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Neural activity of the amygdala as measured by neurotrophin levels of fmri knockout mice versus normal mice

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Title:
Neural activity of the amygdala as measured by neurotrophin levels of fmri knockout mice versus normal mice
Creator:
Greenhill, Timothy Scott
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Language:
English
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vii, 31 leaves : ; 28 cm

Thesis/Dissertation Information

Degree:
Master's ( Master of Arts)
Degree Grantor:
University of Colorado Denver
Degree Divisions:
Department of Psychology, CU Denver
Degree Disciplines:
Clinical psychology

Subjects

Subjects / Keywords:
Amygdaloid body ( lcsh )
Fragile X syndrome ( lcsh )
Neurotropin ( lcsh )
Amygdaloid body ( fast )
Fragile X syndrome ( fast )
Neurotropin ( fast )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

Notes

Bibliography:
Includes bibliographical references (leaves 28-31).
General Note:
Department of Psychology
Statement of Responsibility:
by Timothy Scott Greenhill.

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|University of Colorado Denver
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Auraria Library
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All applicable rights reserved by the source institution and holding location.
Resource Identifier:
123128074 ( OCLC )
ocn123128074
Classification:
LD1193.L645 2006m G73 ( lcc )

Full Text
NEURAL ACTIVITY OF THE AMYGDALA AS MEASURED BY
/
NEUROTROPHIN LEVELS OF FMR1 KNOCKOUT MICE VERSUS NORMAL
Timothy Scott Greenhill
B.S., University of Wisconsin, Madison, 2002
A thesis submitted to the
University of Colorado at Denver and Health Sciences Center
in partial fulfillment
of the requirements for the degree of
Master of Arts
Clinical Psychology
MICE
by
2006


This thesis for the Master of Arts
degree by
Timothy Scott Greenhill
has been approved
by
David Albeck
Richard M. Allen
Eric Benotsch


Greenhill, Timothy Scott (M.A., Clinical Psychology)
Neural Activity of the Amygdala as Measured by Neurotrophin Levels of FMR1
Knockout Mice Versus Normal Mice
Thesis directed by Associate Professor David Albeck
ABSTRACT
Fragile X Syndrome (FXS) is one of the leading forms of inherited mental
retardation (MR). Onset of the syndrome is linked to the lack of Fragile X Mental
Retardation Protein (FMRP), a protein responsible for normal maturation of dendritic
spines and synapses (Castren et al., 2002). In order to better understand the role of
FMRP in the central nervous system functioning, researchers turned to a genetically
manipulated knockout (KO) mouse which is deficient in FMRP (Dutch-Belgian
Fragile X Consortium, 1994). There have not been consistent findings in learning
and memory impairment; however a recent study found KO mice as compared to WT
mice to be significantly impaired in an escape/avoidance learning paradigm (Brennan
et al., 2005). Based on the results of this study, we conducted a study looking at
neural activity in the learning and memory systems of KO versus WT mice. This
present study focuses on the basal levels of neurotrophins (BDNF and NGF) in the
brain regions implicated by the Multiple Parallel Memory Systems (MPMS) model
(White & McDonald, 2002) in these two treatment groups. Although three different


brain regions are targeted, the amygdala is examined more closely due to its
implication in this type of learning. However, no significant basal BDNF or NGF
levels in the amygdala, hippocampus, or dorsal striatum were found before any type
of learning took place. Future studies will look at these same brain regions of Fragile
X Syndrome versus wild-type mice after learning has taken place in the
escape/avoidance paradigm.
This abstract accurately represents the content of the candidates thesis. I recommend
its publication.
Signed
David Albeck


ACKNOWLEDGEMENT
Many thanks to my advisor, David Albeck, for opening his lab to me and his constant
support of all my ideas and research. Thank you to Eric Benotsch and Rich Allen for
serving as member on my committee and for their advice and patience in this project.
I would also like to thank all the members of the lab who helped out at various times
in this research including Kazu Sang, Elizabeth Ortiz, Megan Nelson, and Nicole
Brevik. Lastly, I thank my family for their constant love and support of all of my
endeavors.


TABLE OF CONTENTS
Figures....................................................................vii
Chapter
1. Introduction..............................................................1
1.1 Animal Model of Fragile X Syndrome.......................................2
1.2 Targeted Memory Systems..................................................4
1.3 Neurotrophins, LTP, and LTD..............................................7
1.4 Purpose of study........................................................10
2. Materials and Methods....................................................14
2.1 Experimental Subjects...................................................14
2.2 Dissection.............................................................14
2.3 BDNF and NGF Assays....................................................15
2.4 Statistical Analyses...................................................16
3. Results..................................................................17
3.1 Neurotrophin Levels.....................................................17
4. Discussion...............................................................22
4.1 Practical Issues Concerning Methodology.................................22
4.2 Future Implications....................................................24
References..................................................................28
vi


LIST OF FIGURES
Figure
3.1 Table of Basal Descriptive Statistics of BDNF levels
(pg/mg) of KO and WT mice in the Hippocampus,
Dorsal Striatum, and Amygdala.......................................18
3.2 Graph of Basal BDNF Levels of WT versus KO Mice......................19
3.3 Table of Basal Descriptive Statistics of NGF levels
(pg/mg) of KO and WT mice in the Hippocampus,
Dorsal Striatum and Amygdala........................................20
3.4 Graph of Basal NGF Levels of WT versus KO Mice.......................21
vii


1.
Introduction
Fragile X Syndrome (FXS) is one of the leading genetic causes of mental retardation
(MR), occurring in approximately 1/4000 males and 1/6000 females (Turner et al.,
1996). Common symptoms have been found to include mental impairment, attention
deficits, hyperactivity, anxiety, unstable mood, autistic behaviors, long face, large
ears, flat feet, seizures, and hyper-extensible joints (see, among others, Mineur et al.,
2002; Qin et al., 2002; Yan et al., 2004). Individuals with FXS lack the protein
FMRP (Fragile X Mental Retardation Protein), which is necessary for normal
maturation of dendritic spines and synapses (Castren et al., 2002). Dendritic spines
are important to examine because not only are they a site where communication
between neurons take place, but abnormalities have been found in them in several
different varieties of mental retardation disorders (Marin-Padilla, 1972; Purpura, 1975
as cited in Nimchinsky et al., 2001). The absence of FMRP has been found to be due
to a result of a repeat expansion of trinucleotide (CGG) triplet on the FMR1 gene
located on the long arm of the X chromosome (Oberle et al., 1991 as cited in Gruss &
Braun, 2004). In normal individuals the CGG repeat occurs between five and 50
times, with an average of 30 repeats. When the repeat sequence occurs in the 40 50
range, this is considered a gray zone, however if the range reaches 50 200 repeats
then this is termed as a premutation carrier. At this level an individual may begin to
exhibit some subtle learning or emotional deficits, such as those seen in the disorders
1


Premature Ovarian Disease (POF) and Fragile X Tremor Ataxia Syndrome (FXTAS)
(Ranum & Day, 2004). When the CGG repeat expansion reaches over 200, as it does
in FXS, it is considered a full mutation, which leads to the FMR1 gene switching off
and no longer producing the protein FMRP.
1.1 Animal Model of Fragile X Syndrome
To study the behavioral and physiological correlates of FXS, an animal model was
created in which the FMR1 gene was turned off, therefore not producing FMRP. The
animal model that receives the most attention is the genetically manipulated FMR1
Knock-Out (KO) mouse which was developed in 1994 (Dutch-Belgian Fragile X
Consortium, 1994). This FXS mouse model shares several of the common
characteristics seen in the human syndrome, including enlarged testicles; long, thin
dendritic spines; some subtle spatial learning abnormalities; auditory hypersensitivity;
and increased susceptibility to audiogenic seizures (Qin et al., 2002). However, there
are mixed findings reported about anxiety in the mouse model as compared to the
human syndrome. There have been several reports of low anxiety levels observed in
the FMR1 KO mice. This is based on the observation of FMR1 KO mice in an Open
Field Activity in which they were found to move a greater distance into the open field
than their Wild-Type (WT) counterparts. Normally rodents being prey animals seek
cover and avoid open spaces; therefore, this finding of increased exploration by the
2


FMR1 KO mice is thought to suggest a decrease in anxiety (Qin et al., 2002; Yan et
al., 2004). Yan et al. (2004) suggest that based on the high incidence of anxiety-
related disorders seen in human FXS, tests of the mouse model for this phenotype is
worthwhile. Subsequent testing in the Elevated Plus Maze (EPM), another test
sensitive to anxious behavior in rodents, did not show any difference between the two
genotypes. These disparate findings have led to an alternative explanation for the
amount of time spent in the open field: that the FMR1 KO mice have a different
exploratory propensity than their WT counterparts (Yan et ah, 2004). It seems that
more research on anxiety-like behaviors in the animal model of FXS is needed to
confirm whether anxiety is affected, and if so, how.
Cognitive deficits in FMR1 KO mice have been difficult to demonstrate and
furthermore reported data seem to conflict. Data show mild impairment in
performance on the Morris Water Maze and spatial position learning tests, some
impairment in the passive-avoidance test, and hyperactivity to auditory stimuli
(Ventura et ah, 2004). Brennan et ah (2006), set out to assess how FMR1 KO mice
would perform in a leverpress escape/avoidance task. This research group found
FMR1 KO mice to escape at the same rate as WT mice; however the KO mice were
significantly impaired on avoidance of the stressful stimuli as compared to the WT
counterparts. In this experiment, an escape was defined as a lever-press after the
shock had begun, while an avoidance response was defined as a response that
3


occurred during the initial 60 seconds of the auditory warning signal before the shock
was activated. Furthermore, the KO mice also did not acquire the lever-press
response to any appreciable degree. The present study will begin to explore the
neural activity involved in this behavioral deficit on this learning paradigm.
1.2 Targeted Memory Systems
According to the Multiple Parallel Memory Systems (MPMS) model there are three
primary memory systems operating in parallel, each responsible for different aspects
of experience (White & McDonald, 2002). The three memory systems in this model
are represented by the most central brain structures of each: the hippocampus, the
dorsal striatum, and the amygdala. These three neural systems continually process
information and influence behavior. The hippocampal system has been implicated in
working memory, the dorsal striatum encodes stimulus-response formation, which
is similar to classical conditioning, and the amygdala processes emotional memory
such as in the stimulus-reinforcer model or operant conditioning (White &
McDonald, 2002).
Due to the confusion that often exists between stimulus-response (S-R) and
stimulus-reinforcer (S-Rf) models, a more detailed explanation is needed. According
to White & McDonald (2002), the components of these two models include: neutral
cue (S), reinforcer (S*), and three different types of responses elicited by reinforcers.
4


These responses consist of observable approach/escape responses (R*), unobservable
central and autonomic responses (r...r), such as neural activity, neurotransmitter
release, and hormonal changes. This previous type of response (r...r) is thought to
constitute rewarding or affective states or internal affective stimulus (Sa). The final
type of response elicited by a reinforcer is modulation (M), which is the enhancement
or strengthening of recently acquired memories.
The S-R model, which is much like Pavlovian or Classical conditioning states
that an animal makes a response (R) in the presence of an environmental stimulus (S)
and if a reinforcer (S*) is encountered at around the same time as the association
between S and R then this association is strengthened or enhanced. This strengthening
of the association leads to an increase in the probability that the same stimulus will
elicit the same response in the future; also called modulation. A key feature in this
model is that the stimulus properties and the affective state produced by reinforcers
are not involved in this form of learning; it is more of an automatic response to a
stimulus that the organism does not even think about before performing. However,
the S-Rf model is more like Operant conditioning, in which an animal learns the
association of a neutral stimulus (S) with a reinforcer (S*). This learned association
allows the once neutral stimulus (S) to elicit a variety of conditioned responses, which
include conditioned approach/escape responses (R*) and conditioned affective
responses (Sa) similar to those that were initially elicited by the reinforcer itself. In
5


the S-Rf model versus the S-R model, behavioral performance of the association is
not needed in order to learn (White & McDonald, 2002).
Several reports in the literature have demonstrated that in FMR1 KO mice,
hippocampal mediated tasks are not impaired, strongly suggesting that other types of
cognitive tasks such as striatal or amygdala mediated tasks are likely to be the class of
tasks impaired. Recently, a deficit in object recognition was found in the FMR1 KO
mice (Ventura et al., 2004), which is presumably a striatal task, meaning striatal
impairments may exist.
A recent investigation of neurotrophic factor levels in these brain regions of
rats tested in the leverpress Escape/Avoidance learning task (E/A) may provide a
framework in which to examine the KO mouse model. This study (Albeck et al.,
2005) examined the effects of this task on BDNF and NGF levels in rats that were
either exposed to the task or were home cage controls and were not exposed to the
task. The experiment revealed that exposure to a leverpress E/A task produces
significant increased levels of both BDNF and NGF in the hippocampus (and basal
forebrain). However, no significant changes were observed in the dorsal striatum
with E/A training. This finding suggests the striatal memory system is not involved
in the E/A learning paradigm.
6


1.3 Neurotrophins, LTP and LTD
Neurotrophic Factors, such as NGF and BDNF are measured in order to determine
relative neural activity levels in particular brain regions. The Neurotrophin family,
especially BDNF and NGF, have been found to influence survival, differentiation,
and morphological maturation of neurons; formation of functional synapses; and
plasticity of synaptic connections during development and adulthood (Thoenen, 1995;
McAllister et al., 1999; Huang & Reichardt, 2001 as cited in Castren et al., 2002).
During early development of the brain, neurotrophins help guide the initial
synaptogenesis that creates a functional brain. In the mature brain, the formation and
maturation of synaptic connections has been described as the process of learning and
memory at the cellular level. In support of neurotrophin involvement in learning and
memory, there is evidence that suggests that BDNF signaling is in a key position to
influence the induction of Long-Term Potentiation (LTP) (Yamada et al., 2002 as
cited in Liu et al., 2004). LTP is the stable and enduring increase in the magnitude of
the response of neurons after afferent cells have been stimulated with bursts of
electrical stimuli of moderately high frequency (Rosenzweig et al., 2002). In other
words, LTP is when neurons become linked to each other in a neuronal network due
to constant firing together such as when learning takes place. The converse to this
process is Long-Term Depression (LTD), which is in a sense pruning of the neuronal
network; that is when neurons stop communicating with each other because they are
7


not firing at a frequent enough intensity together. Therefore, LTP and LTD impact
learning and memory storage at the synaptic level.
Taken together, neurotrophins are needed for the maturation, formation, and
survival of the neurons, while LTP and LTD is the communication processes of these
neurons at the synaptic level. The question then remains, how is this important in
Fragile X Syndrome? The answer lies in FMRPs role in learning and memory. Both
FMRP and BDNF are associated with synaptogenesis in the developing brain. This
synaptogenesis that occurs in the developing brain is similar to the formation and
strengthening of neuronal connections in the adult brain during learning. Since these
two proteins (FMRP and BDNF) are involved in higher cognitive functions, such as
learning and memory, they were studied to see if there is any connection or
correlation between their involvements (Castren et al, 2002). This study demonstrated
that BDNF expression regulates the levels of FMRP mRNA expressed (in
hippocampus), which means that BDNF is implicated in Fragile X Syndrome.
FMRP, which is necessary for normal maturation of dendritic spines and synapses as
mentioned previously, is not produced in Fragile X Syndrome, because the FMR1
gene is turned off. It was recently found that the loss of FMRP increases LTD (in
hippocampus) (Bear et al., 2004). This study found that FMRP usually functions to
inhibit synthesis of proteins involved in the stabilization of LTD and puts a brake on
LTD. Bear et al. (2004) suggest that exaggerated LTD may slow net synaptic
8


maturation and therefore contribute to the developmental delay and cognitive
impairments seen in Fragile X Syndrome. During LTP, NGF is released, suggesting
that NGF plays a role in the synaptic strengthening that occurs during learning
(Isacson et al., 2002). The lack of NGF in the rat brain impairs the
electrophysiological properties of neurons (Albeck et al., 1999). All of this taken
together, it appears that neurotrophins (esp. BDNF) may be implicated in this
syndrome.
If neuronal communication is occurring in a specific brain region,
neurotrophins should be present, because they are released when a postsynaptic cell is
activated (LeDoux, 2002). The released neurotrophin acts to strengthen that
particular synaptic connection, as it does during the early developmental stages of the
brain. Therefore, if significant increases in levels of BDNF or NGF are found in a
specific brain region as compared to baseline measures of these neurotrophins in the
same brain region, then this region theoretically should be involved in the learning
that is taking place. Since no significant neurotrophic factor levels were reported in
the dorsal striatum in normal rats during the leverpress E/A task, it is possible to
conclude that this brain structure may not be activated in this type of learning, and
therefore other brain structures should be further explored. However, Albeck et al.
(2005) did find significantly higher levels of both BDNF and NGF in the
hippocampus. Taken together, it appears that the hippocampus, but not the dorsal
9


striatum is activated during the E/A learning paradigm. The amygdala, however, has
not been studied in the E/A learning paradigm and has not been a major focus in
Fragile X Syndrome research; therefore, the present study will explore this brain
regions role.
1.4 Purpose of Study
Due to this hole in this line of research to date, the current study will focus on the
neural activity of the amygdala of the FMR1 KO mice as compared to WT mice. The
amygdala has been found to be critical for the acquisition and performance of
conditioned approach responses, rewarding affective states, avoidance responses,
aversive affective states, and memory modulation (White & McDonald, 2002). The
E/A learning paradigm (Brennan et al., 2006) included conditioned approach and
avoidance responses, which was demonstrated by the mouse learning the association
between approaching the lever and therefore avoiding the stressful stimuli of the
shock. Both the aversive and rewarding affective states are also implicated in this
learning paradigm. The footshock will lead to an aversive affective state, while the
termination of footshocks due to the pressing of the lever will lead to a rewarding
affective state, such as relief of not being shocked. Finally, it appears that success in
this E/A paradigm over time means that memory modulation is taking place. That is
as the mouse learns to press the lever to avoid the shock; the association between
10


stimulus and response is strengthened and will continue to occur in the future. Since
it appears that such a learning paradigm would include both positive and negative
affective states, approach and avoidance responses, as well as memory modulation it
seems likely that the amygdala would be implicated. Although, this learning
paradigm is not termed as a classical fear conditioning task, it does however, have
components of fear conditioning involved. For example, in classical fear
conditioning an animal learns the association between an aversive stimulus and a
neutral stimulus, which it is then conditioned to fear. In this learning paradigm the
mouse first needed to learn the association between shock and a warning signal and
then learn to avoid/escape both by pressing a lever. Several studies suggest that fear
conditioning is dependent on the functioning of the amygdala (Stork et al., 2001;
Savonenko et al., 2003; Paradee et al., 1999; McDonald & Hong, 2004; Yee et al., in
press; Rattiner et al., 2004). Further support of the amygdalas involvement in fear
conditioning comes from LeDoux (2002) and his lab which have found the central
nucleus of the amygdala to have connections with networks that control fear behavior
and associated changes in body physiology. His lab team states that when the lateral
nucleus of the amygdala detects some threatening stimulus, the central nucleus
initiates the expression of defensive behaviors and other bodily behaviors associated
with fear reactivity. Since the KO mice were found to be impaired on this E/A task
(Brennan et al., 2006), it is hypothesized that the amygdala may be dysfunctional in
11


either the encoding of the stimuli (shock) or in the execution of fear-related
behaviors. That is, the KO mouse is not learning to avoid the shock by pressing the
lever because the mouse does not perceive the stimuli as stressful or if it does
perceive it as stressful, this information is not being communicated to the nucleus of
the amygdala that is responsible for proper behavioral responses to the stimulus. If
improper encoding or execution at the amygdala level is occurring, it is predicted that
appropriate neural activity is not occurring.
Neurotrophin involvement is implicated in the amygdala during the
escape/avoidance task as well. It was found that significant BDNF changes were
found in the basolateral amygdala (BLA) two hours after fear conditioning took place
(Rattiner et al., 2004). Furthermore, NGF levels in the amygdala have also been
found to relate to anxiety/fear behavior as seen in mice on the EPM and Conditioned
Freezing paradigms (Yee et al., in press). A more general finding that implicates
potential BDNF involvement is the finding that mice with reduced BDNF expression
have been found to spend more time in the center of an open field (Chourbaji et al.,
2004). This finding is important because as stated previously FMR1 KO mice tend to
spend more time in an open field than do WT mice (Qin et al., 2002; Yan et al.,
2004), which may mean that an increased exploratory drive is found in BDNF-
deficient mice. However, the present study will not focus on the mice involved in a
learning paradigm. Before the mice can be studied using a learning paradigm and
12


more specifically the Escape/Avoidance Learning Task, a baseline neural
measurement of amygdala functioning is needed to compare the FMR1 KO mice to
WT mice.
In order to measure the relative level of neural activity that is occurring within
the amygdala, measurements of BDNF and NGF will be analyzed. As stated above,
these two neurotrophic factors are critically important for synaptic plasticity, the most
widely accepted model for memory changes at the cellular level. Also, BDNF will be
a key measurement since it was found that FMRP is involved in BDNF-induced
synaptic plasticity (Castren et al., 2002). This study will serve as a baseline
measurement of the amygdala before learning has occurred. Therefore, it will
examine whether the MPMS brain regions activity levels differ before learning takes
place. It is hypothesized that baseline measurements between the knock-outs and
wild-type mice will be significantly different, with BDNF and NGF levels being
lower in the FMR1 KO mice as compared to WT mice. This outcome is predicted
due to the impairment found in the KO mice on the E/A learning task (Brennan et al.,
2006). In addition to the analysis of the amygdala, the other brain regions implicated
by the MPMS (White & McDonald, 2002) will also be studied. Therefore, the
hippocampus and dorsal striatum BDNF and NGF levels will also be analyzed.
13


2.
Materials and Methods
2.1 Experimental Subjects
Subjects were male FMR1 KO (N=6) and WT (N=7) mice, derived from C57/BL6J
and bred at the colony at Baylor College of Medicine (Peier et al., 2002). Subjects
were 60-90 days old at the time of sacrifice. All subjects were maintained on a 12:12
light/dark cycle with lights on at 0700. Subjects were group-housed (3-4 to a cage)
and maintained on ad lib food and water.
2.2 Dissection
The frozen mouse brain (-70 F) was placed briefly (approximately 2 minutes) in a -
20 F freezer to let it thaw. At that point the brain was removed and three slices were
taken from it in order to remove the hippocampus, dorsal striatum, and amygdala.
Each slice of tissue was approximately 2 mm in depth. In order to remove the
amygdala bilaterally, a 1 mm diameter tissue punch was utilized. The dorsal striatum
and hippocampus were then removed bilaterally as well using a razor blade. Each
brain region was removed with the guidance of a mouse atlas and following key
landmarks of the brain. These tissue samples were immediately placed in pre-
weighed test tubes and weighed again in order to find each tissue sample weight. Due
to the miniscule size of the amygdala, an average weight was used. This average was
14


calculated by taking 12 punches of tissue in the approximate location of the amygdala
from a few different mouse brains not used in the present study, weighing them, and
taking the average. Since the amygdala was removed bilaterally, each tube contained
two punches; therefore the average weight was multiplied by two in order to come up
with tissue sample weight, which would then later be used to calculate the amount of
solution that would be added when preparing for the BDNF and NGF assays.
2.3 BDNF and NGF Assays
BDNF and NGF protein were measured using ELISA kits (from Promega Corp.,
Madison, WI, USA) according to kit instructions. Briefly, the appropriate brain
region is dissected and tissue homogenized in the following buffer: 0.137 NaCl,
20mM Tris-HCl (pH 8.0), 1% NP40, 10% glycerol, ImM PMSF, 10 microg/ml
aprotinin, 1 microg/ml leupeptin, 0.5 mM Na vanadate. Standard 96 well flat-bottom
NUNC-Immuno maxisorp ELISA plates are incubated with carbonate coating buffer
containing polyclonal anti-BDNF antibody overnight at 4C. The next day, plates are
blocked by incubation for the required time at room temperature with block and
sample buffer. Serial dilutions of known concentrations of BDNF and NGF ranging
from 0-500 pg are performed in duplicate for the standard curve. Brain tissue is
diluted 1:20 w/v, homogenized and centrifuged at 4C at 5000 rpm for 10 min. Wells
are then incubated for 2 h at room temperature. Wells are then washed, and a
15


secondary antibody solution (anti-BDNF or NGF) is added and incubated for another
2 h at room temperature. This step is followed by an anti-human IgG conjugated to
HRP for 1 h at room temperature. A TMB/peroxidase solution develops color in the
wells. This reaction is terminated with acid and the optical density measured at 480
nm in a plate reader. Inter-plate reliability is tested between ELISA plates by
including three randomly chosen samples analyzed on other ELISA plates. Average
recovery levels are also tested by adding known quantities of synthetic BDNF and
NGF to randomly chosen samples and comparing these values to the sample value
alone.
2.4 Statistical Analyses
All analyses were conducted using the statistical software SPSS for Windows
(version 14). BDNF levels and NGF levels were analyzed via independent sample t-
tests (Knockouts vs. Wild-Types) for the amygdala, hippocampus, and dorsal
striatum. These three brain regions were also analyzed using a non-parametric test in
case the data was not normally distributed. Therefore, the Mann-Whitney Test was
utilized.
16


3.
Results
3.1 Neurotrophin Levels
BDNF and NGF levels were analyzed via independent sample t-tests (KO vs. WT)
and the Mann-Whitney Test (KO vs. WT) for each of the three brain regions. BDNF
values and standard deviations are presented in Figure 3.1 and 3.2, while NGF values
and standard deviations are presented in Figure 3.3 and 3.4. In all three brain regions
(amygdala, dorsal striatum, and hippocampus) neither BDNF nor NGF was found to
be significantly different between the KO and WT mice using both the independent
sample t-test and the Mann-Whitney Test. The t-test analysis of the BDNF levels
found hippocampal levels were not significantly different (t=-.664, p=.552); dorsal
striatum not significant (t=.528, p=.609); amygdala not significant (t=.745, p=.474).
For the NGF levels, the hippocampus levels were not significant (t=.623, p=.546);
dorsal striatum not significant (t= 1.339, p=.208); amygdala not significant (t=-.698,
p=.5). According to the Mann-Whitney Test, no significance was found in BDNF
levels or NGF levels in the three brain regions analyzed. In the hippocampus no
significance was found for BDNF (Z=-0.661, p=0.530) or NGF (Z=-0.714, p=0.534);
in the dorsal stratum no significance in BDNF (Z=-1.227, p=0.268) or NGF (Z=-
1.286, p=0.234); and in the amygdala no significance in BDNF (Z=-0.758, p=0.530)
or NGF (Z=-0.429, p=0.731).
17


TX N Mean Std. Deviation Std. Error Mean
BDNF HC KO 5 5.96520 8.687714 3.885264
WT 7 18.37254 40.574817 5.335839
BDNF DS KO 5 5.73660 6.531719 2.921074
WT 7 2.82021 5.996767 2.266565
BDNFAM KO 5 7.39935 8.378324 3.746900
WT 7 2.90186 4.117914 1.556425
Figure 3.1 Basal Descriptive Statistics of BDNF levels (pg/mg) of KO and WT
mice in the Hippocampus (HC), Dorsal Striatum (DS), and Amygdala
(AM)
18


BDNF (pg/mg)
Treatment
Knockout
Wild-Type
30.000H
Error Bars show Mean +/ 1.0 SE
Bars show Means
Dorsal Striatum
Brain Region

Amygdala
Figure 3.2 Basal BDNF (pg/mg) Levels of Wild-Type (WT) Mice versus FMR1
Knock-Out (KO) Mice per Brain Region
19


TX N Mean Std. Deviation Std. Error Mean
NGF HC KO 6 161.11073 96.585817 39.430995
WT 7 125.48970 107.747985 40.724910
NGF DS KO 6 122.25751 81.659496 33.337350
WT 7 66.75296 67.993264 25.699038
NGF AM KO 6 93.19895 60.726010 24.791290
WT 7 123.47603 89.802818 33.942275
Figure 3.3 Basal Descriptive Statistics of NGF levels (pg/mg) of KO and WT
mice in the Hippocampus (HC), Dorsal Striatum (DS), and Amygdala
(AM)
20


NGF (pg/mg)
200.000
150.000
100.000
50.000
0.000
Figure 3.4
Treatment
Knockout
E Wild-Type
Error Bars show Mean +/- 1.0 SE
Bars show Means
Amygdala
Brain Region
Basal NGF (pg/mg) Levels of Wild-Type (WT) Mice versus FMR1
Knock Out (KO) Mice per Brain Region
21


4.
Discussion
The present study examined the basal neural activity as measured by the neurotrophin
levels of BDNF and NGF in the MPMS of wild-type mice as compared to FMR1
knock-out mice. Brain regions that were examined included the hippocampus, dorsal
striatum, and the amygdala. No significant differences were found between the WT
and KO mice in any of the brain regions studied. This experiment demonstrates that
before learning takes place in FMR1 KO mice there are no significant difference in
neurotrophin levels in the amygdala, dorsal striatum, or hippocampus as compared to
WT mice.
4.1 Practical Issues Concerning Methodology
The lack of difference between the two treatment groups may also potentially be due
to errors in experimental design and implementation. Some error could have
occurred in the dissection methods used. Although the lab team made every effort to
keep the procedures as standardized as possible, it is possible that some errors were
made. For example, the team had originally planned on using a brain mold slicer, in
order to dissect at exact coordinates and keep the method as standardized as possible.
However, upon receiving the frozen brains we found that this was not going to be a
practical way to dissect due to the variability between the individual brains sizes and
shapes. Therefore, a fast-paced procedure was developed to take approximately equal
22


size and depth slices of the tissue, before the mouse brain completely thawed and the
integrity of the brain was compromised. A mouse brain atlas was utilized and studied
in order to identify key landmarks when making cuts, but due to the extremely small
sizes of both the amygdala and dorsal striatum, it is quite possible that the cuts and
punches were not always the exact same and/or the exact target region that the team
intended to remove. These potential inconsistencies could lead to greater variability
between the tissue samples and therefore abnormal neurotrophin measures in these
specific regions. Another potential problem could come into play with the extremely
small tissue samples when running the BDNF and NGF assays. In order to run the
assays, the sonnicated tissue samples had to be diluted more than usual in order to
have enough volume of sample for the individual assays. These potential problem
areas may be solved through using a microscope and a different type of sheer that
would allow for closer examination of each cut. Also, it would also be beneficial to
use a microscope in order to make sure that appropriate cuts were made or use
staining of the tissue to make sure that each region has the targeted proteins to be
analyzed.
One other issue concerning the amygdala and its removal concerns the
nucleus that was removed. In the dissection, an area was removed which was thought
to have the most amygdala nuclei, which could potentially flaw the data. That is, it
has been found that only specific nuclei of the amygdala would be implicated in an
23


activity involving fear conditioning, therefore if more than one nucleus was taken,
then the activity level as measured by neurotrophin levels may be invalid. As was
mentioned earlier, the central nucleus connects with other networks that control fear
behavior and physiology, while the lateral nucleus is the input zone and is where
information from various senses is sent that are monitoring the world for threatening
stimuli (LeDoux, 2002). Another finding supporting the isolation of specific nuclei is
the fact that in BDNF changes after fear conditioning, significant changes were found
in the basolateral nucleus of the amygdala, but not the nucleus of the medial
amygdala (Rattiner et al., 2004). Therefore, if the amygdala sample contained more
than one nucleus then this would make these tissue samples void. In future studies, it
is of the utmost importance to isolate the specific target nucleus to guard against this
type of error.
4.2 Future Implications
Although these results did not support the initial hypothesis, it is possible that
changes in neurotrophin levels, which are a marker of regional neural plasticity, do
not occur until learning of the E/A paradigm begins. This conclusion is based on
various findings which examined neurotrophin measures in both WT mice and FMR1
KO mice. For example, BDNF levels appear to be affected by Fragile X Syndrome
as noted by Castren et al. (2002), whom found FMRP to be involved in BDNF
24


mediation of synaptic plasticity. Additionally, the findings that in an E/A learning
paradigm, rats that experienced this type of conditioning had significantly higher
levels of both BDNF and NGF in the hippocampus compared to those not trained
(Albeck et al., 2005). Although this group did not find significant differences in the
dorsal striatum, their experiment still shows that this specific learning paradigm does
alter neurotrophin levels. Also, since a behavioral difference was noted by Brennan
et al. (2006), demonstrating a deficit in the KO mice, it seems possible that the true
differences in neural activity do not come into play until the specific learning and
memory systems are called on to perform. Furthermore, the dorsal striatum may also
still be implicated although it was not found to be activated differently by Albeck et
al. (2005), because White & McDonald (2002), state that rats with dorsal striatum
lesions are impaired on several tasks involving escape and avoidance responses. The
last region in the MPMS model, the amygdala, has been implicated as dysfunctional
by Paradee et al. (1999) when this team found KO mice to exhibit less freezing both
during contextual and cued fear conditions. Taken together, it still makes sense to
take this study a step further and examine what happens to the targeted MPMS
regions after these animals are trained in the E/A learning paradigm as compared to
the basal measurements.
However, one problem that may exist when studying these three different
brain regions in the same learning paradigm is the time lag between when learning
25


takes place and when the animal is sacrificed. This time period is crucial because it is
the time in which protein synthesis of new, higher levels of the neurotrophin proteins
that is stimulated by the specific type of learning. The problem comes about between
optimal times of lag time for hippocampus protein synthesis and lag time for
amygdala protein synthesis. In the E/A learning paradigm (Albeck et al., 2005), the
lag time was one hour, however in previous studies looking at the amygdala optimal
lag time (Rattiner et al, 2004; Ressler et al., 2002) was shown to be two hours. In
order to get around this problem more studies will be needed to explore the optimal
lag time for each of the brain regions or more animals will be needed in order to study
one brain region per animal.
Another possibility is that instead of a deficit in neurotrophin levels, there
may actually be an excessive amount in FMR1 KO mice versus WT. If this is the
case, then the finding of a significant bilateral increase in volume of the hippocampus
in FMR1 KO versus WT mice makes sense (Reiss et al., 1994). The greater volume
of the hippocampus would also help in the explanation of anxiety being a common
symptom in human Fragile X Syndrome, since high-anxiety related behavior has
been shown to correlate with an increase in hippocampal volume (Yee et al., in
press). As far as studies looking at neurotrophin measures, Albeck et al. (2005) state
that excessive BDNF impairs avoidance learning. Therefore, it may make sense that
the FMR1 KO mice have higher neurotrophin levels than their WT counter-parts and
26


this may then explain the deficits observed in the E/A learning paradigm (Brennan et
al., 2006).
Since the E/A learning paradigm has an element of fear conditioning, the
stress induced by fear of shock may alter neurotrophin levels. Its been demonstrated
that stress alters BDNF, with an increase in the amygdala (Govindarajan et al., 2006)
and a decrease in the hippocampus (McEwen & Sapolsky, 1995 as cited in
Govindarajan et al., 2006) and reduces NGF (von Richthofen et al., 2003). The stress
induced alterations may interact with any learning-induced increases in neurotrophin
levels.
27


REFERENCES
Albeck, D.S., Backman, C., Veng, L., Friden, P., Rose, G.M. & Granholm, A.-C.E.
(1999). Acute application of NGF increases the firing rate of aged rat basal
forebrain neurons. European Journal of Neuroscience 11, 2291-2304.
Albeck, D. S., Beck, K. D., Kung, L., Sano K. & Brennan, F. X. (2005). Leverpress
Escape/Avoidance Training Increases Neurotrophin Levels in Rat Brain.
Integrative Physiological and Biological Sciences 40(1), 28-34.
Bear, M.F., Huber, K.M. & Warren, S.T. (2004). The mGluR theory of fragile X
mental retardation. TRENDS in Neuroscience 27(7), 370-377.
Brennan, F. X. (2004). Genetic differences in leverpress escape/avoidance
conditioning in seven mouse strains. Genes, Brain and Behavior 3, 110-114.
Brennan, F. X., Albeck, D. S. & Paylor, R. (2006). FMR1 knockout mice are
impaired in a leverpress escape/avoidance task. Genes, Brain and Behavior
5(6), 467-471.
Castren, M., Lampinen, K. E Miettinen, R., Koponen, E., Sipola, I., Bakker, C. E
Oostra, B. A. & Castren, E. (2002). BDNF regulates the expression of Fragile
X Mental Retardation Protein mRNA in the hippocampus. Neurobiology of
Disease 11, 221-229.
Chourbaji, S., Hellweg, R., Brandis, D., Zorner, B., Zacher, C., Lang, U.E., Henn,
F.A., Hortnagl, H. & Gass, P. (2004). Mice with reduced brain-derived
neurotrophic factor expression show decreased choline acetyltransferase
activity, but regular brain monoamine levels and unaltered emotional
behavior. Molecular Brain Research 121, 28-36.
Govindarajan, A., Shankaranarayana Rao, B.S., Nair, D., Trinh, M., Mawjee, N.,
Tonegawa, S. & Chattarji, S. (2006). Transgenic brain-derived neurotrophic
factor expression causes both anxiogenic and antidepressant effects.
Proceedings of the National Academy of Sciences of the United States of
America 103(35), 13208-13213.
28


Gruss, M. & Braun, K. (2004). Age- and region-specific imbalances of basal amino
acids and monoamine metabolism in limbic regions of female Fmrl knock-out
mice. Neurochemistry International 45, 81-88.
Isacson, O., Seo, H., Lin, L., Albeck, D. & Granholm, A.-C. (2002). Alzheimers
disease and Downs syndrome: roles of APP, trophic factors and ACh.
TRENDS in Neuroscience 25(2), 79-84.
LeDoux, J. (2002). Synaptic Self: How Our Brains Become Who We Are. New York,
NY: Penguin Books.
Liu, I.Y.C., Lyons, W.E., Mamounas, L.A. & Thompson, R.F. (2004). Brain-Derived
Neurotrophic Factor Plays a Critical Role in Contextual Fear Conditioning.
Journal of Neuroscience 24(36), 7958-7963.
McDonald, R. J. & Hong, N. S. (2004). A dissociation of dorso-lateral striatum and
amygdala function on the same stimulus-response habit task. Neuroscience
124, 507-513.
Mineur, Y. S., Sluyter, F., de Wit, S., Oostra, B. A. & Crusio, W. E. (2002).
Behavioral and neuroanatomical characterization of the Fmrl knockout
mouse. Hippocampus 12(1), 39-46.
Nimchinsky, E.A., Oberlander, A.M. & Svoboda, K. (2001). Abnormal Development
of Dendritic Spines of FMR1 Knock-Out Mice. The Journal of Neuroscience
21(14), 5139-5146.
Paradee, W., Melikian, H. E., Rasmussen, D. L., Kenneson, A., Conn, P. J. & Warren,
S. T. (1999). Fragile-X mouse: strain effects of knockout phenotype and
evidence suggesting deficient amygdala function. Neuroscience 94, 185-192.
Peier, A. M., Mcllwain, K. L., Kenneson, A., Warren, S. T., Paylor, R. P. & Nelson,
D. L. (2002). (Over)correction of FMR1 deficiency with YAC transgenics:
mice: behavioral and physical features. Human Molecular Genetics 9, 1145-
1159.
29


Qin, M., Kang, J. & Smith, C. B. (2002). Increased rates of cerebral glucose
metabolism in a mouse model of fragile X mental retardation. Proceedings of
the National Academy of Sciences of the United States of America 99, 15758-
15763.
Ranum, L. P. W. & Day, J. W. (2004). Pathogenic RNA repeats: an expanding role
in genetic disease. Trends in Genetics 20(10), 506-512.
Rattiner, L.M., Davis, M., French, C.T. & Ressler, K. (2004). Brain-Derived
Neurotrophic Factor and Tyrosine Kinase Receptor B Involvement in
Amygdala-Dependent Fear Conditioning. Journal of Neuroscience 24(20),
4796-4806.
Reiss, A.L., Lee, J. & Freund, L. (1994). Neuroanatomy of fragile-X syndrome: the
temporal lobe. Neurology 44(7), 1317-1324.
Ressler K.J., Paschall G., Zhou X.L. & Davis M. (2002). Regulation of synaptic
plasticity genes during consolidation of fear conditioning. Journal of
Neuroscience 22, 7892-7902.
Rosenzweig, M.R., Breedlove, S.M. & Leiman, A.L. (2002). Biological Psychology:
An Introduction to Behavioral, Cognitive, and Clinical Neuroscience. (3rd
ed.). Sunderland, MA: Sinauer Associates, Inc.
Savonenko, A., Werka, T., Nikolaev, E., Zielinski, K. & Kaczmarek, L. (2003).
Complex effects of NMDA receptor antagonist APV in the basolateral
amygdala on acquisition of two-way avoidance reaction and long-term fear
memory. Learning and Memory 10(4), 293-303.
Schinder, A. F. & Poo, M. M. (2000). The neurotrophin hypothesis for synaptic
plasticity. TRENDS in the Neurosciences 23, 639-645.
Stork, O., Stork, S., Pape, H. C. & Obata, K. (2001). Identification of genes
expressed in the amygdala during the formation of fear memory. Learning
and Memory 8(4), 209-219.
The Dutch-Belgian Fragile X Consortium (1994). Fmrl knockout mice: A model to
study fragile X mental retardation. Cell 78, 23-33.
30


Turner, G., Webb, T., Wake, S. & Robinson, H. (1996). Prevalence of fragile X
syndrome. American Journal of Human Genetics 64, 196-197.
Ventura, R., Pascucci, T., Catania, M. V., Musumeci, S. A. & Puglisi-Allegra, S.
(2004). Object recognition impairment in Fmrl knockout mice is reversed by
amphetamine: involvement of dopamine in the medial prefrontal cortex.
Behavioral Pharmacology 15, 433-442.
Von Richthofen, S., Lang, U.E. & Hellweg, R. (2003). Effects of different kinds of
acute stress on nerve growth factor content in rat brain. Brain Research
987(2), 207-213.
White, N. M. & McDonald, R. J. (2002). Multiple parallel memory systems in the
brain of the rat. Neurobiology of Learning and Memory, 77, 125-184.
Yamada, K. & Nabeshima, T. (2003). Brain-derived neurotrophic factor / trkB
signaling in memory processes. Journal of Pharmacological Sciences 91,
267-270.
Yan, Q. J., Asafo-Adjei, P. K., Arnold, H. M., Brown, R. E. & Bauchwitz, R. P.
(2004). A phenotypic and molecular characterization of the fmrl-tmlCgr
Fragile X mouse. Genes Brain and Behavior 3, 337-359.
Yee, B.K., Zhu, S.-W., Mohammed, A.H. & Feldon, J. (in press). Levels of
neurotrophic factors in the hippocampus and amygdala correlate with anxiety-
and fear-related behavior in C57BL6 mice. Journal of Neural Transmission.
31