2009, Keren, Lev-Maor et al. 2010, Barrie, Smith et al.

2012). It was originally estimated that at least 75% of human genes are subject to alternative splicing, but more recent estimates suggest that 90-95% of human genes are regulated in this manner (Pan, Shai et al. 2008, Biamonti and Caceres

2009). Furthermore, nearly 90% of alternatively spliced genes include a minor mRNA isoform with an abundance greater than 15% of the total gene expression

(Wang, Sandberg et al. 2008, Barrie, Smith et al. 2012). As such, alternative splicing is not a trivial phenomenon but represents a major regulatory mechanism for the generation of multiple mRNA transcripts and is the basis for the discrepancy between the nearly 25,000 protein encoding genes and the four-fold greater abundance of synthesized proteins (Keren, Lev-Maor et al. 2010).

Alternative splicing of pre-mRNA can occur through multiple, mutually exclusive processes. The most common processes, exon skipping and mutually exclusive exon selection, account for nearly 40% of alternative splicing events in higher eukaryotes. Exon skipping, as the name implies, involves the selective exclusion of a cassette exon along with its flanking introns in the mature mRNA transcript. Mutually exclusive exon selection involves the inclusion of an alternative exon into the mRNA transcript or the replacement of a constitutive exon with an alternative exon through a process similar to exon skipping.

Alternative splicing may also occur due to differential selection of alternative 3′ and/or 5’ splice sites due to the presence of multiple splicing sequences within an

39 exon. This process accounts for roughly 25% of alternative splicing events and results in the partial exclusion of a cassette exon or a partial inclusion of its flanking intronic region into the mRNA transcript. Intron retention, in which an intronic region between two constitutive exons is incorporated into the mRNA transcript, is also possible, although rare, accounting for less than 5% of alternative splicing events. Interestingly, intron retention is a favored mechanism of alternative splicing in plants, fungi and protozoa, suggesting an evolutionary shift in the splicing process and regulation. Finally, production of alternative mRNA transcripts may also occur through infrequent processes such as alternative promoter usage and alternative polyadenylation (Kim, Goren et al.

2008, Keren, Lev-Maor et al. 2010). Collectively, these processes result in, on average, the excision of more than 90% of the pre-mRNA sequence as introns and the synthesis of two to three isoforms for a given gene (Stamm, Ben-Ari et al. 2005).

Despite the identification and characterization of four opioid receptor classes, incomplete cross tolerance to selective receptor ligands as well as the wide variation in physiological responses to different opioids suggests that additional opioid receptor subtypes are present (Pasternak and Standifer 1995,

Zaki, Bilsky et al. 1996, Pan, Xu et al. 2003). Generation of these subtypes was proposed to occur via modifications of known opioid receptors as no additional opioid receptor-transcribing genes have been identified. Epigenetic mechanisms, as previously described, represent a major factor in regulating opioid gene expression; however, differential levels of gene activity does not account for the

40 agonist-selective differences in opioid receptor activity. Therefore, mechanisms of transcriptional regulation generating additional opioid receptor subtypes have been proposed to reconcile pharmacological inconsistencies within the single receptor subtype model. This hypothesis was later confirmed by various studies identifying multiple mechanisms of opioid receptor post-transcriptional regulation.

Of these regulatory mechanisms, alternative splicing of opioid receptor mRNA is particularly interesting given that it results in the synthesis of multiple, structurally different proteins from an individual gene (Gaveriaux-Ruff, Peluso et al. 1997,

Pan, Xu et al. 1999, Pasternak 2001, Pasternak 2014).

All four opioid receptors undergo alternative splicing in varying degrees.

Splicing of the KOR is limited to two isoforms, generated by the existence of two promoters that differentially regulate the excision of the intronic region (Yakovlev,

Krueger et al. 1995, Gaveriaux-Ruff, Peluso et al. 1997, Wei, Law et al. 2004).

Additionally, a third, truncated isoform has been described for the murine KOR

(Alicea, Belkowski et al. 1998, Wei, Law et al. 2004). Similarly, intron inclusion between the first and second exons of the mouse OPRD1 generates two isoforms of the DOR; however, whether this splicing pattern is conserved in humans is unknown (Gaveriaux-Ruff, Peluso et al. 1997). Alternative splicing of

ORL is slightly more complex, as five exons have been identified within the

OPRL1 gene. As such, five known ORL1 isoforms are alternatively spliced by mutually exclusive exon selection, alternative 3′ and/or 5’ splice site selection, and intron inclusion processes (Pan, Xu et al. 1998, Xie, Meuser et al. 1999).

The MOR exhibits the most extensive and complex alternative splicing patterns,

41 further complicated by incomplete homology between species (Pasternak and

Standifer 1995, Levran, Yuferov et al. 2012, Pasternak 2014). The constitutively spliced MOR-1 consists of exons 1, 2, 3, and 4. Synthesis of MOR isoforms primarily incorporates mutually exclusive exon selection, as seen in MOR-1O and

MOR-1X, which replace exon 4 with exon O and exon X, respectively (Pan, Xu et al. 2003). Alternative 3’ and 5’ splice site selection also accounts for many of the

MOR isoforms synthesized. This may occur in isolation, as seen in exon 1 of the

MOR-1I isoform, or in conjunction with other splicing processes. The isoforms

MOR-B1, MOR-1B2, MOR-1B3, MOR-1B4, and MOR-1B5 are synthesized from the replacement of exon 4 with exon 5 and are differentiated from each other by differential 3’ splice site selection within exon 5 (Pan, Xu et al. 2003). Likewise,

MOR-1Y and MOR-1Y2 incorporate a new exon, exon Y, in place of exon 4 as well as incorporating different terminal exons. Exon exclusion and intron retention also account for different MOR isoforms, such as MOR-1A, in which exon 4 is excluded and the intron region following exon 3 is partially retained. Complex combinations of these four alternative splicing processes synthesize additional isoforms, including MOR-1K, MOR-1S, and MOR-1Z (Kvam, Baar et al. 2004).

Utilization of a secondary promoter region, located upstream of a recently identified exon 11, facilitates exon 11 incorporation into the mRNA transcript and, in combination with additional splicing processes, results in the synthesis of additional MOR isoforms, including MOR-1G1, MOR-1G2, and MOR-1H (Pan,

Xu et al. 2001). Overall, the MOR exhibits the most complex splicing of any opioid gene, with over 20 isoforms characterized in humans and additional

42 isoforms predicted based on homology with the nearly 20 rat isoforms and 30 mouse isoforms known (Mayer, Schulzeck et al. 1996, Xin and Wang 2002,

Mizoguchi, Wu et al. 2003, Pan 2003, Schnell and Wessendorf 2004, Doyle,

Sheng et al. 2007, Schnell and Wessendorf 2009, Pasternak and Pan 2013,

Pasternak 2014, Xu, Xu et al. 2014). Furthermore, MOR isoforms are not merely incidental phenomena but likely play a key role in the enormous variability of physiological responses to various opioids, especially considering distinctive localization of these isoforms, particularly within different CNS regions (Pan, Xu et al. 1998, Xie, Meuser et al. 1999, Chevlen 2003, Pan 2003, Schnell and

Wessendorf 2004, Li, Lee et al. 2007, Barrie, Smith et al. 2012, Dever, Xu et al.

2012, Pasternak 2014, Xu, Lu et al. 2014).

43 Exon 11 1 SV 13 2 3 X Y 5 4 O a/b c/b/a A/B a/b e/d/c/b/a d/c/b/a

OPRM1 Gene

MOR-1

MOR-1A

MOR-1B1

MOR-1B2

MOR-1B3

MOR-1B4

MOR-1B5

MOR-1O

MOR-1X

MOR-1Y

‡ MOR-1Y3

MOR-1Y2

‡ MOR-1H

MOR-1I

MOR-1G1

MOR-1G2

MOR-3 (Mu3)

MOR-1K

‡ MOR-1JL

MOR-1W

MOR-1S

MOR-1Z

SV1

SV2

Figure 3.1: Schematic representation of human OPRM1 alternative splicing.

The human OPRM1 gene is composed of numerous exonic and intronic regions that are selectively utilized through alternative splicing mechanisms in order to generate various MOR isoforms. Unfortunately, exon names and definition sequences are not well conserved within the literature, leading to disparities between isoform compositions. Furthermore, additional MOR isoforms have been predicted, but have not yet been verified in vitro or in vivo. As such, splicing patterns of select MOR isoforms are illustrated here according to a comparative

44 analysis of exon and intron inclusions across multiple literature sources. Top schematic represents positions of known exonic regions within the human

OPRM1 gene, with arrows indicating transcription initiation sites. Accepted names for exonic regions are annotated above each region, with sub-annotations indicating variable exon cassettes due to multiple 3’ and 5’ splice sites. Splicing patterns of known opioid receptor isoforms are schematized and aligned below

OPRM1 gene, with accepted isoform names displayed to the left, incorporated exon cassettes represented by solid boxes, and excised regions represented by a thin, dotted line (Reference Sequences: NM_000914.4, NM_001008504.3,

NM_001145282.2, NM_001145283.2, NM_001145284.3, NM_001145285.2,

NM_001145286.2, NM_001008503.2, NM_001008505.2, NR_104351.1,

NR_104349.1, AY364230.1, DQ680044.1, NM_001145279.3, NM_001145280.3,

NM_001145281.2, NM_001285528.1, NM_001145287.2, GQ258059.1,

NM_001285527.1, NM_001285522.1, NR_104350.1; ‡ = predicted isoform)

(Choi, Kim et al. 2006, Cadet, Mantione et al. 2007, Fricchione, Zhu et al. 2008,

Xu, Xu et al. 2009, Andersen, Baar et al. 2013, Pasternak and Pan 2013, Xu, Xu et al. 2013)

3.1.3 Single nucleotide polymorphisms

Complicating the understanding of opioid gene architecture and function is the identification of multiple single nucleotide polymorphisms (SNPs), which consist of a single point mutation resulting in the substitution of alternative nucleotide pairings within the same chromosomal position of different individuals.

These alternative nucleotide pairings, known as alleles, are found throughout the 45 gene sequence, including within the promoter, coding, and intron regions. An extensive search for polymorphisms has identified nine SNPs occurring within

OPRD1, almost 30 SNPs occurring in OPRK1, and over 100 occurring within

OPRM1 (Kosarac, Fox et al. 2009, Shabalina, Zaykin et al. 2009, Levran,

Yuferov et al. 2012, Pasternak and Pan 2013). Additionally, nearly 20 SNPs have been identified for the OLR1 gene (Levran, Yuferov et al. 2012). While most of these SNPs are rare, some show a relatively high allelic frequency among specific populations. For example, the 118G allele of the highly studied SNP

118A>G is highly prevalent in individuals of Asian ancestry (40–50%), moderately prevalent in individuals of European ancestry (15–30%), but has a low prevalence among African Americans (1–3%) and is not found at all in natively African heritage (Levran et al., 2012; Shabalina et al., 2009). Given the sheer number identified, it is not surprising that SNPs represent a major area of investigation in understanding opioid pharmacology.

Many of the hundreds of SNPs located within opioid receptor genes, specifically those within OPRM1, have been found to have functional consequences. These functional consequences include, but are not limited to, changes in opiate metabolism, efficacy, potency, mRNA levels, transcription efficiency, ligand binding, receptor internalization, and signal transduction as well as overall sensitivity to pain (Shi, Hui et al. 2002, Landau, Kern et al. 2008,

Kosarac, Fox et al. 2009, Shabalina, Zaykin et al. 2009, Levran, Yuferov et al.

2012). Furthermore, because of the diploid nature of most cells, functional consequences of SNPs may either be magnified or muted depending on

46 homozygous or heterozygous expression (Kosarac, Fox et al. 2009, Zhang,

Chang et al. 2010). The 118A>G SNP is one of the most functionally characterized OPRM1 SNPs, with the 118G allele being associated with a reduction in mRNA and receptor expression as well as MOR signaling but an increase in β-endorphin affinity, resulting in variations in pain sensitivity (Bond,

LaForge et al. 1998, Crowley, Oslin et al. 2003, Kreek and LaForge 2007,

Vallender, Priddy et al. 2008, Oertel, Kettner et al. 2009, Shabalina, Zaykin et al.

2009, Zhang, Chang et al. 2010, Levran, Yuferov et al. 2012). Additional OPRM1

SNPs, as well as SNPs within OPRD1 and OPRK1, are correlated with changes in the potential risk for opiate and/or alcohol abuse (Mayer and Hollt 2006,

Vallender, Priddy et al. 2008). Alternatively spliced products are subject to polymorphisms as well, with SNPs identified in multiple MOR isoforms (Smith,

Doyle et al. 2005, Vallender, Priddy et al. 2008, Shabalina, Zaykin et al. 2009,

Garriock, Tanowitz et al. 2010, Diatchenko, Robinson et al. 2011, Xu, Lu et al.

2014). While the functional significance of these SNPs are still subject to investigation, SNPs in the MOR-1K isoform are correlated with increased sensitivity to pain (Shabalina, Zaykin et al. 2009). Similarly, the 31G>A SNP, localized within intron 2 of the OPRM1 gene, is associated with heroin addiction among the Han-Chinese population and has been found to weaken binding of the splicing protein hnRNP H (discussed in section 4.2.1), thereby favoring exclusion of exon 2 in OPRM1 splicing and resulting in an altered expression of MOR isoforms (Shi, Hui et al. 2002, Xu, Lu et al. 2014). Therefore, genetic

47 polymorphisms, both individually and in combination with alternative splicing, represents a novel regulatory mechanism of opioid pharmacology.

3.1.4 MicroRNAs

MicroRNAs (miRNAs) are ~22-nucleotide non-coding RNAs that repress gene activity by directly down-regulating mRNA expression. This occurs through the direct binding of miRNAs to partially complementary sequences located in the

3’ and 5’ untranslated regions (UTRs) as well as open reading frames (ORFs) of the target mRNA (Guo, Ingolia et al. 2010, van Kouwenhove, Kedde et al. 2011,

Hwang, Wagley et al. 2012). Over 50% of human gene transcripts are thought to be targets of miRNAs, highlighting their importance in gene regulation. Synthesis of miRNAs is initiated by RNA polymerase II-dependent transcription of a miRNA gene locus, generating a long primary transcript known as the pri-miRNA. The pri-miRNA structure consists of an imperfectly paired stem loop, a terminal loop, and flanking sequences. In addition, pri-miRNA is subject to multiple post- transcriptional regulations, including 3’ adenylation and 5′ capping with a 7- methyl-guanosine sequence. While still in the nucleus, the double-stranded stem of the pri-miRNA is cleaved by the RNase III endonuclease Drosha, resulting in the formation of a ~70 nucleotide sequence referred to as the precursor miRNA

(pre-miRNA). This pre-miRNA is then exported out of the nucleus into the cytoplasm, where it is cleaved again, this time at the terminal loop, by another

RNase III endonuclease, Dicer. This generates a ~22 nucleotide miRNA duplex, which binds to members of the Argonaute (Ago) protein family. This facilitates rearrangements within the protein/RNA complex, resulting in the retention of the 48 mature, single-stranded miRNA into the RNA-induced silencing complex (RISC or miRISC), and the degradation of the second strand (Valencia-Sanchez, Liu et al. 2006, Roush and Slack 2008, Carthew and Sontheimer 2009, Zhang and

Zeng 2010, van Kouwenhove, Kedde et al. 2011). The mechanism through which miRNAs regulate gene expression is dependent on the degree of miRNA-mRNA complementarity, with perfect complementarity facilitating Ago-mediated mRNA degradation while mismatches promote sequestration of mRNA into P-bodies and repression of translation by the miRISC complex (Valencia-Sanchez, Liu et al. 2006, Carthew and Sontheimer 2009).

With roughly 1,500 identified within the human genome, miRNAs are now recognized as key regulators of multiple cellular pathways, including proliferation, differentiation, migration, invasion, and apoptosis, and, as such, regulation of miRNA expression is pivotal for the spatial and temporal regulation of these processes (Bueno and Malumbres 2011, van Kouwenhove, Kedde et al. 2011,

Im and Kenny 2012). Interestingly, MORs have been shown to both regulate and be regulated by miRNA expression while KORs or DORs exhibit no miRNA- mediated regulation. Pharmacological evidence suggests regulation of multiple miRNA families, including miR-190, miR-339 and let-7 miRNA, by µ-selective opioids is agonist selective, possibly due to differences in the signaling cascades stimulated by various µ-selective opioids. Overall, MOR activity increases target miRNA expression (He, Yang et al. 2010, Sanchez-Simon, Zhang et al. 2010,

Zheng, Chu et al. 2010, Hwang, Wagley et al. 2012, Sartor, St. Laurent III et al.

2012, Zheng, Law et al. 2012, Wu, Hwang et al. 2013, Barbierato, Zusso et al. 49 2015). Up-regulation of miRNAs by µ-selective agonists may serve as an autoregulatory mechanism for MOR expression and the development of opioid tolerance, as these and additional miRNA are either known or predicted to target

MOR mRNA. This miRNA-mediated down-regulation of MOR expression primarily occurs though miRNA binding at target sequences within the 3’-UTR of

MOR mRNA (Wu, Law et al. 2008, He, Yang et al. 2010, He and Wang 2012,

Hwang, Wagley et al. 2012, Sartor, St. Laurent III et al. 2012, Wood and Lipovich

2012, Zheng, Law et al. 2012, Wu, Hwang et al. 2013, Barbierato, Zusso et al.

2015). Furthermore, miRNAs may regulate epigenetic and alternative splicing mechanisms both indirectly, by down-regulating epigenetic and alternative splicing machinery, and directly, by targeting the 3’-UTRs of spliced isoforms

(Allo, Buggiano et al. 2009, Barbierato, Zusso et al. 2015). This includes miRNA- mediated regulation of OPRM1 splicing, with both miR-103 and miR-107 being shown to target the 3’-UTR of the MOR-1A isoform and effectively suppressing its expression (Lu, Xu et al. 2014). These findings not only highlight a new mechanism through which miRNAs regulate MOR splicing and expression, but also represent a novel therapeutic approach to opioid receptor pharmacology

(Arvey, Larsson et al. 2010, Lu, Xu et al. 2014).

3.1.5 Polyadenylation

Nearly all mature mRNA transcripts within eukaryotic cells contain a long stretch of adenosines at the their 3’ end, referred to as a poly(A) tail. This sequence plays a key role in virtually all aspects of mRNA metabolism, including

50 stability, definition of terminal exons during splicing, translational efficiency, and transport. Generation of the poly(A) tail requires multiple sequence elements within the pre-mRNA to be present in order to promote cleavage at the 3’ end and recruitment of protein complexes to add the poly(A) sequence. One such element is the nearly universal polyadenylation signal sequence located 10–30 bases upstream of the cleavage/polyadenylation site. This hexanucleotide sequence, AAUAAA, is one of the most highly conserved sequence elements known, being found in 90% of all sequenced polyadenylation elements, with the remaining 10% showing a single AàU conversion within this sequence. The second sequence element required is a less conserved GU-rich motif, located

20-40 base pairs downstream from the cleavage/polyadenylation site, that typically contains five or more consecutive U residues interrupted by a single G residue and can loosely be defined by the consensus sequence YGUGUUYY, where Y is any pyrimidine. The distance between the polyadenylation signal sequence and the GU-rich motif defines the site of cleavage/polyadenylation, which has no identifiable consensus sequence, as well as determines the strength of a poly(A) tail (Colgan and Manley 1997, Blencowe, Bowman et al.

1999, Zhao, Hyman et al. 1999). Catalyzation of polyadenylation is a two-step process facilitated by a multiprotein complex consisting of four components; cleavage-polyadenylation specificity factor (CPSF), cleavage-stimulation factor

(CstF), cleavage factor (CF) I and II, and poly(A) polymerase. This complex first assembles on the conserved polyadenylation signal sequence where it

51 subsequently executes the cleavage and polyadenylation of the 3’ end

(Blencowe, Bowman et al. 1999).

Given the nearly universal expression of poly(A) tails in mature mRNAs and their broad function in mRNA metabolism, any modification to polyadenylation sequence elements can have dramatic effects on mRNA functions, and therefore gene expression. Alternative polyadenylation frequently occurs and results in multiple mRNA products from a single precursor RNA. This process often involves the differential inclusion or exclusion of 3’-terminal exons within multi- exon transcripts, such as those transcribing MOR-1 isoforms. As such, some splicing elements, such as the CT/CGRP intronic sequence element, have been shown to also facilitate cleavage and polyadenylation, linking the two processes

(Lou, Gagel et al. 1996, Lou, Helfman et al. 1999). While a functional polyadenylation signal has been identified in the 3’ UTR of MOR encoding mRNA, studies characterizing this region, particularly within different isoforms, are very limited. Therefore, it remains to be verified whether MOR isoforms contain functional poly(A) sequence elements and poly(A) tails in a physiological context (Wu, Hwang et al. 2005).

3.2 Regulation of OPRM1 Expression by Opioids and HIV

It is now well accepted that multiple transcriptional and post-transcriptional mechanisms exist in order to regulate opioid gene activity and receptor expression. Cellular and physiological processes tightly regulate these mechanisms in order to ensure appropriate temporal and spatial gene expression; however, this does not exclude the possibility that external factors 52 manipulate control mechanisms and alter gene expression. Multiple factors, including drugs of abuse (Miyagi, Chuang et al. 2000, Mahajan, Schwartz et al.

2002, Mahajan, Aalinkeel et al. 2005, Mahajan, Schwartz et al. 2005, Langsdorf and Chang 2011) and infection (Mahajan, Aalinkeel et al. 2005, Chang, Beltran et al. 2007, Liu, Li et al. 2009, Borjabad, Brooks et al. 2010), can regulate gene expression by altering transcriptional and post-transcriptional regulatory mechanisms. This is primarily achieved either by stimulation of signaling pathways (Gies, Peters et al. 1997, Wallington, Peters et al. 2002) that intersect with regulatory signaling mechanisms or by global changes in the cellular or physiological environment (Suzuki, Miyagi et al. 2000) that alter the overall function of regulatory machinery. This is particularly interesting for the opioid genes, which are highly diverse in expression and subject to extensive regulation, specifically by alternative splicing, given that they function to synthesize opioid receptors, which subsequently respond to both endogenous and exogenous opioids. Therefore, the possibility exists in which the transcriptional and post-transcriptional regulation of opioid receptor genes, in conjunction with opioid receptor activation and downstream signaling, is involved in a regulatory feedback mechanism. Additionally, external factors, such as HIV infection, may contribute to the development of a subcellular environment in which the transcriptional and post-transcriptional regulatory mechanisms of opioid receptor genes are altered.

53 3.2.1 Autoregulation of opioid receptor expression by opioids

Opioid gene expression is altered by various stimuli, including opioid treatment. Additionally, this opioid-mediated regulation of gene expression is distinct from the regulatory mechanisms of receptor expression involving internalization and down-regulation (described in section 5.3.2). As with most opioid receptor studies, the majority focuses specifically on MOR expression.

Multiple µ-selective agonists and antagonists have been shown to regulate MOR expression in an agonist-selective as well as a time- and dose-dependent manner (Zadina, Chang et al. 1993, Zadina, Harrison et al. 1994, Suzuki, Miyagi et al. 2000, Teodorov, Modena et al. 2006, Bayerer, Stamer et al. 2007). With respect to transcriptional regulation of OPRM1, opioids facilitate increased binding of transcription factors, including AP1, SP1, SP3, and CREB to OPRM1 promoter regions. This occurs via opioid-mediated activation of the cAMP-PKA pathway, which modifies transcription factor expression and binding activity.

However, whether this facilitates increased OPRM1 transcription is still under investigation, as PKC activation has also been shown to decrease MOR mRNA expression in addition to inconsistent evidence of opioid-mediated increases in

MOR mRNA expression (Castelli, Melis et al. 1997, Gies, Peters et al. 1997, Xu and Carr 2001, Wallington, Peters et al. 2002). Evidence supporting post- transcriptional regulation of MOR expression by opioids is limited but has been found to involve increases in MOR-specific miRNA (Wu, Zhang et al. 2009). In addition, methadone maintained individuals show changes in the expression of alternatively spliced MOR isoforms, with the MOR-1A isoform being up-regulated

54 while the MOR-1O isoform is down-regulated (Vousooghi, Goodarzi et al. 2009).

While this evidence is correlational, opioids have been found to directly regulate the splicing of the NMDAR (Anderson, Del Valle-Pinero et al. 2012) and, more recently, chronic morphine has been shown to alter the mRNA expression of specific MOR isoforms in several CNS regions of both mice and rats (Verzillo,

Madia et al. 2014, Xu, Faskowitz et al. 2015). This suggests that opioids can regulate alternative splicing mechanisms and, as such, be responsible for the splicing pattern changes seen in methadone maintained subjects. Overall, opioid- mediated transcriptional and post-transcriptional mechanisms regulating OPRM1 expression are poorly understood.

3.2.2 Regulation of opioid receptor expression by HIV

It is well established that injection drug abuse, such as that seen with the illicit abuse of exogenous opioids, increases the risk of exposure to blood-borne pathogens, particularly the human immunodeficiency virus (HIV). This is particularly interesting in the context of opioid receptor expression for two reasons. First, in addition to opioid-mediated transcriptional and post- transcriptional control of OPRM1 expression, multiple pro-inflammatory cytokines are known to impact gene expression (Suzuki, Miyagi et al. 2000, Kraus, Borner et al. 2001, Kraus, Borner et al. 2003, Kraus, Borner et al. 2006, Kraus 2009,

Bénard, Cavaillès et al. 2010, Mohan, Davis et al. 2010, Pasternak and Pan

2013). For example, TNFα is known to regulate OPRM1 expression via NF-κB

(Kraus, Borner et al. 2003, Bayerer, Stamer et al. 2007, Pasternak and Pan

2013). Lentiviruses such as HIV exert their pathogenic effects through a 55 specialized class of cytokines, called chemokines, and may therefore indirectly alter OPRM1 activity (Ances and Ellis 2007). In support of this hypothesis, the

HIV viral protein gp120 was shown to up-regulate MOR expression through autocrine/paracrine actions of TNFα while the HIV viral protein Tat alters the expression of MOR and KOR, but not DOR, through increased inflammatory cytokine activity (Cadet, Weeks et al. 2001, Beltran, Pallur et al. 2006, Fitting, Xu et al. 2010). Furthermore, co-administration of Tat attenuates morphine-mediated down-regulation of opioid receptor expression in microglia and instead induces a significant increase in both receptor mRNA and protein, although the mechanisms through which this occurs is not yet understood (Turchan-Cholewo,

Dimayuga et al. 2008). Second, certain pathogens directly regulate OPRM1 expression. This is seen with the bacterial endotoxin lipopolysaccharide (LPS), which up-regulates OPRM1 expression (Chang, Beltran et al. 2007). Additionally, the HIV viral protein Tat exhibits non-specific binding of various RNAs due to its highly basic nature, although direct binding to any opioid receptor RNA has not been identified (Jeang 1996, Li, Li et al. 2009). Therefore, the potential for HIV- mediated OPRM1 activity is two-fold, indirectly through host-mediated pro- inflammatory cytokines in response to infection, and directly by interactions with

HIV viral proteins. Unfortunately, both the role of HIV infection in regulating

OPRM1 activity and the mechanisms through which this may be mediated are poorly understood and, in most cases, contradictory. HIV infection has been found to both decrease and increase MOR expression depending on the cell-type investigated as well as the presence or absence of concomitant opioid abuse

56 (Beck, Mirmohammadsadegh et al. 2002, Chang, Beltran et al. 2007, Turchan-

Cholewo, Dimayuga et al. 2008). Despite this lack of consensus on HIV- mediated changes in MOR expression, it is clearly evident that HIV alters the splicing pattern of the MOR. Studies have found that HIV-1 slightly increases

MOR-1, MOR-1A, and MOR-1X expression in astrocytes but down-regulates

MOR-1A in neurons and microglia, although these findings were only significant for microglia (Dever, Xu et al. 2012). Astrocytes from HIV-infected individuals were also found to have elevated mRNA expression of MOR-1K (Dever, Costin et al. 2014). As such, HIV may directly regulate the differential expression of

MOR isoforms through as of yet unidentified, but possibly cell-type specific, mechanisms.

3.3 Results

3.3.1 Morphine increases MOR-1X mRNA expression in SH-SY5Y

Multiple factors, including methadone and chronic morphine treatment, are correlated with changes in the expression of specific MOR isoforms (Vousooghi,

Goodarzi et al. 2009, Verzillo, Madia et al. 2014, Xu, Faskowitz et al. 2015); however, a direct role for opioids in mediating cell type-specific splicing of the human OPRM1 gene has not been shown. As such, this study examined the splicing pattern of the MOR within various cell types both constitutively and following morphine treatment. Using semi-quantitative, two-step RT-PCR, the current study found that human fetal primary microglia, astrocytes, and neurons, as well as cell lines for both CNS cell-types, such as U87-MG, and non-CNS cell

57 types, such as HeLa, all exhibited little, if any, endogenous expression of MOR isoforms (data not shown). In contrast, SH-SY5Y cells, a model for human dopaminergic neurons, endogenously expressed several MOR isoforms, including the prototypical isoform MOR-1 (Figure 3.2, lane 1; Figure 3.4, lane 1); however, the MOR-1X variant was not detected (Figure 3.2, lane 1). The expression of MOR-1 mRNA was not significantly altered by treatment with

0.1µM morphine for either 1 hour (Figure 3.2, lane 2) or 24 hours (Figure 3.2, lane 3). Likewise, the expression of several other MOR variants was not significantly or consistently altered by treatment with 0.1µM morphine for either 1 hour (Figure 3.4, lane 2) or 24 hours (Figure 3.4, lane 3). However, mRNA expression of the MOR-1X variant was significantly increased following treatment with 0.1µM morphine for both 1 hour (Figure 3.2, lane 2) and 24 hours (Figure

3.2, lane 3).

30 30 *

25 25

20 20 *

15 15 MOR-1 MOR-1X

10 10

5 5 Normalized Band Intensity (Fold-Change) Band Normalized 0 0 1 2 3 4 5 6 1 7 2 8 3 9 4 5 6 7 8 9 MOR-1

MOR-1X

GAPDH - 0.1 0.1 Morphine (µM) - 1 24 Time (hours)

Figure 3.2: Increased expression of MOR-1X mRNA in SH-SY5Y following morphine treatment. MOR-1 and MOR-1X isoform expression from untreated

SH-SY5Y cells (lane 1), and cells treated with morphine for 1 hour (lane 2) or 24

58 hours (lane 3) was analyzed by two-step, semi-quantitative RT-PCR and gel electrophoresis. Semi-quantitative analysis was performed using Image J software to determine normalized band intensities and displayed in the graph as a fold-change difference (mean ± SEM; * = p ≤ 0.05).

3.3.2 HIV Tat attenuates morphine-mediated increases of MOR-1X mRNA

Given the observation that MOR isoform mRNA expression, particularly of

MOR-1X, is subject to regulation by exogenous factors, specifically morphine, this study next sought to determine if additional factors, such as HIV viral proteins, exhibit similar regulatory functions, both independently and concomitantly with morphine. The HIV viral protein Tat, one of the first viral proteins transcribed in early stage infection, is a likely candidate for HIV- mediated affects on MOR isoform expression as it is essential in driving late phase viral transcription and exhibits non-specific binding of various RNAs due to its highly basic nature (Jeang 1996, Li, Li et al. 2009). Examination using a two- step RT-PCR found that, while MOR-1X expression was not significantly altered by 24 hour treatments of either 50nM rTat (Figure 3.3, lane 4) or 100nM rTat

(Figure 3.3, lane 5), concomitant 24 hour treatment with either 0.1µM morphine and 50nM rTat (Figure 3.3, lane 6) or 0.1µM morphine and 100nM rTat (Figure

3.3, lane 7) attenuated the previously observed morphine-mediated increases in

MOR-1X mRNA expression in a dose-dependent manner. Additionally, while expression of MOR-1 mRNA was reduced with by 24 hour treatments of either

50nM rTat (Figure 3.3, lanes 4 and 6) or 100nM rTat (Figure 3.3, lane 5 and 7) in

59 a dose-dependent manner, mRNA expression of additional MOR isoforms in SH-

SY5Y cells was not consistently altered by rTat (Figure 3.4, lanes 4-7).

Furthermore, morphine- and Tat-mediated effects were independent of OPRM1 transcriptional activity, as expression of Exon 3a was not significantly altered

(Figure 3.3).

Exon 1 2 3 X 4 c/b/a a/b d/c/b/a

OPRM1

MOR-1

MOR-1X

Exon 3a

GAPDH

1 2 3 4 5 6 7 Forward Primer - 0.1 0.1 - - 0.1 0.1 Morphine (µM) Reverse Primer - - - 50 100 50 100 rTat (nM) - 1 24 24 24 24 24 Time (hours)

Figure 3.3: HIV viral protein Tat attenuates morphine-mediated increases in

MOR-1X mRNA. Left panel. A schematic representation of MOR Exon 3a, the constitutively spliced MOR-1 mRNA transcript, and the alternatively spliced

MOR-1X mRNA transcript indicating the position of forward and reverse primer positions (arrows). Right panel. MOR isoform expression from untreated SH-

SY5Y cells (lane 1), SH-SY5Y cells treated with 0.1µM morphine for 1 hour (lane

2) or 24 hours (lane 3), SH-SY5Y cells treated with 50nM rTat (lane 4) or 100nM rTat (lane 5) for 24 hours, and SH-SY5Y cells treated with a combination of

0.1µM morphine and either 50nm rTat (lane 6) or 100nm rTat (lane 7) for 24 hours was analyzed by two-step RT-PCR and gel electrophoresis.

60

MOR-1A

MOR-1B2

MOR-1B4

MOR-1B5

MOR-1I

MOR-1K

MOR-1V

MOR-1W

GAPDH

1 2 3 4 5 6 7 - 0.1 0.1 - - 0.1 0.1 Morphine (µM)

- - - 50 100 50 100 rTat (nM) - 1 24 24 24 24 24 Time (hours)

Figure 3.4: Endogenous SH-SY5Y expression of several MOR isoforms is not significantly affected by morphine or HIV Tat. MOR isoform expression from untreated SH-SY5Y cells (lane 1), SH-SY5Y cells treated with 0.1µM morphine for 1 hour (lane 2) or 24 hours (lane 3), SH-SY5Y cells treated with

50nM rTat (lane 4) or 100nM rTat (lane 5) for 24 hours, and SH-SY5Y cells treated with a combination of 0.1µM morphine and either 50nm rTat (lane 6) or

100nm rTat (lane 7) for 24 hours was analyzed by two-step RT-PCR and gel electrophoresis.

3.4 Discussion

The pharmacological profiles of opioids have suggested, for decades, the existence of multiple, ligand specific receptors. Accordingly, four opioid receptor subtypes have been identified, the KOR, the DOR, the MOR, and the ORL1.

These four receptors are highly homologous and are encoded by distinct genes, which are similarly homologous, suggesting their evolution from a common ancestral gene. Various endogenous and exogenous opioid compounds bind to

61 select opioid receptor subtypes with various affinities in order to exert numerous physiological effects. However, despite the identification of four opioid receptor subtypes, the binding profiles of opioid compounds do not correlate with the pharmacological profiles suggested by a four-receptor subtype model, raising the question as to how four opioid receptor-encoding genes generate a complex pharmacological profile that suggests additional receptor subtypes. As such, epigenetic and post-transcriptional mechanisms that generate multiple opioid receptors from individual opioid genes have been proposed. One such mechanism is the utilization of multiple promoters by opioid receptor genes in order to generate multiple pre-mRNA transcripts. For example, the OPRM1 gene utilizes one of three different promoters, a distal and proximal promoter located upstream of exon 1 and a third promoter located upstream of exon 11.

Transcription initiation from these promoters generates pre-mRNA transcripts of different lengths and containing various intronic and exonic regions. Additionally, these pre-mRNA transcripts are subject to constitutive and alternative splicing mechanisms, which selectively remove intronic and exonic regions to generate various isoforms. Therefore, the four known opioid receptor-encoding genes mediate complex pharmacological profiles of opioids through varying degrees of epigenetic and post-transcriptional regulation, most notably alternative promoter usage and alternative splicing, which generate multiple isoforms of classical opioid receptor subtypes.

While multiple factors, including opioids and HIV infection, are known to alter constitutive and alternative splicing in general, factors that specifically

62 regulate the cell-type-specific splicing patterns exhibited by opioid receptors, particularly the MOR, are poorly characterized. Previous studies have suggested that chronic use and abuse of opioids such as methadone and morphine may alter splicing patterns of the MOR (Vousooghi, Goodarzi et al. 2009, Verzillo,

Madia et al. 2014, Xu, Faskowitz et al. 2015). Additionally, while the effects of

HIV infection on overall MOR expression are well characterized, studies identifying a direct role for HIV in the regulation of OPRM1 splicing are limited

(Dever, Xu et al. 2012, Dever, Costin et al. 2014). As such, this study set out to establish whether acute opioid treatment, specifically with morphine, and HIV viral proteins, specifically Tat, directly impacts the alternative splicing of the human OPRM1 gene, resulting in a subsequent alteration in the MOR isoform profile. Cell-type specific expression of MOR isoforms was confirmed by RT-

PCR, as U87-MG, HeLa, and human fetal primary microglia, astrocytes, and neurons all exhibited little, if any, receptor expression, both endogenously and following morphine treatment (data not shown) whereas the SH-SY5Y cell line, a model for dopaminergic neurons, abundantly expressed various MOR isoforms endogenously (Figure 3.2, lane 1; Figure 3.4, lane 1). For the purpose of this study, SH-SY5Y cells were not differentiated as the phenotypic changes associated with differentiation may differ greatly depending upon the agent used

(Pahlman, Odelstad et al. 1981, Pahlman, Ruusala et al. 1984, Adem, Mattsson et al. 1987, Prather, Tsai et al. 1994). Treatment of SH-SY5Y cells with 0.1µM morphine for either 1 hour or 24 hours had various, but inconsistent, effects on the expression of most MOR isoforms (Figure 3.4, lanes 2-3) and did not

63 significantly alter the expression of MOR-1 (Figure 3.2, lanes 2-3); however, the expression of the MOR-1X isoform, which is generated by the replacement of the constitutive exon 4 with the alternative exon X and is not endogenously expressed in SH-SY5Y cells (Figure 3.2, lane 1), was significantly up-regulated by 0.1µM morphine treatments of 1 hour (Figure 3.2, lane 2) and 24 hours

(Figure 3.2, lane 3). Interestingly, 24 hour treatments of 50nM rTat (Figure 3.3, lanes 4 and 6) and 100nM rTat (Figure 3.3, lanes 5 and 7) decreased MOR-1 mRNA expression in a dose-dependent manner, whereas concomitant treatment with 0.1µM morphine and either 50nM rTat (Figure 3.3, lane 6) or 100nM rTat

(Figure 3.3, lane 7) for 24 hours attenuated morphine-mediated increases in

MOR-1X mRNA expression in a dose-dependent manner; however, the expression of other MOR isoforms were not consistently altered by rTat (Figure

3.4, lanes 4-7). Multiple mechanisms exist through which morphine and Tat may regulate MOR-1X expression, including the reduction of MOR-1X specific miRNA expression and/or the stabilization of MOR-1X mRNA polyadenylation.

Epigenetic mechanisms, including the regulation of chromatin accessibility through enzymatic acetylation, methylation, ubiquitination, sumoylation, and/or phosphorylation of histone N-terminals or through the displacement of histones by chromatin remodeling complexes, as well as alternative promoter usage may also account for morphine-mediated increases in MOR-1X expression; however, this seems unlikely as the inconsistent and varied expression of other isoforms does not correlate with what would be predicted from selective promoter usage.

Additionally, the expression of Exon 3a, which composes the transmembrane 64 region expressed by a large majority of MOR isoforms and may be used as a marker for overall MOR expression, was not significantly altered by either Tat or morphine individually or concomitantly (Figure 3.3). As such, morphine most likely alters MOR splicing patterns by directly influencing the composition and/or kinetics of alternative splicing machinery.

Aside from the mechanisms of MOR expression mediated by morphine and Tat, the distinct differences between SH-SY5Y cells, a cell line model for dopaminergic neurons, and human fetal primary neurons in both their MOR isoform profile and susceptibility to modulation by environmental factors may simply be a result of the epigenetic suppression of OPRM1 activity or splicing machinery during embryonic development as SH-SY5Y cells are known to have low basal OPRM1 promoter methylation relative to primary human fetal neurons, thereby permitting extensive OPRM1 activity and expression (Nielsen, Yuferov et al. 2009). Furthermore, OPRM1 activity is often suppressed in non-neuronal cell lines, such as HEK293 and CHO, due to tissue-specific expression of

REST/NRSF. Consequently, regulation of REST/NRSF by neurotropic factors, such as IGF-I, may alter opioid receptor expression (Bedini, Baiula et al. 2008,

Kim, Hwang et al. 2008). Cell-type specific differences in the synthesis of endogenous morphine, which may serve as a neurotransmitter and/or neuroendocrine factor, may likewise alter opioid receptor physiology. Therefore, the absence of MOR-1X and other isoforms in both cell lines and primary CNS tissue cultures does not necessarily indicate the absence of a given isoform in vivo but rather the level of that given isoform fell below the detection limit of the

65 experimental procedures utilized here and in previous studies (Dever, Xu et al.

2012). As such, while the expression of additional MOR isoforms, including

MOR-1X, in various cell types and the regulation of their expression by morphine in vivo cannot be excluded, the current data suggests only that MOR-1X mRNA expression in the dopaminergic neuronal cell line SH-SY5Y is up-regulated by morphine both 1 hour and 24 hours after exposure and that this affect is inhibited by the concomitant treatment of 50nM or 100nM or rTat.

The finding presented here that acute, single dose morphine treatment significantly increases MOR-1X mRNA expression in a human cell line model of dopaminergic neurons, but not other cell types, confirms and expands upon previous studies that identified tissue-specific, chronic morphine-mediated regulation of MOR isoforms in mice and rats and correlated opioid abuse with altered MOR isoform expression in methadone maintained individuals

(Vousooghi, Goodarzi et al. 2009, Verzillo, Madia et al. 2014, Xu, Faskowitz et al.

2015), although this is the first instance in which morphine-mediated regulation of the MOR-1X isoform has specifically been found. Whether this shift in isoform expression facilitates a functional change in opioid sensitivity is still unknown as the MOR-1X receptor is poorly characterized but the rapid up-regulation of this isoform upon acute morphine treatment suggests a level of responsivity and a change in subsequent opioid signaling. While previous studies have also found altered MOR isoform expression following HIV infection (Dever, Xu et al. 2012,

Dever, Costin et al. 2014), this study did not confirm any significant effect of the

HIV viral protein Tat on MOR-1X mRNA expression; however, morphine-

66 mediated increases in MOR-1X expression were attenuated by concomitant Tat expression in a dose-dependent manner. As such, the results presented here are the first to suggest a novel interaction between opioids and HIV viral proteins in the regulation of OPRM1 splicing. The role of this interaction in mediating opioid sensitivity of HIV infected individuals in unknown but suggests a divergent pharmacological profile among infected and non-infected individuals treated with morphine.

67 CHAPTER 4 – REGULATION OF ALTERNATIVE SPLICING MECHANISMS

BY MORPHINE AND HIV

4.1 Mechanisms of Constitutive and Alternative Splicing

The mechanisms of both constitutive and alternative splicing reactions, through which introns are removed from pre-mRNA transcripts and exons are ligated together to produce mature mRNA, are regulated by the interaction between cis-acting sequences within the pre-mRNA transcript and numerous trans-acting factors that collectively represent a complex macromolecular machine referred to as the spliceosome. Traditionally, the spliceosome consists of five small nuclear RNAs (U1, U2, U4, U5 and U6), which complex with Sm or

Sm-like proteins along with additional auxiliary proteins to form small nuclear ribonucleoproteins (snRNPs), as well as multiple, non-snRNP splicing factors.

Assembly of the spliceosome is a highly regulated process, facilitated by the weak protein–protein and protein–RNA interactions between the trans-acting factors that comprise the spliceosome and recognized, cis-acting sequences within the pre-mRNA. As such, pre-mRNA splicing occurs in a stepwise manner through the coordinated remodeling of the spliceosome and the sequential catalysis of the pre-mRNA by each intermediate spliceosome complex (Biamonti and Caceres 2009, Hui 2009, Keren, Lev-Maor et al. 2010).

Conserved, cis-acting sequences located within the pre-mRNA interact with multiple spliceosome proteins to enable RNA recognition, spliceosome formation, and initiation of pre-mRNA splicing. These sequences include the exon–intron junctions at the 5′ and 3′ ends of introns, aptly named the 5′ and 3’ splice sites, 68 respectively, and are commonly defined by GT and AG dinucleotides. Although these sequences are loosely conserved, the 5’ splice site generally conforms to the consensus sequence AGGURAGU (R = any purine) while the 3’ splice site often contains a conserved YAG domain (Y = any pyrimidine) that is preceded by a stretch of pyrimidine residues (Kramer 1996). Additionally, a loosely conserved adenosine branch site sequence, YNCURAY (R = any purine, Y = pyrimidine, and N = any nucleotide), located upstream of the 3′ splice site and a polypyrimidine tract (PPT) sequence located between the 3′ splice site and the branch site are found within the pre-mRNA transcripts of spliced genes. While these cis-acting elements are required for pre-mRNA splicing, their sequences are highly degenerate and fall within relatively large intronic regions, which creates a challenge for consistent intron identification. Therefore, splice site selection is initially driven by the identification of exonic regions, typically spanning an average of 300 nucleotides. This is facilitated by cis-acting sequences within the exon itself and in the adjacent intronic regions that serve primarily as degenerate binding sites for auxiliary splicing factors, although some have been shown to alter splice site recognition by manipulating RNA secondary structure (Kramer 1996, Matlin, Clark et al. 2005, Li, Lee et al. 2007, House and

Lynch 2008, Biamonti and Caceres 2009, Chen and Manley 2009, Hui 2009,

Keren, Lev-Maor et al. 2010). An additional factor in exon definition is that the 3’ terminal exon requires additional processing given the presence of a poly(A) tail in mature transcripts. This is facilitated by interactions between polyadenylation and splicing mechanisms and targets an unidentified cis-acting sequence

69 upstream of the conserved polyadenylation signal motif AAUAAA. Mutations within this region result in aberrant splicing, characterized by the retention of proximal, but not distal, intronic regions (Berget 1995). Together, these cis-acting sequences play a pivotal role in alternative splicing mechanisms, given their role in defining exon and intronic regions. Therefore, the spatial and temporal regulation of their RNA-binding protein partners is a key component of alternative splicing regulation

Trans-acting components of the spliceosome interact with the aforementioned cis-acting elements within the pre-mRNA transcript in a sequential, stepwise manner. As such, pre-mRNA splicing occurs through the assembly and activity of multiple, well-defined, spliceosome intermediate structures. The first intermediate of spliceosome assembly and catalysis, which initiates both constitutive and alternative splicing, is the E complex. This complex is formed by four independent protein-RNA interactions between the U1 snRNP and 5’ splice site, splicing factor 1 (SF1, also referred to as branch point binding protein or BBP) and the branch point sequence, and the 65kDa and 35kDa subunits of the heterodimeric splicing factor U2 snRNP auxiliary factor (U2AF) and the PPT and terminal AG of the 3’ splice site, respectively. Following E complex assembly, U2AF facilitates the recruitment of the U2 snRNP to the branch point sequence, displacing SF1 and forming the A complex intermediate in the first ATP-dependent process. The pre-catalytic B complex is generated by the subsequent recruitment of the U4–U6–U5 tri-snRNP by both the U1 and U2 snRNPs and is followed by a series of complex rearrangements that lead to the

70 displacement of the U1 and U4 snRNPs and activation of the B complex. This stimulates the formation of the catalytic core, comprised of the U2, U5, and U6 snRNPs, and facilitates the first transesterification step of a two-step splicing process in which the 2′-hydroxyl group of the branch site adenosine attacks the 5′ guanosine of the intron, resulting in the formation of the cleaved 5’ exon and an intron–3’-exon lariat intermediate. In the second splicing step, facilitated by the C complex, the free 3′-hydroxl group of the upstream exon attacks the 5′ phosphate of the downstream exon, resulting in the excision of the lariat intron and the ligation of the 5’ and 3’ exons. Following splicing, the mature mRNA transcript is ready to be exported from the nucleus, while lariat introns are either degraded or serve as precursors for miRNAs or small nucleolar RNAs (snoRNAs) (Green

1991, Reed 1996, Blencowe, Bowman et al. 1999, Smith and Valcarcel 2000,

Hastings and Krainer 2001, Black 2003, Matlin, Clark et al. 2005, Sanford, Ellis et al. 2005, House and Lynch 2008, Kim, Goren et al. 2008, Biamonti and Caceres

2009, Chen and Manley 2009, Hui 2009, Risso, Pelisch et al. 2012). It should be noted that the aforementioned spliceosome only catalyzes U2-type introns, which predominate in mammalian splicing. A minor spliceosome, comprised of U11,

U12, U5, and variants of the U4 and U6 snRNPs, catalyzes U12-type introns.

While U12-type introns are rare, they can be located in several neuronal transcripts, making them of particular interest in understanding neuronal-specific mechanisms of splicing. Regardless, U2 and U12 specific spliceosomes are well conserved and, therefore, share similar mechanisms of action (Li, Lee et al.

2007, Hui 2009).

71 The mechanism of pre-mRNA splicing is often viewed in isolation, focusing primarily on the protein-protein and protein-RNA interactions between trans-acting factors and the cis-acting elements within a fully transcribed pre- mRNA sequence. Indeed, pre-mRNA transcription and pre-mRNA processing, including mRNA capping, splicing, and cleavage/polyadenylation, were previously thought to be independent events. However, through a series of cytological, biochemical, and functional experiments, it is now understood that pre-mRNA processing, including splicing, is amalgamated with pre-mRNA transcription both spatially and temporally (Kramer 1996, Caceres and Kornblihtt

2002, Kornblihtt 2005). Coordination between pre-mRNA transcription and splicing can begin as early as splice site recognition, with assembly of the spliceosome E complex occurring while the RNA polymerase enzyme is still actively engaged with the DNA template (Gunderson and Johnson 2009). Two, mutually inclusive models explain regulation of alternative splicing by RNA polymerase. The recruitment model proposes that RNA polymerase, as well as transcription factors, interact with trans-acting splicing factors, both directly and indirectly, modulating their interaction with the pre-mRNA transcript and, thus, altering the efficiency of splicing. This model is supported by the fact that promoter structure has been shown to affect splicing patterns, suggesting that elements required for transcription initiation, such as recruitment of transcription factors and RNA polymerase, also regulate aspects of splicing. A second, kinetic model proposes that the inclusion of alternative exons is regulated by the rate of transcription elongation, given that sufficient time is needed for splice site

72 recognition and spliceosome assembly to occur. Slower elongation rates, or interruptions of elongation, typically favor the inclusion of alternative exons containing weak splice sites, whereas fast, continuous elongation typically favors exclusion of these exons. This is due to competition between 3’ splice sites and, as such, is heavily dependent on the order in which 3’ splice sites are transcribed, specifically the occurrence of a weak 3’ splice site located upstream of a strong 3’ splice site. Rapid, uninterrupted elongation produces a transcript in which both splice sites are simultaneously presented to the spliceosome. In this scenario, the stronger 3’ splice site of the downstream intron is favored over the weaker 3’ splice site of the upstream intron. This results in the definition of an intron that includes the weaker 3’ splice site and, as such, the excision of the upstream exon as part of the lariat. Conversely, slow elongation, or pauses in elongation occurring between the 3’ splice sites, allows for each splice site to be presented to the spliceosome individually. Lacking competition from the stronger

3’ splice site of the downstream intron, the weaker 3’ splice site is utilized and the upstream intron is excised. As elongation continues, the stronger 3’ splice site downstream drives the removal of the downstream intron, leading to inclusion of the upstream exon (Kornblihtt 2005, Chen and Manley 2009). It is important to note, however, that co-transcriptional regulation of pre-mRNA splicing, by either a recruitment or kinetic model, is not a strict process. Exon definition and intron removal does not necessarily occur in the exact order that these regions are transcribed, as this rigidity would eliminate the competition between splicing sites, making alternative splicing impossible (Luco, Allo et al. 2011). Therefore, a

73 fluid model of co-transcriptional pre-mRNA splicing, involving multiple factors, must be considered.

Although it is now understood that pre-mRNA splicing is coupled with pre- mRNA transcription, the contribution of different RNA polymerases to this process is not equal. Transcription of protein-encoding genes by RNA polymerase I is efficient but produces unstable transcripts due to a lack of polyadenylation. Likewise, RNA polymerase III is sufficient to transcribe protein- encoding genes, but transcripts are, again, poorly spliced and polyadenylated.

Additional polymerases, such as T7, show similar problems is RNA processing efficacy. As such, co-transcriptional regulation of pre-mRNA splicing is primarily the result of RNA polymerase II activity. Given this specificity, RNA polymerase II must contain unique structural components that allow it to be permissive for accurate pre-mRNA processing. This functional component has been identified as the C-terminal domain of the large RNA polymerase II subunit. This region is able to facilitate binding of multiple factors necessary for pre-mRNA processing and also is subject to conformational changes by cyclin-dependent kinase (CDK)- mediated phosphorylation due to the presence of over fifty tandem repeats of the consensus sequence YSPTSPS (Blencowe, Bowman et al. 1999, Caceres and

Kornblihtt 2002, Kornblihtt 2005, Das, Dufu et al. 2006, Das, Yu et al. 2007,

Liang, Gao et al. 2015). Phosphorylation of the second and fifth serine of the

YSPTSPS consensus sequence is associated with transcription initiation and elongation, respectively. Given the unique role of RNA polymerase II activity in regulating pre-mRNA splicing, factors that modulate transcription by RNA

74 polymerase II will most likely impact pre-mRNA splicing as well. As such, differential phosphorylation of these regions is associated with the failure to initiate transcription and/or interruption of transcription elongation (Kornblihtt

2005, Das, Yu et al. 2007, Chen and Manley 2009). Interruption of transcription elongation by differential phosphorylation is of particular interest in the regulation of pre-mRNA splicing by RNA polymerase II since reduced elongation rates may allow for the identification and inclusion of weak splice sites into the mRNA transcript, as described by the kinetic model. The activity of RNA polymerase II may also be regulated prior to transcription initiation by epigenetic mechanisms.

Both cis-acting elements, such as promoter structure and transcriptional enhancers, and trans-acting factors, such as transcription factors, are known to modulate RNA polymerase II activity and elongation rates. Manipulation of these factors alters splice site selection, suggesting a complex mechanism of alternative splicing that, in part, involves differential occupation of promoter regions by RNA polymerase II (Cramer, Pesce et al. 1997, Kornblihtt 2005).

While opioids and related signaling pathways, such as MAPK signaling

(discussed in section 5.2.3), have been found to regulate CDK activity (Wang,

Xie et al. 2006, Hisanaga and Endo 2010), the susceptibility of the OPRM1 gene to RNA-polymerase II-mediated changes in splicing specificity as well as the role of opioids in regulating RNA polymerase II activity directly is largely uncharacterized.

75 4.2 Auxiliary Splicing Proteins

As described previously, both constitutive and alternative splicing is facilitated by the spliceosome, a dynamic complex of snRNPs and additional non-snRNP protein factors. Splicing patterns are mediated by a combination of cis- and trans-acting factors that target the spliceosome to defined exonic regions prompting 5’ and 3’ splice site selection. To ensure proper splicing, 5’ and 3’ splice sites, located along exon–intron boundaries, are identified by short consensus sequences; however, consensus sequences at both the 3’ and 5’ splice sites are only loosely conserved. Furthermore, alternative exons often contain suboptimal 3’ and 5’ splice sites compared to constitutive exons. Given these constraints, one would not expect to see the spatially and temporally diverse splicing patterns found throughout many physiological systems. This suggests that additional factors facilitate the selective inclusion and exclusion of suboptimal 3’ or 5’ splice sites in alternative splicing (Lopez 1998, Caceres and

Kornblihtt 2002, Bracco and Kearsey 2003, Stamm 2007). Generally speaking, two classes of proteins are responsible for the selective expression of alternative exons. Prototypical exon inclusion factors include a family of serine-arginine rich proteins, dubbed SR proteins, while prototypical exon exclusion factors involve heterogeneous nuclear ribonucleoproteins (hnRNPs). In general, SR proteins and hnRNPs enhance or diminish, respectively, the utilization of the 3’ and 5’ splice sites they interact with, although opposite interactions have been found to occur (Stamm, Ben-Ari et al. 2005, Stamm 2007, Kelemen, Convertini et al.

2013).

76 4.2.1 Heterogeneous nuclear ribonucleoproteins (hnRNPs)

Heterogeneous nuclear ribonucleoproteins (hnRNPs) are chromatin- associated RNA-binding proteins characterized not only by the presence of RNA- binding motifs, but also by auxiliary domains hypothesized to mediate protein- protein interactions. Despite containing similar structural features, hnRNPs do not represent a family of related proteins. Their role in transcriptional and post- transcriptional regulation was first identified by the characterization of hnRNP K, which can bind single-stranded DNA (ssDNA) and has a high affinity for upstream promoter regions. It is hypothesized that hnRNP K facilitates chromatin remodeling, regulating the recruitment of transcription factors to the promoter region. Accordingly, hnRNP K has been characterized as both a transcriptional activator and repressor. In addition to regulating promoter activity, hnRNPs also recognize RNA sequence elements important for efficient mRNA synthesis, specifically at the 3’ end. Both PTB/hnRNP l and hnRNP H have been identified as cleavage/polyadenylation regulatory factors, as they target the GU-rich motif positioned downstream of the poly(A) site (Krecic and Swanson 1999, Black

2003). The most recognized function of hnRNPs is their selective association with several ESSs, ISEs, and ISSs (Berget 1995, Krecic and Swanson 1999,

Matlin, Clark et al. 2005). Binding of hnRNPs to these intronic and exonic sequences generally promotes exclusion of targeted regions from the mature mRNA. Proposed mechanisms of hnRNP function in alternative splicing include competing with the 65kDa unit of U2AF for binding at the PPT, interfering with splicing complex assembly across introns or exon regions, and mediating

77 inhibitory secondary structures between RNA binding sites (Llorian, Schwartz et al. 2010). Collectively, hnRNP proteins demote intermediary spliceosome formations, specifically the spliceosome E and A complexes (Matlin, Clark et al.

2005). Given this capacity to differentially exclude targeted exons, hnRNP proteins represent a key regulatory mechanism in alternative splicing and, as such, regulation of their expression is essential for proper splicing (Berget 1995).

This is particularly interesting, given that hnRNP expression has been shown to be cell-type specific (Kamma, Portman et al. 1995). As such, cell-type specific expression may account for the differences in alternative splicing between cell types.

4.2.2 SR proteins

The SR protein family of splicing factors, which are remarkably conserved across vertebrates, invertebrates, and plants, contains multiple proteins known as serine/arginine-rich splicing factors (SRSF) or as individually named factors, which include alternative splicing factor/splicing factor 2 (ASF/SF2 or SRSF1),

SC35 (SRSF2), SRp20 (SRSF3), SRp75 (SRSF4), SRp40 (SRSF5), SRp55

(SRSF6), 9G8 (SRSF7), SRp46 (SRSF8), SRp30c (SRSF9), Transformer-2 protein homolog beta (Tra2β or SFRS10), SRp54 (SRSF11), and SRp35

(SFSR12). Additional unrelated proteins have been found containing similar characteristics and are referred to as SR-like proteins. Similar to hnRNPs, SR proteins are characterized by the localization of one or two RRM domains within the N-terminal domain. However, for the majority of SR proteins containing two

RRM domains, the second is less conserved and is often regarded as a RRM 78 homolog. Additionally, a V-RRM domain, characterized by a SWQDLKD motif, is located in all SR proteins with the exception of SRp20, SC35, and 9G8. These

RRM domains facilitate sequence-specific protein-RNA interactions. A third RS- rich domain, characterized by multiple RS and SR dipeptides and appropriately named the RS or SR domain, can be found within the C-terminal domain of SR proteins. This region is highly variable with respect to length; however, the high serine content within this region facilitates extensive phosphorylation of the RS domain within all SR proteins, important for protein-protein interactions (Kramer

1996, Xiao and Manley 1997, Blencowe, Bowman et al. 1999, Blencowe 2000,

Smith and Valcarcel 2000, Hastings and Krainer 2001, Black 2003, Cazalla,

Newton et al. 2005, Shepard and Hertel 2009). Between the RRM-containing N- terminal domain and the RS-containing C-terminal domain lies a series of glycine residues, which form a flexible hinge important for tertiary structure (Zahler, Lane et al. 1992).

The importance of SR proteins in constitutive and alternative splicing cannot be understated. Regulatory roles for SR proteins begin before spliceosome assembly. Both the C-terminal domain of RNA polymerase II as well as numerous transcription factors have been shown to interact with various SR proteins, thereby facilitating their association with transcription initiation sites

(Blencowe, Bowman et al. 1999, Caceres and Kornblihtt 2002). SR proteins also interact directly with pre-mRNA transcripts, with specificity being determined by the RRM domains; however, the RS domain has also been found to interact directly with pre-mRNA transcripts, specifically the branch point sequence.

79 Following these early interactions, recruitment and assembly of the spliceosome is facilitated by protein-proteins interactions between spliceosome proteins and the RS domain of SR proteins (Cazalla, Newton et al. 2005). As such, SR proteins are among the earliest factors incorporated into the spliceosome and commit the pre-mRNA to the splicing pathway. Incorporation of SR proteins into the spliceosome occurs at the time of E complex assembly and, in fact, facilitates

E complex formation by enhancing U1 snRNP binding to 5‘ splice sites. This is likely mediated by direct protein-protein interactions between SR proteins and U1 snRNP. Interestingly, at high enough concentrations, SR proteins can eliminate the need for U1 snRNP binding in spliceosome assembly, suggesting a level of redundancy between these spliceosome components. Following spliceosome assembly, SR proteins continue to serve as a critical component of spliceosome activity. They signal transition from the E complex to the A complex by recruiting

U2 snRNP to the branch site. SR proteins are also required for transition between the A complex and pre-catalytic B complex, as they aid the incorporation of the U4–U6–U5 tri-snRNP into the spliceosome (Sun, Mayeda et al. 1993, Fu 1995, Kramer 1996, Blencowe, Bowman et al. 1999, Hastings and

Krainer 2001, Cazalla, Newton et al. 2005, Shepard and Hertel 2009). Finally, SR proteins facilitate 5’ and 3’ splice site selection through their association with cis- acting elements within the pre-mRNA.

The first SR protein identified, now called ASF/SF2, serves as the prototypical SR protein and, as such, is the best-studied member of the SR protein family along with SC35 (Wang and Manley 1995, Black 2003).

80 Characteristic of SR family proteins, both ASF/SF2 and SC35 contain 2 RRM domains as well as a single RS domain (Zuo and Manley 1994, Wang and

Manley 1995, Hanamura, Caceres et al. 1998). The early steps of spliceosome assembly include incorporation of ASF/SF2 and SC35 into the spliceosome, committing pre-mRNAs to the splicing pathway. As such, ASF/SF2 and SC35 are regarded as essential splicing factors and, given their high degree of homology in both structure and function, were originally thought to be redundant (Wang and

Manley 1995). In support of this, SC35 was found to target the same alternative

5’ splice sites as ASF/SF2. In addition, ASF/SF2 and SC35 were found to have similar effects on 3’ splice site selection, with differences being attributed to suboptimal expression of ASF/SF2 (Fu, Mayeda et al. 1992, Fu 1995). However, additional studies found that optimal RNA binding sites are specific for either

ASF/SF2 or SC35, resulting in either protein having distinct effects on splicing.

How this specificity is distinguished is not fully characterized but is thought to result from differences in RNA and protein binding (Wang and Manley 1995). For

ASF/SF2, the RRM2 domain is known to determine the specificity of splice site selection (van Der Houven Van Oordt, Newton et al. 2000). Additionally, the RS domain for ASF/SF2 is required for its association with U1 and U2 snRNPs during spliceosome assembly at constitutive 5’ splice sites but is dispensable when targeting alternative 5’ splice sites (Zuo and Manley 1994, Wang and

Manley 1995); however, the necessity of this domain in constitutive splicing has recently been called into question (Hastings and Krainer 2001). Another distinguishing feature of ASF/SF2 is that it is essential for cell viability, with

81 knockouts being embryonic lethal. This is not seen for other SR proteins and cannot be rescued by overexpression of other SR proteins, including SC35

(Caceres and Kornblihtt 2002). It is now understood that ASF/SF2 plays a unique and critical role in both splicing and non-splicing processes, and, as such, understanding of ASF/SF2-mediated mechanisms has helped to characterize the roles of SR proteins in general.

Non-splicing functions of ASF/SF2 occur though interactions with both

RNA and proteins. These functions include regulating overall protein- sumoylation, through association with sumoylation ligases (Pelisch, Gerez et al.

2010), facilitating viral genome expression, thereby acting indirectly in immunosuppressive functions (Sariyer and Khalili 2011), and signaling nonsense mediated decay of mRNAs containing premature stop codons (Long and

Caceres 2009, Zhong, Wang et al. 2009) in addition to multiple others (Chen and

Manley 2009). However, one of the most critical non-splicing roles of ASF/SF2 is the maintenance of genome stability through the prevention of R loop formation.

During replication and transcription, chromosomal double-stranded DNA

(dsDNA) unwinds, primarily within the active site of the bound RNA polymerase

II, and allows for the formation of an approximately 8bp RNA:DNA duplex between the open ssDNA strands. As transcription progresses, the nascent RNA transcript is displaced and the two chromosomal DNA strands revert to their closed dsDNA conformation. R loops result from the rare occurrence in which the nascent pre-RNA transcript, upon leaving the RNA polymerase II active site, invades the open chromosomal DNA duplex and binds the complementary DNA

82 strand, forming a three-strand nucleic acid structure comprised of an RNA:DNA duplex plus the displaced non-complementary ssDNA strand. This creates a bubble within the chromosomal DNA, which ultimately results in genome instability, leading to chromosomal mutations and loss. Cells utilize numerous factors, including RNases, to prevent the deleterious consequences of persistent

R loops (Li and Manley 2005, Li and Manley 2005, Aguilera and Garcia-Muse

2012). ASF/SF2 is recruited to nascent pre-mRNA transcripts through interactions with the C-terminal domain of RNA polymerase II, thereby preventing the association between nascent pre-mRNA transcripts and the open chromosomal DNA. Depletion of ASF/SF2 results in cell death due, in part, to increased R loop formation and genomic instability, as is evident in the fact that cell death in ASF/SF2 depleted cells is partially rescued by over-expression of

RNase H (Li and Manley 2005, Li and Manley 2005). ASF/SF2 has also been found to have additional functions in apoptosis and cell proliferation, primarily through the regulation of essential cell cycle and apoptotic protein splicing as decreased expression of ASF/SF2 increases pro-apoptotic splicing patterns and promotes cell cycle arrest (Li, Wang et al. 2005, Massiello and Chalfant 2006,

Moore, Wang et al. 2010, Anczukow, Rosenberg et al. 2012). Therefore, it can be concluded that ASF/SF2 is a mandatory splicing factor with additional, non- splicing functions essential for cell viability.

83 4.3 Regulation of Alternative Splicing by Modification of Auxiliary Splicing

Proteins

Despite the variety of splicing patterns seen across tissue types, highly specific splicing factors are uncommon and, instead, both constitutive and alternative splicing are regulated by a broad pool of general splicing factors.

While the mechanisms of spliceosome formation, activity, and splice site selection have been determined in great detail for constitutive splicing, the mechanisms deciding alternative 3’ and 5’ splice site selection by general splicing factors is not fully understood. This is due to the degeneracy of cis-acting regulatory sequences, making it impossible to accurately predict splicing patterns from the genomic sequence alone. Therefore, complex, combinatorial regulatory mechanisms involving trans-acting splicing factors and cis-acting elements are required for the accurate recognition of splice sites in vivo. Specificity in constitutive and alternative splicing is now understood to involve the selective expression and activation of auxiliary splicing proteins, in addition to the position placement and strength of the cis-acting elements they target (Lamond 1991,

Lopez 1998, Stamm, Ben-Ari et al. 2005). As such, these cis- and –trans acting elements are subject to multiple mechanisms of regulation in order to maintain the level of specificity necessary for proper splicing in vivo. For trans-acting factors, this regulation includes the dynamic phosphorylation, localization, and the relative and overall abundance of auxiliary splicing factors, while for cis- acting factors it involves the relative positions of consensus sequences and RNA secondary structure.

84 4.3.1 Spatial and temporal regulation of auxiliary splicing proteins

It is not surprising that both constitutive and alternative splicing activity exhibit spatial and temporal regulation given that they are functionally coupled to epigenetic and transcriptional mechanisms and dependent on interactions with auxiliary splicing proteins. Initiation of co-transcriptional splicing begins within subcellular compartments of the nucleus called nuclear speckles, which occupy nearly 20% of the total nuclear volume and can exhibit one of two conformations.

Interchromatin granule clusters (IGCs) represent the primary nuclear speckle conformation associated with the storage and reassembly of splicing factors, predominantly SR proteins due to targeted shuttling by their RS domains; however, IGCs also contain transcription factors and ribosomal proteins. The second nuclear speckle conformation, perichromatin fibrils, represents the nuclear site of actively transcribing genes and co-transcriptional splicing. The dynamic nature of co-transcriptional splicing requires that SR and additional splicing proteins be recruited from IGCs to the sites of co-transcriptional splicing within perichromatin fibrils (Blencowe, Bowman et al. 1999, Cramer, Caceres et al. 1999, Misteli 2000, Cazalla, Zhu et al. 2002, Cazalla, Newton et al. 2005,

Shepard and Hertel 2009). Cytoplasmic and nuclear granules, called stress granules, also play a role in the subcellular localization of splicing factors.

Nuclear stress granules recruit ASF/SF2, 9G8, and SRp30c but surprisingly not

SC35, changing the relative abundance of these splicing factors within the nucleus. Cytoplasmic stress granules function similarly, although the only SR protein recruited is ASF/SF2. Formation of these transient structures are induced

85 by numerous cell stressors and, in the case of cytoplasmic stress granules, are mediated by a shuttling RNA-binding protein, TIA-1-related (TIAR) protein. This protein plays a dual role within the cell, facilitating alternative splicing events within the nucleus but repressing translation within the cytoplasm. Translational repression by TIAR protein is mediated by the migration of ASF/SF2 from the nucleus to stress granules, where it interacts with TIAR proteins to reduce mRNA stability and translation (Biamonti and Caceres 2009, Delestienne, Wauquier et al. 2010). The presence of both nuclear speckles and cytoplasmic stress granules, as well as the migration of proteins between these two compartments, highlights the extent to which splicing proteins are spatially regulated in order to facilitate efficient co-transcriptional splicing and translation. As such, factors that alter this dynamic process would be expected to have significant consequences not only in splicing activity and protein expression but in cellular function and viability overall. In respect to this, signaling pathways identified to alter spatial regulation of splicing factors, for example p38 MAPK signal cascade-mediated or

Smu-1-mediated regulation of hnRNP A1 or ASF/SF2 subcellular localization, respectively (Bracco and Kearsey 2003, Sugaya, Ishihara et al. 2011), present novel targets for therapeutic regulation of splicing proteins.

In addition to subcellular spatial regulation, numerous mechanisms of pre- mRNA splicing are differentially regulated in a cell-type-specific manner, resulting in tissue-specific alternative splicing patterns. Indeed, variable expression of ubiquitous auxiliary splicing factors has been found (Hanamura, Caceres et al.

1998). Additionally, tissue-specific alternative splicing regulators, such as

86 NOVA1-2, nPTB, CELF family proteins, and Hu/Elav family proteins, have been identified, particularly in the brain. The selective expression of these splicing factors mediates tissue-specific splicing patterns seen for certain proteins; however, no single splicing factor has been identified as essential for the specificity of splicing in any system (Caceres and Kornblihtt 2002, Black 2003,

Matlin, Clark et al. 2005, Chen and Manley 2009, Luco, Allo et al. 2011, Barrie,

Smith et al. 2012). Regulation of tissue-specific splicing is essential not only for specificity in certain cell-type functions but also for general cell viability. For example, proper Nova-1 mediated splicing of inhibitory receptor pre-mRNAs is essential for postnatal motor neuron viability (Jensen, Dredge et al. 2000).

Although lacking tissue specificity, ubiquitous splicing factors exhibit deviate temporal expression in various tissue systems. This is evident in the fact that concentrations of prototypical SR and hnRNP proteins, ASF/SF2 and hnRNP

A1, respectively, fluctuate within the uterine myometrium during pregnancy

(Pollard, Sparey et al. 2000). Likewise, ASF/SF2 and SRp20 show temporally regulated activity during cell-cycle progression, being associated with chromatin during interphase but disassociating from mitotic chromosomes only to re- associate with late M-phase chromosomes (Loomis, Naoe et al. 2009). This is not unexpected, as several splicing factors are associated with epigenetic regulatory mechanisms, including factors that modify of histone and chromatin structure as well as transcriptional activity (Ge, Si et al. 1998, Malanga, Czubaty et al. 2008, Luco, Pan et al. 2010). Accordingly, fluctuations in the expression of numerous splicing factors are seen throughout development (Grabowski and

87 Black 2001, Caceres and Kornblihtt 2002, Li, Lee et al. 2007). Therefore, essential constitutive and alternative splicing activities within a given tissue system are mediated by a combination of ubiquitously expressed and tissue- specific splicing factors that are temporally and spatially regulated, thereby directing the characteristics of that tissue system.

4.3.2 Phosphorylation of SR proteins

One of the most important aspects regulating SR protein function is their phosphorylation state. Phosphorylation of SR proteins usually occurs at serine residues within the RS domain. The importance of regulated SR protein phosphorylation is evident in the fact that both hyper- and hypo-phosphorylation of the RS domain inhibit SR protein activity (Prasad, Colwill et al. 1999, Black

2003). This suggests two, mutually exclusive possibilities for the level of phosphorylation necessary to mediate SR protein function. Either a consistent level of phosphorylation is necessary throughout SR protein functioning or, more likely, SR protein functioning occurs as a dynamic process requiring different levels of phosphorylation to mediate different stages of co-transcriptional splicing.

The latter has since been shown to be true, with different levels of phosphorylation needed to mediate SR protein shuttling in addition to SR protein phosphorylation facilitating splice site selection and, equivalently, SR protein dephosphorylation catalyzing splicing reactions (Prasad, Colwill et al. 1999,

Shepard and Hertel 2009). Given that SR protein phosphorylation is temporally regulated, specific mechanisms must exist in order to differentially regulate phosphorylation, and identification of these mechanisms is critical in 88 understanding the role of auxiliary splicing proteins in alternative splicing mechanisms.

Phosphorylation states of SR proteins are maintained by a combination of kinases and phosphatases. The protein kinases regulating SR protein phosphorylation are considerably more characterized, with the most recognized being the SR-specific protein kinase (SRPK) family (Hagopian, Ma et al. 2008,

Ma, Velazquez-Dones et al. 2008, Mao, Ceccarelli et al. 2008). Members of the

SRPK kinase family preferentially phosphorylate the serine residues of RSR motifs within the RS domains of SR proteins, going directionally from C-terminal to N-terminal (Prasad and Manley 2003, Velazquez-Dones, Hagopian et al. 2005,

Ma, Velazquez-Dones et al. 2008, Ma, Hagopian et al. 2009). Phosphorylation of

SR proteins by SRPK family kinases is also dependent on the structural organization and conformational changes in both the kinase and target protein, although understanding of this mechanism is incomplete (Hagopian, Ma et al.

2008, Mao, Ceccarelli et al. 2008, Ma, Hagopian et al. 2009). A second kinase family, known as the CDC-like kinase (CLK) family, has also been well characterized (Colwill, Pawson et al. 1996, Velazquez-Dones, Hagopian et al.

2005). Members of the CLK kinase family show dual specificity in phosphorylation, targeting both serine and threonine residues (Colwill, Pawson et al. 1996, Prasad and Manley 2003). The mechanism of CLK-mediated phosphorylation is sequential, similar to that of SRPK. However, whereas phosphorylation by SRPK family kinases is restricted to serines within the N- terminal portion of RS domains, CLK family kinases target the majority of

89 available phosphorylation sites throughout the RS domain. As such, SR proteins cannot be phosphorylated by SRPK and CLK family kinases simultaneously due to steric hindrance, suggesting a level of antagonism between SRPK and CLK family kinases, although this is typically avoided as SRPK and CLK family kinases are spatially regulated, leading to distinct substrates for each kinase family. SRPK family proteins are predominantly expressed in the cytoplasm despite containing nuclear localization motifs. Given that co-transcriptional regulation occurs within perichromatin fibrils located in the nucleus, SRPK family kinases indirectly regulate splicing mechanisms through their interaction with cytoplasmic splicing factors. Conversely, CLK family kinases are localized to the nucleus, where they directly target SR proteins within nuclear speckles (Colwill,

Pawson et al. 1996, Koizumi, Okamoto et al. 1999, Prasad and Manley 2003,

Velazquez-Dones, Hagopian et al. 2005, Ma, Velazquez-Dones et al. 2008).

Additional kinases, such as glycogen synthase kinase-3 (GSK-3), Akt, PKA,

PKC, topoisomerase I, and cdc2 kinase have also been shown to phosphorylate

SR proteins in a manner similar to SRPK and CLK kinase families. These proteins show more temporal than spatial regulation, as is evident in the activation of cdc-2, which is associated the cell-cycle dependent phosphorylation of ASF/SF2 (Okamoto, Onogi et al. 1998, Stamm 2007).

Although not as well characterized as kinases, protein phosphatases represent key factors in the regulation of SR protein phosphorylation states by precipitating protein dephosphorylation (Biamonti and Caceres 2009, Ma, Ghosh et al. 2010). Just as SRPK1 and CLK family kinases mediate phosphorylation of

90 SR proteins in a sequential and directional manner, from C-terminal to N- terminal, dephosphorylation by protein phosphatases, such as protein phosphatase 1 (PP1), also proceeds in a sequential and directional manner, but in the opposite direction, from the N-terminal to the C-terminal. Despite this similar, although inverse, mechanism utilized to maintain proper phosphorylation states of SR proteins, kinases and phosphatases are distinct in their association with the RS domain. SRPK and CLK family kinases bind to their substrates with high affinity and catalyze the phosphorylation of multiple target residues in rapid succession. In contrast, phosphatases bind their phosphorylated substrates with much lower affinity and catalyze dephosphorylation with considerably less efficiency. This is not due to functional differences between kinase and phosphatase enzymes, but rather structural components within their substrates, specifically the N-terminal RRM domain of SR proteins, which selectively diminish phosphatase activity. This is demonstrated by the fact that ablation of the RRM domains in ASF/SF2 enhances PP1 activity toward the RS domain without altering phosphorylation activity (Ma, Ghosh et al. 2010).

Both SRPK and CLK family kinases belong to the larger protein family of

LAMMER signal transduction kinases and, as such, their activity is subject to regulation by downstream signaling cascades, including Ca2+/calmodulin/CaMK,

PI3K/Akt, and several MAPK pathways (Misteli, Caceres et al. 1997, Tarn 2007,

Lynch 2008, Biamonti and Caceres 2009, Hui 2009). These kinase transduction cascades transmit cellular signals that alter phosphorylation of splicing factors in order to regulate splicing events. Multiple stress conditions have been shown to

91 phosphorylate splicing factors through the activation of kinase transduction cascades. Both osmotic shock and ultraviolet-C (UVC) irradiation activate the

MEK3/6-p38 MAPK signaling cascade, which facilitates hyper-phosphorylation of hnRNP A1 by Mnk1/2 kinases, stimulating nuclear export (Tarn 2007, Biamonti and Caceres 2009, Chen and Manley 2009). Additional stress factors, including heat shock and chemical stressors, mediate the translocation of select SR proteins into nuclear stress granules that, as described previously, alter the relative levels of these splicing factors within nuclear speckles and the nucleoplasm (Biamonti and Caceres 2009). In addition to cellular stressors, multiple growth factors also mediate cellular splicing through kinase transduction cascades. Activation of the PI3K/Akt signaling cascade by growth factors, such as EGF and insulin, results in the phosphorylation and activation of both SRPK and Clk family kinases (Patel 2001, Tarn 2007, Jiang, Patel et al. 2009, Zhou,

Qiu et al. 2012). Additional signaling cascades, including the JAK/STAT and ERK

MAPK pathways, have been implicated in EGF-induced alterations in splicing

(Lynch 2008, Zhou, Qiu et al. 2012). Protein phosphatase activity is also regulated by PKC-mediated phosphorylation and activation of inhibitor proteins, such as kinase-enhanced PP1 inhibitor (KEPI). Interestingly, KEPI mRNA within the CNS is up-regulated by both acute and chronic morphine treatment (Liu,

Zhang et al. 2002). Collectively, the provided examples highlight the wide variety of signaling pathways utilized to regulate splicing activity through the phosphorylation of splicing factors.

92 Multiple aspects of SR proteins are regulated through their phosphorylation and dephosphorylation, including subcellular localization, relative activity, and specificity (Cao, Jamison et al. 1997, Hanamura, Caceres et al. 1998, Xiao and

Manley 1998, Hui 2009, Long and Caceres 2009). Hypo-phosphorylated forms of certain SR proteins, including ASF/SF2 and 9G8, are localized to the cytoplasm.

This is mediated by interactions with the nuclear export protein TAP/NFX1, which has a high affinity for hypo-phosphorylated SR proteins. Phosphorylation of SR proteins by cytoplasmic SRPK family kinases initiates their translocation back into the nucleus (Prasad and Manley 2003, Stamm 2007, Ma, Velazquez-Dones et al. 2008, Long and Caceres 2009). Although hypo-phosphorylated forms of SR proteins do not have direct roles in splicing functions, their translocation into the cytoplasm is essential for their non-splicing functions. Inside the nucleus, Clk kinases work in combination with phosphatases to maintain an optimal level of

SR protein phosphorylation in order to facilitate their transition between and function within nuclear speckles. Clk family kinases phosphorylate all the classical SR proteins, including ASF/SF2, SC35, and SRp20. Hyper- phosphorylation of SR proteins by Clk family kinases disrupts their localization within nuclear speckles, resulting in a loss of ICG structural integrity and a diffuse redistribution of splicing factors throughout the nucleus, altering splicing patterns

(Misteli, Caceres et al. 1997, Prasad, Colwill et al. 1999, Prasad and Manley

2003). Additionally, hyper-phosphorylation interferes with the disassociation of

SR proteins from other splicing factors, preventing the transition of the spliceosome B complex from an inactive to active conformation, thereby

93 inhibiting spliceosome catalysis (Xiao and Manley 1998). Hypo-phosphorylation of SR protein RS domains facilitate non-specific RNA binding, reducing proper protein-protein interactions required for 5’ splice site selection, such as between

ASF/SF2 and U1 snRNP, thereby disrupting alternative splicing (Prasad, Colwill et al. 1999). Likewise, hypo-phosphorylation by PP1 disrupts SR protein translocation, early spliceosome assembly, and 5’ splice site selection (Koizumi,

Okamoto et al. 1999). Therefore, dynamic phosphorylation cycles are necessary in order to regulate many aspects of SR proteins, including subcellular localization, protein folding, RNA binding, and protein-protein interactions that, in turn, facilitate sequential spliceosome assembly and catalysis, through the alteration of positive and negative charge ratios. Accordingly, given the complexity of co-transcriptional splicing, it is likely that multiple kinases and phosphatases work in coordination with one another to regulate the many facets of splicing (Colwill, Pawson et al. 1996, Kramer 1996, Xiao and Manley 1997,

Xiao and Manley 1998, Blencowe, Bowman et al. 1999, Misteli 2000).

4.3.3 Splice site consensus sequences for auxiliary splicing proteins

Separate from the regulatory mechanisms that control splicing protein localization and phosphorylation state, factors that impact splicing events also include the characteristics of cis-acting factors, including the PPT, the branch point sequence, the polyadenylation sequence signal within the terminal intron, and, most notably, the 3’ and 5’ splice sites. Given the large size of intronic sequences, early stages of spliceosome assembly involve the definition of exonic

3’ and 5’ splice sites through cross-exonic interactions between the U1 snRNP- 94 bound 5’ exonic splice site and the upstream U2AF complex-bound 3’ splice site.

As co-transcriptional splicing proceeds, the intronic region is defined by cross- intronic interactions between the upstream U1 snRNP-bound 5’ exonic splice site, a downstream U2AF complex-bound PPT, branch point sequence, and 3’ splice site, and the U4–U6–U5 tri-snRNP. The point at which this transition occurs is still unclear but is thought to occur during either spliceosome E complex assembly or spliceosome A complex conversion. However, while the ATP hydrolysis necessary for A complex formation irreversibly selects splice sites and commits to a splicing pattern, exon definition by U1 snRNP and U2AF binding during E complex formation does not, suggesting that splicing patterns are committed to during spliceosome A complex catalysis (Lopez 1998, Hertel and

Maniatis 1999, Chen and Manley 2009). The 3’ and 5’ splice site sequences responsible for recruiting these spliceosome factors are highly degenerate, being loosely characterized by AG and GU dinucleotides at intronic 3’ and 5’ ends, respectively. In fact, splice site consensus sequences are degenerate enough that they can be found randomly within approximately 1% of all RNA sequences, suggesting that the definition and splicing of introns involves selection between multiple candidate sites. This selection is facilitated, somewhat, by the kinetic factors involved in RNA polymerase II transcription as well as steric factors of exon definition; however, the presence of additional sequence elements serves as the primary mechanism for the determining splice site selection. These sequence elements are categorized as exonic splicing enhancers (ESEs), intronic splicing enhancers (ISEs), exonic splicing silencers (ESSs) or intronic

95 silencing silencers (ISSs) based on position and selectively promote the incorporation or exclusion of their adjoining region (Eperon, Makarova et al.

2000, Zheng 2004, Stamm, Ben-Ari et al. 2005).

The most characterized of these additional sequence elements are the exonic splicing enhancer sequences (ESEs). ESE sequences are divided into two classes based on their purine content. Purine-rich ESE sequences are more commonly found and are characterized by a core motif of alternating AG dinucleotides spanning 6 base pairs or longer. Interestingly, nucleotide stretches of similar lengths that only contain repeats of either A or G, not both, do not function as ESE sequences. These cis-acting elements are typically localized within exonic regions downstream of suboptimal 3’ splice sites. Interaction with the RRM domain of select SR proteins facilitates the recruitment and binding of these splicing factors to the ESE domain. ESE-bound RS proteins function to enhance U2AF binding to the upstream 3’ splice site and U1 snRNP binding to the downstream 5’ splice site through protein-protein interactions involving the

RS domain. This ultimately results in the definition of the upstream exon and initiation of spliceosome assembly. As transcription progresses, similar reactions within a downstream exon allows for intronic definition through protein-protein interactions between the U1 snRNP-bound 5’ splice site, the downstream U2AF- bound 3’ splice site, the U4–U6–U5 tri-snRNP, and additional SR proteins, such as ASF/SF2 and SC35, which span the intronic region (Sun, Mayeda et al. 1993,

Adams, Rudner et al. 1996, Smith and Valcarcel 2000, Hastings and Krainer

2001, Black 2003, Long and Caceres 2009, Shepard and Hertel 2009, Wu,

96 Zhang et al. 2009). These SR protein-mediated processes are thought to occur prior to or during initiation of spliceosome E complex formation (Staknis and

Reed 1994, Jamison, Pasman et al. 1995, Kramer 1996). The less common class of ESE sequences, categorized as non-purine-rich ESEs, are comprised of both AC-rich and pyrimidine-rich exonic enhancer motifs and regulate splice site selection by a similar mechanism, although through the recruitment of different splicing factors, such as cold-shock cellular proteins, to splice sites (Zheng

2004).

Opposing the activity of ESE sequences are exonic splicing silencers

(ESSs). These cis-acting sequences are often localized downstream of a juxtaposed ESE sequence, although they can also function upstream of ESEs, and serve to antagonize ESE activity and demote utilization of the upstream suboptimal 3’ splice sites. Unlike ESE sequences, ESSs show little conservation in binding motifs and are largely uncharacterized. As such, regulation of splice site selection by ESS sequences occurs primarily through unknown mechanisms.

It is known, however, that these sequence elements recruit hnRNP binding in order to block spliceosome formation. Generally speaking, ESE and ESS sequences collectively regulate splice site selection through one of two mechanisms. The U2AF recruitment model proposes that ESE sequences recruit

SR proteins, which further recruit components of the U2AF complex to suboptimal 3’ splice sites; however, this model does not account for the activity of

ESS sequences. A second model, known as ESE neutralization or inhibition, hypothesizes that ESS sequences are the primary regulatory factors in exon

97 definition and that the activity of ESE sequences is meant to antagonize this constitutive inhibition. This is supported by the fact that ESE-independent splicing can occur in the absence of an ESS sequence (Zheng 2004, Lin and Fu 2007,

Shaw, Chakrabarti et al. 2007, Long and Caceres 2009).

The least characterized cis-acting elements are the intronic splicing enhancers (ISEs) and silencers (ISSs). As their names imply they are localized to intronic regions, as opposed to exonic regions, where they serve a similar function as ESE and ESS sequences in facilitating inclusion or exclusion of adjoining regions; however, the mechanism through which this occurs is still unclear. (Smith and Valcarcel 2000, Black 2003, Matlin, Clark et al. 2005, Long and Caceres 2009, Shepard and Hertel 2009). Despite unclear mechanisms of actions, numerous auxiliary splicing proteins have been found to bind intronic sequence elements and include hnRNP F, hnRNP H, NOVA1-2 proteins, and

FOX1-2 for ISEs and hnRNP family proteins for ISSs (Kramer 1996, Matlin, Clark et al. 2005, Li, Lee et al. 2007, House and Lynch 2008, Biamonti and Caceres

2009, Chen and Manley 2009, Hui 2009, Keren, Lev-Maor et al. 2010).

Therefore, the importance of these additional intronic sequence elements lies in their dynamic interaction with splicing factors. As such, variations in their localization and specificity of splicing factors recruited serve to differentially regulate splicing patterns.

Although an oversimplification, typically SR proteins bind to ESE elements and facilitate exon inclusion whereas hnRNPs bind to ESS and facilitate exon exclusion; however, not all sequence elements are targeted by the same splicing

98 factors (Tacke and Manley 1999, Smith and Valcarcel 2000, Shin and Manley

2004, Matlin, Clark et al. 2005, Lin and Fu 2007, House and Lynch 2008, Hui

2009). The specificity of SR protein and hnRNP binding to regulatory sequence elements are mediated by sequence-specific cis-acting elements within the pre- mRNA transcript. Promoter sequences have been found to aid in the recruitment of select SR proteins, such as ASF/SF2 and 9G8, to ESE sequences through their varying affinity to promote interactions between SR proteins and RNA polymerase II (Cramer, Caceres et al. 1999). In addition to these promoter elements, various consensus motifs are localized within splicing regulatory regions and facilitate high-affinity binding of specific hnRNPs and SR proteins

(Long and Caceres 2009). Multiple consensus motifs may fall within a given exonic region, suggesting additive or competitive functions between bound splicing factors to allow for fine-tuning (Liu, Zhang et al. 1998). The importance of this mechanism can be seen in the differential recruitment of ASF/SF2 and SC35 to their selective binding motifs. These two SR proteins recognize different consensus motifs within the pre-mRNA, with ASF/SF2, but not SC35, consensus motifs showing high homology to ESE sequences. As such, there is little cross- reactivity between consensus sites and SR protein binding. This differential recruitment of splicing factors results in ASF/SF2-binding motifs displaying ESE functions while SC35-binding motifs do not. Therefore, the presence or absence of various consensus binding motifs differentially regulates the commitment of an exon to alternative splicing through the selective recruitment of splicing factors (R

Tacke 1995, Gallego 1997). The presence of consensus binding motifs for

99 tissue-specific splicing factors, such as NOVA family proteins, adds an additional layer of complexity to the differential splicing mechanisms facilitated by cis-acting enhancer and silencer elements (Jensen, Dredge et al. 2000, Matlin, Clark et al.

2005).

Given the mechanism through which splicing enhancer and silencer sequences facilitate splice site usage, it is not surprising that these cis-acting elements are position-dependent and require close proximity to the site they regulate. Altering the location of ESEs, ISEs, ESSs, and ISSs can result in the recruitment of different splicing factors. The specificity of splicing factor recruitment is essential for determining the splicing activity conferred by the enhancer or silencer sequence, as certain transcription factors cannot facilitate enhancer/silencer activity, as previously stated for SC35. Therefore, translocation or permutation of these sequences may completely alter or abolish their function, as is evident in the diminished hnRNP H binding of the 31G>A OPRM1 SNP (Liu,

Zhang et al. 1998, Lopez 1998, Shi, Hui et al. 2002, Zheng 2004, Sanford, Ellis et al. 2005, Xu, Lu et al. 2014). While this has been particularly useful for the identification and function of regulatory sequence elements in vitro (Liu, Zhang et al. 1998, Smith, Zhang et al. 2006, Erkelenz, Mueller et al. 2013), the translocation and permutation of these motifs within the chromosomal DNA in order to generate pre-mRNA transcripts with differentially localized regulatory sequence elements is exceptionally rare; however, the principal of position- dependent regulatory sequence elements can be seen through other permutations of the pre-mRNA. For example, an ASF/SF2 binding motif localized

100 upstream of a 3’ splice site within L1 adenovirus transcripts function to repress splicing activity upon recruitment due to the steric inhibition of spliceosome A complex formation. This suggests that this ASF/SF2 binding motif, which usually functions as an ESE when localized downstream of a 3’ splice site, instead functions as an ISS when localized upstream of the same splice site (Wang,

Takagaki et al. 1996, Black 2003, Matlin, Clark et al. 2005, Shepard and Hertel

2009). In support of this, binding sites for several other splicing factors have also been found to act as either enhancer or silencer sequences depending on their location (Chen and Manley 2009).

Compounding the significance of position-dependent regulatory sequences is the fact that RNA transcripts form highly stable secondary and tertiary structures. In vivo, RNA-protein interactions prevent mRNAs from folding into stable secondary structures and, due to the co-localization of transcription and splicing machinery, pre-mRNA transcripts only have a limited time to form secondary structures as they come off the RNA polymerase II enzyme before interacting with splicing factors. It has been found that the binding of several SR proteins and hnRNPs depends on RNA secondary structures as well as on consensus binding motifs. Two mechanisms have been proposed to explain the role of RNA secondary structure on the capacity of splicing enhancer and silencer sequences to bind their target splicing factors. The first mechanism proposes simply that secondary structures limit the accessibility of splicing enhancer and silencer sequences to splicing factors. Secondary structure may, therefore, promote exon skipping due to the failure of splicing factors to bind

101 regulatory sequences and facilitate exon- and intron-definition. Therefore, localization of ESE, ISE, ESS, and ISS sequences to areas subject to secondary structure formation is highly unfavorable. The second mechanism proposes a more indirect method whereby RNA secondary structures, which do not directly contain splicing enhancer and silencer sequences, regulate splicing activity by varying the relative distance between splice sites. By altering the distance between 3’ and 5’ splice sites, RNA secondary structure can either enhance or diminish the cross-exon and cross-intronic interactions between ESE-, ISE-,

ESS-, and ISS-bound splicing factors necessary for splicing catalysis. Although in vivo reports of these mechanisms are limited, it is becoming more evident that many (if not most) pre-mRNA transcripts contain select regions subject to folding into well-defined secondary structures (Caceres and Kornblihtt 2002, Buratti and

Baralle 2004, Hui 2009). As such, differences in secondary structure folding may selectively alter the splicing patterns of specific pre-mRNA transcripts due to changes in the accessibility and interactions of cis-acting regulatory elements and, furthermore, may account for differences in splicing patterns seen in vivo and in vitro (Buratti and Baralle 2004, Chen and Manley 2009).

4.3.4 Concentration-dependent activity and antagonism

Given that mechanisms of constitutive and alternative splicing regulation involve the dynamic phosphorylation of auxiliary splicing proteins, the translocation of these proteins within subcellular compartments, and the interaction of these proteins with additional trans-acting factors and cis-acting sequence elements, three additional regulatory conditions are probable. First, 102 given that auxiliary proteins are actively shuttled between cytoplasmic and nuclear localization, their relative concentration must also factor into their activity.

Second, because some cis-acting factors and spliceosome proteins interact with multiple members of SR protein and hnRNP families as part of the larger spliceosome complex, a level of competition is likely present between these auxiliary proteins. Third, assuming that auxiliary proteins compete for incorporation into the spliceosome and that the proximity and localization of cis- acting elements may cause steric hindrance of spliceosome binding, the relative concentrations of auxiliary proteins, specifically SR proteins and hnRNPs, serve to antagonize the activity of one another. Over the past few decades it has become evident that all of these conditions are prevalent in the co-transcriptional splicing environment and, as such, contribute heavily to the selection or skipping of intrinsically weak splice sites in alternative splicing.

The activity of SR and hnRNP proteins is often antagonized by the activity of one another (Fu 1995, Hanamura, Caceres et al. 1998, Blencowe, Bowman et al. 1999, Biamonti and Caceres 2009). This is particularly so for the archetypal member of each protein family, ASF/SF2 and hnRNP A1. As previously described, ASF/SF2 is an essential splicing factor that regulates 5’ splice site selection in constitutive splicing; however, it also participates in alternative splicing. In pre-mRNA transcripts with multiple, competing 5’ splice sites,

ASF/SF2, through the selective binding of ESE sequence elements, facilitates the selection of proximal 5’ splice sites in a concentration-dependent manner.

This reflects the high affinity ASF/SF2 has for recruiting U1 snRNP, which

103 promotes spliceosome assembly around otherwise intrinsically weak 5’ splice sites. However, ASF/SF2-mediated recruitment of U2AF complex to the 3’ splice site may also be involved in 5’ splice site selection, as the U2 snRNP-bound sequence adenosine is covalently bound to the upstream 5’ intron terminus of the intermediate lariat during catalysis of the spliceosome B complex. Despite the fact that increased concentrations of ASF/SF2 facilitate proximal 5’ splice site selection and prevents inappropriate exon-skipping, excessive overexpression of

ASF/SF2 can have an overall inhibitory effect on 5’ splice sites of similar strength, although the constitutive 5’ splice site is still used efficiently. This suggests that simultaneous recognition of 5’ splice sites in close proximity results in the occlusion of spliceosome assembly. As such, 5’ splice sites occur in various strengths, and selection by ASF/SF2 occurs within a hierarchy of splice site strength and proximity (Krainer, Conway et al. 1990, Fu, Mayeda et al. 1992,

Mayeda and Krainer 1992, Caceres, Stamm et al. 1994, Zuo and Manley 1994,

Wang and Manley 1995, Kramer 1996, Hanamura, Caceres et al. 1998,

Blencowe, Bowman et al. 1999, Eperon, Makarova et al. 2000).

Opposite SR proteins, hnRNP family proteins, like hnRNP A1, typically bind ESS sequences to facilitate the selection of distal or intrinsically strong 5’ splice sites with high affinity for U1 snHRP binding. The mechanism of hnRNP function is typically explained as antagonism of SR protein function through competitive binding to pre-mRNA, causing a steric block in the assembly of spliceosome proteins at an adjacent site. Binding of hnRNP A1 is more indiscriminant than ASF/SF2 binding; however, hnRNP A1 is still selectively

104 concentrated around 5’ splice sites. As such, hnRNP A1 interferes with U1 snRNP indirectly by competitively binding the pre-mRNA transcript. Alternatively, as per the ESE neutralization model of alternative splicing, ASF/SF2 function can be described as the inhibition of constitutive hnRNP A1 binding. Given this dual antagonism, the nuclear ratio of ASF/SF2 to hnRNP A1 is critical for the regulation of proximal and distal splice site selection. Changes in this ratio will ultimately lead to differences in splicing patters, exemplified by tissue-specific splicing patterns correlating with different ratios of ASF/SF2 to hnRNP A1

(Mayeda and Krainer 1992, Cáceres and Krainer 1993, Mayeda, Helfman et al.

1993, Caceres, Stamm et al. 1994, Fu 1995, Hanamura, Caceres et al. 1998,

Bai, Lee et al. 1999, Blencowe, Bowman et al. 1999, Eperon, Makarova et al.

2000, Hastings and Krainer 2001, Caceres and Kornblihtt 2002, Black 2003,

Matlin, Clark et al. 2005, Sanford, Ellis et al. 2005, House and Lynch 2008, Long and Caceres 2009). Therefore, factors such as HDAC and DNMT inhibitors

(Piotrowska and Jagodzinski 2009), miRNAs (Wu, Sun et al. 2010, Meseguer,

Mudduluru et al. 2011), pro-inflammatory cytokines like TNFα (Xiong, Shaibani et al. 2006), and tumorigenesis (Karni, de Stanchina et al. 2007), which alter the ratio of SR proteins, like ASF/SF2, to hnRNPs, like hnRNP A1, by changes in either subcellular localization or overall expression, will have a substantial impact on splicing patters through the selective inclusion or exclusion of alternative splice sites. As such, opioids may also impact splicing mechanisms through the alteration of SR and hnRNP protein concentration and subcellular localization, as chronic and acute morphine treatments were found to, respectively, increase and

105 decrease expression of the SR protein Tra2β in the rat locus coerulus through an unknown mechanism (Li, Li et al. 2013). Furthermore, morphine treatment was found to increase both the cytoplasmic and nuclear expression of hnRNP K protein, but not mRNA, in rat primary cortical neurons and the HEK 293 cell line, in a time-dependent and dose-dependent manner through a mechanism involving increased internal ribosome entry segment (IRES)-mediated hnRNP K translation (Lee, Chao et al. 2014). Accordingly, this alteration in SR and hnRNP protein expression is responsible for the morphine-mediated alternative splicing of certain proteins; however, a direct mechanism for morphine-mediated alternative splicing of the MOR involving changes in auxiliary splicing factors has not been identified.

4.4 Autoregulation of HIV viral genome constitutive and alternative splicing

Lentiviruses such as HIV belong to the larger viral family known as retroviruses. Members of the retroviral family are categorized as containing a viral genome composed of a single stranded RNA transcript that is reverse- transcribed before integrating into the host genome. As such, HIV begins its replication cycle as a nascent pre-mRNA transcript and must utilize host RNA processing mechanisms to facilitate the transcription and translation of virally encoded proteins, including reverse transcriptase (Ances and Ellis 2007). Initial transcription of the HIV proviral genome produces short RNA transcripts due to inefficient elongation by the recruited RNA polymerase II enzyme. Although inefficient, this process results in the synthesis of full length viral transcripts in

106 low abundance, which allows for the subsequent translation of Tat, a small protein of variable length between approximately 86 and 101 amino acids that localizes mainly to the nucleus and nucleolus. A second, late phase of productive and processive HIV proviral transcription is then initiated by the HIV promoter region, named the long terminal repeat (LTR), and is Tat-dependent, although exact mechanisms of Tat-mediated transcription are unclear. Additionally, Tat interacts with the trans-activation response (TAR) element within HIV viral RNA and enhances the initiation of reverse transcription. Therefore, HIV utilizes Tat in order to favorably regulate proviral gene expression and efficient reverse transcription (Jeang 1996, Li, Li et al. 2009). It follows then that HIV is also able to employ mechanisms to favorably regulate the host RNA processing mechanisms, including co-transcriptional splicing, in order to facilitate viral replication. Indeed, studies have found that alternative splicing of the HIV viral genome is essential for the transition between early- and late-stage viral replication. Characterization of the splicing patterns of HIV and the mechanisms utilized to facilitate said splicing has not only lead to a more thorough understanding of the HIV viral life cycle but has highlighted new targets for HIV therapeutics.

The integrated HIV viral genome transcribes a single pre-mRNA from which all viral protein-encoding mRNAs are derived. The HIV genome is, therefore, extensively spliced, generating more than 40 different mRNA transcripts. This is due to the presence of multiple constitutive and alternative 3’ and 5’ splice sites

(Purcell and Martin 1993, Tange and Kjems 2001, Caputi, Freund et al. 2004,

107 Long and Caceres 2009). It is now understood that all mRNAs encoding HIV viral proteins are generated by the alternative utilization of four 5’ splice sites and nine

3’ splice sites located within the full-length HIV mRNA. Adding to this complexity is the fact that several gene products, including the gag and pol viral proteins, are translated from unspliced or partially spliced viral mRNAs. This is necessary, given that genes encoding various viral proteins often overlap and exon- and intron-definition is dependent on the reading frame of the gene. For example, gag- and pol- encoding genes are located within the intronic region of pre-mRNA transcripts that encode various HIV regulatory proteins. Therefore, partial splicing of HIV mRNA allows for these transcripts to be polycistronic. Nuclear export of partially spliced or unspliced viral RNA is facilitated by the HIV viral regulatory protein Rev, as incompletely spliced pre-mRNA is often targeted for degradation by nonsense-mediated decay (NMD) pathways. Approximately 50% of viral pre- mRNA is exported in this manner (Purcell and Martin 1993, Caputi, Freund et al.

2004, Ropers, Ayadi et al. 2004). In an oversimplification of HIV splicing patterns, the varying degrees of splicing generate mRNA transcripts for specific HIV viral proteins. Completely spliced mRNAs, approximately 2kb in size, encode regulatory proteins, such as Tat and Rev, as well as accessory proteins, such as

Nef and Vpr. Incompletely spliced transcripts, approximately 4kb in size, are bicistronic, simultaneous encoding Env glycoproteins and Vpu. The unspliced

HIV pre-mRNA, approximately 9kb in size, encodes the Gag and Gag-Pol polyproteins while also serving as the pregenome for Gag assembly (Jacquenet,

Decimo et al. 2005, Jablonski and Caputi 2009, Tazi, Bakkour et al. 2010). In

108 addition to generating polycistronic RNA transcripts, the capacity of HIV to export unspliced pre-mRNA ultimately allows for the packaging of the full-length HIV viral genome RNA into virions during late stage infection.

The splicing pattern of HIV is determined by a hierarchy of 3’ and 5’ splice sites, with sites facilitating the exclusion of non-coding exons generally being favored (Purcell and Martin 1993, Caputi, Freund et al. 2004). Given that alternative splicing of HIV is dependent on the host cell splicing machinery, mechanisms facilitating alternative 3’ and 5’ splice site selection are similar to those found in eukaryotic cells. As with eukaryotic pre-mRNA transcripts, U1 snRNP binding to the 5’ splice site initiates spliceosome E complex formation, which is essential for both maintaining viral mRNA stability and facilitating export of incompletely spliced transcripts. Utilization of HIV 5’ splice sites depends primarily on their intrinsic ability the facilitate U1 snRNA binding, as these sites are relatively homologous between HIV and eukaryotic mRNAs. However, HIV 3’ splice sites, located primarily within the center of the genomic pre-mRNA transcripts, are intrinsically weak. This is due to multiple factors, including a relatively short PPT sequence, which is interrupted by purines, and a non- canonical branch-point sequence, which lacks the conserved adenosine residue.

Furthermore, their accessibility is sometimes hindered by RNA secondary structure. As such, utilization of these suboptimal 3’ splice sites is mediated by the presence of various enhancer or silencer sequences that, as discussed in section 4.3.3, recruit various auxiliary splicing proteins to the viral mRNA to enhance or inhibit binding of U1 snRNP or the U2AF complex. Several ESS

109 sequences have been found to bind hnRNPs, specifically hnRNP A1 and hnHRNP H, to decrease utilization of the second, third, and seventh 3’ splice site.

Antagonizing this inhibition is the presence of multiple ESE sequences that recruit various SR proteins to enhance splice site usage. Interestingly, certain

ESE sequences are bidirectional, promoting the recognition of both upstream and downstream splice sites. This is the case for the GAR ESE sequence element located upstream of the fourth recognized 5’ splice site in the HIV genomic mRNA. Activation of this sequence element is required for proper splicing of mRNA transcripts encoding for the HIV viral proteins Tat, Rev, and

Nef as well as for partially spliced transcripts. Additional ESE, ESS, and ISS regulatory sequences have also been identified and the collective activity of these domains determines splice site selection (Tange and Kjems 2001, Caputi,

Freund et al. 2004, Ropers, Ayadi et al. 2004, Jacquenet, Decimo et al. 2005,

Asang, Hauber et al. 2008, Jablonski and Caputi 2009, Suptawiwat, Boonarkart et al. 2010, Tazi, Bakkour et al. 2010). Therefore, factors that affect the activation of ESE, ESS, and ISS sequence elements will alter the selection of competing splice sites, disrupting the ratio of HIV mRNA and viral proteins, ultimately resulting in changes in HIV replication and infectivity.

Multiple auxiliary splicing proteins, including SRp40, SRp75, 9G8, and

SC35 have been shown to selectively bind ESE elements within the HIV pre- mRNA transcript to promote splice site usage. These proteins were found to target specific splice sites and, in some cases, have opposing effects of HIV viral genome activity. Of the known auxiliary splicing factors, ASF/SF2 is by far the

110 most commonly recruited and is requisite for constitutive splicing (Tange and

Kjems 2001, Caputi, Freund et al. 2004, Jacquenet, Decimo et al. 2005, Long and Caceres 2009). As such, ASF/SF2 is now understood to be an essential splicing factor for HIV viral replication as it is required for the proper splicing of

HIV regulatory proteins, such as Tat (Fu 1993). Interestingly, the effect of

ASF/SF2 in the pre-mRNA splicing of HIV transcripts in highly variable. For example, in vitro studies found that efficient splicing of HIV pre-mRNA transcripts encoding Tat required abundant ASF/SF2 expression; however, in vivo splicing of the same transcript was enhanced by ASF/SF2 depletion (Wang, Xiao et al.

1998). Additionally, while ASF/SF2 overexpression specifically increased expression of certain mRNA transcripts, such as those encoding Vpr, other transcripts, such as those encoding Nef, where decreased. Overall, SR proteins were shown to reduce HIV genomic RNA expression. This is in line with the observation that SR proteins are required to facilitate mRNA expression in early

HIV infection but can inhibit late stages of HIV replication (Ropers, Ayadi et al.

2004, Jacquenet, Decimo et al. 2005, Jablonski and Caputi 2009). Given that fluctuations in the concentration of ASF/SF2, as well as other SR proteins, impacts HIV mRNA splicing (Krainer, Conway et al. 1990), it is not surprising that

HIV utilizes mechanisms to actively regulate SR protein levels, both spatially and temporally, to ensure the proper balance of fully-, partially-, and unspliced mRNA transcripts. Accordingly, HIV infection has been found to alter the expression of several SR proteins, including SC35 (Maldarelli, Xiang et al. 1998, Dowling,

Nasr-Esfahani et al. 2008), 9G8 (Ryo, Suzuki et al. 2000), SRp75, SRp55,

111 SRp40, SRp30c, SRp20, and ASF/SF2 (Fukuhara, Hosoya et al. 2006), as well as several hnRNPs, including hnRNP A1 and hnRNP H (Dowling, Nasr-Esfahani et al. 2008, Monette, Ajamian et al. 2009). HIV-mediated variations in auxiliary splicing factor expression exhibit both spatial regulation, with the nuclear and cytoplasmic proportions of certain factors being specifically altered (Dowling,

Nasr-Esfahani et al. 2008, Monette, Ajamian et al. 2009), and temporal regulation, with stark differences found between early and late infection (Dowling,

Nasr-Esfahani et al. 2008). This spatial and temporal regulation is facilitated by transcripts expressed during late-stage HIV infection, such as Tat, thereby titrating SR protein expression as infection progresses from early to late stage

(Ropers, Ayadi et al. 2004, Jacquenet, Decimo et al. 2005, Fukuhara, Hosoya et al. 2006, Asang, Hauber et al. 2008, Dowling, Nasr-Esfahani et al. 2008). New

HIV therapeutics seek to target these unknown regulatory mechanisms in order to disrupt HIV viral replication, as HIV viral production is dependent on proper alternative splicing. One such therapeutic, an indole derivative known as IDC16, interferes with SF2/ASF interactions with ESE elements and, as a result, suppresses the production of key viral proteins, thereby compromising HIV-1 replication and assembly into virions (Bakkour, Lin et al. 2007, Keriel, Mahuteau-

Betzer et al. 2009, Long and Caceres 2009).

112 4.5 Results

4.5.1 Morphine-mediated increases in ASF/SF2 protein is attenuated by Tat

The prototypical SR family member protein ASF/SF2 serves a unique and critical role in both constitutive and alternative splicing by facilitating splice site selection and subsequent spliceosome assembly. As such, fluctuations in

ASF/SF2 subcellular localization and concentration are sufficient to alter the splicing patterns of alternatively spliced mRNAs. Additionally, the functions of

ASF/SF2 cannot be compensated for by other splicing factors, suggesting that although additional splicing factors may also contribute to alternative splicing mechanisms, ASF/SF2 is a requisite factor. Therefore, regulation of ASF/SF2 expression is a major mechanism through which splicing patterns are determined. Given that morphine treatment of SH-SY5Y was found to increase expression of the MOR isoform MOR-1X and that this morphine-mediated increase was attenuated by concomitant rTat treatment, as well as the fact that

HIV infection is known to alter the expression of multiple auxiliary splicing factors

(Ryo, Suzuki et al. 2000, Fukuhara, Hosoya et al. 2006, Dowling, Nasr-Esfahani et al. 2008, Monette, Ajamian et al. 2009), this study sought to determine if the mechanisms through which morphine and rTat regulate MOR-1X expression involve fluctuations in ASF/SF2 protein expression. Indeed, results showed that 1 hour treatment with either 0.1µM morphine (Figure 4.1, lane 2) or 1µM morphine

(Figure 4.1, lane 3) increased ASF/SF2 protein expression in SH-SY5Y cells nearly, whereas treatment with 1nM rTat for 24 hours did not significantly alter

ASF/SF2 protein expression (Figure 4.1, lane 4). Furthermore, treatment with 113 1nM rTat 24 hours prior to 1 hour treatment with either 0.1µM morphine (Figure

4.1, lane 5) or 1µM morphine (Figure 4.1, lane 6) attenuated the morphine- mediated increase in ASF/SF2 protein expression. As expected, the pattern of regulation exhibited here for ASF/SF2 mirrors that seen for MOR-1X mRNA expression.

400

350 *

300 *

250

200

150

100

50 ASF/SF2 Protein Expression (% Control) ASF/SF2 Expression Protein

0 1 2 3 4 5 6 7 8 9 10 11 12 33kDa ASF/SF2 50kDa β-Tubulin - 0.1 1 - 0.1 1 Morphine (µM) - - - 1 1 1 rTat (nM)

Figure 4.1: ASF/SF2 protein expression in SH-SY5Y following opioid and

Tat treatments. ASF/SF2 protein expression from untreated SH-SY5Y cells

(lane 1), SH-SY5Y cells treated for 1 hour with 0.1µM morphine (lane 2) or 1µM morphine (lane 3), SH-SY5Y cells treated for 24 hours with 1nM rTat (lane 4), and SH-SY5Y cells pre-treated with 1nM Tat for 24 hours then treated for 1 hour with 0.1µM morphine (lane 5) or 1µM morphine (lane 6) was analyzed by

Western blotting and quantified using the Li-Cor Odyssey CLx Infrared Imaging

System (mean ± SEM; * = p ≤ 0.05).

4.5.2 Overexpression of ASF/SF2 increases MOR-1X mRNA expression

Given that morphine and rTat were both found to alter ASF/SF2 protein expression in a manner that correlates with morphine- and Tat-mediated changes in MOR-1X expression, it is plausible that that splicing patterns of the 114 MOR are determined, in part, by fluctuations in ASF/SF2 concentration. As such, this study next sought to determine whether ASF/SF2 was directly involved in the morphine-mediated alternative slicing of the MOR-1X isoform. However, examination of the functional significance of ASF/SF2 expression in MOR splicing is complicated by the fact that siRNA knockdowns and knockouts of

ASF/SF2 proved to be lethal in this and previous studies (Caceres and Kornblihtt

2002). Therefore, ASF/SF2 was overexpressed in SH-SY5Y cells using a pCGT7-SF2/ASF-FL expression plasmid. Overexpression of ASF/SF2 was confirmed by Western blot using antibodies against both the T7-Tag and total

ASF/SF2 (Figure 4.2, lane 3), although the band intensity of ASF/SF2 was unusually strong as compared to that of the T7-Tag and ran at a slightly lower molecular weight. This may simply be an artifact of excessive protein expression due to transient transfection, resulting in protein overloading and discrepancies between the different exposures, as the ASF/SF2 exposure required adjustment in order to also show the significantly lower expression of ASF/SF2 protein in untreated and morphine treated samples; however, given the differences in band sizes, this may also indicate autoregulation of ASF/SF2 expression and splicing, as has previously been found to occur (Sun, Zhang et al. 2010). Regardless of this this discrepancy, treatment of SH-SY5Y cells with 0.1µM morphine for 1 hour increased both ASF/SF2 protein and MOR-1X mRNA expression levels as expected (Figure 4.2, lane 2). Furthermore, as predicted, overexpression of

ASF/SF2 protein was sufficient to increase MOR-1X mRNA levels in the absence of morphine (Figure 4.2, lane 3). Therefore, increased expression of ASF/SF2

115 protein appears to directly promote the expression of MOR-1X mRNA in SH-

SY5Y cells.

200

180

160

140

120

100

80

60

40

MOR-1X Signal Intensity (% Control) MOR-1X Signal 20

0 1 2 3 4 5 6 7 8 9 10 11 12 MOR-1X

GAPDH 33kDa ASF/SF2

33kDa T7-Tag ASF/SF2 50kDa β-Tubulin

- 0.1 - Morphine (µM) - - + T7-ASF/SF2

Figure 4.2: Overexpression of ASF/SF2 protein increases MOR-1X mRNA.

Protein and cytoplasmic RNA extracts from untreated SH-SY5Y cells (lane 1),

SH-SY5Y cells treated for 1 hour with 0.1µM morphine (lane 2) or transfected with pCGT7-SF2/ASF-FL (lane 3) were analyzed, respectively, by Western blotting using the Li-Cor Odyssey CLx Infrared Imaging System or by two-step, semi-quantitative RT-PCR and gel electrophoresis. Expression of the pCGT7-

SF2/ASF-FL plasmid was determined using specific antibodies against the T7- tag as well as total ASF/SF2 levels. Semi-quantitative analysis was performed using the Image J software to determine normalized band intensities.

4.5.3 Absence of SFRS1 transcriptional regulation by morphine and Tat

Transcriptional and post-transcriptional regulation of protein expression is often mediated through alterations in gene activity and mRNA transcript expression, respectively. As such, changes in the activity of the ASF/SF2 encoding gene, SFRS1, and in the abundance of ASF/SF2 mRNA were 116 examined in order to determine if the mechanism through which morphine regulates ASF/SF2 expression involves transcriptional and post-transcriptional regulation. SFRS1 promoter activity in SH-SY5Y cells was determined by CAT assay analysis using transfected pBLCAT3-pSF2 (-400 to +47) and pBLCAT3- pSF2 (-200 to +47) reporter constructs. Results found that the activity of the -200 and -400 promoter regions of SFRS1 was not significantly altered following a 1 hour treatment with either 0.1µM morphine (Figure 4.3A, lane 2) or 1µM morphine (Figure 4.3A, lane 3). Likewise, there were no significant changes in

ASF/SF2 RNA following morphine treatment (Figure 4.3B, lanes 2-3).

Furthermore, treatment with 1nM rTat for 24 hours (Figure 4.3B, lane 4) and treatment with 1nM rTat 24 hours prior to 1 hour treatment with either 0.1µM morphine (Figure 4.3B, lane 5) or 1µM morphine (Figure 4.3B, lane 6) did not significantly alter ASF/SF2 RNA expression. It should be noted, however, that a small, but statistically insignificant, dose-dependent increase in the activity of the

-400 SFRS1 promoter region (Figure 4.3A) following morphine treatment as well as slight increases and decreases in ASF/SF2 RNA following a 1 hour treatment with 0.1µM morphine (Figure 4.3B, lane 2) and concominant morphine and rTat treatments (Figure 4.3B, lanes 5-6), respectively, were observed and, as such, more sensitive measures may elucidate mild transcriptional regulatory mechanisms. Therefore, the mechanism through which morphine and rTat mediate ASF/SF2 protein expression remains unclear but appears to be independent of transcriptional regulation and correlates with MOR-1X mRNA expression. 117 160 160 140 140 120 120 100 100 80 A. -200 80 160 -200 -400 60 -400 60 140 40 40 120 20 20 100 0 1 2 3 1 2 3 0 1 80 2 3 1 2 3 60

40

20 ASF/SF2 Promoter Activity (% Control)

0 1 2 3 4 5 6 7 8 9 - 0.1 1 Morphine (µM)

B. ASF/SF2 GAPDH 1 2 3 4 5 6 - 0.1 1 - 0.1 1 Morphine (µM) - - - 1 1 1 rTat (nM)

Figure 4.3: Morphine and Tat do not alter SFRS1 promoter activity or

ASF/SF2 RNA expression. A. SFRS1 promoter activity was measured by CAT reporter analysis using lysates from pBLCAT3-pSF2 (-400 to +47)- or pBLCAT3- pSF2 (-200 to +47)-transfected SH-SY5Y cells treated for 1 hour with either

0.1µM morphine (lane 2) or 1µM morphine (lane 3). Samples were first used in liquid chromatography and exposed to radiographic film in order to assess the migration of unacetyled, mono-acetylated, and di-acetylated chloramphenicol

(blot). Mono- and di-acetylated chloramphenicol and unacetyled chloramphenicol were quantitated separately using liquid scintillation counting. Promoter activity was determined by the abundance of di- and mono-acetylated chloramphenicol relative to the unacetyled chloramphenicol (graph; mean ± SEM). B. ASF/SF2 mRNA expression from untreated SH-SY5Y cells (lane 1), SH-SY5Y cells treated for 1 hour with 0.1µM morphine (lane 2) or 1µM morphine (lane 3), SH-SY5Y cells treated for 24 hours with 1nM rTat (lane 4), and SH-SY5Y cells pre-treated with 1nM Tat for 24 hours then treated for 1 hour with 0.1µM morphine (lane 5) or

118 1µM morphine (lane 6) was analyzed by two-step RT-PCR and gel electrophoresis.

4.6 Discussion

Both constitutive and alternative splicing of pre-mRNA transcripts is initiated by the spliceosome, a large, fluid ribonucleoprotein complex comprised of various snRNPs and numerous non-snRNP splicing factors. These trans-acting factors interact with cis-acting elements, such as 3’ and 5’ splice sites and exon splicing enhancers and silencers, within the pre-mRNA template to selectively incorporate or exclude intronic and exonic regions in the mature mRNA. As such, the generation of mRNA isoforms via alternative splicing events is determined by the relative activity of and interaction between cis- and trans-acting factors; however, considering the difficulty of altering cis-acting factors in vivo, alternative splicing patterns are determined primarily through the modification of trans-acting spliceosome proteins, specifically SR proteins and hnRNPs, via phosphorylation as well as the increased expression of spliceosome proteins both overall and relative to competing factors. Initial spliceosome assembly involves the incorporation of two SR proteins, ASF/SF2 and SC35, and commits the pre- mRNA to the splicing pathway. Initially, it was assumed that ASF/SF2 and SC35 were redundant due to their high degree of homology in both structure and function; however, it has since been revealed that lethality of ASF/SF2 knockouts cannot be rescued by SC35 or other SR protein splicing factors. As such,

ASF/SF2 is regarded as an essential splicing factor in both constitutive and alternative splicing. 119 Given the importance of ASF/SF2 is both constitutive and alternative splicing, this study sought to determine whether the mechanisms through which morphine and rTat alter the expression of MOR-1X involve the regulation of

ASF/SF2 expression and if this regulation occurs at a transcriptional or post- transcriptional level. Results found that regulation of ASF/SF2 protein expression in SH-SY5Y cells by morphine and rTat, both independently and concomitantly, mirrored that seen for MOR-1X expression, with 1 hour treatments of 0.1µM morphine (Figure 4.1, lane 2) and 1µM morphine (Figure 4.1, lane 3) significantly increasing ASF/SF2 protein expression while pre-treatment with 1nM rTat for 24 hours attenuated morphine-mediated increases (Figure 4.1, lanes 5-6). This suggests that the mechanism through which morphine and rTat regulate MOR-

1X mRNA expression in SH-SY5Y cells involves fluctuations in ASF/SF2 expression. This proposed mechanism is further supported by the finding that overexpression of ASF/SF2 in SH-SY5Y cells is sufficient to increase MOR-1X mRNA expression in the absence of morphine (Figure 4.2, lane 3). The role of

ASF/SF2 overexpression in the up-regulation of MOR-1X is not entirely unexpected, as ASF/SF2 facilitates the selection of proximal 5’ splice sites in a concentration-dependent manner and the 5’ splice site of alternative exon X is proximal to that of the constitutive exon 4 in the MOR pre-mRNA transcript.

Therefore, it is likely that levels of ASF/SF2 constitutively expressed in SH-SY5Y cells are not sufficient to readily promote U1 snRNP recruitment and spliceosome assembly around the intrinsically weak exon X 5’ splice site, but as ASF/SF2 levels are increased with morphine treatment, selection of the exon X 5’ splice 120 site is favored. Furthermore, the role of Tat in attenuating morphine-mediated increases in ASF/SF2 expression is not entirely unexpected. Previous studies have found that early HIV infection is correlated with increased SR protein expression and decreased hnRNP expression, which favors the alternative splicing of the early viral protein Tat. During late stage viral replication, when Tat is abundant, the splicing profile changes to favor inhibition of Tat splicing

(Dowling, Nasr-Esfahani et al. 2008). This temporal shift in the HIV-mediated regulation of auxiliary splicing factor expression may involve an autoregulatory feedback loop generated by abundant Tat expression, as overexpression of Tat was found to decrease SR protein expression, specifically SC35 (Fukuhara,

Hosoya et al. 2006).

The results presented here suggest a mechanism by which morphine and concomitant HIV regulate MOR splicing specificity, particularly of the MOR-1X isoform, through the inverse regulation of auxiliary splicing factors, specifically

ASF/SF2. This is particularly important, as previous studies have only described the phenomena of altered MOR splicing pattern following opioid treatment and

HIV infection and have not suggested a mechanism through which this is mediated. Furthermore, neither exacerbation nor attenuation of morphine- mediated effects on splicing by HIV infection has previously been described.

Unfortunately, the mechanism through which morphine and rTat regulate

ASF/SF2 expression is still unclear, although it appears to be independent of

SFRS1 promoter activity (Figure 4.3A). A potential mechanism may involve inverse regulation in ASF/SF2 mRNA expression (Figure 4.3B); however,

121 additional mechanisms, including fluctuations in ASF/SF2 phosphorylation, ubiquitination, and proteasomal degradation as well as the expression of

ASF/SF2-targeting miRNA, cannot be excluded. It is also highly likely that morphine- and HIV-mediated effects on ASF/SF2 protein expression entail some level of translational regulation, which consists of a cap-dependent mechanism facilitated by eukaryotic initiation factor 4F (eIF4F)-mediated binding of ribosomes to the mRNA 5’ UTR and a cap-independent mechanism involving direct ribosomal binding to internal ribosome entry site (IRES) within the mRNA

(Gingras, Raught et al. 1999, Holcik, Sonenberg et al. 2000, Pyronnet, Pradayrol et al. 2000, Hellen and Sarnow 2001, Komar and Hatzoglou 2005). Multiple signaling pathways, which overlap with known opioid signaling cascades

(discussed in section 5.2), have been found to initiate or inhibit both cap- dependent and –independent translation, including Akt/PI3K, PKC, Ras , and several MAPK pathways (Gingras, Kennedy et al. 1998, Gingras, Raught et al.

1999). Furthermore, previous studies have found that internal translation contributes to morphine-mediated increases in hnRNP K (Lee, Chao et al. 2014); however, whether morphine mediates increased expression of additional auxiliary splicing factors through a similar mechanism has not been investigated.

As such, more sensitive measures are needed to determine the exact transcriptional, post-transcriptional, and translational mechanisms through which morphine and concomitant HIV viral protein Tat regulate ASF/SF2 protein expression.

122 CHAPTER 5 – STRUCTURAL AND FUNCTIONAL VARIABILITY OF MOR

ISOFORMS

5.1 Structural Organization of Opioid Receptors

For the purpose of signal transduction across the cell membrane, cells utilize various membrane-spanning receptors that connect the extracellular and intracellular environments. One of the largest families of transmembrane receptors is the G-protein-coupled receptor (GPCR) family, with over 800 members identified in humans and an estimated 5% of the human genome committed to their synthesis. GPCRs are characterized by seven transmembrane helices conjoined by three alternating intracellular and extracellular domains, called loops, and terminate at either end in an extracellular N-terminus and a cytoplasmic C-terminus. As their name implies, these receptors are associated with intracellular proteins known as G proteins, the activation of which propagates GPCR signals intracellularly. However, in light of recent data suggesting that GPCRs can signal in a G protein-independent manner, they are also referred to as 7 transmembrane (7TM) receptors. A wide variety of physiological and environmental signals, including hormones, neurotransmitters, olfactory and gustatory stimuli, chemokines, and opioids, utilize GPCRs.

Additionally, GPCR ligands exhibit a wide variety in size, ranging from photons of light to large polypeptides. As such, GPCRs represent key targets of pharmaceuticals and currently represent the most targeted receptor class for clinical therapeutics (Devi 2001, Ferguson 2001, Perez and Karnik 2005, Choe,

Park et al. 2011). This is exemplified by the fact that hundreds of biotech 123 companies are currently working on the development of GPCR-targeting peptides within various physiological systems, with more than 70 GPCR-targeting therapeutic peptides on the market, over 150 peptides in clinical development, and a staggering 400 or more in advanced pre-clinical studies. Of the clinical trial targets for GPCR ligands, cancer accounts for 30%, metabolic disease and diagnostic tools account for 20% each, inflammatory processes encompass roughly 13%, CNS interactions comprise 12%, and virological functions represent the remaining 5% (Bellmann-Sickert and Beck-Sickinger 2010). Given this critical role in pharmaceutical drug discovery and development, and that opioid receptors represent a subfamily of GPCRs, understanding of the structural components of GPCRs that confer specific intracellular signaling is of critical importance.

5.1.1 The G protein-coupled receptor family

Within the thousands of G protein-coupled receptors identified throughout numerous species, a common tertiary structure has been found, consisting of an extracellular N-terminus, seven α-helical transmembrane domains that generate alternating intracellular and extracellular loops, and a cytoplasmic C-terminus.

Collectively, the GPCR family displays low sequence homology; however, short peptide sequences and single amino acid residues are conserved enough to afford a commonality in tertiary structure. The GPCR family is, therefore, subdivided into three distinct classes based on sequence similarity. Class B and

C receptors are characterized by their distinct N-terminal domains, which are relatively large and, in B class GPCRs, contain several well-conserved cysteine 124 residues. While both of these classes contain receptors of great physiological importance, collectively they represent only a small portion of the GPCR family

(Devi 2001). Class A GPCRs comprise the largest portion of the GPCR family and, accordingly, are the most studied. Receptors of this class are characterized by a palmitoylated cysteine residue in the C-terminal domain in addition to multiple conserved residues in their transmembrane domains, the key motifs being conserved D/ERY, XBBXXB, and NPXXY(X) sequences (B = basic, X = non-basic). These motifs are located within intracellular loops around the third, sixth, and seventh transmembrane domains, respectively (Devi 2001, Surratt and

Adams 2005, Choe, Park et al. 2011). Additionally, conserved cysteine residues are found within the second and third extracellular loops that form conserved disulfide bridges between transmembrane domains. Likewise, the extracellular N- terminal and intracellular C-terminal domains contain several conserved sites for glycosylation and phosphorylation, respectively (Perez and Karnik 2005, Surratt and Adams 2005).

The conservation of these regions within GPCRs across species suggests that they have a critical functional role in preserving receptor tertiary structure and/or facilitating agonist-mediated signaling. On the extracellular side, disulfide bridges formed by cysteine residues within loop structures facilitate proper protein folding and regulate the formation of high affinity binding sites. The

D/ERY motif, positioned between the third transmembrane domain and the second intracellular loop, is the most readily identified motif, having a conserved role in signaling by maintaining an inactive receptor conformation. This inactive

125 tertiary structure is maintained through ionic pairings between negatively charged residues within the D/ERY motif and surrounding positive residues. The role of negatively charged D/ERY residues in receptor activity is understood from mutational studies, which found that neutralization of this motif resulted in constitutive receptor activity. The XBBXXB and NPXXY(X) motifs, as well as a sixth transmembrane aromatic cluster motif with the loosely conserved sequence

FXXXWXXX(F), are also implicated in GPCR signaling regulation through their interaction with the D/ERY motif. Multiple models exist to explain the interactions between these motifs that facilitate the transition between inactive and active receptor conformations and the induction of G protein signaling pathways.

Collectively, these proposed models suggest that electrostatic interactions between these residues hold the receptor in an inactive tertiary structure. Upon agonist binding, conformational changes facilitate heterotrimeric G-protein binding of intracellular loops, primarily mediated by the XBBXXB motif. This disrupts the electrostatic interactions between the aforementioned structural motifs and results in a rotation of the third transmembrane domain relative to the sixth transmembrane domain, a process that is highly conserved among GPCRs

(Wang 1999, Seifert and Wenzel-Seifert 2002, Chaipatikul, Loh et al. 2003,

Waldhoer, Bartlett et al. 2004, Perez and Karnik 2005, Surratt and Adams 2005).

The subsequent conformational change converts the receptor from an inactive to an active state and facilitates additional structural changes, ultimately resulting in the activation of G protein coupling signaling cascades.

126 In addition to regulatory motifs within transmembrane and intracellular loop structures, GPCRs display a conserved cysteine residue in the proximal portion of the C-terminal domain; however, no conserved consensus motif has been identified for this site. Similar to residues within the intracellular loops, this cysteine is often palmitoylated, allowing for a portion of the C-terminal domain to insert into the intracellular side of the plasma membrane and generating an additional intracellular loop. Functionally, this cysteine has been implicated in the maturation and trafficking of GPCRs to the plasma membrane, as mutations have been shown to impair these processes. Furthermore, this residue may also function in GPCR signaling. For most GPCRs, this conserved cysteine exists within a dynamic state of palmitoylation and depalmitoylation, with the depalmitoylation state favoring kinase activity at the C-terminal domain. The proposed model for palmitoylated cysteine-mediated regulation of GPCR signaling suggests that upon receptor activation, G protein coupling increases the affinity for depalmitoylating enzymes, and the subsequent removal of the palmitate moiety allows for increased kinase activity at the C-terminal domain, increasing its phosphorylation state. This model is supported by evidence showing that mutation of the palmitoylated cysteine residue alters GPCR internalization and down-regulation (Surratt and Adams 2005, Petaja-Repo,

Hogue et al. 2006), both processes that commonly occur following GPCR agonist-stimulation and is often dependent on receptor phosphorylation

(discussed in section 5.3.2). Therefore, the major GPCR structural domains that contribute to G protein signaling are generally the second and third intracellular

127 loops as well as the C-terminal domain (Georgoussi, Merkouris et al. 1997,

Chaipatikul, Loh et al. 2003, Yeagle and Albert 2003). The biochemical properties of conserved amino acid motifs located within these regions facilitate the interactions necessary to transition the receptor between inactive and active conformations, thus regulating receptor signaling. As such, alterations in the primary sequence of these motifs are likely to alter GPCR functioning.

5.1.2 The opioid receptor family

The conventional opioid receptors belong to the Class A GPCR family and, as such, contain many of the key structural features necessary for receptor activation and signaling (Surratt and Adams 2005, Petaja-Repo, Hogue et al.

2006, Pasternak and Pan 2013). A D/ERY motif, expressed as DRY in opioid receptors, as well as a XBBXXB motif, expressed as LRRITR in opioid receptors, and a NPXXY motif, expressed as NPVLY in opioid receptors, have been identified within homologous regions of the various opioid receptor subtypes and have been shown to have functional significance in opioid-mediated signaling

(Chaipatikul, Loh et al. 2003, Waldhoer, Bartlett et al. 2004, Surratt and Adams

2005, Connor and Traynor 2010, Pasternak 2010). Accordingly, amino acid substitutions in the DRY and LRRITR motifs are associated receptor stabilization, modified G protein binding, and constitutive activity (Ferguson 2001, Li, Chen et al. 2001, Connor and Traynor 2010, Pasternak and Pan 2013) while substitutions in the NPXXY motif are associated with alterations in agonist binding, recruitment of G proteins and receptor kinases, and receptor endocytosis, trafficking, and recycling (Ferguson 2001, Wang, Loh et al. 2003). Likewise, the proximal C- 128 terminal domain of the MOR contains palmitoylated cysteine residues characteristic of Class A GPCRs. For MORs this palmitoylation is highly dynamic, with constitutive palmitoylation occurring during the translocation of newly synthesized receptors while agonist-mediated palmitoylation/depalmitoylation cycles likely regulate signaling transduction stimulated by opioid-bound receptors

(Minami and Satoh 1995, Surratt and Adams 2005, Petaja-Repo, Hogue et al.

2006). High affinity binding sites are generated by disulfide bonds between two conserved cysteine residues found in the first and second extracellular loops

(Minami and Satoh 1995). An aromatic cluster motif, with the conserved sequence FXXXWXXXH, has also been identified within the opioid receptor family. Although it is not the terminal phenylalanine often associated with the conserved GPCR motif, the histidine residue within opioid receptors is thought to function in a similar manner by facilitating agonist-mediated disruptions of electrostatic interactions, toggling the receptor between active and inactive states

(Surratt and Adams 2005). Collectively, these conserved structural motifs interact in such a way as to generate two broad regions critical in opioid receptor G protein signaling: the third intracellular loop and the C-terminal domain

(Georgoussi, Merkouris et al. 1997). Overall, opioid receptor subtypes are about

60% identical in their primary structure, with greater conservation of approximately 73-76% and 86-100% found in the transmembrane regions and intracellular loops, respectively, and lesser conservations of approximately 9-

10%, 14-72%, and 14-20% found in the N-terminal, extracellular loops, and C-

129 terminal, respectively (Minami and Satoh 1995, Wei, Law et al. 2004, Pasternak

2010).

The conserved structural motifs between opioid receptors and other Class

A GPCRs only serve to confer a similar tertiary structure and facilitate G protein coupling and signaling cascades. Additional motifs, unique to opioid receptors, complement these general GPCR family motifs in maintaining the active and inactive conformations of opioid receptors and confer specific opioid-mediated signaling mechanisms (Li, Huang et al. 2001). For example, selective binding of opioids is determined, in part, by the third extracellular loop of opioid receptors, with varying lengths altering the affinity for certain opioid agonists and antagonists. However, studies using chimeric µ/κ opioid receptors suggest that any change in structure between the center of the third intracellular loop to the C- terminal domain, specifically within MORs, may alter binding of selective opioid agonists (Xue, Chen et al. 1995). Accordingly, it is now understood that multiple structural motifs within opioid receptors interact with the chemical structure of opioid ligands to generate a selective binding pocket. Specificity of opioid receptors is mediated by differential occupancy of one of two binding pocket domains and is ligand-dependent. These binding pockets involve interactions between sixth and seventh transmembrane domain for certain ligands, while others ligands target a binding pocket involving interactions between the second, third, and seventh transmembrane domains. As such, the efficacy of a given opioid ligand is determined by several residues within the second, third, sixth,

130 and seventh transmembrane domains (Capeyrou, Riond et al. 1997, Gaibelet,

Capeyrou et al. 1997, Waldhoer, Bartlett et al. 2004, Filizola and Devi 2012).

Following ligand binding, opioid receptor-specific signaling pathways are activated. As with most GPCRs, this is facilitated by the recruitment of G proteins, which causes conformational changes allowing for the depalmitoylation of cysteine residues, ultimately resulting in increased phosphorylation of specific motifs within the C-terminal domain (Chen, Shahabi et al. 1998, Surratt and

Adams 2005, Petaja-Repo, Hogue et al. 2006, Clayton, Bruchas et al. 2010).

Consequently, substitution of conserved cysteine residues within the C-terminal domain, particularly C348 and C353, alters the basal rate of G protein binding

(Connor and Traynor 2010). Several potential PKA and PKC phosphorylation motifs have been identified in the second and third intracellular loops as well as the C-terminal domain (Minami and Satoh 1995, Schulz, Mayer et al. 2004). A unique agonist-induced phosphorylation motif, defined by the consensus motif

TXXXPS, has also been identified for opioid receptors and phosphorylation at this site is thought to activate downstream signal cascades (Kramer and Simon

1999, Wei, Law et al. 2004). Additional conserved tyrosine residues are phosphorylated and are thought to be involved in receptor trafficking and signaling, particularly in a switch from adenylyl cyclase inhibition to stimulation following prolonged agonist application (Wang, Guang et al. 2007, Clayton,

Bruchas et al. 2010). Endocytic trafficking of MORs, which functions to remove receptors from the plasma membrane following prolonged activation and target them for degradation, can occur through two separate processes. Structural

131 motifs within the first intracellular loop and C-terminal domain, which are unique to the MOR, mediate an ubiquitination-dependent endocytic trafficking pathway in a late stage of receptor down-regulation. Early stage down-regulation of MORs is also mediated by structural motifs localized to the C-terminal domain but is ubiquitination-independent (Hislop, Henry et al. 2011). Additional residues, including multiple leucine residues within the C-terminal domain (Tanowitz and von Zastrow 2003, Wang, Loh et al. 2003, von Zastrow 2004) and third intracellular loop (Wang, Loh et al. 2003), have also been implicated in the endocytosis, trafficking, and recycling of multiple opioid receptor subtypes.

Therefore, multiple functions of the opioid receptor family are mediated by a combination of conserved Class A GPCR structural motifs and unique residues, with the latter conferring specific opioid ligand binding and signaling activity.

5.2 Mechanisms of GPCR and Opioid Receptor Signal Transduction

The mechanism through which GPCRs and, as an extension, opioid receptors transduce extracellular stimuli into intracellular signals was initially regarded as linear and involved agonist-mediated conformational changes in the transmembrane heptahelical binding pocket, converting the receptor from an inactive tertiary conformation to an active conformation and stimulating heterotrimeric G proteins signaling cascades through subsequent conformational changes in intracellular loops and the C-terminal domain. However, it is now understood that GPCR activation is a complex process involving a range of active and inactive conformations. In this multistate model, different ligands induce distinct active conformations by differentially interacting with the binding 132 pocket and causing unique conformational changes that, in turn, facilitate coupling of different G protein subtypes through the differential regulation of intracellular loops and C-terminal domain activity. Although activation of different

G protein subtypes accounts for some diversity in GPCR signaling, there is considerably less G protein subtypes than would be expected given the extent of

GPCR signaling (Law and Loh 1999, Maudsley, Martin et al. 2005). This necessitates that the various activation states of GPCRs, including opioid receptors, stimulate both G protein-dependent and G protein-independent signaling cascades. Furthermore, certain opioid agonists and antagonists can completely circumvent receptor binding and activation to autonomously stimulate unique signaling pathways. Collectively, these various signaling mechanism interact to generate specific pharmacokinetic profiles for opioid ligands as well as their target receptors.

5.2.1 G protein-dependent signaling mechanisms

G proteins are comprised of a single α, β, and γ subunit to form a single heterotrimeric complex. While the receptor is inactive, Gα is bound to both the

Gβγ subunit and a guanosine-diphosphate (GDP) molecule. This G protein complex is often anchored to the plasma membrane by covalently attached lipid tails. Upon receptor activation, conformational changes promote GPCR binding of the membrane bound G protein complex. Receptor binding triggers further conformational changes within the G protein complex, resulting in the exchange of GDP for a guanosine-triphosphate (GTP) molecule and the subsequent

133 dissociation of the GTP-bound Gα subunit from the Gβγ dimer. In this state, both the Gα and Gβγ subunits are free to interact with several downstream effectors, triggering various signaling cascades. Following this activation, the inherent

GTPase activity of the Gα subunit hydrolyzes the GTP to GDP, promoting the re- association of the Gα and Gβγ subunits and reverting back to an inactive conformation (Downes and Gautam 1999, Luttrell 2008, Tuteja 2009). Diversity in

G protein signaling is generated by the existence of multiple subtypes of the α, β, and γ subunits. Currently, 16 different genes are known to encode for Gα subunits, while Gβ and Gγ subunits are encoded by 5 and 12 different genes, respectively. Gα subunits are categorized into four subfamilies based both on sequence homology and function; the Gαs subfamily, the Gαi/o subfamily, the

Gαq/11, and the Gα12/13 subfamily. Likewise, the Gβ and Gγ subunits are both categorized into subfamilies. Two distinct families of Gβ proteins have been established based on sequence homology while the Gγ subunit is characterized into one of four families based on overall homology as well as sequence homology within the C-terminal domain, which regulates receptor interactions.

These subunits, particularly Gα, show selectivity for certain effectors. Gαs (for stimulatory) subfamily proteins activate adenylate cyclases, while Gαi (for inhibitory) subfamily proteins inhibit adenylate cyclases as well as regulate ion channel activity. Other unique Gα subunits target different effectors, for example

Gαq/11 subfamily proteins activate phospholipase C (PLC) while Gα12/13 subfamily proteins activate Na+/H+ exchangers. Other effector systems targeted by the Gα

134 complex include Ca2+ and K+ channels and various protein kinases. The Gβ and

Gγ subunits also target downstream effectors; however, they are only known to function as a dimeric complex as the individual subunits are inactive. The Gβγ complex can act as both a positive and negative regulator of cell signaling and is known to interact with K+ channels, adenylyl cyclase, phospholipase A (PLA), and PLC. The signaling interactions of G protein subunits are further complicated by the tissue-specific expression of certain subtypes. As such, mammalian G proteins fall into one of three broad categories; ubiquitous or nearly-ubiquitous G proteins, tissue-specific G proteins, and cell-type specific G proteins (Standifer and Pasternak 1997, Downes and Gautam 1999, Wong 2003, Defea 2008,

Luttrell 2008, Tuteja 2009).

Many types of bacteria utilize ADP-ribosylating toxins, including pertussis toxin (PTX) and cholera toxin (CTX), in order to exert their cytotoxic effects.

Despite their lethality, these ADP-ribosylating toxins are of particular use in studying G protein signaling pathways because of their specific interactions.

Pertussis toxin, produced by Bordetella pertussis, specifically targets Gαi subfamily proteins, which includes Gαi and Gαo subunits, at a conserved cysteine residue. ADP-ribosylation at this conserved residue inhibits Gαi coupling to GPCRs, blocking signal transduction. Another Gαi subfamily member, Gαz, lacks this conserved cysteine residue and is accordingly PTX-insensitive. In a similar manner, CTX, produced by Vibrio cholera, targets a conserved arginine residue of the Gαs subfamily. However, ADP-ribosylation at this conserved

135 residue causes permanent activation of the Gαs subunit by inhibiting the intrinsic

GTPase activity of Gαs (Mangmool and Kurose 2011). Given this specific interaction with G protein subfamily members, PTX and CTX have been useful in determining what G proteins subunits mediate certain signaling pathways. While slight variations exist between MORs, DORs, and KORs, the primary, but not exclusive, G protein subtype associated with opioid receptors are members of the Gαi/o subfamily, which is comprised of three Gαi (Gαi1, 2, and 3), two Gαo (A and B) and the PTX-insensitive Gαz. Opioid receptor binding to Gαi/o subfamily proteins was determined by the ability of PTX to inhibit many opioid receptor signaling pathways (Connor and Christie 1999, Johnson, Christie et al. 2005,

Traynor 2012). Opioid-induced Gαi/o activity affects several downstream effectors. This includes inhibiting adenylyl cyclase, which reduces cyclic adenosine monophosphate (cAMP) levels. Opioid-mediated Gαi/o protein signaling also inhibits voltage-dependent N-type and P/Q-type Ca2+ channels while activating inward rectifying K+ channels (Childers 1991, Fowler and Fraser

1994, Minami and Satoh 1995, Reisine 1995, Yu 1996, Standifer and Pasternak

1997, Law, Wong et al. 2000, Williams, Christie et al. 2001, Waldhoer, Bartlett et al. 2004, Wei, Law et al. 2004, Zhang, Chen et al. 2008, Pasternak 2010). Gαi/o- coupled opioid receptors also activate phospholipase C (PLC), which catalyzes the formation of inositol 1,4,5-triphosphate (IP3) and diacylglycerol, triggering the

2+ release of intracellular Ca . Collectively, these opioid-induced Gαi/o protein signaling pathways result in a hyperpolarization of the cell membrane that

136 reduces cellular excitability and inhibits neurotransmitter release, ultimately resulting in the antinociception characteristic of opioids (Roy and Loh 1987,

McFadzean 1988, Loh and Smith 1990, Laugwitz, Offermanns et al. 1993, D

Smart 1995, Mestek, Hurley et al. 1995, Minami and Satoh 1995, Satoh and

Minami 1995, Piros, Hales et al. 1996, Williams, Christie et al. 2001, Wei, Law et al. 2004, Zhang, Chen et al. 2008, Pasternak 2010, Lamberts, Jutkiewicz et al.

2011). Opioid receptors have also been shown to stimulate cholera toxin- sensitive accumulation of cAMP and inhibition of K+ channel activity, suggesting that in certain cell types these receptors can couple Gαs subtypes. Therefore, under certain conditions, opioids may mediate excitatory effects in neurons through the coupling of Gαs subtypes, which activate adenylyl cyclase, increase cAMP concentrations, and facilitate cAMP-dependent voltage-sensitive ionic conductance (Crain and Shen 1990, Childers 1991, Fowler and Fraser 1994,

Minami and Satoh 1995, Piros, Hales et al. 1996, Steiner, Avidor-Reiss et al.

2005, Gintzler and Chakrabarti 2006). However, Gαs association with opioid receptors, MOR in particular, is dependent on the phosphorylation state of the G protein. This may be a byproduct of changes in G protein hydrophobicity, as dephosphorylation augments lipid solubility, and suggests that Gαs coupling to opioid receptors occurs predominantly in lipid-rich membrane regions

(Chakrabarti, Chang et al. 2010). Furthermore, the specific Gα subunit coupled by opioid receptors is dependent on the specific agonist bound as well as multiple cellular factors (Raehal, Schmid et al. 2011).

Many downstream signaling cascades activated by opioid receptors are 137 initiated by G protein-dependent mechanisms. Opioid receptor-mediated phosphorylation of PKA, PKC, and calmodulin-dependent protein kinase II

(CaMKII), facilitated by PLC activation, exacerbates hyperpolarization through interactions with Ca2+ and K+ channels, while opioid receptor-mediated phosphorylation of PKA antagonizes membrane hyperpolarization (Reisine and

Bell 1993, Yu 1996, Law, Wong et al. 2000, Wei, Law et al. 2004, Freye and

Levy 2005, Zhang, Chen et al. 2008). Activation, through phosphorylation, of the

PI3K/Akt/mTOR/p70 S6K and p38 MAPK/NF-κB pathways within the hippocampus and nucleus accumbens, respectively, was shown to mediate conditioned place preference in mice, an important paradigm for drug addiction

(Cui, Zhang et al. 2010, Zhang, Cui et al. 2011). Activation of the

PI3K/Akt/mTOR/p70 S6K pathway also mediates neuronal survival and translational control and, as such, is implicated in opioid modulation of neuronal development, long term memory, and synaptic plasticity (Polakiewicz, Schieferl et al. 1998). Additionally, activation of PI3K/Akt by morphine stimulates the nNOS/NO/KATP pathway in primary nociceptive neurons to produce antinociception (Cunha, Roman-Campos et al. 2010). Collectively, these G protein-dependent downstream signaling cascades, in addition to many others, such as ERK1/2 and JNK MAPK signaling cascades, mitigate the unique cellular signals of opioid ligands. As such, disruption of Gαi/o or Gαs coupling would be expected to disrupt multiple signaling pathways stimulated by opioid receptors.

138 5.2.2 G protein-independent signaling mechanisms

The classical mechanism through which opioid receptors, as Class A

GPCRs, transmit extracellular signals to the interior of the cell is through the recruitment and activation of heterotrimeric G proteins that, in turn, activate both ion channels and second messenger signaling cascades. However, GPCRs have also been shown to mediate signaling through G protein-independent mechanisms that involve the recruitment, activation, and scaffolding of cytoplasmic signaling complexes (Lefkowitz and Shenoy 2005, DeWire, Ahn et al. 2007). One such protein is the ubiquitous intracellular Ca2+ sensor calmodulin

(CaM). In addition to its established role in G protein-dependent activation of

CaMKII, CaM may also directly compete with G protein subunits for binding to the third intracellular loop and, therefore, acts as a G protein-independent second messenger under certain conditions (Wang, Sadee et al. 1999). The primary factors identified in G protein-independent signaling, however, are members of the arrestin family of proteins, which consist of visual arrestin (arrestin 1), β- arrestin 1 (arrestin 2), β-arrestin 2 (arrestin 3), and cone arrestin (arrestin 4)

(Cen, Xiong et al. 2001, Gurevich and Gurevich 2006, Defea 2008). Collectively, arrestins are ubiquitous; however, not all cell types express each arrestin subtype. Expression of both visual and cone arrestins are restricted to retinal rod and cone cells, whereas β-arrestin 1 and β-arrestin 2 are ubiquitously expressed.

As such, arrestin proteins are divided into two subfamilies based on structure and function, with visual and cone arrestins comprising the visual/sensory arrestin subfamily and β-arrestin 1 and β-arrestin 2 comprising the non-visual arrestin 139 subfamily (Gurevich and Gurevich 2006, Barki-Harrington and Rockman 2008).

Functionally, different β-arrestins bind different classes of GPCRs with various strengths. β-arrestin 2 binds Class A GPCRs with a much greater affinity than β- arrestin 1, and this interaction quickly disassociates once the receptor is internalized. In contrast, Class B GPCRs bind both β-arrestins with equal affinity and is much more stable, with the interaction remaining intact throughout receptor internalization. Interestingly, these properties of β-arrestins appear to be determined by the C-terminal domain of their target receptors, as switching this region between Class A and B GPCRs reverses their affinity for β-arrestins

(Barki-Harrington and Rockman 2008). Indeed, direct interactions between opioid receptors, CaMKII, and β-arrestins have been shown to involve serine and threonine residues within the receptor C-terminal domain and the third intracellular loop. It is now understood that the third intracellular loop, in addition to its role in G protein activation, directly interacts with CaM through CaMKII activity while the C-terminal domain serves as the primary target for β-arrestin interactions (Wang, Sadee et al. 1999, Cen, Xiong et al. 2001). Furthermore, β- arrestin interaction is not consistent between opioid receptor subtypes, particularly the MOR, and may be due, in part, to alternatively spliced isoforms that differentially interact with β-arrestins (Cen, Xiong et al. 2001).

β-arrestins primarily function as scaffold proteins and, as such, their G protein-independent signaling involves simultaneous binding of multiple cytoplasmic and nuclear factors. For example, receptor-bound β-arrestins recruit

140 several protein members of various MAP kinase cascades, including the apoptosis signal-regulating kinase (ASK) 1/MKK4/JNK3 and c-Raf-1/MEK1/ERK2 pathways. Through this simultaneous interaction with several signaling partners,

β-arrestins temporally and spatially orchestrate enzyme and substrate interactions, thereby facilitating G-protein-independent signaling pathways

(Gintzler and Chakrabarti 2006, Gurevich and Gurevich 2006, Defea 2008).

Consequently, β-arrestin signaling complexes have been shown to regulate many cellular functions (Ferguson 2001, Lefkowitz and Shenoy 2005, Ma and Pei

2007). One such cellular function is transcription. In response to activation by certain GPCR ligands, including opioids, β-arrestins translocate from the cytoplasm to the nucleus. Once localized to the nucleus, β-arrestins can regulate transcription directly by binding to promoter regions of target genes and promoting the recruitment of transcriptional co-factors like CREB. This transcription-protein complex may then associate with target gene promoters to initiate transcription. β-arrestin-mediated transcription has been found to occur indirectly through the regulation of transcription-mediating signaling pathways.

Indirect mechanisms of β-arrestin-mediated transcription have also been found and include the inhibition of NF-κB mediated transcription through the stabilization of the inhibitory IκBα/NF-κB complex. Increased activity of nuclear receptors, such as retinoic acid receptors, is also mediated by β-arrestins

(DeWire, Ahn et al. 2007, Ma and Pei 2007, Rajagopal, Rajagopal et al. 2010).

An additional mechanism of β-arrestin-mediated transcription involves histone

141 hyperacetylation due to the enhanced recruitment of histone acetyltransferases to chromatin (Kang, Shi et al. 2005). Regulation of multiple kinase signaling pathways has also been shown to include associations with β-arrestins. For example, growth factor stimulation of the PI3K/Akt pathway and attenuation of apoptosis are β-arrestin-dependent (DeWire, Ahn et al. 2007). However, of all the kinase signaling pathways mediated by β-arrestin, MAPK signaling pathways remain the most thoroughly investigated (Gurevich and Gurevich 2006, Ma and

Pei 2007, Defea 2008).

5.2.3 Activation of MAPK pathways

Among the signaling cascades that mediate cellular responses to extracellular stimuli, such as growth factors, cytokines, or environmental stressors, the mitogen-activated protein kinases (MAPKs) family is one of the most characterized. The MAPK family is divided into five distinct subfamilies within mammals; the extracellular signal-regulated kinases 1 and 2 (ERK1/2), the stress-activated protein kinases (SAPK) that are also known as c-Jun amino- terminal kinases 1, 2, 3 (JNK1/2/3), the p38 MAPK isoforms α, β, γ, and δ, the

ERK3/4 kinases, and the ERK5 kinase, although the latter two kinase families are poorly understood. In general, the MAPK subfamilies are selectively activated by different extracellular stimuli. Growth factors typically activate the ERK1/2 signaling cascade while environmental stressors typically activate either the

SAPK/JNK or p38 MAPK signaling cascades. Despite this difference in ligand recognition, MAPK pathways share common mechanisms of downstream

142 signaling. All MAPK family signaling pathways are comprised of three sequential phosphorylating steps that allow for the amplification of the external signal.

Following GPCR activation, downstream effector GTP-binding proteins, such as

Ras and Rho, facilitate the phosphorylation and activation of serine/threonine

MAPK kinase kinases (MAPKKKs), the first upstream mediators of the MAPK signaling cascade. Activated MAPKKKs then target and phosphorylate additional serine/threonine kinases known as MAPK kinases (MAPKKs). Phosphorylation activates MAPKKs and promotes the dual phosphorylation of their downstream target, the MAPKs, at a conserved serine/threonine TXY motif. Once phosphorylated by MAPKKs, MAPKs phosphorylate target substrates on serine/threonine and proline residues, facilitating additional downstream signaling pathways. Despite this broad mechanism, specificity in MAPK signaling is tightly regulated by the MAPKKKs and MAPKKs activated by different G proteins as well as specific interaction motifs on MAPK substrates (Martin-Blanco 2000,

Johnson and Lapadat 2002, Roux and Blenis 2004). Additionally, it is now recognized that MAPK cascade specificity is also regulated by scaffolding proteins, such as β-arrestins (Roux and Blenis 2004). This presents two distinct possibilities for MAPK activation, being mediated in either a G protein-dependent or –independent manner.

Many secondary messenger proteins mediate G protein-dependent activation of MAPK signaling pathways, particularly small, monomeric GTP- binding proteins known as small GTPases. These proteins are regulated by multiple GPCR-stimulated signaling cascades, including Ca2+, PKA, PKC, PLC,

143 and cAMP (Grewal, York et al. 1999, Takai, Sasaki et al. 2001). As such, activation of G protein subunits by GPCR ligand binding mediates MAPK signaling through the activation of secondary messenger/small GTPase cascades. One such cascade involves the recruitment of PI3K to the plasma membrane following the disassociation of GTP bound-Gα from Gβγ. Activated

PI3K increases Src-like kinase activity, which initiates the Shc/Grb2/Sos/Ras signaling cascade and ultimately increases MAPK activity (Lopez-Ilasaca,

Crespo et al. 1997, Belcheva and Coscia 2002). Opioid receptors have been found to activate MAPK signaling in a similar manner, as opioid-mediated activation of the SAPK/JNK signaling cascade was found to involve Gβγ, Src kinase, and Rac, among other signaling factors. The necessity for PI3K in this activation was dependent on the receptor subtype, with MORs utilizing PI3K- dependent signaling cascades whereas DORs and KORs utilize PI3K- independent mechanisms (Kam, Chan et al. 2004). Following acute opioid receptor activation by certain agonists, the Gβγ subunit released from Gαi activates Ras through PI3K recruitment. Activated Ras stimulates the serine/threonine kinase Raf, which phosphorylates the upstream MAPKK ERK kinase, facilitating the phosphorylation and activation of ERK1/2. Binding of

Ca2+/CaM to the third intracellular loop of opioid receptors may also mediate ERK signaling via Ras activation. Additionally, the PTX-insensitive subunit Gαq may activate ERK1/2 through the activation of a PLC/Ca2+/PKC pathway (Belcheva,

Vogel et al. 1998, Belcheva and Coscia 2002). These findings are in line with the fact that Gαi-derived Gβγ and Gαq subunits are the most common G proteins 144 associated with MAPK pathway activation. However, additional G protein subunits may also play a role. Similar to Gαq, the Gαo subunit activates ERK1/2 through PKC activation; however, this mechanism is Ras-independent and, instead, is thought to involve a different small GTPase, Rap1/B-Raf. Both Gαz and Gα12, which are also PTX-insensitive, are thought to mediate the inhibition of

EFG-activated ERK1/2 through an unknown mechanism following chronic MOR activation (Grewal, York et al. 1999, Belcheva and Coscia 2002). Activation of

Gαs-bound GPCRs may also stimulate MAP kinase signaling through cAMP accumulation (Fukunaga and Miyamoto 1998). However, an indirect mechanism of Gαs-mediated MAPK activation may be more likely as Gαs-mediated PKA phosphorylation of certain GPCRs switches the G protein coupling from Gαs to

Gαi, allowing for Gαi-mediated MAPK signaling (Belcheva and Coscia 2002).

Collectively, this data shows that multiple G proteins differentially associate with opioid receptors to activate or inhibit MAPK signaling through their selective interaction with second messenger kinases and small GTPases.

Activation of MAPK pathways through G protein-independent mechanisms has also been readily identified for many GPCRs and is mediated primarily by the recruitment of β-arrestins to the activated GPCR. It is now understood that β- arrestins serve as a scaffold to physically link the activated GPCR to MAPK family member proteins, including ERK1/2, p38 MAPK, and SAPK/JNK members. Scaffolding characteristics also enable β-arrestins to recruit multiple second messenger proteins as well, including Src, PI3K, and Akt. Mechanisms

145 involved in β-arrestin-mediated MAPK signaling are poorly understood, but a plausible model, based on p38 MAPK activation, suggests that β-arrestins generate a MAPK signaling complex containing the required secondary messengers and sequential kinase cascade of MAPKKK, MAPKK, and MAPK proteins. As such, the mechanism of G protein-independent signaling facilitated by β-arrestins is similar to G protein-dependent mechanisms in that they involve secondary messengers and small GTPases (Ferguson 2001, Luttrell and

Lefkowitz 2002, Gurevich and Gurevich 2006, Gurevich 2013). Activation of

GPCRs results in the recruitment of β-arrestins, causing structural rearrangements that facilitate the recruitment of secondary messengers such as

Src. Secondary messengers then proceed to activate downstream signaling cascades, including small GTP-binding proteins, like Ras, that act as MAPKKKs to initiate the sequential phosphorylation of the MAPK cascade (Ferguson 2001,

Luttrell and Lefkowitz 2002). Therefore, β-arrestins provide a second mechanism through which GPCRs can activate MAPK signaling cascades.

As GPCR activation of MAPK effectors is mediated through G protein- dependent and -independent mechanisms, the strength, kinetics, and localization of MAPK signaling is ultimately regulated by the dynamic balance of G proteins and β-arrestins. Agonist-bound GPCRs initiate the first wave of MAPK signaling through G protein-dependent activation of second messengers and small

GTPases. This activated MAPK signal is both rapid and transient, with peak signaling occurring within seconds to minutes, resulting in unique MAPK downstream effects. For example, G protein-dependent activation of ERK1/2 146 promotes translocation of the proteins into the nucleus, where it associates with transcription factors. Additionally, as this initial wave of MAPK signaling is G protein-dependent, it is typically sensitive to PTX, unless Gαq, Gαz, or Gα12 is utilized. The transient nature of initial G protein-dependent MAPK signaling is due to the binding of β-arrestins to active GPCRs, which displace G proteins from

GPCRs almost immediately after receptor activation. Indeed, the classical function of β-arrestins is the termination of G protein signaling. However, as described previously, β-arrestins can scaffold components of MAPK kinase signaling cascades, for example Raf-1, MEK1, and ERK1/2. This β- arrestin/MAPK complex is able to initiate a second wave of MAPK signaling. The

MAPK signaling pathways initiated by β-arrestins are comparatively delayed in onset but more persistent than those initiated by G proteins, peaking within minutes of receptor activation but with signaling continuing for hours. The prolonged signaling of β-arrestin-mediated MAPK signaling is a direct result of the β-arrestin/MAPK signaling complex being retained within the cytoplasm, thereby enhancing cytoplasmic MAPK signaling while diminishing MAPK nuclear functions (Williams, Christie et al. 2001, Luttrell and Lefkowitz 2002, Ahn, Shenoy et al. 2004, Gurevich and Gurevich 2006, Macey, Lowe et al. 2006, DeWire, Ahn et al. 2007, Ma and Pei 2007, Barki-Harrington and Rockman 2008, Defea 2008,

Kovacs, Hara et al. 2009, Pasternak 2010, Zheng, Zeng et al. 2010, Gurevich

2013). Additionally, the activation of MAPK signaling pathways by β-arrestins is independent from their role in receptor endocytosis (Kramer and Simon 2000,

147 Trapaidze, Gomes et al. 2000). Specificity of β-arrestin/MAPK signaling is regulated by the stimulus and GPCR activated, which promote the differential recruitment of second messenger proteins that may have opposing effects. This is found with Akt, which is either activated or suppressed by β-arrestin through differential recruitment of Src or protein phosphatase 2A (PP2A), respectively

(Kovacs, Hara et al. 2009). Overall, the distinct physiological endpoints of MAPK signaling are temporally and spatially regulated through a two-phase signaling cascade. An initial, rapid activation of unbound MAPKs by G proteins facilitates their translocation throughout the cytoplasm and nucleus. A delayed but prolonged activation of MAPK is sequentially initiated by β-arrestins, which simultaneously disrupt G protein-dependent signaling while recruiting and binding

MAPK cascade proteins, forming a MAPK signaling complex that is restricted to the cytoplasm, thereby prolonging their cytoplasmic function.

MAPK signaling cascades mediate a wide range of cellular functions, with specificity being determined through the targeting of distinct cytoplasmic and nuclear factors by different MAPK subfamily proteins. Of the five identified MAPK subfamilies, the cellular functions mediated by ERK1/2, p38 MAPK, and

SAPK/JNK signaling cascades are the most characterized. The ERK1/2 MAPK signaling cascade is primarily activated by growth factor signaling and, as such, is involved in the regulation of meiosis, mitosis, and post-mitotic functions in differentiated cells (Johnson and Lapadat 2002). Furthermore, ERK1/2 signaling has specific, activity-dependent functions within neurons, including the regulation of synaptic plasticity, long-term potentiation (LTP), and cell survival (Grewal, York 148 et al. 1999, Belcheva and Coscia 2002). The p38 MAPK signaling cascade is stimulated by environmental stress factors, primarily inflammatory signals, and serve as key regulators of inflammatory cytokine expression and as inhibitors of cell cycle progression and proliferation (Martin-Blanco 2000, Johnson and

Lapadat 2002, Kovacs, Hara et al. 2009). Furthermore, p38 MAPK signaling is critical for normal immune and inflammatory responses, as it regulates macrophage, neutrophil, and T lymphocyte functional responses and apoptosis

(Roux and Blenis 2004). The SAPK/JNK MAPK signaling pathway is similarly activated by environmental stressors and serves to increase transcriptional activity in response to decreased protein synthesis. The primary substrates of

SAPK/JNK MAPK are transcription factors, including the c-Jun/AP-1 transcription complex, which mediates the transcription of multiple cytokine encoding genes

(Johnson and Lapadat 2002, Roux and Blenis 2004). It should be noted, however, that these pathways do not exist in isolation and, in fact, dynamic cross-signaling pathways between MAPK subfamilies mediate cellular functions.

As such, the interactions between ERK1/2, p38, and SAPK/JNK MAPK signaling pathways have been found to play a central role in many cellular functions, the most vital being apoptosis (Fukunaga and Miyamoto 1998).

Regulation of cellular functions by MAPK signaling pathways is due to

MAPK-mediated phosphorylation of several downstream effectors, including phospholipases, transcription factors, and cytoskeletal proteins as well as several protein kinases. These MAPK-activated protein kinases include 90kDa ribosomal

S6 kinases (RSKs), mitogen- and stress-activated kinases (MSK) 1 and 2,

149 MAPK-interacting kinases (MNK) 1 and 2, and MAPK-activated protein kinases

(MK) 2, 3, and 5. Members of the p90 RSK family (RSK1/2/3/4) as well as MNK2 are preferentially activated by ERK1/2 MAPK signaling, while MK2/3/5 is preferentially activated my p38 MAPK signaling. The remaining factors, MSK1/2 and MNKs, are activated by both ERK1/2 and p38 MAPK signaling cascades. No known members of MAPK-activated protein kinase families have been found to interact with JNK MAPK signaling cascades. The significance of differential regulation of MAPK-activated protein kinases stems from their distinct roles in certain cellular functions. MNK1/2 displays various basal activity in cells and are responsive to both stress- and mitogen-stimulated pathways, suggesting a functional role in cellular responses to environmental stressors (Roux and Blenis

2004). MSK1/2 are usually localized to the nucleus, which suggests a functional role in transcriptional regulation in response to stress and mitogens through selective phosphorylation of nuclear factors, including NF-κB and histones.

MSK1/2 may also regulate apoptosis by phosphorylating and inhibiting pro- apoptotic members of the Bcl-2 protein family; however, the biological significance of this processes remains to be determined (Roux and Blenis 2004,

Hauge and Frodin 2006, Anjum and Blenis 2008). The RSK family proteins are typically localized to the cytoplasm along with their necessary activating kinase

ERK1/2. However, upon phosphorylation, RSKs translocate to the nucleus, suggesting a nuclear function. As such, RSKs are proposed to play a key role in regulating transcription as well as cell cycle progression and viability. To this end,

RSKs are known to phosphorylate many immediate-early gene products, such as

150 c-Fos and c-Jun, in addition to transcriptional factors like CREB. RSK-mediated transcriptional regulation also occurs indirectly, as is evident by the RSK- mediated phosphorylation and inhibition of the NF-κB inhibitor IκBα, resulting in the activation of NF-κB transcription (Roux and Blenis 2004, Hauge and Frodin

2006, Anjum and Blenis 2008). Interestingly, activation of the MOR has been found to regulate NF-κB signaling in a similar manner, although it may involve additional second messenger intermediates, including PI3K, Akt, ERK1/2,

SAPK/JNK, CaMKII, and Src (Liu and Wong 2005). Collectively, RSK-mediated transcriptional regulation promotes cell survival, including the survival of primary cortical neurons, by enhancing the expression of survival-promoting genes.

Direct mechanisms of RSK-mediated cell survival have also been identified in primary cortical neurons. This occurs through the RSK-mediated phosphorylation and inactivation of pro-apoptotic Bcl-2 family proteins, such as Bad. Another key protein in both transcriptional regulation and cell survival signaling cascades,

GSK-3β, is also subject to phosphorylation and inhibition by RSK1. It should be noted, however, that most RSK studies have not determined which specific RSK isoforms can and cannot mediate phosphorylation of particular substrates and, as such, many of the identified RSK targets may be shared by various RSK family members (Roux and Blenis 2004, Hauge and Frodin 2006, Anjum and

Blenis 2008). The functional significance of RSK family member proteins is present in the fact that the loss of RSK2 results in the development of Coffin-

Lowry syndrome, which is characterized by mental retardation, growth deficits, skeletal deformations, and psychosis (Sheffler, Kroeze et al. 2006). 151 Opioid receptors show an extensive amount of MAPK signaling following their activation by different opioid ligands. Opioid-induced MAPK signaling is temporally regulated, with acute and chronic opioid exposure resulting in distinct

MAPK signaling cascades. Furthermore, the molecular process mediated by

MORs, DORs, and KORs are not identical, leading to ligand and receptor differences in MAPK signaling (Kam, Chan et al. 2004, Chen, Geis et al. 2008,

Miyatake, Rubinstein et al. 2009, Wang, Sun et al. 2010). Multiple studies have found that MORs, KORs, and DORs differentially regulate ERK1/2, p38 MAPK, and SAPK/JNK signaling cascades. As previously stated, opioids mediate the activation of SAPK/JNK signaling through the activation of Gβγ, Src kinase, and the small GTPases Rac and Cdc42. MOR-mediated SAPK/JNK signaling is dependent on PI3K activity, whereas both KOR- and DOR-mediated SAPK/JNK signaling is not. The reason for this discrepancy is unclear; however, it may involve selective binding of different Gαi/o and Gβγ subunits (Ai, Gong et al. 1999,

Kam, Chan et al. 2004, Chen and Sommer 2009). Repeated morphine exposure also increases p38 MAPK phosphorylation, leading to an increase in CREB phosphorylation (Ma, Zheng et al. 2001). Furthermore, morphine-mediated activation of both p38 MAPK and SAPK/JNK signaling pathways induce tau hyper-phosphorylation, which may be responsible for morphine-induced neurotoxicity (Cao, Liu et al. 2013). Despite activation of both the SAPK/JNK and p38 MAPK signaling pathways, morphine-mediated ERK1/2 activation is the primary MAPK signaling cascade associated with the characteristic features of opioids and, as such, their differential regulation may play a key functional role in 152 opioid actions (Ligeza, Wawrzczak-Bargiela et al. 2008). Differential ERK1/2 signaling is due, in part, to the dissimilar utilization of Gαi/o and Gαz by MORs,

KORs, and DORs (Kam, Chan et al. 2004). This is in line with the finding that acute activation of MORs and DORs in COS cells activates rapid, transient

ERK1/2 signaling, whereas KOR activation does not (Gutstein, Rubie et al. 1997,

Belcheva, Clark et al. 2005). The absence of ERK1/2 signaling by KORs, however, may be cell-type dependent, as it is present in endothelial cells. It would appear, then, that MOR- and DOR-mediated ERK1/2 signaling occurs in both neuronal and non-neuronal cell types, whereas KOR-mediated ERK1/2 signaling is restricted to non-neuronal cell types. Cell specificity of opioid- mediated ERK1/2 signaling may be due to the disparity of second messengers available between tissues (Gupta, Kshirsagar et al. 2002, Mouledous, Diaz et al.

2004). To that extent, activation of ERK1/2 signaling by MORs is both CaM- and

PKC-dependent, although this has not been shown for DORs (Belcheva, Szucs et al. 2001, Bilecki, Zapart et al. 2005, Chen and Sommer 2009). In the case of

MORs, both acute and chronic morphine treatment activate ERK1/2 MAPK signaling, resulting in the activation of transcription factors (Przewlocki 2004).

Again, however, conflicting studies report that chronic MOR activation by morphine or the µ-selective agonist DAMGO may also dephosphorylate ERK1/2 or that acute morphine is not sufficient to activate ERK1/2 signaling while chronic morphine exposure is. The mechanisms of temporal ERK1/2 regulation by MOR activation is explained in two-step processes involving the initial activation of second messenger proteins and their downstream effects. In the case of ERK1/2 153 inhibition following chronic opioid administration, the initial acute MOR activation stimulates Ca2+/calmodulin and PKC activation that, in turn, promotes ERK1/2 phosphorylation. However, the persistent increase in PKC and CaMKII mediated by chronic opioid exposure feeds back to disinhibit MOR ERK1/2 signaling and dephosphorylate ERK1/2. To reconcile the opposite finding, it is suggested that weaker opioids cannot stimulate second messenger signaling following a single dose, but instead require repeated MOR activation by chronic exposure in order to up-regulate the various second messengers required for ERK1/2 activation

(Bilecki, Zapart et al. 2005, Macey, Bobeck et al. 2009). Furthermore, MOR- mediated activation of ERK1/2 signaling cascades is also differentially regulated by agonist selectivity for G protein-dependent or –independent signaling, resulting in either the rapid and transient phosphorylation of ERK1/2 or delayed, prolonged phosphorylation (Zheng, Loh et al. 2008, Zheng, Loh et al. 2010,

Raehal, Schmid et al. 2011). The functional importance of differential ERK1/2 signaling is that, in addition to G protein-dependent signaling effects, such as cAMP inhibition, Ca2+ channel inhibition, and K+ channel activation, the ERK1/2 signaling pathway is thought to contribute to the physiological characteristics associated with opioid use, including analgesia, sedation, tolerance, and physical dependence. This is evident in the fact that differential ERK1/2 activation mirrors physiological effects. As such, both MORs and DORs, which stimulate ERK1/2 activation, produce euphoria, whereas KORs, which do not readily activate

ERK1/2 signaling, cause dysphoria. Although it is possible that physiological properties of opioid receptors can be completely explained by the anatomic

154 differences in their localization, molecular evidence suggests that ERK1/2 as well as other signal transduction mechanisms are involved in the physiological response of opioids (Gutstein, Rubie et al. 1997).

5.2.4 Agonist-independent signaling mechanisms

The Lefkowitz two-state model of GPCR ligand binding, although now understood as an over-simplification, remains extremely useful in understanding the activation states of GPCRs. It was originally viewed that agonist binding, through the promotion of conformational changes within the GPCR tertiary structure, stabilized the active state of the receptor, allowing for G protein binding and activation. Based on this assumption, inverse agonists were identified as

GPCR ligands that stabilized the inactive state of the receptor. Collectively, this model suggests that for any GPCR, it exists in a state of equilibrium between active and inactive states, and its activity is therefore determined by the dynamic conversion from an inactive state to an active state. Given this equilibrium and fluctuation in receptor activation states, basic thermodynamics mandate that there must be a finite probability that this conversion also occurs spontaneously in the absence of an agonist. Indeed, it is now recognized that virtually all

GPCRs, without mutation, express some level of measurable constitutive activity.

The extent to which this occurs is highly inconsistent, as even closely related

GPCRs express significantly different levels of constitutive activity when expressed at equal levels. (Liu and Prather 2001, Seifert and Wenzel-Seifert

2002, Milligan 2003, Hill 2006, Tao 2008). Furthermore, constitutive activity for certain GPCRs exhibit cell-type specificity, due to selective expression of GPCR- 155 interacting proteins (Milligan 2003), and can be generated or exacerbated by receptor overexpression, particularly for GPCRs that couple to Gαs, due to a higher probability of spontaneous conversion into an active conformation (Liu,

Ruckle et al. 2001, Hill 2006, Tubio, Fernandez et al. 2010). Opioid receptors, specifically the DOR, provided the first evidence supporting constitutive activity of

GPCRs (Seifert and Wenzel-Seifert 2002). This discovery was based on the finding that competitive δ-selective antagonists decreased GTPase activity in the absence of agonist. This intrinsic activity suggested a basal activity for the endogenous δ opioid receptor (Tao 2008). In addition to constitutively active

DORs, MORs have been identified to signal in the absence of agonist binding.

Given that MORs are Gαi/o coupled GPCRs, it is not surprising that constitutively active MORs inhibit adenylyl cyclase activity and may be involved in thermal nociception (Liu, Ruckle et al. 2001, Connor 2009, Lam, Maga et al. 2011).

Based on the findings that opioid receptors display a basal level of agonist- independent activity, it is now well established that nearly all GPCRs can spontaneously assume an active state. In addition to the basic thermodynamic properties that allow opioid receptors to spontaneously adopt an active conformation, environmental factors can actively shift the equilibrium between active and inactive states. For example, chronic morphine treatment increases

MOR constitutive activity in vivo (Connor and Traynor 2010, Lam, Maga et al.

2011). This is a result of the partial-agonistic property of morphine, which has a relatively high activity at the MOR but fails to produce the desensitization seen with other agonists, such as DAMGO. As such, opioid-mediated enhancement of 156 MOR constitutive activity has only been demonstrated following chronic morphine treatment (Liu and Prather 2001, Waldhoer, Bartlett et al. 2004).

A second method of agonist-independent GPCR signaling has also been identified and involves receptor-mediated modulations of G protein availability, thereby impacting the signaling of a second receptor (Tubio, Fernandez et al.

2010). All GPCRs within a given cell share the same intracellular pool of G proteins. This is particularly so for GPCRs and G proteins in close proximity to one another at the plasma membrane. In that respect, DORs and MORs, despite showing a distinct preference for particular Gαi/o subtypes, do not display distinct receptor structures that govern G protein specificity, suggesting that the subcellular compartmentalization of opioid receptors and G proteins mediates receptor signaling specificity at some level. As such, the observed cross- reactions between GPCRs, including the DOR and MOR, are postulated to occur at the level of G proteins, as both receptors activate Gαi/o protein subtypes (Alt,

Clark et al. 2002). This mechanism, referred to as homologous or heterologous desensitization, has since been shown to function heavily in opioid receptor signaling. For example, prolonged DAMGO exposure was found to cause heterologous desensitization of IFG-I-mediated ERK1/2 phosphorylation through the cross-activation of the IGF receptor by the DAMGO-activated MOR.

Homologous desensitization was also found with DAMGO-bound MORs trans- activating unbound MORs. Although an exact mechanism for homologous or heterologous desensitization is unclear, it is thought to occur due to the promiscuity of second messengers, such as Src or β-arrestins, which are 157 transferred from the bound to the unbound receptor (Li, Eitan et al. 2003, Sparta,

Baiula et al. 2010). Opioid receptors may also be the target of heterologous desensitization. For example activation of A1 adenosine receptor by its agonist caused heterologous desensitization of the DOR, resulting in DOR-mediated cAMP inhibition and Akt phosphorylation (Cheng, Tao et al. 2010). There is also evidence that opioid receptors mediate heterologous desensitization of EGF receptors via Gαi/o, Gαq, and Gβγ subunits, resulting in EGF receptor-mediated phosphorylation of ERK1/2 (Schulz, Eisinger et al. 2004). Similarly, MOR activation potentiates NMDAR signaling in the absence of NMDAR agonists through an Akt/NOS/PKC/Src pathway (Sanchez-Blazquez, Rodriguez-Munoz et al. 2010). Therefore, opioid receptors have two mechanisms through which they can signal in the absence of specific ligands: the spontaneous adoption of an active conformation or through trans-activation mediated by G proteins and/or second messengers activated by a second, ligand-bound, active receptor.

5.2.5 Opioid receptor-independent signaling mechanisms

The classical mechanism of action for various opioids involves their selective binding to opioid receptor subtypes and the subsequent stimulation of both G protein-dependent and –independent signaling pathways. However, opioid signaling mechanisms independent of opioid receptors have also been identified for many opioid ligands. Opioid receptor-independent signaling is most often associated with stereoselective enantiomers of opioid compounds that do not have an affinity for classical opioid receptors. Typically, opioid receptors bind the levorotatory (-)-isomers of opioid compounds due to the stereoselectivity of 158 the binding pocket. This is evident in the fact that the dextrorotatory (+)-isomer of methadone produces analgesia that is 50-fold less potent than the levorotatory

(-)-isomer (Laurel Gorman, Elliott et al. 1997). However, dextrorotatory (+)- isomers of both opioid agonists and antagonists have recently been shown to be active in various tissues. For example, dextrorotatory (+)-opioids were found to suppress analgesia mediated by levorotatory (-)-opioids (Wu, Thompson et al.

2005, Wu, Sun et al. 2006, Wu, Sun et al. 2006, Hutchinson, Zhang et al. 2010,

Tseng 2013). Many studies suggest that anti-analgesia stimulated by dextrorotatory (+)-opioids results from p38 MAPK activation mediated by an unidentified non-opioid receptor (Wu, Sun et al. 2006, Wu, Sun et al. 2006,

Tseng 2013). As such, the identification of non-classical opioid receptors, capable of interacting with either levorotatory (-)-opioids or dextrorotatory (+)- opioids, has been critical in understanding the non-opioid receptor-mediated signaling of these compounds.

Many non-opioid receptors, not necessarily other GPCRs even, have been implicated in mediating the effects of dextrorotatory (+)-opioids. One such receptor is toll-like receptor (TLR) 4, which is thought to bind both dextrorotatory and levorotatory opioid enantiomers, resulting in a non-stereoselective TLR4 activation (Hutchinson, Zhang et al. 2010). Another major receptor identified as a target for opioid receptor-independent signaling is the N-methyl-d-aspartate

(NMDA) receptor (NMDAR). Racemic methadone mixtures, which contain both methadone enantiomers, have been found to have non-competitive antagonistic activity at the NMDAR, resulting in the reduction of NMDA-induced

159 depolarization, which activates descending serotonin and noradrenaline pathways. While this effect has typically been attributed to the classically active levorotatory (-)-isomer, both enantiomers have similar affinity for the NMDAR and, furthermore, have been found to individually protect cortical neurons from

NMDA-mediated neurotoxicity (Choi and Viseskul 1988, Laurel Gorman, Elliott et al. 1997, Trescot, Datta et al. 2008). As such, the non-stereospecific binding of opioid ligands by NMDAR represents an opioid-independent signaling mechanism for certain opioids. A novel non-opioid binding site, NOX2, is thought to contribute to the inhibition of microglia overactivation and superoxide production stimulated by both dextrorotatory and levorotatory enantiomers of naloxone (Wang, Zhou et al. 2012). Additional targets for opioid receptor-

2+ independent signaling by classical opioids include voltage-gated Na and KATP channels, which are blocked and activated, respectively, by opioids without MOR activation, resulting in the inhibition of neuronal activity (Kim and Lemasters

2006, Hashimoto, Amano et al. 2009).

The functional consequences of opioid receptor-independent signaling are varied. In some cases, opioid receptor-independent signaling opposes the functional consequences of opioid receptor-dependent signaling, such as the anti-analgesic effects mediated by dextrorotatory (+)-opioids (Wu, Thompson et al. 2005, Wu, Sun et al. 2006, Wu, Sun et al. 2006, Hutchinson, Zhang et al.

2010, Tseng 2013). In other cases, opioid receptor-independent signaling represents a unique signaling pathway, such as the opioid-mediated neuroprotection facilitated by non-competitive opioid antagonism of the NMDAR

160 (Choi and Viseskul 1988, Laurel Gorman, Elliott et al. 1997, Trescot, Datta et al.

2008). Collectively, opioid receptor-independent signaling is found to mediate a wide variety of cellular functions. Endogenous opioids regulate innate immune responses by mediating nitrite release in a dose-dependent manner, with low concentrations of endogenous opioids inhibiting nitrite release and high concentrations stimulating release (Singh and Rai 2010). Additionally, both morphine enantiomers have been found to significantly inhibit microglial activation following LPS stimulation (Qian, Tan et al. 2007). Morphine has also been shown to increase cytosolic nitric oxide (NO) via the direct activation of KATP channels, preventing tumor necrosis factor (TNF) α- and Fas ligand (FasL)- mediated apoptosis (Kim and Lemasters 2006). Pain modulation by opioids may also occur through opioid receptor-independent signaling. It is found that the endogenous opioid dynorphin A can directly active bradykinin receptors to cause increased pain. Promiscuous dynorphin A binding to bradykinin receptors switches G protein signaling to incorporate Gαs, leading to increased PKA activity and the activation of L- and P/Q-type calcium channels, resulting in Ca2+ influx and increased pain sensations. Dynorphin A–mediated inhibition of N-type calcium channels through the activation of opioid receptors does not compensate for this bradykinin receptor mechanism (Altier and Zamponi 2006). As studies continue to investigate the opioid receptor-independent mechanisms of many clinically used opioids, a portrait of opioid action is emerging that suggests the functional activity of opioids mediated through opioid receptors only represent a portion of opioid activity, and that non-classical mechanisms have an equally 161 important role in the physiological effects of opioids (Maneckjee and Minna 1992,

Shukla and Lemaire 1994, Hatzoglou, Ouafik et al. 1995, Carpenter, Gent et al.

1996, Hatzoglou, Bakogeorgou et al. 1996, Hatzoglou, Bakogeorgou et al. 1996,

Hung, Tsai et al. 1998, Pugsley 2002, Xiao, Zhou et al. 2003, Kampa,

Papakonstanti et al. 2004, Murakawa, Hirose et al. 2004, Pugsley 2004,

Wollemann and Benyhe 2004, Farooqui, Geng et al. 2006, Ide, Minami et al.

2006).

5.3 Modulation of GPCR and Opioid Receptor Signaling

Pluridimensional efficacy is the phenomenon through which agonist binding of GPCRs results in the activation of multiple downstream effector pathways.

Initially, pluridimensional efficacy was thought to be the result of cell type-specific expression of effectors, such as G proteins, in addition to receptor heterogeneity.

However, there are comparatively fewer genes encoding G protein subunits than

GPCRs. In addition, it is now understood that multiple G protein subtypes bind a single GPCR, allowing for the activation of multiple signaling pathways by a single receptor. Furthermore, ligand-biased signaling has been shown for many

GPCRs, particularly opioid receptors, as the binding of different agonists and antagonists selectively activate distinct signaling cascades through an individual receptor (Maudsley, Martin et al. 2005, Rajagopal, Rajagopal et al. 2010). Given the promiscuity of G proteins and second messenger proteins, in addition to a limited effector pool and the potential for ligand-biased signaling, cellular mechanisms must be utilized in order to maintain GPCR signaling specificity. The major mechanism through which cells maintain signaling specificity is receptor 162 heterogeneity, which arises from the existence of multiple genes that encode similar, but distinct, receptors subtypes, in addition to alternative splicing of gene transcripts that produce various receptor isoforms (Maudsley, Martin et al. 2005).

Additional specificity of receptor activity may also be differentially modulated by regulatory proteins and kinases, which alter the activation state of G proteins and the receptor, respectively. Internalization of GPCRs, removing it from the cytoplasmic face of the cell, thereby decreasing ligand interactions, is an efficient mechanism through which cells regulate signaling mediated by chronic ligand exposure. And lastly, GPCRs may dimerize or oligomerize with one another to form receptor complexes with altered receptor pharmacology and signaling

(Maudsley, Martin et al. 2005, van Rijn, Whistler et al. 2010).

5.3.1 Regulators of G protein signaling

Following G protein activation and the dissociation of Gα and Gβγ subunits, the intrinsic GTPase activity of the Gα subunit hydrolyzes the bound GTP to

GDP. This facilitates the reassociation of the Gα and Gβγ subunits and quenches the G protein-dependent signaling cascade. However, the intrinsic enzymatic

GTPase activity of the Gαi/o subunit is particularly slow, with a GTP/GDP turnover rate of only 2–5 units per minute, and is not sufficient to rapidly deactivate G proteins in order to allow for subsequent activation. Therefore, regulatory proteins are necessary to enhance Gα protein GTPase activity and the recycling of the G protein subunits. Regulator of G protein signaling (RGS) proteins are a family of over twenty different molecules that are able to modulate the duration of

163 G protein signaling by binding active GTP-bound Gα subunits and accelerating the hydrolysis of GTP by over 100-fold, thereby acting as negative regulators of

G protein-dependent signaling. This negative regulation applies to both ligand- bound and constitutively active GPCRs, as both stimulate G protein-dependent signaling cascades (Neubig 2002, Xie, Li et al. 2007, Pasternak 2010, Traynor

2012, Wang and Traynor 2013). The activity of RGS proteins is facilitated by a conserved RGS homology domain, which serves as a target for GTP-bound Gα subunit binding (Xie, Li et al. 2007, Pasternak 2010, Wang and Traynor 2013). A variety of RGS proteins have been shown to regulate opioid receptor-mediated G protein signaling. Interactions between endogenous RGS proteins and the MOR attenuate MOR-mediated inhibition of adenylyl cyclase and stimulation of MAPK signaling cascades, altering opioid-mediated analgesia (Xie, Li et al. 2007,

Wang, Liu-Chen et al. 2009). RGS proteins show selectivity in which receptors they mediate. For example, RGS19 negatively modulates MOR-mediated activation of ERK1/2 and inhibition of adenylyl cyclase but does not have any effect on DOR or ORL1. This cannot be ascribed to characteristics of G proteins, as both the MOR and DOR recruit the Gαi/o protein subtypes. As such, structural differences between opioid receptor subtypes, particularly in the C-terminal domain, have been hypothesized to regulate specificity of RGS interactions

(Wang and Traynor 2013). Indeed, studies involving the exchange of MOR and

DOR C-terminal domain regions showed that replacement of the C-terminal domain facilitated the acquisition or loss of specific RGS protein interactions (Xie,

Li et al. 2007, Leontiadis, Papakonstantinou et al. 2009). In addition to RGS- 164 mediated regulation of opioid receptor-stimulated G protein signaling, the dynamic interaction between RGS proteins and opioid receptors also permits the regulation of RGS expression via opioid receptor signaling. Opioid treatment was found to increase both the levels and activity of various RGS proteins. However, this effect was variable depending on both the time of agonist exposure and the physiological region examined (Traynor 2012, Wang and Traynor 2013). The mechanism of opioid-mediated RGS expression is thought to involve MOR or

DOR activation of PKC and MAPK signaling pathways (Wang and Traynor 2013).

Therefore, the dynamic relationship between RGS proteins and opioid receptors is such that activation of opioid receptors initiates G protein activation, facilitating second messenger signaling that enhances the activity of RGS proteins while simultaneously increasing their expression, thereby promoting RGS-mediated hydrolysis of GTP-bound Gα proteins and quenching further opioid receptor signaling.

5.3.2 Receptor phosphorylation, desensitization, and internalization

As mentioned previously, post-translational modifications of GPCRs include palmitoylation at conserved cysteine residues as well as constitutive and/or ligand-mediated phosphorylation at conserved serine, tyrosine or threonine residues. Although little is known about the protein kinases responsible for constitutive GPCR phosphorylation, two different classes of protein kinases catalyze ligand-mediated phosphorylation. The first class of GPCR- phosphorylating kinases is comprised of a family of serine/threonine kinases aptly named G protein-coupled receptor kinases (GRKs), which includes seven 165 subtypes and is further divided into three subfamilies (Leurs, Smit et al. 1998,

Zhang, Xiong et al. 2009). These kinases are localized within the cytoplasm and require active Gβγ subunit-binding in order to localize to the cell membrane, where they are activated further through phosphorylation (Wang 2000). The second class of GPCR-phosphorylating kinases are second messenger- dependent protein kinases, which include PKA, PKC, and CaMKII (Leurs, Smit et al. 1998, Zhang, Xiong et al. 2009). As implied by the name, these kinases are activated by second messenger signaling cascades following GPCR activation.

The mechanism involved in GPCR phosphorylation following agonist binding requires conformational changes in a fourth intracellular loop region generated by the post-translational palmitoylation of a conserved cysteine residue within the proximal portion of the GPCR C-terminal domain. Agonist binding triggers the conformational changes necessary to increase depalmitoylating enzyme activity, thereby initiating removal of the palmitate moiety. Depalmitoylation of cysteine residues within the C-terminus permits the recruitment of GRKs and second messenger-dependent proteins kinases, although depalmitoylated GPCRs may have a higher affinity for GRKs (Surratt and Adams 2005). Recruited protein kinases are then able to phosphorylate serine, tyrosine or threonine residues, some located within conserved phosphorylation motifs, of the C-terminal domain.

However, the exact residues phosphorylated are dependent on the cell-type. As such, GRK and/or second messenger-dependent protein kinase-mediated phosphorylation of GPCRs represents a critical initiating step in a series of events that modulates receptor functions. These events include desensitization

166 of G protein signaling, internalization and down-regulation of receptor expression, and activation of G protein-independent signaling cascades (Kelly, Bailey et al.

2008, Zhang, Xiong et al. 2009).

Generally speaking, desensitization refers to the loss of response by

GPCRs to agonists through the uncoupling of G proteins from the activated receptor. The primary mechanism of GPCR desensitization was originally thought to involve GPCR phosphorylation by second messenger-dependent protein kinases like PKA and PKC until the discovery of GRKs, which have since been shown to play a central role in agonist-induced phosphorylation and desensitization as well. It is unclear exactly how phosphorylation by either class of kinases works to uncouple G proteins from the active GPCR; however, it is hypothesized that phosphorylation sterically hinders interactions between

GPCRs and G proteins. What is evident is that desensitization mediated by

GRKs or second messenger-dependent protein kinases are not identical. One key difference between the two kinase classes is that PKA and PKC are, in some instances, able to phosphorylate unbound, inactive GPCRs. This is thought to be responsible for the previously mentioned agonist-independent signaling mechanisms seen for various GPCRs. Another major difference between GRK- and second messenger-dependent protein kinase-mediated phosphorylation and desensitization is the concentration of agonists required to stimulate kinase activity. GRK-mediated phosphorylation typically requires much higher concentrations of ligand compared to second messenger-dependent protein kinases due to the amplification of PKA/PKC signals through cAMP generation.

167 Further complicating the interactions of GRKs and second messenger-dependent protein kinases is the fact the many GRKs are, themselves, phosphorylated and activated, and this is mediated by second messenger-dependent protein kinases

(Kelly, Bailey et al. 2008, Luttrell 2008). However, the greatest distinction between GRK- and second messenger-dependent protein kinase-mediated phosphorylation is the mechanism through which they facilitate desensitization of

GPCR signaling. The mechanism through which second messenger-dependent protein kinase-mediated GPCR phosphorylation promotes receptor desensitization is poorly characterized. In contrast, GRK-mediated phosphorylation facilitates receptor desensitization by increasing receptor affinity for β-arrestins, although GRKs may also facilitate receptor desensitization by directly binding to G proteins, particularly Gαq (Leurs, Smit et al. 1998, Kelly,

Bailey et al. 2008, Feng, Li et al. 2011).

Receptor desensitization occurs through two, temporally distinct pathways.

Short-term desensitization occurs through the inhibition of G protein coupling and is the result of both second messenger-dependent kinase-mediated and GRK- mediated phosphorylation of GPCR C-terminal domain and intracellular loop domain. However, GRK-mediated phosphorylation is not sufficient to completely desensitize GPCR signaling and, as such, utilizes a second mechanism that involves the selective recruitment of auxiliary proteins. The first proteins recruited are β-arrestins, which binds with high affinity to agonist-occupied, GRK- phosphorylated receptors, inhibiting G protein interactions and thus inducing short-term desensitization. In addition to promoting short-term desensitization, as 168 well as activating G protein-independent signaling, including MAPK cascades, β- arrestins also facilitate long-term receptor desensitization by mediating receptor internalization and trafficking. The mechanism of receptor internalization involves

β-arrestin-mediated targeting of the GRK-phosphorylated receptor to clathrin- coated pits (Leurs, Smit et al. 1998, Luttrell and Lefkowitz 2002, DeWire, Ahn et al. 2007, Barki-Harrington and Rockman 2008, Kelly, Bailey et al. 2008, Calebiro,

Nikolaev et al. 2010, Gurevich 2013). Agonist-dependent interactions between

GRKs and PI3K mediate the translocation of an adaptor protein, AP-2, to the plasma membrane, where it interacts with β-arrestin-receptor complexes to promote the direct binding of clathrin to β-arrestin, which promotes receptor internalization within trafficking endosomes referred to as clathrin-coated vesicles

(Anderson 1998, Brodsky, Chen et al. 2001, Barki-Harrington and Rockman

2008). The activity of β-arrestins is regulated by numerous factors. For example, the ubiquitination status of β-arrestins determines both the stability and trafficking of the internalized receptor to which it is bound (Barki-Harrington and Rockman

2008, Defea 2008) whereas dynamic phosphorylation cycles regulate both the localization and activity of β-arrestins in associating with GCPRs and internalization machinery (DeWire, Ahn et al. 2007, Barki-Harrington and

Rockman 2008, Defea 2008). Given this regulation, many GPCRs show ligand biases in receptor internalization and endocytic trafficking (Violin and Lefkowitz

2007). However, the mechanisms involved in ligand-biased β-arrestin signaling have not been fully resolved. One possibility is that heterogeneity in the

169 phosphorylation sites differentially promotes β-arrestin recruitment, which is plausible given that GRK-mediated phosphorylation occurs at both the C-terminal and the third intracellular loop. In particular, the conserved NPXXY motif within the C-terminal domain may be involved in ligand-biased β-arrestin signaling as its necessity in receptor internalization varies (Trapaidze, Keith et al. 1996,

Segredo, Burford et al. 1997, Gurevich 2013). Additionally, β-arrestins are able to bind non-phosphorylated receptors, suggesting that ligand-biased internalization by β-arrestins may also be mediated through a GRK-independent mechanism

(Gurevich 2013). Furthermore, GPCRs may be subject to agonist-independent internalization, assuming that the tertiary conformation of constitutively active receptors mimics that of agonist-bound receptors (Leurs, Smit et al. 1998).

Regardless of the mechanism that initiates receptor internalization, endocytic sorting of GPCRs ultimately terminates in one of two ways. Dephosphorylation of

GPCRs within clathrin-coated vesicles targets the receptor back to the plasma membrane and, as such, they are recycled. Conversely, internalized receptors can be targeted to lysosome and/or proteasome systems, where they are enzymatically degraded, resulting in a down-regulation of receptor expression

(Leurs, Smit et al. 1998, Belcheva and Coscia 2002, Kelly, Bailey et al. 2008,

Calebiro, Nikolaev et al. 2010, Wang, Sun et al. 2010).

Many physiological aspects of opioids, such as desensitization, resensitization, tolerance, and dependence, involve phosphorylation and trafficking of opioid receptors following agonist exposure. As with other GPCRs, acute desensitization is mediated through the phosphorylation of agonist- 170 activated receptors, subsequent β-arrestin recruitment, uncoupling of G proteins, and endocytosis of receptors into clathrin-coated pits, while long term desensitization is mediated by lysosomal degradation of internalized receptors and the altered genetic expression facilitated by G protein-dependent and - independent pathways (Henriksen and Willoch 2008, Zhang, Chen et al. 2008,

Schmid and Bohn 2009, Dang, Chieng et al. 2011). There are over 20 serine, tyrosine and threonine residues throughout the intracellular loop and C-terminal domains of the MOR that are accessible to protein kinases and, as such, are potential sites for GRK- or second messenger-dependent-kinase mediated phosphorylation. Basal phosphorylation of tyrosine residues within the first and second intracellular loops determine signaling efficacy while selective phosphorylation of certain serine or threonine residues within the MOR C- terminal domain are predicted to mediate receptor trafficking (Kramer and Simon

1999, Wang, Chang et al. 2002, Johnson, Christie et al. 2005, Wang, Chen et al.

2008, Zhang, Xiong et al. 2009). For example, it is predicted that the unique agonist-induced phosphorylation motif TXXXPS in the C-terminal domain of opioid receptors is subject to phosphorylation by specific GRK subtypes, as well as second messenger-dependent kinases (Kramer and Simon 1999, Wei, Law et al. 2004). Phosphorylation of MORs at this motif and other residues is generally assumed to produce results typical of other GPCRs, including acute desensitization, receptor internalization and trafficking, and long-term desensitization of receptor activity (Zhang, Xiong et al. 2009). GRKs appear to be the primary kinases utilized by MORs following agonist binding, as certain

171 subtypes have been shown to be required for C-terminal domain phosphorylation and subsequent desensitization (Celver, Lowe et al. 2001, Zhang, Xiong et al.

2009). However, second messenger-dependent kinases, including CaMKII, PKA, and PKC, have also been suggested to phosphorylate MORs (Kramer and Simon

1999, Zhang, Xiong et al. 2009, Feng, Li et al. 2011). As with most GPCRs,

GRK-mediated phosphorylation promotes β-arrestin recruitment to the active

MOR, leading to receptor desensitization and internalization within clathrin- coated pits (Zhang, Chen et al. 2008, Feng, Li et al. 2011). Far less is understood about second messenger-dependent kinase-mediated phosphorylation of MORs. Evidence suggests that PKC-mediated phosphorylation may be able to mimic the short-term desensitization mediated by

GRK phosphorylation, as it is also able to disrupt G protein coupling. However,

PKC-mediated phosphorylation inhibits MOR internalization, demarcating a clear distinction between GRK and second messenger-dependent kinase function

(Feng, Li et al. 2011).

The MOR was the first GPCR shown to exhibit ligand-biased β-arrestin recruitment, as studies indicated that enkephalins and certain opioids, such as

DAMGO and etorphine, stimulate receptor internalization while other opioids, like morphine, do not. Ligand-biased signaling is due to relative differences in agonist potency and the individual ability of agonists to stimulate GRK-mediated phosphorylation and to recruit β-arrestins (Keith, Murray et al. 1996, Zhang,

Ferguson et al. 1998, Connor, Osborne et al. 2004, von Zastrow 2004, Waldhoer,

Bartlett et al. 2004, Violin and Lefkowitz 2007, Raehal and Bohn 2008, Zhang, 172 Xiong et al. 2009, Berger and Whistler 2010, Imai, Sudo et al. 2011, Raehal,

Schmid et al. 2011). This has also been shown to occur with other classical opioid receptor subtypes, although the mechanisms are not identical (Jordan,

Cvejic et al. 2000, Kam, Chan et al. 2004, Melief, Miyatake et al. 2010). Evidence in support of a GRK-dependent mechanism is seen in the fact that, whereas both morphine and etorphine effectively activate the MOR and cause short-term desensitization, only etorphine induces GRK-mediated phosphorylation, resulting in long-term desensitization through receptor internalization. The inability of morphine to induce GRK-mediated phosphorylation results in a lack of β-arrestin binding and MOR endocytosis. However, morphine signaling becomes indistinguishable from etorphine when GRK proteins are overexpressed, with both agonists promoting β-arrestin binding and MOR internalization (Zhang,

Ferguson et al. 1998, Ferguson 2001, Raehal and Bohn 2008). It is hypothesized that the mechanism of ligand-biased signaling involves differences in the conformational changes induced by agonist binding, suggesting the existence of multiple agonist-specific active receptor conformations with unique affinities for

GRK-mediated phosphorylation (Zhang, Ferguson et al. 1998, Ferguson 2001,

Beaulieu 2005, Perez and Karnik 2005, Raehal and Bohn 2011). As such, certain amino acid residues exhibit ligand-biased phosphorylation mediated by the specific recruitment of either GRK subtypes or second messenger-dependent kinases, including PKA, PKC, CaMKII, and MAPKs (Wang 2000, Wang, Chang et al. 2002, Schulz, Mayer et al. 2004, Johnson, Christie et al. 2005, Perez and

Karnik 2005, Kelly, Bailey et al. 2008, Zhang, Xiong et al. 2009, Chu, Zheng et al. 173 2010, Wang, Chabot et al. 2011). Generally, agonists with relatively low intrinsic efficacies do not promote GRK-mediated phosphorylation due to low Gβγ activity, which is inadequate to localize GRKs to the cell membrane and, therefore, does not promote β-arrestin-mediated internalization (Melief, Miyatake et al. 2010).

Adding to the complexity of ligand-biased signaling is the fact that MOR activity displays cell-type specific regulation, possibly as the result of cell-type-dependent expression of GRKs and second messenger-dependent kinases (Zhang, Xiong et al. 2009). Therefore, ligand-biased signaling through the MOR is generated from the unique conformational changes induced by ligand binding, resulting in ligand- specific active receptor conformations that uniquely regulate the recruitment of

GRK and second messenger-dependent kinases and the accessibility of potential phosphorylation residues, thereby altering the balance between GRK- and second messenger-dependent kinase-mediated phosphorylation and, in turn, regulating both short-term and long-term desensitization mechanisms.

5.3.3 Receptor oligomerization

The classical paradigms of GPCR ligand binding, signal transduction, desensitization, and internalization generally assume that receptors exist and function as monomeric units (Devi 2001, Milligan 2004, Terrillon and Bouvier

2004). However, it is now understood that the classical GPCR model is an oversimplification and that, in reality, receptors from all three GPCR classes interact with one another to form homomers, consisting of identical receptors, and heteromers, consisting of non-identical receptors. Additionally, these

174 interactions can occur between monomeric GPCRs, forming dimers, or multimeric GPCRs, to form oligomers. Multiple domains within the GPCR, including the N-terminal and/or the C-terminal domains have all been suggested to contribute to GPCR oligomerization. Additionally, computational studies of transmembrane regions suggest that junctions between GPCRs may involve interactions between the fifth and sixth transmembrane domain as well as interactions between the second and third. The interactions between these

GPCR domains may be facilitated by covalent (disulfide) and/or non-covalent

(ionic or hydrophobic) interactions; however, exact mechanisms vary between

GPCR classes as well as individual receptor interactions. As for the subcellular localization of GPCR oligomeric assembly, two possibilities exist. GPCR dimers could assemble in the endoplasmic reticulum, as proteins are synthesized, and transported to the cell membrane as complete multimeric units. As these multimeric units are synthesized at the earliest point of protein production, agonist treatment would have little effect on oligomer assembly. Alternatively,

GPCRs could be synthesized and transported to the cell membrane as monomeric units. The assembly of GPCR multimeric structure occurs after transmigration, and may be enhanced or inhibited in an agonist-dependent fashion. The reality of GPCR oligomerization is that it occurs through a combination of these two mechanisms (Devi 2001, Bai 2004, Milligan 2004,

Terrillon and Bouvier 2004, Lambert 2010, Palczewski 2010). As such, there is no general consensus as to the role of agonist-promoted assembly of GPCR oligomers, although it is generally accepted that this is a rare event for GPCR,

175 unlike other receptor types (i.e. tyrosine kinase receptors) (Bai 2004, Terrillon and Bouvier 2004).

The exact functional consequences of GPCR oligomerization are still being characterized, as they are dependent on the unique composition of the dimer or oligomer. However, it is evident that receptor oligomerization is a pivotal aspect of GPCR structure and function. As such, GPCR trafficking, signaling, and pharmacology show distinct differences between multimeric GPCRs and the monomeric units of which they are comprised. Hetero-oligomerization of several

GPCRs generates novel binding pockets, resulting in the induction of unique signaling cascades. The pharmacological profiles of heteromeric receptors are distinct from those of their individual receptor components as well as from the collective signaling profile expected from co-expression, and may represent changes in the G protein subtypes coupled (Lee, O'Dowd et al. 2003, Bai 2004,

Hebert 2008). Homo- and hetero-oligomerization may also serve as a mechanism of endoplasmic reticulum (ER) quality control, as the interactions involved in oligomer assembly may also mask specific ER retention signals and hydrophobic regions that would otherwise inhibit transport to the plasma membrane (Bai 2004, Terrillon and Bouvier 2004). Likewise, protein stability is highly variable between oligomerized receptors and their individual subcomponents, with lengths of association ranging from seconds to weeks. This suggests that some GPCRs exist within a monomer-oligomer equilibrium, adding a further layer of complexity to GPCR multimer function (Lambert 2010).

Receptor hetero-oligomerization may also have inhibitory effects by inactivating

176 the signaling of one or all of the subcomponent receptors (Bai 2004). Given the vast amount of pharmaceuticals that target GPCRs, the functional impact of

GPCR oligomerization is of critical importance when considering possible secondary effects (Hebert 2008).

Studies examining opioid receptor functions, specifically those of the DOR and KOR, were the first to suggest that GPCR heterodimerization could generate pharmacological diversity. Since this discovery, homomers of all three classical opioid receptors, as well as heteromers of DOR/KOR, DOR/MOR, and

MOR/KOR have all been identified. Furthermore, classical opioid receptors can form heteromers with additional GPCRs, including chemokine receptors (Smith and Lee 2003, Gomes, Gupta et al. 2004, Maudsley, Martin et al. 2005, Gray,

Coupar et al. 2006). Opioid receptor multimers are assembled through interactions between select domains in the C-terminal domain. This is interesting, as multimer assembly of most GPCRs does not involve this region (Cvejic and

Devi 1997, Bai 2004, Fan, Varghese et al. 2005). Evidence shows that opioid multimers, particularly MOR/DOR heteromers, are formed intracellularly but are retained in the Golgi, ubiquitinated, and degraded. Multiple chaperone proteins are therefore necessary to facilitate the transport of MOR/DOR heteromers to the cell surface, suggesting a mechanism of regulating MOR/DOR heteromer expression. As such, MOR/DOR heteromer trafficking appears to be shifted towards the DOR, as DOR monomers are also retained intracellularly, within the

ER, and associate with chaperone proteins to facilitate trafficking to the plasma membrane (Ong and Cahill 2014). The functional consequences of these opioid

177 homomers and heteromers have since been characterized and show effects at every level of receptor functioning (Gomes, Jordan et al. 2000, Gomes,

Filipovska et al. 2002, Levac, O'Dowd et al. 2002, Kivell, Day et al. 2004,

Waldhoer, Bartlett et al. 2004, Drake, Chavkin et al. 2007, Muller, Glattard et al.

2008, Gupta, Mulder et al. 2010). First, ligand affinity for certain µ-selective opioids is decreased by MOR/DOR heteromer assembly, presumably due to alterations in the extracellular domains which comprise the ligand binding pocket

(Jordan and Devi 1999, Maudsley, Martin et al. 2005, Ong and Cahill 2014). Most of the ligands identified to bind opioid multimers are also ligands of monomer opioid receptors, suggesting some level of conservation in binding sites.

However, a bivalent ligand, with chemical moieties of both µ- and δ–specific ligands, was recently found to be selective for MOR/DOR heteromers, indicating that multimer binding regions also display unique properties (Ong and Cahill

2014). Second, opioid receptor heterodimerization alters G protein selectivity and coupling. For example, MORs and DORs show decreased Gαi coupling when co- expressed with the chemokine receptors CCR5 and CCR2 (Terrillon and Bouvier

2004). Additionally, activation of co-expressed MORs and DORs stimulates PTX- insensitive G protein-dependent pathways, suggesting that MOR/DOR heteromers associate with PTX-insensitive G proteins like Gαz as opposed to the classical Gαi/o subtype (Lee, O'Dowd et al. 2003, Bai 2004, Maudsley, Martin et al. 2005). This results in distinct downstream signaling cascades for opioid receptor multimers. In contrast to MOR and DOR monomers, which initiate rapid, transient ERK1/2 phosphorylation through Gαi/o-stimulated PKC signaling, 178 MOR/DOR heteromers initiate delayed, persistent ERK1/2 phosphorylation through either Gαz or β-arrestin-mediated signaling cascades (Rozenfeld, Abul-

Husn et al. 2007, Ong and Cahill 2014). Finally, opioid heteromers show distinct differences in desensitization and internalization (von Zastrow 2004). For example, etorphine-mediated internalization of DORs is inhibited when DORs and co-expressed with KORs, which are not internalized by etorphine (Jordan and Devi 1999, Maudsley, Martin et al. 2005). Likewise, the post-internalization trafficking of MOR/DOR heteromers is shifted towards the DOR, as monomeric

MORs are typically recycled following internalization, but MOR/DOR heteromers are degraded (Ong and Cahill 2014). Therefore, the overall significance of opioid receptor oligomerization is that a diverse pharmacokinetic profile is generated from a relatively few number of opioid receptors subtypes due to the unique characteristics of opioid heteromers (Lee, O'Dowd et al. 2003).

5.3.4 Divergent signaling of opioid receptor isoforms

As stated previously, constitutive and alternative splicing of pre-mRNA transcripts accounts for the disproportionate amount of proteins produced from the relatively small number of protein encoding genes. This process involves the selective inclusion and exclusion of defined RNA nucleotide sequences, termed exons or introns, from the mature mRNA transcript, resulting in multiple mRNA transcripts with unique nucleotide sequences. Translation of these alternatively spliced transcripts produces various isoforms of a given protein that differ in their amino acid sequence and, as such, are differentially subjected to post- translational modifications and protein folding. Their unique amino acid 179 sequence, post-translational modifications, and tertiary structure cause many isoforms to display enzymatic activity, ligand binding, cellular localization, and protein stability that is distinct from other isoforms of the same protein

(Lipscombe 2005, Li, Lee et al. 2007, Hui 2009, Markovic and Challiss 2009).

The physiological significance of alternative splicing is seen in the fact that 15%-

50% of all human genetic disorders, including various cancers, muscular dystrophy, cystic fibrosis, asthma, and type I diabetes, arise from mutations affecting proper splicing (Matlin, Clark et al. 2005, Markovic and Challiss 2009).

Many of these disease-linked isoforms belong to the GPCR family of proteins

(Markovic and Challiss 2009). Therefore, the generation of functionally distinct isoforms through alternative splicing represents a critical mechanism through which GPCR signaling is regulated.

Over half of all GPCRs contain two or more exons and, although this does not definitively mean they are alternatively spliced, it suggests that many GPCRs exist in various isoforms. Obvious functional effects are found in GPCR splicing patterns that alter conserved motifs required for classical GPCR structure, G protein binding, and activating downstream signaling cascades, such as the

D/ERY, XBBXXB, and NPXXY(X) consensus sequences. However, given the low sequence homology between GPCR families, potential functional consequences are predicted based of broad structural changes within the N- and C-terminal domains and transmembrane regions instead of defined amino acid sequences.

As such, the GPCR structure can be divided into functional regions and changes within these regions, due to either mutations or alternative splicing events, are

180 predicted to have distinct functional consequences. The extracellular N-terminal domain, described previously, is involved in ligand binding. As such, variations or truncations of the N-terminal domain due to alternative splicing may result in altered ligand binding. If binding is altered to such a degree that ligands cannot activate the receptor, overexpression of the GPCR isoform(s) expressing this alternative N-terminal domain may result in a dominant-negative effect. Similarly, alterations of the extracellular loop structures may alter ligand binding.

Transmembrane regions of GPCRs are critical for proper tertiary structure, trafficking to the cell membrane, and maintaining the inactive and active conformations of the receptor. Alternative transmembrane sequences, particularly within the seventh transmembrane domain, may impair receptor trafficking and membrane expression, decreasing receptor concentrations and resulting in dominant negative phenotypes. Additionally, the presence of premature stop codons anywhere between the first and seventh transmembrane domains generates a truncated GPCR variant. Due to the absence of one or multiple transmembrane domains, these truncated GPCR isoforms may localize as cytoplasmic or secreted soluble proteins, resulting in vastly different mechanisms of action (Markovic and Challiss 2009). GPCR intracellular loop structures typically help facilitate G protein selectivity and binding through the establishment of activation and selectivity domains. Accordingly, variant structures at these two functional domains may alter the fidelity of G protein subtype selectivity or the kinetics of G protein coupling/uncoupling and may even result in increased constitutive activity (Milligan 2003, Wong 2003, Markovic and

181 Challiss 2009). Finally, the C-terminal domain represents one of the most important functional regions of GPCRs, containing a variety of palmitoylation and phosphorylation motifs that regulate receptor activity, signaling, and trafficking.

GPCRs with alternatively spliced C-terminal domains exhibit distinct GPCR signaling, receptor internalization, and protein-protein interactions with receptor kinases and β-arrestins in addition to distinctly regulating constitutive activity of the receptor (Milligan 2003, Markovic and Challiss 2009). Consequently, alternative splicing of GPCRs has the potential to greatly alter receptor function through sequence and structural changes within the transmembrane domains, extracellular and intracellular loops, and N- and C-terminal domains.

Although all opioid receptors are alternatively spliced to some extent, the

MOR shows extensive splicing patterns within the coding regions of every major

GPCR structural domain, including the transmembrane domains, extracellular and intracellular loops, and N- and C- terminal domains. As such, MOR isoforms can be categorized into multiple classes based on their structural and functional similarities. The first class consists of MOR isoforms that are typically generated through alternative 3’ splice site selection and comprise full-length receptor variants. These isoforms share identical N-terminal domains, transmembrane regions, and intra- and extracellular loop structures. In following, these isoforms are highly selective for µ-selective opioids and show little variability in receptor binding affinities, as their conserved sequences encode the binding pocket domain. However, the distal C-terminal domains of these isoforms are altered due to the utilization of alternative, suboptimal 3’ splice sites within the C-terminal 182 domain encoding exon 4, the substitution of exon 4 with an alternative exon, or the exclusion of exon 4 entirely followed by intron retention. The majority of MOR isoforms, including MOR-1A and MOR-1X, belong to this class. The variant C- terminal domains of these isoforms are differentially palmitoylated, ubiquitinated, and phosphorylated and, as a result, display distinct regional and cell-type specific localizations, G protein coupling, desensitization, internalization, and post-endocytic sorting. Additionally, C-terminal splicing greatly impacts both the potency and efficacy of µ-selective agonists. The selective incorporation or exclusion of putative phosphorylation sites in the C-terminal domain of MOR isoforms alters ligand-biased signal transduction pathways, most likely due to differential recruitment of receptor kinases and β-arrestins. For example, morphine and DAMGO are typically regarded as stimulating different levels of receptor phosphorylation; however, certain variants show equal levels of phosphorylation and, furthermore, internalization by these two compounds.

Similar differences in ligand-mediated internalization can be seen for many C- terminal domain variants of the MOR. As a result, some MOR isoforms modulate second messenger signaling, including adenylate cyclase, Ca2+/NFAT, and

MAPK activity, with distinct differences. This change in ligand-biased signaling among C-terminal domain isoforms may provide a better understanding of the complex pharmacology of µ-selective opioids, particularly that of morphine and morphine metabolites. (Zimprich, Simon et al. 1995, Rossi, Leventhal et al. 1997,

Schulz, Schreff et al. 1997, Koch, Schulz et al. 1998, Pan, Xu et al. 1999,

Abbadie, Gultekin et al. 2000, Abbadie, Pan et al. 2000, Abbadie, Pan et al. 183 2000, Pan, Xu et al. 2000, Abbadie, Pasternak et al. 2001, Koch, Schulz et al.

2001, Pasternak 2001, Abbadie, Rossi et al. 2002, Stander, Gunzer et al. 2002,

Wu, Mizoguchi et al. 2002, Narita, Imai et al. 2003, Bolan, Pan et al. 2004, Cadet

2004, Horner and Zadina 2004, Pasternak, Pan et al. 2004, Pasternak 2004,

Waldhoer, Bartlett et al. 2004, Pan, Xu et al. 2005, Pan 2005, Pan, Xu et al.

2005, Pasternak 2005, Surratt and Adams 2005, Zhang, Pan et al. 2006, Doyle,

Rebecca Sheng et al. 2007, Oldfield, Braksator et al. 2008, Schnell and

Wessendorf 2008, Tanowitz, Hislop et al. 2008, Song, Choi et al. 2009,

Pasternak 2010, Pasternak and Pan 2011, Dever, Xu et al. 2012, Pasternak and

Pan 2013, Xu, Xu et al. 2014).

A second class of MOR isoforms are generated by the substitution of exon

1 with exon 11 and frequently results in the loss of the first transmembrane region and the development of a unique N-terminal domain that protrudes into the intracellular region as opposed to the extracellular environment. As exon 11 is upstream of the exon 1 distal and proximal promoter regions, expression of exon 11 containing variants is controlled by a novel promoter region upstream of exon 11. As expected, expression of these N-terminal variants produces a diminished response to certain opioids, with no effect seen to others, suggesting a change in the selective binding of certain ligands. Evidence from in vivo studies using exon 1 and exon 11 knockout mice suggests that these variants are particularly important for heroin and M6G activity as well as mediating the actions of novel opioid compounds, such as 3-Iodobenzoylnaltrexamide 1 (IBNtxA), that lack side-effects of respiratory depression, physical dependence, and rewarding

184 behavior typically associated with µ-selective compounds (Rossi, Pan et al. 1995,

Schuller, King et al. 1999, Pan, Xu et al. 2001, Pan 2002, Abbadie, Pan et al.

2004, Pasternak 2004, Waldhoer, Bartlett et al. 2004, Pasternak 2005, Klein,

Rossi et al. 2009, Pan, Xu et al. 2009, Xu, Xu et al. 2009, Pasternak 2010,

Majumdar, Grinnell et al. 2011, Mizoguchi, Watanabe et al. 2011, Pasternak and

Pan 2011, Xu, Xu et al. 2011, Majumdar, Subrath et al. 2012, Pasternak and Pan

2013, Xu, Xu et al. 2013, Wieskopf, Pan et al. 2014, Xu, Xu et al. 2014).

Additionally, the substitution of exon 1 for exon 11 may result in MOR variants with cellular and molecular functions completely opposite of classical MORs. This is demonstrated by the exon 11 variant MOR-1K, which is retained in the cytoplasm where it couples Gαs, as opposed to Gαi/o. In following, activation of

MOR-1K was found to enhance cAMP, Ca2+, and NO production and resulted in cellular excitation, as opposed to the classical MOR-mediated cellular inhibition

(Gris, Gauthier et al. 2010).

A group of severely truncated MOR receptors comprises the third class of

MOR isoforms. These variants are produced by transcription initiation at the exon

11 promoter region but excise the majority of recognized exons, including exons

2 and/or 3, from their final mRNA transcript. Given that exons 2 and 3 encode the majority of the MOR transmembrane domains, these variants only contain a single transmembrane region. As such, these membranes do not bind opioid ligands nor are they expressed in a typical manner within the plasma membrane.

Instead, these variants are thought to function as receptor chaperones to reduce

ER-associated degradation of full-length MOR variants, enhancing receptor 185 expression (Pan, Xu et al. 2001, Mizoguchi, Wu et al. 2002, Pan 2002, Cadet,

Mantione et al. 2003, Pasternak and Pan 2013, Xu, Xu et al. 2013, Xu, Xu et al.

2014). In support of this, MOR-1 and the SV1 and SV2 isoforms of the MOR have been found to dimerize either during or shortly after translation resulting in inhibited ligand binding (Choi, Kim et al. 2006). Interestingly, certain single transmembrane MORs appear to compliment certain six transmembrane MORs and their physical interaction has been shown; however, the functional significance of this association has yet to be characterized (Abbadie, Pan et al.

2004).

In addition to alternative splicing, OPRM1 polymorphisms have the potential to alter mRNA transcript sequences. The OPRM1 gene displays high polymorphism relative to other GPCR genes, with over 100 polymorphisms identified in the human OPRM1 gene. However, a large majority of the SNPs detected within OPRM1 occur within non-coding regions rather than translated sequences, with coding polymorphism frequencies around 1% (Mayer and Hollt

2001, Ide, Han et al. 2005). Polymorphisms within non-coding regions, specifically within the 3’-UTR, of MORs may regulate the rate of translation and degradation of mRNA, thereby modulating OPRM1 activity and, ultimately, may be correlated with individual sensitivity to opioids (Ide, Han et al. 2005, Han,

Kasai et al. 2006). Likewise, polymorphisms within coding regions, despite their infrequent occurrence, have significant effects on MOR functions. This includes a serine-to-proline mutation of the conserved RXXS motif within the third intracellular loop of the MOR, responsible for ligand-induced G protein activation

186 through CaMK II mediated phosphorylation (Mayer and Hollt 2001, Lotsch and

Geisslinger 2005). Likewise, polymorphisms of the XBBXXB motif within the third intracellular loop, as well as mutations within the sixth transmembrane domain, may lead to the constitutive activation of PTX-sensitive G proteins by MORs or, conversely, may reduce agonist potency (Huang, Li et al. 2001). Overall, nearly

30 distinct polymorphisms within the transmembrane and extracellular loop domains of MORs have been found to affect ligand binding affinity and potency

(Chavkin, McLaughlin et al. 2001), while over 30 additional polymorphisms within the transmembrane, intracellular loop, and C-terminal domains of MORs alter G protein coupling, receptor phosphorylation, desensitization, internalization, recycling, and constitutive activity (Chavkin, McLaughlin et al. 2001, Huang, Li et al. 2001, Mayer and Hollt 2001, Lotsch and Geisslinger 2005, Pang, Ithnin et al.

2012). Complicating the issue of functional MOR polymorphisms is the fact that many have been identified within alternatively spliced MOR isoforms. Although the functional significance of MOR isoform polymorphisms is poorly characterized, these isoforms, in conjunction with several SNPs, are understood to have important physiological signifigance in opioid sensitivity and addiction

(Lotsch and Geisslinger 2005, Kreek and LaForge 2007, Klein, Rossi et al. 2009,

Ravindranathan, Joslyn et al. 2009, Pang, Ithnin et al. 2012), as some polymorphisms in the MOR-1K (Shabalina, Zaykin et al. 2009, Diatchenko,

Robinson et al. 2011) and MOR-1X (Pang, Ithnin et al. 2012) variants have been found to alter opioid drug response, while others have not (Smith, Doyle et al.

2005, Mayer and Hollt 2006). Therefore, MOR polymorphisms, in addition to

187 alternative splice variants, display unique cellular and molecular functions that contribute to the variability seen in the clinical response to opiates. As such, additional characterization of MOR polymorphisms and isoforms will provide valuable insight into MOR pharmacology (Ravindranathan, Joslyn et al. 2009).

5.4 Results

5.4.1 Comparison of MOR-1 and MOR-1X amino acid sequences and predicted functional motifs

The MOR isoforms MOR-1 and MOR-1X are generated through alternative splicing mechanisms that involve the incorporation of exons 1, 2, and

3 and the mutually exclusive incorporation of either exon 4 or exon X, respectfully, as the terminal exon. It is therefore not surprising that the amino acid sequence of MOR-1 and MOR-1X are over 99% similar, as indicated by

BLAST sequencing of the predicted translated protein. Accordingly, MOR-1 and

MOR-1X have identical extracellular N-terminal domains, transmembrane domains, and extracellular and intracellular loops, including a conserved DRY motif in the 2nd intracellular loops, as these regions are transcribed by the conserved exons 1, 2, and 3. Additionally, the proximal portion of the C-terminal domain, which contains a palmitoylated cysteine residue and the an agonist- induced phosphorylation motif TXXXPS, expressed as TREHPS and evolutionarily conserved among opioid receptors (Wei, Law et al. 2004), is conserved between the MOR-1 and MOR-1X receptors (Figure 5.1). Therefore, potential functional differences between MOR-1 and MOR-1X will be attributed to

188 the unique distal portion of the C-terminal domain encoded by the alternatively spliced exon. Given that the C-terminal domains of many GPCRs are the site of phosphorylation reactions essential for initiating conformational changes and

GPCR signal transduction, this study sought to identify predicted phosphorylation motifs within the unique C-terminal domains of MOR-1 and MOR-1X. The unique portion of the MOR-1 C-terminal domain encoded by exon 4 is unremarkable, containing only 12 additional amino acid residues and no additional phosphorylation motifs (Figure 5.1A), as predicted by the kinase-specific phosphorylation site prediction tool NetPhosK (Blom, Sicheritz-Ponten et al.

2004). Comparatively, the unique portion of the MOR-1X C-terminal domain encoded by exon X is much larger, containing nearly 60 additional amino acid residues and multiple phosphorylation motifs, including 2 serine residues predicted to serve as PKA phosphorylation sites as well as a second copy of the evolutionarily conserved agonist-induced phosphorylation motif TXXXPS, expressed as TAPSPS (Figure 5.1B). Therefore, despite the two receptors being nearly identical, MOR-1X has a greater potential for phosphorylation than MOR-1 due to the unique portion of the C-terminal domain encoded by the alternative exon X.

189 A. B. MOR-1 MOR-1X

C C

T T R R E E H H P P S S

L E N L E A E L P I P S L S T C A P L P A P L D Y R V L P G Q L P G P Y V V L C G Q E L A W I

L H S S C L R G N T A P S P S G G A F L L S

Palmitate Conserved Residue PKA Phosphorylation Site Conserved Sequence Non-conserved Residue Plasma Membrane Conserved Opioid Receptor Agonist-Induced Phosphorylation Motif

Figure 5.1: Comparison of MOR-1 and MOR-1X amino acid sequences and predicted functional motifs. Comparison of the primary amino acid sequences of A. MOR-1 and B. MOR-1X was performed using the National Center for

Biotechnology Information (NCBI) BLAST, Swiss Institute of Bioinformatics

ExPASy Translate, and NetPhosK tools online. Predicted conservation of subcellular localization is demonstrated by insertion into the plasma membrane as shown, with the 7 transmembrane regions, intracellular and extracellular loops, and amino acid sequences conserved between MOR-1 and MOR-1X represented by a solid line, except where indicated. Non-conserved amino acid residues are shown individually and highlighted accordingly.

5.4.2 Activation of MAPK cascades by MOR-1X is distinct from MOR-1

Opioid agonists are known to stimulate numerous signaling cascades, including MAPK (Gutstein, Rubie et al. 1997, Schulz, Eisinger et al.

2004). Given that the activation of these pathways is determined primarily by the phosphorylation state of the receptor, and that MOR-1 and MOR-1X show distinct structural differences in their phosphorylation potential due to their unique

190 C-terminal domains, it is possible that MOR-1 and MOR-1X have distinct variations in MAPK pathway activation. Therefore, to identify changes in MAPK signaling of MOR-1 and MOR-1X, this study examined the signaling of MOR-1 and MOR-1X individually in the HEK293 cell line, which does not endogenously express opioid receptors. HEK293 cells transfected with plasmids expressing either MOR-1 or MOR-1X were assessed using a human phospho-MAPK array that detects relative phosphorylation of 26 different kinases, including 9 MAPKs.

Results showed distinct differences in MAPK signaling in cells expressing MOR-1 and MOR-1X (Figure 5.3), with the most divergent signaling observed within the

ERK/RSK signaling cascade (Figure 5.2). Expression levels of phosphorylated

ERK1/2 in vector-transfected cells were not prominently affected by treatment with 1µM morphine for 15 minutes (Figure 5.2B, lanes 1-2; Figure 5.2C, lanes 1-

2). However, expression levels of phosphorylated ERK1/2 were increased in both pCMV6-MOR-1-transfected cells (Figure 5.2B, lanes 3-4; Figure 5.2C, lanes 3-4) and pCMV6-MOR-1X-transfected cells (Figure 5.2B, lanes 5-6; Figure 5.2C, lanes 5-6). Interestingly, pCMV6-MOR-1-transfected cells, but not pCMV6-MOR-

1X-transfected cells, exhibited a significant response to a 15 minute treatment of

1µM morphine, with expression levels of phosphorylated ERK1 increasing and

ERK2 decreasing, but still remaining significantly higher than vector-transfected controls (Figure 5.2B, lanes 3-6; Figure 5.2C, lanes 3-6).

Expression of phosphorylated p90 RSK1 and 2 (RSK1/2), downstream multi-functional effectors of the ERK1/2 pathway, as well as the related MSK2 also exhibited significant differences between pCMV6-MOR-1 and pCMV6-MOR- 191 1X-transfected cells. This difference was most prominent for phosphorylated

RSK1, as it was significantly increased in pCMV6-MOR-1-transfected cells

(Figure 5.2D, lane 3) but significantly decreased in pCMV6-MOR-1X-transfected cells (Figure 5.2D, lane 5). Furthermore, treatment with 1µM morphine for 15 minutes significantly reduced phosphorylated RSK1 expression to baseline levels in pCMV6-MOR-1-transfected cells (Figure 5.2D, lane 4) but significantly increased its expression above baseline levels in pCMV6-MOR-1X-transfected cells (Figure 5.2D, lane 6). Expression of phosphorylated RSK2 exhibited a similar pattern of inverse regulation, as treatment with 1µM morphine for 15 minutes significantly reduced expression below baseline levels in pCMV6-MOR-

1-transfected cells (Figure 5.2E, lane 4) but significantly increased its expression in pCMV6-MOR-1X-transfected cells (Figure 5.2E, lane 6). However, unlike phosphorylated RSK1, expression levels of phosphorylated RSK2 were not significantly altered by the constitutive activity of either MOR-1 or MOR-1X nor were the effects of morphine significantly different from constitutive receptor activity (Figure 5.2E, lanes 3-6). Expression of phosphorylated MSK2 closely resembled that of phosphorylated RSK1, with expression being significantly increased in pCMV6-MOR-1-transfected cells (Figure 5.2F, lane 3), although pCMV6-MOR-1X-transfected cells did not exhibit a constitutive decrease (Figure

5.2F, lane 5). Furthermore, treatment with 1µM morphine for 15 minutes reduced and increased expression in pCMV6-MOR-1 and pCMV6-MOR-1X-transfected cells, respectively (Figure 5.2F, lanes 3-6), although this was only significant for pCMV6-MOR-1X-transfected cells (Figure 5.2F, lanes 5-6). 192 A. No Treatment 1µM Morphine Coordinate Target Phosphorylation Site A1, A2 Reference 1 2 A21, A22 Reference B3, B4 Akt1 S473 B5, B6 Akt2 S474 Vector B7, B8 Akt3 S472 B9, B10 Akt pan S473, S474, S472 B11, B12 CREB S133 B13, B14 ERK1 T202/Y204 B15, B16 ERK2 T185/Y187 B17, B18 GSK-3α/β S21/S9 B19, B20 GSK-3β S9 3 4 C3, C4 HSP27 S78/S82 C5, C6 JNK1 T183/Y185

MOR-1 C7, C8 JNK2 T183/Y185 C9, C10 JNK3 T221/Y223 C11, C12 JNK pan T183/Y185, T221/Y223 C13, C14 MKK3 S218/T222 C15, C16 MKK6 S207/T211 C17, C18 MSK2 S360 D3, D4 p38α T180/Y182 5 6 D5, D6 p38β T180/Y182 D7, D8 p38δ T180/Y182 D9, D10 p38γ T183/Y185 MOR-1X D11, D12 p53 S46 D13, D14 p70 S6 Kinase T421/S424 D15, D16 RSK1 S380 D17, D18 RSK2 S386 D19, D20 TOR S2448 E19, E20 PBS F1, F2 Reference

* 200 B. 200C. * C. 180 180 * * * 160 160 * * * 140 * 140 *

120 120

100 100

80 80

60 60

40 40 pErk2 Protein Expression (% Control) Expression Protein pErk2 pErk1 Protein Expression (% Control) Expression Protein pErk1 20 20

0 0 S 1 2 3 4 5 6 Panel7 8 9 10 11 121 2 3 4 5 6 Panel7 8 9 10 11 12 - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) + + - - - - Vector + + - - - - Vector - - + + - - MOR-1 - - + + - - MOR-1 - - - - + + MOR-1X - - - - + + MOR-1X

D. 250 E. 200 F. 200 * * 180 180

200 160 160 * p = 0.06 140 140 * * * * 150 120 120 * 100 100 * 80 100 * * 80 60 60

50 40 40 MSK2 Protein Expression (% Control) Expression MSK2 Protein pRSK1 Protein Expression (% Control) Expression Protein pRSK1 20 20 pRSK2 Protein Expression (% Control) Expression Protein pRSK2

0 0 0 1 2 3 4 5 6 Panel7 8 9 10 11 121 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 12 - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) + + - - - - Vector + + - - - - Vector + + - - - - Vector - - + + - - MOR-1 - - + + - - MOR-1 - - + + - - MOR-1 - - - - + + MOR-1X - - - - + + MOR-1X - - - - + + MOR-1X

Figure 5.2: Divergent ERK/RSK signaling in MOR-1- and MOR-1X- transfected HEK293 cells constitutively and following morphine treatment.

A. Protein lysates from vector-transfected (1), vector-transfected, morphine- treated (2), pCMV6-MOR-1-transfected (3), pCMV6-MOR-1-transfected, morphine-treated (4), pCMV6-MOR-1X-transfected (5), and pCMV6-MOR-1X-

193 transfected, morphine-treated HEK293 cells (6) were used in a human phospho-

MAPK array (R&D Systems) examining the expression of multiple, phosphorylated MAPK proteins (table). B-F. Semi-quantitative analysis of phosphorylated ERK1, ERK2, RSK1, RSK2, and MSK expression, respectively, in vector-transfected (lane 1), vector-transfected, morphine-treated (lane 2), pCMV6-MOR-1-transfected (lane 3), pCMV6-MOR-1-transfected, morphine- treated (lane 4), pCMV6-MOR-1X-transfected (lane 5), and pCMV6-MOR-1X- transfected, morphine-treated HEK293 cells (lane 6) was performed using the

Image J software to determine normalized band intensities (mean ± SEM; * = p ≤

0.05).

194 A. 200 B. 200 C. 200 180 180 180

160 160 160

140 140 140

120 120 * 120 * 100 100 100 * * * * 80 * 80 80

60 60 60

40 40 40 pAkt3 Protein Expression (% Control) Expression pAkt3 Protein pAkt1 Protein Expression (% Control) Expression pAkt1 Protein 20 (% Control) Expression pAkt2 Protein 20 20

0 0 0 1 2 3 4 5 6 7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 12 - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) + + - - - - Vector + + - - - - Vector + + - - - - Vector - - + + - - MOR-1 - - + + - - MOR-1 - - + + - - MOR-1 - - - - + + MOR-1X - - - - + + MOR-1X - - - - + + MOR-1X

D. 200 E. 200 F. 200 180 180 180

160 160 160

140 140 140

120 * 120 120 * * * * * 100 100 * 100

* 80 80 80 * * 60 60 60

40 40 40

MKK3 Protein Expression (% Control) Expression MKK3 Protein 20 (% Control) Expression MKK6 Protein 20 pAkt Pan Protein Expression (% Control) Expression pAkt Protein Pan 20

0 0 0 1 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 12 - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) + + - - - - Vector + + - - - - Vector + + - - - - Vector - - + + - - MOR-1 - - + + - - MOR-1 - - + + - - MOR-1 - - - - + + MOR-1X - - - - + + MOR-1X - - - - + + MOR-1X

G. 200 H. 200 I. 200

180 * 180 180 * * 160 * 160 160

* 140 140 140 * * * 120 * 120 120 * * * 100 100 100 * * 80 80 80

60 60 60

40 40 40 MAPK Protein Expression (% Control) Expression MAPK Protein MAPK Protein Expression (% Control) Expression MAPK Protein MAPK Protein Expression (% Control) Expression MAPK Protein ! α β 20 20 20 p-p38 p-p38 p-p38 0 0 0 1 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 12 - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) + + - - - - Vector + + - - - - Vector + + - - - - Vector - - + + - - MOR-1 - - + + - - MOR-1 - - + + - - MOR-1 - - - - + + MOR-1X - - - - + + MOR-1X - - - - + + MOR-1X

J. 200 K. 200 L. 200 180 180 180

160 160 160 * * * * * * * * 140 140 140

* 120 120 120 * * * * * * 100 100 100

80 80 * 80 *

* 60 60 60

40 40 40 MAPK Protein Expression (% Control) Expression MAPK Protein δ pJnk1 Protein Expression (% Control) Expression Protein pJnk1 20 20 (% Control) Expression Protein pJNK2 20 p-p38 0 0 0 1 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 12 - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) + + - - - - Vector + + - - - - Vector + + - - - - Vector - - + + - - MOR-1 - - + + - - MOR-1 - - + + - - MOR-1 - - - - + + MOR-1X - - - - + + MOR-1X - - - - + + MOR-1X

195 M. 200 N. 200 O. 200 180 180 180

160 160 160

140 140 * * * 140

120 120 * 120 * 100 * 100 100 * * * * 80 * * 80 80

60 60 60

40 40 40 pJnk3 Protein Expression (% Control) Expression Protein pJnk3

20 20 (% Control) Expression Protein pHSP27 20 pJnk pan Protein Expression (% Control) Expression Protein pan pJnk

0 0 0 1 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 12 - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) + + - - - - Vector + + - - - - Vector + + - - - - Vector - - + + - - MOR-1 - - + + - - MOR-1 - - + + - - MOR-1 - - - - + + MOR-1X - - - - + + MOR-1X - - - - + + MOR-1X

P. 200 Q. 200 R. 200 180 180 180

160 160 160

140 140 140 * 120 120 120 * 100 100 100 * * 80 80 * 80 * * 60 60 60 Protein Expression (% Control) Expression Protein Protein Expression (% Control) Expression Protein β / β 40 40 α 40

20 20 20 pGSK-3 pGSK-3

p-p70 S6 Kinase Protein Expression (% Control) Expression Protein S6 Kinase p-p70 0 0 0 1 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 12 - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) + + - - - - Vector + + - - - - Vector + + - - - - Vector - - + + - - MOR-1 - - + + - - MOR-1 - - + + - - MOR-1 - - - - + + MOR-1X - - - - + + MOR-1X - - - - + + MOR-1X

S. 200 T. 200 U. 200 180 180 180

160 160 160

140 140 140

120 120 120 * * 100 * 100 * 100 * * * 80 * 80 80

60 60 60

40 40 40 p-p53 Protein Expression (% Control) Expression Protein p-p53 pTOR (% Control) Expression Protein

20 20 (% Control) Expression Protein pCREB 20

0 0 0 1 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 112 2 3 4 5 6 Panel7 8 9 10 11 12 - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) - 1 - 1 - 1 Morphine (µM) + + - - - - Vector + + - - - - Vector + + - - - - Vector - - + + - - MOR-1 - - + + - - MOR-1 - - + + - - MOR-1 - - - - + + MOR-1X - - - - + + MOR-1X - - - - + + MOR-1X

Figure 5.3 Divergent MAPK signaling in MOR-1- and MOR-1X-transfected

HEK293 cells constitutively and following morphine treatment. A-U. Semi- quantitative analysis of a human phospho-MAPK array (R&D Systems) examining phosphorylated Akt1, Akt2, Akt3, Akt pan, MKK3, MKK6, p38α MAPK, p38β MAPK, p38γ MAPK, p38δ MAPK, Jnk1, Jnk2, Jnk3, Jnk pan, HSP27, p70

S6 kinase, GSK-3β, GSK-3α/β, TOR, p53, and CREB expression, respectively, in

196 vector-transfected, untreated HEK293 cells (lane 1) vector-transfected HEK293 cells treated with 1µM morphine for 15 minutes (lane 2), pCMV6-MOR-1- transfected, untreated HEK293 cells (lane 3), pCMV6-MOR-1-transfected

HEK293 cells treated with 1µM morphine for 15 minutes (lane 4), pCMV6-MOR-

1X-transfected, untreated HEK293 cells (lane 5), and pCMV6-MOR-1X- transfected HEK293 cells treated with 1µM morphine for 15 minutes (lane 6) was performed using the Image J software (mean ± SEM; * = p ≤ 0.05)..

5.5 Discussion

As members of the Class A GPCR family, conventional opioid receptors contain many structural features conserved among GPCRs, such as D/ERY,

XBBXXB, and NPXXY motifs, as well as many structural features uniquely conserved among opioid receptor subtypes, such as the TXXXPS motif within the

C-terminal domain. These structural regions regulate both the transition between active and inactive receptor conformations and the accessibility of functional domains to interacting proteins, such as kinases and β-arrestins, which subsequently facilitate the activation of G protein-dependent and –independent signaling pathways in a receptor- and agonist-specific manner. Given the close relationship receptor structure has to receptor function, alterations in receptor structure, such as those generated by alternative splicing events, are predicted to have distinct functional consequences depending on the region in which they occur. Variations or truncations of the N-terminal and extracellular loop domains may result in altered ligand binding whereas disruption of transmembrane

197 regions will likely alter receptor trafficking and agonist-induced conformational changes. Additionally, variations in the intracellular loop and C-terminal domains are likely to alter intracellular signaling and constitutive receptor activity, as these regions facilitate the selective recruitment of GPCR interacting proteins, including

G proteins, receptor kinases, small GTPases, and β-arrestins, and the subsequent palmitoylation, phosphorylation, signal transduction, internalization, trafficking, and down-regulation or recycling of the receptor. Therefore, highly similar variants may still exhibit unique pharmacokinetic properties if variations fall within particular, highly conserved functional regions.

The alternatively spliced isoform MOR-1X is generated through alternative splicing mechanisms that replace the terminal exon of MOR-1 with an alternative exon cassette, resulting in both receptors being 99% conserved overall and containing identical N-terminal, loop, and transmembrane domains as well as a proximal portion of the C-terminal domain, all of which contain conserved functional motifs, including the DRY and TREHPS motifs, essential for GPCR- and MOR-specific signaling (Figure 5.1). As such, any functional differences between MOR-1 and MOR-1X will likely be attributed to the unique distal portion of the C-terminal domain, a region encoded by the terminal exon of both MOR-1 and MOR-1X and the site of phosphorylation reactions essential for initiating conformational changes and GPCR signal transduction. Examination of the predicted primary sequence of this unique region showed that while the distal portion of the MOR-1 C-terminal domain, encoded by exon 4, does not contain any identifiable phosphorylation motifs (Figure 5.1A), the distal portion of the

198 MOR-1X C-terminal domain, encoded by exon X, contains multiple phosphorylation motifs, including two PKA phosphorylation sites and a second copy of the opioid receptor-specific agonist-induced phosphorylation motif

(Figure 5.1B) suggesting that, despite a high degree on conservation between these two receptors, the MOR-1X isoform has a greater potential for phosphorylation, both constitutively and following agonist binding, than the stereotypical MOR-1 isoform and may stimulate unique signaling cascades, such as MAPK.

Investigation of MAPK signaling differences between MOR-1 and MOR-1X receptors found that the expression of several MAPK proteins displayed distinct differences (Figure 5.3). The most distinct effects were observed in the ERK/RSK signaling cascade, with expression of phosphorylated ERK1/2 being constitutively elevated in both pCMV6-MOR-1-transfected and pCMV6-MOR-1X- transfected cells but with only pCMV6-MOR-1-transfected cells exhibiting a significant response to morphine (Figure 5.2B, lanes 3-6; Figure 5.2C, lanes 3-6).

Furthermore, downstream effectors p90 RSK1 (Figure 5.2D) and p90 RSK2

(Figure 5.2E), and the related MSK2 (Figure 5.2F) exhibited an inverse pattern of morphine-mediated phosphorylation/dephosphorylation between pCMV6-MOR-1- transfected and pCMV6-MOR-1X-transfected cells. Additionally, it should be noted that certain MAPK effector proteins exhibited statistically significant differences between pCMV6-MOR-1- and pCMV6-MOR-1X-transfected cells that may not represent significant functional differences, as changes were small, and, as such, may be an artifact of the single time point investigated, as the timeframe

199 for GCPR signal transduction ranges from seconds to hours. Therefore, divergent regulation of MAPK signaling, both constitutively and following morphine treatment, is exhibited by cells expressing either MOR-1 or MOR-1X and is likely mediated by the respective absence or presence of unique phosphorylation motifs in the distal C-terminal domain of these receptors, although this cannot be definitively concluded from the present study.

The exact mechanisms through which MOR-1 and MOR-1X distinctly alter

MAPK signaling is unclear, although multiple, mutually inclusive possibilities exist. First, opioid-mediated ERK1/2 signaling in HEK293 may be due to cell-type specific disparity of G protein and second messenger expression and may therefore not be an accurate model for MOR-1 and MOR-1X signaling in cell types that natively express these receptors. Second, virtually all GPCRs express some level of measurable constitutive activity, as is evident by the constitutive activity of both MOR-1 and MOR-1X exhibited here in certain MAPK signaling cascades. However, the extent to which constitutive activation occurs is highly inconsistent even between closely related GPCRs like MOR-1 and MOR-1X and, as such, unique motifs of MOR-1X that localize to the C-terminal domain, a region known to influence constitutive activity, may result in significantly different levels of constitutive activity between MOR-1 and MOR-1X even when expressed at equal levels. Finally, differences between the C-terminal domains of MOR-1 and MOR-1X may selective recruit interacting proteins, such as GRKs, second messenger protein kinases, RGS proteins, and, most notably, β-arrestins.

Regarding receptor kinase recruitment, there multiple serine, tyrosine and

200 threonine residues within the C-terminal domain of the MOR that are potential sites for GRK- or second messenger-dependent protein kinase-mediated phosphorylation, and the addition or subtraction of these residues by alternative splicing may drastically alter GRK- and second messenger-dependent protein kinase-mediated signaling. Typically, GRK-mediated phosphorylation requires a much higher agonist concentration than second messenger-dependent protein kinase-mediated phosphorylation; however, single exposures of weaker opioids, such as morphine, cannot effectively stimulate the second messenger signaling needed to activate second messenger-dependent protein kinases, instead requiring repeated MOR activation by chronic exposure to activate downstream signaling cascades such as ERK1/2. However, the additional PKA and PKC phosphorylation motifs in MOR-1X may allow for elevated recruitment of these second messenger-dependent protein kinase, therefore requiring less activation of upstream second messengers and facilitating the stimulation of second messenger-dependent protein kinase downstream signaling cascades at lower concentrations, shorter exposures, and by weaker opioids like morphine.

Regarding β-arrestin recruitment, selectivity of β-arrestins is often determined by the receptor C-terminal domain as well as specific GRK- and second messenger- dependent protein kinase-mediated phosphorylation of the receptor. More importantly, the recruitment of β-arrestins represents an important kinetic switch between G protein-dependent and G protein-independent signaling. The initial wave of MAPK signaling stimulated by G protein-dependent activation of second messengers and small GTPases is both rapid and transient, with peak signaling 201 occurring within seconds to minutes, and results in unique MAPK downstream signaling cascades, such as the translocation of ERK1/2 into the nucleus and the activation of ERK1/2 transcriptional pathways. However, displacement of G proteins by β-arrestins interrupts this G protein-dependent signaling and facilitates the construction of β-arrestin signaling complexes, which results in a second wave of unique MAPK downstream signaling cascades that are comparatively delayed in onset but more persistent than those initiated by G proteins. Due to the fact that β-arrestin signaling complexes are sequestered in the cytoplasm, these G protein-independent MAPK signaling cascades exhibit enhanced cytoplasmic signaling but diminished nuclear signaling. Therefore, differences between MOR-1 and MOR-1X in the recruitment of β-arrestins may alter the distinct physiological endpoints of MAPK signaling cascades that are temporally and spatially regulated through a two-phase signaling cascade; however, the kinetic differences between MOR-1 and MOR-1X signaling cannot be determined from the current study as it used a single time point.

202 CHAPTER 6 – OPIOIDS AND HIV-ASSOCIATED NEUROPATHOGENESIS

6.1 Mechanisms of Programmed Cell Death

Cellular viability and death are highly regulated process mediated by a series of complex signaling pathways that are collectively grouped into one of two broad categories: autophagy and apoptosis. Macroautophagy, often referred to simply as autophagy, is the process through which subcellular components are sequestered within vesicles, which are then fused to lysosomes and subsequently hydrolyzed. The digestion of subcellular structures has numerous physiological roles, including the regulation of free amino acid levels, provision of substrates for Krebs cycle catalysis and ATP production, clearance of toxic or unneeded protein aggregates, reduction of reactive oxygen species (ROS), prevention of neurodegeneration, suppression of tumor growth, eradication of intracellular microbes, and regulation of innate and adaptive immunity. Multiple, evolutionarily conserved gene products collectively known as Atg proteins, of which Beclin-1 and microtubule‐associated protein light chain 3 (LC3) are members, as well as PI3K initiate the formation of the autophagosome, a specialized organelle formed by the elongation and enclosure of a vesicular sac, or phagophore, around targeted cytoplasmic components. The process of autophagy is executed with the fusion of the autophagosome with a lysosome in order to form an autolysosome structure that catalyzes the digestion of the enclosed material. Low levels of autophagic activity occur under basal conditions as a method of recycling cellular components; however, this process is highly dynamic and, as such, can be rapidly induced by various stimuli. Starvation is the 203 most notable stress stimulus for the induction of autophagy but other stress stimuli, including hypoxia, ROS production, ER stress, and heat-shock, as well as various cellular factors, including hormonal, pharmacological, and immunological signals can influence autophagic activity (Kim, Rodriguez-Enriquez et al. 2007,

Mizushima and Yoshimori 2007, Mizushima, Yoshimori et al. 2010, Zhao, Zhu et al. 2010, Scherz-Shouval and Elazar 2011, Galluzzi and Kroemer 2013). This dynamic nature is necessary in order to maintain autophagic activity at the level required for proper cellular functioning in homeostatic and stress conditions.

Therefore, cellular health and viability is compromised by both insufficient and excessive levels of autophagy (Kim, Rodriguez-Enriquez et al. 2007).

The collective process of programmed cell death is responsible for the genetically determined elimination of cells during embryonic development and aging, the homeostatic maintenance of cell type populations in various tissues, and the overall viability of cells under physiological and pathological stress conditions. The classical method of programmed cell death is referred to as apoptosis and is distinguished from cellular death seen during necrosis as it does not stimulate an inflammatory response. This is due to the fact that the process of apoptosis does not trigger the release of cellular contents into the extracellular environment, rapidly induces phagocytosis by surrounding cells, and does not trigger the production of anti-inflammatory cytokines. Initiation of apoptosis occurs through one of three pathways, each of which requires specific signaling in order to activate an energy-dependent molecular signaling cascade. The perforin/granzyme pathway, which is mediated by T lymphocytes, is unique in

204 that it initiates apoptosis in a caspase-independent fashion, through the actions of granzyme A and B. Caspases are a family of proteolytic enzymes that typically cleave proteins at aspartic acid residues, although neighboring amino acid residues may dictate different specificities for various caspases. Ten major caspases have been identified to date and are categorized as initiator caspases

(caspase-2,-8,-9,-10), effector or executioner caspases (caspase-3,-6,-7) and inflammatory caspases (caspase-1,-4,-5). Under homeostatic conditions, caspases are normally expressed as inactive proenzymes. Stimulation of the extrinsic and intrinsic pathways by pathway-specific mechanisms activates unique initiator caspases through proteolytic cleavage of the proenzyme. This activates a caspase signaling cascade in which upstream caspases cleave and activate downstream proenzyme caspases, amplifying apoptotic signaling.

Therefore, it is typically accepted that activation of caspase cascades by either the extrinsic or intrinsic pathways irreversibly commits the cell to undergo apoptosis (Elmore 2007).

Extrinsic signaling pathways, also known as the death receptor pathways, initiate apoptosis through the activation of various transmembrane receptors.

Many of these death receptors belong to the TNF receptor gene superfamily, which is characterized by cysteine-rich extracellular domains and a conserved cytoplasmic domain, referred to as the death domain, that is essential for apoptotic signal transduction. The signaling mechanisms involved in the extrinsic pathway are best characterized by the actions of the FasL/FasR and

TNFα/TNFR1 models, although other, well-characterized death receptors (DR)

205 and their corresponding ligands include Apo3L/DR3, Apo2L/DR4 and

Apo2L/DR5. Ligand binding of death receptors initiates the recruitment of cytoplasmic adaptor proteins, such as Fas-associated death domain (FADD) and

TNFR1-associated death domain (TRADD) proteins, which then associate with inactive procaspases, such as procaspase-8. The subsequent formation of a death-inducing signaling complex (DISC) results in the autolytic cleavage of procaspase-8 to form the active initiator caspase, caspase-8. Activation of initiator caspases propagates the apoptotic signal through the activation of downstream effector caspase pathways (Brunet, Datta et al. 2001, Emeterio,

Tramullas et al. 2006, Elmore 2007, Garcia-Fuster, Ramos-Miguel et al. 2008).

However, activation of initiator caspases by the extrinsic pathway does not necessarily commit the cell to apoptosis, as numerous regulatory proteins, including c-FLIP and Toso, have been found to directly inhibit initiator caspase activity.

The intrinsic signaling pathway, also known as the mitochondrial pathway, initiates apoptosis through a diverse array of death receptor-independent stimuli that disrupt mitochondrial functioning. The nature of these stimulating factors can either be negative (e.g. the removal of necessary growth factors results in a failure to suppress intrinsic apoptotic signaling cascades), or positive (e.g. stimuli such as radiation, toxins, hypoxia, viral infections, and ROS directly activate apoptotic signaling cascades). Collectively, these positive and negative stimuli initiate conformational changes within the inner mitochondrial membrane by initiating the formation of mitochondrial permeability transition (MPT) pores,

206 which result in the loss of the mitochondrial transmembrane potential and the release of sequestered pro-apoptotic factors into the cytosol. The most recognizable of these pro-apoptotic factors is cytochrome c, which binds to Apaf-

1 and procaspases-9 to form a protein complex referred to as an apoptosome.

Autolytic cleavage of procaspases-9 within the apoptosome results in the formation of the active initiator caspase, caspase-9, and the subsequent activation of downstream effector caspases, including caspase-3, a key protease in mammalian apoptosis. Additional pro-apoptotic factors released from the mitochondrial inner-membrane space include Diablo/Smac and HtrA2/Omi, which promote apoptosis by blocking the activity of inhibitors of apoptosis proteins

(IAP). Late-stage mitochondrial-mediated apoptosis is characterized by the release of additional apoptotic proteins, including apoptosis inducing factor (AIF), endonuclease G, and caspase-activated DNase (CAD). AIF and endonuclease G both function in a caspase-independent manner by directly causing DNA fragmentation. Similarly, CAD directly causes DNA fragmentation; however, activation of CAD is dependent on caspase-3-mediated cleavage, which removes

CAD from its bound inhibitor ICAD (Brunet, Datta et al. 2001, Emeterio,

Tramullas et al. 2006, Elmore 2007, McGinnis, Gnegy et al. 2008). Regardless of the type of apoptotic stimuli present, the intrinsic, extrinsic, and perforin/granzyme pathways all converge a common pathway recognized as the terminal apoptotic pathway and referred to as the execution pathway. The characteristic morphological features associated with apoptosis, such as cell shrinkage, chromatin condensation, and phagocytosis of apoptotic bodies, are all

207 mediated by the execution pathway through the activation of effector caspases, such as caspase-3, caspase-6, and caspase-7. The subsequent activation of cytoplasmic endonucleases, which degrade nuclear material, and proteases, which degrade both nuclear and cytoskeletal proteins, results in disintegration of the cell into apoptotic bodies, which are rapidly phagocytized (Elmore 2007).

The generation of ATP, which is essential for cellular metabolism, occurs within the mitochondria through a series of oxidation and reduction reactions that transport protons from the mitochondrial matrix across the inner mitochondrial membrane and generate cytotoxic reactive oxygen species (ROS) byproducts, including H2O2 and superoxide (Kim, Rodriguez-Enriquez et al. 2007, Scherz-

Shouval and Elazar 2011). Therefore, precise mitochondrial events are essential for maintaining cellular viability and alterations of mitochondria structure and function not only represent required steps in the induction of early stage apoptosis but also serve as points of convergence between extrinsic and intrinsic signaling pathways (Elmore 2007, Kim, Rodriguez-Enriquez et al. 2007,

McGinnis, Gnegy et al. 2008). Regulation of these mitochondrial events is mediated by a wide variety of proteins, the most recognized of which belong to the Bcl-2 protein family. Members of the Bcl-2 protein family are divided into subfamilies of either anti-apoptotic proteins, which include Bcl-2, Bcl-x, Bcl-XL,

Bcl-XS, Bcl-w, and BAG, or pro-apoptotic proteins, which include Bax, Bcl-10,

Bak, Bid, Bad, Bim, Bik, and Blk (Jiang and Wu 1999, Yuan and Yankner 2000,

Mao, Liu et al. 2004, Elmore 2007). Interestingly, certain anti-apoptotic Bcl-2 family proteins are also known to inhibit autophagosome formation through

208 interactions with Beclin-1, further highlighting the importance of this protein family in regulating cell viability (Zhao, Zhu et al. 2010). Four conserved Bcl-2 homology domains, designated BH1-4, as well as a C-terminal transmembrane domain that serves to anchor the protein to either mitochondrial or other intracellular membranes are characteristic of many Bcl-2 family member proteins. As a result, many Bcl-2 family member proteins are localized to the ER, perinuclear membrane, or mitochondrial outer membrane (Jiang and Wu 1999, Li and Dou

2000, Yuan and Yankner 2000, Tsuruta, Masuyama et al. 2002). However, several proteins within the Bcl-2 family, including Bcl-2 and Bax, have both membrane-bound and soluble forms that are generated through alternative splicing mechanisms (Jiang and Wu 1999). Often, translocation of cytoplasmic

Bcl-2 family member proteins to the mitochondrial outer membrane is indicative of apoptosis. For example, inactive Bax primarily localizes to the cytoplasm due to the fact that the tertiary structure of inactive Bax sequesters the conserved C- terminal transmembrane domain within a hydrophobic pocket. Initiation of apoptosis causes a conformational change in Bax involving the release of the conserved C-terminal transmembrane domain from the hydrophobic pocket and resulting in the translocation and anchoring of active Bax into the mitochondrial outer membrane, where it facilitates the release of pro-apoptotic factors, including cytochrome C (Tsuruta, Masuyama et al. 2002, Schinzel, Kaufmann et al. 2004, McGinnis, Gnegy et al. 2008). In this manner, the collective activation and localization of pro- and anti-apoptotic Bcl-2 family member proteins regulates mitochondrial membrane permeability and the subsequent release of

209 sequestered pro-apoptotic factors (Jiang and Wu 1999, Brunet, Datta et al. 2001,

Tsuruta, Masuyama et al. 2002, Elmore 2007).

Expectedly, the processes regulating expression, translocation, and activation of Bcl-2 family member proteins involve downstream signaling cascades initiated by the extrinsic or intrinsic apoptotic pathways. For example, in addition to directly activating caspase-3, caspase-8, an initiator caspase of the extrinsic pathway, also facilitates translocation of Bid from the cytoplasm to the mitochondria (Brunet, Datta et al. 2001). Likewise, the activity of many Bcl-2 family member proteins is regulated by phosphorylation facilitated by JNK, ERK, and p38 MAPKs as well as factors downstream of MAPK signaling such as p90

RSK (Yuan and Yankner 2000, van Laethem, van Kelst et al. 2004, Cai, Chang et al. 2006). Expression of many Bcl-2 family member genes, such as those encoding Bim and Bax, is regulated by downstream transcription factors, like

FOXO and p53, that are activated in response to apoptotic stimuli (Brunet, Datta et al. 2001) while degradation of certain Bcl-2 family member proteins, such as

Bax, is regulated by an ATP-dependent ubiquitin-proteasome pathway (Li and

Dou 2000). Cross-interactions between pro- and anti-apoptotic Bcl-2 family member proteins also regulate expression, translocation, and activation of Bcl-2 family member proteins by serving as chaperones and inhibitors of one another.

Bcl-B, an anti-apoptotic Bcl-2 family member protein, has been shown to directly binds to Bax and suppress Bax-mediated apoptosis (Ke, Godzik et al. 2001).

Similarly, both Bax and Bad have been found to bind Bcl-2 and neutralize its anti- apoptotic function through poorly understood mechanisms (Jiang and Wu 1999,

210 Elmore 2007). As such, the execution of apoptosis by mitochondrial events is largely due to the relative ratio of active and inactive pro- and anti-apoptotic Bcl-2 family member proteins (Jiang and Wu 1999, Yuan and Yankner 2000, Elmore

2007).

Among the various extrinsic and intrinsic pathways involved in the initiation of apoptosis, the PI3K/Akt pathway has been found to play a central role, as inhibition of this pathway consistently reduces cell viability. Various receptors and second messenger proteins activate cytoplasmic PI3K through a Gβγ-dependent mechanism, resulting in PI3K-mediated regulation of Akt localization and activity.

Akt subsequently regulates cell viability through the maintenance of several key survival proteins, including direct and indirect regulation of Bcl-2 family member proteins and other mitochondrial factors (Yuan and Yankner 2000, Brunet, Datta et al. 2001, Burke 2007, Duronio 2008). Direct mechanisms of Akt-mediated regulation of mitochondrial events involve phosphorylation of both Bcl-2 family member proteins and additional apoptotic proteins, including caspases. In this manner, Akt is thought to directly phosphorylate caspase-9, Apaf-1 or IAPs in order to regulate apoptotic signaling. Furthermore, phosphorylation of specific

Bcl-2 family member proteins can disrupt cross-interactions with chaperone proteins, such as 14-3-3, and with other Bcl-2 family member proteins, thereby regulating their translocation and pro- or anti-apoptotic functions (Kennedy,

Wagner et al. 1997, Yuan and Yankner 2000, Brunet, Datta et al. 2001, Tsuruta,

Masuyama et al. 2002, Elmore 2007). Indirect mechanisms of Akt-mediated regulation of mitochondrial events involve the activation or inhibition of several

211 transcription factors, including CREB, NF-κB, and p53. For example, activation of

NF-κB by Akt results in the increased expression of certain anti-apoptotic Bcl-2 family member proteins as well as IAPs (Brunet, Datta et al. 2001). Additionally,

Akt can mediate mitochondrial events through a downstream effector, glycogen synthase kinase-3 (GSK-3). Two mammalian GSK-3 proteins, α and β, are encoded by separate genes but share 85% sequence homology overall and 98% sequence homology within the conserved kinase domain. Additionally, both GSK-

3α and GSK-3β gene products undergo constitutive and alternative splicing, generating short and long isoforms with unique tissue expression. In general,

GSK-3α and GSK-3β activity is inhibited by phosphorylation of the N-terminal S21 and S9 residues, respectively, and enhanced by phosphorylation of “T-loop” Y279 and Y216 residues, respectively. Mechanisms of inhibitory GSK-3 phosphorylation involve multiple protein kinases, including Akt, PKA, and p90 RSK. Likewise, multiple protein kinases facilitate GSK-3 activation. Interestingly, MAPKs specifically regulate GSK-3β activity through unique mechanisms, with p38

MAPK stimulating activity through phosphorylation of C-terminal S389 and T390 residues and ERK1/2 inhibiting activity through phosphorylation of the T43 residue. Both GSK-3α and GSK-3β function as serine/threonine kinases with multiple downstream substrates, which include regulatory proteins, enzymes, and transcription factors. As such, GSK-3 proteins mediate numerous physiological functions, including metabolism, transcription, and cell viability. Within the CNS,

GSK-3β is involved in neuronal migration, axonal remodeling, synaptogenesis,

212 synaptic plasticity, and synaptic transmission. Regarding cell viability, GSK-3 proteins exhibit both pro- and anti-apoptotic function. Pro-apoptotic functions are mediated through direct phosphorylation and activation of pro-apoptotic Bcl-2 family member proteins, such as Bax, in addition to the respective activation and inhibition of pro- and anti-apoptotic transcription factors, including CREB and p53. Anti-apoptotic mechanisms of GSK-3 activity are mediated through NF-κB signaling. Overall, multiple cellular factors, including cell type and specific cellular signaling, determine the overall effect of GSK-3 on apoptosis. (Doble and

Woodgett 2003, Franke, Hornik et al. 2003, Linseman, Butts et al. 2004,

Dewhurst, Maggirwar et al. 2007, Duronio 2008, Beaulieu, Gainetdinov et al.

2009, Medina and Wandosell 2011, Oksana Kaidanovich-Beilin 2011, Jacobs,

Bhave et al. 2012). Therefore, activation of the PI3K/Akt/GSK-3 pathway represents one of multiple mechanisms through which mitochondrial events associated with apoptosis and autophagy, including Bcl-2 family member protein localization and activity, are regulated. As such, extrinsic and intrinsic stimuli that promote PI3K/Akt activity, such as opioid receptor activation, may have a role in modulating cell viability.

6.1.1 Modulation of cell viability by opioids

Opioid receptor signaling has been shown to impact cellular viability through numerous signaling cascades. This includes the induction of autophagy by opioids through a G protein-dependent, PTX sensitive mechanism. While the exact mechanism of autophagic induction by opioids is not completely understood, morphine has been found to increase the Atg protein Beclin-1, an 213 essential component of autophagosome assembly. It is proposed that this shift in the ratio of Beclin-1 reduces its overall interaction with Bcl-2, thereby increasing the pool of unbound Beclin-1 and subsequently enhancing Beclin-1-mediated pro-autophagic activity. This hypothesis is supported by the observation that overexpression of Bcl-2 inhibits morphine-mediated autophagy. As such, the neuronal injury and cell death seen in chronic morphine treatment is partially attributed to the induction of this autophagic mechanism (Zhao, Zhu et al. 2010).

Opioid-mediated regulation of cell viability also involves modulation of extrinsic signaling pathways of apoptosis, as interactions between opioid signaling pathways and p53-dependent genes, such as FasR, FasL, and FADD, have been identified (Boronat, Garcia-Fuster et al. 2001, Singhal, Bhaskaran et al.

2002, Suzuki, Chuang et al. 2003, Tegeder, Grosch et al. 2003, Emeterio,

Tramullas et al. 2006, San-Emeterio and Hurle 2006, Yin, Woodruff et al. 2006,

Garcia-Fuster, Ramos-Miguel et al. 2008, Zhang, Chen et al. 2008). However, the most well characterized mechanisms of opioid-mediated regulation of cell viability involve cross-interactions with multiple factors of the intrinsic signaling pathway of apoptosis.

As described previously, opioid receptor activation facilitates PI3K/Akt signaling through G protein-dependent mechanisms and is implicated in the mediation of neuronal development, long term memory, synaptic plasticity, and neuronal survival (Polakiewicz, Schieferl et al. 1998, Law, Wong et al. 2000).

Therefore, it is not surprising that intrinsic apoptotic mechanisms are altered by opioid treatment through the activation of PI3K/Akt signaling. Interestingly,

214 opioids have a dual effect on apoptosis, inhibiting it in some instances while promoting it in others (Tegeder, Grosch et al. 2003, Chen, Cui et al. 2008, Cui,

Chen et al. 2008, Katebi, Razavi et al. 2013). The anti-apoptotic mechanisms of opioid activity are mediated through Gαi/o- and Gβγ-dependent activation of the

PI3K/Akt and ERK1/2 signaling pathways (Iglesias, Segura et al. 2003, Tegeder,

Grosch et al. 2003, Tegeder and Geisslinger 2004, Yin, Woodruff et al. 2006,

Sanchez-Blazquez, Rodriguez-Munoz et al. 2010). This culminates in the inhibition of intracellular and mitochondrial events associated with the induction of apoptosis, such as ROS accumulation and cytochrome c release (Lin, Li et al.

2007). Regulation of proteasomal degradation is also suggested to be involved in anti-apoptotic mechanisms of opioid activity, as morphine has been found to regulate various aspects of the ubiquitin-proteasome degradation pathway, including the 20S and 26S proteasomes, resulting in the enhanced ubiquitination and clearance of oxidized, misfolded, and pro-apoptotic proteins such as Bax

(Rambhia, Mantione et al. 2005, Cui, Chen et al. 2008, Zhang, Chen et al. 2008).

Pro-apoptotic mechanisms of opioid activity are mediated through p38

MAPK and GSK-3β signaling cascades that inhibit NF-κB activity (Tegeder,

Grosch et al. 2003, van Laethem, van Kelst et al. 2004, Yin, Woodruff et al. 2006,

Li, Sun et al. 2009, Xie, Li et al. 2010). Likewise, JNK signaling pathway activation and subsequent ROS accumulation are known to facilitate pro- apoptotic mechanisms of opioid activity (Lin, Wang et al. 2009, Gach, Wyrebska et al. 2011). Additional pro-apoptotic mechanisms of opioid activity, which are independent of Gαi, adenylyl cyclase, and PKA signaling, have also been 215 characterized and instead involve a p53 signaling pathway (Gach, Wyrębska et al. 2012). Ultimately, these mechanisms culminate in the modulation of mitochondrial events through dynamic changes in Bcl-2 family member protein activity (Li, Sun et al. 2009, Lin, Wang et al. 2009, Xie, Li et al. 2010, Gach,

Wyrebska et al. 2011, Gach, Wyrębska et al. 2012). Select opioid agonists promote apoptosis by concurrently up-regulating Bax and down-regulating Bcl-2, causing an increase in cytochrome C release and subsequent activation of caspase-3 (Singhal, Sharma et al. 1998, Singhal, Kapasi et al. 1999, Boronat,

Garcia-Fuster et al. 2001, Singhal, Bhaskaran et al. 2002, Berrios, Castro et al.

2008, Zhang, Chen et al. 2008, He, Li et al. 2011, Gach, Wyrębska et al. 2012).

Similarly, opioid antagonists protect against apoptosis by down-regulating Bax and Bad without altering Bcl-2 expression (San-Emeterio and Hurle 2006). The importance of Bcl-2 family member proteins in opioid-mediated apoptosis is highlighted by the fact that β-arrestin-dependent signaling inhibits opioid- mediated apoptosis through the activation of Akt and the inhibition of caspase-8, both of which regulate apoptotic signaling upstream of the mitochondria (Li, Sun et al. 2009, Zhao, Zhou et al. 2009). As such, opioids mediate apoptosis, evident in many CNS regions, including the parietal, frontal, temporal, occipital, entorhinal, pyriform, and hippocampal regions (Zhang, Chen et al. 2008), primarily through the dynamic regulation of pro- and anti-apoptotic Bcl-2 family member proteins.

Given the fact that different opioid treatments can stimulate mutually exclusive apoptotic pathways, even within the same cell type, predicting the

216 terminal result of opioid signaling on cell viability is particularly complex.

However, it appears that two primary determinants of whether opioids mediate pro-apoptotic or anti-apoptotic signaling cascades are the concentration of opioid agonists and the duration of exposure (Emeterio, Tramullas et al. 2006, Cui,

Chen et al. 2008). With respect to the time-dependent nature of opioid-mediated apoptosis, studies have shown that acute opioid treatment has little effect on cell viability, as measured by TUNEL and active caspase-3 expression. Furthermore, acute opioid exposure may protect against both extrinsic and intrinsic mechanisms through the down-regulation of FasL and Bax (Mao, Sung et al.

2002, Emeterio, Tramullas et al. 2006). In contrast, chronic opioid exposure is associated with increased levels of apoptosis. This is mediated through the up- regulation of multiple pro-apoptotic factors, including FasR/FasL, Bad, Bax, caspase-8 and caspase-3 expression (Mao, Sung et al. 2002, Emeterio,

Tramullas et al. 2006, Nasiraei-Moghadam, Kazeminezhad et al. 2010, Katebi,

Razavi et al. 2013, Li-Wei Liu 2013). This is accompanied, in some cases, by a concomitant down-regulation of Bcl-2 expression (Mao, Sung et al. 2002,

Nasiraei-Moghadam, Kazeminezhad et al. 2010, Li-Wei Liu 2013). However, with respect to the dose-dependent nature of opioid-mediated apoptotic, chronic morphine exposure has also been found to down-regulate Bax expression and protect against apoptosis at doses lower than those found to induce apoptosis

(Chen, Cui et al. 2008, Cui, Chen et al. 2008). Therefore, short-term administration of opioids as well as long-term administration of opioids specifically at low doses may stimulate anti-apoptotic signaling cascades,

217 whereas chronic, high dose administration of opioids exert pro-apoptotic effects mediated through both intrinsic and extrinsic apoptotic pathways (Emeterio,

Tramullas et al. 2006, Chen, Cui et al. 2008, Cui, Chen et al. 2008, Sanchez-

Simon, Zhang et al. 2010). Unfortunately, this general rule for opioid-mediated apoptotic signaling is further complicated by cross-interactions between opioid receptors subtypes and non-opioid receptors. For example, the anti-apoptotic signaling stimulated by high dose µ-selective agonist administration is partially attributed to non-specific interactions with DORs and KORs (Katebi, Razavi et al.

2013). Furthermore, inhibition of DORs by δ-selective antagonists promotes apoptosis, suggesting a mechanism of constitutive anti-apoptotic signaling by

DORs that may cross-react with apoptotic signaling mediated by other opioid receptor subtypes (Zhou, Guo et al. 2013). Likewise, cross-reactions with

NMDARs may regulate opioid receptor-mediated apoptosis, as co-administration with a non-competitive NMDAR antagonist mitigated the up-regulation of Bax and caspase-3 stimulated by opioid treatment (Mao, Sung et al. 2002). Therefore, while it is clearly evident that opioid receptor signaling impacts cell viability, the exact nature of opioid-mediated apoptotic signaling is highly dependent on the experimental parameters through which it is investigated.

6.2 Opioids & HIV Pathogenesis

In addition to their antinociceptive effects, many opioids stimulate profound immunosuppression, thereby increasing the susceptibility of individuals chronically using opioids, both clinically and illicitly, to various infections. The mechanism of opioid-mediated immunosuppression is thought to involve cross- 218 talk between immune system and CNS regulatory pathways; however, it is now understood that opioids also modulate immune system activity by directly interacting with immune cells. This direct interaction is mediated through the various opioid receptor subtypes expressed by immune cells and results in the modulation of their cytotoxic activity, proliferation, inflammatory molecule release, surface antigen expression, and antibody production (Taub, Eisenstein et al.

1991). While both endogenous and exogenous opioids modulate immune system activity and increase susceptibility to infection, the illicit use of opioids such as heroin, serves as an additional risk factor for the transmission of blood-borne pathogens, particularly HIV, through the sharing of contaminated syringes.

Among the nearly 16 million injection drug users (IDUs) across nearly 150 countries, an estimated 3 million IDUs, primarily within China, the United States, and Russia, are HIV-positive. As such, injection drug use has driven HIV epidemics in numerous countries, is the fastest growing risk factor for HIV transmission in the United States and the third-most frequently reported after male-to-male sexual contact and high-risk heterosexual contact, and, excluding epidemics in sub-Saharan Africa, accounts for nearly 30% of HIV infections globally (Taub, Eisenstein et al. 1991, Hauser, El-Hage et al. 2005, CDC 2009,

Vlahov, Robertson et al. 2010). Although the percentage of new HIV infections attributed to injection drug use has decreased substantially in the United States over the last decade, the comorbidity of HIV infection and injection drug abuse still presents a significant public health concern, as nearly half of HIV-positive

IDUs are unaware of their status (Volkow 2006). Furthermore, in addition to

219 increasing the risk of HIV transmission, injection drug abuse, specifically of opioids, alters the pathogenesis of HIV as well as enhances HIV-associated systemic and neurological complications, including deficits in attention, working, and episodic memory, executive function, decision-making, attention, concentration, and fine motor function (Hauser, El-Hage et al. 2005, Anand,

Springer et al. 2010). Therefore, understanding of the immunosuppressive effects of opioids, as well as their direct and indirect modulation of systemic and neurological HIV pathogenesis, is of the utmost clinical importance.

6.2.1 Opioid-mediated immunomodulation

In general, the immune system is divided into two separate components.

The initial immune response is mediated by the innate immune system and involves the complement system, natural killer (NK) cells, and phagocytic cells such as eosinophils, neutrophils, monocytes, and macrophages. A second phase of immune responses is mediated by the adaptive immune system, which is further subdivided into two categories; cell-mediated immune responses that are mediated by thymus-derived T lymphocytes and humoral immune responses that are mediated by bone-marrow derived, antibody producing B lymphocytes.

Collectively, adaptive immune responses involve the specific recognition, processing, and presentation of antigens followed by the subsequent B lymphocyte-mediated production of antibodies and T lymphocyte-mediated cytotoxicity (Roy and Loh 1996). Opioids have a profound effect on multiple aspects of both innate and adaptive immunity mechanisms. For example, chronic opioid treatment inhibits proliferation of macrophage progenitors mediated by 220 macrophage-colony stimulating factor (M-CSF). This subsequently compromises multiple functions of macrophages, including phagocytosis and the synthesis of superoxide (SO), nitric oxide (NO), and, most notably, pro-inflammatory cytokines (Rogers, Taub et al. 1990, Rouveix 1992, Bhargava, Thomas et al.

1994, Guan, Townsend et al. 1994, Roy and Loh 1996, Stefano, Scharrer et al.

1996, Sharp, Roy et al. 1998, Bonnet, Beloeil et al. 2008, Vassou, Bakogeorgou et al. 2008, Matsunaga, Isowa et al. 2009). Likewise, proliferation of lymphocytes, which include B, T, and NK cells, is inhibited by opioids and may be attributed to the opioid-mediated atrophy of the spleen and thymus (Carr 1991,

Rouveix 1992, Bhargava, Thomas et al. 1994, Roy and Loh 1996, Sharp, Roy et al. 1998, Bidlack 2000). Both acute and chronic morphine exposure modulate lymphocyte activity (Carr 1991, Rouveix 1992, Bhargava, Thomas et al. 1994,

Roy and Loh 1996, Stefano, Scharrer et al. 1996, Eisenstein and Hilburger 1998,

McCarthy, Wetzel et al. 2001) as well as inhibit antibody production (Weber,

Ikejiri et al. 1987, Carr 1991, Taub, Eisenstein et al. 1991, Guan, Townsend et al.

1994, Carr, Rogers et al. 1996, Bidlack 2000, McCarthy, Wetzel et al. 2001) presumably through JNK/c-Jun, p38/CREB, and/or PI3k/Akt signaling mechanisms (Vassou, Bakogeorgou et al. 2008). Many immune cells exhibit migratory behavior called chemotaxis, which is directed towards the site of inflammation or antigenic challenge and is mediated by a concentration gradient of signaling molecules. This important functional property is likewise influenced by opioids, with macrophage and lymphocyte migration being directed towards the opioid injection site (Guan, Townsend et al. 1994, Stefano, Scharrer et al.

221 1996, McCarthy, Wetzel et al. 2001, Chuang, Suzuki et al. 2005). Lymphocyte rolling and adherence, both important processes in chemotaxis, are also attenuated by opioid treatment (Ni, Gritman et al. 2000). Overall, opioids are considered to have an extensive immunosuppressive effect involving impaired proliferation and chemotaxis of immune cells as well as increased lymphocytic and phagocytic cell apoptosis, resulting in reduced effector cell responses, which include phagocytic and cytotoxic activity and the release of inflammatory molecules and antibodies (Taub, Eisenstein et al. 1991, Makman 1994, Bidlack

2000, Welters 2003, Chuang, Suzuki et al. 2005).

In contrast to the well-established immunosuppressive effects induced by opioids, certain opioid treatment conditions have been found to enhance immune system activity. For example, chronic opioid treatment markedly increases the synthesis of multiple inflammatory molecules, including TNFα, interleukin (IL)-1β,

IL-12, and interferon (IFN)-γ, while inhibiting the synthesis of anti-inflammatory cytokines like IL-4 and IL-10 (Guan, Townsend et al. 1994, Bidlack 2000, Wetzel,

Steele et al. 2000, Welters 2003, Rock, Hu et al. 2006). As with opioid-mediated cell viability, a major determinant of whether opioids enhance or inhibit immune system activity is the concentration of opioid agonists and antagonists present, with low concentrations often enhancing immune system activity while high concentrations often mediate immunosuppression (Janković and Radulović 1992,

Rouveix 1992). For example, morphine promotes NF-κB activation and TNFα production at low concentrations but suppresses these functions at high concentrations (Dinda, Gitman et al. 2005). The functional effect of opioids on 222 immune activity may also be determined by the types of opioids present, as endogenous opioid peptides and exogenous non-peptide opioids often have opposing functional effects (Guan, Townsend et al. 1994, Eisenstein and

Hilburger 1998, Berrios, Castro et al. 2008). Furthermore, the state of immune cell activation serves as a unique determinant of opioid functional effects on the immune system, as numerous cytokines and interleukins regulate opioid receptor expression in immune cells (Eisenstein and Hilburger 1998, Kraus, Lehmann et al. 2010). This is mediated through epigenetic mechanisms involving cytokine- and interleukin-mediated activation of transcription factors, including STAT1,

STAT3, STAT6 and GATA3, which result in chromatin remodeling, demethylation of the OPRM1 promoter region, and enhanced gene transcription and receptor expression (Borner, Stumm et al. 2007, Kraus, Lehmann et al. 2010). As such, opioid-mediated regulation of immune system activity involves complex, reciprocal interactions that may result in opposing functional effects depending on various factors.

The interactions through which opioids modulate immune system activity can be categorized as either direct or indirect. In support of direct interactions, multiple studies have found that various immune cells, including B lymphocytes,

T lymphocytes, monocytes, macrophages, and NK cells, express various opioid receptor subtypes (Bhargava, Thomas et al. 1994, Makman 1994, Chuang,

Killam et al. 1995, Gaveriaux, Peluso et al. 1995, Carr, Rogers et al. 1996, Chao,

Gekker et al. 1996, Roy and Loh 1996, Stefano, Scharrer et al. 1996, Madden,

Whaley et al. 1998, Sharp, Roy et al. 1998, Sharp 2003, Vallejo, de Leon-

223 Casasola et al. 2004, Dinda, Gitman et al. 2005, Berrios, Castro et al. 2008,

Ninkovic and Roy 2013). Not surprisingly, a wide variety of endogenous and exogenous opioids interact directly with opioid-receptor expressing immune cells, stimulating downstream signaling cascades that modulate proliferation, surface antigen expression, cytotoxic activity, and the synthesis and release of pro- and anti-inflammatory molecule among many other effects on cellular function (Taub,

Eisenstein et al. 1991, Chuang, Suzuki et al. 2005). This includes cell viability, as opioids have been found to modulate intrinsic and extrinsic signaling pathways within lymphocyte cells through mechanisms involving p38 MAPK, Bcl-2/Bax, p53, and FasR/FasL (Nair, Schwartz et al. 1997, Singhal, Kapasi et al. 1999, Hu,

Sheng et al. 2002, Singhal, Bhaskaran et al. 2002). Indirect mechanisms of opioid-mediated immunomodulation involve interactions with the autonomic nervous system and, in particular, the hypothalamic-pituitary-adrenal (HPA) axis

(Rouveix 1992, Bhargava, Thomas et al. 1994, Stefano, Scharrer et al. 1996,

McCarthy, Wetzel et al. 2001, Berrios, Castro et al. 2008). Activation of HPA neurons by opioids stimulates corticotropin-releasing hormone and adrenocorticotropic hormone (ACTH) secretion, which results in the subsequent release of various immunosuppressive compounds, including anti-inflammatory glucocorticoids, catecholamines such as epinephrine and norepinephrine, and prolactin (Rouveix 1992, Roy and Loh 1996, Bidlack 2000, Welters 2003, Dinda,

Gitman et al. 2005, Sacerdote 2008, Stefano and Kream 2008, Ninkovic and Roy

2013). Therefore, opioids modulate immune system activity by directly interacting

224 with immune system effector and accessory cells as well as by altering hormone signaling through the activation of HPA neurons.

6.2.2 Modulation of HIV infectivity by opioids

Given the profound immunosuppressive effects opioids often mediate, it is not surprising that the abuse of opioids has been found to increase the susceptibility to various infections, including HIV (Peterson, Sharp et al. 1990,

Taub, Eisenstein et al. 1991, McCarthy, Wetzel et al. 2001). Opioid abuse increases the susceptibility to HIV infection through numerous mechanisms, including increased exposure due to the use of contaminated syringes as well as systemic immunosuppression that diminishes the secretion of HIV-inhibitory chemokines (Vallejo, de Leon-Casasola et al. 2004, Chuang, Suzuki et al. 2005).

Additionally, opioids may directly influence HIV infectivity by enhancing viral transmission. Productive infection of HIV occurs in a variety of CD4+ immune cells, such as T lymphocytes, monocytes/macrophages, and microglia. Viral entry is mediated through the binding of the HIV viral protein gp120 to CD4 in conjunction with the α-chemokine receptor CXCR4 and/or the β-chemokine receptors CCR3 and CCR5. Utilization of CCR5 as a coreceptor is indicative of macrophage-tropic HIV strains, whereas utilization of the CXCR4 coreceptor is indicative of T lymphocyte-tropic HIV strains (Kaul, Garden et al. 2001, Vallejo, de Leon-Casasola et al. 2004, Mahajan, Schwartz et al. 2005, Ances and Ellis

2007). Opioid abuse may directly increase HIV infectivity by up-regulating lymphocyte expression of the chemokine coreceptors CCR5, CXCR4 and CCR3, among others, through opioid receptor signaling mechanisms that activate NF-κB 225 and TNFα or IL-2 in macrophages and lymphocytes, respectively (Miyagi,

Chuang et al. 2000, Guo, Li et al. 2002, Li, Wang et al. 2002, Mahajan, Schwartz et al. 2002, Suzuki, Carlos et al. 2002, Suzuki, Chuang et al. 2002, Suzuki,

Chuang et al. 2002, Ho, Guo et al. 2003, Li, Merrill et al. 2003, Steele,

Henderson et al. 2003, Chuang, Suzuki et al. 2005, Hauser, El-Hage et al. 2005,

Mahajan, Aalinkeel et al. 2005, Mahajan, Schwartz et al. 2005, Cabral 2006,

Berrios, Castro et al. 2008, Finley, Happel et al. 2008, Happel, Steele et al. 2008,

Noel, Rivera-Amill et al. 2008, Burbassi, Sengupta et al. 2010, Nath 2010,

Reddy, Pilakka-Kanthikeel et al. 2012). Furthermore, opioids may increase HIV infectivity by down-regulating α- and β-chemokines, which compete with HIV for binding of chemokine coreceptors, via p38 MAPK and/or CREB signaling pathways (Guo, Li et al. 2002, Li, Wang et al. 2002, Mahajan, Schwartz et al.

2002, Li, Merrill et al. 2003, Mahajan, Aalinkeel et al. 2005, Mahajan, Schwartz et al. 2005, Cabral 2006, Berrios, Castro et al. 2008, Noel, Rivera-Amill et al. 2008,

Reddy, Pilakka-Kanthikeel et al. 2012). Following viral entry and the establishment of productive infection, opioids may continue to modulate HIV infection by protecting infected cells from apoptosis. Reduced p53 phosphorylation and activation is mediated by opioid stimulation of immune cells and results in a subsequent decrease in Bax and increase in Bcl-2, dampening apoptotic signaling and promoting cell cycle progression. As such, morphine may protect HIV-infected lymphocytes from apoptotic death, allowing the virus to persist and replicate, propagating the infection systemically (Suzuki, Chuang et al. 2003, Chuang, Suzuki et al. 2005). Collectively, opioids indirectly mediate a 226 bimodal enhancement of HIV infection, first facilitating viral entry through the increased expression of chemokine coreceptors and decreased expression of α- and β-chemokines then protecting infected cells from apoptosis through the mediation of mitochondrial events, thereby allowing continued viral replication and transmission. However, despite modulating the expression of α- and β- chemokines and their corresponding receptors in such a way that would promote increased HIV infection, opioid treatment may also decrease HIV infection by diminishing chemokine coreceptor activity through opioid receptor-mediated cross-desensitization (Szabo, Wetzel et al. 2003, Chen, Li et al. 2004) in addition to stimulating previously discussed pro-apoptotic pathways in lymphocytes. This discrepancy in enhanced or diminished HIV viral replication may also be an indirect result of morphine mediated immunosuppression, as a weakened immune response would preferentially promote replication of HIV viral strains with high pathogenicity but inhibit replication of HIV viral strains with lower pathogenicity (Rivera-Amill, Silverstein et al. 2010). Therefore, the role of opioids in modulating HIV infection indirectly through chemokine receptor activity and anti-apoptotic signaling is dependent on multiple cellular factors and viral pathogenicity as well as the opioid agonist and conditions under which disease progression is investigated (Chao, Gekker et al. 1996, Peterson, Gekker et al.

1999, Nath, Hauser et al. 2002, Hauser, El-Hage et al. 2005).

In addition to enhancing viral entry and the viability of infected cells, opioids mediate HIV infection through direct and indirect modulation of HIV replication

(Peterson, Gekker et al. 1993). The profound immunosuppressive effects of 227 opioids also decrease the activity of DNA repair mechanisms within lymphocytes, resulting in increased genetic damage, mutagenesis, and apoptotic cell death.

These stress events are known to stimulate increased proliferation and release of retroviruses such as HIV. As such, opioids may indirectly stimulate HIV replication through depressed DNA repair activity and increased cellular stress

(Madden, Wang et al. 2002). Opioids can also modulate HIV replication directly through various cell-signaling cascades. For example, opioid-mediated increases in Fos and c-Jun protein expression modulate transcription of HIV through the subsequent activation of transcription factors, such as AP-1, NF-κB, and SP-1, that target cis-acting regulatory sequences within the HIV LTR (Squinto, Mondal et al. 1990, Sundar, Kamaraju et al. 1996, Li, Wang et al. 2002, Borner, Warnick et al. 2009). Opioids also enhance HIV replication through the modulation of cytokine and interferon signaling pathways. This involves opioid-mediated activation of proviral cytokines and/or opioid-mediated suppression of antiviral cytokines, interferons, and interferon-inducible genes that respectively enhance or inhibit HIV viral replication (Peterson, Sharp et al. 1990, Wang, Wang et al.

2012). Another key component of innate defense mechanisms against retroviruses modulated by opioids is the expression of miRNAs. Pro-inflammatory pathways contain multiple targets for regulatory miRNAs such as miRNA-15b and miRNA-181b. As such, opioid-mediated changes in miRNA profiles impact inflammatory and oxidative stress events, which, as previously mentioned, are known to stimulate increased proliferation and release of retroviruses such as

HIV (Dave and Khalili 2010). Several miRNAs, including miRNA-28, -29a, -125b,

228 -150, -198, -223, and -382, also target HIV accessory genes, thereby directly inhibiting HIV viral expression and inducing latency. Therefore, opioid-mediated suppression of these anti-HIV miRNAs promotes the replication of latent HIV in resting lymphocytes (Wang, Ye et al. 2011, Purohit, Rapaka et al. 2012). Overall, opioids enhance multiple facets of HIV infection, including HIV viral entry and replication, resulting in increased viral loads and exacerbating disease progression both systemically and within the CNS (Fitting, Xu et al. 2010).

6.2.3 HIV-associated neurocognitive dysfunction

Current estimates by the World Health Organization suggest that over 40 million people worldwide are infected with HIV. The predominant clinical observation associated with HIV infection is the ablation of immune cells, particularly CD4+ T lymphocytes, resulting in the development of acquired immunodeficiency syndrome (AIDS), a diagnosis typically made when an HIV- positive individual presents with one or more AIDS-defining illnesses and a CD4+

T lymphocyte count below a particular threshold. Treatment for HIV typically involves a combination of different classes of medications customized to the individual’s viral load, viral strain, CD4+ T lymphocyte count, and additional disease symptoms. This treatment regiment, typically referred to as highly active antiretroviral therapy (HAART) or combination antiretroviral therapy (cART) cannot clear HIV infection completely, as HIV integrates into the host genome; however, implementation of HAART/cART therapy in the mid-1990’s has since changed HIV infection from a fatal diagnosis to a chronically managed disease, delaying or preventing the onset of symptoms and the progression to AIDS, 229 thereby prolonging life expectancy of HIV-positive individuals. In the era preceding the development HAART/cART therapy, symptomatic HIV infection initially manifested with a wide range of neurological disorders, collectively known as HIV-associated neurocognitive disorders (HAND). The incidence of subclinical neurologic disease was fairly high, occurring within 90% of HIV infected individuals, while upwards of 20% of HIV infected individuals exhibited some form of neurological complications, including deficits in memory, attention, executive function, language, and/or perceptual skills with up to 60% of these individuals exhibiting symptoms of HIV-associated dementia (HAD), the most severe HAND disorder. The incidence of HAD has since decreased due to the use of HAART/cART, although roughly 40% of HIV infected individuals continue to exhibit symptoms of HAND. Additionally, the prevalence of HAND, in milder forms, is increasing due, in part, to the increased life expectancy of HIV infected individuals maintained on antiretroviral therapy (Volkow 2006, Ances and Clifford

2008, Grant 2008, Lindl, Marks et al. 2010, Rappaport and Berger 2010, Desai,

Hu et al. 2013). Originally, neurological complications associated with HIV infection were classified into one of two syndromes; severe cognitive, motor, and/or emotional/personality disturbances that significantly impacted the ability to manage independently on a daily basis were characterizing symptoms of HAD while milder symptoms that did not disturb daily functioning were characterizing features of minor cognitive motor disorder (MCMD). This classification system has since been revised in order to emphasize the importance of documented neurocognitive disturbances in the diagnosis of HAND and specifies precise

230 criteria for the diagnosis of three separate syndromes. The mildest syndrome, asymptomatic neurocognitive impairment (ANI), is characterized by acquired impairments in at least two domains of cognitive functioning, including verbal/language, attention/working memory, abstraction/executive memory, information processing, sensory/perceptual, and motor skills; however, these deficits do not impact daily functioning and does not meet the criteria for delirium or dementia. Mild neurocognitive disorder (MND) is characterized by the same acquired impairments of cognitive functioning seen in ANI, however these symptoms present more moderately and thus impact daily functioning, although still not meeting the criteria for delirium or dementia. HIV associated dementia

(HAD) represents the most severe syndrome and is classified by stark impairments of cognitive functioning that severely impact daily functioning and meet the criteria for dementia, but not delirium (Ances and Clifford 2008, Grant

2008, Anand, Springer et al. 2010). The development of HAD is frequently accompanied by HIV encephalitis (HIVE), a neurological condition characterized by astrogliosis, the formation of microglial nodules and multinucleated giant cells, and neuronal loss associated with demyelination and both axonal and dendritic damage. As expected, encephalitic brains of HAD patients contain apoptotic neurons, astrocytes, and other CNS cells types in several regions, including the frontal and temporal cortex, basal ganglia, limbic system, and brain stem

(Masliah, Ge et al. 1996, Kaul, Garden et al. 2001, Desai, Hu et al. 2013).

The development and progression of neurocognitive dysfunction due to HIV infection first requires the establishment of productive HIV infection within CNS.

231 This is characteristic of lentiviruses as a group, as they tend to exhibit both neurotropism and neurovirulence. In the case of HIV, this is thought to occur through a “Trojan horse” mechanism in which systemically infected monocytes and macrophages migrate across the blood-brain barrier and establish productive infections within microglia and perivascular macrophages. While the implementation of HAART/cART therapy has allowed for the maintenance of systemic HIV infection and the reduction of HIV viral load outside the CNS, early entry of HIV into the CNS coupled with the poor CNS penetrance of protease inhibitors and nucleoside analogues used in HAART/cART therapy allows for independent progression of HIV infection within a protected CNS reservoir (Kaul,

Garden et al. 2001, Hauser, El-Hage et al. 2005, Ances and Ellis 2007, Lindl,

Marks et al. 2010). As this unchecked infection progresses, HIV-mediated STAT1 and PI3K signaling induces endothelial dysfunction, resulting in the breakdown of the blood-brain barrier. Ultimately, this results in the increased penetrance of both free virus and infected monocytes/macrophages into the CNS, raising the viral load within the CNS and stimulating neurodegeneration (Yang, Singh et al.

2010).

Prior to the implementation of HAART/cART therapy, the development of

HAND correlated with disease progression from a pre-symptomatic phase into symptomatic AIDS. The introduction of antiretroviral therapy has since resulted in the suppression of systemic HIV infection, arresting disease progression in the pre-symptomatic phase and subsequently altering the course and prognosis of both HIV infection and HIV-related disorders. Likewise, the incidence of

232 opportunistic CNS infections often associated with AIDS, such as JC virus (JCV),

Epstein-Barr virus (EBV), and cytomegalovirus (CMV), have since declined. As such, it would be expected that the progression of HAND severity in

HAART/cART maintained HIV positive individuals would be similar to that of pre- symptomatic, non-HAART/cART maintained HIV positive individuals; however, the CNS of HAART/cART maintained HIV positive individuals still show high levels of inflammation, particularly microglial activation (Gray, Chretien et al.

2003, Langford, Letendre et al. 2003, Anthony and Bell 2008). Although neurological complications represent a major cause of disability and death in

HIV, the prevalence of these symptoms are limited to developed countries where

HAART/cART therapy is available, as neurological dysfunction occurs during late stage infection. Therefore, it is not surprising that in developed countries, where the implementation of HAART/cART therapy has decreased systemic HIV viral load and prolonged patient survival, the prevalence of HAND has increased

(Gray, Chretien et al. 2003, Langford, Letendre et al. 2003). For this reason, in addition to the poor penetrance of antiretroviral drugs, the subsequent establishment of a HIV viral reservoir within the CNS, and the emergence of neurovirulent strains of HIV, HAND is now regarded as a chronic condition as well as a significant public health concern (Langford, Letendre et al. 2003).

Furthermore, while the development of HAND and HIVE is directly correlated with HIV viral load within the CNS, the severity of cognitive dysfunction is not.

Instead, the clinical symptoms of HAND are associated with decreased synaptic and dendritic density as well as selective neuronal loss, despite the lack of

233 productive HIV infection in neurons. Therefore, HIV infection must promote neurodegeneration through mechanisms independent of direct infection (Masliah,

Ge et al. 1996, Kaul, Garden et al. 2001, Hauser, El-Hage et al. 2005, Lindl,

Marks et al. 2010, Hauser, Fitting et al. 2012).

Currently, two mutually inclusive models account for neurodegeneration and the development of neurological symptoms in HAND: the indirect model and the direct model. The indirect model proposes that HIV-mediated neurodegeneration is a secondary effect of the inflammatory responses and deregulation of glial function caused by infected and non-infected glial cells within the CNS (Kaul, Garden et al. 2001, Lindl, Marks et al. 2010). The direct model proposes that HIV-mediated neurodegeneration is a primary effect of the interaction between neurons and HIV viral proteins secreted from infected monocyte-derived cells within the CNS (Kaul, Garden et al. 2001, Lindl, Marks et al. 2010). Following the establishment of productive HIV infection within the CNS, multiple inflammatory proteins, including HIV viral proteins, cytokines, and chemokines, secreted by infected cells, activate uninfected microglia and macrophages. With regard to the indirect model of HIV-mediated neurodegeneration, the activation of these cells is significant as both activated and HIV-infected macrophages and microglia release neurotoxic substances, including TNFα, free radicals, quinolinic and arachidonic acid, and excitatory amino acids like glutamate and L-cysteine. These substances act directly on neurons to induce dendritic and synaptic damage, with prolonged exposure resulting in neuronal apoptosis. More importantly, secreted inflammatory

234 cytokines like TNFα and IL-1β stimulate the formation of reactive astrocytes, which subsequently release additional neurotoxic factors. For example, the release of NO from reactive astrocytes reacts with superoxide to generate the neurotoxic compound peroxynitrite. However, the predominant mechanism of reactive astrocyte-mediated neurotoxicity, and a defining characteristic of the indirect model of HIV-mediated neurodegeneration, is the establishment of an excitotoxic microenvironment. Astrocytes normally function to clear glutamate from the synaptic cleft; however, the secretion of neurotoxic substances, particularly arachidonic acid and TNFα, impairs this function, resulting in the accumulation of glutamate. Excessive glutamate overstimulates NMDARs on nearby neurons, activating NMDAR-coupled Ca2+ ion channels. The subsequent influx of Ca2+ stimulates free-radical production, the activation of neurotoxic enzymes, and the release of additional glutamate, which propagates this excitotoxic signaling in neighboring neurons. Additionally, HIV viral proteins such as Tat can directly stimulate glutamate release in a dose-dependent manner through p38 MAPK and ERK1/2 signaling mechanisms (Kaul, Garden et al. 2001,

Albright, Soldan et al. 2003, Hauser, El-Hage et al. 2005, Borjabad, Brooks et al.

2010, Gupta, Knight et al. 2010, Lindl, Marks et al. 2010). Therefore, certain mechanisms of HIV-mediated neurodegeneration are secondary to HIV-mediated glial dysfunction, through which HIV indirectly damages neurons due to the release of neurotoxic and excitotoxic substances.

Despite the lack of productive infection, HIV may still interact directly with neurons as they often express CCR5 and CXCR4. Therefore, secreted viral 235 proteins, such as gp120, Tat, and Vpr may also contribute to neurodegeneration independent of the intermediary functions of microglia and astrocytes (Kaul,

Garden et al. 2001, Desai, Hu et al. 2013). This direct model of HIV-associated neurotoxicity is mediated through various intrinsic and extrinsic apoptotic mechanisms. For example, both gp120 and Tat are known to disrupt Ca2+ regulation by altering voltage-dependent Ca2+ channels, glutamate receptor channels, and membrane transporters, thereby facilitating excessive Ca2+ influx

(Kaul, Garden et al. 2001, Desai, Hu et al. 2013). Additionally, Tat up-regulates

IP3 expression, which subsequently triggers the release of Ca2+ from IP3- sensitive ER stores. The deregulation of intracellular Ca2+ levels facilitates free radical production and mitochondrial dysfunction. In following, p53 expression and phosphorylation is enhanced by both gp120 and Tat, initiating a concomitant decrease in Bcl-2 expression and the migration and insertion of Bax into the mitochondrial membrane, resulting in cytochrome C release and caspase-3 activation (Chang, Mukerjee et al. 2011, Desai, Hu et al. 2013). The HIV viral protein Vpr is also implicated in mitochondrial dysfunction, as it has been shown to interact with the mitochondrial membrane by directly binding to the adenine nucleotide translocator (ANT), a component of the mitochondria permeability transition pore, and triggering the release of pro-apoptotic mitochondrial proteins

(Desai, Hu et al. 2013). Aside from excitotoxic and mitochondrial signaling mechanisms, gp120-stimulated neuronal dysfunction may occur through the activation of neuronal chemokine receptors, specifically CXCR4, while limited data suggests that Tat-mediated neurotoxicity may occur through the induction of

236 miRNAs that target pro-survival gene products (Chang, Mukerjee et al. 2011).

Furthermore, both gp120 and Tat activate a wide variety of intracellular signaling cascades, including PI3K/Akt/GSK-3 and MAPK pathways (Chang, Mukerjee et al. 2011, Desai, Hu et al. 2013). For example, Tat and gp120 increase p38 and

JNK MAPK phosphorylation in primary striatal neurons, resulting in a subsequent increase in capase-3 activity and apoptosis (Singh, El-Hage et al. 2005).

Therefore, HIV-mediated neurotoxicity is likely to occur through a combination of direct and indirect mechanisms, although distinct neuronal populations differ in their susceptibility to particular mechanisms (Masliah, Ge et al. 1996).

6.2.4 Opioid synergism in HIV-associated neurocognitive dysfunction

In addition to enhancing the susceptibility to and progression of HIV infection, opiate drug abuse is now recognized to interact synergistically with both direct and indirect mechanisms of HIV-associated neurotoxicity. This synergy is primarily mediated through activation of the MOR, although limited evidence suggests roles for KORs and DORs as well. As previously detailed, HIV infection directly and/or indirectly stimulates neuronal dysfunction and subsequent apoptosis, whereas opioid abuse can independently stimulate both pro- and anti-apoptotic signaling pathways through numerous mechanisms. As such, the synergistic effects of opioids in HAND are paradoxical, with neuroprotective or neurodegenerative effects being determined by the target tissue and the pharmacodynamics of the specific opioid receptor subtypes and isoforms activated. Despite conflicting possibilities, HIV and µ-selective opioid synergy is primarily considered to exacerbate the neuronal loss characteristic of 237 HAND pathology through the disruption of glial homeostasis and/or the respective increase and decrease in pro- and anti-apoptotic protein expression within neurons (Sheng, Hu et al. 1997, Gurwell, Nath et al. 2001, Nath, Hauser et al. 2002, Khurdayan, Buch et al. 2004, Hauser, El-Hage et al. 2005, Hauser, El-

Hage et al. 2006, Hauser, Fitting et al. 2012).

The indirect model of HAND development involves HIV-mediated glial dysfunction, particularly of microglia and astrocytes, and the subsequent loss of metabolic and trophic support in addition to the release of cellular toxins, including cytokines such as TNFα, interleukins, arachidonic and quinolinic acids,

NO, L-cysteine, and glutamate. These glial processes, particularly cytokine/chemokine production and HIV viral replication, are also modulated by opioids, as glial cells express various opioid receptor subtypes. Therefore, microglia and astrocytes are likely points of intersection between HIV and opioid neurotoxic signaling (Hauser, El-Hage et al. 2005, Hauser, El-Hage et al. 2006,

Hauser, Fitting et al. 2012). Increased glial cell apoptosis constitutes one such intersection between HIV and opioid signaling, as the loss of microglia reduces viral reservoirs and dissemination whereas the loss of astrocytes reduces neuronal metabolic and trophic support. Any positive benefit of glial apoptosis in reducing HIV viral replication is potentially offset by the synergistic effect of opioids, even at moderate levels and short-term exposure, and HIV viral proteins, specifically Tat, in rapidly increasing the activation of astrocytes, macrophages, and microglia, of which overactivation and/or dysregulation is neuropathogenic despite being associated with neuroprotective mechanisms, such as the

238 elimination of cellular debris and the release of neurotrophic and anti- inflammatory factors (Bokhari, Yao et al. 2009, Fitting, Xu et al. 2010, Fitting, Zou et al. 2010). Microglial activation is accompanied by multiple changes, including a morphological shift from a quiescent, ramified state to an activated, macrophage- like phenotype, an up-regulation of multiple cell surface antigens, and microgliosis and astrogliosis, specifically in microglia expressing CD68 and major histocompatibility complex class II and astrocytes expressing CCL2, which subsequently increase microglial activation further via CCR2 signaling (El-Hage,

Wu et al. 2006, Hauser, El-Hage et al. 2006, Hauser, El-Hage et al. 2007,

Bokhari, Yao et al. 2009). Dysregulated production of additional cytokines, chemokines, and other neurotoxic compounds by HIV-infected macrophages and microglia is also exacerbated by concomitant opioid abuse. This includes significant alterations in the production and secretion of IL-1b, IL-6, TNFα, CCL2

(also known as monocyte chemoattractant protein-1 or MCP-1), inducible nitric oxide synthase (iNOS) and NO, CD40 ligand, INF-γ-inducible protein 10 (IP-10) and ROS (Hauser, El-Hage et al. 2005, Hauser, El-Hage et al. 2007, Bokhari,

Yao et al. 2009, Li, Li et al. 2009, Turchan-Cholewo, Dimayuga et al. 2009, Zou,

Fitting et al. 2011, Dave 2012). In some instances, the synergistic effects of HIV and opioids on cytokine/chemokine expression are time-dependent. For example, morphine treatment of HIV-infected macrophages in vitro initially delays the HIV-mediated increase in MCP-2 production; however, prolonged morphine treatment of HIV-infected macrophages stimulates an increase in MCP-2 secretion that is significantly greater than that stimulated by HIV infection alone 239 2+ (Dave 2012). Augmentation of astroglial Ca homeostasis by opioids via Gαq/11 subsequently increases PLC expression, resulting in an additional, IP3- dependent increase in intracellular Ca2+, whereas HIV viral proteins, particularly

Tat and gp120, decrease glutamate uptake and activate NF-κB-dependent cytokine/chemokine release in addition to increasing intracellular Ca2+. As such, opioids and HIV viral proteins synergistically increase Ca2+ release from IP3- dependent intracellular stores, resulting in a subsequent increase in ROS and

NF-κB-dependent cytokine/chemokine production, particularly of IL-6, RANTES,

CCL2 and MCP-5, while decreasing glutamate uptake due to decreased excitatory amino acid transporter-2 (EAAT2) expression. The enhanced potentiation of astroglial chemokine release, particularly of MCP-1, MCP-5, and

RANTES, by concomitant HIV and opioid exposure also serves to increase microglial chemotaxis. Collectively, these processes increase neuronal injury through the establishment of intercellular feedback loops between astrocytes, macrophages, microglia, and neurons that increase inflammation and excitotoxicity (Khurdayan, Buch et al. 2004, El-Hage, Gurwell et al. 2005,

Hauser, El-Hage et al. 2005, El-Hage, Wu et al. 2006, El-Hage, Wu et al. 2006,

Hauser, El-Hage et al. 2006, Hauser, El-Hage et al. 2007, El-Hage, Bruce-Keller et al. 2008, Li, Li et al. 2009, Hauser, Fitting et al. 2012). Opioid abuse with concomitant Tat exposure also stimulates increased miRNA-29b expression within astrocytes, which is then shuttled to neurons via exosomes where it decreases expression of the neurotropic factor platelet-derived growth factor

(PDGF)-B, resulting in neuronal death (Hu, Yao et al. 2012). Multiple signaling 240 pathways have been implicated as points of convergence between HIV- and opioid-mediated glial dysfunction and apoptosis, including PI3K/Akt, IκB/NF-κB,

FasR/FasL, β-arrestins, and ERK1/2, JNK, and p38 MAPKs (Hauser, El-Hage et al. 2005, Hu, Sheng et al. 2005, Hauser, El-Hage et al. 2006, El-Hage, Bruce-

Keller et al. 2008, Moorman, Zhang et al. 2009). Therefore, the neuronal damage and loss observed in HAND, particularly in white matter tracts, is considered to occur mainly through indirect mechanisms, as neurons lack the CD4 receptor required for productive HIV infection. Opioids are considered to exacerbate

HAND pathology by synergistically decreasing trophic and metabolic support and enhancing marginally neurotoxic, excitotoxic, and inflammatory cellular stressors secreted by dysfunctional glial cells, all of which may occur in the absence of glial cell loss (Langford, Letendre et al. 2003, El-Hage, Gurwell et al. 2005, Hauser,

El-Hage et al. 2006, Hauser, Fitting et al. 2012).

Although it is typically thought that HIV-associated neuronal damage occurs indirectly due to glial dysfunction, neurons may also serve as a point of direct intersection between HIV and opioid neurotoxic signaling given that neurons abundantly express multiple opioid receptor subtypes as well as the chemokine receptors necessary to facilitate interaction with HIV viral proteins secreted from neighboring glia. Histopathological studies often highlight the neuronal and glial cell death observed in terminal stage HAND; however, current evidence increasingly supports the notion that sublethal synaptodendritic injury and the subsequent loss of neural circuitry preceding neuronal cell death is responsible for the neurobehavioral deficits characteristic of HAND, suggesting that 241 synergistic opioid- and HIV-mediated deficits in CNS functioning occur through mechanisms involving dendritic pruning, synaptic culling, and cumulative, sublethal synaptodendritic injury that eventually results in neuronal cell death

(Fitting, Xu et al. 2010, Hauser, Fitting et al. 2012). The HIV viral proteins Tat and gp120 are both directly excitotoxic, as they overactivate both NMDARs and glutamate receptors, and neurotoxic, as Tat and gp120 are endocytosed through interactions with a low density lipoprotein receptor-related protein (LRP) and heparin sulphate proteoglycan or axonally-expressed CXCR4, respectively, and disrupt amyloid precursor protein metabolism, histone acetylation, and neurotrophin signaling as well as cause mitochondrial dysfunction via a decreased BCL-2/Bax ratio and focal swelling, which are themselves accompanied by disruptions in ATP production, ion homeostasis including IP3- dependent intracellular Ca2+ stores, and neuritic transport (Hauser, El-Hage et al.

2005, Bachis, Aden et al. 2006, Li, Li et al. 2009, Malik, Khalique et al. 2011,

Zou, Fitting et al. 2011, Hauser, Fitting et al. 2012, Reddy, Pilakka-Kanthikeel et al. 2012). Furthermore, HIV viral protein interactions with dendrites are associated with the formation of autophagosomes and a localized elevation in cleaved caspase-3 at the sites of dendritic swelling, suggesting a level of HIV- mediated synaptic autophagy and/or apoptosis (Fitting, Xu et al. 2010, Hauser,

Fitting et al. 2012). Opioids have long-been associated with this type of neuronal damage, reducing both the complexity of dendrites and the density of dendritic spines in a variety of brain regions through mechanisms involving decreased

NeuroD phosphorylation and subsequently increased CaMKII phosphorylation as

242 well as alterations in microRNA-190 expression. Opioids are also known to exacerbate HIV-mediated excitotoxicity of dopaminergic neurons projecting from the ventral tegmental area (VTA) to striatal spiny neurons through overlapping actions on K+ channels, which hyperpolarize GABAnergic interneurons within the

VTA. Inward-rectifying K+ channel activity is reduced due to the loss in MOR coupling, thereby exaggerating the activity of outward rectifying K+ channels. This biased activation of outward rectifying K+ channels reduces ERK signaling while simultaneously activating JNK and p38 MAPK signaling, resulting the in activation of caspase-3 apoptotic signaling pathways (Hauser, Fitting et al. 2012).

Opioids also disrupt neurotrophic chemokine signaling by interacting with CCR1,

CCR2, CCR5, CXCR1, CXCR2, and CXCR4 via dimerization and/or heterologous desensitization mediated by Gαs-coupled PKA or Gαi/Gαq-coupled

PKC activation; however, it is unclear whether the neurotoxicity caused by synergistic opioid- and HIV-mediated chemokine signaling dysfunction occurs through direct or indirect mechanisms, as both neurons and glia express opioid and chemokine receptors (Steele, Szabo et al. 2002, Hu, Sheng et al. 2005,

Patel, Sengupta et al. 2006, Burbassi, Aloyo et al. 2008, Finley, Chen et al. 2008,

Hereld and Jin 2008, Pello, Martinez-Munoz et al. 2008, Sengupta, Burbassi et al. 2009, Avdoshina, Biggio et al. 2010, Pitcher, Shimizu et al. 2010). Overall, concomitant HIV viral protein and chronic opioid exposure is typically accompanied by altered patterns of gene activation, decreased neurotrophic signaling, increased ROS production and oxidative stress, and enhanced mitochondrial dysfunction within neurons due to synergistic disruption of second

243 messenger cascades, including adenylyl cyclase, SDF-1, PKA, PKB, PI3K/Akt, p38 MAPK, ERK1/2, JNK, GSK-3β, IKK-α/Iκ-Bα/NF-κB, CREB, p53, PTEN, calcineurin, Bcl-2 family member proteins, endonuclease G, and caspase-1, -3, and -7 (Langford, Sanders et al. 2002, Nath, Hauser et al. 2002, Hauser, El-Hage et al. 2005, Hauser, El-Hage et al. 2006, Hauser, El-Hage et al. 2007, Peng,

Dhillon et al. 2008, Li, Li et al. 2009, Bandaru, Patel et al. 2011, Malik, Khalique et al. 2011, Hauser, Fitting et al. 2012, Reddy, Pilakka-Kanthikeel et al. 2012).

Therefore, in addition to indirect, glia-dependent mechanisms, marginally toxic opioids directly exacerbate the excitotoxic, dendrotoxic, and neurotoxic events triggered by secreted HIV viral proteins through the synergistic disruption of numerous signaling cascades, which, in turn, trigger sublethal synaptodendritic injury that culminates in the activation of caspase-dependent and caspase- independent apoptotic mechanisms, ultimately resulting in the neuronal cell loss characteristic of HAND.

244 6.3 Results

A. 140

120

100

80

60

40

Beclin-1 Protein Expression (% Control) Expression Protein Beclin-1 20

0 1 2 3 4 5 6 7 8 9 10 B. 120

100

80

60

* 40 *

20 LC3-I:LC3-II Protein Expression (% Control) Expression Protein LC3-I:LC3-II

0 1 2 3 4 5 6 7 8 9 10

C.

60kDa Beclin

19kDa LC3-I

17kDa LC3-II 15kDa

50kDa β-Tubulin

1 2 3 4 5 6 7 8 9 10 - 10 - 10 - 10 - 10 - - Morphine (µM) - - + + ------Vector - - - - + + - - - - MOR-1 ------+ + - - MOR-1X 1mM 5nM CdCl2 Baf.

Figure 6.1: Morphine does not affect Beclin-1 expression or LC-3 conversion in either MOR-1 and MOR-1X expressing HEK293 cells. A.

Quantification of Beclin-1 protein expression and B. Quantification of LC3-I conversion to LC3-II using C. Western blot analysis of protein expression in untransfected, untreated HEK293 cells (lane 1), untransfected HEK293 cells treated every 2 hours with 10µM morphine for 24 hours (lane 2), vector- transfected, untreated HEK293 cells (lane 3) vector-transfected HEK293 cells treated every 2 hours with 10µM morphine for 24 hours (lane 4), pCMV6-MOR-1-

245 transfected, untreated HEK293 cells (lane 5), pCMV6-MOR-1-transfected

HEK293 cells treated every 2 hours with 10µM morphine for 24 hours (lane 6), pCMV6-MOR-1X-transfected, untreated HEK293 cells (lane 7), pCMV6-MOR-

1X-transfected HEK293 cells treated every 2 hours with 10µM morphine for 24 hours minutes (lane 8), untransfected HEK293 cells treated with 1mM CdCl2 for 1 hour (lane 9), and untransfected HEK293 cells serum starved in HBSS media and treated with Baf for 4 hours was performed using the Li-Cor Odyssey CLx

Infrared Imaging System (mean ± SEM; * = p ≤ 0.05).

6.3.1 MOR-1X uniquely regulates apoptotic, but not autophagic, proteins

In addition to modulating nociception, opioid receptor signaling has been shown to impact cellular viability through numerous mechanisms, including the induction of autophagy by G protein-dependent, PTX sensitive signaling, the modulation of extrinsic signaling pathways of apoptosis by interacting with death receptor factors like FasL/FasR, and, most notably, the regulation of intrinsic signaling pathways of apoptosis by altering the expression of pro- and anti- apoptotic proteins, including Bcl-2 family member proteins such as Bax.

Furthermore, opioid signaling directly and indirectly enhances the susceptibility to and progression of HIV infection as well as synergistically interacts with direct and indirect mechanisms of HIV-associated neurotoxicity, exacerbating HIV- associated neurocognitive dysfunction. Given this role in altering mechanisms of cellular viability and that previous results found that MOR-1 and MOR-1X stimulate MAPK signaling pathways in a divergent fashion, this study sought to

246 determine whether these receptors also exhibit differences in the stimulation of autophagic and apoptotic signaling cascades in both the presence and absence of HIV viral proteins, specifically Tat and Vpr. Investigation of autophagic and apoptotic signaling cascades were conducted using chronic, high dose conditions of both morphine and HIV viral protein exposure established through treatment with 10µM morphine every 2 hours for 24 hours and transfection with pCDNA3-

Vpr-WT and pCMV-Tat86 expression plasmids as these conditions, specifically for morphine, are often associated with pro-apoptotic signaling cascades mediated through intrinsic and extrinsic apoptotic pathways, whereas both acute administration and chronic, low dose administration are often associated with anti-apoptotic signaling cascades.

Investigation of autophagic mechanisms did not show significant differences between MOR-1 and MOR-1X signaling as neither receptor significantly altered the expression of autophagic protein markers (Figure 6.1).

Specifically, the expression of Beclin-1, an essential protein component of autophagosome assembly, was not significantly altered by chronic, high dose morphine treatment in untransfected HEK293 cells (Figure 6.1A, lanes 1-2;

Figure 6.1C, lanes 1-2), vector-transfected cells (Figure 6.1A, lanes 3-4; Figure

6.1C, lanes 3-4), pCMV6-MOR-1-transfected cells (Figure 6.1A, lanes 5-6; Figure

6.1C, lanes 5-6) or pCMV6-MOR-1X-transfected cells (Figure 6.1A, lanes 7-8;

Figure 6.1C, lanes 7-8) as well as in untransfected cells treated with 1mM CdCl2 for 1 hour (Figure 6.1A, lane 9; Figure 6.1C, lane 9) or serum starved in HBSS media and treated with 5nM Baf for 4 hours (Figure 6.1A, lane 10; Figure 6.1C,

247 lane 10). Expression of LC3-I and LC3-II proteins, which specifically localize to forming and newly formed autophagosomes, were not significantly different between untransfected cells (Figure 6.1C, lanes 1-2), vector-transfected cells

(Figure 6.1C, lanes 3-4), pCMV6-MOR-1-transfected cells (Figure 6.1C, lanes 5-

6) and pCMV6-MOR-1X-transfected cells (Figure 6.1C, lanes 7-8), although untransfected cells treated with 1mM CdCl2 for 1 hour (Figure 6.1C, lane 9) or serum starved in HBSS media and treated with 5nM Baf for 4 hours (Figure 6.1C, lane 10) did exhibit an increased expression in LC3-II protein. Accordingly, the ratio of LC3-I to LC3-II, used as a marker for LC3 conversion during autophagosome formation, was not significantly different between morphine treatment conditions (Figure 6.1B, lanes 1-8), but was significantly decreased in untransfected cells treated with 1mM CdCl2 for 1 hour (Figure 6.1B, lane 9) or serum starved in HBSS media and treated with 5nM Baf for 4 hours (Figure 6.1B, lane 10), indicating increased autophagosome production. Therefore, while autophagy was clearly utilized by HEK293 cells under stress conditions, neither

MOR-1 nor MOR-1X signaling significantly altered autophagic mechanisms.

A well-known substrate of the ERK/RSK pathway is the pro-apoptotic protein Bad, which is inactivated by RSK-mediated phosphorylation, causing it to dissociate from anti-apoptotic proteins that subsequently inhibit another pro- apoptotic protein, Bax (Betito and Cuvillier 2006, Anjum and Blenis 2008,

Romeo, Zhang et al. 2011). Given this role in altering mechanisms of cellular viability and that MOR-1 and MOR-1X were previously observed to alter ERK1/2 and p90 RSK1/2 signaling pathways in a divergent fashion (Figure 5.2), this

248 study assessed whether these receptors also exhibit differences in the stimulation of apoptotic signaling cascades, specifically by examining Bax protein expression. Expression of Bax protein was not significantly altered in untransfected HEK293 cells treated with chronic, high dose morphine (Figure

6.2A, lane 2), serum starved in HBSS media for 4 hours (Figure 6.2A, lane 3), or serum starved in HBSS media and treated with 5nM Baf for 4 hours (Figure 6.2A, lane 4) but was significantly up-regulated in untransfected HEK293 cells treated with 1mM CdCl2 for 1 hour (Figure 6.2A, lane 5), a method frequently used for induction of apoptosis through mitochondrial dysfunction. Similarly, Bax protein was not significantly altered in vector-transfected HEK293 cells treated with chronic, high dose morphine (Figure 6.2A, lane 7). Despite significant effects on phosphorylated ERK1/2 and RSK1/2 expression, the activity of MOR-1 did not differ from the effects observed in MOR-null and vector-transfected HEK293 cells, as Bax protein expression in pCMV6-MOR-1-transfected, untreated cells

(Figure 6.2B, lane 2) and pCMV6-MOR-1-transfected cells treated with chronic, high dose morphine (Figure 6.2B, lane 3) was not significantly altered.

Conversely, Bax expression was constitutively down-regulated in pCMV6-MOR-

1X-transfected cells (Figure 6.2B, lane 8) and was reduced further by chronic, high dose morphine treatment (Figure 6.2B, lane 9), although the effect of morphine was not significantly different from MOR-1X constitutive activity.

Therefore, MOR-1 and MOR-1X expressing cells display distinct differences in

Bax proteins expression, which may be due to disparate activation of upstream signaling kinases, RSK1/2 and ERK1/2.

249 With respect to transfected HIV viral proteins, only untreated, vector/pCDNA3-Vpr-WT co-transfected HEK293 cells exhibited a significant decrease in Bax expression (Figure 6.2A, lane 8). Likewise, comorbidity between

MOR-1 signaling and HIV viral proteins was not readily observed, both constitutively and following chronic, high dose morphine treatment (Figure 6.2B, lanes 4-7). In contrast, Bax expression remained significantly reduced in both pCMV6-MOR-1X/pCDNA3-Vpr-WT and pCMV6-MOR-1X/pCMV-Tat86 co- transfected HEK293 cells treated with chronic, high dose morphine (Figure 6.2B, lanes 11 and 13), although this was not significantly different from non-HIV conditions and therefore should not be regarded as a combinational effect.

250

A. 50005000 10001000 160

140

120

100 * 80

60

40 Bax Protein Expression (% Control) Expression Bax Protein 20

0 1 2 3 4 5 6 7 8 9 10 11 12 23kDa Bax

50kDa β-Tubulin

- 10 - - - - 10 - 10 - 10 Morphine (µM) ------Vpr Vpr Tat Tat HIV - - - - - + + + + + + Vector HBSS 5nM 1mM Baf. CdCl2

B.

160 160

140 140

120 120

100 100 * 80 80 * * 60 60 *

40 40 *

Bax Protein Expression (% Control) Expression Bax Protein 20 20

0 0 1 2 3 4 5 6 7 88 99 1010 1111 12 12 13 Bax

β-Tubulin

- - 10 - 10 - 10 - 10 - 10 - 10 Morphine (µM) - - - Vpr Vpr Tat Tat - - Vpr Vpr Tat Tat HIV - + + + + + + ------MOR-1 ------+ + + + + + MOR-1X

Figure 6.2 Constitutive reduction in Bax by MOR-1X is not synergistic with

HIV viral protein signaling. A. Quantification of Bax protein expression in untransfected, untreated HEK293 cells (lane 1), untransfected HEK293 cells treated every 2 hours with 10µM morphine for 24 hours (lane 2), untransfected

HEK293 cells serum starved in HBSS media for 4 hours (lane 3), untransfected

HEK293 cells serum starved in HBSS media and treated with 5nM Baf for 4 hours (lane 4), untransfected HEK293 cells treated with 1mM CdCl2 for 1 hour

(lane 5), vector-transfected, untreated HEK293 cells (lane 6), vector-transfected

251 HEK293 cells treated every 2 hours with 10µM morphine for 24 hours (lane 7), vector/pCDNA3-Vpr-WT co-transfected, untreated HEK293 cells (lane 8), vector/pCDNA3-Vpr-WT co-transfected HEK293 cells treated every 2 hours with

10µM morphine for 24 hours (lane 9), vector/pCMV-Tat86 co-transfected, untreated HEK293 cells (lane 10), vector/pCMV-Tat86 co-transfected HEK293 cells treated every 2 hours with 10µM morphine for 24 hours (lane 11), and B. untransfected, untreated HEK293 cells (lane 1), pCMV6-MOR-1-transfected, untreated HEK293 cells (lane 2), pCMV6-MOR-1-transfected HEK293 cells treated every 2 hours with 10µM morphine for 24 hours (lane 3), pCMV6-MOR-

1/pCDNA3-Vpr-WT co-transfected, untreated HEK293 cells (lane 4), pCMV6-

MOR-1/pCDNA3-Vpr-WT co-transfected HEK293 cells treated every 2 hours with

10µM morphine for 24 hours (lane 5), pCMV6-MOR-1/pCMV-Tat86 co- transfected, untreated HEK293 cells (lane 6), pCMV6-MOR-1/pCMV-Tat86 co- transfected HEK293 cells treated every 2 hours with 10µM morphine for 24 hours

(lane 7), pCMV6-MOR-1X-transfected, untreated HEK293 cells (lane 8), pCMV6-

MOR-1X-transfected HEK293 cells treated every 2 hours with 10µM morphine for

24 hours (lane 9), pCMV6-MOR-1X/pCDNA3-Vpr-WT co-transfected, untreated

HEK293 cells (lane 10), pCMV6-MOR-1X/pCDNA3-Vpr-WT co-transfected

HEK293 cells treated every 2 hours with 10µM morphine for 24 hours (lane 11), pCMV6-MOR-1X/pCMV-Tat86 co-transfected, untreated HEK293 cells (lane 12), pCMV6-MOR-1X/pCMV-Tat86 co-transfected HEK293 cells treated every 2 hours with 10µM morphine for 24 hours (lane 13) was analyzed by Western blotting and

252 quantified using the Li-Cor Odyssey CLx Infrared Imaging System (mean ± SEM;

* = p ≤ 0.05).

6.3.2 MOR-1X signaling reduces mitochondrial dehydrogenase activity but not viability

The ratio of pro- and anti-apoptotic Bcl-2 family member proteins is one of many critical aspects that determine the influence of stress factors on cell viability and the activation of apoptotic signaling pathways. Given that MOR-1 and MOR-

1X expressing cells exhibit distinct differences in the expression of the pro- apoptotic Bcl-2 family member protein Bax, both constitutively and following morphine treatment, as well as with concomitant expression of the HIV viral proteins Vpr and Tat, it is likely that the activity of these receptors exhibit divergent regulatory functions in the activation of intrinsic signaling mechanisms of apoptosis. As such, this study sought to determine whether expression of

MOR-1 and MOR-1X altered cell viability constitutively, following treatment with morphine every 2 hours for 24 hours, constitutively with concomitant expression of Vpr or Tat, or following treatment with morphine every 2 hours for 24 hours with concomitant expression of Vpr or Tat. Early and late stage apoptosis was determined by Annexin/7-AAD staining in HEK293 cells transfected with pCMV-

MOR-1 or pCMV6-MOR-1X with and without co-transfection of pCDNA3-Vpr-WT or pCMV-Tat86 and with or without treatments of 10µM morphine every 2 hours for 24 hours. Results found that MOR-1 and MOR-1X expressing cells do not exhibit significant differences in the establishment of either early or late stage

253 apoptosis constitutively, with chronic, high dose morphine treatment, constitutively with concomitant expression of Vpr or Tat, or with chronic, high dose morphine treatment and concomitant expression of Vpr or Tat (Table 6.1).

Therefore, despite significant differences in the regulation of Bax protein expression, neither MOR-1 nor MOR-1X activity alters cellular viability, even in the presence of the HIV viral proteins Vpr and Tat.

Prior to the terminal execution of procaspases-3 activity and the presence of early and late stage apoptotic markers, shifting mitochondrial activity alters multiple cellular functions, including cellular metabolism. Therefore, despite the fact that no difference is seen in early and late stage apoptosis of MOR-1 and

MOR-1X expressing cells, these receptors may still divergently regulate other cellular functions such as cellular metabolism. As such, this study sought to determine whether MOR-1 and MOR-1X have opposing effects on cellular metabolism using an MTT assay, which measures the reduction of the tetrazolium dye 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide

(MTT) to insoluble formazan, a process dependent on cellular metabolic activity, specifically the activity of the mitochondrial dehydrogenase enzyme. Results found that, relative to the untreated, untransfected control, nearly every treatment condition slightly, but significantly, altered mitochondrial dehydrogenase activity

(data not shown). Therefore, significant changes in cellular metabolic activity due to opioid receptor activity were determined relative to untreated, vector- transfected cells. Accordingly, untransfected cells serum starved in HBSS media for 4 hours (Figure 6.3, lane 3), serum starved in HBSS media and treated with

254 5nM Baf for 4 hours (Figure 6.3, lane 4), or treated with 1mM CdCl2 for 1 hour

(Figure 6.3, lane 5) exhibited significantly reduced mitochondrial dehydrogenase activity. Conversely, mitochondrial dehydrogenase activity was not significantly altered in pCMV6-MOR-1-transfected cells (Figure 6.3, lane 12) or pCMV6-MOR-

1X-transfected cells (Figure 6.3, lane 18). Likewise, treatment with chronic, high dose morphine did not significantly alter mitochondrial dehydrogenase activity in vector-transfected cells (Figure 6.3, lane 7) or pCMV6-MOR-1-transfected cells

(Figure 6.3, lane 13); however, mitochondrial dehydrogenase activity was significantly reduced in pCMV6-MOR-1X-transfected cells following chronic, high dose morphine treatment (Figure 6.3, lane 19), further highlighting the functional differences between MOR-1 and MOR-1X. With respect comorbitity between opioid and HIV viral protein signaling, only vector/pCDNA3-Vpr-WT and vector/pCMV-Tat86 co-transfected HEK293 cells exhibited a signifigant, additive effect from chronic, high dose morphine treatment (Figure 6.3, lanes 8-11). While pCMV6-MOR-1X/pCDNA3-Vpr-WT co-transfected cells treated with chronic, high dose morphine treatment also exhibited decreased mitochondrial dehydrogenase activity, this was not significantly different from untreated pCMV6-MOR-

1X/pCDNA3-Vpr-WT co-transfected cells and therefore should not be regarded as a combinational effect.

255

102 102 ** ** 100 100

** 98 98 ** **

96 ** 96 ** ** 94 ** 94 ** ** 92 92

# 90 90 Mitochondrial Dehydrogenase Dehydrogenase Mitochondrial Activity (% Control) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 - 10 - - - - 10 - 10 - 10 - 10 - 10 - 10 - 10 - 10 - 10 Morphine (µM) ------Vpr Vpr Tat Tat - - Vpr Vpr Tat Tat - - Vpr Vpr Tat Tat HIV - - - - - + + + + + + ------Vector ------+ + + + + + ------MOR-1 ------+ + + + + + MOR-1X HBSS 5nM 1mM Baf. CdCl2

Figure 6.3: Morphine-mediated reduction in cellular metabolism by MOR-1X is not synergistic with HIV viral protein signaling. Cellular metabolism, as measured by mitochondrial dehydrogenase activity, was examined in untransfected, untreated HEK293 cells (lane 1), untransfected cells treated with

10µM morphine every 2 hours for 24 hours (lane 2), untransfected cells serum starved in HBSS media for 4 hours (lane 3), untransfected cells serum starved in

HBSS media and treated with 5nM Baf for 4 hours (lane 4), untransfected cells treated with 1mM CdCl2 for 1 hour (lane 5), vector-transfected, untreated cells

(lane 6), vector-transfected cells treated with 10µM morphine every 2 hours for

24 hours (lane 7), vector/pCDNA3-Vpr-WT co-transfected, untreated cells (lane

8), vector/pCDNA3-Vpr-WT co-transfected cells treated with 10µM morphine every 2 hours for 24 hours (lane 9), vector/pCMV-Tat86 co-transfected, untreated cells (lane 10), vector/pCMV-Tat86 co-transfected cells treated with 10µM morphine every 2 hours for 24 hours (lane 11), pCMV6-MOR-1-transfected, untreated cells (lane 12), pCMV6-MOR-1-transfected cells treated with 10µM

256 morphine every 2 hours for 24 hours (lane 13), pCMV6-MOR-1/pCDNA3-Vpr-WT co-transfected, untreated cells (lane 14), pCMV6-MOR-1/pCDNA3-Vpr-WT co- transfected cells treated with 10µM morphine every 2 hours for 24 hours (lane

15), pCMV6-MOR-1/pCMV-Tat86 co-transfected, untreated cells (lane 16), pCMV6-MOR-1/pCMV-Tat86 co-transfected cells treated with 10µM morphine every 2 hours for 24 hours (lane 17), pCMV6-MOR-1X-transfected, untreated cells (lane 18), pCMV6-MOR-1X-transfected cells treated with 10µM morphine every 2 hours for 24 hours (lane 19), pCMV6-MOR-1X/pCDNA3-Vpr-WT co- transfected, untreated cells (lane 20), pCMV6-MOR-1X/pCDNA3-Vpr-WT co- transfected cells treated with 10µM morphine every 2 hours for 24 hours (lane

21), pCMV6-MOR-1X/pCMV-Tat86 co-transfected, untreated cells (lane 22), and pCMV6-MOR-1X/pCMV-Tat86 co-transfected cells treated with 10µM morphine every 2 hours for 24 hours (lane 23) using a colorimetric MTT assay (mean ±

SEM; * = p ≤ 0.05, # = 48%).

257 Table 6.1: Viability of MOR-1 and MOR-1X expressing HEK293 cells.

Live Early-Phase Late-Phase

1

- 1X - - + - + + - (Annexin /7-AAD ) (Annexin /7-AAD ) (Annexin /7-AAD ) HIV (µM) Vector MOR MOR Morphine % Gated p-value % Gated p-value % Gated p-value

- - - - - 93.2 1.3 3.65

10 - - - - 91.6 0.58 1.5 0.42 4.45 0.57

- - + - - 94.15 0.73 0.65 0.13 3.65 1.00

10 - + - - 96.55 0.34 0.5 0.11 2.2 0.41

- - + - - 95.65 0.45 0.3 0.13 2.8 0.60

10 - + - - 95.05 0.54 0.75 0.17 3.15 0.75

- - + - - 94.35 0.68 0.75 0.21 3.35 0.84

10 - + - - 94.5 0.65 0.5 0.11 3.5 0.92

HBSS - - - - 92.35 0.83 1.5 0.83 4.65 0.60

5nM Baf - - - - 85.25 0.22 2 0.32 9.3 0.13

1mM CdCl2 - - - - 5.75 0.00 12.25 0.17 81.9 0.01

- - - + - 95.95 0.41 0.55 0.15 2.3 0.45

10 - - + - 96.9 0.30 0.45 0.20 2.15 0.40

- Vpr - + - 95.9 0.43 0.6 0.13 2.55 0.55

10 Vpr - + - 96.1 0.38 0.5 0.11 2.2 0.41

- Tat - + - 95.25 0.50 0.45 0.13 3.1 0.74

10 Tat - + - 96.1 0.40 0.65 0.17 2.3 0.45

- - - - + 95.35 0.49 0.55 0.15 2.75 0.58

10 - - - + 95.05 0.54 0.8 0.20 2.8 0.59

- Vpr - - + 95.6 0.45 0.75 0.17 2.45 0.48

10 Vpr - - + 95 0.55 0.55 0.15 3.3 0.81

- Tat - - + 94.9 0.58 0.9 0.29 3 0.71

10 Tat - - + 95.85 0.41 0.65 0.28 2.6 0.58

6.4 Discussion

It is well established that opioid receptors have functional significance aside from modulating nociception. These additional functions include mediating immunosuppression and regulating autophagic and apoptotic signaling.

Consequently, these opioid-mediated effects are of great importance in HIV infection, as they directly and indirectly enhance susceptibility to HIV, increase viral replication, and synergistically interact with direct and indirect mechanisms 258 of HIV-associated toxicity, particularly in the CNS. Unfortunately, understanding of the influence each individual MOR isoforms has on these cellular and viral processes is particularly lacking; however, MOR-1K expression in HIV infection is correlated with the severity of neuropathology and excessive MOR-1K signaling is thought to contribute to opioid-mediated exacerbation of HAND, suggesting that the variable expression of individual MOR isoform may have significant physiological consequences, particularly in HIV-associated neuropathology

(Dever, Costin et al. 2014). As such, this study sought to determine whether distinct differences in autophagic and apoptotic signaling cascades, as well as subsequent cellular functions, occurred between cells expressing the stereotypical MOR-1 receptor and the alternatively spliced isoform MOR-1X, the expression of which is inversely regulated by morphine and the HIV viral protein

Tat and which exhibits unique regulation of MAPK signaling. Furthermore, this study sought to determine whether the apoptotic signaling cascades stimulated by MOR-1 and MOR-1X exhibit differences in the exacerbation or rescue of HIV- mediated cellular dysfunction.

Investigation of autophagic mechanisms was performed by examining the expression of the autophagosomal protein markers Beclin-1 and microtubule- associated protein light chain 3 (LC3). Beclin-1 is an evolutionarily conserved Atg protein essential to the assembly of autophagosomes. Likewise, LC3 is a mammalian autophagosomal ortholog of yeast Atg8 and exists in the cell as

ProLC3, LC3-I, and LC3-II, although ProLC3 is typically converted to cytoplasmic

LC3-I shortly after synthesis. The conversion of LC3-I to LC3-II by enzymatic

259 cleavage of a 22 amino acid region of the C-terminal domain and conjugation with phosphatidylethanolamine (PE) is commonly assessed as a method of measuring autophagic activity given that this process converts LC3 protein from its cytosolic form to its membrane-bound form, which selectively localizes to forming and newly formed autophagosomes (Kim, Rodriguez-Enriquez et al.

2007, Mizushima and Yoshimori 2007). Results from this study found that expression of Beclin-1 was not significantly altered by chronic, high dose morphine treatment in cells expressing MOR-1 or MOR-1X (Figure 6.1A, lanes 5-

8; Figure 6.1C, lanes 5-8) however, positive controls using either serum starvation and the autophagosomal inhibitor bafilomycin (Baf), which prevents the maturation of autophagic vacuoles by inhibiting fusion between autophagosomes and lysosomes, or the apoptotic compound CdCl2 also did not exhibit significantly altered expression of Beclin-1 (Figure 6.1A, lanes 9-10;

Figure 6.1C, lanes 9-10) and, as such, it is difficult to form a definitive conclusion on the effect of MOR-1X signaling on autophagic protein expression. However, although conversion of LC3-I to LC3-II was not significantly altered in cells expressing MOR-1 or MOR-1X (Figure 6.1B, lanes 5-8; Figure 6.1C, lanes 5-8), positive controls did significantly increase the conversion of LC3-I to LC3-II, confirming increased autophagosomal formation under certain stress conditions

(Figure 6.1B, lanes 9-10, Figure 6.1C, lanes 9-10). However, western blot analysis of LC3 conversion is complicated by the fact that LC3-II is itself degraded by the formation of autophagolysosomes (Kim, Rodriguez-Enriquez et al. 2007, Mizushima and Yoshimori 2007). Therefore, while this study did not find

260 a significant impact on autophagic mechanisms in MOR-1 and MOR-1X expressing cells, both constitutively and following chronic, high dose morphine treatment, investigation of these mechanisms using more sensitive measures may highlight subtle differences between MOR-1 and MOR-1X autophagic signaling cascades.

Investigation of intrinsic signaling mechanisms of apoptosis was performed by examining the expression of Bax protein, a pro-apoptotic member of the Bcl-2 protein family essential in neuronal apoptosis that translocates and inserts into the mitochondrial outer membrane, facilitating the release of pro- apoptotic factors (McGinnis, Gnegy et al. 2008). Results from this study found that overall expression of Bax protein was not significantly altered by chronic, high dose morphine treatment in cells expressing MOR-1 (Figure 6.2B, lanes 2-

3) but was significantly decreased in cells expressing MOR-1X both constitutively and following chronic, high dose morphine treatment (Figure 6.2B, lanes 8-9).

Similarly, concomitant expression of HIV viral proteins Vpr and Tat by transfection of pCDNA3-Vpr-WT and pCMV-Tat86 expression plasmids, respectively, did not significantly alter Bax protein expression in MOR-1 transfected cells (Figure 6.2B, lanes 4-7); however, the down-regulation of Bax protein expression in MOR-1X expressing cells by chronic, high dose morphine was maintained in pCDNA3-Vpr-WT (Figure 6.2B, lanes 11) and pCMV-Tat86

(Figure 6.2B, lanes 13) co-transfected cells. This finding is particularly interesting in the context of HIV-associated neuropathogenesis as it is typically thought that opioids reduces the threshold of neurotoxicity due to convergent signaling events

261 within the intrinsic apoptotic pathway which potentiate HIV-mediated apoptotic signaling, thereby exacerbating the marginally cellular and viral cytotoxic products (Hauser, El-Hage et al. 2006). Despite these differences in Bax expression, chronic, high dose morphine treatment of both MOR-1 and MOR-1X expressing cells, with and without concomitant transfection of pCDNA3-Vpr-WT and pCMV-Tat86 expression plasmids, did not significantly alter cell viability, as both early and late stage apoptosis was not observed (Table 6.1). This finding does not necessarily dismiss potential synergism between mechanisms of HIV- associated apoptotic signaling and the distinct signaling pathways of MOR-1 and

MOR-1X, as indirect mechanisms of neurotoxicity, involving glial dysfunction, the loss of trophic support, and the release of inflammatory, cytotoxic, and excitotoxic compounds were not investigated. Furthermore, current evidence increasingly supports the notion that neuronal apoptosis in HIV-associated neurocognitive dysfunction is preceded by sublethal synaptodendritic injury, subsequent loss of neural circuitry, and alterations in various cellular functions. As such, examination of cellular metabolism using an MTT assay found distinct differences between

MOR-1 and MOR-1X. Accordingly, mitochondrial dehydrogenase activity, a measure of cellular metabolism, was significantly decreased with chronic, high dose opioid treatment in pCMV6-MOR-1X-transfected cells (Figure 6.3, lanes 18-

19), but not pCMV6-MOR-1-transfected cells (Figure 6.3, lanes 12-13).

Furthermore, the unique opioid signaling pathways of both MOR-1 and MOR-1X do not appear to converge on either Vpr or Tat signaling cascades (Figure 6.3, lanes 14-17 and 20-23). The observation that chronic, high does morphine

262 treatment of pCMV6-MOR-1X-transfected cells decreases cellular metabolism is unexpected, as MOR-1X was found to decrease the pro-apoptotic protein Bax, presumably increasing mitochondrial metabolism. The potential mechanisms through which MOR-1X mediate these unique effects are numerous. RSK- mediated regulation of cellular viability is primarily due to phosphorylation and/or inactivation of pro-apoptotic proteins, as observed here; however, RSK1/2, as well as MSK2, may also utilize mechanisms involving downstream transcriptional factors like p53 and CREB, which subsequently direct the synthesis of pro- and anti-apoptotic Bcl-2 family member proteins, respectively (Hauge and Frodin

2006, Anjum and Blenis 2008, Krishna and Narang 2008, Gurevich 2013).

Likewise, increasing evidence suggests that cellular metabolism is regulated by

MAPKs, such as ERK1/2 and p90 RSK, through complex signaling pathways mediating substrate phosphorylation and transcriptional regulation (Gehart,

Kumpf et al. 2010). Therefore, decreased Bax expression and cellular metabolic activity in MOR-1X expressing cells, constitutively and following morphine treatment, respectively, is most likely due to dynamic and complex interactions between independent ERK/RSK and MSK2 signaling mechanisms involving direct phosphorylation of downstream substrates as well as transcriptional regulation.

263 CHAPTER 7 – CONCLUSIONS AND FUTURE DIRECTIONS

7.1 Conclusions

7.1.1 Alternative splicing of the MOR is inversely regulated by morphine and Tat through modulation of ASF/SF2 expression

The SH-SY5Y cell line, a model for dopaminergic neurons, was found to express numerous alternatively spliced isoforms of the MOR. Although the expression of most isoforms was not consistently altered by morphine treatment, expression of the MOR-1X isoform, which is generated by the substitution of the distal exon 4 with the proximal exon X, was consistently and significantly increased both 1 hour and 24 hours after morphine treatment. Additionally, this increase in MOR-1X expression was attenuated by concomitant treatment with recombinant Tat protein, an early gene product of HIV viral infection known to promiscuously interact with RNA, in a dose-dependent manner. A proposed mechanism was found to involve the regulation of an essential splicing factor,

ASF/SF2, that facilitates the selection of proximal 5’ splice sites in a concentration-dependent manner. Accordingly, morphine was found to increase

ASF/SF2 protein expression in SH-SY5Y cells, presumably enhancing the utilization of proximal 5’ splice sites such as exon X. Furthermore, this morphine- mediated increase in ASF/SF2 protein expression was attenuated by pre- treatment with recombinant Tat. The role of ASF/SF2 expression in regulating

MOR-1 mRNA splicing is further supported by the fact that overexpression of

ASF/SF2 in the absence of morphine was sufficient to increase MOR-1X mRNA.

264 A mechanism through which morphine and Tat regulate ASF/SF2 expression has not been identified, however results from this study suggest that it is independent of SFRS1 transcriptional activity. However, mild, but insignificant, transcriptional regulation was observed, and, therefore, transcriptional regulatory mechanisms may be elucidted through the use of more sensitive measures. As such, it can only be concluded that morphine and Tat inversely regulate the alternative splicing of the MOR-1X mechanism by altering expression of the ASF/SF2 splicing factor through an unknown mechanism.

7.1.2 Unique MAPK signaling of MOR-1X is attributed to additional phosphorylation motifs of the C-terminal domain

The stereotypical MOR-1 isoform and the alternatively spliced isoform

MOR-1X are nearly identical, as exon 1, exon 2, and exon 3 are conserved in the mRNA transcript. The only distinction between these two isoforms is the selective incorporation of either exon 4 or exon X, respectively, as the terminal exon, which encodes the distal portion of the C-terminal domain. Given that this region has high functional significance, as it is the site of multiple phosphorylation reactions that mediate conformational changes and initiate signal transduction cascades, unique motifs within this region may convey distinct signaling properties to each receptor. Comparison of the MOR-1 and MOR-1X distal C- terminal domains found that the MOR-1 domain has no additional phosphorylation motifs whereas the MOR-1X domain has 2 additional PKA phosphorylation motifs as well as a second TXXXPS motif recognized as an agonist-induced phosphorylation motif conserved within the opioid receptor 265 family. As such, the MOR-1X receptor has a far greater potential for phosphorylation than MOR-1. Investigation of signaling differences, specifically within MAPK signaling cascades, in the MOR-null cell line HEK293 found that

MOR-1 and MOR-1X have distinct affects on the expression of phosphorylated

ERK1/2, p90 RSK1/2, and MSK2, both constitutively and following acute morphine treatment. Therefore, given that these receptors are identical in all other areas, it is likely that these differences in constitutive and agonist-mediated signaling are attributed to unique C-terminal domains of each receptor, although this was not directly confirmed.

7.1.3 MOR-1X constitutively decreases Bax expression and decreases cellular metabolism upon chronic, high dose morphine treatment

Opioids have been found to modulate cellular viability through the activation and/or inhibition of various autophagic and apoptotic signaling cascades. This capacity to stimulate pro- and anti-apoptotic and autophagic signaling cascades has many functional consequences for the abuse of opioids, including the well-documented acceleration of HIV-associated neurocognitive dysfunction by opioids through the convergence of opioid- and HIV-mediated signaling cascades and the exacerbation of sublethal neuronal injury. However, the synergistic affects of opioids in the exacerbation of HIV neuropathogenesis have only been attributed generally to MOR activity and investigation of individual

MOR isoform contributions to this process is severely lacking. Given the structural differences between MOR-1 and MOR-1X, the divergence in MAPK signaling, and the regulation of MOR-1X expression by morphine and Tat, it is 266 likely that MOR-1 and MOR-1X have unique roles in the progression of neuronal dysfunction in HIV. Investigation of autophagic mechanisms using the MOR-null cell line HEK293 found no difference between MOR-1 and MOR-1X in the expression of Beclin-1 or the conversion of LC3-I to LC3-II both constitutively and following chronic, high dose morphine treatment generally regarded as cytotoxic.

Conversely, MOR-1X, but not MOR-1, significantly decreased the expression of the pro-apoptotic Bcl-2 family member protein Bax, both constitutively and following chronic, high dose morphine treatment. Furthermore, the morphine- mediated decrease of Bax protein in MOR-1X expressing cells was maintained, but not exacerbated, by concomitant expression of Vpr and Tat. Despite this difference, cell viability of MOR-1 and MOR-1X expressing cells was not significantly altered by constitutive receptor expression, chronic, high dose morphine treatment, or concomitant HIV viral protein expression. This result is most likely due to an insufficient induction of cell death, thereby masking more subtle difference in the regulation of cell viability; however, cell death is often preceded by sublethal changes in cellular function that may be more readily identifiable. Indeed, investigation of cellular metabolism found that chronic, high dose morphine treatment of MOR-1X, but not MOT-1, significantly reduced mitochondrial dehydrogenase activity. As with Bax protein expression, this effect was maintained, but not exacerbated, by concomitant expression of Vpr and Tat.

Therefore, it can only be concluded that MOR-1X displays a unique regulation of

Bax protein expression constitutively and mitochondrial dehydrogenase activity

267 following chronic, high dose morphine treatment, but does not significantly alter cell viability within the timeframe investigated.

7.2 Future Studies

7.2.1 Cell-type specificity in opioid pharmacology

One of the major difficulties in studying opioid pharmacology is the disparity of opioid receptor subtypes and isoforms in different tissues due to various mechanisms of epigenetic, transcriptional, and post-transcriptional regulation. Epigenetic mechanisms not only exhibit temporal and cell-type specific diversity but also exhibit diversity across ethnicity and opioid drug usage, as increased CpG methylation of OPRM1 is found in African Americans, heroin addicts, and former addicts administered methadone as a therapeutic. Similarly, hundreds of single nucleotide polymorphisms (SNPs) identified within opioid receptor genes exhibit ethnic diversity in their frequency. Transcriptional regulation of OPRM1, while lacking known ethnic diversity, is still known to occur in a cell-type specific manner, with suppression being mediated through the expression of REST/NRSF in non-neuronal cell lines. Furthermore, the expression and activity of transcription factors, as well as that of post- translational regulatory factors like opioid receptor-specific miRNAs, is modulated by opioid receptor signaling. Together, these epigenetic, transcriptional, and post-transcriptional mechanisms have well defined roles in generating diverse

MOR expression profiles across different cell-types and ethnic backgrounds; however, characterization of their roles in regulating the expression of individual

268 MOR isoforms is severely lacking. Therefore, given the emerging importance of individual MOR isoforms in opioid signaling, extensive genetic studies involving the characterization of ethnic and cell-type-specific diversity in and opioid- mediated modulation of CpG methylation, histone modification specifically by

OPRM1-targeting HDAC1 and HDAC2 or by enzymatic acetylation, methylation, ubiquitination, sumoylation, and/or phosphorylation, transcription factor expression and activity including that of AP1, SP1, SP3, and CREB, and opioid- specific miRNA synthesis including that of miR-190, miR-339 and let-7 miRNA, are needed in order to understand both the genetic mechanisms through which diversity in MOR isoform expression is generated and how this translates to differences in opioid pharmacology.

In addition to the genetic regulation of MOR isoform expression, cell-type specific differences also have implications in the investigation of downstream opioid signaling cascades. Investigation of specific opioid receptor signaling cascades has benefited from the cloning of opioid receptors as each receptor subtype, and some receptor isoforms, can be examined independently (Reisine and Bell 1993). As such, criteria for choosing an appropriate cell line to examine opioid receptors independently include the lack of endogenous opioid receptor expression and accessibility for transfections. Commonly used cell lines that fit these criteria include the non-neuronal Chinese hamster ovary (CHO), human embryonic kidney (HEK) 293, and African green monkey kidney (COS-7) cell lines. However, expression of these receptors in non-neuronal cell lines may generate different pharmacological or biochemical profiles due to the cell-type

269 specific disparity in the expression of endogenous G proteins and second messengers involved in the signal transduction pathways (Standifer and

Pasternak 1997, Connor and Christie 1999, Milligan 2003, Pan 2003, Horner and

Zadina 2004). The generation of opioid receptor knockout mice (Pasternak 2010) has aided in the examination of individual opioid receptors in different neuronal tissue types but presents its own problem of species-specific differences in opioid receptor splicing and pharmacology, as the expression of opioid receptor isoforms, the mechanisms of opioid metabolism (Trescot, Datta et al. 2008,

Pasternak and Pan 2013), and certain opioid-interacting physiological systems, such as the immune system (Bidlack, Khimich et al. 2006), are not well conserved between species. Furthermore, the existence of unidentified SNPs within cell lines, plasmids, or knockout strains can have significant functional consequences in transcription efficiency, mRNA expression, ligand binding, efficacy, potency, opiate metabolism, and mechanisms of signal transduction, including G protein coupling, receptor phosphorylation, desensitization, internalization, recycling, and constitutive activity (Chavkin, McLaughlin et al.

2001, Huang, Li et al. 2001, Mayer and Hollt 2001, Lotsch and Geisslinger 2005,

Pang, Ithnin et al. 2012). Therefore, interpretations of opioid receptor studies utilizing non-native cell types is limited due to the fact that the restricted cell environment may not accurately reflect the milieu of signaling factors utilized in vivo (Pan 2003).

270 7.2.2 Complexity of alternative splicing mechanisms

Although this study found that overexpression of ASF/SF2 is sufficient to increase the expression of MOR-1X, presumably by favoring the selection of the proximal MOR-1X 5’ splice site and supporting the notion that elevation of individual splicing factors can activate weak splice sites (Fu, Mayeda et al. 1992,

Wang and Manley 1995, Blencowe, Bowman et al. 1999), it is highly unlikely that this is the only mechanism through which alternative splicing of the MOR-1X isoform is regulated as no single splicing factor has been identified as essential for the specificity of splicing in any system. Therefore, multiple studies examining the role of additional splicing mechanisms in the synthesis of MOR-1X, and other

MOR isoforms, are essential. This includes investigation of co-transcriptional splicing mechanisms such as the recruitment and kinetic models of RNA polymerase II interaction, which may be modified through opioid-mediated phosphorylation of the RNA polymerase II C-terminal domain. The contribution of additional splicing factors must also be characterized, as many of these factors, including ASF/SF2, are, themselves, expressed as alternatively spliced isoforms with different, and sometimes autoregulatory, splicing functions (Sun, Zhang et al. 2010). Furthermore, post-transcriptional modifications, including phosphorylation and ubiquitination, of splicing factors are also likely to play a role in opioid-mediated regulation of alternative splicing mechanisms, as these modifications are essential to the subcellular localization, activity, and proteasomal degradation of splicing factors (Misteli 2000, Lin and Fu 2007,

Risso, Pelisch et al. 2012). As such, characterization of protein kinase and

271 phosphatase expression following opioid exposure would be beneficial in understanding opioid-mediated regulation of splicing factor activity. Aside from the characterization of their function and regulation, the role of individual splicing factors in specific transcripts has been complicated in the past by the inability to identify specific binding sites within mRNA transcripts and to accurately predict splice site usage; however, recent bioinformatics approaches and experimental techniques, such as SELEX and CLIP, have been useful in identifying ESE and

ESS motifs and the binding specificity of individual SR proteins, allowing for a better prediction of SR protein interaction using pre-mRNA sequence (Li, Lee et al. 2007, Lin and Fu 2007, Long and Caceres 2009, Kelemen, Convertini et al.

2013). Utilization of these assays in conjunction with new a class of indole derivative splicing inhibitors, which have selective action against the ESE- dependent activity of SR proteins (Keriel, Mahuteau-Betzer et al. 2009), and sensitive genome-wide microarrays will allow for comprehensive detection, measurement and characterization of known and predicted mRNA isoforms

(Griffith, Griffith et al. 2010). As such, new tools being developed to explore regulatory elements, scan previously uncharacterized exons, and predict tissue- dependent splicing patterns will be beneficial for future studies (Barash, Calarco et al. 2010).

7.2.3 In vitro models of HIV-associated neurocognitive dysfunction

The application of HIV viral proteins individually, either as recombinant protein or as transfected expression plasmids, in a homogeneous cell culture is beneficial in the characterization of direct interactions between opioids and 272 specific viral proteins. Utilizing this approach, the current study was able to determine unique roles for specific HIV viral proteins, specifically Tat, in the regulation of alternative splicing machinery as well as in cross-interactions with downstream opioid signaling cascades. However, the lack of accessory cells and productive viral replication may not accurately reflect the interactions between individual HIV viral proteins and the physiological opioid system, as many essential indirect interactions would be absent. For example, multiple pro- inflammatory cytokines, which are secreted from both infected and uninfected immune cells such as macrophages and microglia, are known to regulate

OPRM1 gene expression. Additionally, peripheral opioid effects, which are not readily detectable, are rapidly induced after the induction of inflammatory pathways, suggesting that previously inactive opioid receptors are activated by changes in the inflammatory milieu (Stein, Schafer et al. 1995). The greatest omittance of this in vitro system, however, is the essential, but indirect contribution of glial cells to HIV-associated neurocognitive dysfunction. HIV- mediated glial dysfunction, particularly of microglia and astrocytes, and the subsequent loss of metabolic and trophic support and release of neurotoxic, excitotoxic, and inflammatory compounds mediate the indirect model of HAND development and is considered to be the primary mechanism through which HIV and opioids individually and synergistically cause neuronal damage. In the absence of productively infected glial cells, establishment and exacerbation of neuronal dysfunction by HIV viral proteins and opioids is only possible through the direct model of HAND development, in which HIV viral proteins and opioids

273 interact directly with neurons to stimulate extrinsic and intrinsic apoptotic pathways; however, these direct mechanisms of HIV- and opioid-mediated neuronal dysfunction are considered secondary to indirect mechanisms mediated by glial dysfunction and, furthermore, may not be translatable to a non-neuronal cell line. As such, an in vitro co-culture model in which both productively infected glial cells and neighboring neuronal cells are treated with opioids would better replicate in vivo conditions. With regard to investigating specific MOR isoform contributions, however, this model is complicated by the cell-type specific expression of endogenous MOR isoforms. Therefore, the generation of a completely MOR-null, HIV infected CNS co-culture model in which individual

MOR isoforms can be selectively expressed would be highly beneficial in determining the roles of MOR isoforms in exacerbating HIV neurocognitive dysfunction.

274

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