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The Functional Integration of Adult-born
Granule Cells into Dentate Gyrus Circuitry
Aneta Dominika Krakowski
A thesis submitted in conformity with the requirements
for the degree of
Master of Science, Institute of Medical Science
University of Toronto
© Copyright by Aneta Dominika Krakowski 2010
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The Functional Integration of Adult-born Granule Cells
into Dentate Gyrus Circuitry
Aneta Dominika Krakowski
Master of Science, Institute of Medical Science
University of Toronto
2010
ABSTRACT
New neurons are generated throughout adulthood in the dentate gyrus of the
hippocampus. The aim of the current study was to address whether differences in the
morphological complexity of adult-born granule cells affect their integration into existing
dentate gyrus circuitry. To selectively label proliferating cells, we injected a CAG-
retrovirus into the dentate gyrus of mice. Either 10, 20, 40, or 80 days following viral
infection, mice were injected with pentylenetetrazol (PTZ) to induce hippocampal
activation, and expression of the immediate early gene c-fos was used as a marker of
activated neurons. We then compared morphological features of neurons across age
groups and between Fos+ and Fos- neurons within each age group. We found that
dendritic length and branch number increased from 10 to 20 days post infection.
Unexpectedly, we also found that dendritic length and branch number decreased from 20
to 40 days post infection, suggesting that the maturation of adult-generated neurons is
associated with an active pruning process. Furthermore, we found no significant
differences in morphological complexity between Fos+ and Fos- neurons, suggesting that
dendritic morphology does not influence integration into dentate gyrus circuitry.
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ACKNOWLEDGEMENTS
This project would not have been possible without the assistance of many individuals.
First, I would like to thank my supervisor Dr. Paul Frankland for his constant guidance
and support. I would also like to thank my project advisory committee members Dr. José
Nobrega and Dr. Vince Tropepe and for their feedback on my project.
From the Frankland lab, I would like to thank Maithe-Arruda Carvalho, Mansori
Sakaguchi, and Mika Yamamoto for retroviral production. I would also like to thank
Alonso Martinez Canabal and Leonardo Restivo for providing assistance with histology,
imaging, and data analysis. Also, thanks to Toni DeCristofaro and Russell Braybon for
animal breeding and technical support. Finally, thanks to Katherine Akers for comments
on previous drafts of this thesis.
This project was funded by CIHR and NSERC.
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TABLE OF CONTENTS
LITERATURE REVIEW ................................................................................................ 1
1.1 Introduction to adult neurogenesis ..................................................................................... 1
1.2 Hippocampus ............................................................................................................................ 2
1.2.1 Anatomy and connectivity ................................................................................................ 2
1.2.2 Functional role .................................................................................................................... 3
1.3 Dentate Gyrus .............................................................................................................................. 4
1.3.1 Anatomy and connectivity ...................................................................................................... 4
1.3.2 Functional role of the dentate gyrus .............................................................................. 5
1.4 Labeling adult-born granule cells .......................................................................................... 8
1.4.1 Incorporation of nucleotide analogs ............................................................................. 8
1.4.2 Expression of specific markers ........................................................................................ 8
1.4.3 Retroviral-labeling .............................................................................................................. 9
1.5 Development of Dentate Granule Cells ............................................................................ 10
1.5.1 Embryogenesis and early post-natal period ................................................................ 11
1.5.2 Adulthood............................................................................................................................ 12
1.6. Factors affecting proliferation and survival of adult-born granule cells .................. 14
1.6.1 Genetic Influences ............................................................................................................ 15
1.6.2 Extrinsic influences .......................................................................................................... 15
1.7 Mechanisms of neuronal migration, morphological development, and spine
formation ............................................................................................................................................. 16
1.7.1 Neuronal migration ......................................................................................................... 16
1.7.2 Growth of axons and dendrites .................................................................................... 17
1.7.3 Spine formation ................................................................................................................. 18
1.8 Anatomical Integration of Granule Cells during adulthood and early-postnatal
development ....................................................................................................................................... 18
1.8.1 Migration ............................................................................................................................ 18
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1.8.2 Passive membrane properties ...................................................................................... 19
1.8.3 The growth of axons and dendrites ............................................................................. 19
1.8.4 Afferent connections ........................................................................................................ 20
1.8.5 Efferent connections ........................................................................................................ 21
1.9 Functional integration of adult-born granule cells .......................................................... 22
1.9.1 Physiological maturation of adult-born granule cells .......................................... 22
1.9.2 Immediate-early gene (IEG) expression .................................................................... 23
1.9.2.1 Correlation between IEG expression and neuronal activation .................... 23
1.9.2.2 Role of IEG s in memory ....................................................................................... 24
1.9.2.3 IEG activation in adult-born cells following neuronal stimulation ........... 24
1.10 Factors affecting morphological development of neurons during embryogenesis
and early-postnatal development .................................................................................................. 26
1.10.1 Transcription factors ...................................................................................................... 26
1.10.2 Extrinsic factors ............................................................................................................... 26
1.10.3 Activity-dependent regulation ..................................................................................... 27
1.10.3.1 Spontaneous activity .............................................................................................. 27
1.10.3.2 Afferent-dependent activity ................................................................................. 27
1.11 Factors affecting anatomical and functional maturation of adult-born granule
cells ....................................................................................................................................................... 28
1.11.1 Extrinsic signals ............................................................................................................. 29
1.11.2 Activity-dependent regulation .................................................................................... 31
1.11.2.1 Afferent-independent activity regulation – GABA ..................................... 31
1.11.2.2 Afferent-dependent activity regulation ........................................................... 32
AIMS AND HYPOTHESES .......................................................................................... 34
2.1 Study Rationale ......................................................................................................................... 34
2.2 Experimental design ................................................................................................................ 35
2.3 Specific aims and hypotheses................................................................................................ 36
MATERIALS AND METHODS ................................................................................... 37
3.1 Subjects and stereotaxic surgery .......................................................................................... 37
3.2 Retroviral-mediated labeling of adult-born neurons in the mouse hippocampus .. 37
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3.3 Seizure induction ....................................................................................................................... 38
3.4 Tissue preparation ...................................................................................................................... 38
3.5 Immunohistochemistry ............................................................................................................ 39
3.6 Identification of GFP+ Fos+ cells ........................................................................................ 40
3.7 Dendritic properties ................................................................................................................... 40
3.7.1 Sholl analysis ..................................................................................................................... 41
3.7.2 Branch order analysis ..................................................................................................... 42
3.7.3 Branch thickness ............................................................................................................... 43
3.8 Spine Properties ........................................................................................................................ 43
3.8.1 Spine and mushroom spine density ............................................................................. 44
3.9 Statistics ........................................................................................................................................ 45
RESULTS ........................................................................................................................ 47
4.1 Adult-born granule cells mature with age ......................................................................... 47
4.2 Dendritic morphology of adult-born granule cells changes with age ........................ 51
4.3 Spine density of adult-born granule cells changes with age ........................................ 55
4.4 Seizure induction activates Fos ............................................................................................ 57
4.5 Proportion of GFP+ cells expressing Fos increases with age ...................................... 58
4.6 Dendritic morphology does not differ between Fos+ and Fos– neurons within
groups ................................................................................................................................................... 60
4.7 Spine density between Fos+ and Fos– neurons does not differ within groups ....... 64
DISCUSSION .................................................................................................................. 66
5.1 Maturation of adult born-granule cells ............................................................................... 66
5.1.1 Dendritic morphology of adult-born granule cells changes with age .............. 66
5.1.2 Spine density across age groups .................................................................................. 66
5.1.3 Dendritic pruning during embryogenesis and adult neurogenesis .................... 67
5.1.4 Mechanisms of dendritic pruning in adult-born granule cells ............................ 68
5.1.5 The significance of dendritic pruning in adult-born cells .................................... 69
5.1.6 Alternative explanation for pruning............................................................................ 71
5.2 Functional integration of adult-born cells into dentate gyrus circuitry ..................... 72
5.3 Morphological differences between Fos+ and Fos- neurons ....................................... 72
5.3.1 Examining morphological differences between Fos+ and Fos- neurons shortly
before or after 20 days of age ................................................................................................... 73
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5.3.2 Differences in hippocampal stimulation following seizures and learning tasks
........................................................................................................................................................... 74
5.3.3 Dendritic computational properties ............................................................................ 75
5.4 Technical limitations ............................................................................................................... 76
5.4.1 Dendritic morphology analysis .................................................................................... 76
5.4.2 Spine morphology analysis ............................................................................................ 77
5.4.3 Surgery ................................................................................................................................ 77
FUTURE DIRECTIONS ................................................................................................ 79
6.1 Does afferent activity induced by learning affect the pruning of adult-born granule
cells? ..................................................................................................................................................... 79
6.2 Do differences in dendritic morphology and spine density at or before 20 days of
age affect functional integration into dentate gyrus circuitry following PTZ seizures?
................................................................................................................................................................ 83
6.3 Do differences in dendritic morphology affect functional integration into dentate
gyrus memory networks? ................................................................................................................ 84
CONCLUSIONS ............................................................................................................. 87
REFERENCES ................................................................................................................ 89
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LIST OF FIGURES
Figure 1.1: The hippocampal trisynaptic circuit ................................................................3
Figure 1.2: Dentate gyrus structure ....................................................................................5
Figure 1.3: Development of the dentate gyrus ................................................................12
Figure 1.4: Developmental stages during mitotic and post-mitotic neurogenesis ...........14
Figure 2.1: Experimental design ......................................................................................35
Figure 3.1: CAG-retrovirus production ...........................................................................38
Figure 3.2: Sholl analysis .................................................................................................41
Figure 3.3: Branch order analysis ....................................................................................43
Figure 4.1: Dendritic morphology of adult-born granule cells at 10 dpi. ....................... 46
Figure 4.2: Dendritic morphology of adult-born granule cells at 20 dpi .........................47
Figure 4.3: Dendritic morphology of adult-born granule cells at 40 dpi .........................48
Figure 4.4: Dendritic morphology of adult-born granule cells at 80 dpi .........................49
Figure 4.5: Sholl analysis for the number of a, intersections and b, dendritic length at 10,
20, 40, and 80 dpi ...............................................................................................................50
Figure 4.6: Branch order analysis for the number of dendrites at 10, 20, 40, and 80 dpi 53
Figure 4.7: Branch order analysis for branch thickness at 20, 40, and 80 dpi .................54
Figure 4.8: Spine analysis at 20, 40, and 80 dpi ..............................................................55
Figure 4.9: Fos expression in the dentate gyrus following PTZ induced seizures ..........56
Figure 4.10: Fos expression in the dentate gyrus following PTZ induced seizures ......... 57
Figure 4.11: The proportion of GFP cells positive for Fos following PTZ induced seizures
at 10, 20, 40, and 80 dpi .....................................................................................................58
Figure 4.12: Sholl analysis for the number of a, intersections and b, dendritic length in
Fos+ and Fos- neurons at 20 dpi ........................................................................................60
Figure 4.13: Sholl analysis for the number of a, intersections and b, dendritic length in
Fos+ and Fos- neurons at 40 dpi ........................................................................................61
Figure 4.14: Sholl analysis for the number of a, intersections and b, dendritic length in
Fos+ and Fos- neurons at 80 dpi ........................................................................................62
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Figure 4.15: Spine density between Fos+ and Fos- neurons at a, 20 dpi; b, 40 dpi, and c
80 dpi. ................................................................................................................................63
Figure 4.16: Mushroom spine density between Fos+ and Fos- neurons at a, 20 dpi; b, 40
dpi, and c, 80 dpi. ..............................................................................................................64
Figure 6.1: Experimental design for investigating the effects of activity induced by
learning on pruning. ...........................................................................................................80
Figure 6.2: Experimental design for examining morphological correlates of functional
integration following PTZ induced seizures. .....................................................................82
Figure 6.3: Experimental design for investigating morphological correlates of functional
integration into a spatial memory network ........................................................................83
Figure 6.4: The YFP construct before and after Cre-mediated recombination ................84
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LIST OF ABBREVATIONS
ANOVA analysis of variance
AMP adenosine monophosphate
AMPA α-amino-3-hydroxyl-5-methyl-4-isoxazole-propionate
BDNF brain derived neurotrophic factor
BrdU 5-bromo-2-deoxyuridine
Cdk5 cell division protein kinase 5
CREB- cAMP (adenosine monophosphate)-responsive element modulator
DCX doublecortin
DG- dentate gyrus
DISC1 disrupted-in-Schizophrenia 1
DNA deoxyribonucleic acid
dpi days post infection
E embryonic day
Ec entorhinal cortex
EGFP enhanced green fluorescent protein
fMRI functional magnetic resonance imaging
GABA γ-Aminobutyric acid
GCL granule cell layer
GFP green fluorescent protein
GTPses GTP (guanosine 5‘-triphosphatase)-activating proteins
IEG immediate early gene
IGF insulin-like growth factor
i.p. intraperitoneal
KA kainic acid
LTP long-term potentiation
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MAM methylazoxymethanol
ML molecular layer
mEPSP minature excitatory post-synaptic potential
NMDA N-methyl-D-aspartate
NR2B NMDA receptor 2B
PBS phosphate-buffered saline
PFA paraformaldehyde
POMC proopiomelanocortin
PTZ pentylenetetrazol
RNA ribonucleic acid
Sb subicular complex
Sc Schaffer collateral
Sdm secondary dentate matrix
SDS sodium dodecyl sulfate
shRNA short hairpin (Ribonucleic acid )RNA
Tdm tertiary dentate matrix
TrkB tropomyosine related kinase
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LITERATURE REVIEW
1.1 Introduction to adult neurogenesis
For a long time, it was thought that the formation of new neurons was limited to
embryonic and early postnatal development and that the adult human brain had little or
no capacity to generate new neurons. Neuronal plasticity was believed to be limited to
changes in synaptic reorganization and in gene transcription. In the 1990s, this belief was
overturned when it was discovered that in two regions of the brain new neurons are
continuously generated throughout the lifetime of humans (Eriksson et al. 1998; Gage et
al., 2000). The first region is the subventricular zone of the lateral ventricles. From here,
new neurons migrate along the rostral migratory stream to settle in the olfactory bulb.
The second region is the dentate gyrus of the hippocampus.
Since its discovery in the human brain, adult neurogenesis has spurred a great deal of
excitement in the scientific community and significant efforts have been made towards
identifying factors that regulate adult-born cell maturation. However, our understanding
of the functional integration and functional contribution of adult-born neurons to the adult
brain, especially to the dentate gyrus, is still in its infancy. An understanding of adult
neurogenesis on the functional level is critical towards harnessing its potential as a source
of regenerative therapy for individuals suffering from brain damage, such as dementia.
Without understanding how these neurons function or what factors promote their
functional integration, we cannot possibly move forward with using them for clinical
therapy.
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Interestingly, various neuropathological states such as stress and depression have been
associated with reduced neurogenesis (Sahay and Hen, 2007; Mirescu and Gould, 2006).
Whether reduced neurogenesis is a cause or consequence of neuropathology is unknown.
A greater understanding of adult-born neurons on a functional level will help us advance
our knowledge of these neurological disorders and develop more effective treatments.
Overall, it is believed that newly-generated neurons in the adult brain allow for a unique
form of structural plasticity, specifically in learning and memory. As the dentate gyrus is
important for a variety of learning and memory tasks, I will focus on neurogenesis in this
area.
1.2 Hippocampus
1.2.1 Anatomy and connectivity
The mammalian hippocampus is compromised of four anatomically distinct areas: the
entorhinal cortex, the subicular complex, the hippocampus proper (subdivided into CA1,
CA2 and CA3) and the dentate gyrus (Amaral and Witter, 1989).
Although there are several reciprocal connections, the circuitry of the hippocampus is
mostly unidirectional and forms the trisynaptic circuit (Amaral and Witter, 1989) (Figure
1.1). The entorhinal cortex projects to the dentate gyrus via the perforant pathway. The
granule cells of the dentate gyrus project their output to CA3 via mossy fibers, and CA3
pyramidal cells project to CA1 via the Schaffer collateral pathway. CA1 cells project to
the subicular complex, and then output from the subicular complex projects back to the
entorhinal cortex closing the circuit.
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Figure 1.1: The hippocampal trisynaptic circuit.The entorhinal cortex (EC) projects to the
dentate gyrus (DG) via the perforant pathway. The granule cells of the DG project to
CA3 via mossy fibers. CA3 pyramidal cells project to CA1 via the Schaffer collateral
pathway (SC). CA1 cells project to the subicular complex (Sb), which then projects back
to the entorhinal cortex. This closes the circuit.
It is important to note that input from the entorhinal cortex can bypass the dentate gyrus
through direct projections to other areas (Amaral and Witter, 1989). There are direct
connections from the second layer of the entorhinal cortex to CA3 and from the third
layer of the entorhinal cortex to CA1.
1.2.2 Functional role
Historically, the role of the hippocampus was inferred from lesion studies in human
patients. One of the most famous patients (H.M.) was examined by Milner (1968). H.M
had bilateral lesions of the medial temporal lobe, which contained the hippocampus, and
showed evidence of anterograde amnesia (the ability to form new memories) and some
retrograde amnesia (ability to remember events before the surgery that caused the lesion).
Since H.M., various behavioural, electrophysiological, and imaging studies have
provided support for the idea that the hippocampus is important for the encoding and
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retrieval of memories for facts and events (Squire et al., 2004). Many other theories
regarding hippocampal function have also emerged. Another major theory focuses on the
role of the hippocampus in spatial memory and the formation of cognitive maps (O‘Keefe
and Nadel, 1978). Today, the specific contribution of the hippocampal formation remains
a matter of debate, although most experts agree that it plays a role in associative memory
(Richard, 2006).
Using a computational model, Rolls and Kesner (2006) have teased apart the role of these
different subregions. They propose that the dentate gyrus generally serves as the input
layer. Its main role is to remove redundant information and separate overlapping or very
similar input. The CA3 region encodes associations. Associations allow a whole memory
to be retrieved upon the presentation of only a single cue relevant to the memory. Finally,
the CA1 region provides an output function. It retrieves information and forwards it to
the cortex for processing.
1.3 Dentate gyrus
1.3.1 Anatomy and connectivity
The dentate gyrus is a laminated structure composed of three layers: the molecular layer
(ML), the granule cell layer (GCL) and the hilus (Amaral et al., 2007). In the interface
between the GCL and the hilus lies the subgranular zone (SGZ) (Figure 1.2). The granule
cell layer has the greatest number of cells among all three layers. In the dentate gyrus of
an adult mouse, there are approximately 240 000 granule cells (Kempermann et al.,
1998).
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Figure 1.2: Dentate gyrus structure. The dentate gyrus consists of three layers: the
molecular layer (ML), the granule cell layer (GCL) and the hilus. The subgranular zone
(SGZ) lies between the hilus and GCL. This is where adult-born granule cells are formed.
Cell nuclei are stained with Hoechst and are seen in blue.
Dendrites in the outer third of the molecular layer receive input from the lateral
entorhinal area, whereas dendrites in the middle third of the molecular layer receive input
from the medial entorhinal area (Amaral et al., 2007). This input is primarily
glutamatergic. Granule cells also receive inhibitory GABAergic input from interneurons,
mostly those lying in the hilus (Amaral and Witter, 1995). The axons of granule cells
target interneurons of the hilus, primarily mossy cells, and pyramidal cells of the CA3
region (Amaral and Dent, 1981; Seress and Ribak, 1995). These contacts are primarily
glutamatergic (Jonas et al., 1993).
1.3.2 Functional role of the dentate gyrus
One of the main roles attributed to the dentate gyrus is pattern separation. Approximately
200, 000 cells from the entorhinal cortex project to over one million cells in the dentate
gyrus of the rat (Amaral et al., 1990), undoubtedly giving rise to the theory that the
dentate gyrus separates information. This theory has been supported by many studies. For
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example, a recent animal study found impairments in contextual discrimination upon
deletion of NMDA receptors in the dentate gyrus (McHugh et al., 2007). Additionally, a
study in humans found that brain activity (as measured by fMRI) was highest in the
dentate gyrus during a pattern separation task (Bakker et al., 2008).
1.3.3 The functional role of adult-born granule cells
Soon after neurogenesis was discovered in the dentate gyrus, the quest for its functional
significance began. To examine the role of adult-born neurons in memory function,
studies have ablated neurogenesis using approaches such as gamma irradiation,
antimitotic agents such as methylazoxymethanol acetate (MAM), and genetic
manipulation. The results of ablation on hippocampal-dependent tasks have been
inconsistent. Some studies have found that ablating neurogenesis leads to impairments in
water maze performance (Rola et al., 2004; Synder et al., 2005), contextual fear
conditioning (Winocur et al., 2006; Saxe et al., 2007) and object recognition (Winocur et
al., 2006). Other studies, however, have not found any effects of ablation on behaviour in
identical tasks (Shors et al., 2002; Bruel-Jungerman et al., 2005; Saxe, 2006).
These discrepancies likely result from differences in the behavioural procedures and
ablation approaches used (Zhao et al., 2008 b). For example, Winocur and colleagues
(2006) found that neurogenesis ablation resulted in impairments in fear conditioning
when the task involved pairing the shock with contextual cues. On the contrary, fear
conditioning was not impaired following neurogenesis ablation when a homogenous
chamber was used and contextual discrimination was not required (Shors et al., 2002).
Similarly, contextual fear memories were affected by neurogenesis ablation when the
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neurons ablated where at least six weeks old (Saxe et al. 2006; Winocur et al. 2006; Saxe
et al. 2007), but not when the neurons affected were less than 12 days old (Shors et al.,
2002).
Recently, progress has been made in examining the effect of ablating neurogenesis on
behavioural tasks that specifically target the dentate gyrus, rather than the hippocampus
as a whole. In a recent study, Clelland and colleagues (2009) found that mice with
ablated neurogenesis were impaired in spatial discrimination tasks with little spatial
separation, but not in spatial discrimination tasks that were more widely separated.
Computational models have proposed specific roles for adult-born neurons in pattern
separation. Aimone and colleagues (2009) suggested that adult-born neurons allow
distinct events occurring at the same time to be integrated. Neurons born at different
times then provide temporal separation of the events. For example, granule cells born
around the same time would help recall events that occurred during a high school trip to
Europe while another set of granule cells would help recall events occurring during a
college internship. Becker and colleagues (2009) proposed a very similar model to
Aimone and colleagues (2009), and predicted that adult-born neurons help distinguish
between similar events that occur at different times. For example, adult-born neurons
would help an individual distinguish between where they parked their car on Monday and
where they parked their car on Sunday.
It is clear that the contribution adult-born granule cells make to dentate gyrus circuitry is
complex. To help us better understand this contribution, we need to devote more effort
towards understanding how these adult-born neurons develop, specifically how they
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anatomically and functionally integrate into dentate gyrus circuitry. This will help us
determine any unique properties that characterize these neurons and therefore generate a
better framework towards understanding their function in the dentate gyrus.
1.4 Labeling adult-born granule cells
1.4.1 Incorporation of nucleotide analogs
The first approach used to identify adult-born granule cells involved the use of [3H]
thymidine by Altman and colleagues (1965). [3H] thymidine incorporates into the DNA
of dividing cells during the S phase of the cell cycle and is passed onto the cell‘s progeny.
By varying the time of examination from the time of injection, newly-generated cells can
be detected at various points of their maturation. To detect [3H] thymidine,
autoradiographic methods are used. In 1989, Nowakowski and colleagues introduced 5-
bromo-2-deoxyuridine (BrdU) labeling to identify new-born cells. BrdU is an analog of
thymidine, and because it can be detected using immunohistochemistry it provides the
opportunity to label adult-born cells with other histological markers and therefore to
phenotype cells. The limitations with both [3H] thymidine and BrdU labelling are that the
tissue needs to be fixed (therefore live cells cannot be analyzed) and labeling is limited to
the cell nucleus. Furthermore, these analogs can incorporate into cells undergoing DNA
repair.
1.4.2 Expression of specific markers
During their development, adult-born granule cells display specific markers at varying
points during their maturation (Kempermann et al., 2004). One can take advantage of
these markers by developing transgenic mice that express genes of interest (ie. Green
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Fluorescent Protein - GFP) under the control of a desired marker that acts as a promoter.
For example, adult mice can express GFP under the control of a nestin promoter to label
neurons very early during their development (Yamaguchi et al., 2000). Similarly,
Overstreet and colleagues (2004) developed mice with enhanced green florescent protein
(EGFP) driven by a proopiomelanocortin (POMC) promoter, which is transiently
expressed in immature, but differentiated, neurons. The main concerns with the use of
this method are that adult-born cells can only be labeled at transient intervals during their
development.
1.4.3 Retroviral-labeling
The use of retroviruses for labeling adult-born cells is particularly useful as it allows
long-term expression of a transgene, such as GFP, throughout the neuron. This allows
researchers to characterize the morphological and physiological features of adult-born
cells throughout their development.
In order to express their genome, retroviruses must integrate into a host cell and use the
cell‘s machinery to generate double-stranded DNA from their RNA. Oncoretroviruses,
such as the Moloney murine leukemia virus, can only enter the nucleus of a host cell once
it is broken down, since they lack nuclear import mechanisms (Lewis and Emermann,
1994). This characteristic makes such retroviruses useful for labeling newly-generated
cells. When the nucleus envelope of a dividing cell breaks down during prometaphase,
oncoretroviruses enter the cell and express their genome, including the transgene marker
used for their detection.
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Retroviruses were first used to trace neuronal lineages in the 1980s (reviewed by Zhao,
2008 a). In these early studies, -gal encoded by the gene lacZ was used as a marker. In
2002, van Praag and colleagues used a NIT-GFP retroviral vector for the first time to
label adult-born cells in the dentate gyrus. This vector has since been replaced with the
CAG-retrovirus, since it allows for a greater amount of labeling of adult-born cells (Zhao
et al., 2006). Consistent with BrdU labeling, approximately 70 % of GFP + neurons are
positive for the mature neuronal marker NeuN four weeks after injection with the CAG-
retrovirus. A much smaller percentage of GFP+ neurons are postive for NeuN after
injection with the NIT-GFP retrovirus.
The retrovirus not only specifically labels adult-born cells, but it also allows us to track
the course of their development. The time from the injection of the retrovirus to the
sacrifice of the animal corresponds to the age of the neuron. Even though infected cells
may re-divide, a study by Zhao and colleagues (2006) found that overlap between
infected cells and the proliferation marker Ki67 is low, at approximately 18% at 3 dpi, 3
% at 7 dpi, and less than 1 % at 10 dpi. Since the retrovirus is made replication
incompetent, it also cannot produce infectious virus particles that can infect neurons at a
later time. Finally, the expression of the GFP transgene in the infected cells is persistent
since the transgene integrates into the genome of the host cell. Zhao and colleagues
(2006) found that labeling is still seen 14 months after infection. Overall, the retrovirus
provides strong temporal resolution. Silencing of the GFP retrovirus over time has not
been observed.
1.5 Development of dentate granule cells
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1.5.1 Embryogenesis and early post-natal period
Granule neurons are the last cells to be generated in the hippocampal formation (Bayer
and Altman, 1974). Granule cell neurogenesis begins in late embryogenesis and
continues through the second postnatal week. Although a small percentage of granule
cells are born during embryogenesis, over 80% are born after the birth of the animal.
Granule cells are descendants of the primary dentate neuroepithilium (Altman and Bayer,
1990a). In rats, cells begin proliferating in the primary dentate neuroepithilium by E16.
By E18, proliferating cells leave this region and form a secondary dentate matrix. By
E19, proliferating cells of the secondary dentate matrix migrate towards the developing
dentate gyrus and start the dentate migration process.
Studies in rats have shown that the dentate migration process consists of two phases
(Altman and Bayer, 1990 b) (Figure 1.3). The first migration provides the source of the
earliest generated granule cells that form the outer shell of the granule cell layer, and it is
completed before birth. The second migration begins after birth and continues into the
first month of life. It gives rise to the tertiary dentate matrix. Granule cells from the
tertiary dentate matrix settle underneath the outer granule cell layer to create the inner
cell layers. It is important to note that this developmental pattern greatly contrasts to the
‗inside-out‘ pattern found in other areas of the mammalian cerebral cortex where cells
generated later occupy positions at the top of the cell layers. The tertiary dentate matrix
also forms the subgranular zone. Some of the precursor cells in the subgranular zone
maintain their proliferative activity in the adult dentate gyrus.
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Figure 1.3: Development of the dentate gyrus. a, late in development (E15-P1), neural
progenitor cells in the secondary dentate matrix (sdm) begin the first dentate migration
and generate granule cells that form the outer granule cell layer. b, a second dentate
migration after birth (>P1) forms the tertiary dentate matrix (tdm). Neural progenitors
from this matrix generate granule cells to form the inner granule cell layer. These
neuronal progenitor cells continue to reside in the subgranular zone (SGZ) and generate
granule cells throughout adulthood. Adapted from Piatti et al., 2006.
It is important to note that the development and maturation of granule cells in the rodent
brain occurs along two gradients (Rahimi and Claiborne, 2007). One of these gradients is
the septotemporal gradient. Neurons that are generated first form the upper blade of the
dentate gyrus closer to the septal (dorsal) pole while neurons that are generated later form
the lower blade closer to the temporal (ventral) pole. The second gradient is the
transverse gradient. Neurons that are generated first form the most lateral cell body layer
along the upper blade. Additional neurons then add to the middle of the upper blade, and
finally to the most medial regions.
1.5.2 Adulthood
13
Neurogenesis continues throughout adult life in the dentate gyrus. In a young adult
C57B1/6 mouse, an estimated 1600 cells are generated each day (Hayes and
Nowakowski, 2002). Neurogenesis in the dentate gyrus decreases with age, possibly due
to a decrease in proliferation of granule cell precursors (Kuhn et al., 1996).
Three different types of cells have been identified at the mitotic stage of neurogenesis in
the dentate gyrus (Figure 1.4) (reviewed by Kempermann et al., 2004 and Zhao et al.,
2006). Type 1 cells are putative stem cells, have long apical processes and express
Nestin, Sox2, and the astrocyte marker GFAP (Seri et al., 2001; Kronenberg et al., 2003;
Suh et al., 2007). Type 2 cells are putative progenitor cells, have short processes and
express Sox 2 (Kronenberg et al., 2003; Suh et al., 2007). They do not express GFAP or
any other astrocyte characteristics (Kronenberg et al., 2003). It has recently been shown
that type 2 cells can self-renew in vivo and differentiate into astrocytes and neurons
reinforcing the idea that these progenitors have stem cell properties (Suh et al., 2007).
Type 2 cells have been further divided in Type 2A and Type 2 B cells (Kronenberg et al.,
2003). Although both are positive for the stem cell marker Nestin, Type 2B cells express
the immature cell marker doublecortin (DCX) while Type 2A cells do not. Type 3 cells
no longer express Nestin but still retain some proliferative capacity and express DCX
(Kronenberg et al., 2003). It has been suggested that Type 1, Type 2, and Type 3 cells
derive from each other in a sequential fashion with a progression in neuronal lineage
determination (Kempermann et al., 2004).
Once the developing cells become postmitotic they express the neuronal marker NeuN
(Figure 1.4). Immature neurons also express calretinin, while mature neurons express
calbindin (Brandt et al., 2003). The majority of immature neurons are eliminated over the
14
next couple of weeks (Kempermann et al., 2003). Neurons that have survived the first
two weeks are likely to stably integrate into neuronal circuitry (Bischofberger and
Schinder, 2008).
Figure 1.4: Developmental stages during mitotic and post-mitotic neurogenesis. Each
developmental stage during mitotic and post-mitotic neurogenesis can be identified by a
unique subset of expression markers. Type 1 cells express Nestin and GFAP, Type 2 a
cells express Nestin, Type 2 b cells express Nestin and DCX, and Type 3 cells express
DCX. Immature neurons express NeuN and calretinin, while mature neurons express
NeuN and calbindin. Adapted from Kempermann et al. (2004).
1.6. Factors affecting proliferation and survival of adult-born granule cells
Both intrinsic factors (Kempermann and Gage, 2002) and extrinsic factors (Ming and
Song, 2005) have been shown to influence neurogenesis. Such factors can affect the
proliferation (number of new neurons generated), differentiation (the selection of a
neuronal fate), and the survival of adult-born neurons (neurons that do not die two-three
weeks after birth and are stably integrated).
15
1.6.1 Genetic Influences
The influence of genetic background on adult neurogenesis in the dentate gyrus was first
examined by Kempermann and colleagues (1997). The study found significant
differences among four different mouse strains in the proliferation, survival, and
phenotype (neuron vs. glia) of adult-generated neurons. Further studies have continued to
find differences in neurogenesis among different mouse strains (Kempermann 2002;
Schauwecker, 2006). In all these studies, the degree of difference and which aspect of
neurogenesis was being affected depended on the mouse strains being compared.
A more wide-scale analysis of the influence of genetic variance on neurogenesis was
recently conducted by Kempermann and colleagues (2006). The comparison of 52
different mouse strains revealed over 100 genes that were correlated with differences in
neuronal proliferation, survival, and differentiation. Interestingly, all these genes were
linked with stem cell maintenance, neurogenesis, or gliogenesis. Clearly, further work
needs to be done to determine how these genes interact with one another and with the
environment to influence neurogenesis.
1.6.2 Extrinsic influences
Unlike during embryonic neurogenesis, neurogenesis in the adult needs protection from
anti-neurogenic influences. Likewise, it needs the help of an environment that favours
neuronal development at a time when the rest of the brain has ceased developing. Not
surprisingly, various extrinsic signals such as growth factors and neurotransmitters play
an important role in regulating proliferation, differentiation, and survival of adult-born
cells in the dentate gyrus. Insulin-like growth factor (IGF), for example, increases the
16
proliferation of adult-born cells (Aberg et al., 2000). Differentiation has been shown to be
affected by the neurotransmitter GABA, which depolarizes type 2 progenitors resulting in
the influx of calcium and leading to increased expression of the neuronal differentiation
factor NeuroD (Tozuka et al., 2005). Meanwhile, survival of adult-born cells (especially
at three weeks after birth) has been shown to be heavily influenced by neuronal activity
resulting from NMDA channel activation (Tashiro et al., 2006).
Along with extrinsic signals, systemic factors such as the environment, behaviour, drugs,
and pathological stimulation have been shown to regulate neurogenesis in the dentate
gyrus. Cell proliferation increases with voluntary exercise (van Praag et al., 1999a; van
Praag et al., 1999b; Kronenberg et al., 2003; Brandt et al., 2003) and survival increases
with environmental enrichment (Kempermann et al., 1998). Hippocampal-dependent
learning is also a positive regulator of SGZ neurogenesis, although its effects are complex
and are affected by such factors as the age of the neurons and the stage of learning
(reviewed by Zhao et al., 2008 b). Finally, neurogenesis increases after pathological
stimulation such as seizure (Parent et al., 1997; Scott et al., 2000) and stroke (Kee et al.,
2001). Negative regulators of neurogenesis have been shown to include stress (Gould et
al. 1998), and drugs such as alcohol (Jang et al., 2002; Nixon and Crews, 2002) and
nicotine (Jang et al., 2002).
1.7 Mechanisms of neuronal migration, morphological development, and
spine formation
1.7.1 Neuronal migration
17
Before neurons can develop synaptic connections, they need to migrate from their
birthplace to their final position in the adult brain after exiting the cell cycle. In general,
neuronal migration involves a certain sequence of events (Tsai and Glesson, 2005;
Bellion et al., 2005). Migrating neurons have a leading process on one end and a trailing
process on the other end. First, a growth cone at the edge of the leading process helps the
cell extend. Then, the nucleus and other organelles are translocated forward. The trailing
process then retracts. There are two main ways by which a neuron can migrate (reviewed
by Ayala et al., 2007).The first is radial migration, by which neurons migrate by using
radial glia as a scaffold. The second is tangential migration, by which neurons migrate
perpendicular to radial glia.
1.7.2 Growth of axons and dendrites
Morphological development in neurons involves growing an axon, which sends output,
and several dendrites, which receive input. Dendritic and axonal growth involves a
complex process of cytoskeleton remodeling involving microtubules and actin (reviewed
by Conde and Caceres, 2009). Actin is typically situated at the tip of the dendrite or axon
and makes up an important component of the growth cone, while microtubules make up
the core of the dendrite or axon. In the process of dendritic growth, actin helps the
dendrite sense out its environment while microtubules help stabilize the dendrite
following extension or retraction. The movement of the dendritic growth cone has been
shown to be largely mediated by a family of RhoGTPases (Watabe-Uchide et al., 2006).
During cytoskeleton remodeling, actin transitions from an active GTP bound state, which
allows it to bind to other proteins and move the growth cone, to an inactive GDP bound
state. Rho GTPases help catalyze GDP to GTP.
18
1.7.3 Spine formation
Over 90 % of excitatory synapses are found on spines (Nimchinsky et al. 2002), therefore
spines play an important role in the development of synaptic connectivity. Growing
spines are called fliopodia. These spines contain a long, thin neck and are highly
dynamic, undergoing rapid extension and retraction (Dailey and Smith, 1996). A popular
model of spine development involves filopodia actively seeking out presynaptic partners
(Ziv and Smith, 1996). Once a synaptic connection is made, the spine shortens and
stabilizes. Spines are generally classified into three types based on the size of the head
and neck length (Peters and Kaiserman-Abramof, 1970). Mushroom spines have a large
head and small neck length, stubby spines have a large head and no neck, and tiny spines
have a small head and a long neck length. Since they contain actin, spines are capable of
motility after they are formed (Matus, 2000) providing an important source of synaptic
plasticity.
1.8 Anatomical integration of granule cells during adulthood and early-
postnatal development
1.8.1 Migration
A major challenge unique to dendrites and axons in newly-generated granule cells within
the adult brain consists of migrating through densely packed cell layers filled with mature
dendrites and axons. To overcome this challenge, adult-born granule migrate with the
help of radial glia (Shaprio et al., 2005). Lie and Gotz (2008) proposed that migration in
adult-born granule cells is also likely to depend on the help of doublecortin (DCX)
(Brown et al. 2008), which is a protein found in microtubules, and PSA-NCAM (Seki
19
2002), which labels immature adult-born cells and is an adhesive protein. Both these
proteins have been found to be important for migration in the olfactory bulb (Hu et al.,
1996; Koizumi et al., 2006), therefore it is possible that they are also involved in granule
cell migration (Lie and Gotz, 2008).
1.8.2 Passive membrane properties
In early stages of development, adult-born granule cells display a high input resistance,
which reflects a low density of ion channels (Esposito et al., 2005; Overstreet-Wadiche et
al., 2006 c). Input resistance decreases as the cells mature. Furthermore, as expected,
membrane capacitance (which is proportional to the area of the soma) is low in immature
neurons and increases to higher levels as cells mature (Esposito et al., 2005). Similar
observations have been noted during the maturation of newly-generated granule cells
during early post-natal development (Liu et al., 2000).
1.8.3 The growth of axons and dendrites
The growth of axons and dendrites in adult-born neurons shares similarities with granule
cells born in the developing brain (reviewed by Ribak and Shapiro, 2007). In developing
adult-born granule cells, dendrites are thin and show immature features such as growth
cones, lamellipodia, and filopodia (Ribak et al., 2004), similar to granule cells in early
post-natal development (Lubbers and Frotscher, 1988). These growth cones are visible in
the new-born neuron 24-48 hours after birth (Shapiro et al., 2007). Furthermore, basal
dendrites are a transient feature of both newly-generated neurons in the adult brain
(Ribak et al., 2004) and developing brain (Jones et al., 2003).
20
To help with their development, adult-born granule cells are situated close to blood
vessels and astrocytes forming a ―neurogenic niche‖ that is rich in neurotrophic factors
(Palmer et al., 2000).
1.8.4 Afferent connections
Early during their development, adult-born granule cells are spatially restricted to the
subgranular zone and lack afferent synaptic contacts (Esposito et al., 2005). Beginning at
three days of age, however, they are capable of receiving tonic GABA activation caused
by the activation of GABAA receptors through non-vesicular release (Ge et al., 2006 b).
After one week, there is considerable neuronal migration from the SGZ toward the first
and second granule cell layers (Esposito et al., 2005). Around this time, the dendritic
processes of these neurons also reach the inner molecular layer (Zhao et al., 2006) and
receive their first afferent connections. These connections are GABA-mediated and are
formed close to the soma and on distal dendrites (Esposito et al., 2005). At this time,
GABA is excitatory and produces a depolarizing current in granule cells.
Dendritic processes of adult-born granule cells grow to the middle of the molecular layer
at two weeks, and reach the edge of the molecular layer after three-four weeks (Zhao et
al,. 2006; Esposito et al., 2005). Spines began to form on dendrites at 16 day post
infection (dpi) (Zhao et al., 2006). By three weeks, afferents of newborn neurons make
exctitatory glutamatergic contacts with the perforant pathway and by four weeks they
receive somatic GABAergic contacts from interneurons (Esposito et al., 2005).
GABAergic input at this time is inhibitory. Spine density continues to increase until 56
21
dpi, where it starts to plateau (Zhao et al., 2006). However, mushroom spine density
continues to increase past 100 dpi.
Overall, afferent connectivity proceeds in a similar manner within the adult and post-
natal brain (Lapagne et al., 2006). However, the time course of afferent connectivity in
granule cells in the developing and adult brain differs. Granule cells in neonates receive
perforant input by the end of the first postnatal week (Liu et al., 2000); in contrast to
adult-born granule cells that receive perforant input at 3 weeks of age (Esposito et
al.,2005). Furthermore, spine formation and dendritic growth in granule cells differs
between the developing and adult brain (Zhao et al., 2006). While spine growth is seen as
early as 12 dpi in postnatal brains, it is not seen until 16 dpi in adult brains. Similarly,
dendritic growth of granule cells appears to be slower than in postnatal brains, with
neurons at 12 dpi showing significantly more dendritic length and branching points in
postnatal brains than adult brains. Furthermore, afferent input is delayed in adult-born
granule cells.
1.8.5 Efferent connections
Axons of adult-born granule cells first reach the CA3 region at 10 dpi and continue to
increase in length until 16-56 dpi (Zhao et al., 2006). Toni and colleagues (2008) showed
that these axons begin to establish contacts with postsynaptic targets in the CA3 area and
the hilus as early as 17 dpi. Postsynaptic targets include mossy cells, interneurons of the
hilus, and pyramidal cells in CA3. These synaptic contacts are functional, and release
glutamate as their main transmitter. Faulkner and colleagues (2008) further showed that
22
the synaptic boutons connecting mossy fiber terminals to CA3 pyramidal cells continue
to mature between two and four weeks of age, and reach maturity at around eight weeks.
Efferent connectivity proceeds in a similar manner in granule cells within the adult-born
and developing brain. In both cases, axons reach CA3 before spines begin to develop
(Jones et al., 2003; Zhao et al., 2006) and axons synapse with dendritic shafts before they
synapse with dendritic spines (Seress et al., 1995; Toni et al., 2008).
Axonal growth, however, is delayed in neurons born in adulthood (Zhao et al., 2006).
Axons of granule cells born in the post-natal brain migrate significantly further at 12 dpi
than axons of cells born during adulthood. Furthermore, mossy fiber boutons reach
maturity by three weeks in the developing brain as compared to eight weeks in the adult
brain.
1.9 Functional integration of adult-born granule cells
1.9.1 Physiological maturation of adult-born granule cells
With the use of the GFP-retrovirus, a landmark study by Van Praag and colleagues
(2002) showed that adult-born granule cells acquire physiological properties of mature
granule cells and become functional in vivo. They found that adult-born cells fire
spontaneous postsynaptic currents with fast onset and a slow exponential decay, which is
typical of postsynaptic currents responding to fast neurotransmitters such as glutamate
and GABA. They also fire postsynaptic currents in response to extracellular stimulation
of the perforant path, suggesting that adult-born granule cells receive input and are
functionally integrated into the dentate gyrus.
23
Despite similarities in physiological properties between adult-born and mature granule
cells, it is important to note that adult-born granule cells exhibit certain characteristics
that make them unique. Adult-born granule cells show a lower LTP induction threshold at
around two to four weeks of age (Schmidt-Hieber et al., 2004; Ge et al., 2007). The LTP
amplitude is also larger than that exhibited by mature cells at around four to six weeks of
age and has been shown to depend on NR2B subunits of the NMDA receptors (Ge et al.,
2007).
1.9.2 Immediate-early gene (IEG) expression
Alongside electrophysiology, immediate early gene expression is used to determine
whether neurons are functional in vivo. Immediate early genes (IEG s) serve as indicators
of neuronal activity as they are expressed transiently after neuronal activation. IEG s
encode a variety of proteins, including transcription factors, signal transduction proteins,
and growth factors (Lanahan and Worley, 1998). Many of these proteins are believed to
influence synaptic strength (Guzowski et al., 2002).
1.9.2.1 Correlation between IEG expression and neuronal activation
Many studies have established a correlation between neuronal activation and expression
of IEG s. To detect expression of IEG mRNA, the animal is sacrificed approximately 30
minutes after stimulation and in-situ hybridization is used to detect mRNA levels. To
detect expression of IEG proteins, on the other hand, the animal is sacrificed 1-2 hours
after stimulation and immunohistochemsitry is used to detect protein levels (Guzowski et
al., 2005).
24
Morgan and colleagues (1987) first established the link between neuronal activation and
expression of IEG s by showing Fos expression throughout several brain regions after the
induction of seizures. The expression of other IEG s such as zif 268, c-jun, and jun-B has
also found to be induced by convulsive agents (Saffen et al., 1988) and by synaptic
NMDA receptor activation induced by LTP (Cole et al., 1989). Importantly, IEG
expression has been correlated with neuronal firing (Labiner et al., 1993).
1.9.2.2 Role of IEG s in memory
Although the exact role of IEG s in memory formation is unclear, it is well established
that they are required for memory maintenance. Rats that receive Fos antisense
oligodeoxynucleotide infusions have been shown to have impairments in the acquisition
and retention of conditioned taste aversion (Yasoshima et al., 2006) and for consolidation
of socially transmitted food preference (Countryman et al., 2005).
IEG expression is useful in mapping circuits activated during learning and recall.
Learning has been shown to regulate the expression of the IEG s Arc, Fos, and zif268 in
the water maze (Guzowski et al., 2001) and Fos in the socially transmitted food
preference task (Smith et al., 2007). Recent studies have used this approach to identify
circuits supporting recall of spatial (Maviel et al., 2004), aversive (Frankland et al.,
2004), appetitive (Bertaina and Destrade, 1995), olfactory (Smith et al., 2007) and
gustatory (Yasoshima et al., 2006) memories.
1.9.2.3 IEG activation in adult-born cells following neuronal stimulation
Many immunohistochemical studies thus far have found that adult-born cells express IEG
s following various forms of stimulation. In an important study, Jessberger and
25
Kempermann (2003) showed for the first time that adult-born cells express the immediate
early gene markers c-fos, zif268, and Homer1A following kainic acid (KA) and
pentylenetetrazol (PTZ) induced seizures. The proportion of adult-born cells expressing
IEG s following seizure activity was considerably greater in neurons 25 days of age than
35 days of age showing that adult-born cells acquire responsiveness to activating stimuli.
Furthermore, at 35 days of age, a similar ratio of adult-born and mature granule cells
participated in IEG-expression. In another study, Bruel-Jungerman and colleagues (2006)
showed that two-week old but not one-week old neurons expressed the IEG marker
Zif268 following high-frequency electrical perforant path stimulation.
Further studies show that adult-born cells respond to environmental stimulation.
Jessberger and Kempermann (2007) showed that mature adult-born cells express the IEG
marker c-fos following water maze training. Similarly, Ramirez-Amaya and colleagues
(2006) found that mature adult-born cells express Arc following spatial exploration.
To determine whether adult-born neurons are stably incorporated into hippocampal
memory circuits, Kee and colleagues (2007) examined activation of adult-born cells
following recall of a spatial memory. The main idea of their experimental design was that
if BrdU-labeled neurons are incorporated into dentate gyrus circuitry supporting spatial
memory during training, they should express Fos following testing. Excitingly, they
found that adult-born neurons are functionally incorporated into dentate gyrus circuitry
supporting spatial memory and that the incorporation is age dependent. Through the use
of various controls they also showed that gene expression was not associated with
nonspecific aspects of the task (for example, swimming, physical exercise, stress or
arousal).
26
1.10 Factors affecting morphological development of neurons during
embryogenesis and early-postnatal development
1.10.1 Transcription factors
The majority of studies examining the influence of transcription factors on dendrtic
development have been done in Drosophila. A recent RNA interference screen has
revealed that more than 70 transcription factors regulate dendrtic growth of class 1
sensory neurons in the Drosophila nervous system (Parrish et al., 2006). In mammals, the
dendritic morphology of neurons has been shown to be controlled by transcription factors
such as Neuro1D (Gaudilliere et al., 2004) and CREB (Redmond et al., 2002).
1.10.2 Extrinsic factors
The influence of extrinsic factors on dendritic arborization in embryogenesis and early-
postnatal development has been extensively studied. Chemical cues play a particularly
important role in influencing the direction of dendritic growth. In the rat cortex, for
example, growth of apical dendrites to the pial surface in pyramidal cells is influenced by
the chemoattracant semaphorin 3A (Polleux et al., 2000).
Along with influencing the direction of dendritic growth, extrinsic signals influence
dendritic growth dynamics, by inhibiting or stimulating dendritic growth. For example,
Notch signaling has been shown to decrease dendritic growth (Redmond et al., 2000). On
the other hand, neuotrophins such as nerve growth factor (NGF) and brain-derived
neurotrophic factor (BDNF) increase dendritic growth (Huang and Reichardt, 2001).
Neurotrophins act on TrkB receptors, and activate the MAP kinase and PI-3 kinase
pathways which have been connected with cytoskeleton remodeling (Wu et al., 2001).
27
Finally, hormones also influence dendritic growth dynamics, including thyroid
horomone, glucocorticoids, and estrogen (Gould et al., 1991).
1.10.3 Activity-dependent regulation
It is well established that in early development two types of activity influence the
development of neurons (Feller, 1999). The first is spontaneous activity, independent of
afferent input; the second is experience-dependent activity driven by afferent input.
1.10.3.1 Spontaneous activity
Spontaneous activity consists of rhythmic bursts of action potentials across neurons and
mostly influences early stages of neuronal maturation, such as migration and the
formation of initial synaptic connections (Feller, 1999). In general, action potentials
increase levels of intracellular calcium which then affect cytoskeleton remodeling.
Spontaneous activity has been most extensively studied in the retina and has been shown
to occur across a variety of species, including chickens, turtles, mice, and ferrets early in
post-natal development (reviewed by Wong, 1999). In the retina, spontaneous activity
generally consists of three sequential phases: the first is driven by electrical coupling via
gap junctions, the second by acetycholine (ACh), and the third by glutamate (Feller et al.,
1996; Syed et al., 2004). In the CA1 regions of the developing hippocampus,
spontaneous action potentials have been shown to be generated by GABA (Garaschuk et
al., 1998).
1.10.3.2 Afferent-dependent activity
The relationship between synaptic input and dendritic growth during embryogenesis has
28
been extensively examined. Many studies point to synaptic input as providing a ―go‖
signal for dendritic growth (reviewed by Wong, 2002). This is commonly seen with
synaptic input mediated by sensory stimulation. For example, using time-lapse imaging
in the tadpole tectum a study by Sin et al. (2002) showed that dendritic growth
significantly increases shortly after tadpoles are exposed to light. The dendritic growth
was shown to be mediated by NMDA receptors and Rho GTPases.
Interestingly, some studies have found that blocking activity increases dendritic growth
(reviewed by McAllister, 2000) suggesting that activity stabilizes or ―stops‖ dendritic
growth. For example, Rocha and Sur (1995) showed that blocking NMDA receptors in
the lateral geniculate nucleus increases dendritic growth.
Overall, it appears like a combination of factors influence whether activity promotes or
inhibits dendritic growth. For example, a study by Rajan and Cline (1998) showed that in
early stages of tectal neuron development, activation of NMDA receptors increases
dendritic length. During later stages of dendritic maturation, when the ratio of AMPA to
NMDA receptors increases, the activation of AMPA receptors by sensory activity
stabilizes dendritic growth. A more recent study by Tripodi and colleagues (2008) has
further suggested that the interaction between activity and dendritic growth is
characterized by a homeostatic mechanism and dendritic arbors adjust according to their
level of active synaptic sites.
1.11 Factors affecting anatomical and functional maturation of adult-born
granule cells
Adult-born granule cells in the dentate gyrus face many challenges. Only approximately
29
40% of adult-born cells that are generated survive and differentiate (Dayer et al., 2003).
Then, these neurons face the difficult task of anatomically and functionally integrating
into a mature neuronal circuit within the dentate gyrus. Adult-born neurons face not only
limited space, but also a more heterogeneous environment than in the embryo. To date, a
significant amount of attention has been devoted towards examining factors that affect
the proliferation and survival of adult-born neurons; much less attention, however, has
been devoted towards identifying which factors affect the integration of these neurons.
Integration is a complex process requiring migration, neuronal growth, acquisition of
intrinsic excitability, and synapse formation.
1.11.1 Extrinsic signals
While the effect of various external molecular cues on dendritic maturation has been
extensively explored in the developing nervous system, the influence of external signals
on dendritic maturation in neurogenesis has only recently begun to be examined. With the
use of inducible transgenic mice and viral-mediated gene transduction, significant
progress has started to be made in manipulating genes affecting signaling pathways that
are important in adult neurogenesis, including their integration. A common approach, for
example, involves using a virus that encodes Cre recombinase, which recognizes and
recombines loxP sites that are positioned on the ends of a gene of interest—a ‗floxed‘
gene. Stereotaxic infusion of a virus encoding Cre into the brain of a floxed mouse allows
regionally specific gene knockout.
One molecule that has been closely linked with maturation of adult-generated neurons is
DISC1 (Duan et al., 2007). The expression of the DISC1 gene is high in development and
30
has particularly high expression in adult-born neurons in both the hippocampus and
olfactory bulb (Austin et al., 2004) making it a strong candidate for regulating
neurogenesis. Interestingly, Duan and colleagues (2007) found accelerated neuronal
maturation upon knocking down DISC1 in adult-born granule cells by using a retrovirus
encoding a short hairpin RNA (shRNA). These neurons had greater dendritic complexity
(length and crossings) and exhibited enhanced excitability as measured by membrane
resistance and action potential firing. Accelerated maturation, however, was accompanied
by ectopic cell bodies and defective neuronal positioning. In a similar manner,
knockdown of DISC1 resulted in accelerated axonal maturation with defective axonal
targeting and synaptic output formation (Faulkner et al., 2008).
While DISC1 negatively regulates neuronal maturation, most other molecules examined
positively regulate neuronal maturation. Cell division protein kinase 5 (Cdk5), for
example, is a kinase that phosphorylates many molecules regulating neuronal growth and
synapse formation (Dhariwala et al., 2008). Knocking down Cdk5 using a retroviral-
based approach results in aberrant growth of dendrites, altered neuronal migration, and
ectopic synapse formation with target cells (Jessberger et al., 2008).
Other signaling pathways that positively regulate the maturation of adult-born cells
include brain derived neurotrophic factor (BDNF) and its receptor tropomyosine related
kinase (TrkB). Tamoxifen-induced deletion of TrkB results in deficits in both anatomical
and functional integration with reduced growth of dendrite and spines and impaired long-
term potentiation (Bergami et al., 2008). In a similar manner, knocking down Notch leads
to a decrease in dendritic complexity (Breunig et al., 2007). Further studies point to the
role of downstream transcription factors in positively regulating dendritic maturation,
31
particularly the cyclic AMP response element binding protein (CREB) (Fujioka et al.,
2004).
1.11.2 Activity-dependent regulation
1.11.2.1 Afferent-independent activity regulation – GABA
Similar to development, recent studies have shown that GABA plays an important role in
regulating various stages of granule cell development within the adult brain, including
neuronal maturation and synaptic integration.
GABA has been shown to influence neuronal development when it has an excitatory role
on neurons (Ge et al., 2006 a). Whether GABA results in excitation through
depolarization or inhibition through hyperpolarization depends on the expression of the
chlorine transporters NKCC1 (a chlorine importer) and KCC2 (a chlorine exporter). In
early stages of maturation, there are higher levels of NKCC1 resulting in a high chloride
ion concentration and a depolarizing effect by GABA. Over a period of 2-3 weeks as the
cells mature, levels of NKCC1 decrease leading to a lower level of chloride ion inside the
cell and therefore an inhibitory effect by GABA.
To examine the role of GABA on adult-born granule neurons, Ge and colleagues (2006
b) used shRNAS against NKCC1 to make GABAergic activity hyperpolarizing in
immature neurons. This resulted in decreased neuronal complexity and delayed formation
of GABAergic and glutamatergic synapses, pointing to the role of activity mediated by
GABA in setting the ‗tempo‘ for maturation (Ge et al., 2006 a). Although the mechanism
by which GABA activation influences anatomical and functional integration of adult-
born cells is unknown, several mechanisms have been proposed. It has been suggested
32
that depolarization induced by GABA could activate transcription factors involved in
dendritic growth and synaptogenesis such as CREB (Overstreet-Wadiche et al., 2006 a)
and/or calcium signaling leading to rearrangement of the cytoskeleton (Ge et al., 2006 a).
Global spontaneous neuronal activity in the form of seizures also regulates neuronal
maturation. Seizures cause abnormal morphological maturation in adult-born neurons
such as growth of hilar basal dendrites and defective migration (Jessberger et al., 2007).
Overstreet-Wadiche and colleagues (2006 b) also showed that seizures accelerate
anatomical and functional integration of adult-born cells resulting in greater dendritic
complexity (number of branches, dendritic length) and accelerated synapse formation
with perforant path input. It has been suggested that accelerated anatomical and
functional integration could result from enhanced GABA-mediated depolarization
following seizures or the upregulation of neurotrophic factors such as BDNF (Overstreet-
Wadiche et al., 2006 b).
1.11.2.2 Afferent-dependent activity regulation
The effect of afferent-dependent activity on dendritic growth in adult-born granule cells
has not directly been examined. However, two recent studies have examined the effect of
enhanced network activity through learning on the dendritic growth of adult-born granule
cells in the hippocampus. Interestingly, Ambrogini and colleagues (2009) showed that
adult-born granule cells in rats trained in the Morris water maze have accelerated
formation of GABAergic synapses and a greater number of primary dendrites than
controls. Tronel and colleagues (2010) further showed that spatial learning increases
dendritic complexity (as seen in dendritic length, nodes, terminals) and spine density in
33
adult-born cells. The increase in complexity is dependent on the cognitive demand of the
task and on the activation of NMDA receptors. Together, these studies suggest that
afferent activity accelerates the anatomical and functional maturation of adult-born
granule cells. The relationship between the anatomical maturation of adult-born granule
cells and their functional integration into dentate gyrus circuitry remains unexplored.
34
AIMS AND HYPOTHESES
2. 1 Study rationale
Since neurogenesis was discovered in the adult human hippocampus approximately a
decade ago, a large amount of progress has been made in identifying intrinsic and
extrinsic factors that affect early stages of maturation in adult-born granule cells,
primarily their proliferation, differentiation, and survival. With the introduction of
retroviral-mediated cell labeling, many studies have also characterized their anatomical
and functional integration. However, our understanding of the factors affecting these later
stages of development, especially their functional integration, is quite limited.
It is possible that morphological correlates of adult-born granule cells affect their
functional integration. The majority of excitatory synapses terminate on dendrites,
therefore they play an important role in integrating input to produce neuronal output
(Johnston et al., 1996). Several studies have also found an association between an
increase in dendritic complexity and memory enhancement (Liu et al., 2008; Eadie et al.,
2005). Spines, meanwhile, are the postsynaptic components of excitatory synapses and
regulate the synaptic excitation of the dendrite (Jaslove, 1992; Harris and Kater, 1994). In
fact, studies have found that an increase in spine density results in a significant increase
in the size of miniature excitatory post-synaptic potentials (mEPSCs) (El-Husseini et al.,
2000; Matsuzaki et al., 2001). Since differences in dendritic complexity and spine density
affect how neurons process and integrate excitatory input, it is highly plausible that they
might influence whether or not adult-generated neurons become functionally integrated
into dentate gyrus circuitry.
35
2. 2 Experimental design
In the following study, we stereotaxically injected a CAG-retrovirus into the dentate
gyrus of mice. This allowed us to selectively label proliferating cells with GFP and to
define morphological features of dendrites and spines. Either 10, 20, 40, or 80 days
following viral infection, mice were injected with pentylenetrazol (PTZ), to activate the
maximum number of adult-born granule cells (Figure 2.1). The expression of the IEG
protein c-fos was used as a marker of activated neurons, as Fos expression has been
correlated with neuronal firing following PTZ induced seizures (Labiner et al., 1993).
Morphological features of Fos + and Fos- adult-born cells within groups were then
compared.
Figure 2.1: Experimental design. The retrovirus was stereotaxically infused into the
dentate gyrus and 10, 20, 40, or 80 days later seizures were induced and the mice were
perfused. The time from surgery to perfusion corresponds to the age of the adult-born
granule cells.
36
2.3 Specific aims and hypotheses
Our main aim was to examine the relationship between dendritic and spine properties of
adult-born granule cells and their integration into dentate gyrus circuitry following PTZ
induced seizures. This involved within-group comparisons. We hypothesized that
dendritic complexity and spine density would be significantly greater in GFP+/Fos+ than
GFP+/Fos- neurons, especially at 20 and 40 days of age. Greater dendritic complexity
and spine density likely reflects a more mature neuronal phenotype, increasing the
likelihood that such neurons will be integrated into dentate gyrus circuitry.
37
MATERIALS AND METHODS
3.1 Subjects and stereotaxic surgery
Six to seven week old male mice (C57B1/6NTac 129S6/SvEv Tac) were housed in
standard conditions with 4-5 mice per cage. Prior to surgery, mice were anesthetized with
4% chlorol hydrate (Sigma). Virus (1.0 l at 0.15 l min -1
) was infused bilaterally into
the dentate gyrus (anteroposterior = -2.2 mm from bregma; lateral = 1.6 mm; ventral =
2.0 mm). Animal protocols were approved by the SickKids Animal Use and Care
Committee.
3.2 Retroviral-mediated labeling of adult-born neurons in the mouse
hippocampus
We used a replication-deficient retroviral vector based on the Moloney murine leukemia
virus to express GFP driven by a CAG promoter (Zhao et al., 2006). First, two plasmids
containing an amphotropic envelope (vsvg) and the transgene (pCAG-GFP) were
transfected into Plat-gp cells, and concentrated through ultra-speed centrifugation to
produce a virus (Figure 3.1). We then infected Plat-E cells with the virus. This resulted in
a stable virus-producing cell line. The virus from this cell line was concentrated through
ultra-high speed centrifugation to produce an ecotropic virus with a high titer: 5.0 108
–
5.0 109 infection units.
38
Figure 3.1: CAG-retrovirus production. VSVG and pCAG-GFP plasmids were
transfected into a Plat-gp cell line. The amphotropic virus then infected Plat-E cells and
the supernatant was centrifuged to produce a pCAG-GFP ecotropic virus.
3.3 Seizure induction
At periods of 10, 20, 40 or 80 days following surgery, animals were injected with
pentylenetetrazol (PTZ) (Sigma) to induce seizure activity. Seizures were induced at the
same time in all animals within each housing group. First, a single intraperitoneal
injection of 30 mg/kg PTZ was given. After 10 min, a 10 mg/kg injection was given
every 15 minutes until the animal seized. Animals were observed closely and only those
exhibiting generalized clonic activity were analyzed. Generalized clonic activity was
characterized by a sudden loss of upright posture, whole body clonus involving all four
limbs and tail, and rearing (Ferraro et al., 1999). These signs were followed by a
quiescent period.
3. 4 Tissue preparation
39
Ninety minutes following generalized clonus activity, mice were anaesthetized deeply
with 4% chlorol hydrate (400 mg/kg) (Sigma) and perfused transcardially with 0.15 M
phosphate buffered saline (PBS) followed by 4 % paraformaldehyde (PFA) in 0.15 M
PBS. Brains were removed and postfixed in 4 % PFA overnight. They were then cut on a
vibratome (Leica VT1200S). Coronal sections of 50- m were taken throughout the entire
extent of the hippocampus and transferred to a cryoprotecting solution (60 % glycerol,
0.1 % sodium azide, and 0.15 M PBS). They were stored overnight at 4 C and then
transferred to -20 C.
3.5 Immunohistochemistry
Free-floating sections were rinsed (3 5 min) in 0.15 PBS and incubated in 0.02 %
sodium dodecyl sulfate (SDS) (10 min). They were then rinsed (5 5 min) in 0.15 PBS
and treated with 1 % hydrogen peroxide (30 min) to block endogenous peroxidase
activity. Following rinsing (3 5 min) they were incubated for 2 hours in donkey
blocking solution. The blocking solution consisted of 2.5 % bovine serum albumin
(Sigma), 5 % donkey serum (Jackson Laboratories), and 0.3 % Triton X-100 (Sigma).
This was followed by 48 hours of incubation with primary anti-GFP antibody (IgG rabbit,
1:500; Invitrogen) and primary anti-Fos antibody (goat, 1:100, Santa Cruz) at 4 C .
After washing with 0.05% Tween in PBS (6 10 min), sections were incubated for 2
hours in AlexaFluor488 donkey anti-rabbit (1:500, Invitrogen), AlexaFluor 568 donkey
anti-goat (1:500, Invitrogen), and Hoescht (1:1000, Invitrogen). All antibodies were
diluted in the donkey blocking solution described earlier. Sections were washed with 0.05
40
% Tween in PBS (6 10 min) and mounted with Vectashield mounting medium (Vector
Laboratories).
3.6 Identification of GFP+ Fos+ cells
An epifluorescent microscope (Olympus BX61) with a 60 oil objective (NA; 1.42,
Olympus) was used to quantify the phenotype (Fos+/Fos-) of all GFP + cells manually.
The image was moved in and out of focus throughout the entire z axis of each cell. A
subset of Fos+ GFP+ were confirmed using a confocal microscope (Olympus IX81 DSU)
with a 40 oil objective. To verify that Fos+ GFP+ cells were double-labeled, 20 focal
planes were collected to create a three-dimensional image and ensure that the
fluorochromes originated from the same cell. Partially labeled or sectioned cells were not
counted. Also, cells in the uppermost and lowermost 5 m-focal plane were not included.
To quantify the proportion of GFP + cells that were Fos+ within each group, 25 neurons
per animal were randomly selected for analysis and their phenotype (Fos+ or Fos- ) was
determined. Three animals were analyzed at 10 dpi, 7 at 20 dpi, 9 at 40 dpi, and 5 at 80
dpi.
3. 7 Dendritic properties
Using 10 magnification, the dentate gyrus was identified and granule neurons
throughout the dentate gyrus were randomly selected for analysis. For within-group
comparisons, neurons were first identified as Fos+ or Fos-. GFP + neurons selected for
analysis contained at least one primary, secondary, and tertiary branch. Mature granule
cells in the dentate gyrus are expected to fulfill this criteria (Claiborne, 1990); therefore,
41
this criteria was used to avoid analyzing neurons greatly affected by cutting. Neurons that
met this criteria were traced using an epifluorescent microscope (Olympus BX61) with a
60 oil objective (NA; 1.42, Olympus), a computerized stage, and Neuroleucida
software (Version 9, Microbrightfield).
3.7.1 Sholl analysis
We first conducted Sholl analysis (Sholl, 1956) by reconstructing the traced neuronal
images using NeuroExplorer (Version 9, Microbrightfield). A series of concentric
spheres, centered on the cell body and spaced 20 m apart, were placed over the neuron
and the number of times the dendrite intersected each sphere and the total dendritic length
within each sphere was quantified (Figure 3.2). Sholl analysis was conducted for all radii
at 20-200 m away from the soma. The majority of neurons were cut at around 220 m
away from the soma; hence, radii from 220-260 m were eliminated from analysis.
Figure 3.2. Sholl analysis. A series of concentric spheres, centered on the cell body and
spaced 20 m apart, are placed over the neuron. Only rings at 20 and 40 m are shown in
this diagram.
42
For among-group analysis, neurons were randomly selected from three animals in the 10
dpi group and from ten animals in each of the 20, 40, and 80 dpi groups. In the final
sample, tracings were made on 14 neurons from the 10 dpi group, 89 neurons from the 20
dpi group, 97 neurons from the 40 dpi group, and 52 neurons from the 80 dpi group. A
minimum of five neurons were selected from each animal.
For within-group analysis, neurons were analyzed from 8 animals at 20 dpi, 8 animals at
40 dpi, and 6 animals at 80 dpi. For the final quantification, the following number of
neurons were included for analysis: 40 Fos+, 41 Fos- neurons in the 20 dpi group, 68
Fos+ , 33 Fos -neurons in the 40 dpi group, and 34 Fos+, 18 Fos- neurons in the 80 dpi
group. A minimum of 5 neurons were selected from each animal.
3.7.2 Branch order analysis
We also performed branch order analysis to provide an additional measure of dendritic
complexity (Figure 3.3). In this type of analysis, when a primary dendrite bifurcates, the
dendrites extending from the branch point are classified as secondary dendrites. We
recorded the quantity of dendrites at each branch order. The same neurons that were used
for Sholl analysis were used for branch order analysis.
43
Figure 3.3. Branch order analysis. The first branch order is shown in pink, the second in
yellow, and the third in blue. Branches are labeled for only a portion of the neuron in this
diagram.
3.7.3 Branch thickness
To analyze branch thickness, traced neuronal images were analyzed using NeuroExplorer
(Version 9, Microbrightfield). Branch thickness of 1st, 2
nd, 3
rd, 4
th, and 5
th order branches
was collected from 5 animals in each of the 20, 40, and 80 dpi groups. In the final
sample, tracings included a total of 66 branches at the 1st order, 112 branches at the 2
nd
order, 114 branches at the 3rd
order, 217 branches at the 4th
order, and 146 branches at the
5th
order. A minimum of five neurons were randomly selected for analysis from each
animal.
3. 8 Spine Properties
For spine analysis, z-series images at 0.25 m increments were acquired with a 100 oil
objective (NA 1.40, Olympus) and Neuroleucida software (Version 9, Microbrightfield).
44
Images were taken of third and fourth order dendritic segments as they were found in the
greatest quantity within neurons. Third and fourth order dendritic segments also make
synaptic contacts with both the medial and lateral perforant pathways, which provide
afferent input to granule neurons. Spines were quantified manually from image stacks
using NeuroExplorer (Version 9, Microbrightfield). Quantification was performed blind
to the phenotype of the cell (Fos+ vs. Fos-).
3.8.1 Spine and mushroom spine density
To calculate spine density, the number of spines was divided by the length of the
dendritic segment. Dendritic segments had a minimum length of 50 m. For a subset of
dendritic segments, the diameter of the spine heads and the length of the spine necks was
determined to help with the classification of mushroom spines. Since mushroom spines
have large diameters and relatively short neck lengths (Peters and Kaiserman-Abramof,
1970), a spine was classified as mushroom if its diameter was more than twice the size of
the spine neck length.
For among-group analysis of spine density, segments were taken from 8 animals at 20
dpi, 8 animals at 40 dpi, and 4 animals at 80 dpi. The total sample included a total of 111
segments at 20 dpi, 53 segments at 40 dpi, and 20 segments at 80 dpi. For the
quantification of mushroom spine density, segments were taken from 7 animals at 20 dpi,
7 animals and 40 dpi, and 4 animals at 80 dpi. The total sample included 83 segments at
20 dpi, 18 segments at 40 dpi, and 19 segments at 80 dpi. A minimum of four dendritic
segments were taken from each animal.
45
For within-group analysis of spine density, segments were taken from 8 animals at 20
dpi, 8 animals at 40 dpi, and 4 animals at 80 dpi. The total sample included a total of 57
Fos+ and 54 Fos- segments at 20 dpi, 24 Fos+ and 24 Fos- segments at 40 dpi, and 14
Fos+ and 13 Fos- segments at 80 dpi. For the quantification of mushroom spine density,
segments were taken from 7 animals at 20 dpi, 7 animals and 40 dpi, and 4 animals at 80
dpi. The total sample included 45 Fos+ and 38 Fos- segments at 20 dpi, 20 Fos+ and 15
Fos- segments at 40 dpi, and 14 Fos+ and 13 Fos- segments at 80 dpi. A minimum of
four dendritic segments were taken from each animal.
3.9 Statistics
To compare the number of intersections and dendritic length across different age groups
repeated-measures ANOVAs were used with age as the between subject factor and the
distance from the soma (radii) as the within subject factor. Subsequent Fisher’s post-hoc
LSD tests were used to examine overall differences between age groups as well as
differences between age groups at specific radii. In a similar manner, to compare the
total number of dendrites at each branch order a repeated measures ANOVA was used
with age as the between subject factor and branch order as the within subject factor.
Subsequent Fisher’s post-hoc LSD tests were used to examine overall differences
between age groups as well as differences between age groups at specific branch orders.
An unpaired, two-tailed student’s t-test was used to compare branch thickness between
20 and 40 dpi at the 4th
and 5th
branch order and between 20 and 80 dpi at the 4th
and 5th
branch order.
46
To compare spine and mushroom spine density across age groups univariate ANOVAs
were used with age as the between subject factor. Subsequent Fisher’s post-hoc LSD tests
were used to examine differences between age groups. Similarly, to compare the
proportion of GFP cells expressing Fos between age groups a univariate ANOVA was
used with age as the between subject factor. Subsequent Fisher’s post-hoc LSD tests were
used to examine differences between age groups. Finally, to compare the number of
intersections and dendritic length between Fos+ and Fos- neurons for each age group,
repeated-measures ANOVAs were used with Fos expression as the between subject
factor and distance from the soma (radii) as the within subject factor.
47
RESULTS
4.1 Adult-born granule cells mature with age
To characterize the dendritic morphology of adult-born granule cells at various ages, we
used the CAG-retrovirus (Zhao et al., 2006). As expected, neurons at 10 days post-
infection (dpi) showed many immature features such as short processes, varicosities, and
the absence of spines (Figure 4.1).
Figure 4.1: Dendritic morphology of adult-born granule cells at 10 dpi. a, retroviral-
labeling of adult-born granule cells in the dentate gyrus. The square indicates the area
imaged in b. b, a retroviral-labeled neuron. The square indicates the area imaged in c. c,
spines on a dendritic segment. DAPI is blue; GFP is green.
48
Neurons at 20 dpi also showed features of immature neurons such as varicosities, thin
branches, and a low spine density. Despite their immature features, neurons at 20 dpi
showed complex dendritic arborization and the majority of the neurons had dendrites that
reached the outer edge of the molecular layer (Figure 4.2).
Figure 4.2: Dendritic morphology of adult-born granule cells at 20 dpi. a, retroviral-
labeling of adult-born granule cells in the dentate gyrus. The square indicates the area
imaged in b. b, a retroviral-labeled neuron. The square indicates the area imaged in c. c,
spines on a dendritic segment. DAPI is blue; GFP is green.
49
Neurons at 40 and 80 dpi showed complex dendritic arborization and had dendrites
covered with spines (Figures 4.3 and 4.4).
Figure 4.3: Dendritic morphology of adult-born granule cells at 40 dpi. a, retroviral-
labeling of adult-born granule cells in the dentate gyrus. The square indicates the area
imaged in b. b, a retroviral-labeled neuron. The square indicates the area imaged in c. c,
spines on a dendritic segment. DAPI is blue; GFP is green.
50
Figure 4.4: Dendritic morphology of adult-born granule cells at 80 dpi. a, retroviral-
labeling of adult-born granule cells in the dentate gyrus. The square indicates the area
imaged in b. b, a retroviral-labeled neuron. The square indicates the area imaged in c. c,
spines on a dendritic segment. DAPI is blue; GFP is green.
51
4. 2 Dendritic morphology of adult-born granule cells changes with age
To compare dendritic morphology of adult-born granule cells across age groups, Sholl
analysis was conducted for the number of intersections and dendritic length (Figure 4.5).
The number of intersections was significantly different among age groups and radii
(ANOVA, F 3,247 = 21.8, p<0.01; F9,2223 = 58.7, p<0.01, respectively ). The interaction
between groups and radii was significant (F27,2223= 7.59, p=0<0.01) indicating that the
number of intersections across radii depends on the age of the adult-born granule cells.
Dendritic length was also significantly different among age groups and radii (ANOVA, F
3,225 = 29.1, p< 0.01; F 9,2025 = 69.0, p<0.01, respectively). Likewise, the interaction
between groups and radii was significant (F 27,2025 = 9.6; p <0.01) indicating that dendritic
length across radii differs depending on the age of the adult-born granule cells.
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
0 20 40 60 80 100 120 140 160 180 200 220 240 260
Nu
mb
er
of
Inte
rse
ctio
ns
Distance from soma (µm)
10 dpi
20 dpi
40 dpi
80 dpi
* *
* *
* *
* *
* * *
*
* *
* *
* *a
* ** ** *
* ** ** *
* ** ** *
* ** *
* *
* ** ** *
52
Figure 4.5: Sholl analysis for a, the number of intersections and b, dendritic length in
neurons at 10, 20, 40, and 80 dpi. Significant differences are denoted by ** if p<0.01, and
* if p<0.05. Asterisks are red for differences between 10 dpi and 20 dpi, green for
differences between 10 dpi and 40 dpi and purple for differences between 10 dpi and 80
dpi. Asterisks are in green for differences between 20 and 40 dpi and in purple for
differences between 20 and 80 dpi.
As expected, post-hoc Fisher‘s tests revealed that overall, neurons at 10 dpi had a
significantly lower number of intersections and dendritic length than neurons at 20, 40,
and 80 dpi (p<0.01). Specifically, the number of intersections and dendritic length was
significantly lower in neurons at 10 dpi than in neurons at 20, 40, and 80 dpi across 60-
160 m away from the soma (p<0.01). This indicates that neurons at 10 dpi have smaller
dendritic arbors than their older counterparts.
Most interestingly, neurons at 20 dpi had an overall significantly greater number of
intersections and dendritic length than neurons at 40 dpi and 80 dpi (p<0.01).
Specifically, the number of intersections was significantly greater in neurons at 20 dpi
0
10
20
30
40
50
60
70
80
90
100
110
0 20 40 60 80 100 120 140 160 180 200 220 240 260
De
nd
riti
c L
en
gth
(u
m)
Distance from soma (µm)
10 dpi
20 dpi
40 dpi
80 dpi
* ** ** * * *
* *
* *
* *
* *
* *
* * b
* ** *
* ** *
* ** *
* ** *
* ** *
* ** *
* ** *
* ** *
* ** *
* ** *
53
than neurons at 40 and 80 dpi across 80-160 m away from the soma (p<0.05). Dendritic
length was significantly greater in neurons at 20 dpi than neurons at 40 and 80 dpi across
80-180 m away from the soma (p<0.01). Overall, this shows that the dendritic arbors of
neurons at 20 dpi are larger than those of older neurons and suggests a possible pruning
mechanism occurring between 20 to 40 dpi in adult-born granule cells.
To provide another measure of dendritic arbor complexity, branch order analysis was
conducted for the number of dendrites at each branch order (Figure 4.6). There were
significant differences among groups and branch order (ANOVA, F 3,257 = 16.7, p<0.01;
F 6,1542 = 135.0, p<0.01, respectively). The interaction between groups and branch order
was significant (F 18,1542 = 6.7, p<0.01) indicating that number of dendrites across branch
order depends on the age of the adult-born granule cells.
As expected, a post-hoc Fisher‘s test showed that overall neurons at 10 dpi had a
significantly lower number of dendrites than neurons at 20, 40, and 80 dpi (p <0.01).
Specifically, the number of dendrites was significantly lower in neurons at 10 dpi than in
neurons at 20,40, and 80 dpi at the 3rd
and 4th
branch orders (p<0.01). Neurons at 20 dpi
showed an overall significantly greater number of dendrites than neurons at 40 and 80 dpi
(p<0.01). Specifically, significant differences in the number of dendrites were seen at the
3rd
, 4th
, 5th
, and 6th
branch orders (p<0.05). This provides further support for a pruning
mechanism and suggests that more distal dendrites are retracted between 20 to 40 days of
age.
54
Figure 4.6: Branch order analysis for the number of dendrites at 10, 20, 40, and 80 dpi.
Significant differences are denoted by ** if p<0.01, and * if p<0.05. Asterisks are red for
differences between 10 dpi and 20 dpi, green for differences between 10 dpi and 40 dpi
and purple for differences between 10 dpi and 80 dpi. Asterisks are in green for
differences between 20 and 40 dpi and in purple for differences between 20 and 80 dpi.
Although neurons at 20 dpi have larger dendritic arbors than those of their older
counterparts, analysis of branch order thickness shows that dendrites at 20 dpi are smaller
in diameter at higher branch orders than dendrites at 40 and 80 dpi (Figure 4.7). An
unpaired, two-tailed t-test reveals a significant increase in branch thickness from 20 to 40
dpi in the 4th
(t 137 = 3.87, p <0.01) and 5th
branch order (t 91 = 4.68, p< 0.01) and from 20
to 80 dpi in the 4th
(t 124 = 4.67, p< 0.01) and 5th
branch order (t 92= 5.36, p< 0.01).
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
1 2 3 4 5 6 7
To
tal
Nu
mb
er
of
De
nd
rite
s
Branch Order
10 dpi
20 dpi
40 dpi
80 dpi
** *
* *
* *
* *
* *
* ** ** *
* ** ** * * *
* ** ** *
* * *
55
Figure 4.7: Branch order analysis for branch thickness at 20, 40, and 80 dpi. Significant
differences between neurons at 20 dpi and 40 dpi are denoted by * * if p<0.01.
Significant differences between neurons at 20 dpi and 80 dpi are denoted by * * if
p<0.01, and * if p<0.05.
4. 3 Spine density of adult-born granule cells changes with age
There was a significant difference in spine density between groups (ANOVA, F 2,181 =
139.7, p< 0.01). As expected, a Fisher‘s post-hoc analysis showed that spine density at 20
dpi was significantly less than at 40 dpi (p<0.01) and 80 dpi (p<0.01) (Figure 4.8a). Spine
density at 20 dpi was also considerably more variable between dendritic segments than at
40 and 80 dpi (Figure 4.8b) reinforcing that a considerable amount of spine growth
occurs around this time.
0
0.5
1
1.5
2
2.5
1 2 3 4 5
Bra
nch
Th
ick
ne
ss (
um
)
Branch Order
20 dpi
40 dpi
80 dpi
* * * *
* * * *
56
There was also a significant difference in mushroom spine density between groups
(ANOVA, F 2,117 = 29.0, p<0.01). As expected, a Fisher‘s post-hoc analysis showed that
spine density at 20 dpi was significantly less than at 40 (p<0.01) and 80 dpi (p<0.01)
(Figure 4.8 c).
Figure 4.8: Spine analysis at 20,40, and 80 dpi. a, spine density analysis. b, cumulative
probability plot of spine density. c, mushroom spine density analysis. Significant
differences are denoted by * * if p<0.01 and * if p<0.05
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Sp
ine
s/u
m
Days Post Injection20 40 80
a ** **
0
20
40
60
80
100
<0.05 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Cu
mu
lati
ve
pro
ba
bil
ity
(%
)
Spines/µm
20 dpi
40 dpi
80 dpi
b
>1.0
0
0.1
0.2
0.3
0.4
0.5
Mu
shro
om
sp
ine
s/u
m
20 40 80Days Post Injection
c ** **
57
4.4 Seizure induction activates Fos
Animals were characterized has having a seizure when they exhibited generalized clonic
activity. Seizure activity resulted in strong Fos expression throughout the dentate gyrus
(Figure 4.9).
Figure 4.9: Fos expression in the dentate gyrus following PTZ induced seizures. a, Fos
expression in the dentate gyrus following a PTZ induced seizure b, DAPI. c, An overlay
of Fos (red) and DAPI (blue).
58
4. 5 Proportion of GFP+ cells expressing Fos increases with age
Fos was not seen in neurons at 10 dpi. A subset of GFP-labeled neurons at 20, 40, and 80
dpi showed Fos expression following PTZ-induced seizures (Figure 4.10).
Figure 4.10: a, Fos expression in the dentate gyrus following a PTZ induced seizure. The
square indicates the area imaged in b. c, Co-localization between GFP and Fos. GFP is
green and Fos is red.
59
There was a significant difference in the proportion of GFP+ labeled granule cells
expressing Fos following PTZ-induced seizures between groups (ANOVA, F 3,48 =
415.2, p <0.01 ) (Figure 4.11). A Fisher‘s post-hoc revealed that the proportion of GFP+
cells expressing Fos was significantly less at 10 dpi than at 20,40, and 80 dpi (p<0.01). A
Fisher‘s post-hoc also revealed that the proportion of GFP+ cells expressing Fos was
significantly less at 20 dpi than at 40 and 80 dpi (p<0.01). This parallels with the
functional maturation of adult-born granule cells and suggests that adult-born granule
cells are more likely to be functionally integrated into dentate gyrus circuitry as they age,
particularly between 20 and 40 days of age.
Figure 4.11: The proportion of GFP cells positive for Fos following PTZ induced
seizures at 10, 20, 40, and 80 dpi. Significant differences are denoted by * * if p< 0.01.
0
10
20
30
40
50
60
70
80
90
100
GF
P +
/ F
os
+ n
eu
ron
s (%
)
Days Post Injection
40 8020
** **
10
** ** **
60
4. 6 Dendritic morphology does not differ between Fos+ and Fos– neurons
within groups
Contrary to our hypothesis, Fos+ and Fos- neurons at 20 dpi showed no significant
differences in dendritic morphology (Figure 4.12). There were no significant differences
in the number of intersections between Fos+ and Fos- neurons (ANOVA, F 1,79 = 0.00,
p=0.99) and the interaction between groups and radii was non-significant (ANOVA, F
9,711 = 0.89, p=0.53). Likewise, there were no significant differences in dendritic length
between Fos+ and Fos- neurons (ANOVA, F 1,79 = 0.00, p=0.96) and the interaction
between groups and radii was non-significant (ANOVA, F 9,711 = 1.1, p=0.94 ).
Fos+ and Fos – neurons at 40 dpi also showed no significant differences in dendritic
morphology (Figure 4.13). There were no significant differences in the number of
intersections between Fos+ and Fos- neurons (ANOVA, F 1,99 = 0.90, p=0.77 ) and the
interaction between groups and radii was non-significant (F 9,891 = 0.55, p=0.84).
Likewise, there were no significant differences in dendritic length between Fos+ and Fos-
neurons (ANOVA, F 1,99 = 0.00, p=0.96) and the interaction between groups and radii
was non-significant (F 9,891 = 0.61, p=0.79).
Finally, Fos+ and Fos– neurons at 80 dpi showed no significant differences in dendritic
morphology (Figure 4.14). There were no significant differences in the number of
intersections between Fos+ and Fos- neurons (ANOVA, F 9,891 = 0.61, p=0.79) and the
interaction between groups and radii was non-significant (F 9,432 = 1.93, p=0.05).
Likewise, there were no significant differences in dendritic length between Fos+ and Fos-
neurons (ANOVA, F 1,48 = 0.24, p=0.63) and the interaction between groups and radii
was non-significant (F 9,432 = 1.76, p=0.07).
61
Figure 4.12: Sholl analysis for a, the number of intersections and b, dendritic length in
Fos+ and Fos- neurons at 20 dpi.
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62
Figure 4.13: Sholl analysis for a, the number of intersections and b, dendritic length in
Fos+ and Fos- neurons at 40 dpi.
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63
Figure 4.14: Sholl analysis for a, the number of intersections and b, dendritic length in
Fos+ and Fos- neurons at 80 dpi.
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64
4. 7 Spine density between Fos+ and Fos– neurons does not differ within
groups
There were no significant differences in spine density between Fos+ and Fos- neurons at
20 dpi (t-test, t56 = 0.97, p=0.34), 40 dpi (t-test, t46= 1.13, p=0.27), and 80 dpi (t-test,
t25=0.77, p=0.45) (Figure 4.15).
Figure 4.15: Spine density between Fos+ and Fos- neurons at a, 20 dpi; b, 40 dpi, and c,
80 dpi.
0
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65
There were also no significant differences in mushroom spine density between Fos+ and
Fos- neurons at 20 dpi (t-test; t81 = 0.81, p=0.42), 40 dpi (t-test ; t33= 0.77, p=0.45), and
80 dpi ( t25 = 0.52, p=0.61) (Figure 4.16).
Figure 4.16: Mushroom spine density between Fos+ and Fos- neurons at a, 20 dpi; b, 40
dpi, and c, 80 dpi.
0
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66
DISCUSSION
5.1 Maturation of adult born-granule cells
5.1.1 Dendritic morphology of adult-born granule cells changes with age
To date, few studies have examined changes in the dendritic arbor of adult-born
hippocampal granule cells with age. The few studies to do so looked at only two
parameters: total dendritic length and total number of branch points (Van Praag et al.,
2002; Esposito et al., 2005; Zhao et al., 2006). They also looked at a limited number of
time points: Esposito and colleagues (2005) compared neurons at 14 and 28 dpi, and
Zhao and colleagues (2006) qualitatively assessed neurons at various time points;
however, only quantitatively assessed neurons at 12 and 16 dpi. Our study is therefore the
first to provide a comprehensive assessment of dendritic morphology at several time
points (10,20,40 and 80 dpi).
We found that dendrites matured as expected from 10 to 20 dpi, with an overall increase
in dendritic length and the number of dendritic branches. Unexpectedly, we found that
neurons at 20 dpi had an overall greater dendritic length and a greater number of
intersections than neurons at 40 and 80 dpi. This suggests that the maturation of adult-
born granule cells involves a growth phase, followed by an active pruning process. This
is the first study to suggest that adult-born neurons undergo pruning.
5.1.2 Spine density across age groups
As expected, spine and mushroom spine density increased from 20 dpi to 40 dpi. This
agrees with a study by Zhao and colleagues (2006) that also noted a significant increase
67
in spine density between similar time points (21 dpi and 42 dpi). However, while Zhao
and colleagues found an increase in mushroom spine density from 56 dpi to 126 dpi, we
did not find a significant increase from 40 dpi to 80 dpi. These differences could result
from different imaging and quantification methods used. Zhao and colleagues used
confocal imaging for spine analysis while we used an epifluorescent microscope.
Furthermore, they classified a spine as mushroom if it had a spine head surface area of
less than 0.4 µm 2, while we classified a spine as mushroom if its spine diameter was
more than twice the size of the spine neck length. Alternatively perhaps our results differ
from those of Zhao and colleagues because mushroom spine density remains stable from
40 to 80 dpi, and only significantly increases after 80 dpi.
5.1.3 Dendritic pruning during embryogenesis and adult neurogenesis
Although dendritic pruning during adult neurogenesis has not been examined, dendritic
pruning during embryogenesis has been extensively studied in different species and in
different regions of the brain (reviewed by Hua and Smith 2004). For example, afferent
pruning has been examined in the cerebellum, the somatosensory cortex, and brain
regions involved in vision, such as the superior colliculus and lateral geniculate nucleus.
The maturation of dendritic arbors in dentate granule neurons has been most studied in
rats using intracellular labeling techniques, such as horseradish peroxidase labeling and
Golgi staining. An important study by Rihn and Claiborne (1990) showed that granule
cells reach adult size early in their development, at around day 14. From 14 to 60 days of
age, the neurons showed elongation of dendritic branches and a loss of dendritic
branches, leading to an overall conservation in total dendritic length. Zher and colleagues
68
(2008) found further evidence of dendritic pruning in granule cells by comparing neurons
in male hamsters that were 21 days old and 35 days old. They found that granule neurons
at 35 days of age showed significantly fewer intersections and dendritic length than
granule neurons at 21 days of age in the inner two thirds of the dendritic arbor.
Overall, our findings show many similarities with studies that assessed dendritic
maturation during early post-natal development. Similarly to Rihn and Claiborne (1990),
we observed a decrease in the number of dendritic segments between younger and older
granule neurons. Like Zher and colleagues (2008), we also observed a decrease in the
number of intersections and dendritic length between younger and older granule neurons
in the inner two-thirds of the dendritic arbor.
Unlike Rihn and Claiborne, we did not find a total conservation of total dendritic length
between neurons at 20 dpi and those at 40 and 80 dpi. Differences in the technique used
could account for this discrepancy. While Claiborne and colleagues (1990) used 400 m
thick coronal sections, we used only 50 m sections. Cutting at 50 m could have
underestimated dendritic length, particularly in more distal dendritic segments.
Alternatively, dendritic pruning mechanisms may differ between rats and mice or
between neuronal development in early post-natal and adult animals.
5.1.4 Mechanisms of dendritic pruning in adult-born granule cells
While the morphological development of granule cells during early post-natal
development has been extensively studied, few studies have examined the development
of granule cells in the adult brain. By suggesting that adult-born granule cells undergo
pruning, this study draws a possible new parallel between dendritic maturation in early
69
post-natal development and adulthood and introduces new avenues of research. For
example, it would be interesting to examine whether molecular signals that affect
neuronal pruning during early post-natal development, such as caspases (Williams et al.,
2006) and RhoGTPases (Hall et al., 2000), also affect pruning in the adult brain.
Alongside various molecular signals, it is clear that activity influences dendritic pruning
in early post-natal development. Pruning has been linked to both spontaneous activity
(Hooks and Chen, 2006) and afferent-dependent activity driven by sensory experience
(Bodnarenko et al., 1995; Antonini and Stryker, 1996). Since we observed a decrease in
dendritic length from 20 to 40 dpi, and spontaneous activity driven by the depolarizing
effect of GABA ends around 20 dpi (Ge et al., 2007) it is unlikely that any pruning is
driven by spontaneous activity. Consequently, it would be interesting to examine if
afferent-dependent activity drives pruning.
In adult neurogenesis, experience-dependent activity has been shown to be an important
regulator of adult-born cell survival in the dentate gyrus. The survival of 1-2 week old
adult-born granule cells is increased by hippocampal-dependent learning such as trace-
eye blink conditioning and spatial learning in a water maze task (Gould et al., 1999).
Likewise, stimulation of the perforant path increases adult-born granule cell survival
(Bruel-Jungermann et al., 2006). Here, we propose that experience-dependent activity
first plays an important role in selecting granule cells for survival; then, activity further
fine-tunes these neurons through an active pruning process.
5.1.5 The significance of dendritic pruning in adult-born cells
70
The occurrence of a pruning mechanism from 20 to 40 dpi would correspond well with
the anatomical and functional integration time course of adult-born granule cells. At
around 20 dpi, adult-born neurons start to establish glutamatergic synaptic connections
with afferents originating from the perforant pathway (Esposito et al., 2005; Toni et al.,
2007). Incoming activity from these afferents could influence dendritic pruning.
Furthermore, since dendritic growth dynamics and synaptic scaling are coordinated (Peng
et al., 2009), it is possible that pruning occurs to balance the formation of new excitatory
synapses and prevent the adult-born granule cells from overexcitation.
The role of dendritic pruning during development is mainly to sharpen responses to
sensory input (Hua and Smith, 2004). During adulthood, dendritic pruning may serve to
maximize a neuron‘s ability to integrate synaptic input and make an important
contribution to dentate gyrus function. Whether adult-born granule cells make a similar
contribution to dentate gyrus function as mature granule cells or whether they make a
unique contribution remains debated. Either way, pruning is likely to help shape neurons
for their functional role.
A recent study by Schmidt-Hieber and colleagues (2007) has shown that dentate granule
cells propagate distal synaptic signals to the soma quickly with little attenuation, unlike
neurons in other regions of the hippocampus such as the CA1 region. The authors
suggested that this contributes to the role of the dentate gyrus in separating similar input
patterns from the entorhinal cortex. They also attributed the ability to relay voltage
signals faithfully from distal segments to the soma on the neuron‘s compact electrotonic
structure, which is determined by passive membrane properties (ie. membrane resistance)
and morphology. Since passive membrane properties are relatively uniform between
71
neurons of a particular type, dendritic morphology can greatly shape this property.
Pruning may therefore play an important role in sculpting dendritic arbors of adult-born
granule cells for optimal function, whether that involves helping separate spatial input,
like mature granule cells (Celland, 2009), or integrating similar spatial input and
separating it on a temporal scale (Aimone, 2009).
In general, pruning in higher level processing areas, such as the dentate gyrus, has not
been very well examined. Rather, dendritic pruning has mostly been examined in vivo by
manipulating sensory experience and examining subsequent changes in dendritic
arborization within sensory areas. Therefore, if pruning does indeed occur in adult-born
cells within the dentate gyrus it will introduce an exciting new area of research.
5.1.6 Alternative explanation for pruning
Although it is possible that a pruning mechanism occurs in adult-born granule cells
between 20 and 40 days, limitations in the analysis make it difficult to provide strong
support for this idea. Since we only looked at snapshots of neuronal maturation (ie. at 20
and 40 days) we can only guess what happened in between and an explanation other than
pruning may explain the decrease in arborization from 20 to 40 days. For example, it is
possible that 20 day old adult-born granule cells with less complex arborization are
selected for survival over neurons with more complex arborization. Apoptosis of adult-
born cells continues until four weeks after birth (Dayer, 2003) and the preferential
survival of neurons with less complex arborization may result in neurons with less
complex arborization on average in the 40 day group. A high degree of arborization may
pose a disadvantage to a neuron due to the high metabolic costs associated with lots of
72
dendrites and the risk of overexcitation (Peng et al., 2009). Selection of these neurons for
apoptosis may therefore be part of an important homeostatic mechanism. This alternative
hypothesis can be tested by staining for apoptotic markers at 20 days such as caspase-3,
and determining whether neurons with more complex arborization are more likely to be
colocalized with these markers.
5.2 Functional integration of adult-born cells into dentate gyrus circuitry
As hypothesized, we found that adult-born cells became more responsive to hippocampal
stimulation as they matured. We did not observe Fos expression in adult-born neurons at
10 dpi following PTZ induced seizures, and found that significantly more neurons
expressed Fos at 40 and 80 dpi than at 20 dpi. This parallels the observations made by
Jessberger and Kempermann (2003), who also found that adult-born cells at 15 dpi did
not express Fos following KA-induced seizures, and that significantly more neurons
expressed Fos at 35 than 25 dpi. Similarly, studies have shown that significantly more
mature granule cells express Fos than younger granule cells following hippocampal
stimulation with a water maze task (Jessberger and Kempermann, 2003; Kee et al.,
2007). In line with these studies, our results suggest that adult-born cells are incorporated
into dentate gyrus circuitry and this incorporation is age-dependent.
5.3 Morphological differences between Fos+ and Fos- neurons
Contrary to our hypothesis, we found no significant differences in dendritic complexity
and spine density between Fos+ and Fos– neurons at 20, 40, or 80 dpi following PTZ
induced seizures. Since neurons that are integrated into dentate gyrus circuitry are likely
73
to respond to seizure stimulation, our results suggest that integration into dentate gyrus
circuitry is not correlated with adult-born cell morphology.
Alternatively, perhaps morphological features do influence the ability of adult-born
granule cells to become integrated into dentate gyrus circuitry, and these differences
simply could not be detected using our experimental design. For example, perhaps
differences in morphology are evident at time points not examined in our study, such as a
few days before or after 20 dpi (ie. 16-24 dpi). The use of different forms of hippocampal
stimulation, such as learning, might also show differences in morphology between
integrated and non-integrated neurons. Finally, differences in other properties influencing
dendritic computation that were not examined by our study could influence functional
integration.
5.3.1 Examining morphological differences between Fos+ and Fos- neurons shortly
before or after 20 days of age
Adult-born granule cells undergo considerable changes in excitability and synaptic
connectivity around 20 days of age, suggesting that this is an important time for
functional integration. Around 2-3 weeks the effect of GABA switches from excitatory to
inhibitory and at 3 weeks of age somatic GABAergic contacts are made resulting in fast
inhibitory GABAergic post-synaptic potentials (Esposito et al., 2005). Spines begin to
form at 16 days of age (Zhao et al., 2006), and around 2.5-3.5 weeks of age excitatory
glutamatergic contacts are also made (Esposito et al., 2005). The results of our study
further suggest that significant morphological changes occur from 20-40 dpi. Together,
these findings suggest that differences in dendritic morphology and spine density may
influence integration into dentate gyrus circuitry around 20 days of age. Although we did
74
not find any differences between Fos+ and Fos– neurons at 20 days of age, it is possible
that there is a time frame before or after 20 dpi where dendritic and spine properties
influence the likelihood of a neuron becoming integrated into dentate gyrus circuitry.
5.3.2 Differences in hippocampal stimulation following seizures and learning tasks
It is possible that we failed to see morphological correlates of functional integration
because of our hippocampal stimulation paradigm. Seizures may not have been the best
way to discriminate between Fos+ and Fos- neurons, as approximately 40% of our
neurons were Fos+ at 20 dpi, and 85 % were Fos+ at 40 and 80 dpi. On a functional level,
this suggests that at all time points, a large proportion of neurons were functionally
integrated into dentate gyrus circuitry. In other words, once GABA inhibition was
removed by PTZ, excitatory input from afferent connections helped elicit neuronal firing.
As adult-born neurons are likely to functionally integrate if they have survived to two
weeks of age (Bischofberger and Schinder, 2008), it is not surprising to see such high
levels of Fos activation in adult-born cells.
In contrast, in learning paradigms, discrimination between Fos+ and Fos- neuronal
populations is much higher with approximately only 1 % of adult-born neurons
expressing Fos at 14 dpi, 2 % expressing Fos at 28 dpi, and 4 % expressing Fos at 42 dpi
during memory recall (Kee et al., 2007). On a functional level, this suggests that a very
small proportion of adult-born neurons within the hippocampus are selected to be part of
a given memory trace. Since the probability of being activated and expressing Fos is
lower in memory tasks, it is possible that differences in morphology between integrated
and non-integrated neurons will be more apparent, should they exist.
75
Recent studies lend further support for the idea that differences in morphology correlate
with differences in functional integration within memory networks. Dupret and
colleagues (2008) found that learning promotes the survival of mature-adult born neurons
at the expense of immature neurons, suggesting the presence of a homeostatic mechanism
by which learning selects neurons for survival. A subsequent study by Tronel and
colleagues (2010) found that the mature neurons selected for survival following learning
have more complex dendritic arbors and spine density than controls. Together, the
findings from these studies suggest that morphological complexity could promote
functional integration into dentate gyrus circuitry.
5.3.3 Dendritic computational properties
The role of a neuron is to transform synaptic input into patterns of synaptic output. Its
ability to integrate a range of synaptic input into output involves combining changes in
voltage across the neuron into a single change in membrane potential (Magee, 2000).
Undoubtedly, neuronal morphology affects synaptic integration. The length of dendrites,
the number of dendrites, the degree of branching, and synaptic density influences
neuronal excitation (Brown et al., 2008). Studies have also linked changes in dendritic
arborization and spine density with changes in learning (Eadie et al., 2005; Liu et al.,
2008). Overall, neuronal morphology provides a simple measure of synaptic integration.
By analyzing only morphology, however, differences in dendritic properties between
Fos+ and Fos– neurons may be overlooked.
Dendritic computation is complex and is influenced by not only morphology, but also by
biophysical properties. Voltage-gated ion channels and synaptic properties have a
76
particularly important effect on neuronal computation (Magee, 2009). Synaptic scaling
has especially received a lot of attention over the past few years (reviewed by Turrigiano,
2008). Synaptic scaling is characterized by a neuron increasing or decreasing the strength
of its synapses to stabilize neuronal excitability. This is accomplished by changing local
levels of AMPA glutamate receptors. Interestingly, a recent study by Peng and colleagues
(2009) showed that dendritic arborization and synaptic scaling are coordinated during
development. A complex interplay between dendritic arborization and synaptic scaling
may therefore influence functional integration of adult-born granule cells.
5.4 Technical limitations
5.4.1 Dendritic morphology analysis
The thickness of the sections used for analysis limited our ability to analyze the
morphology of neurons as a whole. Sections were cut at 50 m since this is the maximum
thickness sections can be cut at for immunohistochemistry; unfortunately, sections
thicker than 50 m do not allow antibodies to penetrate the tissue. Although sections at
50 m still allow for morphological analysis, they underestimate various morphological
parameters such as dendritic length since dendrites are cut when sectioning. The total
dendritic length of dentate granule cells in mice has been shown to be as great as 2264
m in 2- to 4-month-old C57BL/6 mice, as determined by filling neurons in 350 m
sections with biocytin and using two-photon microscopy (Schmidt-Hieber et al., 2007).
Fortunately, slices were cut along the transverse plane in our study, and the transverse
spread of dentate granule cells is approximately twice the size of the longitudinal spread
along the septotemporal axis (Claiborne et al., 1990). Furthermore, the majority of
77
granule cells have their transverse spread at, or within 30 degrees of the transverse plane.
This limits the amount of dendritic cutting.
5.4.2 Spine morphology analysis
In this experiment, spines were acquired using an epifluorescent light microscope. The
use of other microscope systems, particularly a confocal microscope, could have
provided greater resolution. Light and confocal microscopes have similar pixel
resolution, however, voxel resolution is considerably greater in the confocal system
allowing for more accurate assessment of spine volume. Furthermore, spines can be
captured in all the z planes with a confocal microscope (ie. spines pointing toward and
away from the observer), while they can only be captured in the x and y planes with an
epifluorescent microscope.
Along with the type of microscope system used, the type of stain can have a great impact
on the visualization of spines. Fluorescence can result in high background making it
difficult at times to distinguish spines from other sources of noise, especially tiny spines
that have small diameters. GFP fluorescence intensity can also vary between neurons
depending on where the retrovirus incorporates within the host genome. At times, the
retrovirus can label adult-born neurons poorly making small spines difficult to see. This
limits the sample of neurons that could be used for analysis. Stains such as DAB pose
considerably less problems and are easier to visualize; however, they cannot be co-
localized with Fos staining.
5.4.3 Surgery
78
The retrovirus has considerable advantages over other techniques used to label neuronal
precursors, such as BrdU, as it labels the entire neuron and does not lose signal over time.
However, unlike other labeling techniques, it is quite invasive and requires delivery by
stereotaxic surgery. As with any other invasive technique, the surgery can induce local
inflammatory reactions. Interestingly, inflammation induced by lipopolysaccharide
injections does not affect neuronal morphology of adult-born cells (Jakubs et al., 2008)
including differences in neuronal location, dendritic complexity, and spine density. It
does, however, result in enhanced GABA-mediated inhibition. Inflammation also
activates microglia that release cytokines and growth factors (Ekdahl et al., 2009) and
can potentially affect dendritic morphology. To avoid any such influences, neurons in
proximity to the site of injection were excluded from analysis.
79
FUTURE DIRECTIONS
The results from our study introduce exciting new avenues of research. A particularly
interesting question arising from this work is: Does neuronal activity induced by learning
affect the pruning of adult-born granule cells? We are currently working to address this
question. Furthermore, although we did not find any significant differences in neuronal
morphology between Fos+ and Fos- neurons following PTZ induced seizures at 20,40, or
80 dpi, it would be interesting to see if differences between Fos+ and Fos– neurons are
found shortly before or after 20 dpi, particularly at 16,18,22,and 24 dpi as these are times
of considerable change in synaptic connectivity. It would also be interesting to examine
whether differences in dendritic morphology affect functional integration into dentate
gyrus memory networks.
6. 1 Does afferent activity induced by learning affect the pruning of adult-
born granule cells?
During development, afferent-dependent activity driven by sensory experience has been
shown to influence pruning (reviewed by Wong and Ghosh, 2002). It would be
interesting to see if afferent-dependent activity driven by learning influences pruning of
adult-born granule cells. Here, I propose three possible effects of afferent-dependent
activity driven by learning on pruning.
First, it is possible that afferent-dependent activity promotes survival of dendritic
branches. Early in their development, trophic factors and other molecular signals would
promote dendritic growth, irrespective of any synaptic input. Later in their development,
dendrites would sense their environment. The formation of synaptic contacts driven by
80
learning would stabilize and maintain the dendrite, while the absence of synaptic contacts
would trigger a pruning mechanism. Although pruning is metabolically costly, it may
help a neuron conserve energy over the long-term by eliminating the need to sustain
dendrites that are not being used. Evidence for activity maintaining dendritic structure
comes from a study by Rajan and Cline (1998), where they showed that blocking
glutamate activity led to a loss of dendritic branches in the rectal neurons of Xenopus.
A second possibility is that afferent-driven activity promotes dendritic pruning. A
dendritic arbor with multiple branches and extensive dendritic length may not be able to
effectively integrate neuronal input. Synaptic activity driven by sensory input or learning
would therefore prune dendritic arbors accordingly. In sensory systems within the brain,
neurons with small receptive fields maximize the signal to noise ratio for neuronal input.
Adult-born granule neurons in the adult brain may work in a similar manner.
Support for the role of afferent-driven activity promoting dendritic pruning is provided by
a study by Blake and Claiborne (1995). The authors examined the growth pattern of
dendrites in granule cells from 14 to 24 days of age in developing rats. In control
conditions, the authors observed a decrease in the number of branches from 14 to 24 days
of age. Upon blocking N-methyl-D-aspartate (NMDA) glutamate receptors, the authors
did not observe dendritic branch loss. This suggests that activity promotes dendritic
pruning. In light of these findings, the authors proposed that an increase in sensory input
to the entorhinal cortex around 14 to 24 days of age shapes the dendritic arbors of granule
cells.
81
We plan on testing these two theories using the following experimental design (Figure
6.1). First, we will stereotaxically infuse the CAG-retrovirus into the dentate gyrus of
three groups of animals. The first group will be sacrificed at 20 dpi, while the second
group will be sacrificed at 40 dpi. The dendritic morphology of both groups will be
analyzed and consistent with our current study, we expect to see greater dendritic length
and number of intersections in the 20 dpi group than in the 40 dpi group. The third group
will be subjected to a water maze training and testing protocol for 8 days (3 trails a day
and a probe test on alternating test) starting at 20 dpi. We hypothesize that if afferent-
dependent activity driven by learning promotes the survival of dendritic length and
branches, then animals subjected to water maze training and testing will have greater
dendritic length and a greater number of dendritic branches at 40 dpi than controls.
Alternatively, if afferent-driven activity driven by learning increases pruning of dendritic
length and branches, then animals subjected to water maze trainng and testing will have
less dendritic length and a fewer number of dendritic branches at 40 dpi than controls.
82
Figure 6.1: Experimental design for investigating the effects of activity induced by
learning on pruning. The retrovirus will be stereotaxically infused into the dentate gyrus
and animals in group 1 will be perfused 20 days later. Animals in group 2 will be
perfused 40 days later. Animals in group 3 will be trained and tested in the water maze
starting at 20 days, and will be perfused at 40 days. The time from surgery to perfusion
corresponds to the age of the adult-born granule cells.
A third possibility is that afferent- driven activity controls dendritic growth in a
homeostatic manner. Afferent-driven activity might ‗fine-tune‘ dendrites of adult-
generated granule cells by increasing the length of a dendritic arbor, keeping it the same,
or decreasing it depending on other biophysical properties of the dendrite such as
synaptic properties. It would be interesting to test this theory should the other two
theories I presented prove to be incorrect. As synaptic activity is largely dependent on the
level of AMPA receptors (Turrigiano, 2008), testing this theory would involve comparing
the ratio of AMPA receptors to dendritic length within individual neurons. Neurons that
show a significant reduction in length from 20 to 40 dpi should have higher levels of
83
AMPA receptors, while neurons that do not show a significant reduction in length from
20 to 40 dpi should have lower levels of AMPA receptors.
6.2 Do differences in dendritic morphology and spine density at or before 20
days of age affect functional integration into dentate gyrus circuitry following
PTZ seizures?
Considerable changes in synaptic connectivity and neuronal excitability occur around 20
days of age. Although we did not find any differences in dendritic morphology or spine
density at 20 dpi, it would be interesting to see if these differences are apparent before or
after this time point, particularly at 16, 18, 22, or 24 dpi. This can be tested by
stereotaxically infusing the retrovirus into the dentate gyrus of mice, and subjecting them
to PTZ-induced seizures at 16,18, 22, or 24 dpi (Figure 6.2). Similar to the hypothesis
made in our study, we hypothesize that Fos+ neurons will have greater dendritic
complexity and spine density than Fos- neurons.
84
Figure 6.2: Experimental design for examining morphological correlates of functional
integration following PTZ induced seizures. The retrovirus will be stereotaxically infused
into the dentate gyrus and 16,18,22, or 24 days later seizures will be induced and the
mice perfused. The time from surgery to perfusion corresponds to the age of the adult-
born granule cells.
6.3 Do differences in dendritic morphology affect functional integration into
dentate gyrus memory networks?
While most neurons that survive past two weeks of age are functionally incorporated into
dentate gyrus circuitry, only a select few are functionally incorporated into memory
circuitry following a learning task. Greater dendritic arborization and spine density might
increase the likelihood that adult-born neurons will be functionally incorporated into a
given memory trace. To test this theory, the CAG-retrovirus will be stereotaxically
infused into the dentate gyrus of mice to label the dividing cell population (Figure 6.3).
Either 10, 20, 40, or 80 days later mice will be trained in the water maze (5 days, 6 trials
per day). One day later, animals will be tested, perfused, and the tissue will be processed
for Fos immunohistochemistry. Dendritic morphology and spine density between Fos+
85
and Fos- neurons will then be compared. Similar to the hypothesis made in our study, we
hypothesize that Fos+ neurons will have greater dendritic complexity and spine density
than Fos- neurons. If no differences are found, it would be interesting to examine
dendritic and spine differences between Fos+ and Fos– neurons a few days before or after
20 dpi (ie. 16 – 24 dpi), as this is a time of considerable change in synaptic connectivity
and differences between Fos+ and Fos– neurons may be evident at one of these time
points.
Figure 6.3: Experimental design for investigating morphological correlates of functional
integration into a spatial memory network. The retrovirus will be stereotaxically infused
into the dentate gyrus and animals will start training in the water maze 20, 40 or 80 days
later. Training will take place for 5 days with 6 trials per day. One day later animals will
tested and perfused.
Unfortunately, because the retrovirus labels a maximum of 100 neurons at 20 dpi and
previous studies have shown that approximately 2 % of adult-born neurons express Fos
following such a task (Kee et al., 2007), finding Fos+ neurons following a water maze
protocol will prove to be very challenging. This obstacle can be overcome by using a
86
CRE-ERT2ROSA-YFP mouse (Figure 6.4). In this mouse, the expression of CreERT2 is
driven under the control of a Nestin promoter. An IP injection of tamoxifen activates Cre
by binding to ERT2 receptors. Once activated, Cre excises a YFP stop codon. This results
in expression of YFP. The start of IP tamoxifen injections approximates the birth-date of
adult-born granule cells. Unlike the retrovirus, this technique should theoretically label
all adult-born granule cells in the mouse brain, providing us with the opportunity to find a
greater number of Fos+ neurons. These mice are currently successfully bred by our lab;
however, we are finding it difficult to visualize spines with the YFP labeled neurons.
Figure 6.4: The YFP construct before and after Cre-mediated recombination. Prior to Cre
activation, a YFP stop codon prevents YFP from being expressed. Following Cre
activation by tamoxifen, the YFP stop codon is excised resulting in YFP expression.
Arrows show the direction of transcription. Triangles represent loxP target sites for Cre-
mediated recombination.
87
CONCLUSIONS
Our understanding of mammalian neurogenesis has significantly advanced since its
discovery in the human brain more than a decade ago. In 2006, the CAG-retrovirus
introduced a particularly exciting labeling technique by allowing us to track the
morphological development of adult-born cells. The results of our study provide further
insight into the morphological development of adult-born granule cells by unexpectedly
showing that their dendritic arbors decrease in size from 20 to 40 days of age. This
suggests for the first time that adult-born granule cells undergo an active pruning process
during their maturation. Dendritic pruning is common in early post-natal development
and its occurrence in adult-born granule cells introduces exciting new avenues of
research. If pruning does occur, it is important to examine the factors controlling this
mechanism in order to gain a better understanding of how adult-born granule cells
functionally integrate into dentate gyrus circuitry and contribute to hippocampal-
dependent behaviours.
Along with allowing us to track the morphological development of adult-born granule
cells, the CAG retrovirus, together with other techniques, allows us to investigate factors
affecting the anatomical and functional integration of adult-born granule cells. For the
first time, our study investigates if dendritic morphology and spine density influence
whether or not adult-born granule cells integrate into dentate gyrus circuitry. Contrary to
our hypothesis, we did not find any significant morphological differences between adult-
born granule cells that were integrated into circuitry and those that were not integrated at
20,40, and 80 dpi. It is important to extend this experiment to memory tasks to determine
88
whether morphological differences affect the integration of adult-born granule cells into a
memory trace. Other measures influencing dendritic computation, such as synaptic
scaling, might also need to be considered.
In today‘s society, many individuals suffer from neurodegenerative disorders such as
Alzheimer‘s, Parkinson‘s and Huntington‘s disease. Adult-born neurons hold great
promise for neuroregenerative therapy. Before we can harness their potential, however,
we need to better understand the factors affecting their anatomical and functional
integration into dentate gyrus circuitry. A better understanding of their functional
integration will also help us identify their contribution to dentate gyrus circuitry and
therefore allow us to better help those individuals suffering from neurological disorders
where neurogenesis is reduced. Our study advances our understanding of adult-born
granule cells and introduces new questions that pave the road for important future
research.
89
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