ELECTROCHEMICAL INVESTIGATIONS OF DOPAMINE USING
ROTATING DISK ELECTRODE VOLTAMMETRY: STUDY OF
RELEASE AND REUPTAKE KINETICS AND INHIBITION
OF THE NEURONAL DOPAMINE TRANSPORTER
By
Peter Alan Lukus
A dissertation submitted in partial fulfillment
of the requirements for the degree of
DOCTOR OF PHILOSOPHY
WASHINGTON STATE UNIVERSITY
Department of Chemistry
December 2013
To the Faculty of Washington State University:
The members of the Committee appointed to examine the dissertation of
PETER ALAN LUKUS find it satisfactory and recommend that it be accepted.
________________________________________________
Kenneth L. Nash, Ph.D., Chair
________________________________________________
Chulhee Kang, Ph.D.
________________________________________________
Herbert H. Hill, Jr., Ph.D.
________________________________________________
Jaak Panksepp, Ph.D.
ii
ACKNOWLEDGEMENTS
Of all the pieces of this document, writing the acknowledgements may
indeed be the most difficult, because I know if I leave someone out they will
never let me live it down.
To begin, I believe an explanation is necessary. During my 4 th year at
WSU, Dr. James O. Schenk underwent treatment for cancer. Due to various
complications, Dr. Schenk did not survive this battle, and passed away Thursday,
January 31st, 2013. Shortly after Dr. Schenk’s death, I was offered a Scientist
position at Moses Lake Industries, Inc., which I accepted, despite not having
completed my dissertation. Since April of 2013, I have been working for MLI and
working on my dissertation. Due to Dr. Schenk’s death, much of the work he and
I planned to put into this document could not happen.
First and foremost, I’d like to thank my mentor, Dr. Jim Schenk. You were
there for me in times of happiness, sadness, despair, jubilation, discovery, and,
more occasionally than it likely should have been, bar room shenanigans. Your
experiences, both in and out of the laboratory, helped me in ways that I can’t
begin to express, and will never be able to fully repay you for. My only regret is
that you are not here to see the final product of your 4 year investment, which I
only hope you’d be proud of. You taught me that being a good scientist is more
than being in a lab, and that being an intellectual is more than being a good
scientist. Our talks over beer (and wine…and sometimes liquor) were some of
the most enjoyable experiences I had throughout graduate school, and I can only
iii
hope to one day pass on as much knowledge and joy to my own students as you
did to me.
I’d also like to thank the members of my committee, Dr’s. Ken Nash, Herb
Hill, Chulhee Kang, and Jaak Panksepp, for their support throughout my
graduate school career. Dr. Nash, you supported me through several difficult
times, and I can’t thank you enough for the help and focus you gave me through
these last few months. To Dr. Panksepp, thank you for helping me see through
the traditional paradigms of science, to question everything, and most
importantly, teaching me that there is no proof, there is only the weight of
evidence. And to Dr. Kang, apart from sharing with me your wealth of knowledge
on subjects ranging from plants to rice wine, you also showed me that an
autoclave can be used to cook a pork roast, which may be one of the most
incredible things I learned in graduate school.
To my undergraduate advisor Dr. Donald Zapien, thank you for pushing
me as hard as you did, and for helping instill in me the drive and determination
needed to be a successful scientist.
To my friends Adam Barden and Robert Hayes, I owe my sanity and much
of my success to you. You are better friends than I could have ever hoped for,
and our early morning coffees, late night talks, and various random guitar
sessions are some of my fondest memories of graduate school. I am honored to
call you my friends. To Meg and Julian, you both brought joy to my life in times
of hardship. Meeting you both was one of the best things that has happened to
iv
me, and I thank you for dealing with my increased bouts of insanity and stress
this past year.
To my brother Michael and my sister Jessica, you supported me through
all of this without question, and where there for me when I needed you, even with
the 3 hour time difference. To my surrogate brothers Jake and Stuck, we’ve
been through hell and back together, and I thank you for being with me through
everything that has come my way.
Last, but certainly not least, I’d like to thank my parents. To my father
Gordon and my mother Cheryl, you’ve done and continue to do more for me than
I deserve, and more than for which I could ever repay. You gave me strength,
courage, love, determination, and support, no matter the circumstances. I have
you to thank for my entire career, past, present, and future, and I love you both
more than words could possibly convey. My only hope is that I’ve made you as
proud to call me your son, as I am to call you my parents.
I thank you all for being there for me, and for supporting me through this
entire ordeal. I am eternally grateful.
v
ELECTROCHEMICAL INVESTIGATIONS OF DOPAMINE USING
ROTATING DISK ELECTRODE VOLTAMMETRY: STUDY OF
RELEASE AND REUPTAKE KINETICS AND INHIBITION
OF THE NEURONAL DOPAMINE TRANSPORTER
Abstract
By
Peter A. Lukus, Ph.D.
Washington State University
December, 2013
Chair: James O. Schenk and Kenneth L. Nash
The dopamine transporter (DAT) is the neuronal transporter for the
neurotransmitter dopamine (DA). The use of rotating disk electrode voltammetry
(RDEV) is a technique used to study transport of DA by DAT. This can be done
in normal tissue, as well as tissue samples that have received pharmacological
manipulation, such as the addition of the DAT uptake inhibitors cocaine and
methamphetamine (METH). In Chapter Two, the rates of exogenous uptake of
DA via DAT in rat striatal tissue is studied. Studies are conducted in whole
striatal samples, as well as in anterior and posterior sections of striatal tissue to
assess variability in DAT function as a function of DA concentration. It is found
that the kinetic rates of transport in exogenous tissue vary between anterior and
vi
posterior sections, as does the rate of reuptake after stimulation of DA release
via KCl addition. Release and reuptake rates of anterior and posterior striatum
vary, suggesting that DAT is not kinetically regulated by available local DA
concentrations.
Chapter Three details studies on the differences of release and
subsequent reuptake of DA via DAT in response to METH and amphetamine
(AMPH) stimulation. A comparison of the amount of DA released, as well as
release and reuptake rates, is presented. Findings suggest that AMPH
stimulation causes a similar concentration of DA to be released in comparison to
METH, while METH caused greater reduction of DA uptake. AMPH salts such as
Ritalin are common medications for children with ADHD, and alternative
therapeutic measures for ADHD management are discussed.
Chapter Four presents analysis of DAT function in hooded rats afflicted
with Parkinson’s symptoms. Transport rates of exogenous DA uptake, as well as
stimulated DA release and subsequent reuptake, are measured. DAT kinetic
function is shown to be retained in Parkinson’s rats, suggesting that the
transporter is unaffected by the disease in the striatal tissue.
Chapter Five presents a brief overview of the work discussed, along with
conclusions and future work.
vii
TABLE OF CONTENTS
Page
ACKNOWLEDGEMENTS……………………………………………………………...iii
ABSTRACT……………………………………………………………………………...vi
LIST OF TABLES……………………………………………………………………….xi
LIST OF FIGURES…………………....……………………………………………….xii
DEDICATION…………………………………………………………………………..xiv
CHAPTER
1. INTRODUCTION TO ELECTROCHEMICAL INVESTIGATIONS OF
DOPAMINE AND THE DOPAMINE TRANSPORTER…….......………………..1
ABSTRACT……………………………….......……....…………………2
INTRODUCTION……………………………………...………………...3
DOPAMINE LOCALIZATION………………....……...………………..3
DOPAMINE AND DOPAMINE BIOSYNTHESIS………....………….5
DOPAMINE PATHWAYS……………....……...………....…………..10
MESOLIMBIC DOPAMINE SYSTEM/SEEKING
SYSTEM.........................................................................................11
DOPAMINE TRANSPORTER……….......……....…………………..11
COCAINE…………………...…………....…………………………….16
AMPHETAMINE AND METHAMPHETAMINE……....……………..16
ELECTROCHEMISTRY IN BRAIN SYSTEMS…….......…………..19
CHRONOAMPEROMETRY……………….......……………………..20
viii
CYCLIC VOLTAMMETRY……....……...….......…………………….22
CARBON ELECTRODES…….......…………...........……....……….24
ROTATING DISK ELECTRODE
VOLTAMMETRY............................................................................25
NEUROANALYTICAL ELECTROCHEMISTRY..............……….…27
CONCLUSION……....…....……………….......………………………38
REFERENCES………………………......…….......…………............39
2. DIFFERENCES IN THE ANATOMICAL FUNCTIONALITY OF THE
DOPAMINE TRANSPORTER IN RAT STRIATUM IN VITRO USING
ROTATING DISK ELECTRODE VOLTAMMETRY………………………….....47
ABSTRACT…………………....…………………………………….....48
INTRODUCTION……....……....………………………………….......49
MATERIALS AND METHODS………....………………………….....53
RESULTS………........…....…………....……………………..…........59
DISCUSSION…....………....……………………………………….....65
CONCLUSION……........………………………………………….......72
REFERENCES………............……………………………………......75
3. VOLTAMMETRIC ANALYSIS OF AMPHETAMINE AND
METHAMPHETAMINE INDUCED DOPAMINE RELEASE AND
REUPTAKE IN RAT STRIATUM: A KINETIC COMPARISON……....…....….80
ABSTRACT……………….....………………………………………....81
INTRODUCTION…………....…………....……………………….......82
ix
MATERIALS AND METHODS…...........….....………………….......86
RESULTS……………..………….....………………………...............89
DISCUSSION…………………………………………....………….....89
CONCLUSION....……...……………………………………………....98
REFERENCES…………….......………………………………….....100
4. RELEASE AND REUPTAKE KINETICS OF THE DOPAMINE
TRANSPORTER IN PARKINSONIAN RATS……....………………………....104
ABSTRACT………………………....………………………………...105
INTRODUCTION……………...........………………………………..106
MATERIALS AND METHODS………....……....………...………...112
RESULTS…………....……………....……………...………………..117
DISCUSSION……………………....………………....……………...117
CONCLUSION………....…....……...………………………………..125
REFERENCES…….......…………....…………………………….....126
5. CONCLUSION………....…………...…....……………………………………....130
x
LIST OF TABLES
CHAPTER 2
TABLE 1. Comparison of DAT uptake velocities in rat striatal tissue……61
TABLE 2. Rate constants of stimulated DA release and reuptake……….71
TABLE 3. DA concentrations available for release in striatal tissue……..73
xi
LIST OF FIGURES
CHAPTER 1
FIGURE 1.
Chemical structure of dopamine………....………….......…....4
FIGURE 2.
Dopamine distribution in the rat caudate…....………………..6
FIGURE 3.
Dopamine biosynthesis……………....………...……........…...8
FIGURE 4.
Dopamine transport mechanism………………....……………9
FIGURE 5.
Dopaminergic pathways in the brain….......…....…………...12
FIGURE 6.
Neuronal transporter for dopamine……...………....………..14
FIGURE 7.
Kinetic mechanism for dopamine transport...........…………15
FIGURE 8.
Chemical structure of cocaine....…...………...........………..17
FIGURE 9.
Chemical structures of amphetamine and
Methamphetamine.......…………………………………….….18
FIGURE 10. Chronoamperometric waveform and response........…….…21
FIGURE 11. Cyclic voltammogram............……………………......……….23
FIGURE 12. Experimental setup for RDEV…........………………………..28
FIGURE 13. Chronoamperometric response of dopamine
release.................................................................................29
FIGURE 14. Dopamine release in response to amphetamine.................31
FIGURE 15. Dopamine release in presence of cocaine..................…….32
FIGURE 16. Chemical structure of methylphenidate..........……..............34
FIGURE 17. Dopamine transport in presence of cocaine…......….....…..35
FIGURE 18. Dopamine release in response to reward cues...........…….37
xii
CHAPTER 2
FIGURE 1.
Dopamine distribution in rat caudate…………………..........50
FIGURE 2.
Experimental setup of RDEV…………………………...........55
FIGURE 3.
Kinetic analysis of dopamine release and reuptake
data......................................................................................58
FIGURE 4.
Electrochemical response of stimulated dopamine
release.................................................................................60
FIGURE 5.
Comparison of dopamine uptake rates in
rat striatal tissue..................................................................62
CHAPTER 3
FIGURE 1.
Chemical structures of amphetamine and
methamphetamine……….......………………………………..83
FIGURE 2.
Amphetamine stimulated dopamine release…........…….....90
FIGURE 3.
Release and reuptake rate constants of amphetamine
and methamphetamine stimulated dopamine release……..91
FIGURE 4.
Average concentrations of amphetamine and
methamphetamine stimulated dopamine release....…….....92
CHAPTER 4
FIGURE 1.
Chemical structure of L-DOPA..................……....…......…108
FIGURE 2.
Experimental setup for RDEV........…...……...………........111
FIGURE 3.
Saggital brain section showing areas of experimental
Interest...…………....…...……........……………....…..........113
FIGURE 4.
Kinetic analysis of dopamine release and reuptake rate
xiii
constants....................………………….…………....………116
FIGURE 5.
Exogenous dopamine reuptake rates…....…...…………...119
FIGURE 6.
Dopamine release rate constants....…………………….....120
FIGURE 7.
Dopamine uptake rate constants....……………………......121
xiv
This document is dedicated to my mother Cheryl, and to my father Gordon.
Thank you for your love and inspiration.
xv
CHAPTER 1
Introduction to Electrochemical Investigations of Dopamine and the
Dopamine Transporter
Peter A. Lukus1 and James O. Schenk1,2
1
Department of Chemistry and 2Programs in Pharmacology/Toxicology and
Neuroscience, Washington State University, Pullman, Washington, 99164.
1
Abstract: Electrochemistry has been used for the past 40 years in various
chemistry and neuroscience laboratories to study the structure and function of
neurotransmitters. The following chapter is intended to introduce the use of
electrochemistry for looking at neurotransmitters in rat brain tissue, and more
specifically for the use of looking at dopamine and dopamine transporter
functionality. Basic electrochemical and neuroscience concepts relating to this
work will be discussed, as well as past and current work in the area, including
key contributors to the field.
2
Introduction
Since the 1950’s, dopamine(DA), shown in Figure 1, has been at the
forefront of a multitude of discoveries involving human and animal physiology,
namely neurophysiology. As much as our understanding of this molecule and its
functions has grown over the past 60 years, our knowledge of complex
interactions that occur between DA and other molecules and structures in the
brain is still vastly incomplete. Furthermore, knowledge of the effects of drugs of
abuse on the function and transport of DA is still growing, and the study of how
DA is transported can, and has, had profound effects on the scientific community.
Electrochemistry has become a powerful tool to help narrow the gaps in our
knowledge of neurotransmitter function, and this opening chapter will serve as
both an introduction as well as a review of dopamine, as well as the
electrochemical methods used to detect it. The majority of this chapter will
explain the function of dopamine and how electrochemistry has been used to
study it’s structure and functions, mainly in the realm of drugs of abuse such as
methamphetamine (METH) and cocaine, but also with diseases such as
Parkinson’s and Huntington’s Chorea, both neurodegenerative diseases that can
be traced to DA imbalances in the brain.
Dopamine localization
Dopamine (DA) is one of over one hundred known neurotransmitters in
the brain, and is found in the A8, A9, and A10 regions of the brain(1). Along with
acting as a precursor norepinephrine(NE), DA is highly innervated in the areas of
brain controlling movement, motivation, addiction, reasoning, and behavior (2).
3
Figure 1. Chemical structure of dopamine.
4
As mentioned, the regions of the brain containing the highest
concentrations of DA are the A8, A9, and A10 regions, which include the
substantia nigra (SN), the caudate and putamen, which are collectively referred
to as the striatum in the rat brain, the nucleus accumbens (NAc), the ventral
tegmental area (VTA), the olfactory tubercles (OT), the prefrontal cortex (PFC),
the subthalamic nucleus (STN), and the central nucleus of the amygdala (CNA),
with many other structures containing varying levels of DA. Not only do the
concentrations of DA vary between anatomical structures, but also within the
same anatomical structure. Figure 2 shows studies done by Milby et al (3),
indicating that the concentration of DA actually decreases as you move from
anterior to posterior in the rat striatum. Questions have been asked as to
whether or not DAT follows a similar gradient. Additionally, it is unclear as to
whether DAT function follows this gradient. In this context, DAT function refers to
the kinetic rate of transport of DA via DAT. Expression of functional DAT may or
may not follow this gradient, which will be discussed shortly.
Dopamine biosynthesis and metabolism
DA synthesis begins with the amino acid tyrosine, a non-essential amino
acid which functions both as a proteinogenic molecule, as well as functionally in
signal transduction processes (4). DA is then converted to Ldihydroxyphenylalanine (L-DOPA) via tyrosine hydroxylase. L-DOPA is the main
precursor to DA, and is used mainly as a treatment for Parkinson’s disease,
where death of dopaminergic cell bodies severely compromises movement, as it
is able to cross the blood-brain barrier and be metabolized into DA (5). L-DOPA
5
Figure 3. Concentration gradient of DA in the rat caudate. Figure
taken from Milby et al.
Figure 2. Concentration gradient of DA in the rat caudate. Figure
taken from Milby et al.
6
is then converted to DA via L-aromatic amino acid decarboxylase, or DOPA
decarboxylase. Figure 3 gives a description of DA biosynthesis. The fate of DA
depends both on the needs of the body, as well as the location in which it is
synthesized. Some DA will be converted to norepinephrine (NE), which will
subsequently be converted to epinephrine (EPI), i.e. adrenaline. Another portion
will be stored in vesicles for future use, being released as needed by the body.
DA release is calcium-dependent, and is the result of action potentials, which are
electrical signals that result due to a concentration gradient formed across the
cell membrane, acting on the nerve terminal. Upon this action potential, DA is
released into the synapse, the space between the neuron releasing DA and the
neuron receiving DA, where it acts upon DA receptors found on the dendritic
extensions of the receiving neuron. Interaction of DA with DA-specific receptors
signals secondary messengers in the receiving neuron to send a signal down the
axon to another area of the brain, where the signal is received and a function is
performed. A diagram of the synapse and corresponding interaction of DA with
its receptors is shown in Figure 4.
Upon interaction with its receptor, the fate of DA is two-fold; it is either
metabolized via monoamine oxidase (MAO) and aldehyde dehydrogenase to
dihydroxyphenylacetic acid (DOPAC), or it can be metabolized to homovanillic
acid (HVA) via catechol-o-methyl transferase (COMT) and MAO. In rats, DOPAC
is the main metabolite, whereas in humans it is HVA. The second fate
isrecycling of DA via the dopamine transporter (DAT) and subsequent storage
7
Figure 4. Dopamine biosynthesis from tyrosine. Norepinepherine and
epinepherine biosynthesis are also shown.
8
Figure 5. Dopamine transport mechanism. A presynaptic action potential causes a
release of dopamine from neuronal storage vesicles. Dopamine is then transported to the
synapse, where it binds to dopamine receptors and is transported back to the cell via
DAT.
9
of DA into dopaminergic storage vesicles. DAT binds free DA in the synapse and
returns it to the neuron, where it can then be metabolized or restored, depending
on the needs of the cell. These mechanisms are targets of many drugs such as
buproprion (antidepressant), haloperidol (antipsychotic), cocaine, and
methamphetamine.
Dopamine Pathways
To understand neural connections through which DA travels, it DA
pathways are generally split into three categories: 1) Ultrashort systems are
dopaminergic systems which make extremely localized connections, such as
linking the inner and outer plexiform layers of the retina, as well as connections
within the olfactory bulb, which is where the sensory perception of smell is
processed in the brain. 2) Intermediate length systems are slightly longer than
the ultrashort systems, and connect areas such as the dorsal and posterior
hypothalamus with the dorsal anterior hypothalamus, which, among other things,
helps regulate connection between the nervous system and the endocrine
system via the pituitary gland, and 3) Long systems are neural projections
linking areas such as the ventral tegmental area and substantia nigra with the
neostriatum and frontal cortex. These are the connections that form what is often
referred to as the “reward pathway” in the brain. A more correct term would be
an “appetitive motivational system”, or a SEEKING system, such as that
described by Panksepp (6). This system serves not only as a reinforcement
pathway, but also as a motivational pathway to seek out various rewards, both
10
natural (food, water, sex, etc.) and synthetic (methamphetamine, cocaine). This
system will be discussed in greater detail below.
Mesolimbic dopamine system/SEEKING system
The mesolimbic DA system of the brain connects the ventral tegmental
area (VTA) of the midbrain to the limbic system via the nucleus accumbens
(NAc) and amygdala, and the hippocampus, as well as to the prefrontal cortex
(PFC)(7). The system is shown in Figure 5. While the system is involved in
reward, it is also involved in all things that motivate humans, making it an
appetitive motivational system, or a SEEKING system as termed by Panksepp
(6). The mesolimbic system is responsible for reinforcing all behavior, from
finding food and water, to copulation, to drug seeking behavior. DA disturbances
in this system are also involved in depression (8) and schizophrenia (9), with DA
imbalances thought to be one of the leading causes of such neurological
diseases. Altered DA transport in this region of the brain is also thought to be the
“motivating factor” in drug seeking behavior.
Dopamine Transporter
The neuronal dopamine transporter (DAT) is a Na+ and Cl- dependent
transmembrane transporter that functions to end dopaminergic
neurotransmission by clearing it from the synaptic cleft (10). As discussed
previously, upon release in the brain DA interacts with dopaminergic receptors on
the post-synaptic cell, after which it is either taken back up by DAT into the presynaptic cell, where it is either metabolized or stored in neuronal vesicles for
future use.
11
Figure 6. Dopaminergic pathways in the human brain. Serotonin pathways are
also shown.
12
The DAT is a 619-amino acid protein with 12 putative hydrophobic
membrane-spanning domains. A depiction of the transporter is shown in Figure
6. Molecular characterization and cloning of rat, bovine, and human DATs have
shown that these proteins are highly conserved between species with similar
orientation in the plasma membrane and potential sites of glycosylation and
phosphorylation. DAT function and inhibition may play a role in Parkinson’s
disease (11), Tourette’s syndrome (9), and attention deficit hyperactivity disorder
(12). As previously discussed, it is also a target for drugs of abuse such as
METH and cocaine, as well as therapeutic agents such as methylphenidate (13,
14, 15). The kinetic mechanisms of the DAT will be discussed briefly; however
they have been described in detail by Schenk and Wightman (16). A depiction of
typical DAT kinetic schemes is shown in Figure 7, taken from Jones et al,
showing both normal DA binding kinetic as well as binding kinetics in the
presence of a DA analog, such as amphetamine (AMPH). Na+ and Cl- bind first,
followed by DA. The order in which Na+ and Cl- bind has been debated (17, 18),
however it has been shown that this binding is absolutely essential, otherwise
transport does not occur (19). In the case of DA analogs, such as AMPH and
METH, competitive inhibition occurs. Due to the similar structures of METH,
AMPH, and DA, both transport inhibition and vesicle displacement occur.
Inhibition of the transporter via cocaine, and displacement and inhibition via
METH are mechanisms that cause the “high” described by users, due to the
excess of DA that becomes trapped in the synapse. This DA is then free to
continually bind to receptors.
13
Figure 7. Depiction of the neuronal transporter for DA.
14
Figure 8. Kinetic mechanism of DA transport under normal conditions, as well as in the
presence of a transport inhibitor such as amphetamine (Ao). Taken from Jones et al.
15
Cocaine
Cocaine is a powerful, short-acting central nervous system (CNS)
stimulant (20). The structure is shown in Figure 8. The main action of cocaine
has been found to be inhibition of the DA transporter via allosteric binding, in
which cocaine blocks the ability of Na+ to bind to the transporter (21), essentially
replacing Na+ as the binding moiety. Since Na+ binds to DAT before Cl-,
followed by the binding of DA, the ability of the DAT to reuptake DA is inhibited.
This results in DA remaining in the synapse for an extended period of time,
where it binds repeatedly to dopaminergic receptors. This in turn stimulates the
mesolimbic DA system, and results in a rewarding and pleasurable feeling for the
user, a.k.a. the euphoric high often described. The effects of cocaine typically
last between 5 and 20 minutes depending on dosage and purity of the sample,
and the tolerance of the user (22). The speed of metabolism of the drug often
causes users to “chase” the high, resulting in large amounts of the drug being
administered over a very short period of time, which can result in cardiac
complications. In addition, physical and chemical dependence will develop if this
behavior persists over a long period, though the time it takes to reach a
dependent state varies between users.
Amphetamine and methamphetamine
Methampetamine (METH) is, as the same suggests, methylated
amphetamine. The structures of both METH and amphetamine are shown in
Figure 9. While amphetamine (AMPH) has found several clinical uses, including
treatment for ADHD and narcolepsy (23), the uses of METH have been mainly
16
Figure 9. Chemical structure of cocaine.
17
Figure 10. Chemical structures of amphetamine and
methamphetamine.
18
recreational drug use. Like cocaine, METH is a CNS stimulant, however its
mechanism of inhibition of DAT is markedly different, while causing similar,
though longer lasting, affects. Unlike cocaine, METH is a substrate analog of
DA, and when administered, is taken up by DAT into the cell. METH displaces
DA, which is stored in neuronal vesicles, and causes the transporter to reverse
directions via an increased concentration of DA in the cell (25). Upon release,
DA binds to DA receptors repeatedly, causing the euphoric “high” described by
users. Effects of a METH dose typically last from 10 to 12 hours (26). METH is
protected from degradation via MAO by the attached methyl group, allowing it to
remain in the neuronal vesicles and cytosol longer. A main metabolite of METH
is amphetamine, which may also be a factor in the length of time the effects of
METH last in users. As with cocaine abuse, physical and chemical dependence
result, and neurological and cardiac complications are typical in METH abusers
(27).
Electrochemistry in brain systems
For the majority of scientists, up until the 1970’s, electrochemistry was
used mainly as a tool for detection and analysis of analytes in aqueous solutions.
Many chemists were drawn to electrochemistry mainly for its sensitivity and,
when done correctly, selectivity of many electroactive species. The use of
electrochemistry strictly for analytical and physical chemistry applications
changed in the 1970’s with the work of Adams, who published a great number of
papers in the time period regarding electrochemical detection of
neurotransmitters in the brain (28, 29, 30). Adams found that many
19
neurotransmitters, such as DA, NE, and serotonin (5-HT), are electroactive, and
are easily detectable using electrochemical methods. Furthermore, the
development of carbon fiber microelectrodes for use in brain tissue gave
researchers a tool which could be used to probe brain chemistry without
damaging the tissue, something that was not possible before. Two of the most
popular methods used to detect neurotransmitters in brain tissue have been
chronoamperometry and cyclic voltammetry.
Chronoamperometry
Chronoamperometry is an electrochemical technique in which a constant
potential, or potential step, is applied to the electrode, and the resulting current is
measured as a function of time. The shape of the current response can be
predicted using equation 1, known as the Cottrell equation
Eq. 1
i=nFACOD1/2/(πt)1/2
where i is the current, n is the number of electrons transferred, A is the area of
the electrode in cm2, CO is the concentration of the oxidized species, D1/2 is the
diffusion coefficient of the oxidized species in cm2/s, and t is the time in seconds.
The data is obtained via a current vs. time curve, called a chronoamperogram.
This can be done in either one or two “steps”. A single step measures only the
oxidation or reduction of a species, while two steps, known as double potential
step chronoamperometry, measures both the oxidation and reduction of the
species. An example of the resulting signal is shown in Figure 10. The figure
20
Figure 11. Chronoamperometric excitation waveform and resulting current
response.
21
shows both the potential excitationsignal, i.e. the potential step, as well as the
resulting current response, which in this case is a double potential step
chronoamperogram. Chronoamperometry can give information about electrode
area, diffusion properties, and redox potentials of molecules of interest. The
latter, however, can be difficult to ascertain using chronoamperometry alone, and
specificity is difficult to achieve with chronoamperometry alone. Typically, the
redox potentials of the molecules of interest are determined before
chronoamperometric techniques are used. Despite this limitation,
chronoamperometry is extremely useful in research pertaining to transport and
diffusion of molecules from a point source, which in this case would be the
working electrode. Carbon-fiber microelectrodes are used by many labs (31, 32,
33) for chronoamperometric measurements in brain tissue, due to increased
sensitivity and specificity given. In the effort to determine the redox potentials of
the molecules of interest, or to kinetically resolve multiple species of interest in
the same solution or anatomical area, cyclic voltammetry becomes incredibly
useful.
Cyclic Voltammetry
Cyclic voltammetry is a technique in which a current is measured in
response to a varying potential. The resulting curve, called a cyclic
voltammogram, is a plot of current as a function of varying potential. An example
of such a curve is shown in Figure 11. Cyclic voltammetry differs from
chronoamperometry in that a cyclic voltammogram is a current that results from a
potential scan over a particular range, i.e. a ramping waveform, whereas
22
Figure 12. Current vs. Potential response of a cyclic
voltammetric experiment.
23
chronoamperometry is a single potential applied throughout the entire
experiment. The attraction of cyclic voltammetry to scientists is due to its relative
simplicity and the wealth of information that can be obtained by the
voltammograms given. Information on redox potentials, electron transfer
mechanisms, peak height, peak width, and more can be obtained via a cyclic
voltammogram. Additionally, cyclic voltammograms serve as a type of fingerprint
for a molecule, allowing investigators to know exactly what type of molecules
they are looking at, which is especially useful for areas of the brain that contain
multiple electroactive species, such as the prefrontal cortex. The redox
characteristics, and thus the cyclic voltammograms, of most molecules are
unique, therefore it is an incredibly powerful analytical tool. In the event that
molecules of interest have similar redox potentials, variations in scan rate can be
used to kinetically resolve redox systems.
Carbon Electrodes
Of the various types of electrode materials used to investigate
electrochemical phenomena, carbon is by far one of the most popular. Several
reasons exist for this popularity. Carbon is inexpensive and available in a variety
of forms. Carbon also oxidizes very slowly, allowing a wide potential range to be
examined, and giving carbon a significant advantage over materials such as
mercury and platinum, whose background signals at oxidative potentials are
often overwhelming, and little to no analytical information can be obtained from
these. Glassy carbon and carbon fiber electrodes are two commonly used
variations of carbon solid electrodes, and the use of carbon fiber microelectrodes
24
in brain tissue was one of the biggest contributions to the beginnings of
neuroanalytical electrochemistry. Glassy carbon is also used frequently in
neuroanalytical applications, due to its wide potential range, low resistance, and
inertness. While carbon fibers are typically used for in vivo analysis due to their
small size, glassy carbon is more frequently used for in vitro analysis. Carbon is
amenable to all types of electrochemistry, and has become a fundamental tool in
many analytical chemistry and neuroscience laboratories.
Rotating disk electrode voltammetry
RDE voltammetry has been used over the years by this lab (34) and
others (35) to produce kinetically resolved voltammograms of DAT transport in
vitro. An electrode is connected to a metal shaft and covered in Teflon, creating
a planar diffusion surface. Upon rotation of the electrode, solution is transported
to the surface of the electrode orthogonally, and upon brief interaction with the
electrode surface is then radially swept away from the electrode and back into
the bulk solution. RDE voltammetry is typically done at a single potential step,
and the current is then observed as a function of time. The maximum current
response at the electrode occurs when the rate of oxidized species being swept
away from the electrode is equal to the amount arriving at the electrode surface,
a condition known as the limiting current, which is described mathematically
using equation 2, which is known as the Levich equation,
Eq. 2
iL=0.62nFACD2/3υ-1/6ω1/2
25
where iL is the limiting current, n is the number of electrons transferred, F is the
Faraday constant (96,485 C/mol), A is the area of the electrode in cm 2, C is the
concentration of the solution, D is the diffusion coefficient in cm 2/s, υ is the
kinematic viscosity of the fluid in cm2/s, and ω is the angular velocity of the disk,
where ω=2πN, and N is in rotations per second. RDE voltammetry provides
several advantages over other in vitro and in vivo methods, being fast enough to
provide a kinetically resolved image (20ms response time is orders of magnitude
faster than the time in which DA transport occurs) while also being sensitive
enough to measure small quantities of tissue (in this lab, average whole striatal
tissue sample weighs 45-50mg, while anterior and posterior sections weigh on
average 20-25mg each). RDE voltammetry, as its name suggests, uses a
rotating, disk shaped electrode, in which forced convection to the electrode
surface is the dominant force acting on the solution. This allows for controlled
diffusion, allowing the electroactive species to reach and be measured by the
electrode, as opposed to an electrode in a static solution, which relies on the
speed of mass transport diffusion to the electrode surface. Glassy carbon
electrodes are the electrode of choice of this lab for the reasons stated in the
previous section. The biggest disadvantage to this technique is that it cannot be
done in vivo, however for transport studies, it is often advantageous to use RDEV
as a complementary method, and to be able to obtain kinetically resolved
information concerning the species of interest. For biological samples, a
physiological buffer is used as the electrolyte, while a stream of 95% O 2/5% CO2
26
is applied across the top of the solution during the experiment, shown in Figure
12.
Neuroanalytical Electrochemistry
The field of neuroanalytical electrochemistry, as stated previously, started
with the work of Ralph Adams in the early 1970’s. Due to Adam’s work,
electrochemistry has gone from a tool that was used strictly by chemists to a tool
that has widespread use in biology, pharmacology, and neuroscience labs.
While a detailed foray into every area that electrochemistry is used is beyond the
scope of this chapter, neuroscience research has profited greatly from the use of
electrochemistry, especially in areas such as addiction research.
DA is one of the most frequently studied neurotransmitters, and the role of
DA in addiction pathways, as well as several other pathways of the brain, has
been found to be more complex than originally thought. It has long been known
that DA is one of the main neurotransmitters involved with addiction, and
electrochemical methods have been used to elucidate many of the mechanisms
involved. Early studies done by Adams group at the University of Kansas
showed that not only could neurotransmitters such as DA, NE, and EPI be
detected via electrochemical measurements (36, 37), but also that release of DA
in the striatum could be elicited by drug administration. The subsequent release
of DA could be monitored in vivo via carbon-fiber microelectrodes (38), as shown
in Figure 13. Adams further influenced the field by applying other analytical
techniques to the study of brain function, namely chromatography. Adams was
one of the first scientists to couple chromatography to electrochemical detection.
27
Figure 13. Experimental setup for use of RDEV to probe neuronal transport
mechanisms.
28
Figure 14. Chronoamperometric measurements of DA release upon
stimulation of neuronal tissue by KCl. Taken from Adams et al.
29
Adams frequently used this technique to separate and identify various
neurotransmitters in rat brain tissue (39).
While Adams was the first to apply electrochemistry to the field of
neuroscience, many since have advanced the field in tremendous ways via their
many discoveries. Francois Ganon made several contributions to the field, and
along with Adams was among the first to use carbon-fiber microelectrodes to
investigate electrochemical phenomena in brain tissue. He has also made
contributions to addiction research, and was involved in the discovery that AMPH
not only blocks DA transport, but is also involved in DA vesicular release (40).
Figure 14 shows voltammetric and amperometric data of the difference in DA
release between normal striatal tissue, and that which has been dosed with
AMPH. As can be seen, a higher response, in the case of the naïve tissue,
indicates a greater amount of DA present, as current response is proportional to
concentration of analyte in the system.
Chemist’s such as Mark Wightman have made extensive progress in the
field, making discoveries in primates about the effects of reward delivery on pH,
oxygen, and DA (41), while also making significant strides in the effects of
cocaine on dopaminergic systems (42). Figure 15, taken from Venton et al (42),
shows the difference in release of DA with and without cocaine injections in wildtype and knockout mice, which are lacking in synapsin I/II/III. Synapsins are
phosphoproteins which serve to modulate reserve pools of neurotransmitters, or
30
Figure 15. Release of striatal DA in brain slices via stimulation by KCl
(control) and amphetamine. Measurements were made using
chronoamperometry with carbon fiber microelectrodes. Taken from
Schmitz et al.
31
Figure 16. DA release pre (left) and post (right) cocaine injection.
Curves are traces from cyclic voltammograms. WT=wild type,
TKO=knockout.
32
DA in this case. As shown in Figure 15, DA reserve pools are significantly
depleted in the knockout mice. Cyclic voltammetry and chronoamperometry
were used to validate the existence of DA, as well as to measure release
concentrations from synaptic pools. Andrew Ewing has done more work than
anyone else in studying dopaminergic function in drosophila melanogaster (43),
showing that DA transport and inhibition behave similarly to that of rats and
primates, thus proving the efficacy of the model, as well as providing a more cost
efficient means of an animal model for testing. Furthermore, Ewing was able to
show evidence that methylphenidate (structure shown in Figure 16) may block
binding of cocaine to the DAT (44), thus potentially providing an additional
therapeutic benefit of methylphenidate.
The Schenk lab has provided many contributions as well. Schenk’s lab
has focused mainly on DAT kinetics, and binding of DA to DAT for transport.
Schenk has looked at both rat (45) DAT function, as well as human DAT function
expressed in HEK cells (46). Figure 17 shows exogenous addition plots of DA
uptake under control conditions, as well as in the presence of cocaine, no Na +,
and 5mM Cl-. As discussed earlier, DAT is a Na+/Cl- dependent transporter, and
varying the concentrations of Na+ and Cl- was shown to greatly affect uptake,
especially in the case of Na+. While the exact order of the 2 Na+ and 2 Cl- ions
needed to bind has been debated, these results have shown that at least one Na
+
ion must bind in order for uptake to occur at any appreciable rate, while
lowering Cl- concentration affects transport to a lesser degree. Also shown in
Figure 17 is the comparison of rates of uptake of the response curves. As
33
Figure 17. Chemical structure of methylphenidate.
34
Figure 18. Inhibition of DA transport in the presence
of cocaine, in the absence of Na+, and under
lowered Cl- concentrations. The top figure shows
raw current vs. time responses of tissue samples to
the pharmacological manipulations. Taken from
Earles et al.
35
expected, control samples have the highest rate of uptake, while eliminating Na +
and introducing cocaine to the solution severely reduces uptake. In addition to
the data shown here, the Schenk group has recently developed models
suggesting that while the concentration of DA differs anatomically in certain parts
of the brain, the rate of transport via DAT does not rely on this gradient, and
furthermore DAT kinetically fluctuates, suggesting that there is much more to be
discovered regarding the intricacies of DA transport via DAT, both under normal
physiological conditions, as well as under the influence of DAT inhibitors such as
cocaine and methamphetamine.
Researchers such as Paul EM Phillips at the University of Washington
have also been making progress in DA research using electrochemical methods.
Phillip’s group has recently looked at DA activity in response to escalating cost of
effort in rats (47). Figure 18 shows results from recordings taken in the core of
the NAc, an area which is thought to be heavily involved in motivation response,
along with the NAc shell. Rats were presented with a reward in the form of a
food pellet, and the number of lever presses required to access this reward
varied. DA release was monitored using fast-scan cyclic voltammetry. Results
indicate that the level of effort given towards a given reward depend on the value
seen in the reward, which can be measured by measuring DA responses to
reward cues. Additionally, results suggest that DA responses to the reward and
the indicator of the reward can be differentiated in the NAc, and that DA
responses can also be differentiated via escalating cost of the reward. Additional
research done by Phillips’s group (48) has also shown, using fast-scan cyclic
36
Figure 19. DA release and reuptake in response to varying reward cues.
Taken from Wanat et al.
37
voltammetry, that over time, DA response to Pavlovian cues begins to resemble
baseline scans. This indicates that, while initially rewarding, the cues to
Pavlovian conditioning become less rewarding, i.e. less DA is released, as the
cue is given over time. This has profound implications in motivation research,
especially in regards to drug seeking behavior. The rewarding nature of certain
actions, such as drug use, becomes less and less in terms of DA release as the
behavior is repeated, requiring more, or sometimes different, cues to illicit the
same response expected by the user. This gives further explanation to drug
seeking behavior, as well as the phenomena of chemical dependence.
Conclusion
As stated earlier, the purpose of this review was not to be exhaustive in
nature, nor was it intended to give the entire overview of addiction research using
analytical methods. There are certainly more analytical tools that have become
extremely useful in addiction research, and neuroscience in general, and
electrochemistry is only one of them. Other methods include MALDI, NMR, mass
spectrometry, and chromatography, and all have found their usefulness in many
fields of neurobiology and neuroscience. Likewise, electrochemistry has found
its niche as well, and with advances being made every day, it will likely continue
to help scientists made breakthroughs in several fields for years to come.
38
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46
CHAPTER TWO
Differences in Anatomical Functionality of the Dopamine Transporter in Rat
Striatum In Vitro Using Rotating Disk Electrode Voltammetry
1
Peter A. Lukus and 1,2,*James O. Schenk
1
Department of Chemistry and 2Programs in Pharmacology/Toxicology and
Neuroscience, Washington State University, Pullman, Washington, 99164.
Preface: The following chapter is formatted for submission to the Journal of
Neurochemistry. All research in this chapter was done by Peter A. Lukus, with
equipment and lab space provided by Dr. James O. Schenk.
47
Abstract
The dopamine transporter (DAT) is responsible for the reuptake of dopamine
(DA) in the striatum, as well as other areas of the brain. Through examination of
immunohistochemical data, high concentrations of DAT have been shown in the
anterior, but not posterior, portions of the striatum. Functionality of DAT in these
areas has yet to be explored. In this study, anterior and posterior striatal
sections were dissected and analyzed electrochemically using rotating disk
electrode (RDE) voltammetry. Kinetic analyses were done to measure and
compare DA uptake velocities, as well as release and reuptake rate constants
and initial concentrations of available DA in each section, with average in vitro
uptake rates being 31% greater in anterior vs. posterior striatal tissue. Left
striatal tissue showed a much smaller disparity when compared to right, with right
anterior tissue showing a 32% increase in uptake velocity vs. posterior,
compared to only an 8% disparity between left anterior and posterior tissue. This
result suggests a greater role for left posterior DAT in striatal function with
regards to DA, as well as the possibility of laterality contributions. The DAT
inhibitor cocaine, as well as the selective serotonin reuptake inhibitor (SSRI)
citalopram, has been used to gauge the effect of the serotonin transporter
(SERT) on DA uptake. Cocaine treatments led to approximately 30-50% DAT
inhibition, while citalopram showed statistically insignificant effects on DAT
activity. Lastly, K+ stimulation of DA showed much higher concentrations of DA
in anterior vs. posterior sections, indicating DAT functionality may be dependent
on extracellular DA concentrations, rather than vesicular storage concentrations.
48
Introduction
The neurotransmitter dopamine(DA) is one of over a hundred known
neurotransmitters, and is prevalent in various areas of the brain, including the
striatum, substantia nigra, olfactory tubercles, nucleus accumbens, and medial
prefrontal cortex (Cooper et al, 2002). Along with acting as a precursor to
norepinephrine (NE), DA is highly innervated in the areas of the brain controlling
movement, reward, and motivation, and fluctuations in the level of DA available
to bind to DA receptors in these areas leads to massive changes in behavior
(Pesek-Cotton et al, 2011). The nigrostriatal and mesocorticolimbic dopamine
pathways are two pathways (three if the mesolimbic and mesocortical pathways
are considered separately) with major contributions to addictive behaviors,
stemming from the effects of drugs like cocaine on DA transport, as well as their
effects on neuronal plasticity (Thomas et al, 2008).
High concentrations of DA are found in these anatomical areas, especially in the
striatum and substantia nigra. Milby and coworkers (Milby et al, 1982) through
examination of posterior tissue, found that the concentration of DA decreases
from anterior to posterior in the rat caudate. Results are shown in Figure 1. As
can be seen, there is a marked decrease in DA concentration in the posterior
caudate, with a 54% decrease being seen from anterior to posterior. Typically,
areas with high concentrations of DA were assumed to have the most DAT, and
thereby the most DAT functionality. The word “functionality”, as used in this
context, refers to the activity of the transporter in a certain region, i.e. how fast
and to what degree it responds to the presence of DA natively, as well as in the
49
Figure 1. Dopamine distribution in the rat caudate. Distances on
the x-axis refer to mm from bregma.
50
presence of drugs of abuse, specifically, in this case, cocaine.
The neuronal transporter for dopamine, known as the dopamine transporter
(DAT), is a seven-transmembrane spanning protein (Schenk, 2002) consisting of
619 amino acids. It is a member of the Na+ and Cl- dependent family of
transporters (Amara and Kuhar, 1993). When DA is released from vesicular
storage into the synapse, it binds to receptors and autoreceptors alike, and is
subsequently taken up by DAT and transported back into the presynaptic space,
released, and then metabolized into DOPAC or homovanillic acid(HVA). Once
DA is released, DAT then returns to the synapse to begin the process again. It
has long been thought that areas with high intracellular concentrations of DA not
only have more DAT, but that DAT has higher functionality than areas with lower
concentrations of DA. While it has been found that DAT is highly concentrated in
areas with high concentrations of DA , the functionality of the transporter in these
areas has been investigated sparingly (Cline et al, 1995; David et al, 1998).
The psychostimulant cocaine is a known DAT inhibitor, preventing the reuptake
of DA and causing an increase of DA in the synapse, leading to the euphoric
feeling, or “high”, users and abusers tend to experience. The affects on the
functionality of DAT in various anatomical areas has been studied by this lab in
vitro (Meiergerd and Schenk, 1994; Meiergerd et al, 1997; Povlock and Schenk,
1997), however these studies did not investigate differences in DAT function
within the same anatomical area, such as anterior and posterior striatum.
RDE voltammetry has been used over the years by this lab and others (McElvain
and Schenk, 1992; Meiergerd and Schenk, 1994; Earles and Schenk, 1998; Volz
51
and Schenk, 2004; Volz et al, 2004; Zapata and Shippenberg, 2002 ) to produce
kinetically resolved voltammograms of DAT transport in vitro. RDE voltammetry
provides several advantages over other in vitro and in vivo methods, being fast
enough to provide a kinetically resolved image (20 ms response time is orders of
magnitude faster than the time in which DA transport occurs) while also being
sensitive enough to measure small quantities of tissue (average whole striatal
tissue sample weighs 45-50 mg, while anterior and posterior sections weigh on
average 20-25 mg each). RDE voltammetry, as its name suggests, uses a
rotating, disk shaped electrode, in which forced convection to the electrode
surface is the dominant force acting on the solution. This allows for controlled
diffusion, allowing the electroactive species to reach and be measured by the
electrode, as opposed to an electrode in a static solution, which relies on the
speed of mass transport diffusion to the electrode surface (Adams, 1969).
In this laboratory, the current interest is in studying the kinetics of DA uptake via
DAT. Specifically, the aim of this study is to examine DAT functionality in rat
striatum, examining both anterior and posterior striatum. The goal is to
determine whether DAT function correlates to DA concentration in anterior and
posterior striatal tissue. In the case of this study, DAT function will be assessed
through kinetic investigations, measuring uptake and release of DA via DAT.
Using both exogenous DA addition and K+ stimulated release of DA, the
anatomical variability in DAT functionality has been investigated in the anterior
and posterior areas of the striatum. Release and reuptake rates were calculated,
both for cocaine and citalopram inhibited and non-inhibited DAT, along with
52
kinetic rate constants for release and reuptake of DA in K+ stimulated release
models. The Na+ channel blocker tetrodotoxin (TTX) was used to confirm the
anatomical effects of K+ stimulation on voltage-gated Na+ channels.
Materials and Methods
Preparation of Striatal Suspensions and Measurement of Transport by RDE
Brain tissue was prepared as previously described(Bjorklund et al, 2007), with
anterior and posterior dissection described below. Briefly, male Sprague-dawley
rats weighing between 300-450 g were decapitated and their brains rapidly
dissected and placed in oxygenated physiological buffer. Before experimentation
rats were housed 2-4 per cage in a 12-hour light/dark cycle ad libitum to food and
water. Unless otherwise indicated, rats were not treated with drugs before they
were killed. All procedures with animals were reviewed and approved by the
University Laboratory Animal Care and Use Committee. Whole striata(left and
right) were dissected out, with sections being taken from anterior 2700-2400 µm
to posterior 1200-1500 µm(Palkovits and Brownstein, 1988).
For experiments investigating differences in DAT function in the striatum, anterior
and posterior sections of striatal tissue were dissected and analyzed separately.
Anterior portions, on average, measured from anterior 2700-2400 µm to anterior
300 µm(approximately), while posterior portions measured, on average, from
anterior 300 µm or 0 µm(midbrain) to posterior 1200-1500 µm. Striatal sections
were then chopped on an ice-cold watch-glass and placed into an RDE
incubation chamber (Figure 2) in 1250 µL of physiological buffer, homogenized
by pipetting, and then washed with fresh physiological buffer six times. The RDE
53
was then placed into the incubation chamber, and an electrode rotation speed of
2,000 rpm was applied with a Pine Instruments (Grove City, PA, U.S.A.) rotator.
A potential sufficient enough to oxidize and detect dopamine was applied, +0.450
V relative to a Ag/AgCl reference electrode. Potential was applied to the RDE via
a Bioanalytical Systems (West Lafayette, IN, U.S.A.) LC4C potentiostat, and the
current was monitored on a Nicolet Instruments Corp. (Madison, WI, U.S.A.)
model 2090 digital storage oscilloscope. Data points were taken every 50 ms for
2.0 minutes. For experiments involving exogenous addition of DA, the initial
signal, consisting of the background current from the tissue preparation in buffer,
was allowed to reach a baseline, at which point 20 µL of DA was added to the
tissue suspension such that the resulting DA concentration in the suspension
would be 0.5 µM. For experiments involving K+ stimulated release and
subsequent reuptake, the solution of brain tissue and buffer were brought to
baseline, and buffer with elevated KCl was added such that the first addition led
to a 15 mM KCl concentration in the cell, and a second addition led to a 30mM
KCl concentration inside the cell. The resulting signal was plotted as [DA] o vs.
time. Initial release rates were defined as the linear portion of the positive slope
of [DA]o vs. t, while initial reuptake rates were defined as the linear portion of the
negative slope of [DA]o vs. t.
Cocaine and Citalopram
54
Figure 2. Experimental setup for RDEV analysis on rat striatal tissue.
A constant stream of 95% O2 / 5% CO2 was applied across the solution
surface, and water was circulated through the cell jacket at 37 oC.
55
To investigate the effects of DAT and serotonin transporter (SERT) inhibition on
DA uptake, the DAT/SERT/NET inhibitor cocaine and the selective serotonin
reuptake inhibitor citalopram (trademarked as Celexa) were used. Experiments
involving these inhibitors were done in the same manner as the exogenously
added DA experiments described above, with the difference being that a 0.5 µM
solution of cocaine or citalopram was added to the tissue suspension 30 seconds
before the addition of 0.5 µM DA. The resulting signal was analyzed as
previously described.
TTX
Tetrodotoxin was used to show that blockage of Na+ channels will lead to
decreased DA release. A solution of tetrodotoxin was added to the tissue
suspension 30 seconds prior to K+ stimulation, with the final concentration being
0.1 µM in the cell. In experiments measuring exogenous DA reuptake alone and
with an inhibitor present, a solution of DA was added to the tissue suspension
such that the DA concentration inside the cell would be 0.5 µM. For experiments
involving inhibitors, the inhibitor solution was added to tissue suspension 30
seconds before exogenous reuptake was measured, and was added such that
the volume of inhibitor inside the cell would be 0.5 µM, a concentration of which
is at or above the Ki of both cocaine and citalopram (Povlock and Schenk, 1997;
Baeckstroem et al, 1989 ).
Kinetic Analyses
Analysis of uptake velocities was done using GraphPad Prism Version 5.02 (San
Diego, CA), with the uptake velocity being given by the slope of the linear portion
56
of the [DA] vs t graph. DA uptake velocities are normalized for wet striatal tissue
weight, with the final velocity being reported as pmol/g/s. Release and reuptake
rate constants for K+ stimulated release and reuptake were found by plotting the
ln[DA] vs t (Fersht, 1985). The plot, shown in Figure 3, is used for kinetic data
which follows the equation
[DA] = X{exp(-krt) – exp(-kut)} Eq. 1
where [DA] is total DA concentration, kr is the rate constant for the first process
(in this case DA release), ku is the rate constant for the second process (in this
case reuptake of DA), and X = [DA]o ( 1 + 1/k1 – k2), with [DA]o being the initial
concentration of DA, and exp( ) describing a value raised to an exponential
power. Analysis of the resulting curve is explained in Figure 3. [DA]o can be
found by extrapolation of the ln[DA] vs time graph to x=0. This corresponds to
the concentration of DA initially available for release via forced action potential,
and not the total DA concentration present in the entire tissue. A simulation of
the resulting curve was done using Scientist version 2.0 (Salt Lake City, UT).
Solutions and Chemicals
Solutions were prepared in deionized water purified further by a Nanopure Water
Purification System (Barnstead, Dubuque, IA, U.S.A.). Buffer salts, dopamine
HCl, tetrodotoxin, cocaine HCl, and citalopram HBr were obtained from SigmaAldrich Chemical Co.(St. Louis, MO, U.S.A.).
The physiological buffer at pH 7.4 was comprised of 124 mM NaCl, 1.80 mM KCl,
57
Figure 3. Fersht kinetic analysis of DA release and reuptake data. The slope
of the ln[DA] vs. time graph is used to find ku, while lnΔ vs. time is used to find
kr.
58
1.24 mM KH2PO4, 2.50 mM CaCl2, 1.30 mM MgSO4, 26.0 mM NaHCO3, and
10.0 mM glucose and saturated with a gas mixture of 95% O2 and 5% CO2.
Results
K+ Stimulated Endogenous Release and Reuptake of DA
Figure 4 shows the results of K+ stimulated, endogenous DA release and
reuptake in left anterior and posterior striatal sections, while Figure 5 shows
results for right anterior and posterior striatal sections. Little difference was seen
in concentration of DA release between left and right striatum, while DA release
in the anterior striatum was, on average, more than twice that of the posterior
striatum (130 nM anterior vs. 65.8 nM posterior, 15 mM KCl stimulation; 210 nM
anterior vs. 86.0 nM posterior, 30 mM KCl stimulation). For 15 mM KCl
stimulation, average DA uptake velocity in anterior striatum was found to be 12.1
± 1.96 nmol/g/s, while average uptake in posterior striatum was 9.17 ± 1.64
nmol/g/s. For 30 mM KCl stimulation, average anterior uptake was 46.5 ± 2.45
nmol/s/g, while average posterior uptake was 13.9 ± 1.64 nmol/s/g. Also shown
is the effect of tetrodotoxin on DA release, with a 1.0 µM addition of TTX leading
to greater than 50% inhibition. Table 1 shows the kinetic rates of release (k r) and
uptake (ku), using the method adapted from Fersht.
Exogenous Uptake of DA
Figure 5 shows results of exogenous uptake of DA in left and right, anterior and
posterior striatal tissue samples. Right and left striatal samples showed, in
general, no statistically significant differences, although in some cases the right
59
Figure 4. Concentration vs. time graphs of K+ stimulated release and
subsequent reuptake of DA. (A) Right striatal tissue, weight = 43.1mg. (B) Left
striatal tissue, weight = 45.9 mg. (C) Left anterior (solid) vs. posterior (dashed)
striatal tissue, anterior weight = 20.5 mg, posterior weight = 21.0 mg. (D) Right
anterior (solid) vs. posterior (dashed) striatal tissue, anterior weight = 18.7 mg,
posterior weight = 18.0 mg. The first peak represents profile after 15 mM
stimulation, while the second peak represents profile after 30 mM stimulation.
60
Striatal
Exogenous
Endogenous
Endogenous
Endogenous
Section
Addition (0.5
Release &
Release &
Addition in
uM DA)*
Reuptake (15
Reuptake (30
the Presence
mM KCl)**
mM KCl)**
of Citalopram
(0.5 uM DA,
Citalopram)*
Whole
204 ± 25.6
21.0 ± 5.58
47.4 ± 6.19
217 ± 30.2
Anterior
182 ± 8.04
12.1 ± 1.96
46.5 ± 2.45
192 ± 10.5
Posterior
142 ± 4.81
9.17 ± 1.64
13.9 ± 1.64
205 ± 17.8
Table 1. Comparison of DAT uptake velocities with respect to general
anatomical area, method of uptake measured, and while in the presence of no
inhibitor and the SSRI citalopram . Whole striatal sections weighed 35-50 mg on
average, while anterior and posterior sections weighed 17-25 mg. * Indicates
velocity is in units of pmol/gram wet weight/s. ** Indicates velocity is in units of
nmol/gram wet weight/s.
61
Figure 5. Comparison of average DA uptake velocities for
left/right, anterior/posterior striatal tissue. All uptake velocities
were normalized per gram wet tissue weight.
62
striatum showed a faster uptake velocity than the left. Average uptake velocities
in the right striatum were 210 ± 25.7 pmol/s/g, while the left striatum showed 199
± 25.5 pmol/s/g. Average anterior uptake rate of DA by DAT was found to be 182
± 8.04 pmol/g/s, while average posterior uptake was found to be 142 ± 4.81
pmol/g/s. Right anterior striatal average uptake rate was found to be 205 ± 8.77
pmol/g/s, while average right posterior rate was 140 ± 4.50 pmol/g/s. Likewise,
left anterior striatal average uptake rate was found to be 157 ± 7.33 pmol/g/s,
while left posterior average rate was 145 ± 5.12 pmol/g/s, a value which was
much closer to the anterior average than predicted.
Effects Cocaine on DAT Functionality for Exogenous DA Additions
Inhibition of DAT via cocaine showed reduced transport rates of DA. For a 0.5
µM addition of cocaine 30 seconds before addition of 0.5 µM DA to a tissue
sample, an average of 68% inhibition of transport was seen for the anterior
striatum, with average transport rates dropping from 182 ± 8.04 pmol/g/s for noninhibited to 58.9 ± 3.16 pmol/g/s for inhibited DAT. A similar trend was seen in
posterior striatal sections, with an average 64% inhibition observed, as average
transport rates dropped from 142 ± 4.81 pmol/g/s for non-inhibited, to 51.0 ± 2.22
pmol/g/s for inhibited DAT.
Effects of Citalopram on DAT Functionality for Exogenous DA Addition
The SSRI citalopram was used to determine the contribution of SERT to DA
transport in striatal tissue. Average whole striatal DA uptake velocity was 217 ±
30.2 pmol/g/s, with average uptake velocity of left striatum being 234 ± 40.5
pmol/g/s, and average uptake velocity of right striatum being 200 ± 20.0
63
pmol/g/s. Average uptake velocity of anterior striatal sections was found to be
192 ± 10.5 pmol/g/s, while average uptake velocity of posterior sections was
found to be 205 ± 17.8 pmol/g/s.
Kinetic Rate Constants for Endogenous Release and Reuptake
Kinetic rate constants for endogenous release and reuptake of DA were
determined using the method previously described by Fersht. Whole striatal
average ku for 15 mM K+ stimulation was found to be 0.0115 ± 4.39 x 10-4 s-1,
with the average kr being 0.0826 ± 0.00890 s-1. 30mM stimulation of whole
striatal tissue resulted in an average ku of 0.0111 ± 3.12 x 10-4 s-1 and an average
kr of 0.057 ± 0.013 s-1. For 15 mM stimulation, anterior striatal tissue showed an
average ku of 0.00297 ± 1.13 x 10-4 s-1 and a kr of 0.217 ± 0.00715 s-1, while 30
mM stimulation resulted in an average ku of 0.00518 ± 1.02 x 10-4 s-1 and kr of
0.176 ± 0.0121 s-1. Meanwhile, 15mM posterior stimulation resulted in a ku of
0.00244 ± 1.69 x 10-4 s-1 and a kr of 0.188 ± 0.00256 s-1, while 30 mM stimulation
led to a ku of 0.00296 ± 1.68 x 10-4 s-1 and a kr of 0.170 ± 0.00924 s-1.
Extrapolation of the ln[DA] vs. time curve gave average initial values of DA to be
162 and 296 nM for 15 and 30 mM K+ stimulation of whole striatal tissue, while
15 mM stimulation of left and right anterior striatal tissue lead to 166 and 161 nM
[DA]o, respectively, and 30 mM stimulation of left and right anterior tissue lead to
an average of 230 and 323 nM initial concentrations, respectively. 15 mM
stimulation of left and right posterior tissue resulted in initial DA concentrations of
78.4 and 94.8 nM, respectively, while 30 mM stimulation of left and right posterior
64
tissue resulted in an average initial DA concentration of 96.1 and 117 nM,
respectively.
Discussion
DAT functionality was examined in regards to functional differences when taking
into account anatomical variability. In this study, the functional differences of
DAT were investigated, with the main emphasis being on initial uptake velocities
of DA via DAT, and release and reuptake rates via K+ stimulation in anterior and
posterior sections of the rat striatum. The uptake rates of DAT in anterior and
posterior striatum were also examined under the influence of the DAT inhibitor
cocaine and the SSRI citalopram. This lab has done numerous studies
concerning the kinetics of DAT transport in the rat brain (Schenk et al, 2005;
Bjorklund et al, 2007), and kinetics of DA transport in the rat brain have been
studied by other labs as well (Robinson et al, 2005, Volz et al, 2006 ). However,
the kinetics of DA transport, at least in the striatum, is not constant throughout
the whole of the striatum. While DA transport may indeed depend on DA
concentration in the area in question, it is likely that this is not the only factor
involved in the transport rates of DA, and this study has shown that, at least in
the striatum, this is true.
K+ Stimulated Release and Reuptake of Endogenous DA
Induction of an action potential in whole striatal tissue showed release of DA on
average of 104 nM for a 15 mM KCl stimulation, while a 30 mM stimulation
produced an average of 207 nM DA release. Previous work done by this lab has
shown much higher release values in whole tissue, on the order of 600 nM DA
65
for a 30 mM KCl stimulation (McElvain and Schenk, 1992). This difference could
be attributed to an increased number of tissue washes done in the current
experiment (8 washes done in this experiment, 6 done in McElvain and Schenk).
DA release in whole striatal tissue averaged approximately 104 nM DA release
for a 15 mM KCl stimulation, and 207 nM DA release for 30 mM KCl stimulation.
Anterior striatal release exceeds both these values, with average anterior KCl
stimulated release for 15 and 30 mM KCl stimulation being 130 nM and 210 nM,
respectively. The simple explanation is that one anterior sample led to a 175 nM
DA release for 15 mM KCl stimulation, and a 333 nM DA release for 30 mM KCl
stimulation, making the averages of anterior and posterior striatal sections much
higher than they otherwise would be. Indeed, the concentrations released in said
sample were much higher than in other trials of anterior DA release in the
striatum. However, if this data set is removed from the average, the resulting
mean is 115 nM DA release for 15 mM KCl stimulation, and 170 nM DA release
for 30 mM KCl stimulation. Therefore, even with these data points removed, the
average is still above (in the case of 15 mM KCl stimulation), or close to (in the
case of 30 mM KCl stimulation) whole striatal DA release averages. This trend
can be explained by examining the DA concentration gradient seen in the
striatum. Referring to Figure 1, the further anterior one goes in the striatum, the
higher the concentration of DA. Analysis of a whole striatum is likely to yield an
amount of DA that is weighted toward the average amount of DA found between
the highest and lowest concentration barriers of the striatum. Taking an anterior
section of striatal tissue will result, as shown here, in a release of DA consistent
66
with the concentration gradient in Figure 1. This same rationale applies to
posterior striatal sections as well. Average posterior DA release for 15 mM KCl
stimulation was 65.8 nM, while average release for 30 mM stimulation was 86
nM. Average uptake rates for endogenous DA uptake are shown in Table 1. For
15 mM KCl stimulation, whole striatal endogenous uptake rates averaged 21.0 ±
5.58 nmol/g/s, while 30 mM stimulation led to an average of 47.4 ± 6.19 nmol/g/s.
Anterior striatal 15 mM KCl stimulation led to 12.1 ± 1.96 nmol/g/s, while 30 mM
stimulation led to 46.5 ± 2.45 nmol/g/s average velocity. These results once
again suggest that there is a weighted affect on the transport rates of striatal
DAT. Transport rates in the striatum, at least in this case, seem to follow the
concentration gradient of DA found in the striatum. It is also possible that this
gradient causes a dampening effect on whole striatal DAT velocity. A lower
transport velocity in the posterior section of a whole striatum may lower the
overall DAT uptake velocity, whereas separating the anterior from posterior
striatum allows each area to act individually, removing any influences one side
may have on the other; in this case, the posterior striatum’s lower transport rate
may dampen the higher transport rate of the anterior striatum, leading to a
“leveling out” of the overall transport rate. It must be noted that the average
transport rates for anterior striatal tissue were inflated by one test during K+
stimulation. In this one instance, anterior tissue released 175 nM DA upon 15
mM K+ stimulation, resulting in a transport rate of 20.4 ± 2.25 nmol/g/s. 30 mM
stimulation lead to a 333 nM DA release, with DAT transport velocity being 110 ±
1.75 nmol/g/s. However, despite the increase to the average release and
67
reuptake values this sample caused, the average values of anterior DAT
transport still fall close to values for whole striatal transport. Effects of the Na +
channel blocker TTX were also investigated, mainly to ensure that Na+ channels
were in fact responsible for the release of DA via forced action potential by K +
stimulation. Results showed that a small magnitude of release did occur (≈3 nM)
for a 0.1µM addition of TTX, however this release is insignificant compared to
striatal DA release values previously discussed.
Exogenous DA Reuptake
Uptake via exogenous addition of 0.5 µM DA showed little difference between left
and right striatum, with the uptake velocities being statistically indistinguishable.
However, when looking at anterior and posterior sections, a difference between
left and right begins to appear. Right anterior DA uptake velocities, on average,
were found to be 32% higher than right posterior uptake velocities, while left
anterior uptake was only 7.7% higher on average than left posterior uptake.
There are at least two possible explanations for this phenomenon. First, the
dampening effect mentioned earlier may also apply here, however it is also
possible that the posterior portion of the left striatum has much more
functionality, in terms of DA uptake/DAT, than its DA concentration would
indicate. It is possible that this functionality can only become more apparent
when the posterior and anterior sections are separated, allowing each section to
operate independently of the other, which in turn allows for the actual
functionality of the transporter to be exposed, instead of the averaging effect
seen in the whole striatum. A second possible explanation is laterality of DA, or
68
even possibly DAT protein. Laterality in the brain is in no way uncommon
(Samara et al, 2011; Rosel et al, 2002), and if uptake of DA via DAT is, at least
partially, dependent on DA concentration, then laterality of DA would explain the
increase in posterior striatal uptake of DA. However, if either dampening or
laterality is responsible for the trend in DAT functionality seen here, then why
does it not occur in the right striatum? The answer, once again, may be
laterality, however in this particular instance it would be hemispheric laterality.
Perhaps it is possible that the dorsal striatum of the left hemisphere is more
active due to an increased role in decision-making, while the right ventral
striatum dominates in aspects related to the emotions and motivations which go
into that decision-making process. While both whole striatum are fully functional,
separate areas of each hemisphere’s striata are more functional, and this in turn
could possibly lead to many of the effects seen when dopamine systems are
compromised, as happens with those who abuse drugs. It is also possible that
this effect is simply a result of the separation process of the anterior and
posterior striata, though why the effect is only seen in left striata is still left
unexplained.
Effects of Cocaine and Citalopram on Anterior and Posterior Functionality
While the effects of cocaine on striatal DAT functionality have been well
documented by this lab (Meiergerd et al, 1994; Wayment et al, 1998), these
effects have not been studied in anterior and posterior striatum. In general,
anterior striatal uptake velocities decreased by an average of 68% in the
presence of cocaine, while posterior uptake velocities decreased by 65%. Right
69
anterior uptake velocities decreased by 70%, right posterior by 69%, left anterior
by 65%, and left posterior by 67%. Despite differences in exogenous uptake of
DA, the decreases caused by cocaine inhibition of DAT are consistent, and what
would be expected from a 1:1 addition of cocaine and DA (normally 40-50%
inhibition is seen, however anterior and posterior tissue samples are
approximately half the size of normal striatal tissue preps, making increased
inhibition an expected consequence). Effects of the SSRI Citalopram were also
investigated to see how much of an effect SERT may have on DA transport. As
shown in Table 1, Citalopram had very little effect on DA transport. An
interesting consequence of Citalopram addition was the increase in the average
uptake velocities of the left striatum, as well as the increase in average uptake in
posterior striatal tissue. However, the velocities are still statistically the same
despite the increase, and more tests would be needed to determine if a pattern
exists.
Analysis of Kinetic Rate Constants of DA Release and Reuptake
Using the method adapted from Fersht, release and reuptake rates of DA via K +
stimulation were calculated (average constants shown in Table 2). Average
uptake rate constants for whole striata were in most cases twice that of anterior
and posterior uptake constants, while release constants for anterior and posterior
striata were three times higher than whole striata. The rationale for this is that
while 15 and 30 mM K+ stimulations were used for all samples, the way each
sample “sees” the stimulation is different. The effect of a 30 mM stimulation on
70
ku
kr
Whole
Whole
Anterior
Anterior
Posterior
Posterior
(15 mM)
(30 mM)
(15 mM)
(30 mM)
(15 mM)
(30 mM)
0.0115 ±
0.0111 ±
0.00297
0.00518
0.00244
0.00296
4.39 x
3.12 x
± 1.13 x
± 1.02 x
± 1.69 x
± 1.68 x
10-4
10-4
10-4
10-4
10-4
10-4
0.0826 ±
0.057 ±
0.217 ±
0.176 ±
0.188 ±
0.170 ±
0.0089
0.013
0.00715
0.0121
0.00256
0.00924
Table 2. Rate constants for uptake and release of endogenous DA from
stimulated release via K+ addition. All values are in units of s-1.
71
whole striatal tissue (i.e. 45 mg) versus the effect of the same stimulus on
anterior striatal tissue (i.e. 25 mg) will not be the same. The same stimulus for
half the normal sample will result in a “flood” of stimulus into the smaller striatal
tissue, causing a much faster release of all available DA. The same rationale
applies to the posterior rate constants. Average initial concentrations of DA
available for release were calculated from Equation 1 and are shown in Table 3.
Initial DA levels available range from 323 nM for right anterior striatal tissue to 78
nM for left posterior tissue, with 30 mM stimulations having the larger available
release store in each case. Anterior tissue in both left and right samples showed
comparable DA stores to whole tissue, while posterior tissue gave lower values
compared to both whole and anterior tissue, showing the apparent gradient of DA
in the striatum.
Conclusion
The goal of this study was to investigate how DAT uptake of DA differs in
different local anatomical areas of the rat brain, specifically the anterior and
posterior striatum, and what implications any differences may have in the role of
cocaine inhibition of DAT. Velocities of DA transport in anterior striatal tissue
were shown to be comparable, if not higher than, those found in whole striatal
tissue, and posterior velocities fluctuated in a manner that DA concentrations in
those areas would not predict. On average, DA transport rates were lower in the
posterior striatum when compared to the anterior, however this difference was
found to be much less in the left striatum than the right, implying a greater
functionality of posterior striatal DAT in left striatal activities. Laterality may also
72
Whole
Right
Right
Left
Left
Anterior
Posterior
Anterior
Posterior
15mM K+
162
161
94.8
165
78.4
30mM K+
296
323
117
230
96.1
Table 3. Initial theoretical DA concentrations ([DA]o) available for release during
15 and 30 mM K+ stimulation in striatal tissue. The method of analysis is
discussed in Figure 3. All concentrations are in nM.
73
play a role in differences between anterior and posterior DAT uptake, and while
overall the differences may not be immediately clear, a closer look at individual
test samples reveals that laterality plays a larger role in DA concentration and
DAT functionality in the striatum than may have been previously thought.
Inhibition with DAT via addition of cocaine shows that the effects of cocaine are
seen throughout the striatum, and the gap between anterior and posterior uptake
rates becomes much narrower under the influences of cocaine. Using the SSRI
Citalopram, SERT was shown to have a minimal effect on DAT transport in the
striatum, and though increases in DAT transport rates in the left striatum were
seen, further testing would be needed to determine the cause of this. Overall this
study shows that DAT functionality varies in the striatum, and is not necessarily
dependent on DA concentration. Further studies on DAT functionality throughout
the rat brain should be conducted to determine how DAT responds in other areas
of high and low DA concentration, especially in the presence of drugs of abuse
that target DAT, such as cocaine.
74
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Meiergerd, S.M., and Schenk, J.O. (1994) Kinetic evaluation of the commonality
of the sites of action of cocaine and some other structurally similar and dissimilar
inhibitors of the striatal transporter for dopamine. Journal of Neurochemistry, 63,
1683-1692.
Meiergerd, S.M. and Schenk, J.O. (1995) Measurement of the time-resolved
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Meiergerd, S.M., Schenk, J.O., and Sorg, B.A. (1997) Repeated cocaine and
stress increase dopamine clearance in the rat medial prefrontal cortex. Brain
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79
CHAPTER 3
Voltammetric Analysis of Amphetamine & Methamphetamine Induced
Dopamine Release & Reuptake in Rat Striatum: A Kinetic Comparison
Peter A. Lukus1 and James O. Schenk1,2
1
Department of Chemistry and 2Programs in Pharmacology/Toxicology and
Neuroscience Washington State University, Pullman, WA 98837
Preface: The following chapter is written in a format to be submitted to the
journal Synapse. All experiments and data analysis were done by Peter A.
Lukus, with equipment and lab space provided by Dr. James O. Schenk.
80
Abstract
Methamphetamine (METH) & amphetamine (AMPH) are both dopamine (DA)
releasing agents in the brain, and both are dopamine transporter (DAT) blockers.
Though their mechanism of action, along with structure, is similar, METH has
commonly been seen as the more addictive compound due to greater lipid
solubility. However, the addictiveness of METH when compared to AMPH is
quite high, and it is possible, perhaps even likely, that there is more to uncover
when comparing the mechanism of action of these two drugs. The purpose of
this study is to compare, kinetically, the action of METH and AMPH. Through
comparison of release and reuptake constants, coupled with release
concentration, the data suggests that, from a kinetics standpoint, AMPH has an
equal, if not greater affect on DA release levels in rat striatal tissue. Data also
shows that while AMPH has a greater affect on initial release levels of DA, METH
has a greater affect on reuptake of DA, indicating that DA would be exposed to
post-synaptic receptors longer in the presence of METH. Results suggest that
nurturing of vital PLAY circuits in children may be more effective for long-term
treatment of conditions such as ADHD than the typically prescribed medications
such as the AMPH based Adderall.
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Introduction
The neurotransmitter dopamine(DA) is one of over a hundred known
neurotransmitters, and is prevalent in various areas of the brain, including the
striatum, substantia nigra, olfactory tubercles, nucleus accumbens, and medial
prefrontal cortex (1). Along with acting as a precursor to norepinephrine (NE),
DA is highly innervated in the areas of the brain controlling movement, reward,
and motivation, and fluctuations in the level of DA available to bind to DA
receptors in these areas leads to massive changes in behavior (2). The
nigrostriatal and mesocorticolimbic dopamine pathways are two pathways (three
if you consider the mesolimbic and mesocortical pathways separately) with major
contributions to addictive behaviors, stemming from the effects of drugs like
methamphetamine on DA transport, as well as their effects on neuronal plasticity
(3).
Methamphetamine (METH), shown in Figure 1, is one of the most abused
substances among illicit stimulants (4). The addictive properties of METH stem
mainly from two properties: 1) its ability to stimulate dopamine (DA) release, 2) its
ability to inhibit DA reuptake. The initiation of action potentials is responsible for
causing DA release. An action potential is initiated when the concentration of
Na+ and K+ across the cell membrane are altered, causing the opening of ion
channels that allow the flow of ions into and out of the cell. When DA release is
initiated via neuronal action potential, DA exits storage vesicles into the neuronal
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Figure 1. Chemical structures of AMPH and METH
83
cytoplasm and is transported into the synaptic space via the dopamine
transporter (DAT), where it becomes available to bind to dopaminergic receptors
on the post-synaptic membrane. METH is a substrate analog of DA (5),
meaning it resembles DA closely enough to bind to DAT and be transported into
the neuron, where it then displaces DA from its storage vesicles. Once free in
the cytoplasm, the high concentration of DA causes DAT to release DA from
cytoplasm inside the cell to the exterior synapse. Upon release into the synaptic
space, DA is free to bind to DA receptors on the post-synaptic membrane. Due
to the inhibition of DA via METH, as well as the presence of METH in neuronal
storage vesicles, DA stays in the synapse and repeatedly binds to DA receptors,
causing the euphoric high described by users.
Unlike METH, amphetamine (AMPH), also shown in Figure 1, has therapeutic
benefit, although it is also a class of stimulant. AMPH is a stimulant most
commonly used in the treatment of behavioral disorders such as ADHD (6).
AMPH is also commonly used as a “study drug”, with its stimulant affects being
used to allow long periods of focus for students (7). AMPH has a similar
mechanism of action as METH, in that it binds to DAT, displaces vesicular DA
and blocks transport, allowing DA to be released into the synaptic space to bind
to receptors. AMPH is the non-methylated form of METH, and while the
mechanism of action is similar to METH, the effects of AMPH, in terms of degree
of neurological effects of the drug, are markedly less than that of METH (8,9).
The neuronal transporter for dopamine, known as the dopamine transporter
(DAT), is a seven-transmembrane spanning protein (10) consisting of 619 amino
84
acids, and is a member of the Na+ and Cl- dependent family of transporters (11).
When DA is released from vesicular storage into the synapse, it binds to
receptors and autoreceptors alike, and is subsequently taken up by DAT and
transported back into the presynaptic space, released, and then metabolized into
DOPAC or homovanillic acid(HVA). Once DA is released, DAT then returns to
the synapse to begin the process again. While the affects of METH on users is
known to be more profound and long-lasting, the exact mechanism is unknown.
The additional methyl group found on METH is thought to give the molecule
properties that allow for easier diffusion through the blood brain barrier, as well
as make the molecule resistant to metabolic degradation via monoamine oxidase
(MAO).
RDE voltammetry has been used by this lab and others (12-17 ) to produce
kinetically resolved voltammograms of DAT transport in vitro. RDE voltammetry
provides several advantages over other in vitro and in vivo methods, being fast
enough to provide a kinetically resolved image (20 ms response time is orders of
magnitude faster than the time in which DA transport occurs) while also being
sensitive enough to measure small quantities of tissue (average whole striatal
tissue sample weighs 45-50 mg, while anterior and posterior sections weigh on
average 20-25 mg each). To be clear, in this case the term “kinetic resolution” is
meant to indicate the response time of the instrument compared to the time scale
of the physiological process. Uptake occurs on the order of 120 ms, while the
response time of the instrument is 20 ms. RDE voltammetry, as its name
suggests, uses a rotating, disk shaped electrode, in which forced convection to
85
the electrode surface is the dominant force acting on the solution. This allows for
controlled diffusion, allowing the electroactive species to reach and be measured
by the electrode, as opposed to an electrode in a static solution, which relies on
the speed of mass transport diffusion to the electrode surface (18). This allows
analytical measurements to be made faster than the physiological process of DA
transport. This is crucial, due to the fact that once DA enters the cell it is no
longer able to be detected electrochemically.
The efficacy of METH, when compared to AMPH, is thought to be due to the
extra methyl group found on METH. This methylation increases lipid solubility,
allowing more METH to cross the blood brain barrier at a faster rate than AMPH,
resulting in a greater “high”, as well as increased potential for addiction.
Additionally, the extra methyl group is thought to help prevent degradation of
METH via monoamine oxidase (MAO), further adding to the increased high
experienced by the user (9). The goal of this research is to determine whether
differences exist in the kinetics of release and reuptake of DA in the rat striatum
after stimulation with AMPH and METH. In determining rate constants and fitting
these constants to a kinetic model, it is possible to see whether there are
additional mechanisms that lead to the differences in the degree of
psychostimulus experienced by the user. The results will compare not only
kinetic rates of release and reuptake of DA in the presence of AMPH and METH,
but will also show how the concentrations of DA released differ when comparing
AMPH and METH stimulated release.
Materials and Methods
86
Preparation of Striatal Suspensions and Measurement of Transport by RDE
Brain tissue was prepared as previously described (19). Briefly, male Spraguedawley rats weighing between 300-450 g were decapitated and their brains
rapidly dissected and placed in oxygenated physiological buffer. Before
experimentation rats were housed 2-4 per cage in a 12-hour light/dark cycle ad
libitum to food and water. Unless otherwise indicated, rats were not treated with
drugs before they were killed. All procedures with animals were reviewed and
approved by the University Laboratory Animal Care and Use Committee. Whole
striata(left and right) were dissected out, with sections being taken from anterior
2700-2400 µm to posterior 1200-1500 µm, according to Palkovits and Brownstein
(20). Striatal sections were then chopped on an ice-cold watch-glass and placed
into an RDE incubation chamber in 1250 µL of physiological buffer, homogenized
by pipetting, and then washed with fresh physiological buffer six times. The RDE
was then placed into the incubation chamber, and an electrode rotation speed of
2,000 rpm was applied with a Pine Instruments (Grove City, PA, U.S.A.) rotator.
A potential sufficient enough to oxidize and detect dopamine was applied, +0.450
V relative to a Ag/AgCl reference electrode. Potential was applied to the RDE via
a Bioanalytical Systems (West Lafayette, IN, U.S.A.) LC4C potentiostat, and the
current was monitored on a Nicolet Instruments Corp. (Madison, WI, U.S.A.)
model 2090 digital storage oscilloscope.
Amphetamine and Methamphetamine Induced Dopamine Release
In order to stimulate measurable release of DA from striatal suspensions,
concentrations of AMPH and METH were added such that the concentrations
87
inside the electrochemical cell would be 8x the Ki of each molecule (AMPH
Ki=0.6 µM , METH Ki =65 µM, (21)), resulting in an AMPH concentration of 4.8
µM, and a METH concentration of 500 µM. Addition of each drug was made
after the system had reached a stable baseline current, which was done by
applying +0.450 V until a stable baseline was attained. To ensure that DA levels
measured were in fact due to release of DA via Na+ channel flux, 1µM of the Na+
channel blocker tetrodotoxin (TTX) was added to solution to determine if any
measurable release occurred.
Analysis of Release & Reuptake Data
Analysis of release and reuptake data was done using GraphPad Prism Version
5.02 (San Diego, CA). Release and reuptake rate constants for K+ stimulated
release and reuptake were found by plotting the ln[DA] vs t (22). The plot is used
for kinetic data which follows the equation
[DA] = X{exp(-krt) – exp(-kut)} Eq. 1
where [DA] is total DA concentration, kr is the rate constant for the first process
(in this case DA release), ku is the rate constant for the second process (in this
case reuptake of DA), and X = [DA]o ( 1 + 1/k1 – k2), with [DA]o being the initial
concentration of DA, and exp indicating exponentials. Total concentrations of DA
released were found by measuring the maximum current response after
stimulation of the tissue with AMPH or METH. This number was then matched to
a calibration curve of current response vs. DA concentration to find the maximum
release, expressed in nM.
88
Solutions and Chemicals
Solutions were prepared in deionized water purified further by a Nanopure Water
Purification System (Barnstead, Dubuque, IA, U.S.A.). Buffer salts, dopamine
HCl, amphetamine H2SO4, and methamphetamine HCl, were obtained from
Sigma-Aldrich Chemical Co.(St. Louis, MO, U.S.A.).
The physiological buffer at pH 7.4 was comprised of 124mM NaCl, 1.80 mM KCl,
1.24 mM KH2PO4, 2.50 mM CaCl2, 1.30 mM MgSO4, 26.0 mM NaHCO3, and
10.0 mM glucose and saturated with a gas mixture of 95% O2 and 5% CO2.
Results
Figure 2 shows a typical curve seen after injecting striatal tissue suspensions
with AMPH and METH. The initial upward stroke indicates DA release, while the
downward stroke indicates DA reuptake, most of which occurs via the DAT in
striatal tissue. Average Kr for AMPH (n=4) was 0.113 ± 0.00298, while average
Ku was 0.00739 ± 5.10 x 10-4. Average Kr for METH (n=4) was 0.0608 ±
0.00658, while the average Ku was 0.0031875 ± 4.33 x 10-4. The data is shown
in the bar graph in Figure 3. Average release concentrations of DA were also
determined and compared between AMPH and METH stimulations, shown in
Figure 4. Mean DA release from AMPH stimulation was 260 nM, while mean
release from METH stimulation was 213 nM. Upon application of TTX, no
measureable signal was recorded, indicating that the measured signal was that
of DA released from striatal tissue.
Discussion
METH and AMPH effects on DA transport and DAT
89
Figure 2. Stimulated release of DA via amphetamine
administration to rat caudate-putamen tissue.
90
Figure 3. Comparison of uptake and release rate
constants of DA release stimulated by AMPH and METH.
Average (in s-1) Kr for AMPH (n=4) was 0.113 +/0.00298, while average Ku was 0.00739 +/- 5.10 x 10-4.
Average Kr for METH (n=4) was 0.0608 +/- 0.00658,
while the average Ku was 0.0031875 +/- 4.33 x 10-4. All
errors calculated as standard error of the mean.
91
Figure 4. Average concentration of DA released after AMPH
and METH administration. Average after AMPH
administration was 260 nM, while average release after
METH administration was 213 nM.
92
It has long been thought that the reason for the greater addictive potential of
METH over AMPH was due to the added methyl group found on METH, which
results in greater lipid solubility, allowing for quicker transport through the bloodbrain barrier, thus producing a quicker and longer high. The added methyl group
is also thought to delay metabolic degradation of METH via MAO, allowing the
effects to be longer lasting. While this theory indeed holds water, it has yet been
determined to be the only cause, and while this may indeed be the key reason for
the difference in METH and AMPH efficacy, there may also be underlying
mechanisms, kinetic and otherwise, behind this phenomenon. The results of this
study suggest that AMPH has a similar, if not greater, effect on DA release in
striatal tissue when compared to METH. The rate constants calculated from the
release and reuptake data indicate that AMPH has a statistically similar effect on
DA levels in striatal tissue when compared to METH, and in some cases the
amount of DA released from striatal tissue in response to AMPH stimulation was
greater than DA release due to METH; of the four trials conducted to measure
DA release, AMPH stimulation caused a greater release than METH twice, while
once they were equal. Though it is unknown why exactly this occurs, and indeed
more work would need to be done to ensure that this occurs throughout areas of
the brain affected by AMPH and METH, it is possible that AMPH is able to induce
neuronal action potentials more effectively due to greater receptor binding
efficacy, or perhaps via a second messenger system which, at this point, has yet
to be discovered, or an existing one with an additional function. While the rate
constant at which AMPH is released was found to be larger than that of METH,
93
the rate constant for uptake was larger as well, suggesting that METH is more
efficient at inhibiting DA uptake, likely via DAT. Inhibition can also be modulated
by direction of the transporter. While METH and AMPH may indeed be inhibiting
DA transport via competitive binding to active or allosteric sites, such as where
Na+ and Cl- bind, the replacement of DA by METH and AMPH in vesicles also
reverses transport direction of DAT. Inhibition of DAT in the case of DA
displacement in vesicles is likely two-fold, with inhibition occurring directly via
binding of AMPH and METH to DAT, thereby preventing DA from binding, and
reversal of transport direction of the transporter, keeping it in a state of removal
of DA from the cellular cytoplasm. Taking this into account, the mechanistic
differences between AMPH and METH could perhaps be looked at in a simpler
manner, i.e. AMPH has greater affect on the release of DA, while METH is better
at preventing DA from re-entering the cell, resulting in a longer and more
profound “high”. Additionally, the methyl group, which may in fact reduce the rate
of metabolic degradation of METH, may be the factor that enables METH to be a
more potent inhibitor of DAT reuptake, both via binding to DAT and transporter
direction reversal.
Possible effects of METH and AMPH on other neurotransmitter transporters
It is possible that METH has greater binding affinity for other DA transport
systems as well (VMAT, NET), however further studies would need to be done in
order to determine the degree to which METH may be a more effective inhibitor
for DA uptake when compared to AMPH. Studies done here focused solely on
neuronal DAT as a carrier. While DAT is indeed the main carrier of DA in
94
neuronal striatal tissue, there are small amounts of other known transport
systems, such as VMAT, NET, as well as the organic cation transporter (OCT).
Despite this, it is the thought of this group that the data indeed raises interesting
questions as to the addictive properties of AMPH and METH, and how those
properties contribute to the mechanisms of addiction. Additionally, this study
raises questions as to the efficacy of administration of AMPH for neurological
disorders, such as attention deficit disorder (ADD) and attention deficit
hyperactivity disorder (ADHD). Furthermore, while children do show a different
response to AMPH than do adults, it is possible that alternative methods may be
better suited to children (23), as discussed in further detail in the section on play.
Critiques and further experiments
The added methyl group found on METH is also thought to attribute to the
increased potency of the drug, with the methyl group slowing the rate of
degradation of METH via MAO, as well as increasing lipid solubility of METH.
Increased lipid solubility allows for easier diffusion through the blood brain
barrier, meaning that more METH gets into the brain than does AMPH when
taken in the same amount. This study eliminated the blood brain barrier as a
variable, instead introducing both AMPH and METH directly to striatal tissue. In
order to determine how much blood brain barrier permeability affects transport
inhibition, further studies would need to be done. Indeed, the concentrations of
AMPH and METH available to neurons will certainly affect transport to some
degree. Variations in concentrations of AMPH and METH were not investigated
in this study; however, it is known that higher doses of drugs such as AMPH and
95
METH have greater affects on neuronal function. The concentrations of AMPH
and METH added were determined by adding 8x the inhibition constant of AMPH
and METH for DAT. The inhibition constant, or Ki, is a measure of the
concentration of inhibitor needed to produce 50% inhibition. A problem with the
current study is that the Ki values used were not measured directly in this lab. A
more thorough study would need to be done, measuring Ki’s directly, as well as
the affects of varying the concentrations of AMPH and METH added in relation to
the Ki. Despite this flaw, the current study does show that lower concentrations
of AMPH cause larger releases of DA than METH.
Additionally, the degree of dissociation of METH and AMPH that occurs with
regards to the transporter could also be measured. The dissociation constant of
an inhibitor, Ka, is an indication of how much inhibitor remains bound to the
transporter, as opposed to that which is free in solution. In the simplest terms, K a
can be defined by equation 2 shown below.
Ka ={ [A] x [B]}/[AB] Eqn 2.
In terms of this study, [A] would be defined as the concentration of AMPH or
METH, respectively, that is free in solution, and [AB] would be defined as the
concentration of AMPH or METH that remained bound to DAT. The dissociation
constant is a measure of the potency of a binding species, i.e. how much binds.
When measured as a function of time, Ka also gives information regarding the
length of time the inhibitor spends on the transporter. It is possible that METH
binding lasts longer than AMPH binding on DAT, which would give further
96
reasoning for the prolonged effects of METH inhibition of DA uptake via DAT
compared to AMPH inhibition of DAT.
Potential therapeutic efficacy of increased play in children with ADHD
As stated, the data shown here is intended to raise questions as to the
mechanisms of these drugs, with the hope that further studies will be conducted.
It is the opinion of this lab that the kinetic mechanisms of AMPH and METH are
more complex than initially thought. Furthermore, alternative treatment options
for conditions such as ADHD may be preferential to many, especially in the case
of children. This topic has been reviewed, and Panksepp (24) has suggested
that PLAY is in fact an emotional system that exists in both the animal and
human brain. Citing data from his 2003 paper in Brain and Cognition (25),
Panksepp argues that sufficient amounts of play will facilitate development of
frontal lobe inhibitory skills in children. The neocortex of the human brain
controls many higher functions in humans and primates, including decision
making and motivation . The frontal lobe of the neocortex controls “executive
functions”, which allow humans to control, and in some cases, inhibit, their
emotions. Among other things, the frontal lobe allows humans to determine right
and wrong, as well as what type of behavior is appropriate in certain situations.
In young children, this system has yet to fully develop, which is a key reason as
to the lack of “filter” shown by young children, i.e. children often say what they
are thinking, with little thought as to the consequences of what they are saying,
as well as to how such statements may affect others. As stated by Panksepp,
development of this system allows for regulation of impulsive primary-process
97
emotional urges, and increased play in children may indeed facilitate maturation
of this system. Children who have little chance for play are likely to become antisocial and criminally prone, and despite the scarce research into the value of
play in children, it is entirely possible that increased play may be a more effective
form of treatment for children than AMPH based medications such as Adderall,
and DAT blockers such as Ritalin. Additional research by Panksepp (26)
suggests that ludic tendencies of children, or misbehavior, increase with further
restriction of play, specifically rough and tumble play. Rough and tumble play is
often forbidden in environments such as the classroom, creating additional stress
for the child, and possibly contributing to additional poor behavior. While
medications such as Ritalin and Adderall allow children to be attentive and calm,
these medications often have poor long-term results, and in many cases likely do
not allow for proper and natural maturation of the child’s neurological systems.
As suggested by Panksepp, the increased diagnosis of ADHD in children may be
the result of the restrictive environment that children are placed in now, as
opposed to actual neurological illness. Such environments may lead to poor
social development and learning, and medicating children may lead to further
long-term damage to development of social and emotional systems necessary to
function and succeed in today’s society.
Conclusion
The results presented here show that there may be additional mechanisms
involved in AMPH and METH addiction on a molecular level, and that AMPH may
actually have a greater effect on CNS function due to increased DA release.
98
While the extra methyl group found on METH is indeed a valid theory for the
greater efficacy of METH, it is likely, knowing how complex the brain is, that there
are additional mechanisms at work, and perhaps knowledge of these
mechanisms may eventually lead to improved treatment methods for AMPH and
METH addiction. Furthermore, nurturing of PLAY systems in children may lead
to better long-term results than AMPH-based medications such as Adderall and
Ritalin.
99
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CHAPTER 4
Release and Reuptake Kinetics of the Dopamine Transporter in
Parkinsonian Rats
Peter A. Lukus1, George Stoica3, and James O. Schenk1,2
1
Department of Chemistry and 2Programs in Pharmacology/Toxicology and
Neuroscience, Washington State University, Pullman, Washington, 99164.
3
Department of Pathobiology, Texas A&M University, College Station, Texas,
77840.
Preface: The following chapter is written for submission to the journal Analytical
Biochemistry. All experiments and data analysis was performed by Peter A.
Lukus. Lab space and equipment was provided by Dr. James O. Schenk. Rat
brain tissue was supplied by Dr. George Stoica.
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Abstract: Parkinson’s disease is a degenerative neurological disease wherein
dopaminergic cell bodies found in the brain begin to die, resulting in increased
bouts of uncontrollable shaking and random spasms, and ultimately depression
and/or dementia. The root cause of the cell death is unknown, and the various
models that have been developed over the years have been unsuccessful in
finding a root cause of the condition. In this study, rats naturally experiencing
physical symptoms of Parkinson’s disease were sacrificed, and dopamine
transport was examined in the caudate putamen, mesencephalon, and olfactory
bulb using rotating disk electrode voltammetry, to assess functionality of the
dopamine transporter in rats ataxic for Parkinsons. Uptake was examined
exogenously, while release and reuptake rate constants were found via KCl
stimulation after addition of DA. Results showed that despite variations in
transport and release rates, the transporter for dopamine was still functioning in
the above mentioned areas, and was responsive to both exogenous dopamine
addition, as well as endogenous release stimulation which occurred immediately
after exogenous uptake. While the study shows the functionality of dopaminergic
transmission in ataxic Parkinsonian rats, more data needs to be collected to fully
understand the efficacy, or lack thereof, of the various systems at work in these
brain regions.
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Introduction
The neurotransmitter dopamine(DA) is one of over a hundred known
neurotransmitters, and is prevalent in various areas of the brain, including the
striatum, substantia nigra, olfactory tubercles, nucleus accumbens, and medial
prefrontal cortex (1). Along with acting as a precursor to norepinephrine (NE),
DA is highly innervated in the areas of the brain controlling movement, reward,
and motivation, and fluctuations in the level of DA available to bind to DA
receptors in these areas leads to massive changes in behavior (2). The
nigrostriatal and mesocorticolimbic dopamine pathways are two pathways (three
if you consider the mesolimbic and mesocortical pathways separately) with major
contributions to addictive behaviors, stemming from the effects of drugs like
cocaine on DA transport, as well as their effects on neuronal plasticity (3). Loss
of dopaminergic cell bodies in the substantia nigra is the hallmark of Parkinson’s
disease, resulting in loss of fine motor skills, and often resulting in depression
and psychosis (4).
Parkinson’s disease is a progressive neurodegenerative disorder of the basal
ganglia that is characterized by tremor, muscular rigidity, difficulty in initiating
motor activity, and loss of postural reflexes (1). Parkinson’s mainly affects motor
movement. As dopaminergic cells die off, the balance between acetylcholine
and dopamine is disrupted, and the constant shaking and involuntary movements
that are the hallmark of Parkinson’s disease begin to appear. Fine motor skills
are lost, whereas gross motor skills turn from preconceived movements to
random twitches which are often uncontrollable. While it has been known for
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some time that Parkinson’s disease is characterized by loss of pigmented cells in
the substantia nigra, only since 1960 has it been known that Parkinson’s results
in substantial loss of dopamine in the corpus striatum. The striatum is part of the
nigrostriatal DA system, with the striatum itself functioning to help coordinate
motivation and movement. Among other things, the striatum is involved in
behavior regulation in complex social situations, and inhibiting small involuntary
movements. DA’s role in this is crucial, and loss of dopaminergic cell bodies in
the striatum is responsible, in part, for the frequent shaking and loss of fine motor
skills observed in Parkinson’s patients. Many studies have been done to
elucidate the mechanisms behind Parkinson’s, with hope that one day a more
efficient therapeutic tool may emerge, or perhaps, even a cure. There have been
many approaches to this problem. Some choose to look at certain genetic
factors and predispositions (5, 6, 7), while others have chosen to use chemical
treatments to destroy dopaminergic cell bodies in animals, thereby mimicking
Parkinsonian symptoms (8, 9, 10).
The need for improved Parkinsonian models is due to the current efficacy, or lack
thereof, of treatment for Parkinson’s patients. The main treatment for
Parkinson’s disease has been L-dihydroxyphenylalanine, also known as L-DOPA
or levodopa (11), which is the precursor to DA in its biosynthetic pathway. The
structure of L-DOPA is shown in Figure 1. The efficacy of L-DOPA is due to the
fact that it can cross the blood-brain barrier, whereas DA cannot, which allows it
to be taken orally or injected into the blood stream. The main problem that
occurs with L-DOPA is twofold: 1) while L-DOPA crosses the blood-brain barrier,
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Figure 1. Chemical structure of L-DOPA.
108
there is still a large amount that does not, and it is estimated that only about 1%
of the L-DOPA given to a patient makes it across the blood-brain barrier to be
metabolized into DA, and 2) The main commonality, or perhaps the main flaw,
with these techniques is that the animals have not shown the progression that is
typical of Parkinson’s disease. Instead, they are genetically altered or chemically
treated to mimic neuronal cell death in DA systems.
The neuronal transporter for dopamine, known as the dopamine transporter
(DAT), is a seven-transmembrane spanning protein (12) consisting of 619 amino
acids, and is a member of the Na+ and Cl- dependent family of transporters (13).
When DA is released from vesicular storage into the synapse, it binds to
receptors and autoreceptors alike, and is subsequently taken up by DAT and
transported back into the presynaptic space, released, and then metabolized into
DOPAC or homovanillic acid(HVA). Once DA is released, DAT then returns to
the synapse to begin the process again. It has long been thought that areas with
high intracellular concentrations of DA not only have more DAT, but that DAT has
higher functionality than areas with lower concentrations of DA. While it has
been found that DAT is highly concentrated in areas with high concentrations of
DA , the functionality of the transporter in these areas has been investigated
sparingly (14, 15). There have been several studies on the effect of Parkinson’s
disease on DA uptake via DAT; however all have been done using models
wherein Parkinson’s is induced via 6-hydroxydopamine (6-OHDA) lesions, or via
MPTP toxicity (16, 17).
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Rotating disk electrode voltammetry (RDEV) is a technique that has been used
by this lab (18, 19) and others (20) to study neurotransmitter transporters such as
dopamine transporter (DAT), norepinepherine transporter (NET), and the
serotonin transporter (SERT). The advantage of using RDEV to study
transporter uptake is due to the temporal resolution afforded by the technique. In
RDEV, rotation of the electrode allows for forced convection, wherein analyte is
brought to the electrode surface and either oxidized or reduced, depending on
the potential applied. The analyte is then swept away from the electrode surface
and back into the bulk solution. Transport of neurotransmitters happens very
fast, on the order of milliseconds, and because of this, study of transport via
diffusion controlled techniques, such as chronoamperometry, can be difficult, if
not impossible in some cases. To get a better understanding of the kinetics of
the system, RDEV can be used to temporally resolve the system, with a
response time of approximately 30ms, whereas neurotransmission typically
happens on the order of 120ms. While RDEV cannot be used in vivo, transport
data is collected in a more temporally resolved environment. This also removes
many second messenger systems and additional transport moieties that may be
involved in transport, allowing the experimenter to focus on a small number of
transporters, and, with the correct pharmacological manipulation, individual
transporters. Furthermore, many drug manipulations that are needed can be
added directly into solution, in a much easier fashion than is allowed for in vivo
treatment. A figure of an RDEV setup for neuronal tissue samples is shown in
Figure 2. RDEV has not been used in research on DAT function in Parkinsonian
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Figure 2. Experimental setup for RDEV analysis on rat striatal tissue. A constant
stream of 95% O2 / 5% CO2 was applied across the solution surface, and water
was circulated through the cell jacket at 37oC.
111
animal models to the knowledge of this research group, however the advantages
it offers, and previous research by this lab using RDEV to study neurotransmitter
transport phenomena, suggest that the technique is well suited to investigating
DA uptake in rat brain tissue which is ataxic for Parkinson’s.
Recently, Dr. George Stoica of Texas A&M University generously sent our lab
brain samples from rats presenting symptoms of Parkinson’s disease. No
treatments were given to these animals to induce the condition. Determining DA
transport kinetics in rats of this type could begin to unravel some of the intricacies
of the Parkinsonian brain, and ultimately may lead to novel therapeutics in which
DAT, and improved DAT function, is the target and ultimate goal, respectively.
Previous work was done by this group (21) using ion-mobility mass spectrometry
to compare DA concentrations in a healthy rat brain to ones that showed signs of
Parkinson’s disease, which was visually determined by observation of involuntary
shaking by the rats.
Materials and Methods
Brain sections from hooded rats raised by Dr. Gregory Stoica were dissected and
flash frozen, at which point they were shipped in dry ice to Washington State
University. The areas analyzed were the mesencephalon, olfactory bulb, and
caudate-putamen (striatum), shown in Figure 3. The midbrain is of key interest in
this study because it is where the substantia nigra is located. As previously
state, death of dopaminergic neurons in the substantia nigra is responsible for
the symptoms observed in Parkinson’s patients. Samples were stored in a -80oC
freezer, and thawed in a -20oC freezer overnight before use. The same
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Figure 3. Saggital section showing areas of interest for DA release and uptake
studies.
113
procedure was used for tissue taken from rats that showed and did not show
Parkinson-like behavior. Upon thawing, mesencephalon, olfactory bulb, and
striatal sections were then individually chopped on an ice-cold watch-glass and
placed into an RDE incubation chamber in 1250 µL of physiological buffer,
homogenized by pipetting, and then washed with fresh physiological buffer six
times. The RDE was then placed into the incubation chamber, and an electrode
rotation speed of 2,000 rpm was applied with a Pine Instruments (Grove City, PA,
U.S.A.) rotator. A potential sufficient enough to oxidize and detect dopamine was
applied, +0.450 V relative to a Ag/AgCl reference electrode. Potential was
applied to the RDE via a Bioanalytical Systems (West Lafayette, IN, U.S.A.)
LC4C potentiostat, and the current was monitored on a Nicolet Instruments Corp.
(Madison, WI, U.S.A.) model 2090 digital storage oscilloscope. For experiments
involving exogenous addition of DA, the initial signal, consisting of the
background current from the tissue preparation in buffer, was allowed to reach a
baseline, at which point 20 µL of DA was added to the tissue suspension such
that the resulting DA concentration in the suspension would be 1.0 µM. For
experiments involving K+ stimulated release and subsequent reuptake, the
solution of brain tissue and buffer were brought to baseline, and buffer with
elevated KCl was added such that the first addition led to a 15 mM KCl
concentration in the cell, and a second addition led to a 30 mM KCl concentration
inside the cell. The resulting signal was plotted as [DA]o vs. time. Initial release
rates were defined as the linear portion of the positive slope of [DA]o vs. t, while
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initial reuptake rates were defined as the linear portion of the negative slope of
[DA]o vs. t.
Analysis of Release & Reuptake Data
Analysis of release and reuptake data was done using GraphPad Prism Version
5.02 (San Diego, CA). Release and reuptake rate constants for K+ stimulated
release and reuptake were found by plotting the ln[DA] vs t (22). The plot is used
for kinetic data which follows the equation
[DA] = [DA]o{exp(-krt) – exp(-kut)} Eq. 1
where [DA] is total DA concentration, kr is the rate constant for the first process
(in this case DA release), ku is the rate constant for the second process (in this
case reuptake of DA), and [DA] = [DA]o ( 1 + 1/k1 – k2), with [DA]o being the initial
concentration of DA. Analysis of the resulting curve is explained in Figure 4.
[DA]o can be found by extrapolation of the ln[DA] vs time graph to x=0. This
corresponds to the concentration of DA initially available for release via forced
action potential, and not the total DA concentration present in the entire tissue.
Solutions and Chemicals
Solutions were prepared in deionized water purified further by a Nanopure Water
Purification System (Barnstead, Dubuque, IA, U.S.A.). Buffer salts, dopamine
HCl, and KCl were obtained from Sigma-Aldrich Chemical Co.(St. Louis, MO,
U.S.A.).
The physiological buffer at pH 7.4 was comprised of 124 mM NaCl, 1.80 mM KCl,
1.24 mM KH2PO4, 2.50 mM CaCl2, 1.30 mM MgSO4, 26.0 mM NaHCO3, and
10.0 mM glucose and saturated with a gas mixture of 95% O2 and 5% CO2.
115
Figure 4. Fersht analysis of DA release and reuptake data. The
slope of the bottom curve is used to find the rate of uptake, while the
top curve is used to find rate of release.
116
Results
Exogenous Uptake Rates
Analysis of olfactory bulb uptake and subsequent stimulation of release showed
average uptake values of 214.51 ± 58.66 pmol/sg for control samples, while
analysis of ataxic samples revealed an average uptake value of 107.80 ± 16.30
pmol/sg. Caudate putamen samples showed an average uptake rate of 222.20 ±
75.52 pmol/sg for control samples, while ataxic samples averaged 159.90 ±
70.04 pmol/sg. Finally, mesencephalic tissue samples averaged 256.30 ± 80.95
pmol/sg, while ataxic samples averaged 135.60 ± 84.30 pmol/sg. All errors were
calculated as standard error of the mean.
Endogenous release and reuptake rates
Fersht analysis of rate constants for the release and reuptake processes of the
olfactory bulb showed an average release rate (in s-1) of 0.249 ± 0.1966, with an
uptake rate of 0.00477 ± 0.000845, while ataxic samples had an average release
of 0.105 ± 0.0196, and an average uptake of 0.00689 ± 0.00466. Caudate
putamen samples showed an average release rate of 0.0412 ± 0.0134, and an
uptake rate of 0.01455 ± 0.00736 for control samples, and an average release of
0.166 ± 0.1168, and an uptake rate of 0.0106 ± 0.00393 for ataxic samples.
Finally, mesencephalic samples averaged a release rate of 0.0688 ± 0.00320,
and an uptake rate of 0.0400 ± 0.0178 for control samples, while ataxic samples
showed an average release rate of 0.260 ± 0.134, and an average uptake rate of
0.0106 ± 0.0054.
Discussion
117
Bar graphs comparing uptake velocities, as well as release and reuptake rates,
are shown in figures 5-7. As stated, the experiments needed to be performed in
such a way that release and reuptake data was recorded immediately after
exogenous uptake data was obtained, because little to no DA remains in the
tissue of ataxic samples. The main question that was asked in this study was the
question of whether or not the neuronal transporter for DA is still present and/or
functioning in Parkinsonian brain tissue. It is known that dopaminergic cell
bodies begin to die in Parkinson’s disease, however how this does or does not
affect DAT, and neuronal DA transport, is unknown.
From the results shown here, it is clear that the transporter is not only present,
but, in general, works as efficiently as in healthy brain tissue. This was true for
each tissue portion sampled from the olfactory bulb, caudate putamen, and
mesencephalon. The density of DAT in brain tissue is often correlated with the
amount of DA available in a particular region of the brain. Studies from this lab,
outlined in Chapter 2, suggest that the concentration of DA in a particular region
is not necessarily indicative of increased DAT, at least kinetically. It is possible
that loss of dopaminergic cells would lead to a decrease in total DAT available, or
possibly down regulation of the transporter due to decreased levels of DA
available
However, this does not seem to be the case in tissue samples from
ataxic rats. It is possible that loss of dopaminergic cells in the brain would lead to
an up regulation of DAT in those areas, making DA transport more efficient. Up
and down regulation refers to the brain’s regulation of protein concentrations in
response to availability. For instance, the density of DA receptors in the brain
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Figure 5. DA uptake rates via exogenous uptake by DAT for caudate putamen
(CP), olfactory bulb (OB), and mesencephalon (MS) for both controls (C) and
ataxic, or “shakers” (S). Rates are calculated from the linear portion of the
uptake slope, and normalized for tissue weight. Rates are calculated as pmol/sg.
119
Figure 6. Rate constants of release of DA via KCl stimulation for caudate
putamen (CP), olfactory bulb (OB), and mesencephalon (MS) for both controls
(C), and ataxic, or “shakers” (S). Rates are calculated via Fersht analysis
described in the methods section, and calculated in s-1.
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Figure 7. Rate constants of reuptake of DA via KCl stimulation for caudate
putamen (CP), olfactory bulb (OB), and mesencephalon (MS) for both controls
(C), and ataxic, or “shakers” (S). Rates are calculated via Fersht analysis
described in the methods section, and calculated in s-1.
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down regulates in response to overstimulation, as is the case in chronic abuse of
DA releasing drugs such as cocaine and methamphetamine. Receptor density
decreases with an increase of DA binding frequency, which is what leads to
tolerance. In the case of Parkinson’s disease, death of dopaminergic cells would
ultimately lead to a decrease in DAT available. However, when there is a DA
influx, such as the DA additions done in this study, the remaining DA cells may
up regulate DAT to allow for uptake of the excess DA available. If this is indeed
the case, then transport rates in ataxic tissue samples would mimic, if not
exceed, uptake rates in normal tissue. Despite this evidence, more data is
needed to confirm this hypothesis. Testing of DAT density pre and post addition
of DA need to be done in order to ensure that up regulation is indeed occurring.
Radio labeling of DAT could be achieved using [125I]RTI-55, a common radio
ligand used for detection of DAT via autoradiography (23). Differences between
pre and post DA addition could be done to ascertain how much DAT is in fact
available to participate in DA uptake.
It is also possible that up regulation of DAT does not occur, but instead that the
“functionality” of DAT increases. “Functionality” in this case refers to increased
efficiency of the individual transporters that remain to transport DA, as opposed
to an increase in DAT. Autoradiography experiments would give better insight
into this hypothesis as well. If DAT density increases pre and post addition, than
up regulation likely occurs. However, if DAT density remains stable, and
transport continues to occur at a kinetic rate comparable to that of normal tissue
samples, then it would certainly be possible that signaling molecules may cause
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increases in rates of DA transport of individual DAT proteins. DAT function is
measured as a whole, i.e. the rate measured is assumed to be the average rate
of all DAT molecules participating in uptake of DA. Thus, it is possible that
increased rates of transport for individual DAT proteins may bring the total rate of
DA transport to a “mean” value necessary for proper brain function.
An additional question asked was whether or not DAT will function both ways, i.e.
will it also release DA when stimulated via KCl, as it does in healthy tissue. The
results here show that indeed it does. Due to the depletion of DA in the affected
areas, DA had to be “loaded” into the cells via exogenous uptake. While DAT
function was retained, it is unknown why such a variation in the uptake rates
existed, especially between the same areas, i.e. between CP and CP, MS and
MS, and OB and OB. The variation seen here may be due to the freeze thaw
procedure, and, although the tissue retained function as far as transport is
concerned, there may have been unknown effects caused by long periods of
freezing.
The functionality of additional neuronal transporters was not tested in these
experiments. Previous studies done by this group, discussed in Chapter 2, have
tested the effects of the serotonin (5-HT) transporter on dopaminergic uptake in
the caudate putamen. In this work it was found that there is little effect of this
transporter on the overall rate of DA transport. However, several other
transporters, such as the norepinepherine transporter (NET), organic-cation
transporters 1 and 2 (OCT1 and OCT2), and the vesicular monoamine
transporter (VMAT), have all been shown to have affinities for DA, and are all
123
able to transport DA in some way. It is unknown how the freeze-thaw procedure
affected these transporters and their efficacy for transporting DA between
different sample types, as well as between samples of the same type (i.e. two
MS samples). More control studies would need to be done in order to determine
this, as well as the cause of the large error seen in the measurements. In
addition, the particular effects of the freeze-thaw procedure need to be
determined in order to make more specific conclusions about the above results.
The density of DAT is high in all areas tested, however each area behaved
differently in terms of kinetic regulation of DAT. MS transport of DA averaged
higher uptake rates than that of the CP and OB, although the error found in the
rates calculated, which was calculated as the standard error of the mean (SEM),
show a higher overall error for transport rates measured in the MS as opposed to
the CP and OB. This may be due to varying densities of additional transporters
that would likely be found more in the MS than the CP and OB, with NET and the
serotonin transporter (SERT) being the most likely transporters to assist with DA
transport. Additional transporters, such as VMAT and the plasmalemmal
monoamine transporter (PMAT) may also be involved. Due to use of RDEV,
diffusional variations occurring in the synapse can be eliminated, however
variation in rates due to secondary messenger systems, such as protein kinase
A, are also possible. More experiments are needed to either confirm or deny this
theory.
It is also not clear how neuronal release changes in ataxic rats as opposed to the
controls. As shown in the results, the OB shows release and reuptake rates for
124
control samples are twice that of the ataxic samples. The same does not apply
for the CP and MS areas. The reasons for this are questionable. It is possible
that the extreme reintroduction of DA to the cells may cause differences in
excitation and relaxation potentials in the cells. This effect would cause
variations in release of DA between regions of the brain, as well as between
individual samples. It is also questionable how much, if any, DA is metabolized
upon being taken up by DAT, and how much of a variation exists between control
samples and ataxic samples.
Conclusion
The main question addressed in this work was the function of neuronal DAT in
rats presenting with Parkinsonian symptoms; more specifically, did any exist, and
if it did, was it at all comparable to control samples. From the data shown here, it
is clear that DAT not only still exists in the OB, CP, and MS in Parkinsonian rats,
but it also functions comparably, and in some cases better, than that of control
samples. The main problems with the current work include reproducibility of
data, possibly due in part to the freeze-thaw procedure used, as well as the
countless variables that occur with neuronal transport research. More studies
are needed to confirm what variables do or do not exist in rats such as these that
naturally present with Parkinson’s disease, and what effect these variables have
on overall neurotransmitter transport, specifically that of DA.
125
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CHAPTER 5
CONCLUSION
Introduction
The work presented discusses kinetic analysis of dopamine (DA) transport in rat
brain tissue. Dopamine transporter (DAT) functionality across the striatum was
investigated, and anterior and posterior sections were analyzed to find
differences and similarities in exogenous uptake, as well as stimulated DA
release and subsequent reuptake. Differences in uptake in the presence of
cocaine were also investigated. Comparison of release and reuptake rates of
methamphetamine (METH) and amphetamine (AMPH) were examined, and the
concentration of DA released via neuronal stimulation of each are discussed.
Finally, DA transport in Parkinson’s inflicted rat brain tissue is examined. Kinetic
rate constants of DA release and reuptake, were measured in the olfactory bulb
(OB), mesencephalon (MS), and caudate-putamen (CP).
Anatomical variability of DAT function (Chapter Two)
The goal of this study was to investigate how DAT uptake of DA differs in
different local anatomical areas of the rat brain, specifically the anterior and
posterior striatum. The focus was on implications any differences may have in
the role of cocaine inhibition of DAT. Velocities of DA transport in anterior striatal
tissue were shown to be comparable to, if not higher than, those found in whole
striatal tissue. Posterior velocities fluctuated in a manner that DA concentrations
in those areas would not predict. On average, DA transport rates were lower in
the posterior striatum when compared to the anterior, however this difference
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was found to be much less in the left striatum than the right. The later function
implies a greater functionality of posterior striatal DAT in left striatal activities.
Laterality may also play a role in differences between anterior and posterior DAT
uptake. While overall the differences may not be immediately clear, a closer look
at individual test samples reveals that laterality plays a larger role in DA
concentration and DAT functionality in the striatum than may have been
previously thought. Inhibition with DAT via addition of cocaine shows that the
effects of cocaine are seen throughout the striatum. The gap between anterior
and posterior uptake rates becomes much narrower under the influences of
cocaine. Using the SSRI Citalopram, SERT was shown to have a minimal effect
on DAT transport in the striatum, and though increases in DAT transport rates in
the left striatum were seen, further testing would be needed to determine the
cause of this result. Overall this study demonstrates that DAT functionality varies
in the striatum, and is not necessarily dependent on DA concentration. Further
studies on DAT functionality throughout the rat brain should be conducted to
determine how DAT responds in other areas of high and low DA concentration,
especially in the presence of drugs of abuse that target DAT, such as cocaine.
DA release via stimulation by METH and AMPH
The results presented here show that there may be additional mechanisms
involved in amphetamine (AMPH) and methamphetamine (METH) addiction on a
molecular level, and further that AMPH may actually have a greater effect on
CNS function due to increased DA release. The structure of METH is simply an
AMPH molecule with an additional methyl group. This extra methyl group is
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thought to be the reason for the increased effects of METH compared to AMPH
for two reasons. First, the extra methyl group is thought to give greater lipid
solubility to METH, allowing it to cross the blood brain barrier faster than AMPH.
Crossing the blood brain barrier at an increased rate would allow for a greater
concentration of METH to reach the brain as opposed to AMPH, before either
was exposed to metabolic degradation. Second, the extra methyl group on
METH is thought to protect METH from degradation by monoamine oxidase
(MAO). While both METH and AMPH inhibit MAO to some extent, the extra
methyl group found on METH is thought to inhibit MAO longer, preventing
degradation of both itself and DA. While the extra methyl group found on METH
is indeed a valid theory for the greater efficacy of METH, it is likely, knowing how
complex the brain is, that there are additional mechanisms at work. Perhaps
increased knowledge of these mechanisms may eventually lead to improved
treatment methods for AMPH and METH addiction. Furthermore, nurturing of
PLAY systems in children may lead to better long-term results than AMPH-based
medications such as Adderall, and DAT inhibitors such as Ritalin.
DA release and reuptake in Parkinson’s Rats
The main question addressed in this work was the function of neuronal DAT in
rats presenting with Parkinsonian symptoms; more specifically, did any
connection exist, and if it did, was it at all comparable to control samples. From
the data shown in Chapter Four, it is clear that DAT not only still exists in the
olfactory bulb (OB), caudate-putamen (CP), and mesencephalon (MS) in
Parkinsonian rats, but it also functions comparably, and in some cases better,
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than that of control samples. While DA cell death does occur, it is possible that
the DAT still remaining in the brain increases its transport rate in response to
increased DA levels. It is also possible that up regulation of DAT occurs in
response to increased DA levels. The main problems with the current work
include reproducibility of data, possibly due in part to the freeze-thaw procedure
used, as well as the countless variables that occur with neuronal transport
research. More studies are needed to confirm which variables do or do not exist
in rats such as these that naturally present with Parkinson’s disease, and what
effect these variables have on overall neurotransmitter transport, specifically that
of DA.
Overall conclusions and future work
The body of work presented focuses on DA transport and DAT function. DAT
function has been shown to fluctuate from areas of high to low DA concentration
in the striatum, with overall transport rates being higher in the anterior striatum
than that of the posterior. However, the rates of transport in the anterior striatum
are not consistently higher than that of the posterior, suggesting that regulation of
DAT density may change in the posterior striatum in response to increased DA
concentrations. Additionally, it is possible that individual DAT proteins up
regulate their rate of transport in response to excess DA. Future work will involve
investigation of additional brain regions known to contain DAT, such as the
nucleus accumbens (NAc) and prefrontal cortex (PFC), to determine if DAT
kinetics vary in these areas as well. Chronoamperometric studies would prove
useful, especially in smaller areas such as the NAc. Brain slice and in vivo
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studies would also show if DAT function varies when longer connections are
present (in the case of brain slices), or in the living animal (in vivo studies).
DAT function and DA release have been shown to respond in varying degrees to
METH and AMPH stimulation. On average, AMPH stimulation causes a higher
concentration of DA to be released relative to METH stimulation, while METH
has a greater affect on transport rate inhibition. The methyl group present on
METH may indeed be the reason for the increased neurological affects
experienced by users, though the kinetic differences in release and reuptake
shown in Chapter Three suggest that there may be a kinetic component to this
argument. Studies were done only in striatal tissue, and other dopaminergic
areas, such as the NAc and PFC, need to be investigated in order to discern
whether this is a local phenomenon, or if it happens globally in dopaminergic
regions of the brain. Furthermore, in vivo studies would be extremely helpful to
determine the effects of METH and AMPH on DA release and reuptake in the
living animal.
DA transport in Parkinson afflicted rats was shown to be comparable to that of
normal, healthy neuronal tissue. The areas of interest were the olfactory bulb
(OB), caudate-putamen (CP), and mesencephalon (MS). Transport rates vary
between these areas, however it is clear that DAT still exists in ataxic tissue.
Kinetically, the transporter appears to function normally in ataxic tissue. It is
unclear if this is due to up regulation of DAT in the presence of increased DA, or
if DAT is regulated kinetically to function at a greater rate in the presence of
increased DA. Radio-label studies should be done to reveal the differences of
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DAT density pre, post, and during experimentation. Additionally, the freeze-thaw
procedure adds an additional variable to the experiment, making in vivo and
brain slice experiments necessary to determine if the freezing and thawing of
brain tissue have an adverse affect on the tissue. Binding studies should also be
done to measure the amount of DA bound to the transporter during
experimentation, which would give an additional parameter to determine DAT
function in ataxic tissue samples.
The goal of the studies presented was to examine the kinetics of DAT under
various conditions in rat brain tissue. The work presented demonstrates that the
regulation of DAT is not fully understood, especially in the case of drug binding
and neurodegeneration. Future work in neurotransmitter transport may very well
uncover additional aspects of transport that may lead to significant discoveries in
transporter function, and possibly increase therapeutic options in treating drug
addiction and neurodegeneration.
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