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The structure of loop 2 is important for agonist and ethanol sensitivity in glycine and GABA Alpha receptors

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The structure of loop 2 is important for agonist and ethanol sensitivity in glycine and GABA Alpha receptors

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Content THE STRUCTURE OF LOOP 2 IS IMPORTANT FOR AGONIST AND ETHANOL
SENSITIVITY IN GLYCINE AND GABA A RECEPTORS

by

Daya Perkins

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(MOLECULAR PHARMACOLOGY AND TOXICOLOGY)

May 2010

Copyright 2010 Daya Perkins
ii

EPIGRAPH

P.P.S
“Don't you drink? I notice you speak slightingly of the bottle. I have drunk since I
was fifteen and few things have given me more pleasure. When you work hard all
day with your head and know you must work again the next day what else can
change your ideas and make them run on a different plane like whisky? When you
are cold and wet what else can warm you? Before an attack who can say anything
that gives you the momentary well-being that rum does? The only time it isn't good
for you is when you write or when you fight. You have to do that cold. But it always
helps my shooting. Modern life, too, is often a mechanical oppression and liquor is
the only mechanical relief."

------Ernest Hemingway------
to Ivan Kashkin, 1935
From Selected Letters 1917 – 1961
iii

DEDICATION

To
Jason, Mill and Monk
for teaching me the importance of
sleeping, playing and eating, respectively.

iv

ACKNOWLEDGEMENTS

Personal

Deepest gratitude to…

My parents, Janaki and Kalidas, for raising me to question everything

My husband, Jason, whose intelligence, good humor and encouragement made this
journey possible

My advisor Ron, for his constant support, invaluable scientific input and seemingly
constant availability to assist when needed

My co-advisor Daryl, for his enthusiasm and his support of my eclectic endeavors

My lab members and friends who have always been there to help

Statement of Contributions to works contained in this Dissertation

This dissertation is composed of the author’s original work and contains no material
previously published or written by any other individual except where due reference
is made. All data contained herein was collected and analyzed by D. Perkins. The
authorship on published manuscripts is described in greater detail in the following
page. Molecular modeling was carried out by Dr. James Trudell at Stanford
University. Drs. Alkana and Davies provided discussion and revisions to the
manuscript.

v
Authorships

Published and in press works by the Author incorporated into the Dissertation

Perkins DI, Trudell JR, Crawford DK, Alkana RL, Davies DL. Molecular targets and
mechanisms of ethanol action in Glycine receptors. Invited Review In Press
Pharmacology & Therapeutics. A portion of this review incorporated as Chapter 1,
was co-written by Daniel K. Crawford.
Perkins DI, Trudell JR, Crawford DK, Alkana RL, Davies DL. Targets for ethanol
action and antagonism in loop 2 of the extracellular domain of glycine receptors. J
Neurochem. 2008 Aug;106(3):1337-49. Incorporated as Chapter 2
Perkins DI, Trudell JR, Crawford DK, Asatryan L, Alkana RL, Davies DL. Loop 2
structure in glycine and GABA A receptors plays a key role in determining ethanol
sensitivity. J Biol Chem. 2009 Oct 2;284(40):27304-14. Incorporated as Chapter 4

Additional works by the author relevant to this dissertation but not forming
part of it
Crawford DK, Perkins DI, Trudell JR, Bertaccini EJ, Davies DL, Alkana RL. Roles for
Loop 2 residues of alpha1 glycine receptors in agonist activation. J Biol Chem. 2008
Oct 10;283(41):27698-706.
Research Support
NIH National Institute on Alcohol Abuse and Alcoholism F31 AA017569 (D.I.P) and
AA03972 (R.L.A.)

The USC School of Pharmacy
vi
TABLE OF CONTENTS

Epigraph ii

Dedication iii

Acknowledgements iv

List of Tables viii

List of Figures ix

Abbreviations xi

Abstract xii

Chapter 1 Introduction 1
A. Background 1
B. Glycine and GABA A receptors – targets for ethanol action 5
C. Strategies for identifying sites and mechanisms of ethanol action 12

Chapter 2 Targets for ethanol action and antagonism in Loop 2 of the
extracellular domain of glycine receptors
17
1. Chapter 2 Abstract 17
2. Introduction 18
3. Materials and Methods 23
4. Results 28
Glycine EC50s in WT and mutant α1GlyRs 28
Ethanol sensitivity in WT and mutant α1GlyRs 29
Pressure antagonism sensitivity in WT and mutant α1GlyRs 31
Ethanol and pressure antagonism sensitivity in α2 GlyRs 35
5. Discussion 37

Chapter 3 The presence of charge at position 52 in extracellular domain
Loop 2 of glycine receptors plays different roles in ethanol action and
antagonism
46
1. Chapter 3 Abstract 46
2. Introduction 47
3. Materials and Methods 48
4. Results 54
Glycine EC50s in WT and mutant α1GlyRs 54
Cell surface expression of WT and mutant α1GlyRs 56

vii
Negatively charged amino acid substitutions at position 52
differentially affect sensitivity to ethanol
56
Polarity controls sensitivity to pressure antagonism of ethanol even
in the presence of a charge at position 52

57
Binding a negatively charged MTS reagent at position 52 does not
affect ethanol sensitivity
59
Structure not charge affects ethanol sensitivity at position 52 60
5. Discussion 61

Chapter 4 Loop 2 structure in glycine and GABA A receptors plays a key
role in determining ethanol sensitivity
66
1. Chapter 4 Abstract 66
2. Introduction 67
3. Materials and Methods 71
4. Results 79
Agonist concentration response 79
Ethanol concentration response 82
Additional tests of receptor function 84
Molecular modeling of WT vs. δL2 GlyR 87
5. Discussion 90

Chapter 5 Overall Discussion and Conclusions 99

Bibliography 102

viii
LIST OF TABLES

Table 2.1 Summary of non-linear regression analysis results for
glycine concentration responses and differences in ethanol
sensitivity WT and mutant α1 and α2 GlyRs shown in
terms of increasing polarity of residue at position 52 or 59
29

Table 2.2 Alignment of a portion of the amino terminal regions from
human α1GlyR, α1A52S GlyR and α2GlyR subunit
sequences
35

Table 3.1 Summary of non-linear regression analysis results for
glycine concentration responses and differences in ethanol
sensitivity WT and mutant α1 GlyRs shown in terms of
charge of residue at position 52
55

Table 4.1 Loop 2 sequence alignment for the α1GlyR subunit, δ and γ
GABA AR subunits, α1nAChR subunit and GLIC
72

Table 4.2 Summary of non-linear regression analysis results for
glycine concentration responses in WT, δL2 and γL2
mutant α1GlyRs
80

Table 4.3 Summary of non-linear regression analysis results for
GABA concentration responses in and mutant GABA ARs.
81

ix
LIST OF FIGURES

Figure 2.1 Concentration-response curves for glycine (10-3,000 µM)
activated chloride currents in Xenopus oocytes expressing WT
and mutant α1GlyR subunits
28

Figure 2.2 Polarity of the residue at position 52 in α1GlyRs determines
sensitivity to ethanol
30

Figure 2.3 The polarity and hydrophobicity of substitutions at position 52
are significantly correlated with sensitivity of α1GlyRs to
ethanol
31

Figure 2.4 4 (A). Pressure significantly antagonizes ethanol potentiation in
α1 GlyRs; (B) Pressure Does not Antagonize Ethanol
potentiation in mutant α1A52S GlyRs
32

Figure 2.5 Pressure antagonizes ethanol in α1GlyRs that have a non-polar
residue at position 52
33

Figure 2.6 The polarity of the residue at position 52 in α1GlyRs determines
the receptors sensitivity to pressure antagonism of ethanol
34

Figure 2.7 (A) Concentration-response curves for glycine (10-3,000 µM)
activated Cl- currents in Xenopus oocytes expressing WT and
mutant α2 glycine receptor subunits; (B) Replacing the polar
threonine at position 59 in WT α1GlyRs with the non-polar
alanine changes the α2GlyRs to be α1GlyR-like in response to
ethanol and pressure antagonism of ethanol
36

Figure 3.1 Concentration-response curves for glycine (1-30,000 µM)
activated chloride currents in Xenopus oocytes expressing WT
and mutant α1GlyR subunits
54

Figure 3.2 Differences in sensitivity to ethanol and Glycine are not due to
differences in total or cell surface expressed protein
56

Figure 3.3 Charge of the residue at position 52 in α1GlyRs does not
determine sensitivity to ethanol
57

Figure 3.4 Pressure Does not Antagonize Ethanol potentiation in mutant
GlyRs with charged residues at position 52
58

x

Figure 3.5

Negative charge at position 52 of the α1GlyR is not important
for agonist or ethanol action.

59

Figure 3.6 The structure of the amino acid at position 52 plays a role in
ethanol sensitivity of α1GlyRs
60

Figure 4.1 Concentration-response curves for glycine (1-3,000 µM)
activated chloride currents in Xenopus oocytes expressing WT,
δL2 and γL2 α1GlyR subunits
79

Figure 4.2 Western blot analysis of total and cell surface protein from
Xenopus oocytes expressing WT, δL2 and γL2 α1GlyR subunits
80

Figure 4.3 Concentration-response curves for GABA (1-10,000 μM)
activated chloride currents in Xenopus oocytes expressing WT
and mutant δL2 GABA AR subunits.
81

Figure 4.4 The δL2 GlyR mutation decreased the threshold for ethanol
sensitivity and increased the degree of ethanol potentiation
82

Figure 4.5 The δL2 GABA AR mutation decreased the threshold for ethanol
sensitivity and increased ethanol potentiation in GABA ARs
83

Figure 4.6 The δL2 GlyR mutation did not affect biphasic modulation by
Zn
2+
in GlyRs
84

Figure 4.7 The δL2 GlyR mutation did not affect inhibition by strychnine in
GlyRs
85

Figure 4.8 The δL2 GlyR mutation did not affect inhibition by picrotoxin 86

Figure 4.9 The δL2 GABA AR mutation did not affect sensitivity to diazepam
in GABA ARs
87

Figure 4.10 Molecular models of WT and δL2 α1GlyRs threaded on GLIC. 89
xi
ABBREVIATIONS

5HT3R, 5-hydroxytryptamine 3 receptor;

AMPA, α -amino-3-hydroxyisoxazolepropionic acid

COMP, cartilage oligomeric matrix protein

DMSO, Dimethyl sulfoxide

GABA AR, γ-aminobutyric acid type-A receptor

GLIC, GLIC, Gloeobacter violaceus pentameric ligand-gated ion channel homologue

GlyR, glycine receptor

LGIC, ligand-gated ion channel

MTSES, 2-sulfonatoethyl methanethiosulfonate

nAChR nicotinic acetylcholine receptor

NMDA, N-methyl D-aspartate

PMTS, propyl methanethiosulfonate

SCAM, substituted cysteine accessibility method

TM, transmembrane
xii
ABSTRACT

Glycine receptors (GlyRs) and γ-aminobutyric type A receptors (GABA ARs) are
recognized as the primary mediators of neuronal inhibition in the central nervous
system (CNS). There is a large body of evidence that implicates GABA ARs in the
behavioral effects of ethanol and building evidence supports the notion that ethanol
acting on GlyRs causes at least a subset of its behavioral effects. For several
decades, GlyRs and GABA ARs have been studied at the molecular level for targets for
ethanol action. Despite the advances in understanding the effects of ethanol in vivo
and in vitro, the precise molecular sites and mechanisms of action for ethanol in
ligand-gated ion channels (LGICs) in general, and in GlyRs and GABA ARs specifically,
are just now starting to become understood. The present dissertation focuses on
studies we conducted that address this issue using molecular biology, pressure
antagonism, electrophysiology and molecular modeling strategies to probe, identify
and model the initial molecular sites and mechanisms of ethanol action in GlyRs and
GABA ARs. Specifically, this work focuses on the Loop 2 region in the extracellular
domain of GlyRs and GABA ARs and (1) Provides evidence that position 52 in Loop 2
is a target for ethanol action and antagonism in GlyRs; (2) Demonstrates that the
structural bases for the actions of ethanol and pressure on this common target are
different and (3) Provides strong evidence that the structure of Loop 2 in GlyRs,
GABA ARs and possibly across LGICs may be a key factor in controlling the sensitivity
of these receptors to ethanol. Collectively, the studies provide new models and
mechanisms for ethanol action in GlyRs and GABA ARs.
1
CHAPTER 1

INTRODUCTION

A. Background
Alcohol abuse represents a significant problem in our society, affecting about
17.6 million people in the United States alone (Volpicelli, 2001;Grant et al., 2004).
The economic costs of alcohol-related disorders in the United States is estimated to
exceed 185 billion dollars per year (Grant et al., 2004), compared to the 730 million
dollars spent on alcohol-related research worldwide (Rajendram and Preedy, 2005).
Consumer expenditure on alcohol in the United States in 2001 was 128.6 billion
dollars (Foster et al., 2006). The effects of alcohol abuse and dependence results in
significant loss of workplace productivity, increased accidents, increased risk for
hypertension, cardiomyopathy, obesity, and liver disease. This in turn leads to over
100,000 deaths and costs nearly 200 billion dollars per year (Grant et al.,
2004;Harwood, 2000). Despite the wide consumption and the issues associated
with the excessive intake of alcoholic beverages, the mechanisms of ethanol action
that cause and modulate its behavioral effects are still poorly understood.
Historically, alcohols and anesthetics were believed to act by perturbing the
lipid membrane. Over 100 years ago, H.H. Meyer (Meyer, 1899;Meyer, 1901) and
C.E. Overton (Overton, 1901) independently found that the potency of alcohols and
general anesthetics was proportional to their partition coefficient between the
aqueous phase and the oil phase (water and olive oil, respectively) (Roth,
1979;Heimburg and Jackson, 2007). Structural diversity among anesthetic agents
2
lent support to the concept of a nonspecific, lipid target and mechanism of action for
all anesthetics (Trudell et al., 1973b;Trudell, 1977). Meyer refined the Meyer-
Overton rule (Meyer, 1937) by proposing that anesthesia occurs when any
chemically indifferent substance attains a certain concentration within the lipid
bilayer of the cell (Roth, 1979). L.J. Mullins supported the notion that anesthetic
potency is related to the concentration in the membrane, but suggested that the
volume occupied by the anesthetic is also important for anesthesia (Mullins and
Gaffey, 1954;Roth, 1979). He predicted that anesthesia occurs when a critical
volume fraction of anesthetic exists within the membrane phase. Mullins suggested
that the permeability of ions would be depressed once a critical volume of
anesthetic within the membrane was reached, thus resulting in a loss of excitability.
Later work extended Mullins’ theory to suggest that adsorption of an anesthetic
would expand the membrane, thereby providing a basis for the mechanism of
anesthetic action (Lever et al., 1971;Miller et al., 1973;Halsey, 1982).
The critical volume hypothesis states that "anesthesia occurs when the
volume of a hydrophobic region is caused to expand beyond a certain critical
amount by the adsorption of molecules of an (inert) substance. If the volume of this
hydrophobic region can be restored by changes of temperature or pressure, then
the anesthesia will be removed” (Mullins and Gaffey, 1954). This notion was
supported by studies showing that exposure to high pressures (>100 ATA) could
reverse anesthetic effects of ethanol and other general anesthetic agents (Johnson et
al., 1942;Johnson and Flagler, 1950;Lever et al., 1971;Miller and Wilson,
1978;Halsey et al., 1978;Halsey and Wardley-Smith, 1975;Trudell et al., 1973a;Chin
3
et al., 1976;Galla and Trudell, 1980), as well as by more recent studies
demonstrating a relationship between body temperature and sensitivity to ethanol
at behavioral and biochemical levels (Malcolm and Alkana, 1981;Malcolm and
Alkana, 1983;Alkana et al., 1985;Alkana et al., 1988;Finn et al., 1990;Finn et al.,
1991).
Similarly, the observation that alcohols and anesthetics protected
erythrocytes from hemolysis led to the suggestion that this protection was due to an
expansion of the erythrocyte membrane (Seeman and Roth, 1972). These authors
suggested that the membrane was expanded isotropically in three dimensions;
leading to the proposal that the membrane expansion caused by alcohols and
anesthetics was ten-fold the actual volume of those molecules (Seeman, 1972). For
several years, this proposal presented a conundrum for molecular mechanisms of
intoxication. The realization that a membrane does not expand isotropically, but
rather the membrane thins when the surface area expands (Trudell, 1977), resolved
this controversy. The latter result suggested that the membrane volume in the
presence of alcohols or anesthetics would be only slightly greater than the
combined molecular volumes of the ligands plus the original membrane. This
concept was shown experimentally by measuring how pressure could exclude small
spin-labeled molecules (Trudell et al., 1973a). This notion was codified as a “mean
excess volume hypothesis” (Ueda and Mashimo, 1982;Mori et al., 1984). The
important point of the “mean excess volume” hypothesis is that, in order to have a
response reversed by pressure, the sum of the molar volumes of the agent (alcohol
or anesthetic) plus the target (membrane or protein) must be less than the total
4
volume of the new mixed system. This “excess volume” would come about by
creating disorder in the system; for example, poorer packing of water molecules in
protein cavities or creation of small cavities at the protein-lipid interfaces. Then
pressure would act to restore the system to a more ordered lower-volume state.
However, the properties of bulk phospholipid membranes were only slightly
modified at the pressures that reversed anesthesia (approximately 100 ATA)
(Mastrangelo et al., 1978;Mastrangelo et al., 1979;Galla and Trudell, 1980;Galla and
Trudell, 1981). As a result, many studies investigated the much more sensitive
lateral phase separations in membranes (Trudell, 1977;Galla and Trudell,
1980;Galla and Trudell, 1981).
Convincing evidence indicates that alcohols and anesthetics act on proteins
(either within or independent of the membrane) and that membrane perturbation
alone is not sufficient to cause anesthesia (Hunt, 1985;Deitrich et al., 1989). The
effects of alcohols on membrane disorder are generally measurable only at
concentrations well above the pharmacological range (Goldstein, 1984). For
example, at concentrations associated with anesthesia, there would be only 1
ethanol molecule per approximately 200 lipid molecules. Furthermore, the effects
of intoxicating concentrations of alcohols on membrane order can be mimicked by
an increase in temperature of just a few tenths of a degree Celsius (Pang et al.,
1980;Franks and Lieb, 1982), which clearly does not produce behavioral signs of
alcohol intoxication.
In now classic experiments, Franks and Lieb (Franks and Lieb, 1984) found
that general anesthetics inhibit the light-emitting firefly luciferase reaction (a lipid-
5
free protein preparation) and suggested that anesthetics “act by competing with
endogenous ligands for binding to specific receptors.” Subsequent work found that
highly purified optical isomers of the inhalational general anesthetic isoflurane,
which are equally effective at disrupting lipid bilayers, exhibited clear
stereoselectivity in their effects on particularly sensitive ion channels (Franks and
Lieb, 1991;Jones and Harrison, 1993). Moreover, there was a strong correlation
between the stereoselective effects of isoflurane on these ion channels and the
potency of the anesthetic isomers in vivo (Harris et al., 1992;Lysko et al., 1994).
Collectively, these findings demonstrate that the lipid bilayer cannot account
for all of the alcohol and anesthetic effects in the CNS and that more specific sites of
action (such as membrane proteins) also play an important role. In spite of the
bodies of evidence implicating lipid membranes and proteins, alcohols and
anesthetics could have a multitude of targets, including both head and tail groups of
lipids, membrane proteins, and/or the annular lipids of proteins (Franks and Lieb,
1987a;Franks and Lieb, 1987b). It is unlikely that any one of these targets can
account for all of the alcohol and anesthetic effects in the CNS. More recent research
has increased understanding of the interactions at each of these targets.

B. Glycine and GABA A Receptors—Targets for Ethanol Action
Ligand-gated ion channels (LGICs) have received considerable attention as
putative sites of ethanol action that cause its behavioral effects (Deitrich et al.,
1989;Harris, 1999;Mihic et al., 1997;Ye et al., 1998;Zhou and Lovinger,
6
1996;Cardoso et al., 1999;Davies and Alkana, 2001a;Molander and Söderpalm,
2005;Molander et al., 2007;Rewal et al., 2009). Research in this area has focused on
investigating ethanol’s effects on two large superfamilies of LGICs: 1) The cys-loop
superfamily of LGICs (Ortells and Lunt, 1995;Karlin, 2002) whose members include
nicotinic acetylcholine (nACh), 5-hydroxytryptamine 3 (5HT 3), γ-aminobutyric acid
type-A (GABA A) or type-C (GABA C), and glycine receptors (GlyRs) (Mihic and Harris,
1996;Zhou and Lovinger, 1996;Grant, 1995;Cardoso et al., 1999;Davies et al.,
2002;Davies et al., 2004;Crawford et al., 2007;Perkins et al., 2008) and 2) The
glutamate superfamily of LGICs including N-methyl D-aspartate (NMDA), α -amino-
3-hydroxyisoxazolepropionic acid (AMPA) and kainate receptors (Monaghan et al.,
1989;Sommer and Seeburg, 1992). These studies found that pharmacologically
relevant concentrations of ethanol potentiate (i.e.; allosterically increase or
positively modulate) the action of GABA and glycine on GABA ARs and GlyRs,
respectively. On the other hand, ethanol generally inhibits (i.e., allosterically
decrease; negatively modulate) the actions of glutamate on its receptors (Criswell et
al., 1993;Deitrich et al., 1989;Lin et al., 1993;Franks and Lieb, 1994;Weight et al.,
1992;Mihic et al., 1997;Ye et al., 1998). Other cys-loop receptors such as GABA C,
nACh, and 5-HT3Rs (Mihic and Harris, 1996;Zhou and Lovinger, 1996;Grant,
1995;Cardoso et al., 1999;Davies et al., 2006) as well as the ATP-gated purinergic
(P2X) superfamily (Weight et al., 1999;Xiong et al., 1999;Davies et al., 2002;Davies
et al., 2005;Asatryan et al., 2008;Popova et al., 2010) have also been shown to be
sensitive to the effects of ethanol.
7
(A) GlyRs: GlyRs are recognized as the primary mediators of neuronal inhibition in
the spinal cord. In addition, they mediate inhibition in the brain stem and higher
brain regions known to be sensitive to ethanol (Lynch, 2004;Molander and
Söderpalm, 2005;Molander et al., 2007). In addition to alcohol, GlyRs are modulated
by a variety of other agents including zinc, picrotoxin, strychnine and ivermectin
(Bloomenthal et al., 1994;Laube et al., 1995;Shan et al., 2001;Webb and Lynch,
2007;Yang et al., 2007;McCracken et al., 2010). Functional GlyRs consist of five
subunits which come together to form a single chloride ion channel. GlyR subunits
cloned to date include four α subunits (1 to 4) and one β subunit, which provide for
significant diversity (Lynch, 2004). These receptors undergo a developmental
switch from α2 to α1β by around postnatal day 20 in rat (Watanabe and Akagi,
1995). Adult GlyRs are found in a 2:3 αβ stoichiometry (Webb and Lynch, 2007)
however, most of the information obtained

regarding the molecular structure and
function

of GlyRs, including ethanol studies, have used homomeric α1 GlyRs.
The significance of glycinergic neurons in defined neuronal circuits in the
brain has not been sufficiently investigated. This is a matter of relevance with
regards to functional interpretation of the roles of GlyRs in vivo because the
distribution of GlyR subunits extends to areas in addition to glycinergic axon
terminals (Araki et al., 1988;Malosio et al., 1991). To address this paucity of
information regarding the precise innervation of GlyRs in neurons, a recent study by
Zeilhofer and colleagues (Zeilhofer et al., 2005) generated bacterial artificial
chromosome (BAC) transgenic mice which expressed enhanced green fluorescent
8
protein (EGFP). The EGFP in these mice was conditionally activated under the
control of the neuronal glycine transporter 2 isoform (GlyT2) gene (Liu et al., 1993),
a reliable marker for glycinergic neurons in the CNS (Poyatos et al., 1997;Ponce et
al., 1998). Using these transgenic animals, the authors were able to visualize the
intensely fluorescent neurons expressing GlyT2-EGFP in great detail. This approach
revealed an abundance of neurons exhibiting glycinergic signals (indicated by
fluorescent innervation) in the hypothalamus, intralaminar nuclei of the thalamus
and basal forebrain. In contrast, there was less abundance of positive fibers in the
olfactory bulb, striatum, neocortex, hippocampus and amygdyla. The authors
reported a lack of GlyT2-EGFP-positive cell bodies in the forebrain. The authors also
carried out double immunofluorescence staining between EGFP and GlyT1, the
glycine transporter specific for glia, and reported that there was distinct separation
between the two markers at almost all levels of the neuraxis (Zeilhofer et al., 2005).
Overall, these findings from Zeilhofer and colleagues (Zeilhofer et al., 2005), point
out that the distribution of glycinergic axon terminals is less pervasive than glycine
receptors. This finding has large implications for glycinergic signaling in the CNS,
independent of the traditional, activity-dependent, synaptic release of glycine,
especially when considering the actions of modulators such as alcohol and their
behavioral effects mediated via GlyRs.
Building evidence consistently supports the notion that ethanol acting on
GlyRs causes at least a subset of its behavioral effects and may be involved in
modulating ethanol intake. GlyRs have been identified in key alcohol sensitive brain
regions and play a critical role in modulating the excitability of neurons associated
9
with sensory information and motor control of respiration (Rajendra et al.,
1997;Betz, 1991;Lynch, 2004;Webb and Lynch, 2007). These functions are
significantly altered during ethanol intoxication. In addition, glycine and D-serine (a
glycine pre-cursor) were shown to enhance ethanol-induced loss of righting reflex
in mice (Williams et al., 1995). The effect of glycine on the loss of righting reflex was
blocked by strychnine, suggesting that glycine enhances the action of ethanol by
acting on strychnine-sensitive GlyRs. This notion is consistent with other work
showing that GlyRs mediate part of the immobility produced by anesthetics
(Quinlan et al., 2002;Zhang et al., 2001;Zhang et al., 2003). This conclusion is
further supported by studies in which transgenic expression of S276Q mutant
α1GlyR subunits decreased sensitivity to ethanol-induced loss of righting reflex,
motor incoordination (rotorod) and inhibition of strychnine-induced seizures
(Findlay et al., 2002). Moreover, recent studies using microdialysis infusions of
glycine or strychnine into the nucleus accumbens suggest that GlyRs are important
for regulating voluntary ethanol intake and may act as an entrance point into the
brain reward system (Molander and Söderpalm, 2005;Molander et al., 2007;Ericson
et al., 2009). In addition, studies suggest that Alko Alcohol/Non-Alcohol rats are
differently disposed to ethanol consumption due to the arrangement or placement
and/or compositions of their GlyRs (Jonsson et al., 2009). This work found a strong
positive correlation between α1 subunit expression in the nucleus accumbens and
increased ethanol intake Alko Alcohol rats. Along the same lines, recent studies
using α1 glycine null mutant mice suggests that the α1 subunit may be involved in
10
ethanol consumption (Blednov and Harris, personal communication).
Electrophysiological studies of GlyRs further support a role for GlyRs in
mediating the effects of ethanol on the brain. Behaviorally relevant concentrations
of ethanol positively modulate GlyR function measured in synaptoneurosomes of
whole-rat brain (Engblom and Åkerman, 1991), embryonic spinal neurons of mouse
and chick (Celentano et al., 1988;Aguayo and Pancetti, 1994;Tapia et al.,
1998;Ziskind-Conhaim et al., 2003), freshly dissociated rat neurons (Ye et al.,
2001a;Ye et al., 2001b;Ye et al., 2002;Tao and Ye, 2002;Jiang and Ye, 2003;McCool et
al., 2003) and brain slice preparations (Eggers et al., 2000;Eggers and Berger,
2004;Sebe et al., 2003). In addition, ethanol reliably and robustly potentiates
human recombinant α1 and α2 GlyRs measured electrophysiologically (Mascia et
al., 1996a;Mascia et al., 1996b;Mihic et al., 1997;Valenzuela et al., 1998;Yamakura
and Harris, 2000;Davies et al., 2003;Davies et al., 2004;Crawford et al., 2007;Perkins
et al., 2008;Perkins et al., 2009). Recent work by Mihic and colleagues examined the
effects of ethanol on outside-out patches pulled from Xenopus laevis oocytes
expressing α1 GlyRs (Welsh et al., 2009). The authors reported that ethanol
potentiates GlyR function by increasing burst durations and increasing the number
of channel openings per burst. They reported minimal effects of alcohol on open
and closed dwell times and likelihood. Similarly, the percentage of open time within
bursts was not affected. Their kinetic modeling analyses suggest that ethanol
increases burst durations by decreasing the rate of glycine unbinding (Welsh et al.,
2009).
11
(B) GABA ARs : Gamma (γ)-aminobutyric acid is the major inhibitory
neurotransmitter in the CNS that binds to and activates the Gamma (γ)-
aminobutyric acid type A (GABA A) receptor. Although a variety of subunits have
been cloned (α1–6, β1–3, γ1–3, δ, ε, θ) , GABA ARs in the mammalian CNS form a
functional pentamer that may be homo- or heteromeric with the predominant
arrangement being two α, two β, and one γ or δ subunit (Baur et al., 2006).
Considerable evidence links GABA ARs to both the acute and chronic
behavioral effects of ethanol, including motor incoordination, amnesia,
anticonvulsant and anxiolytic activity, tolerance and dependence. This topic has
been the subject of many excellent reviews (Follesa et al., 2006;Mody et al.,
2007;Olsen et al., 2007). Briefly, behavioral (Liljequist and Engel, 1982;Martz et al.,
1983;Liljequist and Engel, 1984;Nutt and Lister, 1988;Harris, 1990;Chandra et al.,
2008), biochemical (Allan and Harris, 1986;Suzdak et al., 1986;Allan and Harris,
1987;Davies and Alkana, 1998) and electrophyisiological (Sigel and Buhr,
1997;Mihic et al., 1997;Wallner et al., 2003;Wallner et al., 2006;Hanchar et al.,
2006;Santhakumar et al., 2007;Perkins et al., 2009) evidence implicates GABA ARs as
targets for ethanol action. Recent findings, which formed the bases of studies in
Chapter 4, have shown that δ-containing extrasynaptic GABA ARs, also dubbed the
“one glass of wine receptors” (Olsen et al., 2007) are sensitive to low millimolar
concentrations of ethanol in a variety of preparations, which are relevant for
behavioral effects (Wallner et al., 2003;Wei et al., 2004;Hanchar et al., 2005;Liang et
al., 2006;Hanchar et al., 2006;Wallner et al., 2006;Fleming et al., 2007;Glykys et al.,
12
2007;Mody et al., 2007;Santhakumar et al., 2007).
Therefore, in vitro, pharmacological, molecular, electrophysiological and
behavioral evidence indicates that ethanol-induced modulation of GlyRs and
GABA ARs plays a key role in causing behavioral effects of ethanol and may influence
ethanol intake through brain reward pathways.
C. Strategies for Identifying Sites and Mechanisms of Ethanol Action
Despite the advances in understanding the effects of ethanol in vivo and in
vitro described above, the precise molecular sites and mechanisms of action for
ethanol in ligand-gated ion channels in general, and in GlyRs and GABA ARs
specifically, are just now starting to become understood. Part of the difficulty in
identifying the sites of ethanol action, and in determining their roles in causing the
effects of ethanol, reflects the physical-chemical nature of ethanol’s mechanism of
action. This physical-chemical, non-structure based, low affinity mechanism limits
the ability to use standard pharmacological approaches to answer these questions.
Findings over the last fifteen years suggesting that ethanol acts by “binding” to
pockets (Franks and Lieb, 1994;Mihic et al., 1997;Franks and Lieb, 1997;Ye et al.,
1998;Wick et al., 1998;Mascia et al., 2000;Crawford et al., 2007) seem to have
blurred the mechanistic distinction between intoxicant-anesthetics, such as ethanol,
and other psychoactive drugs.
However, the primary determinant of intoxicant-anesthetic potency remains
hydrophobicity, not molecular structure. Furthermore, the millimolar ethanol
concentrations required for its biological actions are inconsistent with high affinity
13
sites of action and suggest that ethanol acts simultaneously by the same mechanism
on different types of initial sites (Deitrich et al., 1989;Davies et al., 2004). Hence,
ethanol’s physical-chemical mechanism of action is fundamentally different from the
selective, high affinity binding mechanism that is known to initiate the behavioral
effects of most psychoactive drugs (Dunn et al., 1999). Therefore, we refer to the
sites of ethanol action as “action sites” and “action pockets” to distinguish them
from classical binding sites and to incorporate findings suggesting that there likely
are multiple ethanol targets within one action pocket.
This atypical mechanism, and resultant lack of high affinity and
pharmacological specificity, precludes the classical approach of using ethanol
receptor antagonists to identify the sites and mechanisms of ethanol action and to
establish cause-effect relationships (Lister and Nutt, 1987;Deitrich et al., 1989;Little,
1991;Davies and Alkana, 2001a). Several strategies have been used to fill this void.
These are briefly described below.
1) Molecular Biology
Techniques involving molecular manipulation, such as mutagenesis and
chimeric strategies, have become a classical approach to study the effect of protein
structure on function and response to drugs. In GlyRs and GABA ARs, this strategy
has been used with numerous assays, such as electrophysiology and biochemistry,
to investigate the role that particular amino acid residues play in the effects of
ethanol. Such molecular manipulations of receptor structure can be used alone or in
combination with reagents that covalently bind to cysteine substituted residues and
14
mimic the effect of “binding” small alcohol molecules. This technique is based on the
premise that these covalently bound alcohol-like anesthetics [e.g.; propanethiol or
propyl methanethiosulfonate (PMTS)] will change the reversible effect of the agent
to an irreversible effect only if the actions of the anesthetic result from acting at this
site (Mascia et al., 2000;Crawford et al., 2007).
2) Pressure Antagonism of Ethanol
A second approach uses increased atmospheric pressure (pressure,
hyperbaric exposure), in lieu of a traditional pharmacological antagonist to help
identify the sites and mechanisms of ethanol action. Our laboratory has shown that
exposure to 4-12 times normal atmospheric pressure (ATA) is a direct ethanol
antagonist that blocks and reverses a broad spectrum of ethanol’s acute and chronic
behavioral effects (Alkana and Malcolm, 1981;Alkana and Malcolm, 1982a;Malcolm
and Alkana, 1982;Nielsen et al., 1987;Alkana et al., 1992a;Bejanian et al.,
1993;Davies et al., 1994;Davies et al., 1999;Davies and Alkana, 2001a), as well as its
effects at the biochemical (Davies and Alkana, 1998;Davies et al., 1999;Davies and
Alkana, 2001a) and molecular (Davies et al., 2003;Davies et al., 2004;Perkins et al.,
2008) levels.
Pressure at this low level (e.g. 4-12 ATA) antagonizes ethanol without
causing changes in behavior or baseline receptor function that called into question
the specificity and utility of the higher pressures (>100 ATA) needed for pressure
reversal of anesthesia (Halsey et al., 1970;Hunter and Bennett, 1974;Brauer et al.,
1979;Miller, 1977;Wann and MacDonald, 1988). These studies at 12 ATA and lower
15
demonstrate that pressure antagonism meets the key criteria, direct mechanism
(Malcolm and Alkana, 1982;Alkana and Malcolm, 1982b;Alkana and Malcolm,
1982a;Syapin et al., 1988;Bejanian et al., 1993;Davies et al., 1994;Syapin et al.,
1996;Davies et al., 1999;Davies and Alkana, 2001a;Davies et al., 2003) and
selectivity (Alkana et al., 1995;Davies et al., 1996;Davies and Alkana, 1998;Davies et
al., 1999;Davies et al., 2001;Davies et al., 2003), necessary for it to be used in a
manner analogous to a traditional pharmacological antagonist to help identify initial
molecular sites of ethanol action and to test cause-effect relationships (Davies and
Alkana, 2001a).
From this perspective, the sites of pressure antagonism are the same as the
sites of ethanol action. Hence, mutation of a site that alters the sensitivity of a
receptor to ethanol should also alter its sensitivity to pressure antagonism, if the
site is an initial site of ethanol action. Therefore, knowledge regarding the sites and
mechanism(s) of pressure antagonism of ethanol in LGICs can identify new sites and
mechanisms of ethanol action.
3) Molecular Modeling
The lack of a crystal structure greatly complicates traditional structure-
function and or docking analyses of agonist and ethanol action in GlyRs and
GABA ARs. As a result, molecular modeling that incorporates evidence generated
from strategies outlined above is used to help define the sites of ethanol action in
these receptors, to suggest structure-function relationships and to identify possible
sites of molecular interaction that mediate ethanol actions. Molecular models of
16
GlyR and GABA AR are typically built by combining multiple X-ray structures from
unrelated organisms to create a suitable template for homology modeling (Trudell
and Bertaccini, 2004). These models have been validated by intermediate
resolution cryo-electron microscopy structures of torpedo nAChR (PDB ID 2BG9)
(Unwin, 2005). This approach has already led to important advances (Yamakura et
al., 2001;Jenkins et al., 2001;Kash et al., 2003;Kash et al., 2004a;Trudell and
Bertaccini, 2004;Kash et al., 2004b;Crawford et al., 2007;Crawford et al.,
2008;Perkins et al., 2009).
Developing models that define the physical-chemical properties of the sites
and mechanisms by which ethanol acts, that determine the properties that
constitute its activation pockets, and that control ethanol sensitivity are key steps
for developing agents to block, modulate and/or mimic the actions of ethanol at
these sites.
Together, molecular, hyperbaric and modeling strategies provide
complementary approaches for identifying, testing and depicting possible sites and
mechanism(s) of ethanol action and antagonism, as well as sites that control ethanol
sensitivity in a variety of receptors. The present dissertation tests the overarching
hypothesis that the extracellular domain of GlyRs and GABA ARs is a target for
ethanol action, antagonism and modulation. In support of the findings hypothesis,
the findings identify possible targets for ethanol action, antagonism and modulation
in these receptors and set the stage for the development of new therapeutic agents
to help prevent or treat alcohol-related problems.
17
CHAPTER 2
TARGETS FOR ETHANOL ACTION AND ANTAGONISM IN LOOP 2 OF THE
EXTRACELLULAR DOMAIN OF GLYCINE RECEPTORS

CHAPTER 2 ABSTRACT
The present studies used increased atmospheric pressure in place of a
traditional pharmacological antagonist to probe the molecular sites and
mechanisms of ethanol action in GlyRs. Based on previous studies, we tested the
hypothesis that physical-chemical properties at position 52 in extracellular domain
Loop 2 of α1GlyRs, or the homologous α2GlyR position 59, determine sensitivity to
ethanol and pressure antagonism of ethanol. Pressure antagonized ethanol in
α1GlyRs that contain a non-polar residue at position 52, but did not antagonize
ethanol in receptors with a polar residue at this position. Ethanol sensitivity in
receptors with polar substitutions at position 52 was significantly lower than GlyRs
with non-polar residues at this position. The α2T59A mutation switched sensitivity
to ethanol and pressure antagonism in the WTα2GlyR, thereby making it α1-like.
Collectively, these findings indicate that: 1) polarity at position 52 plays a key role in
determining sensitivity to ethanol and pressure antagonism of ethanol; 2) the
extracellular domain in α1- and α2GlyRs is a target for ethanol action and
antagonism and 3) there is structural-functional homology across subunits in Loop
2 of GlyRs with respect to their roles in determining sensitivity to ethanol and
pressure antagonism of ethanol. These findings should help in the development of
pharmacological agents that antagonize ethanol.
18
INTRODUCTION
Alcohol (ethanol) abuse represents a major problem in the United States with
an estimated 14 million people being affected (Grant et al., 2004). To address this
issue, considerable attention has begun to focus on the development of medications
to prevent and treat alcoholism (Heilig and Egli, 2006;Steensland et al.,
2007;Johnson et al., 2007). The development of such medications would be aided by
a clear understanding of the sites and mechanisms of ethanol action.
Traditionally, the mechanisms and sites of drug action are studied using the
appropriate receptor agonists and antagonists. To be used in this way, the mechanism
of the antagonism must be direct (mechanistic not physiological) and selective. When
these criteria are met, the site of antagonism is synonymous with and defines the site
causing drug action. However, the physical-chemical mechanism of action as well as
the low affinities of ethanol for its targets limit the utility of traditional
pharmacological receptor agonist and antagonist ligands as tools for investigating
ethanol's sites of action (Eckenhoff and Johansson, 1997;Davies et al., 2003).
Prior studies indicate that increased atmospheric pressure (pressure) is an ethanol
antagonist that can help fill this gap. This work found that low level hyperbaric
exposure (pressure up to twelve times normal atmospheric pressure—12 ATA)
directly antagonizes the behavioral and biochemical actions of ethanol (Alkana and
Malcolm, 1981;Alkana et al., 1992b;Bejanian et al., 1993;Davies and Alkana,
1998;Davies and Alkana, 2001b). The antagonism occurred without causing changes
in baseline behavior or central nervous system excitation (Syapin et al., 1988;Davies
19
et al., 1994;Davies et al., 1999) that called into question the direct mechanism of
earlier studies investigating high pressure reversal of anesthesia (Kendig,
1984;Bowser-Riley et al., 1988;Wann and MacDonald, 1988;Franks and Lieb,
1994;Little, 1996). The low level hyperbaric studies also demonstrated that pressure
was selective for allosteric modulators (Alkana et al., 1995;Davies et al., 1996;Davies et
al., 2003). More recent hyperbaric two-electrode voltage clamp studies demonstrated
that pressure antagonized ethanol potentiation of α1 Glycine receptor (GlyR) function
in a direct, reversible, concentration and pressure dependent manner that was
selective for allosteric modulation by alcohols (Davies et al., 2003;Davies et al., 2004).
Taken together, these findings indicate that pressure is a direct, selective ethanol
antagonist that can be used, in place of a traditional pharmacological antagonist, as a
tool to help identify the sites of ethanol action.
This notion is supported by recent studies using pressure to identify novel
targets for ethanol in GlyRs. Glycine is a major inhibitory neurotransmitter in the
mammalian central nervous system. GlyRs are a member of the superfamily of ligand-
gated ion channels (LGICs), known as Cys-loop receptors (Ortells and Lunt,
1995;Karlin, 2002). Other members of this receptor family include γ-aminobutyric
acid type-A receptor (GABA AR), nicotinic acetylcholine receptor (nAChR) and 5-
hydroxytryptamine 3 receptor (5HT 3R), all of which assemble to form ion channels with
a pentameric structure (Schofield et al., 1987). Glycine causes inhibition in the adult
central nervous system by activating the strychnine-sensitive GlyR. Five GlyR subunits
have been cloned (α1 - α4 and β). The pentamer formed can be homo- or heteromeric
20
(Betz, 1991;Rajendra et al., 1997). Native adult GlyRs contain both α1 and β subunits,

while native neonatal GlyRs contain

both α2 and β subunits (Malosio et al.,
1991;Mascia et al., 1996a;Rajendra et al., 1997;Eggers et al., 2000)
Studies over the last decade have pointed to a role for GlyRs in mediating the
effects of ethanol. This work includes studies that have shown that behaviorally
relevant concentrations of ethanol positively modulate GlyR function measured in a
variety of brain and spinal cord preparations (Engblom and Åkerman, 1991;Aguayo
and Pancetti, 1994;Tapia et al., 1998;Eggers et al., 2000;Ye et al., 2002;Tao and Ye,
2002;McCool et al., 2003;Ziskind-Conhaim et al., 2003). More recent studies also
suggest that GlyRs in the nucleus accumbens are targets for ethanol that are involved
in ethanol-induced mesolimbic dopamine release (Molander and Söderpalm,
2005;Molander et al., 2007), thus linking GlyRs to the rewarding effects of ethanol.
The molecular targets and mechanisms that initiate ethanol action in GlyRs
represent an active area of investigation (Mascia et al., 1996a;Mihic et al.,
1997;Valenzuela et al., 1998;Ye et al., 2002;Davies et al., 2004;Yevenes et al.,
2006;Crawford et al., 2007;Lobo et al., 2008). Considerable research has focused on
potential targets for ethanol action in the transmembrane (TM) domains of GlyRs.
Several of these studies employed the substituted cysteine accessibility method
(SCAM) (Karlin and Akabas, 1998) in combination with the anesthetic-like propyl
methanethiosulfonate (PMTS) (Mascia et al., 2000). The authors proposed that
PMTS would covalently bind to the substituted cysteine residue and change the
normal effect of PMTS (reversible potentiation) to irreversible potentiation if the
21
actions of PMTS and alcohols result from binding at this site. The results and
subsequent studies fit this prediction and provide solid evidence that position 267
and, possibly other sites in the TM domain of GlyRs, are sites of ethanol action and
contribute to an ethanol “binding/action” pocket(Mihic et al., 1997;Ye et al., 1998;Ye
et al., 2002;Lobo et al., 2008).
Studies using pressure indicate that the extracellular domain also contains
important targets for ethanol. These studies found that a naturally occurring
mutation in Loop 2 of the extracellular domain of α1GlyRs (A52S) (Saul et al.,
1994;Ryan et al., 1994) rendered α1GlyRs insensitive to pressure antagonism of
100mM ethanol (Davies et al., 2004). Prior work has also shown that A52S mutant
α1GlyRs are less sensitive to ethanol than WT GlyRs (Mascia et al., 1996b;Davies et
al., 2004;Lobo et al., 2008).
Follow-up studies at normal atmospheric pressure, which utilized the SCAM
technique in combination with PMTS, added two key elements to the evidence
supporting the extracellular domain as an ethanol target (Crawford et al., 2007).
This work found that PMTS exposure caused irreversible alcohol-like potentiation in
α1A52C GlyRs and, thus, suggested a cause-effect relationship between ethanol
acting on this site in the extracellular domain and alcohol-like GlyR modulation
(Crawford et al., 2007). Further studies found that PMTS binding to cysteines in
A52C and S267C α1GlyRs decreased the alcohol cutoff in a manner consistent with
the notion that position 52 in the extracellular domain and position 267 in the TM
domain form part of the same alcohol-action pocket (Crawford et al., 2007). These
22
findings with position 52 of the α1GlyR parallel earlier findings that established the
TM domain as a target for ethanol action. Collectively, these findings indicate that
ethanol acts on targets in both the TM and extracellular domains, and that positions
52 and 267 are part of the same alcohol pocket (Crawford et al., 2007).
Interestingly, hyperbaric and other findings in WT and mutant α1GlyRs suggest
that there may be a relationship between the physical chemical characteristics of the
amino acid at position 52 and sensitivity to ethanol and to pressure antagonism of
ethanol. As discussed above, substituting a polar serine for the non-polar alanine in
WT α1GlyRs reduced ethanol sensitivity and eliminated sensitivity to pressure
antagonism of ethanol (Davies et al., 2004). Moreover, sequence analysis of α1GlyRs
and α2GlyRs indicates that α2GlyRs have a polar threonine at position 59, which is
homologous to position 52 in WT α1GlyRs. Like A52S α1GlyRs, α2GlyRs have reduced
ethanol sensitivity and are insensitive to pressure antagonism of ethanol compared to
α1GlyRs (Davies et al., 2004). Taken together, these findings suggest that the polarity
of the amino acid at position 52 in α1GlyRs, and the homologous position in α2GlyRs,
plays a key role in determining the sensitivity of the receptor to ethanol and pressure
antagonism of ethanol. Prior studies found a significant correlation between the
molecular volume of the amino acid at TM position 267 and ethanol sensitivity (Ye et
al., 1998), which suggests that other physical-chemical parameters at position 52
might also influence sensitivity of the receptor to ethanol and pressure antagonism of
ethanol.
23
The present studies test the hypothesis that the physical-chemical properties
of the specific residue at position 52 in WT α 1GlyRs (A52) or its homologous
position in WT α 2GlyRs (T59), are determinants of the receptor’s sensitivity to
ethanol and pressure antagonism of ethanol. The findings support this hypothesis,
increase our understanding of the molecular targets for ethanol action and
antagonism, and should help in the development of novel prevention and treatment
strategies for alcohol-related problems.

MATERIALS AND METHODS
Materials - Adult female Xenopus laevis frogs were purchased from Nasco
(Fort Atkinson, WI). Penicillin, streptomycin, gentamicin, 3-aminobenzoic acid ethyl
ester, glycine, ethanol, and collagenase were purchased from Sigma (St. Louis, MO).
All other chemicals used were of reagent grade. Certified premixed gases were
supplied by Specialty Air Technologies (Long Beach, CA).
Expression in Oocytes- Xenopus oocytes were isolated and injected with
either human α1, α2 or mutant α1A52C, α1A52F, α1A52I, α1A52S, α1A52T,
α1A52V, α1A52W, α1A52Y, or α2T59A cDNAs (1 ng per 32 nl) cloned into the
mammalian expression vector pCIS2 or pBKCMV as previously described (Davies et
al., 2003) and verified by partial sequencing (DNA Core Facility, University of
Southern California, USA). Mutagenesis of the alanine at position 52 in α1GlyRs or
the threonine at position 59 in α2GlyRs was performed as previously described
(Ryan et al., 1994). After injection, oocytes were stored individually in incubation
24
medium (MBS supplemented with 2mM sodium pyruvate, 0.5mM theophylline,
10,000 U/l penicillin, 10 mg/l streptomycin and 50 mg/l gentamicin) in petri dishes
(VWR, San Dimas, CA). All solutions were sterilized by passage through 0.22 μM
filters. Oocytes, stored at 18°C, usually expressed GlyRs the day after injection.
Oocytes were used in electrophysiological recordings for 3-7 days after cDNA
injection.
Atmospheric conditions - Atmospheric conditions were established as
described previously (Davies et al., 1999;Davies et al., 2003). Briefly, we tested the
1 ATA air condition (control) in a hyperbaric chamber with the lid removed or by
using compressed air with the chamber sealed. Pilot studies determined that there
was no measurable difference between the results obtained by these two methods. To
achieve the 12 ATA heliox condition, the chamber was purged with heliox and then
pressurized to the experimental ATA at the rate of 1 ATA/min using premixed certified
compressed gases. The heliox mixture consisted of 1.7% oxygen and 98.3% helium
resulting in a 0.2 ATA partial pressure for oxygen at 12 ATA; this mixture provides
normal oxygenation. We found previously that this mixture avoids complications
from higher oxygen partial pressures (Alkana and Malcolm, 1981). We replaced the
nitrogen in our gas mixture with helium to avoid the depressant effect of nitrogen at
increased atmospheric pressure (Alkana and Malcolm, 1982a).
Hyperbaric Two-Electrode Whole Cell Voltage Clamp Recording – Two-
electrode voltage clamp recording was performed using techniques similar to those
previously reported (Davies et al., 2003). Briefly, electrodes pulled (P-30, Sutter
25
Instruments, Novato, CA) from borosilicate glass [1.2mm thick-walled filamented
glass capillaries (WPI, Sarasota, FL)] were back-filled with 3M KCl to yield
resistances of 0.5 -3 MΩ. All electrophysiological recordings were conducted within
a specially designed hyperbaric chamber that contains a vibration resistant platform
that supports an oocyte bath, two micro positioners (WPI, Sarasota, FL or Narishige
International USA, Inc East Meadow, NY) and bath clamp (Davies et al., 2003).
Oocytes were perfused in a 100 μl oocyte bath with MBS ± drugs via a custom high
pressure drug delivery system (Alcott Chromatography, Norcross, GA) at 2 ml/min
using 1/16 OD high pressure PEEK tubing (Upchurch Scientific, Oak Harbor, WA).
Oocytes were voltage clamped at a membrane potential of -70 mV using a Warner
Instruments Model OC-725C (Hamden, CT) oocyte clamp. Individual oocytes were
tested at both control and experimental atmospheric conditions and checked for
normal function during pressurization and depressurization. The order of testing
control and atmospheric conditions was counterbalanced to minimize the effects of
testing order and to determine if pressure effects were reversible.
Hyperbaric ethanol experiments – Previous work found that ethanol
potentiation of GlyR function is more robust and reliable when tested in the
presence of low concentrations of glycine (typically EC 2-10) (Davies et al., 2003).
Based on these studies, we used a concentration of glycine producing 2 ± 0.3% of
the maximal effect (EC2). Pilot experiments found that WT and mutant GlyR
responses using a 1 min glycine application reached maximal response, which did
not differ appreciably from results using 30s applications. Therefore, we used the
26
shorter application time to increase efficiency and to minimize desensitization at
the higher glycine concentrations. When testing ethanol potentiation, the oocytes
were preincubated with ethanol for 60 sec prior to co-application of ethanol and
glycine (Davies et al., 2004). Washout periods (5-15 min) were allowed between
drug applications to ensure complete resensitization of receptors. The hyperbaric
experiments for WT α1, α1A52S, and α2T59A were measured across a full ethanol
concentration range (25-200mM). For the α1A52C, α1A52F, α1A52I, α1A52T,
α1A52V, α1A52W and α1A52Y mutants, we tested 100mM ethanol because this
concentration produced a degree of potentiation that was functionally equivalent to
the potentiation produced by ethanol in WT α1GlyRs that were antagonized by
pressure (Davies et al., 2003;Davies et al., 2004). All experiments testing mutant
GlyRs included WT control receptors expressed in the same batch of oocytes as the
respective mutant GlyRs. A chart recorder (Barnstead/Thermolyne, Dubuque, IA)
continuously plotted the clamped currents. The peak currents were measured and
used in data analysis. All experiments were performed at room temperature (20-
23° C).
Data Analysis - Data for each experiment were obtained from oocytes from
at least two different frogs. The n refers to the number of oocytes tested. Results
are expressed as mean ± SEM. Where no error bars are shown, they are smaller
than the symbols. We used Prism (GraphPAD Software, San Diego, CA) to perform
curve fitting and statistical analyses. Concentration response data were analyzed
using non-linear regression analysis: [I = I max [A]
nH
/ ([A]
nH
+ EC 50
nH
)] where I is the
27
peak current recorded following application of a range of agonist concentrations, [A];
I max is the estimated maximum current; EC 50 is the glycine concentration required for a
half-maximal response and n H is the Hill slope. Data were subjected to t-tests, one- or
two-way Analysis of Variance (ANOVA) with Dunnett’s multiple comparison or
Bonferroni post tests when warranted. For the correlation analyses, the change in
ethanol potentiation upon exposure to 12ATA (ΔP) was determined by subtracting
mean ethanol % potentiation at 12ATA from that observed at 1ATA. Polarity values
were assigned to amino acid residues using the Zimmerman polarity scale
(Zimmerman et al., 1968). Hydrophobicity values were assigned using the Eisenberg
hydrophobicity scale (Eisenberg et al., 1984). Molecular volumes were calculated
with the Spartan Molecular Modeling Program (Wave Function, San Diego, CA).
Statistical significance was defined as p < 0.05.

28
RESULTS

Glycine EC50s in WT and Mutant α α α α1GlyRs:
The effect of point mutations at position 52 on glycine sensitivity of α1GlyRs
is shown in Figure 2.1 Inward chloride currents were evoked in a concentration-
dependent manner by glycine in WT and all mutant GlyRs. We found significant
right shifts in glycine EC50 from WT α1GlyR for the polar α1A52S, α1A52T and
α1A52W GlyRs and significant left shifts for the non-polar α1A52I and α1A52V
GlyRs, but not for other substitutions.
FIGURE 2.1

Figure 2.1. Concentration-response curves for glycine (10-3,000 µM) activated chloride
currents in Xenopus oocytes expressing WT and mutant α α α α1GlyR subunits: Glycine induced
chloride currents were normalized to the maximal current activated by a saturating concentration of
glycine (3 mM) when tested under 1 ATA air conditions. The curves represent non-linear regression
analysis of the glycine concentration responses in the α1 mutant GlyRs compared to WT α1GlyRs.
Details of EC 50, Hill Slope and Maximal current amplitude (I max) are provided in Table 2.1. Glycine
was applied for 30 sec. Washout time was 5-15 min after application of glycine. Each data point
represents the mean ± SEM from 4 different oocytes.

29

EC50 values of WT and mutant α1GlyRs did not correlate significantly with
polarity, hydrophobicity, molecular volume, or weight (Data not shown). No
significant differences were observed between WT and mutant GlyRs in Hill slope
(n H) and/or maximal current amplitude (I max) (Table 2.1).

TABLE 2.1

Receptor
(relative
polarity)
Imax (nA) Hill
Slope
EC50 (μM)

Non-polar
α1A52V 17800±1842 2.2±0.3 31±4
α1A52I 18425±2072 2.5±0.4 34±1
α1 A52F 18625±5525 2.3±0.3 199±62
α1 WT (A52) 19875±2932 2.1±0.3 130±48
α2 T59A 17750±4033 1.6±0.4 123±45
Intermediate α1 A52C 18250±2322 2.4±0.3 148±23

Polar
α2 WT (T59) 20687±7026 2.3±0.3 374±61
α1 A52T 18187±4360 2.9±0.5 410±32
α1 A52S 18375±5572 3.4±0.4 387±10
α1A52Y 16687±2809 2.8±0.9 239±58
α1A52W 16750±2809 1.4±0.1 839±112

Table 2.1. Summary of non-linear regression analysis results for glycine concentration
responses and differences in ethanol sensitivity WT and mutant α α α α1 and α α α α2 GlyRs shown in
terms of increasing polarity of residue at position 52 or 59 : Glycine EC50, Hill Slope (n H) and
maximal current amplitude (I max) are presented as mean ± SEM from 4 different oocytes (as shown in
Figure 1). Statistical significance from WT α1GlyRs was assessed using one-way ANOVA with
Dunnett’s post test. GlyRs containing polar substitutions at position 52 were significantly right
shifted from α1WT and not significantly different than WT α2 GlyRs in terms of EC50 with the
exception of A52W. No significant differences were observed from WT α1GlyRs for Hill Slope (n H) or
maximal current amplitude (I max).

Ethanol Sensitivity in WT and Mutant α α α α1GlyRs:
The effect of point mutations at position 52 in α1GlyRs on sensitivity to 100mM
ethanol is shown in Figure 2.2. Ethanol responses for highly polar substitutions at
30
position 52 - α1A52S, α1A52T, α1A52W and α1A52Y were significantly reduced
compared to WT α1GlyRs. Ethanol responses for the intermediate-polar α1A52C
and non-polar α1A52I, α1A52V and α1A52F mutants were not significantly reduced
compared to WT α1GlyRs.
FIGURE 2.2

Figure 2.2. Polarity of the residue at position 52 in α α α α1GlyRs determines sensitivity to ethanol:
Figure shows ethanol % potentiation of glycine induced chloride current at 100mM ethanol. White
bars represent non-polar substitutions at position 52 in α1 GlyRs and grey bars represent polar
substitutions. Ethanol responses for the polar mutants α1A52S, α1A52T, α1A52Y and α1A52W GlyRs
were significantly reduced compared to WT α1GlyRs. There were no significant differences among
the polar mutants with respect to ethanol sensitivity at 100mM. Significance is *p<0.05 vs. WT
α1GlyRs.

There was a significant inverse correlation between polarity and receptor
sensitivity to ethanol (Figure 2.3A). In addition, we found a significant direct
correlation between hydrophobicity of the residue at position 52 and receptor
31
sensitivity to ethanol (Figure 2.3B). The r
2
values from the correlation analyses
indicate that polarity explained approximately 88% of the variability in the
sensitivity of α1GlyRs to ethanol while hydrophobicity accounted for approximately
69% of the variability. In contrast to polarity and hydrophobicity, the molecular
volume and weight of the residues at position 52 did not appear to affect the
sensitivity of α1GlyRs to ethanol (Figure 2.3C-D).
FIGURE 2.3

Figure 2.3. The polarity and hydrophobicity of substitutions at position 52 are significantly
correlated with sensitivity of α α α α1GlyRs to ethanol: The physical-chemical properties of the residues
at position 52 (A) Polarity, (B) Hydrophobicity, (C) Molecular Volume and (D) Molecular Weight
respectively, were correlated against sensitivity to 100mM ethanol.

Pressure Antagonism Sensitivity in WT and Mutant α α α α1GlyRs:
We began testing the hypothesis that the physical-chemical properties at
position 52 in α1GlyRs play a role in determining sensitivity to pressure antagonism of
32
four different concentrations of ethanol by testing A52S GlyRs, in which the non-polar
alanine in WT receptors was replaced by a polar serine. Oocytes expressing α1WT or
A52S GlyRs were voltage-clamped and tested with glycine +/- (25-200mM) ethanol
under both control and pressure conditions. Consistent with previous findings
(Davies et al., 2004), the alanine to serine mutation at position 52 eliminated
sensitivity to pressure antagonism of 100mM ethanol seen in WTα1 GlyRs. This
lack of the antagonist’s effect was evident across a broad range of ethanol
concentrations (Figure 2.4).
FIGURE 2.4

Figure 2.4 (A). Pressure significantly antagonizes ethanol potentiation in α α α α1 GlyRs: The figure
depicts WT α1GlyRs tested at both 1ATA air control (white bars) and 12 ATA heliox (black bars). In
agreement with previous findings, pressure antagonized ethanol potentiation from 50-200mM but
not at 25mM; (B) Pressure Does not Antagonize Ethanol potentiation in mutant α1A52S GlyRs:
The figure depicts results from 25-100 mM ethanol in the mutant (A52S) α1GlyRs form the same
batches of oocytes shown in (A), tested at both 1 ATA air control (white bars) and 12 ATA heliox
(black bars). Data is presented as mean ± SEM of 4-6 oocytes. Data was subjected to two-way
repeated measures ANOVA followed by Bonferroni post-hoc analyses. Statistical significance is *p <
0.05 or ***p<0.001.

We expanded the investigation to test the effects of mutations with different
physical chemical parameters at position 52 on the sensitivity to pressure antagonism
of ethanol in α1GlyRs. Based on the results with ethanol sensitivity (Figures 2.2 and
33
2.3), we focused on polarity and hydrophobicity, but also investigated substitutions
that altered molecular weight and volume. Oocytes expressing the polar α1A52T,

FIGURE 2.5

Figure 2.5. Pressure antagonizes ethanol in α α α α1GlyRs that have a non-polar residue at position
52: The figure depicts mutant α1GlyRs tested at both 1ATA air control (white bars) and 12 ATA
heliox (black bars). Exposure to 12 ATA heliox did not significantly affect ethanol potentiation at
100mM in (A) α1A52C (intermediate, intermediate-polar) (B) α1A52T (intermediate, polar), (C)
α1A52W (bulky, polar) or (D) α1A52Y (bulky, polar) GlyRs. Pressure did significantly antagonize
ethanol potentiation of (E) α1A52F (bulky, non-polar), (F) α1A52I (intermediate, non-polar) and (G)
α1A52V (small, non-polar) GlyRs. Data were analyzed using unpaired t-tests to determine the effect
of atmospheric condition on ethanol potentiation of glycine-activated chloride currents. Statistical
significance is **p<0.01. Data are presented as mean ± SEM of 4-6 oocytes.

α1A52W and α1A52Y GlyRs , the intermediate-polar α1A52C GlyRs and the non-
polar α1A52F, α1A52I and α1A52V GlyRs were voltage-clamped and tested with
glycine +/- (100mM) ethanol under both control and pressure conditions. We found
that exposure to 12 ATA heliox did not significantly affect ethanol potentiation in
34
the polar α1A52C, α1A52T, α1A52W or α1A52Y GlyRs (Figure 2. 5A-D). In contrast,
pressure did significantly antagonize ethanol potentiation of 100mM in the non-
polar α1A52F, α1A52I and α1A52V GlyRs (Figure 2.5 E-G).
Moreover, as with sensitivity to ethanol, there was a significant inverse
correlation between polarity of the residue at position 52 and receptor sensitivity to
pressure antagonism of ethanol (Figure 2.6A) and a significant inverse correlation
between hydrophobicity of the residue at position 52 and sensitivity to pressure
antagonism of ethanol (Figure 2.6B).
FIGURE 2.6

Figure 2.6. The polarity of the residue at position 52 in α α α α1GlyRs determines the receptors
sensitivity to pressure antagonism of ethanol: The physical-chemical properties of the residues at
position 52 (A) Polarity, (B) Hydrophobicity, (C) Molecular Volume and (D) Molecular Weight
respectively, were correlated against change in ethanol potentiation upon exposure to 12ATA (ΔP).

35
The r
2
indicated that polarity explained approximately 84% of the variability in
the sensitivity of α1GlyRs to pressure antagonism of ethanol while hydrophobicity
accounted for approximately 53% of the variability. In contrast to polarity and
hydrophobicity, the molecular volume and weight of the residues at position 52 did
not correlate with sensitivity to ethanol or pressure antagonism of ethanol (Figure
2.6C-D). Collectively, these findings support the hypothesis that the
polarity/hydrophobicity, but not the molecular weight or volume, of the residue at
position 52 in α1GlyRs are key factors in determining the sensitivity of the receptor
to pressure antagonism of ethanol.

Ethanol and Pressure Antagonism Sensitivity in α α α α2 GlyRs:
As described above, α1 and α2GlyRs differ in their sensitivity to ethanol (α1
> α2) and sensitivity to pressure antagonism of ethanol (α1—pressure antagonism
sensitive; α2—pressure antagonism insensitive) (Davies et al., 2004).
TABLE 2.2
Subunit Loop 2 in Extracellular Amino Terminal
Region
EtOH Pressure
* *
α α α α1GlyR 50 S I A E T T M D Y R 60 ++++ Yes
α α α α1A52S 50 S I S E T T M D Y R 60 +++ No
α α α α2GlyR 57 S V T E T T M D Y R 68 +++ No

Table 2.2. Alignment of a portion of the amino terminal regions from human α α α α1GlyR, α α α α1A52S
GlyR and α α α α2GlyR subunit sequences. Asterisks indicate residues that differ between WT α1 and
α2GlyRs. Black boxed in region represents Loop 2. Residues in bold represent position 52 in
α1GlyRs and homologous position 59 in α2GlyR respectively. Relative sensitivity to ethanol
potentiation (EtOH) and whether pressure can antagonize the effects of ethanol (Pressure) are
shown.

36
Sequence alignment between the Loop 2 regions of the receptor subtypes revealed
that the WT α2GlyR has a polar threonine at position 59, the position homologous to
position 52 in α1GlyRs (Table 2.2). Given that substituting the non-polar alanine for
a polar threonine reduces ethanol sensitivity and eliminates sensitivity to pressure
antagonism of ethanol in α1GlyRs (Figures 2.2 and 2.5A), we predicted that mutating
this polar threonine in α2GlyRs to the non-polar alanine would convert the response of
α2GlyRs to ethanol and pressure to be similar to those of α1GlyRs. The α2T59A
mutation yielded functional receptors with glycine concentration responses that were
left shifted compared to WT α2GlyRs and were similar to WT α1GlyRs (Figure 2.7A).
FIGURE 2.7

Figure 2.7(A) Concentration-response curves for glycine (10-3,000 µM) activated Cl- currents
in Xenopus oocytes expressing WT and mutant α α α α2 glycine receptor subunits: Glycine induced
chloride currents were normalized to the maximal current activated by a saturating concentration of
glycine (3mM) when tested under 1 ATA air conditions. Curves represent non-linear regression
analysis of the glycine concentration responses in the α2 WT and mutant GlyRs compared to WT
α1GlyRs. Details of EC 50, Hill Slope and Maximal current amplitude (I max) are provided in Table 1.
Each data point represents the mean ± SEM from 4 different oocytes; (B) Replacing the polar
threonine at position 59 in WT α α α α1GlyRs with the non-polar alanine changes the α α α α2GlyRs to be
α α α α1GlyR-like in response to ethanol and pressure antagonism of ethanol: The figure depicts
mutant α2T59A GlyRs tested at both 1ATA air control (white bars) and 12 ATA heliox (black bars).
As predicted, pressure antagonized ethanol potentiation from 50-200mM but not at 25mM. The
ethanol responses in the mutant were similar to WT α1GlyRs. Data were subjected to two-way
repeated measures analysis of variance (ANOVA) followed by Bonferroni post-hoc analyses.
Statistical significance is *p < 0.05 or ***p<0.001. Data are presented as mean ± SEM of 4-5 oocytes.
37
As predicted, the alanine substitution at position 59 changed WT α2GlyRs from
being insensitive to pressure antagonism of ethanol to being sensitive to the
antagonism (Figure 2.7B). Overall, the findings in α1 and α2GlyRs demonstrate that
switching between non-polar and polar residues at homologous positions 52 and 59
can switch the response of α1GlyRs to ethanol and pressure to be α2-like and vice-
versa.

DISCUSSION

Considerable attention has begun to focus on the development of medications
to prevent or treat alcoholism. This focus is, in part, due to the marked increase in
knowledge regarding the neurochemical targets for ethanol’s effects on brain
function. This includes identification of neurotransmitter systems that appear to be
initial targets for ethanol such as LGICs (e.g., GABA A, glycine, glutamate, 5HT 3) and
other targets that may play a role in mediating physical dependence and craving
(Deitrich et al., 1989;Zhou and Lovinger, 1996;Mihic et al., 1997;Ye et al.,
1998;Harris, 1999;Cardoso et al., 1999;Davies and Alkana, 2001b). However, this
information has not resulted in comparable success in the development of
pharmacological treatments for alcoholism.
Current approved therapeutics for alcoholism focus on deterring drinking by
making alcohol ingestion aversive (e.g., disulfiram) or reducing the craving for
alcohol (e.g., naltrexone and acamprosate) (Heilig and Egli, 2006). However, the
modest success rate of these drugs reflects, at least in part, their proposed
38
mechanisms, which do not focus on blocking the actions of ethanol at initial targets.
Rather, these drugs target neurochemical and neuropeptide systems in the
downstream cascades leading to craving and dependence. Recently, varenicline, an
approved pharmacotherapeutic for smoking cessation, demonstrated significant
reduction in both acute and chronic alcohol consumption in an animal model
(Steensland et al., 2007). Other drugs currently under investigation for alcoholism
include topiramate (Johnson et al., 2007) and rimonabant (Colombo et al., 2007).
But, these drugs also, theoretically, target downstream actions of ethanol.
An alternative approach that we have taken focuses on strategies to develop
agents that are designed to block the initial actions of ethanol at its different
neurotransmitter targets, thus potentially yielding novel prevention and treatment
approaches (Alkana and Malcolm, 1980;Davies and Alkana, 1998). Recent studies
along these lines have investigated the benzodiazepine receptor inverse agonist RO
15-4513 as a novel method of antagonizing ethanol action in GABA ARs (Wallner et
al., 2006).
Presently, we do not know enough about where and how ethanol acts to
develop medications that antagonize ethanol directly. Part of the difficulty lies in
the physical-chemical nature of ethanol’s mechanism of action, which limits the
ability to use standard pharmacological approaches to study ethanol’s actions and
effects, and to identify direct mechanistic ethanol antagonists (Deitrich et al., 1989).
Findings over the last fifteen years suggesting that ethanol acts by “binding” to
“pockets” (Franks and Lieb, 1994;Mihic et al., 1997;Franks and Lieb, 1997;Ye et al.,
1998;Wick et al., 1998;Mascia et al., 2000;Crawford et al., 2007) seem to have
39
blurred the mechanistic distinction between intoxicant-anesthetics, such as ethanol
and other psychoactive drugs. However, the primary determinant of intoxicant-
anesthetic potency remains hydrophobicity, not molecular structure. Furthermore,
the high, millimolar ethanol concentrations required for its biological actions are
inconsistent with high affinity sites of action and suggests that ethanol acts
simultaneously by the same mechanism on different types of initial sites (Deitrich et
al., 1989). Hence, ethanol’s physical-chemical mechanism of action is fundamentally
different from the selective, high affinity binding mechanism that is known to
initiate the behavioral effects of most psychoactive drugs (Dunn et al., 1999). This
atypical mechanism, and resultant lack of high affinity and pharmacological
specificity, precludes the classical approach of using “ethanol receptor” antagonists
to identify the sites and mechanisms of ethanol action.
The present studies used increased atmospheric pressure in place of a
traditional pharmacological antagonist to probe the molecular sites and
mechanisms of ethanol action in GlyRs. We focused on position 52 in Loop 2 in the
extracellular domain of GlyRs based on prior work which indicated that this position
is part of an ethanol action pocket and is also a site of ethanol antagonism (Davies et
al., 2004;Crawford et al., 2007).
We tested the hypothesis that the physical-chemical properties at position 52
in α1GlyRs or the homologous position 59 in α2GlyRs determine sensitivity to
ethanol and pressure antagonism of ethanol. As predicted, we found that pressure
antagonized the effects of ethanol in α1GlyRs that contain a non-polar residue at
40
position 52, but did not antagonize the receptors that had a polar residue at this
position. Moreover, ethanol sensitivity in the receptors with polar substitutions at
position 52 was significantly lower compared to the GlyRs with non-polar residues
at this position.
These findings indicate that the polarity and the hydrophobicity of the
residue at position 52 plays a key role in determining the responsiveness of α1GlyRs
to both ethanol and pressure antagonism of ethanol. Correlation analyses presented
in the present paper support this conclusion in α1GlyRs. In addition, the α2T59A
mutation restored sensitivity to ethanol and pressure antagonism of ethanol in the
α2GlyR, thereby making it α1-like in these respects. Collectively, these findings in
α1 and α2 GlyRs point to Loop 2 in the extracellular domain of GlyRs as a potential
target for the development of alcohol antagonists. They also indicate that there is
structural functional homology across subunits in Loop 2 of the extracellular
domain with respect to the role they play in determining sensitivity to ethanol and
pressure antagonism of ethanol. These findings in the extracellular region differ
from previous studies in the TM region that showed a role for molecular volume at
position 267 in controlling ethanol sensitivity in α1GlyRs (Ye et al., 1998), and
suggest that different physical-chemical properties may influence ethanol action,
respectively, in the extracellular and TM domains.
Although polarity and hydrophobicity are related, and are often thought to be
interchangeable, examining separately their correlations with potency revealed
some insights into the nature of the ethanol binding sites. The Zimmerman polarity
41
scale used in the present study (Zimmerman et al., 1968) is based on the difference
in electronegativity between atoms in the amino acids tested, and is not directly
determined by oil-water partitioning/partition coefficients. However,
hydrophobicity is determined by the oil-water partitioning of the respective amino
acids. Hence, these differences in the physical chemical parameters likely underlie
the respective differences in the strength of the correlations with sensitivity to
ethanol and to pressure antagonism of ethanol.
For example, tryptophan is considered to be a non-polar amino acid due to the
hydrophobic character of its indole ring, which is reflected in its relatively high
positioning in the hydrophobicity scale. In contrast, the electron pair on the indole
nitrogen allows it to form a hydrogen bond and causes it to behave like a polar
amino acid. In addition, the indole ring in tryptophan (and the aromatic rings in
A52F and A52Y) could act as an acceptor in a cation-pi interaction (Dougherty,
1996) and this ability is not reflected in the hydrophobicity scale. In the present
study, tryptophan appears to be a key determinant of the strength of the
correlations with sensitivity to both ethanol and pressure antagonism of ethanol.
Specifically, when its polarity is used, it fits nicely in the linear correlation for both
sensitivity to ethanol, and pressure antagonism of ethanol. In contrast, when its
hydrophobicity is used, tryptophan is an outlier in both cases. This suggests that
polarity, and not hydrophobicity, is the key determinant. Taken together, these
findings suggest that the physical-chemical factors at position 52 that influence
sensitivity to ethanol and sensitivity to pressure antagonism of ethanol are
42
influenced strongly by polarity and that polarity may be the underlying factor that
gives hydrophobicity its correlation.
There are several possible explanations for the antagonistic effects of 12 ATA
pressure observed in the present study. Fortunately, previous studies help to define
the most likely mechanisms. Direct effects of high pressure on protein structure
have been studied extensively. However, these studies typically use 1000 to 10,000
ATA to observe effects (Weber and Drickamer, 1983). Indeed, in the present studies
no effect was observed at 12 ATA in the response of GlyRs in the absence of ethanol.
The effect of pressure on membrane fluidity (Trudell et al., 1973a;Mastrangelo et al.,
1979) and phase transitions (Trudell et al., 1974) in phospholipid bilayers has also
been studied, but approximately 100 ATA was required to observe significant
effects.
More pertinent to interpretation of the present results are studies in which
approximately 10 ATA of Xenon or nitrous oxide was sufficient to displace water
molecules from solvated cavities in proteins. For example, Xenon displaced water
molecules from the pore of the cartilage oligomeric matrix protein (COMP) with
little change in the structure of the water-soluble five stranded coil (Malashkevich et
al., 1996). However, in the case of cavities engineered into T4-lysozyme (Quillin et
al., 2000), occupancy of the cavities by Xenon resulted in swelling of the cavity
volume. Although the latter low pressure studies demonstrated significant effects at
8-12 ATA, there is an important distinction between the soluble gases used in them
and the relatively insoluble heliox used in the present study: Raising the
equilibrium pressure of Xenon from 1 to 10 ATA raises the local concentration of the
43
gas that could enter a cavity by the same ratio. This increase in activity of Xenon is
sufficient to explain its ability to displace water from a binding site.
In contrast, raising the pressure of heliox makes only a small increase in the
concentration of the gas in the cavity, because helium is relatively insoluble in water
and lipid. Moreover, the short period that the solutions used in the present study
were exposed to hyperbaric heliox further reduces the possibility that helium was
dissolved in the solutions. Thus, the antagonism by 12 ATA heliox cannot be
explained by an increase in the local concentration of heliox that displaces water
and/or ethanol from the cavity, but is a direct effect of hydrostatic pressure.
Ethanol could act on GlyRs by creating excess partial molar volume. That is, the
volume of the total system with alcohol present would be greater than the sum of
the volumes of ethanol, water, and GlyR. This hypothesis that alcohols and
anesthetics create excess partial molar volume has been presented in various forms
by several authors (Miller et al., 1973;Mori et al., 1984;Imai et al., 2006) and is
consistent with the swelling of cavities by Xenon described above for T4-lysozyme.
Given that exposure to 12 ATA heliox did not change WT or mutant receptor
function in the absence of ethanol, it is reasonable to conclude that pressure does
not change the way that water hydrates the exterior of the GlyR or fills its internal
cavities. This notion is supported by previous work that shows that glycine
response under 12 ATA heliox remains constant with multiple applications of
glycine over prolonged periods, which indicates that pressure antagonism cannot be
explained by receptor desensitization or rundown (Davies et al., 2003;Davies et al.,
2004). Therefore, the most likely explanation of pressure antagonism of ethanol in
44
GlyRs is that pressure offsets the increase in partial molar volume produced by
ethanol. Pressure could do this by displacing ethanol and/or an ethanol-water
complex from an active site.
The above notion is consistent with our present and previous data that suggest a
continuous thermodynamic opposition between the effects of ethanol and pressure
(Davies et al., 2004). That is, ethanol causes potentiation of α1GlyR, pressure
opposes this potentiation, but the pressure effect can be overcome by increasing the
ethanol concentration (Figure 2.4A). Moreover, the differences in sensitivity to
ethanol, based on the physical chemical properties of mutations at homologous
positions 52 and 59 in α1 and α2 GlyRs, add key information to this model. The
mutation of A52 to more polar residues reduced the potentiation by ethanol. This
change can be explained by the differences in the forces attracting water and
ethanol in the WT and mutant receptors. That is, water is attracted to alanine (non-
polar) in WT A52 α1GlyRs by a combination of London dispersion and van der
Waals forces; whereas, water is attracted to serine (polar) in mutant A52S α1GlyRs
by these forces plus hydrogen bonding. Therefore, it would be harder for ethanol to
displace water in order to access positions 52 when the respective position contains
a polar versus non-polar residue. These differences in the accessibility of ethanol to
a site of action could explain the differences in ethanol sensitivity of WT and mutant
GlyRs.
In conclusion, the findings presented in this report represent the initial steps
towards defining a site and mechanism of ethanol action and antagonism in GlyRs.
45
Additional studies will increase our knowledge regarding the physical-chemical
characteristics necessary for pressure antagonism, and in turn will aid in the
development of molecules that mimic the ethanol antagonizing properties of
pressure. Given the homology between GlyRs and other LGICs (GABA AR, 5HT3R and
nAchRs), the current findings should also provide insight into the molecular
mechanisms and targets of ethanol action and antagonism in other LGICs in the Cys
loop superfamily of receptors.
46
CHAPTER 3
THE PRESENCE OF CHARGE AT POSITION 52 IN EXTRACELLULAR DOMAIN
LOOP 2 OF GLYCINE RECEPTORS PLAYS DIFFERENT ROLES IN ETHANOL
ACTION AND ANTAGONISM

CHAPTER 3 ABSTRACT

Previous studies showed that polarity at position 52 in Loop 2 of α1GlyRs can affect
sensitivity to ethanol and pressure antagonism of ethanol. The present study
extended the investigation to determine how charge at position 52 affects ethanol
sensitivity. We found that substituting Glu at position 52 (A52E) significantly left-
shifted the glycine dose response curve and increased sensitivity to ethanol. On the
other hand, substitution of the negatively charged Asp at this position (A52D)
significantly right-shifted the glycine EC50 but did not affect ethanol sensitivity of
the receptor. Interestingly, substituting the uncharged structural analog of Glu at
position 52, Gln (A52Q), caused the same increase in ethanol sensitivity that was
produced by substituting the negatively charged Glu. Substituting positive charges
at this position did not affect glycine or ethanol sensitivity with respect to WT GlyRs.
In agreement with the effects of uncharged polar residues, all polar charged
substitutions rendered the receptor insensitive to pressure antagonism of ethanol.
This effect on sensitivity to pressure antagonism was independent of the direction
of the charge. Collectively, these findings suggest that subtle differences in
structure/size of the amino acid at position 52 and not charge per se at position 52
affect sensitivity to ethanol. In contrast, the polarity of the residue at this position
plays a key role in determining sensitivity to pressure antagonism of ethanol.
47
INTRODUCTION
Studies described in Chapter 2 (Perkins et al., 2008) found a high inverse
correlation between the polarity of the amino acid at position 52 in Loop 2 of the
extracellular domain of GlyRs and the sensitivity of the receptor to potentiation by
ethanol. We found a similar high inverse correlation between the polarity of the
amino acid at this position and the sensitivity of the receptor to pressure
antagonism of ethanol. These findings supported the hypothesis that the physical-
chemical properties at position 52 in Loop 2 of the extracellular domain of α1GlyRs
determine the sensitivity of the receptor to ethanol and to pressure antagonism of
ethanol (Perkins et al., 2008). These findings also suggest a link between the
structures and mechanisms that cause ethanol action and antagonism by pressure.
However, this physical-chemical study only investigated the sensitivity of the
receptor to ethanol and pressure antagonism when uncharged, neutral residues
were substituted at position 52. This leaves open the question of whether this
relationship would extend to the much higher degree of polarity that would be
produced by the substitution of charged residues.
The present study tested the hypothesis that the degree of polarity at
position 52 is a primary factor that determines the sensitivity of the receptor to
ethanol and pressure antagonism of ethanol. This hypothesis predicts that
substituting highly polar charged residues at position 52 would: 1) Further decrease
ethanol sensitivity versus polar uncharged residues; 2) Render the receptors
insensitive to pressure antagonism of ethanol, if the antagonism is blocked by the
48
presence of any degree of polarity or 3) Switch the antagonistic effect of pressure to
an increase in the positive modulation by ethanol, if the effect of polarity on ethanol
response is on a continuum. The findings confirm Prediction 2 in that substituting
charged residues, independent of the direction of charge (positive or negative),
eliminated sensitivity to pressure antagonism of ethanol. On the other hand, the
findings did not confirm Prediction 1. Rather, the latter findings suggest that subtle
structural differences at position 52, not charge per se, can markedly affect the
receptor’s sensitivity to ethanol.

MATERIALS AND METHODS
Materials - Adult female Xenopus laevis frogs were purchased from Nasco
(Fort Atkinson, WI). Penicillin, streptomycin, gentamicin, 3-aminobenzoic acid ethyl
ester, glycine, ethanol, and collagenase were purchased from Sigma (St. Louis, MO).
All other chemicals used were of reagent grade. Certified premixed gases were
supplied by Specialty Air Technologies (Long Beach, CA).
Expression in Oocytes- Xenopus oocytes were isolated and injected with WT
or human α1 or mutant α1A52C, α1A52D, α1A52E, α1A52H, α1A52K, α1A52N,
α1A52Q or α1A52R cDNAs (1 ng per 32 nl) cloned into the mammalian expression
vector pCIS2 or pBKCMV as previously described (Davies et al., 2003) and verified
by partial sequencing (DNA Core Facility, University of Southern California, USA).
Mutagenesis of the alanine at position 52 in α1GlyRs was performed as previously
described (Ryan et al., 1994). After injection, oocytes were stored individually in
49
incubation medium (MBS supplemented with 2mM sodium pyruvate, 0.5mM
theophylline, 10,000 U/l penicillin, 10 mg/l streptomycin and 50 mg/l gentamicin)
in petri dishes (VWR, San Dimas, CA). All solutions were sterilized by passage
through 0.22 μM filters. Oocytes, stored at 18°C, usually expressed GlyRs the day
after injection. Oocytes were used in electrophysiological recordings for 3-7 days
after cDNA injection.
Atmospheric conditions - Atmospheric conditions were established as
described previously (Davies et al., 2004;Perkins et al., 2008). Briefly, we tested the
1 ATA air condition (control) in a hyperbaric chamber with the lid removed or by
using compressed air with the chamber sealed. Pilot studies determined that there
was no measurable difference between the results obtained by these two methods. To
achieve the 12 ATA heliox condition, the chamber was purged with heliox and then
pressurized to the experimental ATA at the rate of 1 ATA/min using premixed certified
compressed gases. The heliox mixture consisted of 1.7% oxygen and 98.3% helium
resulting in a 0.2 ATA partial pressure for oxygen at 12 ATA; this mixture provides
normal oxygenation. We found previously that this mixture avoids complications
from higher oxygen partial pressures (Alkana and Malcolm, 1981). We replaced the
nitrogen in our gas mixture with helium to avoid the depressant effect of nitrogen at
increased atmospheric pressure (Alkana and Malcolm, 1982a).
Hyperbaric Two-Electrode Whole Cell Voltage Clamp Recording – Two-
electrode voltage clamp recording was performed using techniques similar to those
previously reported (Davies et al., 2003). Briefly, electrodes pulled (P-30, Sutter
50
Instruments, Novato, CA) from borosilicate glass [1.2mm thick-walled filamented
glass capillaries (WPI, Sarasota, FL)] were back-filled with 3M KCl to yield
resistances of 0.5 -3 MΩ. All electrophysiological recordings were conducted within
a specially designed hyperbaric chamber that contains a vibration resistant platform
that supports an oocyte bath, two micro positioners (WPI, Sarasota, FL or Narishige
International USA, Inc East Meadow, NY) and bath clamp (Davies et al., 2003).
Oocytes were perfused in a 100 μl oocyte bath with MBS ± drugs via a custom high
pressure drug delivery system (Alcott Chromatography, Norcross, GA) at 2 ml/min
using 1/16 OD high pressure PEEK tubing (Upchurch Scientific, Oak Harbor, WA).
Oocytes were voltage clamped at a membrane potential of -70 mV using a Warner
Instruments Model OC-725C (Hamden, CT) oocyte clamp. Individual oocytes were
tested at both control and experimental atmospheric conditions and checked for
normal function during pressurization and depressurization. The order of testing
control and atmospheric conditions was counterbalanced to minimize the effects of
testing order and to determine if pressure effects were reversible.
Glycine concentration responses: Oocytes expressing WT or mutant
α1GlyRs were exposed to glycine for 30s, using 5-15 min washouts between
applications to ensure complete resensitization (Mascia et al., 1996a;Mascia et al.,
1996b;Davies et al., 2004;Crawford et al., 2007). Pilot experiments found that WT
and mutant GlyR agonist responses using a 1 min glycine application reached a
steady state equilibrium with results which did not differ appreciably from results
using 30s applications. Therefore, we used the shorter application time to increase
51
efficiency and to minimize desensitization at the higher glycine concentrations.
Responses were normalized to the maximal glycine response. Concentration
response curves were analyzed using non-linear regression.
Ethanol experiments: Previous work found that ethanol potentiation of
GlyR function is more robust and reliable when tested in the presence of low
concentrations of glycine (typically EC 2-10) (Davies et al., 2004;Perkins et al., 2008).
Based on these studies, we used a concentration of glycine producing 2 ± 0.3% of
the maximal effect (EC2). When testing ethanol potentiation, the oocytes were pre-
incubated with ethanol for 60 sec prior to co-application of ethanol and glycine
(Davies et al., 2004). Washout periods (5-15 min) were allowed between drug
applications to ensure complete resensitization of receptors. Note that ethanol is a
low efficacy drug in that millimolar (mM) concentrations are associated with
behavioral signs of intoxication. In studies of ethanol action on ion channels,
concentrations of ethanol (10-100 mM) typically produce responses in the 15-40%
range. Therefore, we used 100 mM ethanol in the present studies in order to reduce
variability inherent with such small changes. We have demonstrated that pressure
antagonizes ethanol at lower concentrations in oocytes (Davies et al., 2004;Perkins
et al., 2008). Moreover, we have shown that pressure antagonizes a spectrum of
behavioral effects of ethanol without altering baseline behavioral function (Syapin
et al., 1988;Davies et al., 1994;Davies et al., 1999). All experiments testing mutant
GlyRs included WT control receptors expressed in the same batch of oocytes as the
respective mutant GlyRs. A chart recorder (Barnstead/Thermolyne, Dubuque, IA)
continuously plotted the clamped currents. The peak currents were measured and
52
used in data analysis. All experiments were performed at room temperature (20-
23° C).
MTS Reagent Protocol: We used MTS reagents in combination with cysteine
substitutions as an alternative approach to mutations for assessing the effect of
charge at position 52 on sensitivity to ethanol. Previous work found that positions
52 and 53 are accessible to and capable of binding MTS reagents (Crawford et al.,
2007;Crawford et al., 2008). Oocytes expressing WT or A52C GlyRs were exposed to
negatively charged MTSES (10mM) for two minutes in order to fully saturate the
substituted cysteine residues. Following the two minute saturation exposure,
oocytes were transferred to the recording chamber and tested as described above
for the glycine concentration response study. MTS solutions were prepared
immediately before testing. Prior work has shown that saturating the oocyte with
MTSES in this manner yielded results which did not differ appreciably from results
obtained by perfusing MTSES (Crawford et al., 2008).
Cell-Surface Biotinylation and Immunoblotting. Biotinylation of surface-
expressed proteins was performed as previously described (Chen et al., 2005).
Oocytes (15 oocytes per group) were incubated with 1.5 mg/mL membrane-
impermeable Sulfo-NHS-SS-biotin (Pierce Biotechnology, Rockford, IL) four days
after cDNA injections, for 30 min at room temperature. After washing once with 25
mM Tris (pH 8.0) and twice with Phosphate Buffered Saline (PBS), oocytes were
homogenized in 500 uL of lysis buffer [40 mM Tris (pH 7.5), 110 mM NaCl, 4 mM
EDTA, 0.08% Triton X-100, 1% protease inhibitor cocktail (Vector Laboratories,
53
Burlingame, CA)]. The yolk and cellular debris were removed by centrifugation at
3600g for 10 min. Aliquots of the supernatant were mixed with 5X Sodium Dodecyl
Sulphate (SDS) loading buffer and stored at -20˚C to assess total receptor fraction.
The remaining supernatant was incubated with streptavidin beads (Pierce
Biotechnology) overnight at 4˚C. Beads were washed three times with lysis buffer
and the biotinylated proteins eluted using SDS loading buffer. The surface and total
proteins were separated using SDS- polyacrylamide gel electrophoresis (SDS-PAGE)
and transferred to polyvinylidene fluoride (PVDF) membranes. The membranes
were incubated overnight with rabbit anti-GlyR antibody (1:500 dilution, Chemicon
International, Temecula, CA), followed by incubation with the appropriate
horseradish peroxidase-conjugated secondary antibody. Protein bands were
visualized using enhanced chemiluminescence (Pierce Biotechnology). The blots
were then scanned and analyzed using Scion Image software (Scion Corporation,
Frederick, MD).
Data Analysis - Data for each experiment were obtained from oocytes from
at least two different frogs. The n refers to the number of oocytes tested. Results
are expressed as mean ± SEM. Where no error bars are shown, they are smaller
than the symbols. We used Prism (GraphPAD Software, San Diego, CA) to perform
curve fitting and statistical analyses. Concentration response data were analyzed
using non-linear regression analysis: [I = I max [A]
nH
/ ([A]
nH
+ EC 50
nH
)] where I is the
peak current recorded following application of a range of agonist concentrations, [A];
I max is the estimated maximum current; EC 50 is the glycine concentration required for a
half-maximal response and n H is the Hill slope. Data were subjected to t-tests, one- or
54
two-way Analysis of Variance (ANOVA) with Dunnett’s multiple comparison tests
when warranted. Statistical significance was defined as p < 0.05.

RESULTS

Glycine EC50s in WT and Mutant α α α α1GlyRs:
The effect of point mutations at position 52 on glycine sensitivity of α1GlyRs is
shown (Figure 3.1). Inward chloride currents were evoked in a concentration-
dependent manner by glycine in WT and all mutant GlyRs.

FIGURE 3.1

Figure 3.1. Concentration-response curves for glycine (1-30,000 µM) activated chloride
currents in Xenopus oocytes expressing WT and mutant α α α α1GlyR subunits: Glycine induced
chloride currents were normalized to the maximal current activated by a saturating concentration of
glycine (30 mM) when tested under 1 ATA air conditions. The curves represent non-linear regression
analysis of the glycine concentration responses in the α1 mutant GlyRs compared to WT α1GlyRs.
Details of EC 50, Hill Slope and Maximal current amplitude (I max) are provided in Table 3.1. Glycine
was applied for 30 sec. Washout time was 5-15 min after application of glycine. Each data point
represents the mean ± SEM from 8 different oocytes.

55
We found a significant left shift in glycine EC50 from WT α1GlyR for the
negatively charged α1A52E and a significant right-shift for the negatively charged
α1A52D (Table 3.1). Substituting the uncharged structural analog of E (Q) at
position 52 (α1A52Q) did not cause a similar left-shift in glycine response.
Substituting the uncharged structural analog of D (N) at position 52 (α1A52N)
caused a dramatic right-shift in glycine concentration response greater than that
observed for α1A52D. Positively charged residues at position 52 did not cause
significant shifts in EC50. With the exception of the A52N mutant, no significant
differences were observed between WT and mutant GlyRs in Hill slope (n H) or
maximal current amplitude (I max) (Table 3.1). Collectively, these changes in glycine
sensitivity are consistent with the notion that position 52 in Loop 2 of GlyRs plays
an important role in agonist activation.
TABLE 3.1
Charge at 52

Receptor Imax (nA) Hill Slope EC50 (μM)

Negative
α α α α1A52E 10595±1516 4.513±0.725 31.28±2.9 **
α α α α1A52D 8813±188 3.312±0.694 587.08±80*

Neutral
α α α α1WT 7650±602 3.094±0.879 374.17±24
α α α α1A52N 1605±339* 1.210±0.204 13358.71±2294.34***
α α α α1A52Q 11962±5018 1.774±0.515 407.50±213.24

Positive
α α α α1A52R 10095±2587 1.876±0.170 313.10±94.7
α α α α1A52H 15770±5640 2.397±0.260 385.33±130.7
α α α α1A52K 8068±1134 2.326±0.467 148.16±33.21

Table 3.1. Summary of non-linear regression analysis results for glycine concentration
responses and differences in ethanol sensitivity WT and mutant α α α α1 GlyRs shown in terms of
charge of residue at position 52: Glycine EC50, Hill Slope (n H) and maximal current amplitude
(I max) are presented as mean ± SEM from 4-7 different oocytes (as shown in Figure 3.1). Statistical
significance from WT α1GlyRs was assessed using one-way ANOVA with Dunnett’s post test.
56
Cell surface expression of WT and Mutant α α α α1GlyRs:
To determine if the shifts in Imax responses of A52N GlyRs reflected changes
in surface expression levels, we compared the GlyR protein content of WT and
mutant GlyRs via cell-surface biotinylation and immunoblotting analysis (Figure
3.2). We did not observe any significant difference between cell-surface or total
expression of GlyR protein between WT and any of the mutant GlyRs tested.

Figure 3.2

Figure 3.2 Differences in sensitivity to ethanol and Glycine are not due to differences in total
or cell surface expressed protein. Western blot analysis of the immunoprecipitate of total cell
lysate and cell surface biotinylated fraction from Xenopus oocyte expression of WT, A52D, A52E,
A52N or A52Q GlyRs. Results shown are for 1ng of WT or mutant GlyR cDNA injected into each
oocyte. Immunoprecipitates were run on SDS-PAGE gel, then transferred to PVDF membrane. Blots
were then probed with rabbit antibody against the α1 subunit of the human GlyR.

Negatively charged amino acid substitutions at position 52 differentially affect
sensitivity to ethanol:
The effect of charged substitutions at position 52 in α1GlyRs on sensitivity to
100mM ethanol is shown (Figure 3.3). Ethanol responses for the negatively charged
α1A52E was significantly increased compared to WT α1GlyRs. In contrast, the
57
negatively charged A52D mutation did not differ from WT with respect to ethanol
sensitivity. Ethanol responses for the positively charged substitutions at position 52
(α1A52H, α1A52K and α1A52R) were not significantly different than WT α1GlyRs
(Figure 3.3). These findings suggest that the presence of charge per se at position 52
in α1GlyRs does not affect ethanol sensitivity.
FIGURE 3.3

Figure 3.3. Charge of the residue at position 52 in α α α α1GlyRs does not determine sensitivity to
ethanol: Figure shows ethanol % potentiation of glycine induced chloride current at 100mM ethanol.
The red bar shows the WT GlyR which has a neutral amino acid at position 52. Black bars represent
negatively charged substitutions at position 52 in α1 GlyRs and grey bars represent positively
charged substitutions. Significance is *p<0.05 vs. WT α1GlyRs.

Polarity controls sensitivity to pressure Antagonism of ethanol even in the
presence of a charge at position 52:
Oocytes expressing WT, negatively charged α1A52D and α1A52E GlyRs and
positively charged α1A52H, α1A52K and α1A52R GlyRs were voltage-clamped and
tested with glycine +/- (100mM) ethanol under both control and pressure
conditions. As previously reported, pressure antagonized ethanol potentiation in
58
FIGURE 3.4

Figure 3.4 Pressure Does not Antagonize Ethanol potentiation in mutant GlyRs with charged
residues at position 52: The figure depicts results from 100mM ethanol in WT or the mutant
α1GlyRs with charged substitutions at position 52. Oocytes tested at both 1 ATA air control (white
bars) and 12 ATA heliox (black bars). Data is presented as mean ± SEM of 4-6 oocytes. Data was
subjected to two-way repeated measures ANOVA followed by Bonferroni post-hoc analyses.
Statistical significance is *p < 0.05 or ***p<0.001.

WT α1GlyRs (Figure 3.4 A). We found that exposure to 12 ATA heliox did not
significantly affect ethanol potentiation in any of the highly polar, charged mutants
regardless of the nature of the charge present (Figure 3.4 B-F). Moreover,
substituting highly polar charged residues at position 52 did not affect the response
to pressure more than did substituting uncharged polar residues in prior studies
described in Chapter 2 (Perkins et al., 2008). These findings indicate that polarity at
position 52 plays a critical role in determining sensitivity to pressure antagonism of
59
ethanol and that this effect is independent of the direction of the charge and the
magnitude of the polarity.
Binding a negatively charged MTS reagent at position 52 does not affect
ethanol sensitivity:
We tested the effect of changing the charge at position A52 on the response
to glycine and ethanol by substituting a cysteine at position 52 and then covalently
binding negatively charged MTSES reagent to the substituted cysteine residue. We
have used this approach successfully to study the effects of introducing a charge at
position 53 in GlyRs on glycine sensitivity (Crawford et al., 2008). Replacing the
neutral alanine at position 52 in WT GlyRs with the neutral cysteine (A52C) right
shifted the glycine concentration response (Fig 3.5A). This substitution also
significantly reduced ethanol response at 100mM (Figure 3.5B).
FIGURE 3.5

A. B.

Figure 3.5 Negative charge at position 52 of the α α α α1GlyR is not important for agonist or ethanol
action (A) Non-linear regression analysis of the glycine concentration responses from oocytes
expressing WT (red), A52C (black) or A52C+ MTSES GlyRs (blue). (B) Bar graphs show %
potentiation at 100mM ethanol of WT (red) vs. A52C (black) vs. A52C+MTSES (blue) GlyRs.
Exposure to negatively charged MTSES did not significantly affect the response of
60
the A52C mutant to glycine (Figure 3.5A) or ethanol (Figure 3.5B). Therefore, the
results suggest that the negative charge per se at position 52 is not important for
agonist activation or ethanol response of GlyRs.
Structure not charge affects ethanol sensitivity at position 52:
Substituting the uncharged structural analog of E (Q) at position 52
(α1A52Q) resulted in a similar increase in ethanol sensitivity to that observed for
A52E. Interestingly, substituting the uncharged structural analog of D (N) at
position 52 (α1A52N) caused a significant decrease in ethanol sensitivity (Figure
3.6). These findings indicate that subtle differences in the structure of the amino
acid at position 52 can have a major impact on ethanol sensitivity in α1GlyRs.
FIGURE 3.6

Figure 3.6 The structure of the amino acid at position 52 plays a role in ethanol sensitivity of
α α α α1GlyRs: The Figure shows ethanol % potentiation of glycine induced chloride current at 100mM
ethanol. The red bar shows the WT GlyR which has a neutral amino acid at position 52. Black bars
represent negatively charged A52E and A52D substitutions at position 52 in α1 GlyRs and blue bars
represent the uncharged structurally analogous substitutions for E and D, A52Q and A52N
respectively. Significance is *p<0.05 or **p<0.01 vs. WT α1GlyRs.

61
DISCUSSION
Prior studies found that the polarity of the residue at position 52 in α1 GlyRs
is highly correlated with the sensitivity of the receptor to ethanol and to pressure
antagonism of ethanol (Chapter 2) (Perkins et al., 2008). The present study
extended this investigation to determine if the relationship to polarity extended to
highly polar charged amino acids. The findings support the hypothesis that the
polarity of the residue at position 52, including highly charged positive and negative
amino acids, plays a significant role in determining sensitivity to pressure
antagonism of ethanol. In contrast, we found that the polarity and structure of the
amino acid at position 52, rather than degree of polarity, both appear to play a role
in determining the sensitivity of the receptor to ethanol. These differences in the
role of polarity and structure on sensitivity to ethanol and pressure antagonism
appear to be independent of the changes caused by the mutations on agonist
sensitivity, and provide insight into the structures and mechanisms of ethanol
action and pressure antagonism.
The effects of substituting charged residues at position 52 in α1 GlyRs did
not consistently affect the sensitivity of the receptor to glycine. Substituting
negatively charged Glu (E), but not other charged residues, strongly increased the
sensitivity of the receptor to glycine. Interestingly, substituting Gln (Q), the
uncharged structural analog for E, at position 52 did not significantly affect glycine
sensitivity. This suggests that the negative charge in E plays a role in changing
glycine sensitivity. However, in contrast to E, substituting the negatively charged
62
Asp (D) at position 52 significantly right-shifted glycine sensitivity. This effect
might reflect the subtle difference in the side-chain structures of these two amino
acids. That is, the additional carbon in the side-chain of E, increases the volume of
this amino acid by 1 Å and could potentially place the charge in a position that is
more likely to interact with surrounding positively charged elements such as Arg
(R) 218 in the pre-M1 region or Lys (K) 276 in neighboring subunits. These
positively charged residues have been shown to be in positions favorable to form
salt-bridges with E53 in Loop 2 and D138 in Loop 7 (Kash et al., 2004b; Crawford et
al., 2008;Perkins et al., 2009). Therefore, in addition to the negative charges of E
and D, their respective structures and resultant orientations appear to be key for
glycine sensitivity.
The conclusion that the presence of a negative charge per se is not a key
factor in determining the sensitivity of α1GlyRs to agonist is further supported by
our findings with binding the negatively charged MTSES reagent at position 52. We
used this strategy previously to determine the role of charge at position 53 on
agonist sensitivity in GlyRs (Crawford et al., 2008). If the mere presence of a
negative charge at position 52 is critical for determining agonist sensitivity, then the
binding of MTSES should have restored the sensitivity of the A52C mutant receptor
back to that of the WT receptor. It did not.
It is notable that substituting N, the uncharged structural analog of negatively
charged D, at position 52 caused a drastic decrease in agonist sensitivity along with
a marked reduction in Imax. Biotinylation experiments followed by Western blot
63
indicated that this change in Imax cannot be explained by a reduction in cell surface
expression. Therefore, it is possible that the substitution of N at position 52
interferes with the formation of functional receptors.
Overall, the findings probing the role of charge and structure at position 52
indicate that, in contrast to polarity (Perkins et al., 2008), charge per se is not a key
factor controlling glycine sensitivity. In contrast, the findings indicate that the
interaction between negative charge and structure can have a major effect on the
sensitivity of α1GlyRs to agonist.
The general effects of substituting charged residues at position 52 on the
sensitivity of α1 GlyRs to ethanol were similar to the effects of these substitutions
on glycine sensitivity. But, there were important differences. As with glycine,
substituting positively charged residues at position 52 did not significantly affect
the sensitivity of the receptor to ethanol. Also as with glycine sensitivity,
substituting the negatively charged E, but not the negatively charged D, significantly
increased the sensitivity of the receptor to ethanol. In contrast to the results for
glycine, substituting Q, the uncharged structural analog of negatively charged E, also
significantly increased ethanol sensitivity. Substituting the N, the uncharged
structural analog of the negatively charged D, drastically reduced ethanol
sensitivity. However, this reduction, as with glycine, likely reflects the decreased
Imax caused by the mutation. The findings clearly indicate that it is the structure of
E and Q and not the negative charge of E alone that increased ethanol sensitivity.
This conclusion is supported by our demonstration that binding the negatively
64
charged MTSES reagent to A52C does not restore the reduced ethanol sensitivity of
the A52C mutant GlyR back to that of WT receptors.
Therefore, these findings with charged residues do not fit predictions based
on the high correlation between the polarity of the residue at position 52 and
ethanol sensitivity reported in Chapter 2 (Perkins et al., 2008). That is, the structure
of the substitution, not its charge per se, is what determined ethanol sensitivity in
the present study. Moreover, in contrast to the interrelationship between charge
and the structure of the amino acid substituted at position 52 on glycine sensitivity,
the effect of these substitutions on ethanol sensitivity appear to reflect subtle
differences only in the structure of the amino acid. Therefore, the physical-chemical
parameters at position 52 that control sensitivity to glycine are different than those
that control sensitivity to ethanol. In addition, prior studies have shown that the
sensitivity of GlyRs to ethanol is not correlated with the glycine EC50 (Chapter 2)
(Perkins et al., 2008). Therefore, it is unlikely that the changes in ethanol sensitivity
produced by these substitutions result from changes in receptor sensitivity to
agonist.
The effects of charged substitutions at position 52 on the sensitivity of α1GlyRs
to pressure antagonism of ethanol appear to be relatively straightforward.
Substituting positively or negatively charged residues eliminated the sensitivity of
the receptors to pressure antagonism of ethanol, but did not produce overshoot that
increased the positive modulation by ethanol beyond that seen in WT receptors.
The effects of charged residues on sensitivity to pressure antagonism were
65
independent of the direction of the charge and the structure of the amino acid
substitution as evidenced by the Q substitution. These findings support the
contention that the presence of polarity at position 52 can eliminate or block the
ability of pressure to offset the effects of ethanol and that substituting highly
charged residues does not produce a greater effect than do uncharged polar
residues.
In summary, the ability of substitutions at position 52 to alter the sensitivity of
α1GlyRs to ethanol and to pressure antagonism of ethanol add to the evidence that
position 52 is a site of action for both ethanol and pressure. Our prior studies
described in Chapter 2 (Perkins et al., 2008), which found a high correlation
between the polarity of the residue at position 52 in α1 GlyRs and the sensitivity of
the receptor to ethanol and pressure antagonism of ethanol, suggested a common
structural basis for these two phenomena. The present study, which found
differences in the effects of physical-chemical and structural properties at position
52 on the sensitivity of the receptor to ethanol and pressure antagonism of ethanol
suggest that, although position 52 may be a common target for both phenomena, the
structural bases underlying their respective actions are different. These differences
may provide insight into the mechanism by which ethanol affects receptor function
and by which pressure antagonizes the effects of ethanol. This knowledge will help
to define the chemical architecture of this site of ethanol action and the key
physical-chemical parameters that cause and antagonize the actions of ethanol in
GlyRs.
66
CHAPTER 4
LOOP 2 STRUCTURE IN GLYCINE AND GABA A RECEPTORS PLAYS A KEY ROLE IN
DETERMINING ETHANOL SENSITIVITY
CHAPETR 4 ABSTRACT
The present study tests the hypothesis that the structure of extracellular domain
Loop 2 can markedly affect ethanol sensitivity in glycine receptors (GlyRs) and
GABA ARs. To test this, we mutated Loop 2 in the α1 subunit of GlyRs and in the γ
subunit of α1β2γ2GABA ARs and measured the sensitivity of wildtype and mutant
receptors expressed in Xenopus oocytes to agonist, ethanol and other agents using
two-electrode voltage clamp. Replacing Loop 2 of α1GlyR subunits with Loop 2
from the δGABA AR (δL2), but not the γGABA AR subunit, reduced ethanol threshold
and increased the degree of ethanol potentiation without altering general receptor
function. Similarly, replacing Loop 2 of the γ subunit of GABA ARs with δL2 shifted
ethanol threshold from 50mM in WT to 1mM in the GABA A γ-δL2 mutant. These
findings indicate that the structure of Loop 2 can profoundly affect ethanol
sensitivity in GlyRs and GABA ARs. The δL2 mutations did not affect GlyR or GABA AR
sensitivity, respectively, to Zn
2+
or diazepam, which suggests that these δL2-induced
changes in ethanol sensitivity do not extend to all allosteric modulators and may be
specific for ethanol or ethanol-like agents. To explore molecular mechanisms
underlying these results, we threaded the WT and δL2 GlyR sequences onto the X-
ray structure of the bacterial Gloeobacter violaceus pentameric ligand-gated ion
channel homologue (GLIC). In addition to being the first GlyR model threaded on
67
GLIC, the juxtaposition of the two structures led to a possible mechanistic
explanation for ethanol’s effects on GlyR based on changes in Loop 2 structure.
INTRODUCTION

Alcohol abuse and dependence are significant problems in our society with
approximately 14 million people in the United States being affected (McGinnis and
Foege, 1999;Volpicelli, 2001). Alcohol causes over 100,000 deaths in the US and
alcohol-related issues are estimated to cost nearly 200 billion dollars annually
(Volpicelli, 2001). To address this, considerable attention has focused on the
development of medications to prevent and treat alcohol-related problems (Heilig
and Egli, 2006;Steensland et al., 2007;Johnson et al., 2007). The development of
such medications would be aided by a clear understanding of the molecular
structures on which ethanol acts and how these structures influence receptor
sensitivity to ethanol.
Ligand-gated ion channels (LGICs) have received substantial attention as
putative sites of ethanol action that cause its behavioral effects (Deitrich et al.,
1989;Harris, 1999;Mihic et al., 1997;Ye et al., 1998;Zhou and Lovinger,
1996;Cardoso et al., 1999;Davies and Alkana, 2001a). Research in this area has
focused on investigating ethanol’s effects on two large superfamilies of LGICs: 1)
The cys-loop superfamily of LGICs (Ortells and Lunt, 1995;Karlin, 2002) whose
members include nicotinic acetylcholine (nACh), 5-hydroxytryptamine 3 (5HT 3), γ-
aminobutyric acid type-A (GABA A), type-C (GABA C) and glycine receptors (GlyRs)
(Mihic and Harris, 1996;Zhou and Lovinger, 1996;Grant, 1995;Cardoso et al.,
68
1999;Davies et al., 2002;Davies et al., 2004;Crawford et al., 2007;Perkins et al.,
2008) and 2) The glutamate superfamily including N-methyl D-aspartate (NMDA), α
-amino-3-hydroxyisoxazolepropionic acid (AMPA) and kainate receptors
(Monaghan et al., 1989;Sommer and Seeburg, 1992). Recent studies have also
begun investigating ethanol action in the ATP-gated P2X superfamily of LGICs
(Weight et al., 1999;Davies et al., 2005;Asatryan et al., 2008).
A series of studies, which employed chimeric and mutagenic strategies combined
with sulfhydryl-specific labeling, identified key regions within cys-loop receptors
that appear to be initial targets for ethanol action that also can determine the
receptors’ sensitivity to ethanol (Zhou and Lovinger, 1996;Mihic et al., 1997;Ye et
al., 1998;Harris, 1999;Cardoso et al., 1999;Davies and Alkana, 2001a;Mascia et al.,
1996a;Valenzuela et al., 1998;Ye et al., 2002;Davies et al., 2004;Yevenes et al.,
2006;Crawford et al., 2007;Lobo et al., 2008). This work provides several lines of
evidence that position 267 and possibly other sites in the transmembrane (TM)
domain of GlyRs, and homologous sites in GABA ARs, are targets for ethanol action
and that mutations at these sites can influence ethanol sensitivity (Mihic et al.,
1997;Ye et al., 1998;Mascia et al., 2000;Lobo et al., 2008).
Growing evidence from GlyRs indicates that ethanol also acts on the
extracellular domain. The initial findings came from studies demonstrating that
α1GlyRs are more sensitive to ethanol than are α2GlyRs despite the high (~78%)
sequence homology between α1 and α2GlyRs (Mascia et al., 1996b). Further work
found that an alanine to serine exchange at position 52 (A52S) in Loop 2, can
69
eliminate the difference in ethanol sensitivity between α1 and α2GlyRs (Davies et
al., 2003;Davies et al., 2004;Perkins et al., 2008). These studies also demonstrated
that mutations at position 52 in α1GlyRS, and the homologous position 59 in
α2GlyRs controlled the sensitivity of these receptors to a novel mechanistic ethanol
antagonist (Perkins et al., 2008). Collectively, these studies suggest that there are
multiple sites of ethanol action in α1GlyRs, with one site located in the TM domain
(e.g., position 267) and another in the extracellular domain (e.g., position 52).
Subsequent studies revealed that the polarity of the residue at position 52
plays a key role in determining the sensitivity of GlyRs to ethanol (Perkins et al.,
2008). The findings with polarity in the extracellular domain contrast with the
findings at position 267 in the TM domain, where molecular volume, but not
polarity, significantly affected ethanol sensitivity (Ye et al., 1998). Taken together,
these findings indicate that the physical-chemical parameters of residues at
positions in the extracellular and TM domains that modulate ethanol effects and/or
initiate ethanol action in GlyRs are not uniform. Thus, knowledge regarding the
physical-chemical properties that control agonist and ethanol sensitivity is key for
understanding the relationship between structure and the actions of ethanol in
LGICs (Kash et al., 2003;O'Mara et al., 2003;Castaldo et al., 2004;O'Mara et al.,
2005;Wang et al., 2007;Crawford et al., 2008;Crawford et al., 2007;Mascia et al.,
2000;Cheng et al., 2007).
GlyRs and GABA ARs, which differ significantly in their sensitivities to ethanol,
offer a potential method for identifying the structures that control ethanol
70
sensitivity. For example, α1GlyRs do not reliably respond to ethanol concentrations
less than 10 mM (Mascia et al., 1996b;Davies et al., 2003;Woodward et al., 2004).
Similarly, γ subunit-containing GABA ARs (e.g., α1β2γ2), the most predominantly
expressed GABA ARs in the CNS, are insensitive to ethanol concentrations less than
50 mM (White et al., 1990;Weiner et al., 1997). In contrast, δ subunit-containing
GABA ARs (e.g., α4β3δ) have been shown to be sensitive to ethanol concentrations as
low as 1-3 mM(Sundstrom-Poromaa et al., 2002;Wei et al., 2004;Hanchar et al.,
2005;Hanchar et al., 2006;Liang et al., 2006;Fleming et al., 2007;Glykys et al.,
2007;Santhakumar et al., 2007). Sequence alignment of α1GlyR, γGABA AR and
δGABA AR revealed differences between the Loop 2 regions of these receptor
subunits. Since prior studies found that mutations of Loop 2 residues can affect
ethanol sensitivity (Crawford et al., 2007;Crawford et al., 2008;Perkins et al., 2008),
the non-conserved residues in Loop 2 of GlyR and GABA AR subunits could provide
the physical-chemical and structural bases underlying the differences in ethanol
sensitivity between these receptors.
The present study tested the hypothesis that the structure of Loop 2 can
markedly affect the ethanol sensitivity of GlyRs and GABA ARs. To accomplish this,
we performed multiple mutations that replaced the Loop 2 region of the α1 subunit
in α1GlyRs and the Loop 2 region of the γ subunit of α1β2γ2 GABA ARs with
corresponding non-conserved residues from the δ subunit of GABA AR and tested the
sensitivity of these receptors to ethanol. As predicted, replacing Loop 2 of WT
α1GlyRs with the homologous residues from the δGABA AR subunit (δL2), but not the
71
γGABA AR subunit (γL2), markedly increased the receptor’s sensitivity to ethanol.
Similarly, replacing the non-conserved residues of the γ subunit of α1β2γ2 GABA ARs
with δL2 also markedly increased ethanol sensitivity of GABA ARs. These findings
support the hypothesis and suggest that Loop 2 may play a role in controlling ethanol
sensitivity across the cys-loop superfamily of receptors. The findings also provide the
bases for suggesting structure-function relationships in a new molecular model of the
GlyR based on the bacterial Gloeobacter violaceus pentameric LGIC homologue
(GLIC).

MATERIALS AND METHODS

Materials - Adult female Xenopus laevis frogs were purchased from Nasco (Fort
Atkinson, WI). Gentamicin, 3-aminobenzoic acid ethyl ester, glycine, GABA, ethanol,
zinc chloride, strychnine, picrotoxin, diazepam and collagenase were purchased
from Sigma (St. Louis, MO). All other chemicals used were of reagent grade. Glycine,
GABA and strychnine stock solutions were prepared from powder. Stock solutions
of picrotoxin and diazepam were prepared in dimethyl sulfoxide (DMSO) and then
diluted to an appropriate concentration with the extracellular solution just before
use. To avoid adverse effects from DMSO exposure, the final concentration

(v/v) of
DMSO was not higher than 0.5%. Picrotoxin stocks and solutions were wrapped in
foil to avoid UV exposure.

72
Expression in Oocytes - The amino acid sequences for α1GlyR and δ and γ GABA AR
subunits were aligned and the Loop 2 regions compared (Table 4.1).
TABLE 4.1
Human GlyR α α α α1 50 S I A E T T M D Y R
Human GABA AR δ δ δ δ 43 H I S E A N M E Y T
Human GABA AR γ γ γ γ2 64 P V N A I N M E Y T
Human nAChR α α α α1 42 N V D E V N Q I V E
GLIC 29 S L D D K A E T F K
Table 4.1. Loop 2 sequence alignment for the α α α α1GlyR subunit, δ δ δ δ and γ γ γ γ GABA AR subunits,
α α α α1nAChR subunit and GLIC.

Individual point mutations in the α1GlyR or γGABA AR subunit cDNA were created so
that the resulting Loop 2 region matched that of the δGABA AR or the γGABA AR
subunits. Xenopus oocytes were isolated and injected with human GlyR cDNAs (1 ng
per 32 nL) or GABA AR cDNAs (1:1:10 ratio for a total volume of 1 ng of α1β2γ2)
cloned into the mammalian expression vector pCIS2 or pBKCMV as previously
described (Davies et al., 2003) and verified by partial sequencing (DNA Core Facility,
University of Southern California, USA). After injection, oocytes were stored in
incubation medium [Modified Barth’s Saline (MBS) supplemented with 2 mM
sodium pyruvate, 0.5 mM theophylline and 50 mg/L gentamycin] in petri dishes
(VWR, San Dimas, CA). All solutions were sterilized by passage through 0.22 μM
filters. Oocytes, stored at 18°C, usually expressed GlyRs the day after injection and
GABA ARs 3-4 days after injection. Oocytes were used in experiments for up to 7 days
after injection.
73
Native delta containing GABA ARs (α4β2/3δ and α6β2/3δ) have been shown to be
sensitive to low ethanol concentrations (1-3 mM) in a variety of preparations
(Sundstrom-Poromaa et al., 2002;Wei et al., 2004;Hanchar et al., 2005;Hanchar et
al., 2006;Liang et al., 2006;Fleming et al., 2007;Glykys et al., 2007;Santhakumar et
al., 2007). However, these receptors are difficult to express in oocytes. This topic
has been the subject of several reviews (Olsen et al., 2007;Borghese and Harris,
2007;Mody et al., 2007). The goal of the present study was to test the hypothesis
that the structure of Loop 2 can markedly affect the ethanol sensitivity of GlyRs and
GABA ARs. We used the δ Loop 2 as a vehicle for testing this hypothesis. In this
context, and given the difficulties described above, we did not include WT δ
containing GABA ARs in the current paper.

Whole Cell Two-Electrode Voltage Clamp Recordings - Two-electrode voltage
clamp recording was performed using techniques similar to those previously
reported (Davies et al., 2003). Briefly, electrodes pulled (P-30, Sutter Instruments,
Novato, CA) from borosilicate glass [1.2mm thick-walled filamented glass capillaries
(WPI, Sarasota, FL)] were back-filled with 3 M KCl to yield resistances of 0.5 -3 MΩ.
All electrophysiological recordings were conducted within a chamber that contains
a vibration resistant platform that supports an oocyte bath, two micro positioners
(WPI, Sarasota, FL or Narishige International USA, Inc East Meadow, NY) and bath
clamp (Davies et al., 2003). Oocytes were perfused in a 100 μL oocyte bath with
MBS ± drugs via a custom high pressure drug delivery system (Alcott
74
Chromatography, Norcross, GA) at 2 mL/min using 1/16 OD high pressure PEEK
tubing (Upchurch Scientific, Oak Harbor, WA). Oocytes were voltage clamped at a
membrane potential of -70 mV using a Warner Instruments Model OC-725C
(Hamden, CT) oocyte clamp. A chart recorder (Barnstead/Thermolyne, Dubuque,
IA) continuously plotted the clamped currents. The peak currents were measured
and used in data analysis. All experiments were performed at room temperature
(20-23°C).

Application of Agonist - For agonist concentration response experiments, WT or
mutant GlyRs or GABA ARs were exposed to
1 μM – 3 mM glycine or 1 μM – 10 mM GABA for 60 sec, using 5-15 min washouts
between applications to ensure complete receptor resensitization.

Application of Ethanol - We used a concentration of glycine or GABA producing 10
± 2% of the maximal effect (EC 10). Agonist EC 10 was applied as a control pre- and
post-ethanol treatment. When testing ethanol potentiation, the oocytes were
preincubated with ethanol for 60 sec prior to co-application of ethanol and agonist
for 60 sec (Davies et al., 2004). Washout periods (5-15 min) were allowed between
agonist and drug applications to ensure complete resensitization of receptors. WT
and mutant α1GlyR responses were measured across an ethanol concentration
range of 1-30 mM. GABA AR responses were measured across an ethanol
75
concentration range of 1-50 mM. Ethanol, in the absence of glycine or GABA, did not
significantly affect the holding currents of the GlyRs and GABA ARs tested.

Application of Antagonists and Modulators - Zinc chloride: Oocytes expressing
WT, δL2 and γL2 GlyRs were tested for response to low (10 μM) and high (100 μM)
concentrations of zinc chloride (ZnCl 2), a bimodal allosteric modulator of the GlyR.
Glycine EC 10 was applied for 60 sec. Oocytes were preincubated with ZnCl 2 60 sec
followed by co-application with glycine EC 10 for 60 sec. Washout periods (5-15 min)
were
allowed between drug applications to ensure complete resensitization of receptors
Strychnine and Picrotoxin: Oocytes expressing WT, δL2 and γL2 GlyRs were tested
for response to the competitive GlyR antagonist strychnine or the non-competitive
GlyR antagonist picrotoxin. Glycine EC 10 was applied for 60 sec. Oocytes were
preincubated with strychnine (50 nM) or picrotoxin (100 μM) for 60 sec followed by
co-application with glycine EC 10 for 60 sec. Washout periods (5-15 min) were
allowed between drug applications to ensure complete resensitization of receptors.
Diazepam - Oocytes expressing WT and δL2 GABA ARs were tested for response to
the benzodiazepine agonist diazepam. GABA EC 10 was applied for 60 sec. Oocytes
were preincubated with diazepam (1 μM) for 60 sec followed by co-application with
GABA EC 10 for 60 sec. Washout periods (5-15 min) were allowed between drug
applications to ensure complete resensitization of receptors.

76
Cell-Surface Biotinylation and Immunoblotting Biotinylation of surface-
expressed proteins was modified from a previous protocol published by Cheng and
co-workers (Chen et al., 2005). Four days after cDNA injections, oocytes (15 oocytes
per group) were incubated with 1.5 mg/mL membrane-impermeable Sulfo-NHS-SS-
biotin (Pierce Biotechnology, Rockford, IL) for 30 min at room temperature. After
washing once with 25 mM Tris (pH 8.0) and twice with Phosphate Buffered Saline
(PBS), oocytes were homogenized in 500 μL of lysis buffer [40 mM Tris (pH 7.5),
110 mM NaCl, 4 mM EDTA, 0.08% Triton X-100, 1% protease inhibitor cocktail
(Vector Laboratories, Burlingame, CA)]. The yolk and cellular debris were removed
by centrifugation at 3600g for 10 min. Aliquots of the supernatant were mixed with
2X Sodium Dodecyl Sulphate (SDS) loading buffer and stored at -20˚C to assess total
receptor fraction. The remaining supernatant was incubated with streptavidin
beads (Pierce Biotechnology) overnight at 4˚C. Beads were washed three times with
lysis buffer and the biotinylated proteins eluted by heating at 95 °C for 10 min in
SDS loading buffer. The surface and total proteins were separated using SDS-PAGE
and transferred to polyvinylidene fluoride membranes. The membranes were
incubated overnight with rabbit anti-GlyR antibody (1:500 dilution, Chemicon
International, Temecula, CA), followed by incubation with the appropriate
horseradish peroxidase-conjugated secondary antibody. Protein bands were
visualized using enhanced chemiluminescence (Pierce Biotechnology). The blots
were then scanned and analyzed to obtain images.
77
Molecular Modeling - Models of the WT and δL2 mutant GlyRs were built using
Discovery Studio 2.1 (Accelrys, San Diego, CA). The GlyR and the mutant sequence
with the δGABA Loop 2 were aligned with the 'Align multiple sequences' module, a
derivative of ClustalW. To ensure compatibility with the literature, a two step
procedure was used to test the alignments; First, we used the alignment of α1GlyR
with α1nAChR suggested by Sixma and co-workers (Brejc et al., 2001). Second, we
used the alignment of α1nAChR with GLIC suggested by Changeux and co-workers
(Bocquet et al., 2007;Bocquet et al., 2009). The resulting alignment of GlyR with
GLIC proved to be correct (Table 4.1). We then submitted the two alignments to the
‘Modeler’ module with the restriction that the cys-loop cysteine disulfide bond
(Cys138-Cys152) should be preserved. For each alignment, 10 initial models were
produced and then each of these was subjected to loop refinement to yield a total of
50 models for WT and mutant receptors. The 'best' model for each alignment was
selected based on total force field (PDF) energy. Then each model was further
refined with the ‘Loop refinement' module. At this point a harmonic restraint of 10
kcal/(mol A
2
) was applied to all backbone atoms of the homopentamers and this
restraint was maintained for all the following steps. Both models were optimized to
a gradient of 0.0001 kcal/Å in Discovery Studio with a conjugate gradient algorithm
using the Accelrys version of the CHARMm force field and the default spherical
nonbond cutoff of 14 Å. Then the models were relaxed with 50,000 one femtosecond
steps of molecular dynamics at 300 K. Finally, the models were optimized again as
described above. The WT and mutated models had final potential energies of -
78
88,054 and -88,487, respectively. These values indicate that the models are stable.
However, due to the extensive changes in amino acids, they cannot be compared to
say which model is more stable. In both models, inter-subunit and intra-subunit
interactions of residues in Loop 2 were detected with two methods; first, the H-bond
detection module was enabled. Second, all residues within 5 Å of any atom in Loop 2
were selected and manually examined.
Data Analysis - Data for each experiment were obtained from 4-8 oocytes from at
least two different frogs. The n refers to the number of oocytes tested. Results are
expressed as mean ± SEM. Where no error bars are shown, they are smaller than
the symbols. We used Prism (GraphPAD Software, San Diego, CA) to perform curve
fitting and statistical analyses. Agonist concentration response data were analyzed
using non-linear regression analysis: [I = I max [A]
nH
/ ([A]
nH
+ EC 50
nH
)] where I is the
peak current recorded following application of a range of agonist concentrations, [A];
I max is the estimated maximum current; EC 50 is the glycine concentration required for a
half-maximal response and n H is the Hill slope. Data were subjected to Student’s t-
tests, one- or two-way Analysis of Variance (ANOVA) with Dunnett’s multiple
comparison or Bonferroni post tests when warranted. To determine the threshold
concentration at which a significant effect of ethanol was first detected in WT and
mutant receptors, we compared the absolute values of agonist induced chloride
currents in the presence and absence of ethanol across ethanol concentrations using
two-way ANOVA followed by Bonferroni post-tests. Statistical significance was
defined as p < 0.05.
79

RESULTS
Agonist Concentration Response
GlyRs: Glycine produced inward Cl
-
currents in WT and mutant GlyRs in a
concentration-dependent manner (Figure 4.1). There were no significant
differences between WT and mutant GlyRs in glycine I max or Hill slope (Table 4.2).
FIGURE 4.1

Figure 4.1. Concentration-response curves for glycine (1-3,000 µM) activated chloride
currents in Xenopus oocytes expressing WT, δ δ δ δL2 and γ γ γ γL2 α α α α1GlyR subunits. Glycine induced
chloride currents were normalized to the maximal current activated by a saturating concentration of
glycine (300 μM - 3 mM). The curves represent non-linear regression analysis of the glycine
concentration responses in the Loop 2 mutant GlyRs compared to WT α1GlyRs. Details of EC 50, I max
and Hill slope are provided in Table 2. Each data point represents the mean ± SEM.

The δL2 mutation but not the γL2 mutation caused a significant reduction in EC 50 in
these receptors compared to WT α1GlyRs.

80
TABLE 4.2
Receptor I max(nA) Hill slope (n H) EC 50 (mM)
α α α α1WT 9000 ± ± ± ± 1620 1.735 ± ± ± ± 0.5 171.962 ± ± ± ± 58
α α α α1δ δ δ δL2 8612 ± ± ± ± 2314 2.685 ± ± ± ± 0.6 14.615± ± ± ± 4 *
α α α α1γ γ γ γL2 8795 ± ± ± ± 2600 1.405 ± ± ± ± 0.1 196.2 ± ± ± ± 18

Table 4.2. Summary of non-linear regression analysis results for glycine concentration
responses in WT, δ δ δ δL2 and γ γ γ γL2 mutant α α α α1GlyRs. Glycine EC 50, Hill slope (n H), and maximal current
amplitude (I max) are presented as mean ± SEM. One-way ANOVA revealed no significant differences
between WT and δL2 GlyRs in I max or Hill Slope. EC 50 in the δL2 GlyRs was significantly reduced
compared to α1WT GlyRs.

Cell-surface biotinylation followed by immunoblotting analysis did not show
a significant difference between cell-surface biotinylated fraction or total expression
of GlyR protein between WT and any of the mutant GlyRs tested (Figure 4.2). This
suggests that the differences in EC 50 of WT vs. δL2 GlyRs do not reflect differences in
surface expression levels due to receptor internalization.

FIGURE 4. 2

Figure 4.2. Western blot analysis of total and cell surface protein from Xenopus oocytes
expressing WT, δ δ δ δL2 and γ γ γ γL2 α α α α1GlyR subunits. Western blot analysis revealed no differences
between WT and mutant GlyRs with respect to total cell lysates and cell surface biotinylated
fractions. Results shown are for 1 ng of WT or mutant GlyR cDNA injected into each oocyte.
Immunoprecipitates were run on SDS-PAGE gel, then transferred to PVDF membrane. Blots were
then probed with rabbit antibody against the α1 subunit of the human GlyR.

81
GABA ARs: GABA produced Inward Cl
-
currents in WT and mutant GABA ARs in a
concentration-dependent manner (Figure 4.3).
FIGURE 4.3

Figure 4.3. Concentration-response curves for GABA (1-10,000 μ μ μ μM) activated chloride
currents in Xenopus oocytes expressing WT and mutant δ δ δ δL2 GABA AR subunits. GABA induced
chloride currents were normalized to the maximal current activated by a saturating concentration of
GABA (10 mM). The curves represent non-linear regression analysis of the GABA concentration
responses in the α1β2γ2(δL2) GABA ARs compared to WT α1β2γ2 GABA ARs. Details of EC 50, I max and
Hill slope are provided in Table 3. Each data point represents the mean ± SEM.

The α1β2γ2(δL2) GABA AR mutation caused a non-significant left-shift in EC 50.
There were no significant differences in I max or Hill slope between WT and mutant
GABA ARs (Table 4.3).
TABLE 4.3
Receptor I max(nA) Hill slope (n H) EC50 (μ μ μ μM)
WTα α α α1β β β β2γ γ γ γ2

5978 ± ± ± ± 2669 1.404 ± ± ± ± 0.2 267.76 ± ± ± ± 63
α α α α1β β β β2γ γ γ γ2(δ δ δ δL2)

3730 ± ± ± ± 1672 1.194 ± ± ± ± 0.2 234.35± ± ± ± 54
Table 4.3. Summary of non-linear regression analysis results for GABA concentration
responses in and mutant GABA ARs. GABA EC 50, Hill slope (n H), and maximal current amplitude
(I max) are presented as mean ± SEM. Student’s t-test revealed no significant differences between WT
and mutant GABA ARs in I max, EC 50 or Hill Slope.
82
Ethanol Concentration Response --- GlyRs: We predicted that mutating the Loop 2
region in α1GlyRs to the homologous residues from the δGABA AR subunit would
increase ethanol sensitivity of α1GlyRs. As predicted, the Loop 2 substitution in
WTα1GlyRs reduced the threshold for ethanol sensitivity from 30 mM in WT GlyRs
to 1mM in the δL2 mutant and increased the degree of ethanol potentiation at all
concentrations tested (Figure 4.4). On the other hand, mutating the Loop 2 region in
α1GlyRs to the homologous residues from γGABA AR did not significantly affect ethanol
sensitivity compared to WT GlyRs. Therefore, changes in ethanol sensitivity caused by
mutating Loop 2 of the α1GlyR to the Loop 2 sequence found in δ and γ GABA AR
subunits respectively, parallel the relative ethanol sensitivities of the GABA ARs from
which the Loop 2 sequence was taken. Overall, these findings support the notion that
the structure of Loop 2 plays a key role in determining ethanol sensitivity in GlyRs.
FIGURE 4.4

Figure 4.4. The δ δ δ δL2 GlyR mutation decreased the threshold for ethanol sensitivity and
increased the degree of ethanol potentiation. Mean ± SEM percent for ethanol potentiation in WT,
δL2 and γL2 GlyRs. Two-way ANOVA followed by Bonferroni post tests revealed that the δL2
mutation reduced the threshold for ethanol sensitivity from 30 mM in WT α1GlyRs (glycine mean
currents = 1013 ± 83 nA versus ethanol mean currents = 1179 ± 121) to 1 mM in δL2 GlyRs (glycine
mean currents = 1050 ± 132 nA versus ethanol 1 mM mean currents = 1351 ± 153 nA) and markedly
increased the magnitude of the response to ethanol compared to WT GlyRs. The γL2 mutation did not
significantly affect receptor response compared to WT GlyRs.
83
GABA ARs: If Loop 2 plays a key role in the ethanol sensitivity of GABA ARs, then
mutating Loop 2 of the γ subunit of α1β2γ2 GABA ARs to the homologous sequence in
the δGABA AR subunit should increase ethanol sensitivity of α1β2γ2 GABA ARs. As
predicted, the δL2 mutation in the γ subunit of GABA ARs shifted the threshold for
ethanol sensitivity from 50 mM in the GABA A γ-δL2 mutant receptor and markedly
increased the magnitude of the ethanol response compared to WT GABA ARs (Figure
4.5). Overall, the results support the notion that the structure of Loop 2 plays a key
role in determining the ethanol sensitivity of GABA ARs.

FIGURE 4.5

Figure 4.5. The δ δ δ δL2 GABA AR mutation decreased the threshold for ethanol sensitivity and
increased ethanol potentiation in GABA ARs. Mean ± SEM percent for ethanol potentiation in WT
and mutant GABA ARs. Two-way ANOVA followed by Bonferroni post tests revealed that the δL2
mutation in the γ subunit of native GABA ARs shifted the threshold for ethanol sensitivity from 50 mM
(GABA mean current = 632.5 ± 11.8 nA versus ethanol mean current = 744 ± 42.6 nA) in WT to 1 mM
(GABA mean current = 499 ± 31.4 nA versus ethanol mean current = 622 ± 19.38 nA) in the GABA A γ-
δL2 mutant receptor and markedly increased the magnitude of the ethanol response compared to WT
GABA ARs.

84
Additional Tests of Receptor Function -- Zinc chloride: Zinc is an allosteric
modulator of the GlyR that modulates the receptor in a bimodal manner.
Submicromolar to micromolar concentrations of ZnCl 2 enhance GlyR function by
acting at a high-affinity Zn
2+
binding site, whereas micromolar concentrations of
ZnCl 2 ≥ 100 μM cause inhibition of GlyR function at a low-affinity Zn
2+
binding site
(Bloomenthal et al., 1994;Laube et al., 1995) In agreement with previous work, low
concentrations of ZnCl 2 (10 μM) enhanced EC 10 glycine-activated currents, whereas
higher concentrations of ZnCl 2 (100 μM) inhibited glycine-activated currents in WT
GlyRs (Figure 4.6). The δL2 mutation did not significantly alter the effects of ZnCl 2
at either concentration tested. 100 μM ZnCl 2 caused a significantly greater
inhibition of glycine-activated currents in the γL2 mutant receptor (Figure 4.6).
FIGURE 4.6

Figure 4.6. The δ δ δ δL2 GlyR mutation did not affect biphasic modulation by Zn
2+
in GlyRs. Zn
2+

allosterically modulated WT, δL2 and γL2 GlyRs in a bimodal manner. 10 μM ZnCl 2 caused
enhancement of glycine-activated currents while 100 μM ZnCl 2 caused inhibition in both WT and
mutant GlyRs. One-way ANOVA followed by Dunnett’s post-tests revealed no significant differences
between WT and δL2 GlyRs with respect to modulation by Zn
2+
at either concentration. The response
to 10 μM ZnCl 2 of γL2 GlyRs did not differ significantly from WT, but the response to 100 μM ZnCl 2
was significantly reduced in these receptors. Data are shown as mean ± SEM percent of control
(where the EC 10 control response is 100%).

85
Strychnine: Strychnine is a competitive antagonist of the glycine binding site in
α1GlyRs (Betz, 1991). In order to test if Loop 2 mutations interfered with
strychnine binding, oocytes expressing WT and Loop 2 mutant GlyRs were tested for
response to 50 nM strychnine. In agreement with previous work (Davies et al.,
2003), strychnine inhibited glycine-activated currents in WT α1GlyRs (Figure 4.7).
The δL2 mutation did not alter the effects of strychnine on these mutant α1GlyRs.
There was a significant increase in strychnine inhibition of glycine-activated
currents in the γL2 mutant receptor.
FIGURE 4.7

Figure 4.7. The δ δ δ δL2 GlyR mutation did not affect inhibition by strychnine in GlyRs. 50 nM
strychnine inhibited WT, δL2 and γL2 α1GlyRs. One-way ANOVA followed by Dunnett’s post-tests
showed no significant difference in the degree of strychnine inhibition between WT and δL2 mutant
GlyRs. In contrast, strychnine inhibited γL2 GlyRs significantly more than WT GlyRs. Data are shown
as mean ± SEM percent of control (where the EC 10 control response is 100%).

Picrotoxin: Picrotoxin is a plant alkaloid convulsant that inhibits homomeric
α1GlyRs with a high potency by blocking the channel pore (Lynch et al., 1995). In
order to test if Loop 2 mutations interfered with the effects of picrotoxin, oocytes
expressing WT and Loop 2 mutant GlyRs were tested for response to 100 μM
86
picrotoxin. Picrotoxin inhibited glycine-activated currents in WT α1GlyRs (Figure
4.8). The δL2 and γ?L2 mutations did not alter the effects of picrotoxin in α1GlyRs.
FIGURE 4.8

Figure 4.8. The δ δ δ δL2 GlyR mutation did not affect inhibition by picrotoxin. Exposure to 100 μM
picrotoxin inhibited EC 10 glycine-activated currents in WT, δL2 and γL2 α1GlyRs. One-way ANOVA
showed no significant effect of mutation on picrotoxin. Data are shown as mean ± SEM percent of
control (where the EC 10 control response is 100%).

Diazepam: Diazepam is the prototypical benzodiazepine agonist and potentiates

the GABA responses through binding to an allosteric modulatory site on the
receptor (Macdonald and Olsen, 1994). In order to test if mutations to the γ subunit
of the GABA AR interfered with the effects of diazepam, oocytes expressing WT and
δL2 mutant GABA ARs were tested for response to 1 μM diazepam. Diazepam
potentiated GABA-activated currents in WT α1β2γ2 GABA ARs (Figure 4.9). The δL2
mutation did not significantly alter the effects of diazepam on the receptor.
Collectively, these findings in GlyR and GABA AR suggest that replacement of
non-conserved residues in Loop 2 with those of δGABA increase ethanol sensitivity
and that these changes in ethanol sensitivity cannot be explained by changes in the
87
basic receptor function. Interestingly, the δL2 mutations did not affect allosteric
modulation by Zn
2+
in GlyRs or by diazepam in GABA ARs, which indicates that the
changes in ethanol sensitivity produced by this mutation does not extend to all
allosteric modulators.
FIGURE 4.9

Figure 4.9. The δ δ δ δL2 GABA AR mutation did not affect sensitivity to diazepam in GABA ARs
Diazepam potentiated EC 10 GABA-activated currents in WT and δL2 mutant GABA ARs. Student’s t-test
showed no significant difference between WT and mutant GABA ARs in potentiation by diazepam.
Data are shown as mean ± SEM percent for diazepam potentiation.

Molecular Modeling of WT vs. δ δ δ δL2 GlyR
The model of the α1GlyR based on the template of the prokaryotic LGIC GLIC (PDB
ID 3EAM) showed that Loop 2 is a tight beta turn (Fig 4.10A). This is an important
point in that the previous best X-ray structure we used as a template for the ligand-
binding domain had a more rounded structure for Loop 2. This template was the
acetylcholine binding protein (AChBP, PDB ID 1I9B) and the differences in Loop
structure are probably due to the AChBP being a water soluble protein with Loop 2
88
facing the aqueous environment, whereas Loop 2 in GlyR is at the relatively
hydrophobic interface of two domains. Another notable feature of this GlyR model is
that Lys276 extends out from the TM2-TM3 linker and makes a salt bridge with
Glu53 in Loop 2 of the adjacent subunit. It is noteworthy that this salt bridge now
extends directly across the inter-subunit cavity.
Three GlyR subunits are shown (Figure 4.10A) in order to emphasize the
inter-subunit interactions that are possible, while specific interactions within Loop
2 are shown in an expanded view of the WT α1GlyR (Figure 4.10B). Here we
consider interactions of GlyR residues 50 to 59 with other residues within Loop 2
and in the β strands surrounding them. Ser50 interacts directly across the top of
Loop 2 and forms an H-bond with Arg59. Ile51 points toward the beta sheet below
whereas Ala52 points more toward the ion pore. In addition, Ala52 is approximately
in the "i" position of a beta turn (Crawford et al., 2008) and Glu53 points away from
the center of the turn and forms a salt bridge with Arg218 in the Pre-TM1 segment
of its subunit and with Lys276 of the neighboring subunit. Thr54 forms an H-bond
with Ser273 in the TM2-TM3 linker and interacts with Phe187. Thr55 interacts
across Loop 2 whereas Met56 points away from Loop 2. Asp57 forms a salt bridge
with Lys104. The backbone "N" and "O" atoms of Tyr58 form reciprocal H-bonds
with the backbone atoms of Leu136. Arg59 interacts with Ser50 and Pro185.

89

FIGURE 4.10

Figure 4.10. Molecular models of WT and δ δ δ δL2 α α α α1GlyRs threaded on GLIC. (A) View of three GlyR
WT subunits from the center of the ion pore. The forward two subunits are not shown for clarity; (B)
Enlarged view of Loop 2 in a single GlyR WT subunit. Residues interacting with Loop 2 are rendered
as colored stick models: Lys104, blue; Leu136, yellow; Arg218, pink, Lys276, green; (C) Enlarged
view of the mutated δ Loop 2 in a single GlyR subunit. Residues interacting with Loop 2 are rendered
as colored stick models like (B).

Although only four of the ten residues in Loop 2 are conserved in the
mutated construct that we made, the global structure of the backbone of Loop 2 is
essentially identical in the GlyR WT (Figure 4.10C) and the δL2 mutant construct
90
(Figure 4.10C). This is remarkable because each of the two sequences was
independently used by the Modeler module of Discovery Studio to build the models.
The "best" of 50 models was selected based on potential energy in the CHARMm
force field, then sidechain positions were adjusted with the auto rotomer module, a
short molecular dynamics run was made, and then the two final structures were re-
optimized. The position of other residues that interact with those in Loop 2 was also
conserved, especially Lys104 and Leu136. Lys276 still projects away from the TM2-
TM3 linker and forms a salt bridge with Glu53 in the adjacent subunit. The most
notable changes are how Arg218 interacts with Glu53 with a much different form of
salt bridge. This change resulted in a small distortion of the pre-TM1 segment
compared to the WT GlyR. As expected, the substitution of Asp57 with glutamate
resulted in a shift of the salt bridge with Lys104 to compensate for the increased
length of the glutamate side chain.

DISCUSSION
The present study tests the hypothesis that the structure of extracellular domain
Loop 2 can markedly affect ethanol sensitivity in both GlyRs and GABA ARs. We
found that replacing Loop 2 of the α1GlyR subunit with that of the δGABA AR subunit,
but not the γGABA AR subunit, reduced the threshold for ethanol sensitivity and
increased the degree of ethanol potentiation without altering the general function of
the receptor. Similarly, replacing the Loop 2 region of the γ subunit of GABA ARs
with the Loop 2 region of δGABA AR shifted the threshold for ethanol sensitivity from
91
50 mM in WT to 1 mM in the GABA AR γ-δL2 mutant. These results indicate that
manipulations of Loop 2 structure can have profound effects on ethanol sensitivity
of these receptors. Given the relatively high structural homology between the cys-
loop superfamily of receptors (Brejc et al., 2001;Castaldo et al., 2004;Wang et al.,
2007;Price et al., 2007), these findings in GlyR and GABA AR could extend to nAChRs
and 5HT 3Rs.
As presented, the δL2 mutations increased ethanol sensitivity without
altering sensitivity of GlyR and GABA AR, respectively, to allosteric modulation by
Zn
2+
and diazepam. Further work is necessary to test other allosteric modulators of
GlyRs and GABA ARs, particularly other general anesthetics like isoflurane, halothane
and propofol (Krasowski and Harrison, 1999;Krasowski and Harrison, 2000;Jenkins et
al., 2001). Nonetheless, the lack of change in sensitivity of δL2 mutant GlyRs and
GABA ARs to the allosteric modulators tested suggests that the changes in ethanol
sensitivity by this mutation do not extend to other allosteric modulators and may be
specific for ethanol or ethanol-like agents.
The mechanism by which mutation of Loop 2 alters ethanol sensitivity in
GlyRs and GABA ARs is unknown. However, the current and previous studies
provide some insights. With one exception, a left shift in glycine EC 50 in the δL2
GlyR, Loop 2 mutations that increased ethanol sensitivity did not alter receptor EC 50,
I max or Hill slope. Similarly the δL2 GABA AR mutation resulted in increased ethanol
sensitivity, without a significant change in GABA sensitivity. Prior studies also
found that mutation of position 52 in Loop 2 could alter ethanol sensitivity in GlyRs
92
without changing EC 50 (Crawford et al., 2007;Perkins et al., 2008). Moreover, the
δL2 mutation in GlyRs did not significantly affect the receptors’ response to
strychnine or picrotoxin. Together, these findings indicate that the increase in
ethanol sensitivity in δL2 mutants cannot be explained by changes in receptor
conformation that alter basic receptor function.
Interestingly, prior studies indicate that ethanol sensitivity in recombinant
α1β2δ GABA ARs expressed in Xenopus oocytes is not increased. Rather, the ethanol
sensitivity of this subunit combination is similar to that seen in WT α1β2γ2
GABA ARs (Sundstrom-Poromaa et al., 2002). Further studies are necessary to
ensure incorporation of the δ subunit in this work. Nonetheless, these findings
suggest that there is an important interaction between α and δ subunits that is
involved in making WT α4β2/3δ and α6β2/3δ GABA ARs highly sensitive to ethanol.
Taken in conjunction with the present results, these findings in α1β2δ GABA ARs also
support the conclusion that the structure of Loop 2 plays a critical role in producing
high ethanol sensitivity in the δL2 mutant GABA ARs, and likely also the δL2 mutant
GlyRs, tested in the present study.
Mutations of Loop 2 structure could alter ethanol sensitivity by changing the
physical-chemical characteristics of the amino acids at key locations and their
interactions within Loop 2 and/or with the TM domain. This notion is supported by
several lines of evidence and by the models described below. Prior studies provide
evidence that position 52 in Loop 2 of the extracellular domain and position 267 in
the TM domain of α1 GlyRs are sites of ethanol action (Crawford et al., 2007;Mihic et
93
al., 1997;Mascia et al., 1996b;Mascia et al., 2000;Davies et al., 2004;Perkins et al.,
2008) and that ethanol causes qualitatively different (position-specific) effects when
acting on these targets (Crawford et al., 2007). Further studies used cysteine
mutations at these positions in combination with PMTS to suggest that these sites
were part of the same ethanol pocket (Crawford et al., 2007). Given that this pocket
contains multiple sites that are capable of producing ethanol effects; we describe the
pocket as an ethanol “action pocket” to distinguish it from classical high affinity
binding sites. Molecular modeling revealed a cavity that extends approximately 28Å
from the Cα atoms of A52 to S267 that could function as this alcohol action pocket
(Crawford et al., 2007). As proposed by these authors, this pocket would be large
enough to hold several ethanol molecules. The estimated 28Å distance between
positions 52 and 267 precludes action by one ethanol molecule on both sites
simultaneously. Hence, the probability that ethanol molecule(s) will be acting on
one or more of these sites at a given moment increases as the ethanol concentration
increases. The net response to ethanol on receptor function will represent the
summation of the actions of ethanol on these potentially independent targets.
Interestingly, further study found that the polarity of the residue at position
52 plays a key role in determining the sensitivity of GlyRs to ethanol (Perkins et al.,
2008). The findings with polarity contrast with the findings at position 267 in the
TM domain, where others found that molecular volume, but not polarity,
significantly affects ethanol sensitivity (Ye et al., 1998). Taken together, these
findings indicate that the physical-chemical parameters at positions in the
94
extracellular and TM domains that modulate ethanol effects and/or initiate ethanol
action in GlyRs are not uniform and may respond to different concentrations of
ethanol.
GABA ARs have not been investigated extensively in this respect, but parallel
studies that implicate the homologous positions in GABA ARs as targets for ethanol
action and modulation combined with the structural homology between GlyRs and
GABA ARs (Mihic et al., 1997;Brejc et al., 2001;Wang et al., 2007;Price et al., 2007)
suggest that the same factors may apply for GABA ARs. Knowledge regarding the
physical-chemical properties that control ethanol sensitivity is key for
understanding the relationship between structure and the actions of ethanol in
receptors and for building molecular models of ethanol’s sites of action.
Several molecular models of LGICs have been developed that have begun to describe
possible pair-wise ionic interactions between critical residues in the extracellular
and TM domains that may contribute to agonist action (Kash et al., 2004b;Castaldo
et al., 2004;Crawford et al., 2008;Dellisanti et al., 2007;Wang et al., 2007;Price et al.,
2007)ff. These studies employed techniques such as charge reversal and cysteine
cross-linking to identify conformational changes in receptor proteins, including
GlyRs and GABA ARs that may be involved in agonist activation or transduction.
Molecular models have been developed that identify putative sites of ethanol action
in GlyRs (Crawford et al., 2007;Cheng et al., 2007;Lobo et al., 2008). However, these
models have not addressed possible molecular mechanisms that initiate, transduce
or modulate the actions of ethanol.
95
Here, we present a molecular model of the GlyR threaded on the X-ray
structure of GLIC. In addition to being the first GlyR model threaded on GLIC, it is
the first model that offers a mechanistic explanation for ethanol’s effects on the GlyR
based on changes in Loop 2 structure. The latter are revealed by juxtaposing the
models derived from threading the WT versus the δL2 GlyR sequences onto GLIC.
The change in conformation as a result of the δL2 substitution in mutant GlyRs
changes the manner in which Arg218 (pre-TM1) interacts with Glu53 (Loop 2) with
a much different form of salt bridge. The delocalized charge of the three partially
positive nitrogen atoms (N-H+ groups) at the guanidinium end of the arginine
sidechain allows it to form a salt bridge with the Glutamate carboxyl group either
straight-on (the longest net distance) or at either side of the Arginine side chain
(shorter net distance and not linear). The result of the δ Loop 2 mutation is to form
the more distorted side-on salt bridge in our modeling. This change causes a small
distortion of the pre-TM1 segment compared to the WT GlyR. Moreover, the δL2
mutant GlyR has a Glutamic acid residue at position 57 in place of the Aspartic acid
found in WT. As expected, the substitution of Asp57 with Glutamate results in a shift
of the salt bridge with Lys104 to compensate for the increased length of the
Glutamate side chain. However, it is unlikely that these are just static changes.
Rather, they would change the ensemble of conformations that may occur during
gating, and may be affected by the presence of alcohol molecules, which could alter
ethanol sensitivity. If valid, this suggests that these dynamic movements are
involved in causing and/or transducing the action of ethanol in Loop 2.
96
Despite the low homology between Loop 2 residues in α1GlyR and δGABA AR,
the global structure of the beta turn is conserved in the chimera, illustrating the
importance of structural homology across the cys-loop superfamily. This suggests
that insights provided by the current model may generalize to GABA ARs and other
members of the superfamily. Two notable differences in the model in Figure 4.10
stand out. First, the side chain of Lys276 extends out from the TM2-3 linker to make
contact with the conserved Glu53 in Loop 2, forming an inter-subunit salt
bridge. This inter-subunit salt bridge has not been observed in previous X-ray or
cryo-electron microscopy structures and is not present in the GLIC template used
for modeling. It is possible that the solvation/ desolvation of this salt bridge is
important for the structural rearrangements that accompany the gating transition
(Honig and Hubbell, 1984). Second, the salt bridge between Arg218 and Glu53 has a
different conformation in the δL2 mutant GlyR. The altered length of this salt bridge
may contribute to the differences in sensitivity to glycine and ethanol. In addition, it
should be noted that the partial negative charges on Glu53, at the tip of the beta turn
in Loop 2, are shared between Arg218 and Lys276. These complicated electrostatic
and steric interactions might be especially sensitive to the presence of ethanol
molecules in the adjacent cavity. These findings exploring the role of Loop 2 and the δ
GABA sequence, exemplify how increasing our knowledge regarding the structures
that can modulate ethanol sensitivity can increase our understanding of the targets for
ethanol and structure-function relationships.
97
GlyRs and GABA ARs are widely held to represent initial targets for ethanol
action that underlie a broad spectrum of ethanol-induced acute and chronic
behavioral effects. Behavioral effects in humans can be detected at blood ethanol
concentrations beginning at approximately 0.03% wt/vol (7mM) (Ogden and
Moskowitz, 2004). The legal limits for alcohol consumption while driving are 0.05%
wt/vol (11 mM) in most European Union countries and 0.08% wt/vol (17 mM) in
the United States (Wallner et al., 2003). A blood alcohol concentration of 0.40%
wt/volume (88 mM) is lethal in fifty percent of the population (Koski et al., 2002).
Therefore, the present studies in recombinant receptors, which identify Loop 2 as a
structure that can modulate ethanol sensitivity across this broad range of
behaviorally and toxicologically relevant concentrations, could provide insight into
the structural bases for individual differences in ethanol sensitivity.
The findings also suggest the exciting possibility that structural modifications
of Loop 2 in GlyR and GABA AR might be used to markedly increase the ethanol
sensitivity in target receptor populations (e.g., specific receptor subtypes or brain
regional populations) in transgenic animals. This approach could result in new tools
for measuring the effects of ethanol on sensitized receptors in which overexpression
of high ethanol sensitivity mutant receptors in neurons will enable us see the effects
of ethanol on these receptors at very low concentrations (~1mM) that should not
elicit responses from endogenous receptors. Hence, we should be able to detect this
effect of ethanol on the neuron without interference from its action on endogenous
receptors. If valid, this would provide an alternative strategy that could be used to
map the specific behavioral effects of ethanol caused by its actions on respective
98
receptor populations. Increased knowledge regarding the initial sites for ethanol
action and the structures that affect sensitivity to ethanol also could provide new
targets for the development of therapeutic agents to prevent or help treat alcohol-
related disorders.
99
CHAPTER 5
OVERALL DISCUSSSION AND CONCLUSIONS

Alcohol is the most abused drug in the world. Although new medications
have been developed, these are few and have not been able to significantly mitigate
the problem. A critical barrier to the development of effective medications to
prevent and treat alcohol-related problems is that we have not known enough about
where and how ethanol acts to identify specific molecular targets for the rational
design of new drugs for the prevention and treatment of alcohol abuse and
dependence.
A major difficulty in identifying the sites of ethanol action and in determining
their roles lies in the physical-chemical nature of ethanol’s mechanism of action.
This physical-chemical mechanism, and resultant lack of high affinity, structure-
activity relationships (SAR) and pharmacological specificity, precludes the classical
approach of using ethanol receptor antagonists to identify the sites and mechanisms
of ethanol action and to establish cause-effect relationships (Lister and Nutt,
1987;Deitrich et al., 1989;Little, 1991;Davies and Alkana, 2001a). The search for
cause-effect relationships for ethanol action on specific targets is further
complicated by the multiple receptors and receptor subunit combinations on which
ethanol is known to act in the brain [e.g., GABA ARs, GlyRs, nAChRs, 5HT3Rs,
NMDARs and P2XRS].
100
Studies included in the current dissertation begin to fill this gap. This work
includes findings that demonstrate that the physical-chemical properties of the
residue at position 52 in extracellular domain Loop 2 can determine sensitivity to
ethanol and pressure antagonism of ethanol. These studies, described in detail in
Chapter 2 (Perkins et al., 2008) found that polarity is the key determinant of
sensitivity to ethanol and pressure antagonism in the extracellular domain. These
findings contrasted with prior findings in the TM domain where molecular volume
determined ethanol sensitivity in GlyRs (Ye et al., 1998). Therefore, these findings
in the extracellular domain were the first to point out that the physical-chemical
parameters underlying the effects of ethanol in the extracellular and TM domains of
GlyRs are not uniform. This notion is consistent with our previous work, which
showed that ethanol modulates the extracellular and TM domains differently (i.e.
negative vs. positive modulation respectively) (Crawford et al., 2007).
We extended the studies in Chapter 2 to test the role of charge at position 52
as an extension of polarity. These studies revealed that while ethanol and pressure
act on the same target (position 52) in Loop 2 of the extracellular domain in GlyRs,
different physical-chemical properties underlie their effects. Specifically, polarity at
all degrees determined sensitivity of GlyRs to pressure antagonism of ethanol. In
contrast, the structure of the residue at position 52 appeared to be the key
determinant of receptor sensitivity to ethanol.
Finally, we found that the structure of Loop 2 can profoundly affect the
ethanol sensitivity of α1GlyRs and of α1β2γ2 GABA ARs. Chapter 4 (Perkins et al.,
101
2009) describes studies wherein we used mutation-induced alterations in ethanol
sensitivity to link structure and function and thus to help identify potential
molecular mechanisms of ethanol action. We established that manipulation of the
structure of Loop 2 can create highly ethanol sensitive mutant GlyRs and GABA ARs
that respond to ethanol concentrations that do not affect WT receptors.
Collectively, this work provides strong evidence that there are sites for
ethanol action in the extracellular domain Loop 2 of GlyRs and GABA ARs. This work
also began to define the three dimensional structures of these targets within the
receptor and the physical-chemical parameters that affect the actions of ethanol on
these targets. These findings represent major advances in our knowledge regarding
the sites and mechanisms of ethanol action in GlyRs and GABA ARs and set the stage
for beginning to translate this information into the development of new therapeutic
agents that can prevent or treat alcohol-related problems.

102
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Abstract (if available)

Abstract Glycine receptors (GlyRs) and gamma-aminobutyric type A receptors (GABA_ARs) are recognized as the primary mediators of neuronal inhibition in the central nervous system (CNS). There is a large body of evidence that implicates GABA_ARs in the behavioral effects of ethanol and building evidence supports the notion that ethanol acting on GlyRs causes at least a subset of its behavioral effects. For several decades, GlyRs and GABA_ARs have been studied at the molecular level for targets for ethanol action. Despite the advances in understanding the effects of ethanol in vivo and in vitro, the precise molecular sites and mechanisms of action for ethanol in ligand-gated ion channels (LGICs) in general, and in GlyRs and GABA_ARs specifically, are just now starting to become understood. The present dissertation focuses on studies we conducted that address this issue using molecular biology, pressure antagonism, electrophysiology and molecular modeling strategies to probe, identify and model the initial molecular sites and mechanisms of ethanol action in GlyRs and GABA_ARs. Specifically, this work focuses on the Loop 2 region in the extracellular domain of GlyRs and GABA_ARs and (1) Provides evidence that position 52 in Loop 2 is a target for ethanol action and antagonism in GlyRs

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Asset Metadata

Creator Perkins, Daya (author)

Core Title The structure of loop 2 is important for agonist and ethanol sensitivity in glycine and GABA Alpha receptors

School School of Pharmacy

Degree Doctor of Philosophy

Degree Program Molecular Pharmacology

Publication Date 05/07/2010

Defense Date 03/18/2010

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag electrophysiology,ethanol,GABA,glycine,molecular models,OAI-PMH Harvest,xenopus oocytes

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Alkana, Ronald L. (committee chair), Brinton, Roberta Diaz (committee member), Davies, Daryl L. (committee member), McKemy, David D. (committee member)

Creator Email dayaperkins@gmail.com,diyer@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m3035

Unique identifier UC189935

Identifier etd-Perkins-3546 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-340212 (legacy record id),usctheses-m3035 (legacy record id)

Legacy Identifier etd-Perkins-3546.pdf

Dmrecord 340212

Document Type Dissertation

Rights Perkins, Daya

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu