determination of the sub-cellular mechanisms underlying ... · toxins which mimic purported...
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Determination of the Sub-Cellular Mechanisms Underlying Neurodegeneration in Parkinson’s Disease
by
Christopher J Yong-Kee
A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Department of Cell & Systems Biology
University of Toronto
© Copyright by Christopher J Yong-Kee 2013
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Determination of the Sub-Cellular Mechanisms Underlying
Neurodegeneration in Parkinson’s Disease
Christopher J Yong-Kee
Doctor of Philosophy
Department of Cell & Systems Biology University of Toronto
2013
Abstract
Parkinson’s disease (PD) is the second most common neurodegenerative disease affecting
approximately 1.8% of the population over 65 years of age. It is characterized by three cardinal
symptoms: bradykinesia, muscle rigidity and resting tremor. Symptoms are presented following
50% loss of dopaminergic neurons within the substantia nigra pars compacta (SNc).
Neurodegeneration is associated with reactive oxygen species (ROS) production, protein
aggregation, mitochondrial dysfunction, ubiquitin-proteasome system (UPS) inhibition and
lysosomal malfunction; however it is unclear if a single mechanism or multiple mechanisms lead
to disease onset. The primary aim of the studies described in this thesis was to elucidate the
interactions between various pathological mechanisms underlying PD pathology. An
examination of organelle function during exposure of SH-SY5Y neuroblastoma to a variety of
toxins which mimic purported pathological processes in PD reveal mitochondrial membrane
potential becomes depolarized, not only following mitochondrial impairment, but also after the
UPS and lysosome are inhibited. Given that mitochondrial dysfunction appeared to be central to
PD pathology, mitochondrial dysfunction was studied in more detail. Mitochondrial fission and
fusion maintains mitochondrial integrity, which is critical to neuronal health. Thus, we
examined mitochondrial dynamics in a common genetic variant linked with familial PD, known
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as leucine-rich repeat kinase 2 (LRRK2). Upon the expression of wild-type and mutant LRRK2,
mitochondrial fusion was inhibited causing fragmentation of mitochondria. This inhibition of
fusion may be the initial step leading to mitochondrial dysfunction, since inhibition of fusion
occurs prior to the induction of cell stress. The findings that mitochondrial dysfunction appears
to be central to PD pathology, suggest that mitochondria may be an excellent therapeutic target
for PD. Thus, the potential neuroprotective function of a regulator of mitochondrial function,
known as SIRT3 was examined. In SH-SY5Y cells, over-expression of SIRT3 protected neurons
from degeneration associated with LRRK2 over-expression. The studies described in this thesis
provide evidence that multiple sub-cellular mechanisms converge to inhibit mitochondrial
function. Furthermore, mitochondrial dynamics which regulate mitochondrial function could be
a key mediator in the pathology associated with PD. The work herein suggests therapies which
target the mitochondria are likely to be successful in the treatment of PD.
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Acknowledgments
I would first and foremost like to thank Dr. Joanne Nash for her constant guidance and
encouragment over the course of my PhD. My skills as an independent researcher have vastly
improved because of the lab environment you have provided. I would also like to thank my
committee members, Dr. Michelle Aarts, Dr. Janelle LeBoutillier and Dr. Mauricio Terebiznik
for giving me enormous insight into the finer details of my project. A special thank you goes to
Sherri Thiele for her support, friendship, many laughs and white girl dances over the years.
Vitali, Ruth, Kristin, I appreciate all of the little errands you ran for me, and especially the crazy
nights caused by the many drinks over lab dinners. Julie, Darren, Sam, Wajma, Suhail, Paul, and
Colin thank you for being excellent peers and for the stress relieving moments in the hallways.
Thank you to my loving parents for providing a stimulating childhood environment which
sparked my fondness of science, and showing interest in my work even though you had no clue
what I was talking about. Thank you to Kacy for being my personal mechanic, and Justin and
Matthew for being my personal punching bags. Do not worry I also appreciate the fun times
each of you have provided me over the years. To the boys, John, Ian, Daniel C., Daniel F. and
Mike, and the girls, Elena and Steph thank you for being great friends.
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Table of Contents
Acknowledgments ......................................................................................................................... iv
Table of Contents ........................................................................................................................... v
List of Tables ................................................................................................................................. ix
List of Figures ................................................................................................................................ x
List of Abbreviaitons .................................................................................................................. xii
1 Introduction ............................................................................................................................... 2
1.1 Parkinson’s disease etiology ................................................................................................ 2
1.2 Genetics underlying Parkinson’s disease ............................................................................ 3
1.2.1 α-synuclein .............................................................................................................. 4
1.2.2 Parkin ....................................................................................................................... 6
1.2.3 UCHL-1 ................................................................................................................... 7
1.2.4 PINK1 ...................................................................................................................... 8
1.2.5 DJ-1 ......................................................................................................................... 8
1.2.6 LRRK2 ..................................................................................................................... 9
1.2.7 ATP13A2 ............................................................................................................... 14
1.3 Environmental toxins linked with Parkinson’s disease pathology .................................... 14
1.4 Cell death mechanisms linked with PD pathology ............................................................ 15
1.4.1 Mitochondrial dysfunction .................................................................................... 18
1.4.2 Dysfunction of the ubiquitin-proteasome system .................................................. 19
1.4.3 Lysosomal dysfunction .......................................................................................... 20
1.4.4 Oxidative stress ...................................................................................................... 20
1.4.5 Protein aggregation ................................................................................................ 21
1.5 Interaction of cell death mechanisms ................................................................................ 22
1.6 Mitochondrial dynamics .................................................................................................... 27
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1.6.1 Regulation of mitochondrial dynamics .................................................................. 30
1.6.2 Function of mitochondrial dynamics ..................................................................... 31
1.6.3 Mitochondrial dynamics and neurodegenerative disease ...................................... 31
1.7 Disease modifying agents .................................................................................................. 32
1.7.1 RGMa .................................................................................................................... 34
1.7.2 SIRT3 ..................................................................................................................... 35
1.8 Models of Parkinson’s disease .......................................................................................... 36
1.8.1 In vitro models ....................................................................................................... 36
1.8.2 In vivo models ........................................................................................................ 38
1.9 Hypothesis and aims .......................................................................................................... 41
2 Mitochondrial Dysfunction Precedes other Sub-Cellular Abnormalities in an In Vitro Model Linked with Cell Death in Parkinson’s Disease ............................................. 45
2.1 Introduction ....................................................................................................................... 45
2.2 Materials and Methods ...................................................................................................... 47
2.2.1 Materials ................................................................................................................ 47
2.2.2 Cell culture ............................................................................................................ 48
2.2.3 Cell viability assays ............................................................................................... 48
2.2.4 Cell death assays .................................................................................................... 48
2.2.5 JC-1 and lysosensor green assays .......................................................................... 49
2.2.6 Proteasome sensor vector assay ............................................................................. 49
2.2.7 Western blotting .................................................................................................... 49
2.2.8 Statistical analysis .................................................................................................. 50
2.3 Results ............................................................................................................................... 50
2.3.1 Effect of toxin exposure on cell viability and cell death ....................................... 50
2.3.2 Effect of toxin exposure on mitochondria, UPS and lysosomes ........................... 54
2.3.3 Effect of toxins on ubiquitin levels ........................................................................ 63
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2.4 Discussion .......................................................................................................................... 66
3 Development and Validation of a Screening Assay for the Evaluation of Putative Neuroprotective Agents in the Treatment of Parkinson’s Disease ..................................... 73
3.1 Introduction ....................................................................................................................... 73
3.2 Materials and Methods ...................................................................................................... 74
3.2.1 Materials ................................................................................................................ 74
3.2.2 Cell culture ............................................................................................................ 75
3.2.3 Effect of toxins on cell viability and cell death ..................................................... 75
3.2.4 Effect of putative neuroprotective agents on toxins .............................................. 76
3.2.5 Statistical analysis .................................................................................................. 76
3.3 Results ............................................................................................................................... 76
3.4 Discussion .......................................................................................................................... 90
4 Effect of Over-Expression of WT and Mutant LRRK2 on Mitochondrial Dynamics ..... 94
4.1 Introduction ....................................................................................................................... 94
4.2 Materials and Methods ...................................................................................................... 99
4.2.1 Constructs .............................................................................................................. 99
4.2.2 Cell culture ............................................................................................................ 99
4.2.3 SDS-PAGE followed by Western blotting .......................................................... 100
4.2.4 Expression profile of constructs .......................................................................... 100
4.2.5 Mitochondrial morphology assay ........................................................................ 101
4.2.6 Tetramethylrhodamine ethyl ester perchlorate (TMRE) assay ............................ 102
4.2.7 Polyethylene glycol-induced (PEG) cellular fusion assay .................................. 102
4.2.8 Mitochondrial fission assay ................................................................................. 103
4.2.9 Statistical analysis ................................................................................................ 104
4.3 Results ............................................................................................................................. 104
4.3.1 Generation of ptracer-3xFLAG-LRRK2-mCherry construct .............................. 104
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4.3.2 Expression of LRRK2 in SH-SY5Y cells ............................................................ 112
4.3.3 Effect of LRRK2 on mitochondrial morphology ................................................ 120
4.3.4 Effect of LRRK2 on mitochondrial fusion and fission ........................................ 127
4.4 Discussion ........................................................................................................................ 133
5 Neuroprotective Actions of SIRT3 and RGM in Advanced In Vitro Models of Parkinson’s Disease .............................................................................................................. 138
5.1 Introduction ..................................................................................................................... 138
5.2 Materials and Methods .................................................................................................... 143
5.2.1 SH-SY5Y cells .................................................................................................... 143
5.2.2 Ventral mesencephalic primary cultures ............................................................. 144
5.2.3 Nigro-striatal organotypic co-cultures ................................................................. 147
5.2.4 Statistical analysis ................................................................................................ 149
5.3 Results ............................................................................................................................. 149
5.3.1 Assessment of neuroprotective effects of RGMa and SIRT3 .............................. 149
5.3.2 Development of an in vitro α-synuclein model utilizing ventral mesencephalic primary cultures ................................................................................................... 159
5.3.3 Development of a nigro-striatal organotypic co-culture model of PD ................ 167
5.4 Discussion ........................................................................................................................ 177
6 Summary and Future Directions ......................................................................................... 183
7 References .............................................................................................................................. 188
8 Appendices ............................................................................................................................. 212
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List of Tables
Table 1.1 Genes linked with familial PD .................................................................................. 4
Table 1.2 Agents tested by CINAPS for neuroprotective potential ........................................ 33
x
List of Figures
Figure 1.1. Schematic diagram showing the LRRK2 gene structure. ......................................... 10
Figure 1.2. Schematic diagram outlining genes and environmental toxins that induce
parkinsonian pathology. ................................................................................................................ 16
Figure 1.3. Schematic diagram showing the interactions of various sub-cellular mechanisms. . 23
Figure 1.4. Schematic diagram showing mitochondrial fission and fusion. . ............................... 28
Figure 2.1. Effect of toxins on cell viability and cell death in SH-SY5Y cells. . ......................... 52
Figure 2.2. Effect of compounds on mitochondrial membrane potential in SH-SY5Y cells. ..... 55
Figure 2.3. Effect of toxins on proteasomal function in SH-SY5Y cells. . .................................. 58
Figure 2.4. Effect of toxin exposure on lysosomal function. ....................................................... 61
Figure 2.5. Western blots to show changes in ubiquitin levels following toxin exposure. ......... 64
Figure 3.1. Effect of toxins on cell viability in SH-SY5Y cells. . ................................................ 78
Figure 3.2. Effect of putative neuroprotective agents on toxin-induced decreases in cell viability.
. ...................................................................................................................................................... 82
Figure 3.3. Effect of putative neuroprotective compounds on viability in SH-SY5Y cells. ....... 88
Figure 4.1. Genetic mutations and toxins that affect mitochondrial processes. .......................... 97
Figure 4.2. Generation of ptracer-mCherry construct. .............................................................. 106
Figure 4.3. Generation of ptracer-3xFLAG-LRRK 2-mCherry construct. . ............................... 109
Figure 4.4. Expression of wild-type LRRK2 and G2019S-LRRK2 in SH-SY5Y cells. ............ 113
Figure 4.5. Wild-type LRRK2 and mutant G2019S-LRRK2 expression time course. . ............ 115
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Figure 4.6. Expression of mCherry tagged wild-type LRRK2 and G2019S-LRRK2 in SH-SY5Y
cells. ............................................................................................................................................. 118
Figure 4.7. Changes in mitochondrial morphology in SH-SY5Y cells. .................................... 121
Figure 4.8. Effect of wild-type LRRK2 and G2019S-LRRK2 on mitochondrial function. ...... 124
Figure 4.9. Effect of wild-type LRRK2 and mutant G2019S-LRRK2 on mitochondrial fusion.
..................................................................................................................................................... 128
Figure 4.10. Effect of wild-type LRRK2 and G2019S-LRRK2 on mitochondrial fission. ....... 131
Figure 5.1. The potential role of RGMa and SIRT3 in preventing PD cell death mechanisms.141
Figure 5.2. Effect of RGMa on toxin-induced reductions of cell viability. ............................... 151
Figure 5.3. Effect of SIRT3 in an SH-SY5Y cell model of PD. ................................................ 153
Figure 5.4. Effect of SIRT3 in differentiated SH-SY5Y cells. .................................................. 155
Figure 5.5. Effect of SIRT3 in primary cultures. ....................................................................... 157
Figure 5.6. Determination of MAPK and GFAP expression in primary culture. ...................... 160
Figure 5.7. Determination of TH and GIRK2 expression in ventral mesencephalic primary
culture. ........................................................................................................................................ 162
Figure 5.8. Effect of mutant A53T α-synuclein expression in ventral mesencephalic primary
cultures. ....................................................................................................................................... 160
Figure 5.9. Representative images showing axon outgrowth projecting from the SNc to STR.
..................................................................................................................................................... 169
Figure 5.10. Expression of TH and GIRK2 in nigro-striatal cultures. ...................................... 171
Figure 5.11. Effect of naphthazarin, PSI and rotenone on toxin-induced cell death. . ............... 173
Figure 5.12. Effect of toxin exposure on TH expression in nigro-striatal oranotypic co-cultures.
..................................................................................................................................................... 175
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List of Abbreviations
6-OHDA 6-hydroxydopamine
AAV Adeno-associated virus
AMCA Aminomethylcoumarin acetate
ATP Adenosine triphosphate
ANOVA Analysis of variance
BCS Bovine calf serum
BFP Blue fluorescent protein
CMA Chaperone-mediated autophagy
cAMP 3’ -5’-cyclic adenosine monophosphate
CINAPS Committee to identify neuroprotective agents in Parkinson’s disease
CMV Cytomegalovirus
DAPI 4',6-diamidino-2-phenylindole
DAT Dopamine transporter
DMEM Dulbecco’s modified Eagle’s medium
Dlp1 Dynamic-like protein 1
DNA Deoxyribonucleic acid
Drp1 Dynamin-related protein 1
Dsred2 Discosoma red 2
ECL Enhance chemiluminescence
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Fis1 Fission 1
GABA Gamma-aminobutyric acid
GIRK2 G protein-activated inward rectifier potassium channel 2
GFAP Glial fibrillary acidic protein
GFP Green fluorescent protein
GPI Glycosylphosphatidylinositol
GTP Guanosine triphosphate
HRP Horseradish peroxidase
LRRK2 Leucine-rich repeat kinase 2
MAO-B Monoamine oxidase-B
MAPK Mitogen-activated protein kinase
Mfn1 Mitofusin 1
Mfn2 Mitofusin 2
mPTP Mitochondrial permeability transition pore
mRNA Messenger ribonucleic acid
MPTP 1-methyl-4-pheny-1,2,3,6-tetrahydropyridine
mtDNA Mitochondrial deoxyribonucleic acid
mtGFP Mitochondrial green fluorescent protein
Opa1 Optic atrophy 1
PBS Phosphate buffered saline
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PD Parkinson’s disease
PEG Polyethylene glycol
PFA Parformaldehyde
PGC1-α Peroxisome proliferator-activated receptor gamma coactivator-1-alpha
PI Propidium iodide
PINK1 PTEN-induced kinase 1
PSD95 Postsynaptic density 95
PSI Z-Ile-Glu(OBut)-Ala-Leu-H
RGMa Repulsive guidance molecule a
ROS Reactive oxygen species
SDS-PAGE Sodium dodecyl sulphate-polyacrylamide gel electrophoresis
SIRT3 Sirtuin 3
SNc Substantia nigra pars compacta
SNCA synuclein a
STR Striatum
TH Tyrosine hydroxylase
TKL Tyrosine kinase like
TMRE tetramethylrhodamine ethyl ester perchlorate
TTBS Tween tris buffered saline
UCHL-1 Ubiquitin carboxy-terminal hydrolase 1
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UPDRS Unified Parkinson’s disease rating scale
UPS Ubiquitin proteasome system
VTA Ventral tegmental area
1
Chapter 1
Introduction
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1 Introduction
1.1 Parkinson’s disease etiology
Parkinson’s disease (PD) was first described by Dr. James Parkinson as a shaking palsy defined
by involuntary motion and loss of muscle power (Parkinson, 2002). PD is now characterized by
three cardinal symptoms, bradykinesia or slowed movement, resting tremor and muscle rigidity
which is responsible for postural instability (Tolosa et al., 2006). Patients frequently suffer from
non-motor symptoms which may begin before motor symptoms are displayed (Koller, 1992).
Such non-motor symptoms include depression, sleep disorders and dementia (Chaudhuri et al.,
2006). Both motor and non-motor symptoms become more severe as the disease progresses.
PD is the second most common neurodegenerative disease next to Alzheimer’s disease. The
cause of PD is elusive and likely variable between patients. In idiopathic PD, interactions
between genes and environment are believed to be involved. Mutations in nine proteins have
been linked with familial PD. No matter what the type of PD, risk factors include exposure to
pesticides, positive family history and old age (Massano and Bhatia, 2012). The worldwide
prevalence of PD in patients over 65 years of age is 1.8% (de Rijk et al., 2000). The average age
of onset is 65 years of age with incidence increasing from 0.6% at age 65-69 years to 2.5-3.5% at
age 85-89 years (de Rijk et al., 2000; Coelho and Ferreira, 2012). Early onset PD is defined as
occuring in patients under the age of 50, and has an incidence rate of 1.5/100 000 persons
(Wickremaratchi et al., 2009). While less prevalent than late-onset PD, symptoms of early-onset
PD are very similar to late-onset PD (Wickremaratchi et al., 2009).
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PD arises from degeneration of the dopaminergic nigro-striatal terminals within the basal ganglia
pathway (Hornykiewicz, 1966; Obeso et al., 2000). There is severe loss of tyrosine hydroxylase
immunoreactive neurons from the ventrolateral portion of the substantia nigra pars compacta
(SNc). Approximately 50% of dopaminergic cells within the SNc have degenerated before
clinical symptoms are present (Murray et al., 1995). However, sub-clinical manifestations are
believed to be caused by pathology that affects non-motor brain areas in early stages of the
disease (Braak et al., 2003). Brain pathology is thought to begin in the dorsal IX/X motor
nucleus and/or adjoining intermediate reticular zone, which then advances into brain stem nuclei
and then extends into cortical areas (Braak et al., 2003). Patients typically do not suffer motor
inabilities prior to being diagnosed with PD however, once diagnosed, motor impairments
become more prominent. A patient’s quality of life is severely affected once diagnosed, but is
improved when medication is prescribed (Den Oudsten et al., 2011). Eventually motor
impairments become so severe that palliative care is necessary. The main treatment for PD is
dopamine replacement therapies which reduce symptoms (Olanow, 2008). L-dopa is the most
effective anti-parkinsonian treatment to date, but is often associated with debilitating side effects
(Tuite and Riss, 2003; Olanow et al., 2004). The ELLDOPA study indicates that in patients
taking L-dopa, 16% develop dyskinesia and 20% have motor fluctuations just nine months after
beginning treatment (Fahn et al., 2004; Stocchi et al., 2008).
1.2 Genetics underlying Parkinson’s disease
Although only 10% of PD cases arise from genetic abnormalities, these cases have helped
scientists understand the cell death mechanisms underlying idiopathic PD (Cannon and
Greenamyre, 2012). There are as many as seventeen genes suspected to be linked with PD,
however most are extremely rare or are questionable causative factors of PD (Houlden and
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Singleton, 2012). Most of these genes have an autosomal dominant mode of inheritance. Each
gene is designated the name PARK and given a name according to its genetic locus, but is
commonly referred to by its gene product (Table 1.1).
Table 1.1: Genes linked with familial PD.Designation Locus Gene InheritancePARK1 4q21-22 SNCA: misense mutation ADPARK2 6q25.2-27 Parkin ARPARK3 2p13 ? ADPARK4 4q21-22 SNCA: multiplication ADPARK5 4p14 UCHL-1 ADPARK6 1p35-1p36 PINK1 ARPARK7 1p36 DJ-1 ARPARK8 12p11.2-q13.1 LRRK2 ADPARK9 1p36 ATP13A2 AR
Abbreviations: AD, autosomal dominant; AR, autosomal recessive
Adapted from: (Hampshire et al., 2001; von Bohlen und Halbach et al., 2004; Poulopoulos et al., 2012)
Each gene is listed in choronological order by its PARK designation.
1.2.1 α-synuclein
α-synuclein is a member of a 15-20 kDa synuclein family of proteins which consist of three
members: α, β, and γ. All three proteins are expressed throughout the brains of humans and
rodents, but it is unclear whether the substantia nigra and striatum contain the highest or lowest
levels of α-synuclein (Solano et al., 2000; Rockenstein et al., 2001). α-synuclein is a soluble
cytoplasmic protein that is ubiquitously expressed throughout the body. The highest expression
of α-synuclein in the body is found in the liver and testes. In neurons it is predominately found
in synaptic terminals where it associates with synaptic vesicles (Cookson, 2005). The function
of α-synuclein was largely unknown at the time of its discovery as a causative factor in PD.
5
More recently it has been implicated in turnover of synaptic vesicles, molecular chaperone
activity, golgi trafficking, regulation of dopamine transporter function and mitochondrial fusion
(Cooper et al., 2006; Vogiatzi et al., 2008; Kamp et al., 2010; Nemani et al., 2010; Lundblad et
al., 2012).
Missense mutations in SNCA were identified as the first genetic cause of PD (Polymeropoulos et
al., 1997). The first identified missense mutation was A53T, which was subsequently followed
by the discovery of A30P and E46K mutations. Patients with missense mutations have early
disease onset combined with severe parkinsonian symptoms (Golbe et al., 1990). SNCA
multiplications were soon found to be a causative factor in familial PD. Gene duplications and
triplications in SNCA have variable disease penetrances (Poulopoulos et al., 2012). SNCA
triplication leads to early onset PD with dementia, while duplication causes late onset PD with
dysautonomia (Poulopoulos et al., 2012). Studies suggest multiplication of SNCA increases the
severity of PD symptoms in a dose dependent manner (Singleton and Gwinn-Hardy, 2004).
Post-mortem examinations of brain tissue from PD patients reveal the presence of Lewy bodies,
which are large protein aggregates which form when misfolded α-synuclein oligomerizes and
then forms fibrils which then aggregate. Brain areas typically affected by Lewy body pathology
include the brain stem (gigantocellular reticular nucleus and caudal raphe nuclei) and cerebral
cortex, as well as the SNc (Braak et al., 2003; Farrer et al., 2004). Missense mutations and
multiplications increase the propensity for α-synuclein to fibrilize and form Lewy bodies (Rochet
et al., 2004). While both misense mutations and gene multiplications lead to fibril formation,
other factors such as oxidative/nitrative stress, posttranslational modifications and incubation
with metals can induce fibril formation (Lee and Trojanowski, 2006; Savitt et al., 2006). No
6
matter what the pathology underlying PD, all forms express α-synuclein-positive LBs with the
exception of PD caused by mutations in Parkin.
1.2.2 Parkin
The human Parkin gene encodes a 465 amino acid RING-finger containing protein that has E3
ubiquitin ligase activity (von Bohlen und Halbach et al., 2004; Dodson and Guo, 2007). Parkin
is mainly localized to the cytosol and endoplasmic reticulum, however small amounts are
localized on the cytoplasmic surface of the outer membrane of mitochondria (Shimura et al.,
1999). It is highly expressed in the substantia nigra, striatum, hippocampal formation and
pallidal formation (Zarate-Lagunes et al., 2001). Aside from its role in attachment of ubiquitin to
proteins destined for degradation, Parkin is important for the regulation of mitochondrial
homeostasis. Indeed, Parkin plays a crucial role with PINK1 to control mitochondrial function
by directing mitochondrial dynamics (Kane and Youle, 2011).
Mutations in Parkin cause autosomal recessive juvenile parkinsonism, which has the earliest
onset. It is characterized by dopaminergic cell death and the absence of Lewy bodies (von
Bohlen und Halbach et al., 2004). Some rare cases occur within the first decade of life, while the
majority occur before the age of 40 (Lucking et al., 2000). The Parkin gene is the only gene
linked to autosomal recessive juvenile parkinsonism (Kitada et al., 1998). Despite misense
mutations and duplications to Parkin, autosomal recessive early-onset PD still occurs, however,
it has been shown that heterozygous mutations in Parkin increase the susceptibility to late-onset
PD (Oliveira et al., 2003). Moreover, this increased susceptibility can lead to the presence of
Lewy body pathology (Farrer et al., 2001).
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1.2.3 UCHL-1
Ubiquitin carboxy-terminal hydrolase 1 (UCHL-1) is a deubiquitinating enzyme that plays a role
in the ubiquitin-proteasome system (UPS) protein degradation pathway. UCHL-1 possesses
carboxy hydrolase activity which breaks peptide bonds between ubiquitin monomers so they may
be reused in the UPS pathway. While UCHL-1 is mainly located in the cytoplasm, there is a
significant proportion that resides within synaptic vesicles (Liu et al., 2003). UCHL-1 mRNA is
widely expressed in the brain, however a study employing in situ hybridization revealed the
highest expression is in the substantia nigra (Solano et al., 2000). More recently UCHL-1 was
discovered to have ATP-independent dimerization-dependent ubiquitin ligase activity and
regulate the degradation of free ubiquitin monomers (Osaka et al., 2003; Healy et al., 2004).
The discovery of a mutation in a German family with a history of PD first linked UCHL-1 with
familial PD. A missense mutation in the UCHL-1 gene changes isoleucine to a methionine at the
amino acid 93 of the fourth exon (Leroy et al., 1998). Symptoms of PD induced by UCHL-1 are
similar to idiopathic PD, however the age of symptom onset occurs earlier (Leroy et al., 1998).
UCHL-1 appears to be found in Lewy bodies, however, this finding is controversial since the
Lewy bodies used in the study did not originate from PD patients (Lowe et al., 1990). The
involvement of UCHL-1 in PD is contentious since mice having UCHL-1 loss of function
mutations fail to present neuronal degeneration in the substantia nigra (Saigoh et al., 1999).
Moreover, I93M mutations only cause a partial loss of UCHL-1 hydrolase activity (Nishikawa et
al., 2003). It is likely that an interplay between I93M mutations and environment leads to PD
onset.
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1.2.4 PINK1
The PTEN-induced kinase 1 (PINK1) gene encodes a 581 amino acid protein that is highly
expressed in the hippocampus, substantia nigra and cerebellum (Blackinton et al., 2007). The
gene contains a mitochondrial targeting sequence and a C-terminal serine-threonine kinase
domain (Kawajiri et al., 2011). Although PINK1 is a mitochondrial membrane protein whose
kinase domain is located in the outer membrane, studies have shown that part of PINK1 is
accessible from the cytosol (Haque et al., 2008; Zhou et al., 2008a). PINK1 is believed to
phosphorylate proteins linked with PD such as Parkin and HtrA2 that are involved in
mitochondrial function (Plun-Favreau et al., 2007; Sha et al., 2010). Another role of PINK1
includes promoting autophagy in SH-SY5Y cells by interacting with the pro-apoptotic protein
Beclin-1(Michiorri et al., 2010).
Mutations in the PINK1 gene lead to autosomal recessive early-onset PD associated with Lewy
body pathology (Samaranch et al., 2010). PINK1 is the second most prevalent cause of familial
PD having a prevalence of 1-8% in familial and early onset PD (Michiorri et al., 2010). Several
mutations occur in the serine-threonine kinase domain suggesting the pathological effects are due
to a loss of kinase activity. Gene expression levels affect penetrance since the mean age of onset
is higher in patients with heterozygous mutations than those with homozygous mutations
(Kumazawa et al., 2008). Moreover, it has been suggested that a heterozygous mutation may
make one more susceptible to PD (Klein et al., 2007).
1.2.5 DJ-1
DJ-1 is a member of the ThiJ/PfpI super family of proteins and is widely expressed in the brain
(Bonifati et al., 2003). It is expressed in the cytoplasm, intermembrane space and matrix of
mitochondria and can translocate from the intermembrane space to the outer membrane during
9
periods of oxidative stress (Canet-Aviles et al., 2004). The biological function of DJ-1 remains
unknown, however it is believed to play a role in oxidative stress and mitochondrial function.
Indeed, in vitro studies reveal that DJ-1 prevents oxidative stress and restores mitochondrial
complex activity in neuroblastoma (Miyazaki et al., 2008).
Mutations in the DJ-1 gene are the least common cause of autosomal recessive parkinsonism,
comprising of only 1-2% of early-onset PD cases (Bonifati et al., 2003). There are a total of 11
different mutations in DJ-1 which include missense, truncating, splice site mutations and large
deletions (Bonifati et al., 2004). All of which suggest that loss of function of DJ-1 is the likely
cause of pathogenicity in PD (Abou-Sleiman et al., 2004). Unlike other recessive forms of PD,
the majority of patients with PD linked to DJ-1 are in their early 30s (Bonifati et al., 2004).
1.2.6 LRRK2
Leucine-rich repeat kinase 2 (LRRK2) is a large protein consisting of 2527 amino acids and is a
member of the ROCO family of proteins. LRRK2 is comprised of several domains including an
ankyrin repeat region, Roc GTPase domain, leucine-rich repeat domain, COR domain, kinase
domain of the tyrosine kinase like (TKL) domain and WD40 domain (Fig. 1.1) (Manning et al.,
2002; Bosgraaf and Van Haastert, 2003; Mata et al., 2006). These domains allow it to bind
various proteins from transcription factors to signaling proteins (Andrade et al., 2001). LRRK2
is an interesting protein in that it contains both a kinase and GTPase domain. However, it is
unclear if these domains play distinct roles or are supportive of each other. Members of the TKL
family are activated by small GTPases, suggesting LRRK2 activity might be regulated by its
GTPase domain (Bosgraaf and Van Haastert, 2003; Korr et al., 2006).
10
Figure 1.1. Schematic diagram showing the LRRK2 protein structure. LRRK2 is a large
protein comprised of 2527 amino acids and various functional domains. The locations of
common pathogenic mutations are highlighted in red. Abbreviations: ANK: ankyrin repeat
region, COR: C-terminal of Ras, LRR: leucine-rich repeat domain, Roc: Ras of complex GTPase
domain.
11
G2019SI2020TY1699C
R1441CR1441G
2527 aa
12
In-situ hybridization experiments reveal the expression of LRRK2 mRNA in dopaminergic
neurons within the SNc (Higashi et al., 2007). LRRK2 mRNA was also detected in the cerebral
cortex and caudate putamen (Galter et al., 2006; Higashi et al., 2007). In neurons, LRRK2 is
mainly localized in perikarya and dendritic and axonal processes (Higashi et al., 2007). This is
also consistent with the localization of LRRK2 in cultured cells (Smith et al., 2005c). LRRK2
localizes to membranous and vesicular structures including lysosomes, mitochondria, transport
vesicles and endosomes (Biskup et al., 2006). Interestingly, 10% of LRRK2 exists on the outer
mitochondrial membrane and closely associates with mitochondrial proteins in this vicinity
(West et al., 2005).
Mutations in LRRK2 are the most common genetic cause of familial and sporadic PD. In certain
populations up to 40% of PD cases can be attributed to LRRK2 mutations (Lesage et al., 2006;
Ozelius et al., 2006). There are at least 20 known mutations in LRRK2 that are linked to
autosomal dominant PD (Mata et al., 2006). Among these, the most common mutant variant is
G2019S, while the more infrequent R1441C, R1441G, and I2020T mutations have been found in
a small number of patients (Kett and Dauer, 2012). These mutations vary in their position on the
LRRK2 gene, where I2020T and G2019S occur in the kinase domain, R1441C and R1441G
occur in the GTPase domain, and Y1699C occurs in the COR domain (Mata et al., 2005).
Moreover, there is varying pathology associated with each mutation. G2019S carriers typically
have Lewy body pathology and exhibit a late-onset phenotype that is indistinguishable from
those with idiopathic PD (Aasly et al., 2005; Ross et al., 2006). R1441C substitutions are linked
with synucleinopathy, tauopathy and neuronal loss in the substantia nigra (Zimprich et al., 2004).
Patients with Y1699C substitutions display neuronal loss and nuclear ubiquitin inclusions (Mata
et al., 2006). The G2019S mutation causes a toxic gain of function, whereby enhanced kinase
activity induces cell death (West et al., 2005; Greggio et al., 2006; Smith et al., 2006). Although
13
a toxic gain of function is conferred by G2019S mutations, it appears other mutations in the same
domain do not consistently show increases in kinase activity due to a gain of function (Jaleel et
al., 2007; West et al., 2007).
The normal function of LRRK2 is largely unknown, but studies suggest it is involved in vesicle
trafficking, neurite outgrowth, mitochondrial function and apoptosis (Plowey et al., 2008; Ho et
al., 2009; Parisiadou et al., 2009; Mortiboys et al., 2010). Previous studies reveal the association
of LRRK2 with lipid rafts, and interestingly, it is suggested to regulate vesicle trafficking
(Hatano et al., 2007). Indeed, in cortical neurons where LRRK2 expression has been silenced,
vesicle redistribution and altered vesicle kinetics occur (Piccoli et al., 2011). Moreover,
transgenic mice expressing G2019S mutations experience lower striatal dopamine content,
dopamine release and uptake (Li et al., 2010). Similarly, primary cultures harbouring LRRK2
mutations display shorter neurite length and less branching (MacLeod et al., 2006).
Modifications to neurite outgrowth and branching may result from phosphorylation of the ezrin,
radixin and moesin proteins by LRRK2 (Parisiadou et al., 2009). Furthermore, a study in
differentiated SH-SY5Y cells suggests neurite shortening caused by LRRK2 is associated with a
dysregulation of autophagic processes (Plowey et al., 2008). Strong evidence for the
involvement of LRRK2 in mitochondrial function comes from a study where patients having
G2019S mutations have mitochondria with reduced membrane potential and ATP production
(Mortiboys et al., 2010). While LRRK2 has been suggested to play a role in apoptosis, it is
likely that LRRK2 induced mitochondrial dysfunction activates apoptosis. However, a study
utilizing primary cultures reveals the extrinsic cell death pathway, rather than the
mitcochondrially mediated cell death pathway, is activated by LRRK2 through interactions with
a death adapter FAS-associated protein (Ho et al., 2009).
14
1.2.7 ATP13A2
ATP13A2 encodes a lysosomal protein that is a member of the P-type ATPase superfamily
(Ramirez et al., 2006). The function of ATP13A2 remains elusive, however it is believed to be
involved in lysosomal function and protein degradation (Usenovic et al., 2012). Real-time PCR
experiments demonstrate that ATP13A2 mRNA is highest in the ventral midbrain and lowest in
the cerebellum (Ramirez et al., 2006). Cellular expression of APT13A2 is confined to lysosomal
vesicles where it co-localizes with lysosomal membrane proteins, LAMP1 and LAMP2 (Ramirez
et al., 2006). Interestingly, restoration of ATP13A2 expression increases lysosomal function and
prevents accumulation of α-synuclein (Usenovic et al., 2012).
Mutations in ATP13A2 genes are associated with Kufor-Rakeb Syndrome which is a juvenile,
early-onset parkinsonism with pyramidal degeneration and dementia (Park et al., 2011).
Frameshift mutations in ATP13A2 genes remove three or six C-terminal transmembrane
domains which cause a loss of function of the protein (Ramirez et al., 2006). In addition to
homozygous mutations, heterozygous and compound heterozygous mutations can lead to onset
of parkinsonism (Park et al., 2011).
1.3 Environmental toxins linked with Parkinson’s disease pathology
Prolonged exposure to various environmental toxins is linked with sporadic PD, and while toxin
exposure alone is thought to cause PD, it is also believed that a combination of environmental
and genetic factors lead to disease onset. Toxins which are implicated in sporadic PD onset
generally affect sub-cellular areas by the same mechanisms as those found in familial PD.
Indeed, toxins such as 1-methyl-4-pheny-1,2,3,6-tetrahydropyridine (MPTP), rotenone, maneb
and paraquat, block mitochondrial function by inhibiting electron transport chain activity. MPTP
15
and rotenone inhibit mitochondrial complex 1, while maneb blocks mitochondrial complex 3
activity, and paraquat causes non-selective inhibition of all the mitochondrial complexes (Zhang
et al., 2003; Richardson et al., 2005; Gomez et al., 2007; Sherer et al., 2007). Other than the
primary effect of rotenone, a secondary effect includes oxidative stress and α-synuclein
aggregation (Sherer et al., 2003a; Testa et al., 2005). Another toxin used in the study of PD is 6-
hydroxydopamine (6-OHDA). Although 6-OHDA is not an environmental toxin, it is has been
utilized in experiments to replicate the pathological and biochemical characteristics of PD. Such
characteristics include the induction of oxidative stress through intracellular and extracellular
mechanisms (Blum et al., 2001; Hanrott et al., 2006). Similarly, exposure of neurons to high
concentrations of dopamine hydrochloride is commonly used as a toxicant to emulate
pathological mechanisms in PD (Yong-Kee et al., 2012).
1.4 Cell death mechanisms linked with Parkinson’s disease pathology
Numerous sub-cellular deficits are believed to be the underlying cause of neurodegeneration
displayed in PD. Studies reveal that malfunction of the mitochondria (Bohlen und Halbach,
2004; Lannuzel et al., 2003; Sherer et al., 2007), the UPS (Ardely et al., 2004; Caneda-Feron et
al., 2008) and the lysosome (Cooper et al., 2006) appear to be sources triggering cell death linked
with PD. Moreover, genetic mutations and environmental toxins specifically target these
organelles (Fig. 1.2). In addition, reactive oxygen species (ROS) production and protein
aggregates are traditionally regarded as key mediators of dopaminergic neuron toxicity. Such
protein aggregates include Lewy bodies that are primarily composed of both α-synuclein and
ubiquitin.
16
Figure 1.2. Schematic diagram outlining genes and environmental toxins that induce
parkinsonian pathology. All mutated genes are synthesized within the nucleus. All
environmental toxins that are known to cause parkinsonism inhibit mitochondrial function.
Arrows point to the organelle or molecule that is affected by each known trigger.
17
18
1.4.1 Mitochondrial dysfunction
Mitchondria are classically known as “powerhouses” of the cell because they supply a large
portion of ATP for cellular processes. However, mitochondria play many roles including
initiating apoptosis, integrating stress response pathways and regulating cellular metabolism. In
neurons, mitochondria are critical to synaptic transmission since mitochondrial density
influences the number and plasticity of spines and synapses (Li et al., 2004). Mitochondria are
comprised of an inner and outer membrane that contains the intermembrane space. A series of
intermembrane proteins or mitochondrial complexes located within the inner membrane form the
electron transport chain. Here, ATP is generated through a series of reactions mediated by
mitochondrial complexes 1-5.
Mitochondrial complexes that reside within the inner membrane of mitochondria are targets for
the different environmental toxins that have been implicated in PD pathogenesis; however
complex 1 is primarily targeted. Rotenone exhibits high affinity binding for the NUO D site
which sits at the junction between the membranous and peripheral domains of mitochondrial
complex 1 (Darrouzet et al., 1998). Binding of rotenone prevents electron flow through
mitochondrial complex 1 which inhibits ATP production by the electron transport chain and
reduces membrane potential (Ramsay et al., 1991). Moreover, studies suggest rotenone enhances
reactive oxygen species production by mitochondria, which further exacerbates the toxic effects
of rotenone (Sherer et al., 2003b). These changes within the mitochondria ultimately lead to the
activation of apoptosis and neurodegeneration in cells within the SNc. Interestingly, mutations
in genes which appear to affect mitochondria do not affect mitochondrial complexes. Rather,
mutations in genes such as DJ-1 induce mitochondrial oxidative stress by preventing
19
mitochondrial uncoupling, while mutations in other genes such as Parkin and PINK1 affect
mitochondrial dynamics (Guzman et al., 2010; Kane and Youle, 2011).
1.4.2 Dysfunction of the ubiquitin-proteasome system
The UPS is one of the key protein degradation pathways within the cell. The UPS degrades
various short-lived proteins, including misfolded, mutant and oxidatively damaged proteins, but
not membranous and extracellular proteins (Betarbet et al., 2005). Another role of the UPS is to
maintain mitochondrial protein quality control by preventing the accumulation of intermembrane
space proteins which can be deleterious if left unregulated (Radke et al., 2008). Aside from
being part of the UPS mediated degradation pathway, ubiquitin plays various roles in DNA
repair, and intracellular signalling (Ikeda and Dikic, 2008). The 20S proteasome is constructed
from four heptameric rings that form a hollow core that contains catalytic sites. Chymoptrypsin–
like, trypsin-like and peptidylglutamyl-peptide catalytic sites are located within the two inner
rings to prevent indiscriminate degradation of proteins (Betarbet et al., 2005). A 19S subunit
resides on either end of the 20S proteasome to form the 26S proteasome. The 19S subunit
confers ATPase and ubiquitin ligase function to the 26S proteasome to regulate the entrance of
proteins into the catalytic core (Smith et al., 2005a). The 19S subunit has three functions which
include opening the 20S subunit so proteins can gain access to the core, unfolding ubiquitin
tagged proteins before entrance into the catalytic core and removing ubiquitin subunits from
tagged substrates. Enzymes such as UCHL-1 and Parkin respectively are involved in recycling
ubiquitin monomers and adding ubiquitin to proteins that will be degraded. The genes of such
enzymes become mutated and cause as much as a 50% decrease in UPS activity which leads to
the formation of protein aggregates. However, evidence also suggests that these mutations
promote aggregate formation which then inhibits the proteasome since mutated UCHL-1 and
Parkin were found in these aggregates (Ardley et al., 2003; Ardley et al., 2004). It appears UPS
20
inactivity can promote protein aggregation or UPS inactivity can result from the presence of
aggregated proteins.
1.4.3 Lysosomal dysfunction
The lysosome plays a major role in macroautophagy, microautophagy and chaperone-mediated
autophagy (CMA). In each of these three processes, the lysosome is responsible for degrading
stable long-lived proteins, damaged proteins, protein complexes, protein aggregates and
organelles. However, in CMA, lysosomal degradation is more specific in that a molecular
chaperone can only escort proteins with a lysosomal targeting motif to the lysosome for
degradation. The lysosome also compensates for the inability of the proteasome to breakdown
large membrane proteins and aggregates that cannot enter the proteasomal core (Cuervo et al.,
2004). Recently, mutations in the gene encoding ATP13A2, a lysosomal membrane protein,
were found in a small cohort of patients with PD (Ramirez et al., 2006). Mutations in the gene
encoding ATP13A2 localizes it to the endoplasmic reticulum where it is subsequently degraded
by the UPS (Park et al., 2011). Moreover, it is possible that this places additional stress on the
UPS pathway leading to protein aggregation (Ramirez et al., 2006). An alternative consequence
of lysosomal dysfunction due to mutations in the ATP13A2 gene is impaired lysosomal
degradation capacity which promotes aggregation of α-synuclein (Dehay et al., 2012; Usenovic
et al., 2012).
1.4.4 Oxidative stress
In the late 1980s and early 1990s, oxidative stress was viewed as the primary source of
pathology in PD because of the involvement of dopamine dysregulation and dopamine
metabolism in dopaminergic neurons (Goldstein et al., 1988; Brannan et al., 1990; Jenner, 1992).
However, oxidative stress is involved in a variety of dysfunctional mechanisms and can be
21
regarded as both a primary and secondary source of pathology. Oxidative stress is mainly caused
by ROS and to a lesser degree, reactive nitrogen species. ROS arise from various sources
including dopamine metabolism, iron dysregulation, superoxide production, and lowered
antioxidant defenses (Jenner, 2003; Chen et al., 2008). Autooxidation of dopamine forms
quinone and semiquinone, and more importantly, the breakdown of dopamine by monoamine
oxidase A can produce H2O2 (Halliwell, 2006). If antioxidant molecules are unable to
metabolize H2O2, iron can react with H2O2 to produce the highly reactive hydroxyl radical
(Jenner and Olanow, 1998). It appears that chemical reactions producing ROS are linked, so that
one reaction may enhance another. ROS production is not only dependent on intracellular
dopamine alone, but extracellular dopamine which is transported into the cell can exacerbate
ROS production (Hanrott et al., 2006). Mutations in the gene encoding DJ-1 appear to be the
only cause of familial PD that is directly associated with oxidative stress. Although an exact
mechanism of DJ-1 action has yet to be delineated, there is substantial evidence that DJ-1 plays a
role in oxidative stress (Taira et al., 2004; Miyazaki et al., 2008).
1.4.5 Protein aggregation
The presence of Lewy bodies in post-mortem brain samples from PD patients has made protein
aggregates the defining feature of PD pathology. Protein aggregates are comprised of many
protein fibrils that are formed from several oligomers with β-pleated sheet conformation.
Oligomer formation is initiated by the misfolding of mutant or modified proteins (Lee and
Trojanowski, 2006). The presence of mutated α-synuclein in Lewy bodies suggests that
mutations in the α-synuclein gene play a role in PD pathology (Zhou et al., 2008b). Evidence
suggests A30P mutations accelerate oligomer formation while A53T enhances fibril formation
(Conway et al., 1998; Conway et al., 2000). The presence of oxidatively modified α-synuclein in
Lewy bodies suggests other factors like oxidative stress influence protein aggregation (Smith et
22
al., 2005b; Gao et al., 2008). Moreover, wild-type α-synuclein without any oxidative
modifications can fibrilize to form protein aggregates (Volpicelli-Daley et al., 2011). Given
various forms of α-synuclein are found in aggregates, it is possible that overexpression of any α-
synuclein variant promotes aggregate formation by a concentration dependent manner. Although
some of the processes involved in protein aggregation are thought to be toxic to cells, it is
unclear whether the final products of protein aggregation serve as a neuroprotective strategy
where toxic proteins are sequestered to prevent them from affecting normal processes. Indeed,
post-mortem brain samples from asymptomatic patients exhibit Lewy bodies and neurons
containing Lewy bodies appear to be more healthy than their non-Lewy body containing
counterparts (Tompkins and Hill, 1997). Although the mechanisms of aggregate toxicity is
unclear, it is plausible that aggregation of proteins, like α-synuclein, prevents these proteins from
performing their normal functions within the cells, which ultimately affects neuronal function
(Lee and Trojanowski, 2006). Further evidence that Lewy bodies have neuroprotective function
is shown by the absence of Lewy bodies in patients displaying early-onset PD caused by
mutations in Parkin.
1.5 Interaction of cell death mechanisms
While the previously mentioned pathological mechanisms act independently to produce
pathology, it is believed that interactions between each can produce or even exacerbate disease
onset (Fig. 1.3). It appears that the interaction between each pathological mechanism could be
direct, however further elucidation of these mechanisms may reveal indirect interactions where
one dysfunctional mechanism induces another pathological mechanism by first acting upon an
intermediary mechanism.
23
Figure 1.3. Schematic diagram showing the interactions of various sub-cellular
mechanisms. Mechanisms that are thought to become dysfunctional at later stages of cell stress
during PD. It is unknown if multiple sub-cellular mechanisms converge upon mitochondria and
if reciprocal interactions exist between them. Single-headed arrows indicate a unidirectional
interaction between sub-cellular domains. Double-headed arrows indicate a reciprocal
interaction between sub-cellular areas.
24
25
There is substantial evidence supporting the production of ROS by dysfunctional mitochondria.
Indeed, large amounts of ROS are by-products of the reactions mediated by mitochondrial
complexes of the electron transport chain (Lin and Beal, 2006). It also appears a link between
mitochondrial dysfunction and UPS inhibition exists since mitochondrial dysfunction at complex
1 promotes UPS inhibition. This is demonstrated by the accumulation of an exogenous protein
that is normally degraded by the UPS in neuroblastoma cells treated with rotenone (Yong-Kee et
al., 2012). The mechanism by which dysfunctional mitochondria affects the UPS is unclear, but
it is likely reduced ATP production prevents ubiquitin tagging and 19S cap opening (Hoglinger
et al., 2003a; Smith et al., 2005a). Moreover, it appears that a reciprocal interaction exists
between the two whereby UPS dysfunction can promote inactivity of mitochondrial complexes
(Sullivan et al., 2004). Studies suggest that protein quality control of mitochondria is regulated
by the UPS in order to prevent excessive accumulation of intermembrane space proteins and
collapse of the mitochondrial network (Radke et al., 2008). A link between mitochondrial
integrity and lysosome function is demonstrated by lysosome inhibition during the presence of
rotenone (Yong-Kee et al., 2012). Although there does not appear to be evidence of
mitochondrial dysfunction directly affecting lysosomes, it is possible that an indirect interaction
by way of UPS inhibition occurs.
Many studies have established a direct interaction of mechanisms between the UPS and
lysosome by demonstrating that inhibition of either system can affect the other. The lysosome
can compensate for the UPS when it is unable to efficiently degrade proteins (Rubinsztein,
2007). This interaction is supported by a study where multiphoton in vivo imaging of mouse
brain expressing α-synuclein reveals the autophagic-lysosome pathway becomes recruited when
UPS mediated degradation of α-synuclein is elevated (Ebrahimi-Fakhari et al., 2011). The UPS
can also compensate for lysosomal inhibition, as evidenced by the increase of ubiquinated
26
proteins in mice lacking proteins necessary for autophagy (Hara et al., 2006). However, only
substrates intended for the lysosome that are small enough to enter the proteasomal core can be
degraded. Compensation for lysosomal inhibition comes at a cost however, since delayed
clearance of ubiquitinated proteins is observed when the lysosome is inhibited (Korolchuk et al.,
2009).
Protein aggregation is an end result of the inability of the UPS and lysosome to clear normal,
oxidatively modified and mutant proteins. It was traditionally thought that UPS and lysosome
dysfunction mediates the formation of aggregates containing ubiquitin and α-synuclein (Rideout
et al., 2001; McNaught et al., 2004; Komatsu et al., 2006). However, a reciprocal interaction
exists where aggregate formation decreases proteasome function (Bence et al., 2001).
Proteasome function is strongly inhibited by binding of α-synuclein aggregates to the 19S cap of
the proteasome (Snyder et al., 2003). Given the interactions and similarities between the UPS
and lysosome, it seems likely that protein aggregation should affect lysosome function as well.
A feature of the lysosome is to contain large aggregates from the cytosolic environment;
however some of the aggregates are insoluble, which would then lead to a failure of autophagy
(Cuervo et al., 2005).
ROS are by-products of many reactions and because of this, interactions with various sub-
cellular systems and proteins often occur. Frequent interactions with proteins combined with
failures in protein degradation pathways influence the formation of protein aggregates. Indeed,
α-synuclein is highly susceptible to oxidative modifications which stabilizes α-synuclein fibrils
and in turn promotes aggregate formation (Souza et al., 2000). Oxidative modification is not
limited to α-synuclein however, as other proteins like Parkin, aggregates once its cysteine rich
27
domain is modified (LaVoie et al., 2007; Meng et al., 2011). Similarly, nitrative modification of
α-synuclein frequently occurs to induce aggregate formation (Stone et al., 2012).
1.6 Mitochondrial dynamics
Mitochondrial dysfunction is regarded as a classical mechanism causing cell death in PD.
Moreover, the first toxin-induced case of PD was caused by a mitochondrial inhibitor. Thus,
mitochondrial dysfunction may be a key mediator of disease pathogenesis in both sporadic and
familial cases. Mitochondrial dynamics consist of various processes that maintain the integrity
and function of mitochondria. Such processes include fission and fusion of mitochondria,
trafficking of mitochondria, and autophagy of mitochondria or mitophagy. Fission is when a
single mitochondrion divides into two mitochondria, while fusion is the process where two
mitochondria contact each other and fuse into one mitochondrion (Fig. 1.4).
28
Figure 1.4. Schematic diagram showing mitochondrial fission and fusion. (a) Fis1 interacts
with Drp1 to promote self-association. Drp1 forms a spiral structure that wraps around
mitochondria during fission. Mitochondria are severed by Drp1 through a GTPase mediated
reaction. (b) Mfn1 and Mfn2 tether mitochondria together during outer mitochondrial membrane
fusion. Inner mitochondrial membrane fusion is then mediated by Opa1. GTP hydrolysis
initiates the reactions mediated by Mfn1, Mfn2 and Opa1. Abbreviations: Drp1: dynamin-
related protein 1, Mfn 1: Mitofusin 1, Mfn2: Mitofusin 2.
29
Drp1
Fis1
a Fission
b Fusion
Mfn2
Mfn1
Opa1
30
1.6.1 Regulation of mitochondrial dynamics
Large GTPase proteins mediate fission and fusion processes. Dynamin-related protein (Drp1)
and fission 1 (Fis1) mediate the mechanisms that orchestrate fission of mitochondria (Knott et
al., 2008). Drp1 is a cytosolic protein that contains an N-terminal GTPase domain. During
fission, Drp1 is believed to translocate from the cytosol to fission sites on mitochondria where it
self-associates to form spiral-like structures (Smirnova et al., 2001). These structures begin to
wrap around and constrict the mitochondria until the mitochondrial membrane is severed by a
GTPase dependent mechanism (Otera and Mihara, 2011). Fis1 is anchored to the outer
mitochondrial membrane with its N-terminus exposed to the cytoplasm. Studies suggest Fis1
plays a role in recruiting Drp1 to sites of fission on the mitochondria (Yoon et al., 2003). Three
large GTPases, mitofusin 1 (Mfn1), mitofusin 2 (Mfn2) and optic atrophy 1 (Opa1) mediate
mitochondrial fusion. Mfn1 and Mfn2 are anchored to the outer mitochondrial membrane with
their N-terminal GTPase and C-terminal coiled coil ends facing the cytoplasm. It is unclear how
Mfn1 and Mfn2 mediate outer membrane fusion, but they are believed to tether mitochondria
together in a GTPase dependent manner. Opa1 is situated in the inner mitochondrial membrane
with its GTPase domain facing the intermembrane space (Otera and Mihara, 2011). The process
of inner membrane fusion is unclear, but the GTPase domain of Opa1 appears to be essential
since mutations in this domain lead to mitochondrial fragmentation (Olichon et al., 2007). While
the proteins that regulate fission and fusion are controlled by GTP hydrolysis, it appears that the
activity of these proteins can also be regulated by phosphorylation by cyclin-dependent kinase 1
and cAMP-dependent protein kinase (Westermann, 2010).
31
1.6.2 Function of mitochondrial dynamics
Mitochondria are constantly undergoing fission and fusion to adjust mitochondrial populations to
meet cellular demands. Processes such as axonal outgrowth and synaptic plasticity require
changes in mitochondrial content which is dependent on mitochondrial fission and fusion
(Morris and Hollenbeck, 1993; Li et al., 2004). Fission and fusion are antagonistic processes and
a delicate balance between the two must be maintained to ensure mitochondria are functional.
Indeed, damaged mitochondrial DNA is eliminated and depolarised mitochondrial membrane
potentials are restored upon completion of mitochondrial fusion. Fusion is also important for the
inheritance and maintenance of mtDNA, which in turn is key to the overall health of
mitochondrial populations (Rapaport et al., 1998). Mitochondrial fission is critical for synaptic
transmission between neurons since the proper function of synapses is reliant on functional
mitochondria at synaptic sites (Li et al., 2004; Ishihara et al., 2009). Fission is implicated in the
regulation of apoptotic processes in neurons since Drp1 is required for cytochrome c release and
caspase activation (Estaquier and Arnoult, 2007; Ishihara et al., 2009).
1.6.3 Mitochondrial dynamics and neurodegenerative disease
The functions performed by fission and fusion are critical to neuronal health which implies that
any perturbations to these processes may be linked with neurodegenerative disease. Several
neurodegenerative diseases are linked to aberrant mitochondrial dynamics. Mutations in Mfn2
cause Charcot-Marie-Tooth type 2A disease which affects sensory and motor neurons (Chen and
Chan, 2009). Dominant optic atrophy is caused by mutations in Opa1 and leads to degeneration
of retinal ganglion cells (Detmer and Chan, 2007). Interestingly, patients with Charcot-Marie-
Tooth type 2A disease display various symptoms including parkinsonism and psychiatric
disturbances (Verhoeven et al., 2006). Alterations to mitochondrial dynamics may be equally
32
important in disorders such as PD where mitochondrial function is especially critical to the
health of nigral neurons.
1.7 Disease modifying agents
Presently, all treatments for PD are focused on treating symptoms of PD by using dopamine
replacement therapy, either by replacing lost dopamine in the form of the dopamine precursor L-
dopa or dopamine agonists, or by enhancing the half-life of remaining dopamine using mono
amine oxidase-B (MAO-B) inhibitors. Levodopa, rotigotine (dopamine agonist), selegiline and
rasagiline (MAO-B inhibitors) are all successful at reducing motor symptoms, however long-
term use is associated with debilitating side effects such as dyskinesias (Schapira, 2009). While
much research is focused on treating symptoms of PD, it would be much more beneficial to
patients if it were possible to stop or slow the progression of neurodegeneration by using a
neuroprotective agent. This would prevent PD progressing to more advanced stages where
patients become seriously disabled and palliative care is necessary. The Committee to Identify
Neuroprotective Agents in Parkinson’s disease (CINAPS) project was the first of its kind to
select a battery of neuroprotective agents to test in clinical trials (Heemskerk et al., 2002; Ravina
et al., 2003). Given the importance of various mechanisms such as oxidative stress and
mitochondrial dysfunction which ultimately cause apoptosis, it is conceivable that putative
neuroprotective agents should act on these pathways. Indeed, some of the various chemicals
tested by CINAPS are involved in the previously mentioned mechanisms (Table 1.2).
33
Table 1.2: Agents tested by CINAPS for neuroprotective potential.Agent Mechanism of ActionCaffeine Adenosine A2A receptor antagonismCoenzyme Q10 Cofactor of electron transport chain; antioxidant propertiesCreatine Indirect antioxidant by enhancing energy transfer during periods of high energy demandEstrogen May act as an antioxidant through upregulation of Bcl-2, BDNF and GDNFGM-1 ganglioside UnknownMinocycline Inhibition of microglial activationNicotine Increases neurotrophic factorsNeuro-immunophilin A Immunophilin ligandSelegeline, Rasagiline MAO-B inhibitorRopinirole, Pramipexole Dopamine agonist with antioxidant properties
Adapted from: (Meissner et al., 2004; Hung and Schwarzschild, 2007)
Many of these agents were found to be neuroprotective in various rodent and primate models
before being considered for clinical trials, while others were tested in clinical trials without prior
testing in animal models (Meissner et al., 2004). Nicotine and caffeine were suggested to be
neuroprotective based on the low incidence rates of PD in humans that frequently consumed
them. Estrogen was selected as a putative neuroprotective agent because of the lower incidence
of PD in women, especially in women receiving estrogen replacement (Saunders-Pullman et al.,
1999). Coenzyme Q10 appears to be the most successful agent, having protective effects in
animal models and placebo-controlled clinical trials. Similarly, selegeline was found to be
beneficial when tested using the Unified Parkinson’s Disease Rating Scale (UPDRS). Indeed,
lower scores were given by patients receiving selegeline treatment, but these results were
questionable due to errors in clinical trial design (Hung and Schwarzschild, 2007). The effect of
creatine was assessed in a two year placebo-controlled clinical trial but protection was not
observed as UPDRS scores were not lowered (Bender et al., 2006). However, further study of
creatine is warranted as it was found that it could not be excluded as a possible neuroprotective
agent in a futility study (2006). It appears that compounds that are neuroprotective in animal
models are not always as successful in clinical trials. However, in cases such as with coenzyme
34
Q10 and creatine, there was benefit in both animal models and clinical trials. Thus it seems there
is a disparity between the predictive capabilities of clinical trials, and improvements in clinical
trial designs are necessary to test the clinical relevance of putative neuroprotective agents.
Alternatively, improvements in cellular and animal models may be necessary so these models are
better reflective of the human disease.
1.7.1 RGMa
Repulsive guidance molecule A (RGMa) is a membrane-associated glycoprotein that was
originally isolated from chick optic tectum (Monnier et al., 2002). The C-terminal is anchored to
the plasma membrane by a glycosylphosphotidylinositol (GPI) domain and the N-terminal
contains a signal peptide sequence. A partial von Willebrand factor domain and RGD sequence
also exist to support membrane adhesion (Monnier et al., 2002). RGMa is part of a family of
RGM proteins (RGMa-c) with each having their own specific function in the central nervous
system. RGMa is localized to the soma in mature and immature neurons, while immature
neurons also contain RGMa in their axons (Brinks et al., 2004; Schwab et al., 2005). RGMa acts
as a guidance cue for retinal axons and induces the collapse of temporal growth cones during
neuronal development (Monnier et al., 2002). Other functions of RGMa include the ability to
regulate neuronal differentiation and prevent apoptosis through its interaction with neogenin, a
homologue of netrin-1 and DCC receptors. Studies reveal that neogenin is a dependence
receptor where activation of pro-apoptotic pathways normally occurs in the absence of a ligand
(Matsunaga and Chedotal, 2004; Matsunaga et al., 2004). Caspase-3 cleavage of neogenin
initiates these apoptotic signalling pathways, which are blocked in the presence of its ligand,
RGMa. Moreover, RGMa overexpression prevents pro-apoptotic signalling while RGMa siRNA
expression has no effect on cell survival (Matsunaga et al., 2004). Although RGMa has the
35
ability to regulate axonal outgrowth and to modulate apoptotic pathways, surprisingly it has not
been studied in various disease models.
1.7.2 SIRT3
The novel family of protein deacetylases, sirtuins, consist of seven family members (SIRT 1-7),
each of which have shown efficacy in the treatment of a wide spectrum of diseases. Sirtuin1
(SIRT1) was the first member of the sirtuins to be extensively studied in mammals (Gan and
Mucke, 2008). Evidence suggests that SIRT1 elicits neuroprotective properties by its actions on
non-histone substrates in the nucleus (Lavu et al., 2008). Another member of the sirtuin family,
SIRT3, is less extensively studied; however, it is believed to be involved in mitochondrial
function. SIRT3 is encoded within the nucleus and then directed to the mitochondria by its N-
terminal mitochondrial localization sequence (Bao et al., 2010). Once inside the mitochondria,
SIRT3 becomes enzymatically active upon cleavage of its localization sequence by a protein
peptidase (Giralt and Villarroya, 2012). SIRT3 is primarily located in mitochondria. Studies
report SIRT3 is also localized in the nucleus and cytosol in its uncleaved form while the cleaved
form is localized in the mitochondria (Cooper and Spelbrink, 2008). Targets of SIRT3 include
acetyl-CoA, the mitochondrial permeability pore and mitochondrial complexes 1-5. Upon
regulation of the respiratory chain, SIRT3 influences energy production (Shimazu et al., 2010;
Verdin et al., 2010). The activation of these targets may be associated with SIRT3’s actions in
the cell’s stress response pathway. SIRT3 is also involved in mitochondrial biogenesis where it
mediates the effects of PGC-1α by acting as a downstream target (Kong et al., 2010). Although
SIRT3 plays many critical roles in mitochondrial function, and its family members are
efficacious in various diseases, most studies on SIRT3 have been performed in the heart, and
nothing is known about its therapeutic effect in neurons.
36
1.8 Models of Parkinson’s disease
Various in vitro and in vivo models have been generated to replicate the mechanisms underlying
PD and the symptoms resulting from PD. Each model utilizes toxins or genetic manipulations to
induce parkinsonian features. Since each model does not fully replicate disease mechanisms or
symptoms, new models that incorporate these important aspects of PD will be invaluable for
therapeutic development. Although the present models lack certain characteristics of PD
mechanisms and symptoms, each have been useful in the development of therapeutics that are
currently available to treat PD.
1.8.1 In vitro models
In vitro models have been extremely valuable tools for determining the cellular mechanisms
underlying PD. Toxins have been applied to in vitro models to study idiopathic forms of PD,
while the insertion of exogenous DNA known to be mutated in individuals with PD into
individual cells has given insight into the mechanisms causing familial PD. Organotypic co-
cultures contain multiple cell types allowing for changes in one cell type to be directly compared
to changes in another cell type while they are in the same microenvironment. Such cultures can
be maintained for up to a few weeks in culture allowing the neurons to mature, which more
closely resembles neurons degenerating in PD. Other advantages of organotypic co-cultures
include neuronal and glial interactions, maintenance of neuronal connections and growth of
synapses while in culture (Lyng et al., 2007). More importantly, organotypic cultures express
dopamine, homovanillic acid and tyrosine hydroxylase from as little as 6 days to 17 days after
culturing (Lyng et al., 2007). Compared to other in vitro models, the production of organotypic
co-cultures is more complicated since slices of multiple brain areas must be obtained from
embryonic and post-natal rodents. Primary cultures have been employed in many studies to
37
discover the biochemical pathways responsible for PD pathology (Hoglinger et al., 2003a;
Lannuzel et al., 2003). Synapses actively form between neurons in primary cultures, but the
intrinsic activity of synapses seen in the brain is not usually found in these cultures. Indeed,
these in vitro neurons were less spontaneously active and never fired in bursts, unlike in vivo
neurons (Rayport et al., 1992). While primary cultures benefit from having neurons and glia and
display the typical characteristics of mature neurons, such as TH and dopamine, generally very
few cells from the culture have these characteristics. However, the presence of dopamine
autoreceptors was identified by neuronal activity in response to quinpirole, a dopamine receptor
agonist (Cardozo, 1993). In vitro models such as cell lines have the advantage of being quickly
generated allowing reproducible effects to be shown. Even the differentiation of neuroblastoma
to neuronal-like cells can take place in a time frame as short as 72 hours, allowing for high-
throughput findings that can be inferred to actual neurons. Disadvantages of cell lines include
being dissimilar from actual neurons and having a microenvironment that is non-physiological.
Since the genes of cells in culture are easily manipulated and their protein products are rapidly
produced, the biochemical pathways and mechanisms involved in PD can be efficiently studied.
Indeed, specific molecular pathways underlying PD can be directly targeted in cellular models
(Dawson et al., 2010). In addition, specific cell types can be isolated to study changes that are
unique to that cell type. Studies show that the various toxins used to create models reliably act
upon their intended target and repeatedly produce cellular dysfunction and markers associated
with the disease state (Sherer et al., 2003b). The efficient nature of in vitro cultures enables their
use for rapid screening of therapeutic compounds. As a result, there will be a quicker “bench to
bedside” process enabling therapeutics to become available on the market more quickly.
However changes observed in cellular models do not exactly correlate with those seen in the
38
disease state, thus more advanced in vivo models, which better emulate disease states, must be
utilized to further substantiate the findings obtained using in vitro models.
In vitro models lack the surrounding micro environment provided by in vivo models, but benefit
from having a more controllable environment (Alberio et al., 2012). Furthermore, most in vitro
models cannot recapitulate the complexity of multiple connections formed by cells from different
areas of the brain. This is highly disadvantageous considering PD pathology affects complex
networks organized between the SNc and striatum. Moreover, multiple cell types are affected,
which makes it difficult to model with most in vitro models, except for those models employing
organotypic cultures that are comprised of neurons from various brain areas (Snyder-Keller et
al., 2001). Given that in vitro models are isolated from organisms, they are unable to show how
changes mediated by therapeutic compounds affect disease symptoms and physiology of the
organism as a whole. Although in vitro models have many benefits, it is necessary to further
characterize and develop in vitro models which display the multitude of pathological
mechanisms found in PD, rather than modeling a single mechanism.
1.8.2 In vivo models
The use of animal models in PD research has been the main approach for developing therapeutic
compounds and studying disease symptoms. Toxin and transgenic animal models have been
used to replicate the pathology in sporadic and familial PD (Sherer et al., 2003a; Rockenstein et
al., 2007). The reserpine-treated rat model was developed in the late 1950’s, resulting in the
discovery of L-dopa as a potential treatment for parkinsonian symptoms. Reserpine application
in rodents induces muscle rigidity, postural flexion, and akinesia, closely resembling symptoms
observed in parkinsonian patients (Carlsson et al., 1957). However, administration of reserpine
produces a model that is acute, reversible and fails to replicate the pathology underlying
39
idiopathic PD. A further disadvantage associated with the reserpine-treated rat is that serotonin
and noradrenaline levels are depleted to a greater extent compared to idiopathic PD. The
unilaterally-lesioned 6-OHDA rat model of PD has proved extremely useful in providing insight
into pathological, electrophysiological and pharmacological changes which occur following
degeneration of the nigrostriatal pathway, increasing our understanding of the mechanisms
underlying the generation of parkinsonian symptoms. Following stereotaxic injection of 6-
OHDA into the medial forebrain bundle, dopamine cell loss is more profound compared to that
observed following injections of 6-OHDA into the SNc (Carman et al., 1991). Metabolism of 6-
OHDA results in a phenomenal amount of oxidative stress, promoting deleterious effects of free
radicals on mitochondrial function, membrane stability and DNA integrity, which ultimately
results in cell death (Schwarting and Huston, 1996). Following unilateral administration of 6-
OHDA, rodents exhibit a spontaneous rotational behaviour ipsiversive to the side of the lesion
which represents an anti-parkinsonian action. Although exhibition of contraversive rotational
behavior in 6-OHDA lesioned animals is thought to represent an anti-parkinsonian action,
parkinsonian symptoms such as rigidity, tremor and bradykinesia are not apparent in these
animals (Ungerstedt, 1968). Furthermore adverse effects including adipsia, aphagia and high
mortality rates make this model less attractive (Ungerstedt, 1971). The MPTP mouse model is
widely used to evaluate potential therapeutic agents for PD (Cannon and Greenamyre, 2010).
This model shows progressive neurodegeneration of the nigro-striatal pathway, and sometimes
motor deficits. Thus, potential neuroprotective agents can be evaluated using post-mortem
measures of dopamine system integrity. The MPTP-lesioned mouse is easy to reproduce, and
more importantly, has proved to be one of the most useful models for assessing neuroprotective
potential of compounds in PD (Pothakos et al., 2009). One drawback of this model is that it does
40
not result in the generation of protein aggregates, which are considered an important component
of PD pathology.
Upon the discovery of new genes linked with familial PD, classical toxin-induced and genetic
models became limited in their scientific value because they were unable to represent the various
forms of PD and their associated pathology. As a result, many animal models now express these
newly discovered genes that underlie PD (Li et al., 2010). This has led to the rapid identification
of the symptoms and pathology associated with certain genetic forms of PD. Models utilizing
AAV-mediated delivery and over-expression of α-synuclein in the rodent replicate the
progression of cell death and molecular pathology most closely to that observed in patients
(Koprich et al., 2010). The model also displays behavioral deficits consistent with a
parkinsonian phenotype. Following unilateral delivery of AAV-α-synuclein, dopaminergic
neurons become dysfunctional, exhibit abnormal axonal morphology and proteinase K-resistant
aggregations of α-synuclein in both terminals and nigral cell bodies, as well as increased striatal
dopamine transporter binding (DAT) (Koprich et al., 2010). These changes are accompanied by
behavioral abnormalities. At later stages, the pathology has progressed further, with marked
presence of dystrophic neurites, reductions in striatal TH, DAT and dopamine and a significant
loss of TH neurons within the nigra.
Animal models are critical for the development of neuroprotective strategies because they have
enabled the discovery of various sub-cellular deficits and various symptoms that arise from
mutations in the genes associated with PD and more importantly, reveal changes that occur in
live organisms. Moreover, these models enhance the clinical applicability of drugs since the
effect of therapeutic interventions on a live organism expressing genetic mutations closely
predicts the effect of the drug on patients. Although the various models replicate one particular
41
aspect of PD, they do not emulate the multifaceted nature of the disease. This is demonstrated
by the inhibition of an individual mechanism by a particular toxin or genetic manipulation, rather
than a multitude of mechanisms as seen in PD patients. Furthermore, certain brain areas that are
not typically affected during PD appear to be vulnerable to degeneration (van der Putten et al.,
2000). Application of rotenone in animal models leads to global degeneration of neurons rather
than specific degeneration within the substantia nigra alone (Meredith et al., 2008). Markers
such as Lewy bodies that are typically found in patients exhibiting PD are not consistently
reproduced by the various toxin and genetic models (Dauer and Przedborski, 2003). Despite the
expression of these markers, many distinguishing features including nigral degeneration and loss
of tyrosine hydroxylase expression do not always occur. Although these models suffer from
disadvantages, they have been extremely useful in delineating gene specific pathology and
symptomatic treatments.
Given the advantages and disadvantages of in vitro and in vivo models with respect to
developing therapeutics to treat PD, these models must be further developed to better emulate all
the pathological mechanisms found in PD; then both models can be utilized to successfully
predict if a neuroprotective agent will be efficacious in clinical trials.
1.9 Hypothesis and aims
In PD, a variety of sub-cellular dysfunctions cause neurodegeneration of the SNc which
ultimately lead to the symptoms of PD. By understanding the function of mutations linked with
familial PD, we know that a number of separate mechanisms can trigger PD pathology.
Moreover, the utilization of environmental toxins in PD models has further highlighted that
multiple mechanisms induce PD pathology. Although a number of dysfunctional mechanisms
exist, the role of mitochondria in PD pathology is becoming more apparent. Thus, I
42
hypothesized that altered mitochondrial function, due to the dysfunction of sub-cellular domains
and inhibition of mitochondrial dynamics, is a primary cause of disease pathology. Furthermore,
potential neuroprotective agents that target the mitochondria will be effective at protecting
degenerating neurons of the SNc. The initial hypothesis of this study was, that no matter what
the initial trigger, a single sub-cellular abnormality activates additional sub-cellular pathways,
such as the mitochondria, that further enhances the pathology of PD. Secondly, I hypothesized
that a correlation between the outcomes of neuroprotective agents in an in vitro model and those
of clinical trials can validate the effectiveness of an in vitro model at predicting potential
neurprotective agents to treat PD. Given the importance of mitochondrial function in the
pathology of PD, and the existence of LRRK2 on mitochondrial membranes, I hypothesized that
LRRK2 alters mitochondrial dynamics causing mitochondrial dysfunction. Moreover, a
potential neuroprotective agent such as SIRT3, which is involved in mitochondrial function, will
be effective at protecting neurons from degeneration.
The first aim of the studies described in Chapter Two was to understand how different triggers
associated with initiating the pathology of PD interact with other known components of the
neurodegenerative process associated with PD. The initial aim of these studies revealed that, no
matter what the initiating trigger, mitochondrial dysfunction occurs early in the cell death
pathway. This suggests that malfunction of mitochondria is central to all pathologies associated
with PD. The studies that were completed as part of the initial aim led to the generation of a cell
model of PD that took into account all known causes of PD. This model is quick, easy and
reliable to produce, thus, in Chapter Three my second aim of the studies validated this as a useful
model to test potential neuroprotective agents in PD using compounds that had previously passed
screening processes and were already in clinical trials. The third aim of the studies described in
Chapter Four was to further investigate how mitochondrial function is affected in PD. Since
43
mitochondrial dynamics are required for physiological mitochondrial function, I investigated
changes in mitochondrial fission and fusion in cell models of PD. This aim revealed that
mitochondrial fusion is inhibited in a common genetic variant of PD. The fourth aim of the
studies outlined in Chapter Five was to evaluate the neuroprotective ability of two novel
compounds in our novel model of PD. This aim affirmed the importance of targeting the
mitochondria when trying to prevent the neurodegeneration associated with PD.
44
Chapter 2
Mitochondrial Dysfunction Precedes other Sub-Cellular Abnormalities in an In Vitro Model
Linked with Cell Death in Parkinson’s Disease
A modified version of this chapter was previously published as:
Yong-Kee CJ, Sidorova E, Hanif A, Perera G, Nash JE (2012) Mitochondrial dysfunction precedes other sub-cellular abnormalities in an in vitro model linked with cell death in
Parkinson's disease. Neurotoxicity research 21:185-194.
45
2 Mitochondrial Dysfunction Precedes other Sub-Cellular Abnormalities in an In Vitro Model Linked with Cell Death in Parkinson’s Disease
2.1 Introduction
By the time patients present with symptoms of PD, approximately 50% of the nigro-striatal
pathway has degenerated (Bernheimer et al., 1973), and a substantial proportion of the remaining
nigral neurons are undergoing some form of cell stress (Murray et al., 1995). Nevertheless
symptoms are typically not severely disabling and patients still have a good quality of life. Thus,
if it was possible to prescribe a disease-modifying agent that stopped or slowed down disease
progression at this stage of the disease, patients would not experience the advanced, severely
disabling stages of the disease. Development of such disease modifying strategy depends
critically upon understanding the sub-cellular mechanisms underlying neurodegeneration in PD.
Although 90-100% of cases of PD are believed to be sporadic, clues regarding the mechanisms
underlying cell death in PD have arisen from the 5-10% of cases that have been shown to be
genetically linked. All 15 loci on the 11 genes that have been linked to familial PD encode
proteins involved in the handling or removal of misfolded proteins, either at the level of the UPS,
macro-autophagy and CMA (Kitada et al., 1998; Ardley et al., 2004; Ramirez et al., 2006; Di
Fonzo et al., 2007; Lees and Singleton, 2007; Hatano et al., 2009), the regulation of
mitochondrial function (Lannuzel et al., 2003; von Bohlen und Halbach et al., 2004; Sherer et al.,
2007) and oxidative stress (Martinat et al., 2004; Shendelman et al., 2004). Furthermore, the
genetic mutations linked with familial PD cause dysfunction in at least one, if not all, of these
regulatory mechanisms (Hardy, 2010; Magen and Chesselet, 2010). For example, loss-of-
46
function mutations in the E3 ubiquitin-protein ligase Parkin, a protein most commonly associated
with early-onset autosomal recessive PD (Kitada et al., 1998) was originally shown to play a role
in tagging proteins for degradation by the proteasome (Cookson, 2003; Sakata et al., 2003).
More recently, Parkin has also been shown to play a role in the regulation of mitochondrial
dynamics (Yun et al., 2008; Whitworth and Pallanck, 2009) as well as in CMA (Olzmann and
Chin, 2008). A second example of a protein associated with familial PD, which appears to cause
multiple problems at the sub-cellular level is α-synuclein. Mutations in α-synuclein cause
impaired UPS and lysosomal function (Stefanis et al., 2001; Tanaka et al., 2001; Cuervo et al.,
2004; Chu et al., 2009), and increased susceptibility of dopaminergic neurons to mitochondrial
toxins such as MPP+, as well as oxidative stress (Kanda et al., 2000; Qian et al., 2008). Finally,
post mortem studies in parkinsonian patients suggest that similar mechanisms are responsible for
causing cell death in both familial and idiopathic cases of this disease, since all show evidence of
impaired function of mitochondrial complex 1, UPS and lysosome, as well as increased oxidative
stress in the SNc and other affected brain regions (Parker et al., 1989; Jenner, 1993; Chu et al.,
2009). If it were possible to identify a common sub-cellular dysfunction that was initiated by all
known cell mechanisms associated with neurodegeneration in PD, this would represent a
valuable target for the development of a disease modifying agent since it would allow the rescue
of the remaining 50% of neurons in the SNc.
Given that multiple sub-cellular mechanisms are involved in Parkinson’s pathology, I
hypothesized that there is a single point of convergence of these mechanisms which results in
cellular stress. The studies described in this chapter sought to identify such a point of
convergence by using a catecholaminergic neuroblastoma cell line, which has previously been
used to study the mechanisms underlying cell death in PD (Dadakhujaev et al., 2010; Xie et al.,
47
2010; Xie et al., 2011; Nonaka and Hasegawa, 2009; Wu et al., 2009), in combination with
toxins that induce cell death via the three mechanisms commonly associated with
neurodegeneration in PD: inhibition of mitochondrial complex 1 (rotenone), inhibition of the
UPS using Z-Ile-Glu(OBut)-Ala-Leu-H (PSI), and disruption of the lysosomal membrane via
5,8-dihydroxy-1,4-naphthoquinone (naphthazarin). In order to determine the effect of these
toxins in early, as compared to later stages of cell stress, when cell damage is unlikely to be
reversible, sub-cellular function was measured after three and twenty four hours of exposure to
toxin.
2.2 Materials and Methods
2.2.1 Materials
SH-SY5Y cells were purchased from ATCC (USA), Dulbecco’s Modified Eagle’s Medium
(DMEM), bovine calf serum, from Wisent (Canada) and trypsin from Sigma (USA). 5,8-
dihydroxy-1,4-naphthoquinone (naphthazarin) and rotenone were purchased from Sigma (USA),
Z-Ile-Glu(OBut)-Ala-Leu-H (PSI) from BIOMOL (USA) and alamar blueTM from Biosource
(Canada). Propidum iodide was purchased from Invitrogen (USA). Lysosensor green and JC-1
were purchased from Invitrogen (USA) and proteasome sensor vector from Clontech (USA).
Ubiquitin anti-rabbit antibody was purchased from Dako (USA), β-actin anti-mouse antibody
from Sigma (USA), anti-mouse and anti-rabbit HRP-conjugated secondary antibodies from
Jackson Laboratories (USA) and nitrocellulose membrane was purchased from BIORAD (USA).
PSI was dissolved in 0.1% dimethyl sulfoxide (DMSO) plus DMEM, and rotenone and
naphthazarin in DMEM only.
48
2.2.2 Cell culture
Human dopaminergic neuroblastoma SH-SY5Y cells (ATCC) (P10-P30) were grown in DMEM
(consisting of 6400 mg/L NaCl, 3700 mg/L NaHCO3, 400 mg/L KCl and 584 mg/L L-glutamine)
supplemented with 5% bovine calf serum in a sterile humidified chamber (37 oC, 5% CO2, 95%
O2) (Incubator: MCO-20AIC, Sanyo, USA) until confluent. Cells were passaged using 0.1%
trypsin for 5 min, then pelleted by centrifuging at 340xg for 5 min (Allegra 6R Centrifuge,
Beckman Coulter, USA).
2.2.3 Cell viability assays
SH-SY5Y cells were grown in 96-well plates at 1.0 x 105 cells/ml. After 24 hours, cells were
exposed to full dose response curves of naphthazarin, PSI or rotenone (0 µM–1000 µM) in the
presence of the redox sensitive dye alamar blue (0.4% of final volume). Cell viability was
assessed by measuring the change in fluorescence of alamar blue (Ex. 544 nm, Em. 590 nm)
using a plate reader (FLUOstar OPTIMA, BMG Labtech, USA) at 3 and 24 hour time points.
Data are expressed as percentage cell viability compared to control ± SEM (n = 4).
2.2.4 Cell death assays
SH-SY5Y cells were grown in 6-well plates at a density of 2.0 x 105 cells/ml. After 48 hours,
naphthazarin (2.17 µM), PSI (80.0 µM) or rotenone (40.0 µM) was added to cells. Three or 24
hours following addition of toxin, propidium iodide (2 µM) was added to cells for 5 minutes, and
the number of propidium iodide positive (dead) cells quantified. Data are presented as
percentage of propidium iodide positive cells out of 150 counted cells ± SEM (n = 4).
49
2.2.5 JC-1 and lysosensor green assays
Twenty-four hours post plating of SH-SY5Y cells, naphthazarin (2.17 µM), PSI (80 µM) or
rotenone (40 µM) were added. Following incubation with toxins for 3 or 24 hours, JC-1 (2 µM)
or lysosensor green (2 µM) was added to each well and incubated with the cells for 30 minutes,
then each well was aspirated and washed with DMEM before recording fluorescence intensity of
each probe (FLUOstar OPTIMA): JC-1 monomer: Ex. 485 nm, Em. 430 nm, J-aggregate: Ex.
535 nm, Em. 590 nm; lysosensor green: Ex. 440 nm, Em. 510 nm. Data from the JC-1 studies
are presented as the J-aggregate/monomer ratio in fluorescence intensity units ± SEM (n = 4).
Data from lysosensor green studies are presented as mean percent fluorescence intensity units
compared to control ± SEM (3 hours: N = 3; 24 hours: N = 4).
2.2.6 Proteasome sensor vector assay
SH-SY5Y cells were electroporated with ZsProSensor-1 using Nucleofector Kit V in A-23 mode
(Amaxa, USA) in 96-well plates. Naphthazarin (2.17 µM), PSI (80 µM) or rotenone (40 µM)
was added to the cells 48 hours after plating. Three or 24 hours following toxin addition,
fluorescence intensity was measured using a FLUOstar OPTIMA plate reader: Ex. 490 nm, Em.
520 nm. Data are presented as mean percent fluorescence intensity compared to control ± SEM
(3 and 24 hours: N = 4).
2.2.7 Western blotting
SH-SY5Y cells were exposed to naphthazarin (2.17 µM), PSI (80 µM) or rotenone (40 µM) for 3
or 24 hours. Cells were washed twice with ice-cold PBSx1 and scraped from 100 mm plates
with Laemmli buffer following toxin incubation. Samples were lysed for 15 minutes in water
(95 oC), and protein concentrations determined using the Bradford method (Bradford 1976).
Protein samples (10-20 µg) were loaded onto gels, and SDS-PAGE followed by Western blot
50
was carried out. Nitrocellulose blots were blocked in 5% non-fat powdered milk (60 min) and
incubated with antibodies against β-actin (1:1000 µl) and ubiquitin (1:500 µl) overnight (4 oC).
Following 5 washes in 0.5% Triton-X in PBS, mouse (1:5000 µl) or rabbit (1:5000 µl) HRP-
conjugated secondary antibodies were incubated at room temperature (60 min) in a 1% non-fat
powdered milk/TTBS (0.1% Tween-20) solution. Protein levels were detected using enhanced
chemiluminescence (Immun-Star, Bio-Rad), then imaged (FluorChem, Alpha Innotech
Corporation) and optical density determined (FluorChem v2.0). Data are presented as mean
optical density ± SEM (n = 4).
2.2.8 Statistical analysis
For each experiment (n or N), each n/N was taken from a different plate of cells. For propidium
iodide assays, there was 1 replicate in each n. For alamar blue assays, there were 6 replicates for
each condition per N. For JC-1 and lysosensor green assays, there were 5 replicates in each N.
For proteasome sensor vector there was one replicate per N. Data generated from cell viability
were analysed using one-way ANOVA with Dunnett’s multiple comparison test post-hoc.
Propidium iodide assays were analysed using two-way ANOVA, using toxin and time of toxin
exposure as variables with Bonferroni test post-hoc. JC-1, proteasome sensor vector, lysosensor
green and Western blot experiments were analysed using one-way ANOVA with Tukey`s
multiple comparisons test post-hoc. For all studies, significance was assigned when P < 0.05.
2.3 Results
2.3.1 Effect of toxin exposure on cell viability and cell death
Exposure to naphthazarin significantly reduced cell viability over the ranges of 1 µM-1000 µM
at 3 hours (Fig. 2.1a) and 24 hours (Fig. 2.1b). The concentration of naphthazarin that decreased
cell viability by approximately 50% (EC50%) was 0.9 µM and 1.0 µM following 3 and 24 hours
51
exposure respectively. PSI significantly reduced cell viability following incubation for 3 hours
and 24 hours. Post hoc analysis demonstrated a decrease in cell viability at concentrations
between 1 µM and 1000 µM following exposure for 3 hours (Fig. 2.1a) and 10 µM-1000 µM
following exposure for 24 hours (Fig. 2.1b) with an EC50% 6.04 µM and 100.0 µM respectively.
Rotenone also reduced cell viability after 3 hours and 24 hours exposure (Fig. 2.1). Post hoc
analysis showed a significant decrease in cell viability at concentrations between 1 µM and 1000
µM following 3 hours (Fig. 2.1a) and 24 hours exposure (Fig. 2.1b) with an EC50% 680.0 µM
and 210.1 µM respectively. Next, based on our findings in the cell viability assays and previous
studies in SH-SY5Y cells (Sapkota et al.; Jiang et al., 2004; Naoi et al., 2005; Chung et al., 2007;
Cho et al., 2008; Koch et al., 2009), approximate EC50% concentrations of each toxin were used
to determine the extent of cell death following 3 and 24 hours of toxin exposure to the cells.
Toxins were added to SH-SY5Y cells, and the amount of cell death was assessed using
propidium iodide. Following incubation of SH-SY5Y cells with toxins and propidium iodide,
there was a significant increase in the number of dead cells over time (Fig. 2.1c). Post-hoc
analysis showed that none of the toxins used significantly increased cell death after a 3 hour
exposure but all toxins caused a significant increase in cell death after 24 hours exposure.
Naphthazarin and rotenone increased cell death by 2-fold compared to vehicle (media), and PSI
increasing cell death by 4-fold compared to vehicle (DMSO).
52
Figure 2.1. Effect of toxins on cell viability and cell death in SH-SY5Y cells. Cells were
incubated with naphthazarin, PSI or rotenone (0.1 µM–1000 µM) in the presence of alamar blue
for (a) 3 or (b) 24 hours, and cell viability was assessed. Data are expressed as mean percentage
fluorescence ± SEM compared to control (N = 4). One way ANOVA showed significant effects
of toxin exposure on cell viability following 3 and 24 hours exposure (naphthazarin: 3 hours: F5
= 84.5, 24 hours: F5 = 204.8; PSI: 3 hours: F5 (toxin) = 7.2, 24 hours: F5 (toxin) = 23.8;
rotenone: 3 hours: F5 (toxin) = 7.2, 24 hours: F5 (toxin) = 23.8). Dunnett’s multiple
comparisons test post-hoc showed that toxins caused a significant decrease in cell viability.
Naphthazarin: *** P < 0.001, compared to vehicle (media). PSI: $ P < 0.05, $$ P < 0.01, $$$ P
< 0.001 compared to vehicle (DMSO). Rotenone: & P < 0.05, && P < 0.01, &&& P < 0.001
compared to vehicle (media). (c) Cell death in SH-SY5Y was assessed following 3 or 24 hours
exposure to naphthazarin (2.17 µM), PSI (80 µM) or rotenone (40 µM) using propidium iodide
(PI). Data are presented as mean number of PI positive cells out of 150 ± SEM (n = 4). Two
way ANOVA showed a significant difference in propidium iodide uptake following incubation
with toxins for 3 and 24 hours compared to control (media for naphthazarin and rotenone;
DMSO for PSI) (F4 (toxin) = 26.49, F1 (time) = 56.76; F4 (interaction toxin x time) = 16.65).
Bonferroni test post-hoc showed a significant increase in propidium iodide uptake in the cells
following incubation with naphthazarin, PSI and rotenone for 24 hours compared to control, with
no significant effect of any toxin following incubation for 3 hours (*** P < 0.001).
53
a
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concentration (τM)
cell viability (% control)
b
0 0.1 1 10 100 10000
20
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54
2.3.2 Effect of toxin exposure on mitochondria, UPS and lysosomes
An early marker of mitochondrial impairment is depolarisation of the mitochondrial membrane
potential. To assess the impact of toxins on mitochondrial function, naphthazarin, PSI or
rotenone were added to SH-SY5Y cells for 3 or 24 hours, and JC-1 was utilised to measure
mitochondrial membrane potential. After 3 hours exposure to all toxins, the ratio of JC-1
monomer to aggregates was significantly increased compared to controls (vehicle-treated cells),
indicating a depolarisation in mitochondrial membrane potential. Post hoc analysis showed that
the monomer to aggregate ratio following naphthazarin, PSI and rotenone treatment was
increased by 2.5-fold, 2-fold and 4.6-fold respectively compared to control (media for
naphthazarin and rotenone; 0.1% DMSO for PSI) (Fig. 2.2). Longer exposure to rotenone (24
hours) enhanced mitochondrial membrane depolarisation 6.1-fold compared to control. In
contrast, following 24 hours exposure to naphthazarin and PSI, there was no significant effect
compared to control (Fig. 2.2).
55
Figure 2.2. Effect of compounds on mitochondrial membrane potential in SH-SY5Y cells.
SH-SY5Y cells were incubated with naphthazarin (2.17 µM), PSI (80 µM) or rotenone (40 µM)
for 3 hours or 24 hours. Changes in mitochondrial membrane potential were assessed using JC-
1. Data are expressed as ratio of mean fluorescence of aggregate to monomer ± SEM (N = 4).
One-way ANOVA showed a significant effect of toxins on mitochondrial membrane potential, 3
hours (F4 = 12.32) and 24 hours (F4 (toxin) = 22.85) following exposure. Tukey’s multiple
comparison test post-hoc: * P < 0.05, *** P < 0.001.
56
Media DMSO NAP PSI ROT0.0
0.5
1.0
1.5 ******
*
3 hours
24 hours
ratio
of m
onom
er/a
ggre
gate
(ave
rage
FIU
)
*
57
To determine the effect of naphthazarin, PSI and rotenone on proteasomal function, toxins were
incubated with cells previously transfected with the proteasome-sensitive fluorescent reporter
ZsProSensor-1 for 3 or 24 hours. When the proteasome is functioning normally, ZsProSensor-1
is broken down, however, when proteasomal function is compromised, ZsProSensor-1
accumulates, resulting in an increase in fluorescence intensity. Three hours of exposure to PSI
caused a significant increase (398%) in ZsProSensor-1 fluorescence compared to control,
indicating impaired proteasomal function however there was no significant effect of
naphthazarin or rotenone on proteasomal function. Following 24 hours exposure, impaired
proteasomal function was observed with all 3 toxins. Naphthazarin, PSI and rotenone increased
the fluorescence intensity of ZsProSensor-1 by 1135%, 2217% and 712% respectively (Fig. 2.3).
58
Figure 2.3. Effect of toxins on proteasomal function in SH-SY5Y cells. Cells were
transfected with the proteasome-sensitive fluorescent reporter ZsProSensor-1 then incubated
with naphthazarin (2.17 µM), PSI (80 µM) or rotenone (40 µM) for (a) 3 hours or (b) 24 hours,
then fluorescence intensity measured. Data are expressed as mean fluorescence ± SEM (N = 4).
One-way ANOVA showed a significant effect of toxins on proteasomal function, 3 hours (F4
(toxin) = 3.15) and 24 hours (F4 = 90.61) following exposure compared to media control
(naphthazarin and rotenone) or DMSO control (PSI). Tukey’s multiple comparison post-hoc: * P
< 0.05, *** P < 0.001.
59
3 hours
24 hours
Media DMSO NAP PSI ROT
aver
age f
luor
esce
nce (
%co
ntro
l)
050
100150200
5001000150020002500 ***
*******
60
To determine the effect of naphthazarin, PSI and rotenone on lysosomes, cells were incubated
with the 3 toxins in the presence of lysosensor green, which fluoresces when taken into the
lysosome, serving as a marker of lysosomal function. Three hours of toxin exposure led to a
significant difference in lysosensor green fluorescence compared to control (Fig. 2.4). Post hoc
analysis showed that naphthazarin decreased fluorescence by 67.24% compared to vehicle,
whereas PSI and rotenone had no effect at this time. Following 24 hours of toxin exposure, there
was a significant effect of all toxins on fluorescence of lysosensor green compared to vehicle.
Post hoc analysis showed that naphthazarin, PSI and rotenone decreased fluorescence intensity
60.93%, 40.35% and 38.05% respectively.
61
Figure 2.4. Effect of toxin exposure on lysosomal function. Lysosomal function was assessed
via measurement of fluorescence of lysosensor green 3 hours or 24 hours after the addition of
naphthazarin (2.17 µM), PSI (80 µM) or rotenone (40 µM). Data are expressed as mean
fluorescence ± SEM (N = 4). One-way ANOVA showed a significant effect of toxins on
lysosomal function, 3 hours (F4 = 3.63) and 24 hours (F4 = 15.31) following toxin exposure
compared to media control (naphthazarin and rotenone) or DMSO control (PSI). Tukey’s
multiple comparison test post-hoc * P < 0.05, ** P < 0.01, *** P < 0.001.
62
0
40
80
120
**
***
3 hours24 hours
**
*
aver
age f
luor
esce
nce (
% co
ntro
l)
Media DMSO NAP PSI ROT
63
2.3.3 Effect of toxins on ubiquitin levels
Post mortem studies have shown increased formation of ubiquitin aggregates in affected brain
regions of patients with PD (Leigh et al., 1989). However, it is not known whether such
pathologies arise due to dysfunction of the mitochondria, proteasome or lysosome, or indeed all
three. As shown in Figure 2.5a, b, a 3 hour exposure to naphthazarin, and PSI, but not to
rotenone altered ubiquitin expression. Following 3 hours of toxin exposure, naphthazarin and
PSI increased ubiquitin expression by 315.94%and 323.19% respectively compared to controls
(Fig. 2.5a,b). Following 24 hours of toxin exposure, ubiquitin expression was dramatically
increased compared to control. Post hoc analysis showed that naphthazarin, PSI and rotenone
increased ubiquitin levels by 7495%, 8954% and 10902% respectively compared to vehicle (Fig.
2.5a,c).
64
Figure 2.5. Western blots to show changes in ubiquitin levels following toxin exposure. SH-
SY5Y cells were exposed to naphthazarin (2.17 µM), PSI (80 µM) or rotenone (40 µM) for 3
hours or 24 hours, harvested, and SDS-PAGE followed by Western blot was performed to detect
levels of ubiquitin. (a) Data are expressed as mean optical density ± SEM (n = 4). One-way
ANOVA showed significant effects following 3 hours (F4 = 5.17) and 24 hours (F4 = 253.1)
following toxin exposure compared to media control (naphthazarin and rotenone) or DMSO
control (PSI). Dunnett’s multiple comparison test post-hoc * P < 0.05, ** P < 0.01, *** P <
0.001. (b) Representative Western blot following 3 hours toxin exposure. (c) Representative
Western blot following 24 hours toxin exposure.
65
a
0
200
400
6006000
8000
10000
12000
***
3 hours24 hours
**
Media DMSO NAP PSI ROT
***
***
*
aver
age o
ptic
al d
ensi
ty(%
con
trol)
bUbiquitin
ß-actin 42 kDa
200-250 kDa
MED
IA
DM
SO
NA
P
PSI
RO
T
c
DM
SO
NA
P
PSI
RO
T
Ubiquitin
ß-actin 42 kDa
200-250 kDa
3 hours
24 hours
66
2.4 Discussion
SH-SY5Y cells were exposed to toxins that cause their effects via different mechanisms that
have been linked with neurodegeneration in PD, i.e., impairment of mitochondrial, lysosomal or
UPS function. The aim of this study was to determine a common cell stress mechanism
triggered by these different sub-cellular dysfunctions during the early stages of cell stress, so that
a target for a disease modifying agent may be revealed. Thus, it was necessary to utilise
concentrations of toxins that caused a significant level of cell stress (as measured by decreased
cell viability), while causing minimal levels of cell death, as this scenario recapitulates the
situation at the time of initial diagnosis of PD, when approximately 50% of neurons in the SNc
are alive, although may be undergoing some form of sub-cellular stress (Bernheimer et al.,
1973). Whilst in this study, cells were exposed to high concentrations of toxins for a relatively
short period of time (24 hrs) to induce acute toxicity. Previous studies have shown that this acute
model does reproduce the cell death processes implicated in PD (Yong-Kee et al., 2011a).
Following 3 hours exposure of all toxins at concentrations that caused an approximate 50%
decrease in cell viability (EC50%), no cell death was observed. Following 24 hours exposure,
the approximate EC50% of all toxins caused a significant increase (approximately 2-4 fold) in
cell death. Thus, following three hours of EC50% toxin exposure, 50% of SH-SY5Y cells
exhibit decreased cell viability, and the remaining 50% are likely to be undergoing some form of
sub-cellular stress, since there is a further decrease in cell viability after 24 hours. This scenario,
in which cells are under-going moderate to high levels of cell stress, although have not yet died,
is likely to be comparable to the situation in surviving neurons of SNc in parkinsonian patients.
Specifically, following 24 hours of toxin exposure, we see a loss of cell viability and an increase
in cell death. Thus, this represents a mixed population of cells, in which some are healthy, some
67
are no longer viable, and some are dead (Bernheimer et al. 1973). Thus, exposure of cells to
toxins that mimic cell death mechanisms associated with PD for short periods (3 and 24 hours) is
a useful model for studying the early events which take place when cells are under cell stress.
Given that catecholaminergic neurons are the most susceptible to neurodegeneration in PD
(Hornykiewicz, 1972; Braak et al., 1996), the catecholaminergic neuroblastoma cell line, SH-
SY5Y, which has previously been used as a model for studying cell death mechanisms in PD
was selected for our studies (Dadakhujaev et al., 2010; Xie et al., 2010; Xie et al., 2011; Nonaka
and Hasegawa, 2009; Wu et al., 2009). Whilst primary mesencephalic cultures are a more
physiological representation of neurons of the substantia nigra pars compacta, it is difficult to
produce them in large quantities, and so it would not have been possible to perform the assays
utilised in the present studies. Previous studies have shown that lower concentrations of
rotenone (15-50 nM) were sufficient to cause cellular dysfunction (Liss & Roeper, 2001;
Shamoto-Nagai et al., 2003; Lannuzel et al., 2003; Lannuzel et al., 2006); in the present study
however, the concentration of rotenone required to decrease cell viability by 50% was 680.0 µM.
There are at least three possible explanations for these variations in the EC50% of rotenone:
firstly, cell type, secondly, the period of time in which rotenone was exposed to the cells, and
finally, the parameter utilised to measure cellular dysfunction. In one study, 15 nM of rotenone
was sufficient to inhibit mitochondrial complex 1 activity by 50% in acute mouse brain slices
(Liss & Roeper, 2001). Indeed, neurons are known to be much more sensitive to cell stress than
other cell types, such as SH-SY5Y cells that were used in the present study. Whilst SH-SY5Y
cells have a neuronal phenotype, they are not neuronal cells, and so are less sensitive to rotenone
as has been shown previously (Shamoto-Nagai et al., 2003; Lannuzel et al., 2003). Another
explanation for the difference in EC50s between the study carried out by Shamoto-Nagai and
colleagues and also Lannuzel et al., compared to the current study, is that in these two previously
68
published studies, different markers of cellular dysfunction were used to measure the impact of
rotenone on cellular dysfunction. Shamoto-Nagai and colleagues measured inhibition of
mitochondrial complex 1 activity, whereas in the current study, changes in cell viability were
assessed. Since inhibition of mitochondrial complex 1 will precede a loss of cell viability, it is
most likely that the rotenone concentration required to cause a 50% inhibition of the
mitochondrial complex 1 is less than that required to cause a 50% decrease in cell viability.
Lannuzel and co-workers utilised loss of TH immunoreactivity as a marker of cell death.
Previously it has been shown that, in dopaminergic neurons, loss of TH phenotype precedes loss
of cell viability and neuronal cell death (Paul et al., 2004), thus providing a possible explanation
as to why the concentration of rotenone required was lower than in the present study.
Interestingly, Shamoto-Nagai and co-workers also used SH-SY5Y cells, and showed that 25-50
nM of rotenone was sufficient to kill 50% of the cells. However, in this study, 50% of cells died
following incubation with toxins for 72-120 hours. Indeed, as in our study, Shamoto-Nagai et
al., observe no cell death following incubation with rotenone for 24 or 48 hours. Finally, in the
present study, we describe an acute model of cellular stress, in which the initial sub-cellular
effects of toxic insult were evaluated. This justifies the use of higher concentrations of toxins for
a shorter time course.
When mitochondria, UPS and lysosomal function was assessed following 3 and 24 hours
exposure to naphthazarin, PSI or rotenone, all toxins caused depolarisation of the mitochondrial
membrane potential at 3 hours, whereas after 24 hours, only rotenone affected mitochondrial
function. This apparent recovery of mitochondrial function may represent a compensatory
mechanism, indeed it has been shown that pre-conditioning of the mitochondria occurs with mild
forms of toxic insults (Gidday, 2006; Busija et al., 2008). Three hours following toxin exposure,
only PSI inhibited proteasomal function, whereas following 24 hours exposure, all 3 toxins
69
inhibited UPS function. Similarly, with respect to lysosomal function, after 3 hours of toxin
exposure, only naphthazarin decreased lysosomal function, whereas, following 24 hours of
exposure to toxins, all 3 toxins inhibited lysosomal function. The early effect of PSI on UPS
function and naphthazarin on lysosomal function confirms that the primary effects of these
toxins are via inhibition of the proteasome and lysosome respectively. Finally, following three
hours of toxin incubation, only naphthazarin and PSI increased levels of ubiquitination, whereas
following 24 hours treatment, all three toxins caused a significant increase in ubiquitin
expression. Both the UPS and lysosome are important for the breakdown of ubiquitinated
proteins (Kettern et al., 2010; Hochstrasser, 1992; Kubota, 2009; Todde et al., 2009), therefore,
the observed increase in ubiquitinated proteins shortly after incubation of cells with toxins that
inhibit these functions is not surprising. The finding that all 3 toxins increased ubiquitin levels
24 hours following toxin exposure is expected, since both lysosome and the proteasome-
mediated de-ubiquitination require ATP, thus extended periods of mitochondrial inhibition will
result in a lack of ATP, hindering physiological function of lysosomes and the UPS. Autophagic
processes require acidified lysosomal compartments that are maintained by ATP-dependent
proton pumps (Terman et al., 2010). Thus, reduced ATP levels may hinder lysosomal function,
by decreasing the rate of activity of the proton pump, which would slow down the ability of the
lysosome to degrade unwanted proteins. Similarly, UPS function relies heavily on a constant
supply of ATP. Access to the proteasomal core is regulated by the opening and closing of the
proteasomal cap (Betarbet et al., 2005). Therefore, since this process is ATP-dependent,
decreased ATP will also prevent protein degradation by the proteasome. Furthermore, excess
proteins in the cytosol may ultimately become deleterious to the cell because increased
misfolded proteins may form toxic aggregates which cause cell death (Mytilineou et al., 2004).
70
Indeed, reduced ATP levels were found to hamper proteasomal activity in primary cultures
(Hoglinger et al., 2003).
Interestingly, both proteasomal and lysosomal inhibition reduced mitochondrial membrane
potential. Mitochondrial dysfunction caused by inhibition of the proteasome has been shown in
other in vitro studies (Qui et al., 2000; Ding and Keller, 2001; Hoglinger et al., 2003). Inhibition
of the proteasome results in an increase in the number of misfolded and aggregated proteins,
which has deleterious effects on the cell, by increasing the number of reactive oxygen species.
The resulting increase in oxidative stress further augments cell stress by increasing influx of Ca2+
into the cell, leading to excitotoxic conditions (Demuro et al., 2005; Danzer et al., 2007).
Increased excitotoxicity, enhances Ca2+ influx into the mitochondria, resulting in the
accumulation of free radicals within the mitochondria, which induces depolarisation of the
mitochondrial membrane potential (Ward et al., 2000) and loss of ATP (Budd and Nicholls,
1996). Whilst, there are no previous studies to show that inhibition of lysosomal function
impacts mitochondrial function, it has been shown that following over-expression of wild-type
α-synuclein in neuronal cultures, this protein accumulates in mitochondria leading to reduced
activity of mitochondrial complex 1 and subsequent mitochondrial dysfunction (Devi et al.,
2008). Whilst the reason why α-synuclein accumulates in the mitochondria is unclear; it is
known that α-synuclein is usually degraded by the lysosome, and that mutant α-synuclein
inhibits lysosome-mediated breakdown of misfolded and toxic proteins, including α-synuclein
(Cuervo et al., 2004; Sarkar et al., 2007). Impaired lysosomal function would also prevent
lysosome-mediated uptake of free radicals, which would in turn cause mitochondrial dysfunction
via similar mechanisms to those described for the proteasome (Kubota et al., 2010). Thus, these
studies indicate that, no matter what the mechanism of insult, mitochondrial dysfunction occurs
71
early in the cell death process, indicating that targeting the mitochondria may be an effective
neuroprotective strategy against all causes of cell death linked with PD.
As mentioned above, previous in vitro studies in cell models of PD have shown a tight link
between mitochondrial and UPS function (Shamoto-Nagai et al., 2003; Sullivan et al., 2004;
Radke et al., 2008). It has also been shown previously that mitochondrial abnormalities result in
lysosomal dysfunction, suggesting that there is also a link between mitochondrial and lysosomal
integrity (Irrcher et al., 2010). The current study is the first to demonstrate the link between
UPS, lysosomal and mitochondrial abnormalities very early in the cell stress pathway. It is
known that lysosomes and the UPS work together to regulate protein degradation within the cell,
the present study also suggests that only after longer periods of impaired lysosomal function does
the UPS become impaired, and vice versa. This delayed impairment of the UPS or lysosome
following prolonged inhibition of lysosome or UPS respectively, is probably due to a build up of
aggregated proteins, as indicated by the increase in ubiquitin levels as early as 3 hours following
exposure to naphthazarin or PSI in the present study.
In conclusion, these studies show that with respect to mechanisms of cellular dysfunction linked
with PD, cells are most sensitive to mitochondrial dysfunction, since any form of cell stress,
whether caused by inhibition of mitochondria, proteasome or lysosome results in mitochondrial
dysfunction early in the cell death pathway. Finally, our findings suggest that protecting
mitochondrial function early in the disease process i.e., upon initial diagnosis could potentially
be a disease modifying strategy for preventing the cell death that characterises later stages of PD.
The assays utilised in these studies may prove useful for testing potential neuroprotective
treatments in the future.
72
Chapter 3
Development and Validation of a Screening Assay for the Evaluation of Putative
Neuroprotective Agents in the Treatment of Parkinson’s Disease
A modified version of this chapter was previously published as:
Yong-Kee CJ, Salomonczyk D, Nash JE (2011) Development and validation of a screening assay for the evaluation of putative neuroprotective agents in the treatment of
Parkinson's disease. Neurotoxicity research 19:519-526.
73
3 Development and Validation of a Screening Assay for the Evaluation of Putative Neuroprotective Agents in the Treatment of Parkinson’s Disease
3.1 Introduction
In order to prevent neurodegeneration, it is necessary to understand how cells die. Genetic and
post mortem studies suggest that inhibition of mitochondrial complex 1, aberrant protein
degradation caused by dysfunction of the UPS and lysosomes, as well as oxidative stress from
dopamine metabolism in neurons of the SNc contribute to neurodegeneration in Parkinson’s
disease (Ardely et al., 2004; Di Fonzo et al., 2007; Kitada et al., 1998; Ramirez et al., 2006).
Both the lysosome and UPS are required for the degradation of damaged proteins. Ubiquitin
motifs are attached to proteins by ubiquitin ligases, which target the protein to proteasomes,
while lysosomes employ chaperone-mediated autophagy for protein degradation. Abnormal
lysosome and UPS function leads to protein accumulation into toxic aggregates that eventually
cause cell death (Betarbet et al., 2005). Presently, there is no evidence that mutations in genes
involved in dopamine metabolism cause PD, however, in any neuron, dopamine metabolism is
inherently toxic, causing oxidative stress, due to the production of semiquinones, and other free
radicals. It is not known why dopaminergic neurons of the SNc are more susceptible to
oxidative stress than any other dopaminergic neuron however (Jenner, 2003).
It is probable that in most parkinsonian patients, a combination of some or all of the above
pathological processes contribute to cell death (Dagda et al., 2008; Canu et al., 2000; Hoglinger
et al., 2003; Pandey et al., 2007). Many animal and cell culture models of PD have been
developed to further understand how these cell death mechanisms interact (Hanrott et al., 2006;
74
Panov et al., 2005) however, it is difficult to develop a model that takes into account the
numerous cell death mechanisms that are likely to cause idiopathic PD. Furthermore, such
models take months or years to develop. Unfortunately, without such a model, it is extremely
difficult to accurately predict the true potential of a putative disease modifying agent for the
treatment of PD.
Herein I hypothesized that a direct correlation between the assay used here, and the assays
conducted by NINDS can validate the effectiveness of this assay to test potential neurprotective
agents. The studies described in this chapter outline the development of an in vitro assay, which
involved exposure of catecholaminergic neuroblastoma cells (SH-SY5Y) to toxins that mimic
what are currently believed to be the main causes of neurodegeneration in PD. To assess the
validity of this assay, we tested five compounds that were previously chosen by the NINDS
sponsored CINAPS to move forward into clinical trials (Ravina et al., 2003; Heemskerk et al.,
2002). The results of this study directly correlate with the success of putative neuroprotective
agents in clinical trials. Therefore, it appears that this cell assay is a rapid and accurate predictor
of the usefulness of potential disease modifying agents for halting the progression of PD. We
propose that this assay will be a useful predictor of potential neuroprotective agents which may
be successful in clinical trials.
3.2 Materials and Methods
3.2.1 Materials
Z-Ile-Glu(OBut)-Ala-Leu-H (PSI) was purchased from BIOMOL (USA), alamar blueTM was
purchased from Biosource (Canada) and propidium iodide from Invitrogen (USA). Dopamine
hydrochloride, 5,8-dihydroxy- 1,4-naphthoquinone (naphthazarin), rotenone, coenzyme Q10,
caffeine, creatine, nicotine, R-(-)-deprenyl hydrochloride (deprenyl), salicylic acid and dimethyl
75
sulfoxide (DMSO) were purchased from Sigma (USA). SH-SY5Y cells were purchased from
ATCC (USA), Dulbecco’s Modified Eagle’s Medium (DMEM), bovine calf serum, and trypsin
from Wisent (Canada).
3.2.2 Cell culture
SH-SY5Y cells were grown in DMEM (6400 mg/L NaCl, 3700 mg/L NaHCO3, 400 mg/L KCl
and 584 mg/L L-glutamine) and supplemented with 10% bovine calf serum in a sterile
humidified chamber (37 °C, 95% CO2, 5% O2) (MCO-20AIC, Sanyo, USA) until 80% confluent.
Cells were passaged using 0.1% trypsin for 5 min, then pelleted by centrifuging at 340xg
(Allegra 6R Centrifuge, Beckman Coulter, USA).
3.2.3 Effect of toxins on cell viability and cell death
To determine the effects of toxins on cell viability, SH-SY5Y cells (P20-P30) were plated at a
density of 1 x 105 per ml into 96 well plates 24 hours prior to the addition of dopamine
hydrochloride (0.1 µM–600 µM), naphthazarin (0.1 µM–1 mM), PSI (0.1 µM–500 µM) and
rotenone (0.1 µM–1 mM). The redox sensitive dye, alamar blue (0.4% of final volume) was
added to the cells immediately after the addition of toxin. Twenty four hours after treatment,
changes in alamar blue fluorescence were quantified (ex. 544 nm, em. 590 nm) using a plate
reader (FLUOstar OPTIMA, BMG Labtech, USA).
Cell death was determined using propidium iodide. SH-SY5Y cells were plated at a density of 1
x 105 per ml onto coverslips (diameter: 22 mm) in 6 well plates 24 hours prior to the addition of
dopamine (600 µM) and propidium iodide (2 µM). Cells were imaged at time 0, and 24 hours
later using confocal microscopy (LSM 510 META, Zeiss).
76
3.2.4 Effect of putative neuroprotective agents on toxins
SH-SY5Y cells (P20-P30) were plated in 96 well plates at a density of 1 x 105 per ml 24 hours
prior to addition of compounds. Putative disease modifying agents were added to the cells 5
minutes before addition of toxins in the following concentrations: coenzyme Q10 (117 µM),
caffeine (140 µM), creatine (25 mM), nicotine (1 µM), R-(-)-deprenyl hydrochloride (10 µM)
and salicylic acid (10 mM). All compounds were dissolved in media. These concentrations
were chosen based on previous studies in cell lines (Andres et al., 2005; Lai & Yu, 1997; Menke
et al., 2003; Paterson et al., 1998; Xie et al., 2005). Approximate EC50 of toxins were added to
the cells; these were as follows: dopamine (30 µM), naphthazarin (2.17 µM), PSI (80 µM) and
rotenone (40 µM). Dopamine, naphthazarin and rotenone were dissolved in media; PSI was
dissolved in 0.1% DMSO. Alamar blue was added to the cells immediately after the addition of
toxin, and cell viability was assessed 24 hours later as described above.
3.2.5 Statistical analysis
A different passage of cells was used for each experiment (n = 1), fluorescence was expressed as
the mean of 6 replicates in each experiment (n = 6). Data are expressed as means ± SEM
compared to vehicle. Effect of toxin concentration on cell viability, and putative neuroprotective
agents on toxins was determined using two-way ANOVA with Bonferroni post hoc. Effect of
neuroprotective agents on cell viability was assessed using one-way ANOVA with Dunnett’s
multiple comparisons post hoc. Significance was assigned when P < 0.05.
3.3 Results
I first determined the EC50 of a battery of toxins that recapitulate the most likely cell death
mechanisms in PD, i.e. oxidative stress (dopamine), inhibition of the lysosome (naphthazarin),
inhibition of the mitochondria (rotenone) and proteasome chymotrypsin like activity inhibition
77
(PSI). SH-SY5Y cells were exposed to a range of toxins for 24 hours, and cell viability assessed
(Fig. 3.1a). Two-way ANOVA, using treatment and concentration as factors, showed significant
effects of toxin treatment and concentration (F3,340 (toxin treatment) = 67.21, P < 0.0001, m =
11490; F16,340 (concentration) = 117.4, P < 0.001, m = 20080; F48,340 (interaction toxin treatment x
concentration) = 4.44, P < 0.001, m = 759.4) (n = 6). Bonferroni post hoc showed that dopamine
caused a significant decrease in cell viability compared to vehicle (media) at concentrations 10
µM–600 µM (P < 0.01–0.001, n = 6). The maximum decrease in cell viability was 83 ± 3.5%
SEM. Naphthazarin caused a significant decrease in cell viability compared to control (vehicle)
at concentrations 3 µM–1000 µM (P < 0.05–0.001, n = 6). The maximum decrease in cell
viability was 98 ± 2.7% SEM. PSI (0.1 µM -500 µM) caused a significant decrease in cell
viability compared to vehicle (0.1% DMSO) at concentrations 15 µM–500 µM (P < 0.05–0.001,
n = 6). Rotenone (0.1 µM–1000 µM) caused a significant decrease in cell viability compared to
vehicle (media) at concentrations 30 µM–1000 µM (P < 0.05–0.001, n = 6). The maximum
decrease in cell viability was 62 ± 5.6% SEM. The maximum decrease in cell viability was 82 ±
6.3% SEM. EC50’s for the toxins were as follows in order of decreasing potency: naphthazarin:
2.17 µM < dopamine hydrochloride: 30 µM < rotenone: 40 µM < PSI: 80 µM. To confirm that
changes in cell viability are a true correlate of cell death, cells were exposed to dopamine (600
µM) in the presence of propidium iodide for 24 hours. Immediately after addition of toxin, cells
appeared healthy, however following 24 hours incubation, the cells had absorbed the red dye,
due to cell membrane permeabilisation indicating that the cells were dead. Thus, measurement
of cell viability using alamar blue is a direct correlate of cell death (Fig. 3.1b).
78
Figure 3.1. Effect of toxins on cell viability in SH-SY5Y cells. (a) SH-SY5Y cells were treated
with concentration response curves of toxin, which were as follows: dopamine hydrochloride
(0.1 µM–600 µM), naphthazarin (0.1 µM–1 mM), PSI (0.1 µM–500 µM) and rotenone (0.1 µM–
1 mM). After 24 hours of toxin treatment, cell viability was assessed using alamar blue.
Dopamine, naphthazarin, PSI and rotenone caused significant decreases in cell viability
compared to vehicle (media or DMSO) (two-way ANOVA with Bonferroni post hoc). Data are
expressed as mean ± SEM percent viability compared to vehicle (DMSO for PSI and media for
all other toxins) (n = 6). (b) SH-SY5Y cells were incubated with dopamine (600 µM) or vehicle
and propidium iodide (2 µM) and imaged immediately following addition of compounds and 24
hours later.
79
b Control DA
0 hr
24 hr
0.0 0.1 1 10 100 10000
20
40
60
80
100
120
140DA
ROTPSINAP
[Toxins]µM
Cel
l Via
bilit
y (%
Con
trol)
a
80
Following establishment of the EC50, putative disease modifying agents were added to the cells
immediately prior to the addition of each toxin. Following dopamine treatment alone, there was
an 88.3 ± 2.4% decrease in cell viability compared to vehicle-treated cells. ANOVA showed a
significant difference in cell viability following co-incubation of potential neuroprotective
compounds with dopamine compared to dopamine treatment alone (Bonferroni post hoc test
(F1,60 (toxin) = 149.2, P < 0.0001, m = 6194; F5,60 (concentration) = 17.0, P < 0.0001, m = 707.5;
F5,60 (interaction toxin x concentration) = 20.9, P < 0.0001, m = 868.7) (n = 6). Coenzyme Q10
(117 µM), creatine (25 mM), nicotine (1 µM) and salicylic acid (10 mM) reduced dopamine
induced toxicity by 16.3 ± 3.3%, 19.4 ± 4.2% 51.5 ± 3.6% and 10.4 ± 1.2% respectively (all P <
0.001, except salicylic acid P < 0.05, n = 6) (Fig. 3.2a). Caffeine (140 µM) and deprenyl (10
µM) had no significant effect on dopamine induced toxicity. There was a significant effect of
neuroprotective agents on naphthazarin-induced decreases in cell viability compared to
naphthazarin treatment alone (F1,60 (toxin) = 59.2, P < 0.0001, m = 958.6; F5,60 (concentration) =
169.3, P < 0.0001, m = 2743; F5,60 (interaction toxin x concentration) = 142.8, P < 0.0001, m =
2314) (n = 6). Following naphthazarin treatment, there was a 79.3 ± 0.6% decrease in cell
viability compared to vehicle-treated cells. When naphthazarin was combined with coenzyme
Q10 (117 µM) or salicylic acid (10 mM) there was a 10.8 ± 1.1% and 60.8 ± 5.2% increase in
cell viability, respectively, compared to naphthazarin alone (both P < 0.001, n = 6) (Fig. 3.2b).
Caffeine (140 µM), creatine (25 mM), nicotine (1 µM) and deprenyl (10 µM) did not attenuate
the reduction in cell viability caused by naphthazarin. Neuroprotective agents significantly
reduced PSI-induced decreases in cell viability compared to PSI treatment alone (F1,60 (toxin) =
161.7, P < 0.0001, m = 7080; F5,60 (concentration) = 11.9, P < 0.0001, m = 521.7; F5,60
(interaction toxin x concentration) = 10.1, P < 0.0001, m = 443.7) (n = 6). PSI caused a 26.6 ±
2.2% decrease in cell viability compared to vehicle-treated cells. Co-incubation of PSI with
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coenzyme Q10 (117 µM), creatine (25 mM), nicotine (1 µM), deprenyl (10 µM) and salicylic
acid (10 mM) led to a 16.2 ± 2.9%, 24.4 ± 3.5%, 24.5 ± 1.9%, 37.1 ± 2.1% and 16.5 ± 5.2%
increase in cell viability, respectively (all P < 0.001, n = 6) (Fig. 3.2c). Caffeine (140 µM) had
no significant effect on the decrease in cell viability caused by PSI. There was a significant
effect of neuroprotective agents on rotenone-induced decreases in cell viability compared to
rotenone treatment alone (F1,60 (toxin) = 531.1, P < 0.0001, m = 31590; F5,60 (concentration) =
18.1, P < 0.0001, m = 1074; F5,60 (interaction toxin x concentration) = 84.6, P < 0.0001, m =
5029) (n = 6). Following rotenone treatment there was a 37.6 ± 2.7% reduction of cell viability
compared to vehicle-treated cells. Coenzyme Q10 (117 µM), caffeine (140 µM), creatine (25
mM), nicotine (1 µM) and deprenyl (10 µM) resulted in a 53.2 ± 4.2%, 75.7 ± 2.1%, 63.4 ±
3.1%, 12.2 ± 3.7% and 73.9 ± 3.1% increase in cell viability respectively, compared to rotenone
treatment alone (all P < 0.001, except nicotine P < 0.05, n = 6) (Fig. 3.2d). Salicylic acid (10
mM) had no effect on the decrease in cell viability caused by rotenone.
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Figure 3.2. Effect of putative neuroprotective agents on toxin-induced decreases in cell
viability. Dopamine hydrochloride (30 µM), naphthazarin (2.17 µM), PSI (80 µM) or rotenone
(40 µM) were added to SH-SY5Y cells. Neuroprotective agents were added immediately prior to
toxins and incubated with cells for 24 hours. Data represent average cell viability as percent
control ± SEM of six independent experiments. * P < 0.05, *** P < 0.001 compared to untreated
control (two-way ANOVA with Bonferroni post-hoc test). (a) Coenzyme Q10, creatine, nicotine
and salicylic acid had significant protective effects compared to dopamine treatment alone. (b)
Reduced cell viability caused by naphthazarin was significantly attenuated by coenzyme Q10
and salicylic acid. (c) Coenzyme Q10, creatine, nicotine, deprenyl and salicylic acid had
significant protective effects compared to PSI treatment alone. (d). Rotenone-induced decreases
in cell viability were negated by coenzyme Q10, caffeine, creatine, nicotine and deprenyl.
83
a
Mµ
Coenz
yme Q
10 11
7 Mµ
Caffein
e 140
Creatin
e 25 m
M Mµ
Nicotin
e 1 Mµ
Depren
yl 10
Salicy
lic A
cid 10
mM
0
20
40
60
80
Vehicle + DopamineTreatment + Dopamine
*** ***
***
*
Cel
l Via
bilit
y (%
Con
trol
)
84
b
Mµ
Coenz
yme Q
10 11
7 Mµ
Caffein
e 140
Creatin
e 25 m
M Mµ
Nicotin
e 1 Mµ
Depren
yl 10
Salicy
lic A
cid 10
mM
0
20
40
60
80
100
Vehicle + NaphthazarinTreatment + Naphthazarin
***
***C
ell V
iabi
lity
(% C
ontr
ol)
85
c
Mµ
Coenz
yme Q
10 11
7 Mµ
Caffein
e 140
Creatin
e 25 m
M Mµ
Nicotin
e 1 Mµ
Depren
yl 10
Salicy
lic A
cid 10
mM
0
50
100
150
Vehicle + PSITreatment + PSI
****** *** ***
***
Cel
l Via
bilit
y (%
Con
trol
)
86
d
Mµ
Coenz
yme Q
10 11
7 Mµ
Caffein
e 140
Creatin
e 25 m
M Mµ
Nicotin
e 1 Mµ
Depren
yl 10
Salicy
lic A
cid 10
mM
0
50
100
150
Vehicle + RotenoneTreatment + Rotenone
*********
*
***C
ell V
iabi
lity
(% C
ontr
ol)
87
It is possible that the apparent neuroprotective effects were caused by the compounds increasing
cell proliferation. To determine whether this was the case, the potential neuroprotective
compounds were incubated with SH-SY5Y cells alone, i.e. in the absence of toxins for 24 hours,
and their effect on cell viability was assessed using alamar blue. ANOVA showed a significant
effect of compound on cell viability. Dunnett’s multiple comparisons test showed that there was
a significant effect of nicotine compared to vehicle. Nicotine increased cell viability by 13.0 ±
2.4% compared to vehicle (P < 0.01, n = 6) (Fig. 3.3), indicating that nicotine has a mild
proliferative effect in SH-SY5Y cells. Coenzyme Q10, caffeine, creatine, deprenyl and salicylic
acid had no effect on cell viability compared to vehicle.
88
Figure 3.3. Effect of putative neuroprotective compounds on viability in SH-SY5Y cells.
SH-SY5Y cells were treated with putative neuroprotective compounds for 24 hours in the
absence of toxins. Nicotine caused an increase in cell viability, while there was no effect of any
other agent on cell viability (one-way ANOVA with Dunnett’s multiple comparisons post hoc).
Data represent average cell viability as percent control ± SEM (n = 6). ** P < 0.01, compared to
untreated control.
89
Vehicl
e Mµ
Coenz
yme Q
10 11
7 Mµ
Caffein
e 140
Creatin
e 25 m
M Mµ
Nicotin
e 1 Mµ
Depren
yl 10
Salicy
lic A
cid 10
mM
0
20
40
60
80
100
120 **C
ell V
iabi
lity
(% C
ontr
ol)
90
3.4 Discussion
Here we demonstrate that exposure of SH-SY5Y cells to different toxins that mimic cell death
mechanisms associated with PD is a valid assay for testing potential disease modifying agents.
Coenzyme Q10 was chosen as one of the 12 putative neuroprotective agents for clinical trials, by
the NINDS-funded CINAPS group. This decision was made based on studies demonstrating that
coenzyme Q10 is neuroprotective, both in vitro and in vivo (Cleren et al., 2008; Moon et al.,
2005; Somayajulu-Nitu et al., 2009). Clinical trials showed that administration of high doses of
coenzyme Q10 to parkinsonian patients in the early stages of the disease significantly decreased
functional decline, as determined by the period of time before patients were required to take L-
dopa to control symptoms, suggesting that coenzyme Q10 slows disease progression (Shults et
al., 2002). In the current study, coenzyme Q10 was the most effective potential neuroprotective
agent tested. Coenzyme Q10 effectively protected against dysfunction of the mitochondria,
proteasome, lysosome and dopamine. The neuroprotective actions of coenzyme Q10 are thought
to be mediated by several mechanisms, which may explain the ability to protect against all four
toxins (Ernster and Dallner, 1995; Forsmark-Andrée et al., 1997). However, the primary
neuroprotective actions of coenzyme Q10 are on oxidative phosphorylation of the mitochondria,
where it transfers electrons from complex 1 and 2, to complex 3, thus facilitating ATP generation
(Schapira, 2006). In addition to this effect on mitochondrial function, coenzyme Q10-induced
increases in ATP production enables increased UPS function, since ATP is required for ubiquitin
conjugation to mis-folded proteins and opening of the proteasome channel for protein
degradation (Ciechanover, 2005). Furthermore, the reduced form of coenzyme Q10 is a strong
antioxidant which enables the effective removal of free radicals from mitochondria (Matthews et
91
al., 1998). This in turn, may eliminate the toxic effects of free radicals produced by dopamine
metabolism and lysosomal destabilization.
To further evaluate the efficacy of this cell assay as a predictor of potential disease modifying
agents for PD, we also evaluated the ability of four other compounds that were chosen by the
CINAPS group: caffeine, creatine, nicotine and the MAO-B inhibitor deprenyl, to prevent
dopamine, naphthazarin, PSI and rotenone-induced toxicity in SH-SY5Y cells. Both creatine
and deprenyl have been shown to decrease cell death in animal models of PD (Hara et al., 2006;
Kragten et al., 1998; Yang et al., 2009). Initial clinical trials suggested that caffeine, creatine,
and deprenyl may delay the progression of parkinsonian symptoms, however, further studies
proved that none of these compounds were effective disease modifying agents (Bender et al.,
2006; Suchowersky et al., 2006; Simon et al., 2008). In this study, caffeine was only protective
against rotenone, having no significant effect on dopamine, naphthazarin and PSI-induced
decreases in cell viability. Creatine and deprenyl afforded significant protection against
dopamine-induced oxidative stress, as well as toxicity caused by mitochondria and proteasome
inhibition, however, neither had any significant effect on naphthazarin-induced decreases in cell
viability. Thus, the current studies suggest that caffeine, creatine and deprenyl were not effective
disease modifying agents in parkinsonian patients because they do not protect cells from all
forms of sub-cellular dysfunction associated with PD such as lysosome dysfunction.
Nicotine protected against dopamine, rotenone and PSI-induced toxicity, having no effect on
naphthazarin. While nicotine was chosen by the CINAPS group as a useful neuroprotective
agent for parkinsonian patients, to date, clinical trials have not been conducted on this
compound. The results from this study suggest that it would not be a good candidate as a disease
modifying agent for patients with PD.
92
Previous studies have shown that both mitochondria and lysosome inhibition leads to the
increased presence of reactive oxygen species and oxidatively modified proteins within cells, and
that salicylic acid acts as a free radical scavenger, resulting in neuroprotection against such
insults (Kataoka et al., 1997; Kiffin et al., 2004; Testa et al., 2005). In addition, it has also been
shown that salicylic acid blocks the neurotoxic effect of MPTP in mice (Ferger et al., 1999;
Mohanakumar et al., 2000). The potential of salicylic acid as a disease modifying agent has not
been verified in the clinic however. Given that the current cell assay appears to be a good
predictor of the neuroprotective potential of agents to treat PD, we evaluated whether salicylic
acid may be such a candidate. Our findings that salicylic acid is effective in protecting against
cellular toxicity induced by dopamine, naphthazarin and PSI, but not rotenone suggests that this
would not be a useful disease modifying therapy for patients with PD.
In this study, we have shown that there is a direct correlation between the efficacy of disease
modifying agents in the clinic for the treatment of PD and the ability of these compounds to
protect cells against a battery of toxins that recapitulate cell death mechanisms associated with
the pathology of this disease. Thus, assessment of the ability of compounds to protect against a
battery of toxins in SH-SY5Y cells represents a simple, rapid, reliable and cost effective method
for evaluating their potential as neuroprotective agents in the treatment of PD. We believe that
using such an assay as a first step to assess purported disease modifying agents will reduce the
time taken for such agents to reach the clinic, as well as increasing the success of clinical trials.
We predict that the most effective agents will be those that protect against the multiple cellular
dysfunctions linked with Parkinson’s pathology.
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Chapter 4
Effect of Over-Expression of WT and Mutant LRRK2 on Mitochondrial Dynamics
94
4 Effect of Over-Expression of WT and Mutant LRRK2 on Mitochondrial Dynamics
4.1 Introduction
Mutations in LRRK2 are responsible for the majority of familial and sporadic cases of PD (Mata
et al., 2006). There are numerous mutant variants of LRRK2; however, G2019S mutations are
the most prevalent in familial PD and in familial cases that were believed to be sporadic (Di
Fonzo et al., 2005; Farrer et al., 2005; Gilks et al., 2005). LRRK2 is a member of the ROCO
family of proteins that contains a Roc GTPase protein domain and kinase domain (Kett and
Dauer, 2012). The LRRK2 kinase domain is believed to be responsible for most of the protein’s
function, while the GTPase domain is less involved in mediating its function (Lee et al., 2012).
Interestingly, studies reveal the activity of the kinase domain is self-regulated by the GTPase
domain (Smith et al., 2006; Ito et al., 2007). These sites are flanked by multiple domains that
allow for numerous protein-protein interactions (Mata et al., 2006). The normal function of
LRRK2 is largely unknown, but has been implicated in neurite outgrowth, autophagy and
mitochondrial dynamics. Transgenic mice expressing mutant G2019S have impeded neurite
outgrowth (Parisiadou et al., 2009). Moreover, neurite shortening is associated with
dysfunctional autophagic processes in neuroblastoma cells (Plowey et al., 2008). Interestingly,
patients with G2019S mutations exhibited impaired mitochondrial function and reduced overall
intracellular ATP levels (Mortiboys et al., 2010). This Chapter is focused on determination of
the role of LRRK2 in the control of mitochondrial dynamics, in particular, fission and fusion.
Mitochondria undergo migration and trafficking, as well as fission and fusion to maintain their
energtic homeostasis and reduce mitochondrial damage; also to maintain quality control of
95
mitochondrial proteins. Fission and fusion are of paramount importance to mitochondrial
function. Fission contributes to the distribution of mitochondria in response to localized ATP
demands, while fusion facilitates mtDNA exchange to rescue damaged mitochondria (Otera and
Mihara, 2011). Inhibition of fission machinery prevents autophagy of mitochondria and
promotes oxidation of mitochondrial proteins (Twig et al., 2008). Furthermore, inhibition of
mitochondrial fusion proteins leads to dysfunctional membrane potential and aberrant cellular
respiration (Olichon et al., 2003; Chen et al., 2005). These studies demonstrate the importance
of mitochondrial dynamics, not only for maintaining mitochondrial integrity, but also with
respect to the entire cell.
Alterations to mitochondrial dynamics have frequently been implicated in neurodegenerative
diseases (Baloh et al., 2007). Mutations in Mfn1 and Opa1 fusion proteins cause Charcot-Marie-
Tooth neuropathy and optic atrophy (Alexander et al., 2000; Zuchner et al., 2004).
Mitochondrial dysfunction is common in PD pathology; however while abnormalities in
mitochondrial dynamics are not believed to be responsible for the pathology of the disease,
mitochondrial dynamics has been shown to be dysfunctional in models of PD, suggesting that
while abnormal mitochondrial dynamics are not one of the initiating factors underlying the
pathology of PD, some of the known initiating factors that do trigger PD pathology do affect
mitochondrial dynamics, which probably exacerbates cell death. Nigral neurons have high
energy demands which make mitochondria critical to their survival (Vila et al., 2008). In
addition, mitochondrial dynamics are essential for distributing mitochondria across the long
processes of nigral neurons (Schon and Przedborski, 2011). Studies utilizing genetic and toxin
cell models of PD demonstrate the importance of mitochondrial dynamics in PD pathology.
Inhibition of mitochondrial fusion caused by α-synuclein is rescued by PINK-1, Parkin and DJ-1
overexpression (Kamp et al., 2010).
96
Large GTPases regulate mitochondrial fission and fusion. Such proteins include Drp1 and Fis1
which mediate fission, and Mfn1, Mfn2 and Opa1 that regulate fusion. Fission is initiated when
cytosolic Drp1 binds to Fis1. Once bound to Fis1, Drp1 forms a multiple Drp1 complex which
leads to scission of the outer membrane (Westermann, 2010). Currently the mechanisms
controlling inner membrane division are unknown. Mfn1 and Mfn2 are transmembrane proteins
that tether opposing mitochondria during fusion (Otera and Mihara, 2011). Tethering brings the
mitochondria together to allow for fusion of the outer membrane (Otera and Mihara, 2011). The
mechanisms of inner membrane fusion is unclear, however Opa1 is believed to mediate this
process (Westermann, 2010). Altered mitochondrial fission and fusion are generally caused by
changes to fission and fusion proteins. Indeed, MPTP and rotenone, toxins used in models of
PD, are implicated in Drp-1 dependent mitochondrial fragmentation (Barsoum et al., 2006).
Mitochondria are important sources of dysfunctional mechanisms underlying familial and
idiopathic PD. Various toxins mediate their effects by inhibiting mitochondrial function, while
many mutations in genes linked with PD alter mitochondrial dynamics, however the effect of
LRRK2 on mitochondria is unknown (Fig. 4.1). Given that various genetic mutations and toxins
are implicated in mitochondrial dysfunction, and that LRRK2 mutations are common among PD
patients, I hypothesized that LRRK2 may alter fission and fusion, which causes mitochondrial
dysfunction linked with PD. The studies described in this chapter examine the effect of wild-
type and mutant LRRK2 (G2019S) on mitochondrial fission and fusion.
97
Figure 4.1. Genetic mutations and toxins that affect mitochondrial processes. Mutations in
genes such as α-synuclein, DJ-1, Parkin and PINK1 have been implicated in the dysregulation of
mitochondrial dynamics. Environmental toxins such as rotenone block mitochondrial function.
Similarly, experimental toxins such as naphthazarin and PSI have been shown to block
mitochondrial function by first inhibiting the function of another organelle. The role of LRRK2
in mitochondrial dynamics and function is currently unknown.
98
Mitochondrial Dynamics Mitochondrial Functionα-synuclein DJ-1 Parkin PINK1 Naphthazarin PSI Rotenone
??? LRRK2 ???
99
4.2 Materials and Methods
4.2.1 Constructs
The pOCT-dsRed2 and pCMV-mitoGFP (kindly donated by Dr. Heidi McBride and Dr. Linda
Mills, respectively) constructs have CMV promoters which drive the expression of the
mitochondrially targeted fluorescent proteins. The pcDNA3.1-3xFLAG-LRRK2 and pcDNA3.1-
3xFLAG-G2019S-LRRK2 (kindly donated by Dr. Christopher Ross) constructs contain a CMV
promoter which drives the expression of the transgene. The 3xFLAG sequence is upstream of
the LRRK2/G2019S sequence. pcDNA3.1-3xFLAG-LRRK2 and pcDNA3.1-3xFLAG-G2019S-
LRRK2 have the same sequence except GGC was replaced by AGC at amino acid 2019. The
pcDNA3.1 empty vector was generated from the excision of the 3xFLAG-LRRK2 sequence at
Xho1 sites. The ptracer-3xFLAG-LRRK2-mCherry and ptracer-3xFLAG-G2019S-LRRK2-
mCherry constructs were generated from pcDNA3.1-3xFLAG-LRRK2, pcDNA3.1-3xFLAG-
G2019S-LRRK2, ptracer-CMV2, and pmCherry-C1 (Clontech, USA). The mCherry sequence
was excised, blunted and inserted into the Pml1 sites of ptracer-CMV2 so that expression of
mCherry was driven by the EF1 promoter. The LRRK2 or G2019S-LRRK2 sequence was then
ligated into the Kpn1 and Not1 sites of ptracer-CMV2-mCherry. LRRK2 and G2019S-LRRK2
was positioned upstream of the mCherry sequence and its expression was regulated by the
CMV2 promoter.
4.2.2 Cell culture
Human dopaminergic neuroblastoma SH-SY5Y cells (ATCC, USA) (P10-P25) were stored in
liquid nitrogen (-200 oC), rapidly thawed and grown in DMEM (consisting of 6400 mg/L NaCl,
3700 mg/L NaHCO3, 400 mg/L KCl and 584 mg/L L-glutamine) supplemented with 5% bovine
100
calf serum in a sterile humidified chamber (37 oC, 5% CO2, 95% O2) (Incubator: MCO-20AIC,
Sanyo, USA) until confluent. Cells were passaged using 0.1% trypsin for 5 min, then pelleted by
centrifuging at 340xg for 5 min (Allegra 6R Centrifuge, Beckman Coulter, USA).
4.2.3 SDS-PAGE followed by Western blotting
SH-SY5Y cells were transfected with pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-3xFLAG-
G2019S-LRRK2 (5µg). After 48 hrs, cells were washed twice with ice-cold PBSx1 and scraped
from 100 mm plates with Laemmli buffer. Samples were lysed for 15 minutes in water (95 oC),
and protein concentrations determined using the Bradford method. Protein samples (10-20µg)
were loaded onto gels, and SDS-PAGE followed by Western blotting was carried out.
Nitrocellulose blots were blocked in 5% non-fat powdered milk (60 min) and incubated with
antibodies against β-actin (1:1000 µl) and FLAG (1:1000 µl) (both Sigma-Aldrich, Canada)
overnight (4oC). Following 5 washes in 0.5% Triton-X in PBSx1, mouse (1:5000 µl) HRP-
conjugated secondary antibodies (Jackson Immunoresearch, USA) were incubated at room
temperature (60 min) in a 1% non-fat powdered milk/TTBS (0.1% Tween-20) solution. Protein
levels were detected using enhanced chemiluminescence (ECL Western Blotting Substrate,
Pierce), then imaged (SRX-101A, Konica Minolta). Three replicates were produced for each
condition.
4.2.4 Expression profile of constructs
SH-SY5Y cells were transfected with pcDNA3.1, pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-
3xFLAG-G2019S-LRRK2 (all 8.6 µg) 24 hours after plating. Cells were fixed 8, 12, 24, 48 and
72 hours after transfection using 4% PFA, permeabilized with 0.1% Trion-X plus 100 mM
glycine, and blocked non-specific proteins with 5% bovine calf serum. Mouse anti-FLAG
(Sigma-Aldrich, Canada) was incubated with cells overnight at 4oC, which was then probed with
101
anti-mouse cy2 (Jackson Immunoresearch, USA). In a separate experiment, SH-SY5Y cells
were transfected with ptracer-mCherry, ptracer-3xFLAG-LRRK2-mCherry or ptracer-3xFLAG-
G2019S-LRRK2-mCherry (all 5 µg) 24 hours after plating. Images were obtained 8, 12, 24, 48
and 72 hours after transfection. Images were captured using an epifluorescent microscope with
attached Apotome grid with 40x oil immersion objective (Axiovert 200, Carl Zeiss, Canada) for
fixed samples or with a 20x long distance objective for live imaging. One hundred cells were
counted for each of four replicates that were positively stained. Data are expressed as mean
number of positive cells ± SEM.
4.2.5 Mitochondrial morphology assay
SH-SY5Y cells were plated on glass coverslips in a 6 well dish 24 hours prior to transfection.
Cells were transiently transfected with pmCherry (0.768 µg), pCMV-mtGFP (1.86 µg) and
pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-3xFLAG-G2019S-LRRK2 (both 8.6 µg). After 48
hours, cells were fixed with 4% parformaldehyde, permeabilized with 0.1% Triton-X plus 100
mM glycine and incubated with 5% bovine calf serum for 1 hour. In order to probe for 3xFLAG,
anti-mouse FLAG primary antibody was incubated at 4 oC overnight, followed by incubation
with anti-mouse cy5 secondary antibody (Jackson Immunoresearch, USA). Cells were imaged
using an epifluorescent microscope equipped with an Apotome grid with a 63x objective. To
determine the relative amounts of mitochondria that were fragmented, elongated or clustered,
one hundred cells from four independent experiments were analyzed in a blinded fashion.
Mitochondria were categorized as fragmented, elongated or clustered if 50% of the total
mitochondrial population in a cell displayed one morphology type. Data are expressed as mean
number of cells having a particular mitochondrial morphology ± SEM.
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4.2.6 Tetramethylrhodamine ethyl ester perchlorate (TMRE) assay SH-SY5Y cells were cultured on glass coverslips in a 6 well dish 24 hours prior to transfection
with pTag-BFP-C (0.78 µg) (Evrogen, USA), pcmv-mtGFP (1.86 µg) and pcDNA3.1,
pCDNA3.1-3xFLAG-LRRK2 or pCDNA3.1-3xFLAG-G2019S-LRRK2 (all 8.6 µg). On the
second day after transfection, cells were labelled with 20 nM TMRE (Invitrogen, USA) for 20
min in DMEM. TMRE is a lipophillic cationic dye that binds to the inner and outer portions of
the mitochondrial inner membrane upon proportion of membrane potential (Scaduto and
Grotyohann, 1999). Fluorescence intensity is reduced as a consequence of depolarisation in
membrane potential. Coverslips were placed in a live imaging chamber with imaging buffer
(116 mM NaCl, 5.4 mM KCl, 0.4 mM MgSO4, 20 mM HEPES, 0.9 mM Na2HPO4, 1.2 mM
CaCl2, 10 mM glucose, 5 mM pyruvate, pH 7.4) and imaged on an epifluorescent microscope
with Apotome with a 40x oil immersion objective. The fluorescence intensity of 30-50
randomly chosen cells from each of four independent experiments was measured using ZEN
2009 (Carl Zeiss, Canada). Then the average fluorescence intensity of all four independent
experiments was determined. Data are expressed as mean TMRE intensity ± SEM.
4.2.7 Polyethylene glycol (PEG)-induced cellular fusion assay
SH-SY5Y cells were plated in 6 well plates 24 hours prior to transfection. One well of cells was
transfected with pcmv-mtGFP (5.0 µg) and pcDNA3.1 (8.6 µg), or pcmv-mtGFP (5.0 µg) and
pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-3xFLAG-G2019S-LRRK2 (both 8.6 ug). Another
well of cells was transfected with pOCT-dsRed2 (2.5 µg) and pcDNA3.1, or pOCT-dsRed2 (2.5
µg) and pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-3xFLAG-G2019S-LRRK2 (both 8.6 µg).
After 8 hrs, cells from each well were co-plated (1:1 ratio) on coverslips and cultured for 16 hrs
in DMEM. Cycloheximide (40 µg/ml), an inhibitor of protein synthesis, was incubated with the
cells for 30 min. Cells were washed with PBSx1 (w/ 40 µg/ml cycloheximide) and incubated
103
with a 50% w/v of PEG 3350 in PBSx1 for 90 sec. PEG induces membrane fusion between cells
by destabilizing lipid bilayers and neutralizing their charge gradient (Boni et al., 1984). Each
well was gently washed four times with PBSx1 (w/ 40 µg/ml cycloheximide). DMEM was
added to each well, and the cells were cultured for an additional 5 hrs prior to fixing with 4%
paraformaldehyde. Mouse anti-FLAG was incubated with cells overnight at 4 oC and incubated
with cy5 for 1 hr at room temperature. Images were acquired using a laser scanning confocal
microscope (Zeiss) with a 100x oil immersion objective. Twenty to forty cells from three
independent experiments were measured blindly for Pearson’s correlation coefficient (R) using
ZEN 2009. Pearson’s correlation coefficient was converted to R2 then to a percentage that
indicates the rate of mitochondrial fusion. Data are expressed as mean percent mitochondrial
fusion ± SEM.
4.2.8 Mitochondrial fission assay
SH-SY5Y cells were plated on glass coverslips in 6 well plates 24 hours before transfection.
Cells were transfected with pcmv-mtGFP (5 µg), or pcmv-mtGFP (5 µg) and ptracer-3xFLAG-
mCherry (8.6 µg), or pcmv-mtGFP (5 µg) and ptracer-3xFLAG-LRRK2-mCherry or ptracer-
3xFLAG-G2019S-mCherry (both 8.6 µg) using Lipofectamine LTX. After 24 hours, coverslips
were placed in a live imaging chamber with fresh DMEM. Images were acquired using a
spinning disk confocal microscope (WaveFX-X1, Quorum, Canada) with a 63x oil immersion
objective equipped with a temperature and CO2 controlled chamber. Images of five cells were
taken from five stage positions at each time point in four independent experiments. Z-stacks
consisting of 0.5 µm slices were acquired every 30 seconds over a 20 min period. Individual
slices were combined to create 3-D projections using Volocity 6.0.1 (Perkin Elmer, USA).
Images from each stage position were skeletonised using Metamorph 7.7.0.0 (Molecular
104
Devices, USA). The number of mitochondria in each skeletonized image was counted using
Metamorph 7.7.0.0. Data are expressed as the number of mitochondria per 30 seconds.
4.2.9 Statistical analysis
A different cell passage was used for each replicate (n = 1). A minimum of three replicates were
used for each experiment. All data were analyzed used GraphPad Prism Version 5 (GraphPad
Software Inc, USA). The statistical tests used include Student’s t-test and one-way ANOVA’s
with associated post-tests. Significance was assigned when P < 0.05.
4.3 Results
4.3.1 Generation of ptracer-3xFLAG-LRRK2-mCherry construct
A variant of the LRRK2 construct with a fluorescent tag was required for live imaging
experiments. Thus, a construct was created which drives the expression of LRRK2 or G2019S-
LRRK2 and mCherry from different promoters within the same construct. The mCherry
sequence was first inserted into the Pml1 sites of ptracer-CMV2 (Fig. 4.2a). Restriction digest at
Bsrg1 and Pml1 sites show the insertion of the mCherry sequence in the correct location and
orientation (Fig. 4.2b). Digest at Bsrg1 and EcoR1 sites produced a 3.5 kb (ptracer sequence)
and a 2.5 kb (mCherry sequence) band. The ptracer-mCherry (5 µg) construct was transiently
transfected into SH-SY5Y cells to test its functionality (Fig. 4.2c). SH-SY5Y cells expressed
mCherry 48 hours after transfection. The 3xFLAG-LRRK2 or 3xFLAG-G2019S-LRRK2
sequence was inserted into ptracer-mCherry at Kpn1 and Not1 sites (Fig. 4.3a). Restriction
digest at Kpn1 and Not1 sites show that 3xFLAG-LRRK2 or 3xFLAG-G2019S-LRRK2
sequences are in the correct location and orientation (Fig. 4.3b). Digest at Kpn1 and Not1 sites
produced an 8 kb (3xFLAG-LRRK2/3xFLAG-G2019S-LRRK2 sequence) and 6 kb (ptracer-
mCherry sequence) band. The ptracer-3xFLAG-LRRK2-mCherry or ptracer-3xFLAG-G2019S-
105
LRRK2-mCherry constructs were transiently transfected into SH-SY5Y cells and their
associated proteins were expressed after 48 hours (Fig. 4.3c). Western blotting also revealed the
expression of the proteins in SH-SY5Y cells (Fig. 4.3d).
106
Figure 4.2. Generation of ptracer-mCherry construct. (a) The mCherry sequence was
inserted into Pml1 restriction sites and driven by the EF1 promoter region. Ampicillin resistance
(AmpR) is conferred to bacteria containing ptracer-mCherry. (b) Bsrg1 and EcoR1 restriction
enzymes were used to determine the correct orientation of the insert. The expected DNA bands
were approximately 3.5 kb and 2.5 kb if mCherry was inserted in the correct orientation. The 2.5
kb band contains the mCherry sequence. (c) Detection of mCherry in SH-SY5Y cell using live
imaging. Red fluorescence indicates mCherry expression driven by ptracer-mCherry construct.
Scale bar = 20 µm.
107
a
108
2.5 kb3.5 kb
b
c
109
Figure 4.3. Generation of ptracer-3xFLAG-LRRK 2-mCherry construct. (a) The 3xFLAG-
LRRK2 or 3xFLAG-G2019S-LRRK2 sequence was inserted into the Kpn1 and Not1 restriction
sites. Bacteria containing ptracer-3xFLAG-LRRK2-mCherry has ampicillin resistance (AmpR).
(b) Restriction digest at Kpn1 and Not1 restriction sites to determine the orientation and location
of the insert. An expected DNA band size of 8 kb indicates the correct orientation of the LRRK2
sequence. (c) Detection of 3xFLAG-LRRK2-mCherry or 3xFLAG-G2019S-LRRK2-mCherry in
SH-SY5Y cells using live imaging. Red fluorescence indicates protein expression driven by
ptracer-3xFLAG-LRRK2-mCherry. Scale bars = 20 µm. (d) Detection of 3xFLAG-LRRK2-
mCherry or 3xFLAG-G2019S-LRRK2-mCherry in SH-SY5Y cells using SDS-PAGE followed
by Western blotting. The full length LRRK2 protein is approximately 250 kDa. – CNT: naive
cells; + CNT: cells transfected with pcDNA3.1.
110
a
a
111
250 kDa
3xFLAG-G2019S-mCherry 3xFLAG-LRRK2-mCherry
8 kb6 kb
c
d
b
112
4.3.2 Expression of LRRK2 in SH-SY5Y cells
Since protein expression varies among cell types, it was first necessary to determine if wild-type
LRRK2 and G2019S-LRRK2 can be expressed in the neuroblastoma cell line SH-SY5Y.
Western blotting was used to detect the expression of these proteins 48 hours after transfection.
Wild-type LRRK2 and G2019S-LRRK2 were highly expressed compared to non-transfected and
empty vector controls (Fig. 4.4). Given that large proteins such as LRRK2 take longer times to
express, and different construct promoters have variable strengths, it was necessary to determine
the protein expression profile over a time course that will be used for future experiments. Here,
SH-SY5Y cells were transfected with wild-type LRRK2 and G2019S-LRRK2 constructs tagged
with 3xFLAG. Each protein was expressed in the cytoplasm of SH-SY5Y cells over the entire
time course (Fig. 4.5a). Wild-type and G2019S-LRRK2 expression was significantly increased
from 8 hours to 24 hours (P < 0.001) (Fig. 4.5b). At 8, 12, 24, and 48 hours, there was a 4.50 ±
0.87, 6.75 ± 0.85, 10.00 ± 1.08, and 14.50 ± 2.63 (P < 0.01, P < 0.001, P < 0.001, P < 0.001 and
P < 0.05, respectively) increase in cells positively stained with LRRK2. While cells expressing
G2019S-LRRK2 increased by 6.25 ± 0.85, 5.25 ± 0.85, 8.50 ± 2.10, and 13.50 ± 0.65 (P < 0.001,
P < 0.01, P < 0.001, P < 0.001 and P < 0.05, respectively) at 8, 12, 24, and 48 hours,
respectively. SH-SY5Y cells expressing wild-type LRRK2 and G2019S-LRRK2 tagged to
mCherry increased over a 24 to 48 hour time course (P < 0.001) (Fig. 4.6). Cells expressing
wild-type LRRK2 tagged with mCherry significantly increased by 7.50 ± 1.26 and 6.00 ± 0.50 at
24 and 48 hours, respectively (both P < 0.001). The number of SH-SY5Y cells expressing
G2019S-LRRK2 also increased by 7.75 ± 1.00 at 24 hours and 7.5 ± 0.76 at 48 hours post-
transfection (both P < 0.001).
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Figure 4.4. Expression of wild-type LRRK2 and G2019S-LRRK2 in SH-SY5Y cells. SH-
SY5Y cells were transfected with pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-3xFLAG-
G2019S-LRRK2 (both 5 µg). Cells were lysed 48 hours after transfection and subjected to SDS-
PAGE followed by Western blotting. Wild-type LRRK2 and G2019S-LRRK2 expression were
determined by measuring 3xFLAG expression. Expression of wild-type LRRK2 and G2019S-
LRRK2 proteins are shown as bands with mass of 250 kDa. β-actin serves as a loading control.
CNT: naive cells; EV: cells transfected with pcDNA3.1; WT: wild-type LRRK2; G2019S:
G2019S-LRRK2.
114
WTCNT EV
42 kDa
250 kDa
β-actin
3xFLAG
β-actin 42 kDa
250 kDa3xFLAG
G2019SCNT EV
115
Figure 4.5. Wild-type LRRK2 and mutant G2019S-LRRK2 expression time course. SH-
SY5Y cells were transfected with pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-3xFLAG-
G2019S-LRRK2 (both 8.6 µg) and were fixed 8, 12, 24, 48 and 72 hrs after transfection. Wild-
type LRRK2 and G2019S-LRRK2 expression was probed using 3xFLAG. (a) Wild-type LRRK2
and G2019S- LRRK2 were expressed in the soma and processes of SH-SY5Y cells. Scale bars =
20 µm. (b) Wild-type LRRK2 and G2019S-LRRK2 expression at 8, 12, 24, 48 and 72 hrs after
transfection. One-way ANOVA with Tukey’s multiple comparison test were performed. * P <
0.05, ** P < 0.01, *** P < 0.001 (WT), $ P < 0.05, $$ P < 0.01, $$$ P < 0.001 (G2019S).
Overall effect of LRRK2 treatment: F4,3 = 0.96, G2019S treatment: F 4,3 = 0.50. Control: naive
cells; empty vector: cells transfected with pcDNA3.1; WT: wild-type LRRK2; G2019S:
G2019S-LRRK2.
116
Con
trol
Empt
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ctor
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G20
19S
8 Hrs 12 Hrs 24 Hrs 48 Hrs 72 Hrsa
117
b
0 10 20 30 40 50 60 70 800
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Empty Vector
*****
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*$$$$$
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$
Time (Hrs)
Num
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Cel
ls
118
Figure 4.6. Expression of mCherry tagged wild-type LRRK2 and G2019S-LRRK2 in SH-
SY5Y cells. SH-SY5Y cells were transfected with ptracer-3xFLAG-LRRK2-mCherry or ptracer-
3xFLAG-G2019S-LRRK2-mCherry (both 5 µg) and were fixed 8, 12, 24 and 48 hours later.
The number of cells expressing wild-type LRRK2 and G2019S-LRRK2 were counted 8, 12, 24
and 48 hours after transfection. Two-way ANOVA with Bonferroni’s multiple comparison test
were performed. *** P < 0.001 (WT), $$$ P < 0.001 (G2019S), &&& P < 0.001 (vector).
Overall effect of treatment: F3,48 = 115.5. Control: naive cells; empty vector: cells transfected
with ptracer-mCherry; WT: wild-type LRRK2; G2019S: G2019S-LRRK2.
119
0 10 20 30 40 50 600
10
20
30
40
50ControlVectorWTG2019S
*** ***$$$ $$$
&&&
&&&
Time (Hrs)
Num
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120
4.3.3 Effect of LRRK2 on mitochondrial morphology
Since familial forms of PD lead to changes in mitochondrial morphology, and LRRK2 is
localized on the outer membrane of mitochondria, the effect of wild-type LRRK2 and G2019S-
LRRK2 on mitochondrial morphology was determined. SH-SY5Y cells were triple transfected
with pmCherry, pCMV-mitoGFP and pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-3xFLAG-
G2019S-LRRK2. A triple transfection approach was used to determine the likelihood of a cell
expressing mtGFP, 3xFLAG-LRRK2 or 3xFLAG-G2019S-LRRK2. Since pmCherry had the
lowest molar ratio of the three plasmids, it is likely that one cell expresses LRRK2 if mCherry is
expressed. Control cells exhibit three types of mitochondrial morphology, clustered, fragmented
and elongated, each demonstrating a static state of mitochondrial dynamics (Fig. 4.7a). Over-
expression of wild-type LRRK2 and G2019S-LRRK2 had significant effects on mitochondrial
morphology (both P < 0.05). Wild-type LRRK2 expression led to a 14.50 ± 2.72 increase in
cells with fragmented mitochondria compared to control (P < 0.05) (Fig. 4.7b). G2019S-LRRK2
expression increased the number of cells having fragmented mitochondria by 18.75 ± 2.53 and
decreased the number of cells with elongated mitochondria by 16.00 ± 4.03 compared to control
(P < 0.001 and P < 0.05, respectively) (Fig. 4.7c). It is well known that mitochondria lose
function, and become fragmented in response to cell stress. In order to determine whether over-
expression of wild-type LRRK2 or G2019S-LRRK2 induces mitochondrial fragmentation by
activating stress response pathways, a TMRE assay was employed to assess mitochondrial
function. There was no difference in TMRE fluorescence intensity in LRRK2 and G2019S-
LRRK2 cells compared to control (P > 0.05) (Fig. 4.8a,b). Rotenone, the inhibitor of
mitochondrial complex 1, induced a significant decrease in TMRE fluorescence intensity (P <
0.05).
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Figure 4.7. Changes in mitochondrial morphology in SH-SY5Y cells. SH-SY5Y cells were
transfected with pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-3xFLAG-G2019S-LRRK2 (both
8.6 µg) and fixed 48 hours after transfection. (a) Representative fluorescent images of
mitochondria expressing mtGFP, mCherry and wild-type LRRK2 or G2019S-LRRK2, showing
SH-SY5Y cells with clustered, elongated or fragmented mitochondria. Scale bars = 10 µm. (b)
Changes in mitochondrial morphology in cells expressing wild-type LRRK2 are shown. One-
hundred cells were counted and categorized as having clustered, elongated or fragmented
mitochondria. (c) Changes in mitochondrial morphology in cells expressing mutant G2019S-
LRRK2 are shown. One-hundred cells were counted and categorized as having clustered,
elongated or fragmented mitochondria. Paired two-tailed t-test was performed. * P < 0.05, ***
P < 0.001. Overall effect of wild-type LRRK2 treatment: t3 = 0.9 (clustered), t3 = 5.3
(fragmented), t3 = 1.4 (elongated); overall effect of G2019S-LRRK2 treatment: t3 = 1.0
(clustered), t3 = 13.6 (fragmented), t3 = 4.3 (elongated). Control: naive cells; Vector: cells
transfected with pcDNA3.1; WT: wild-type LRRK2; G2019S: G2019S-LRRK2.
122
aG2019S
WT
Control
mtGFP FLAGVector
mCherry Merge
123
b
Contro
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T0
20
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ClusteredFragmented
*
Elongated
Mito
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(# o
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Contro
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G2019
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ClusteredFragmentedElongated
****
Mito
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l Mor
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(# o
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c
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Figure 4.8. Effect of wild-type LRRK2 and G2019S-LRRK2 on mitochondrial function.
SH-SY5Y cells were transfected with pcDNA3.1-3xFLAG, pcDNA3.1-3xFLAG-LRRK2 or
pcDNA3.1-3xFLAG-G2019S-LRRK2 (all 8.6 µg), then incubated with TMRE (20 nM) 48 hours
later. (a) Fluorescent images of functional and non-functional mitochondria as shown by TMRE
fluorescence. Mitochondrial morphology is revealed by mtGFP fluorescence. BFP serves as a
transfection control for wild-type LRRK2 and G2019S-LRRK2. Rotenone serves as a positive
control to show changes in TMRE fluorescence. Scale bars = 10 µm. (b) Changes in
mitochondrial function of SH-SY5Y cells expressing wild-type LRRK2 and G2019S-LRRK2 are
shown. TMRE fluorescence intensity was quantified in 30-50 cells. One-way ANOVA with
Bonferroni’s multiple comparison test. * P < 0.05. Overall effect of rotenone treatment: F 4,15 =
3.0. Control: naive cells; Empty Vector: cells transfected with pcDNA3.1; WT: wild-type
LRRK2; G2019S: G2019S-LRRK2; mtGFP: mitochondrial GFP; BFP: blue fluorescent protein.
125
Con
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Empt
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2019
Sa
TMRE mtGFP BFP Merge
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Contro
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Empty V
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Roteno
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G2019
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*
TMR
E (a
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127
4.3.4 Effect of LRRK2 on mitochondrial fusion and fission
Mitochondria are highly dynamic organelles that undergo repeated fusion and fission events.
Increased fragmentation could result from a loss of fusion which would produce many small
mitochondria instead of elongated forms. A classical fusion assay was employed to measure the
amount of fusion events that occur in the presence of wild-type LRRK2 and G2019S-LRRK2
(Fig. 4.9a). Wild-type LRRK2 and G2019S-LRRK2 expression decreased the percentage of
mitochondrial fusion (P < 0.0001). Wild-type LRRK2 and G2019S-LRRK2 reduced the
percentage of mitochondrial fusion by 15.82 ± 2.12% and 14.72 ± 2.77%, respectively (both P <
0.001) (Fig. 4.9b). Although reduced mitochondrial fusion may lead to fragmented
mitochondria, it is likely that excessive mitochondrial fission also fragments mitochondria.
Changes in the number of mitochondrial fission events were explored by utilizing live imaging
of fluorescently labeled mitochondria. Mitochondrial fission was not affected by the expression
of wild-type LRRK2 and G2019S-LRRK2 since there were no changes in the division or number
of mitochondria (P > 0.05) (Fig. 4.10).
128
Figure 4.9. Effect of wild-type LRRK2 and mutant G2019S-LRRK2 on mitochondrial
fusion. SH-SY5Y cells were transfected with pcDNA3.1-3xFLAG-LRRK2 or pcDNA3.1-
3xFLAG-G2019S-LRRK2 (both 8.6 µg). Cell fusion was induced 24 hours later and SH-SY5Y
cells were fixed 5 hours after cell fusion. (a) Laser scanning confocal images showing fused
mitochondria. Different mitochondria populations are represented by mtGFP and dsRed2. Scale
bars = 20 µm. (b) Changes in the percentage of mitochondrial fusion in wild-type LRRK2 and
G2019S-LRRK2 expressing cells are shown. The percentage of mitochondrial fusion is derived
from the amount of colocalization in 20-40 cells per replicate. One-way ANOVA with
Bonferroni’s multiple comparison test was performed. *** P < 0.001. Overall effect of LRRK2
and G2019S: F3,263 = 17.5. Control: naive cells; Empty Vector: cells transfected with
pcDNA3.1; WT: wild-type LRRK2; G2019S: G2019S-LRRK2.
129
mtGFP dsRed2 FLAG MergeC
ontro
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pty
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2019
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Figure 4.10. Effect of wild-type LRRK2 and G2019S-LRRK2 on mitochondrial fission. SH-
SY5Y cells were transfected with pcmv-mtGFP (5 µg) and ptracer-mCherry, or pcmv-mtGFP (5
µg) and ptracer-3xFLAG-LRRK2-mCherry or ptracer-3xFLAG-G2019S-mCherry (8.6 µg).
After 24 hours, cells were imaged live using a spinning disk confocal microscope. The effect of
wild-type LRRK2 and G2019S-LRRK2 on mitochondrial number was measured. One-way
ANOVA with Bonferroni’s multiple comparison test was performed. P > 0.05. Overall effect of
LRRK2 and G2019S: F3,492 = 1.03. Control: naive cells; Empty Vector: cells transfected with
ptracer-mCherry; LRRK2: wild-type LRRK2; G2019S: G2019S-LRRK2.
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0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 448
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ControlEmpty VectorLRRK2G2019S
Time (30 s)
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)
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4.4 Discussion
Regulation of mitochondrial dynamics, such as fission and fusion are of paramount importance
to cells, especially neurons that have high energy needs. Dysregulation of mitochondrial
dynamics is believed to contribute to the pathology of many neurodegenerative diseases
(Alexander et al., 2000; Zuchner et al., 2004; Trushina et al., 2012). To this end, changes in
mitochondrial dynamics were examined in an in vitro model of PD.
Aberrant mitochondrial dynamics are associated with changes in the morphology of
mitochondrial populations. Here, the morphology of mitochondria in response to over-
expression of wild-type LRRK2 and a mutant form of LRRK2, G2019S-LRRK2, was examined.
Interestingly, wild-type LRRK2 expression increased the number of fragmented mitochondria,
while G2019S-LRRK2 reduced the number of elongated mitochondria and increased the number
of fragmented mitochondria. This suggests that wild-type and mutant LRRK2 could regulate
rates of fission or fusion which alters mitochondrial morphology. These findings are in contrast
to previous studies showing an increase in elongated mitochondria in fibroblasts expressing
G2019S-LRRK2 (Mortiboys et al., 2010). This disparity may be due to the different cell type
used. Given that G2019S-LRRK2 leads to a toxic gain of function, it makes sense that over-
expression of this mutation leads to pathological changes, such as an increase in the number of
fragmented mitochondria. Moreover, this finding suggests that a pathological mechanism
involving G2019S-LRRK2 may decrease fusion or increase fission to promote these changes in
mitochondrial morphology. Indeed, studies have shown that mitochondria fragment in response
to abnormal mitochondrial dynamics caused by MPTP administration and over-expression of
mutated forms of Parkin (Lutz et al., 2009; Wang et al., 2011).
134
Changes in mitochondrial morphology could be caused by cell stress and subsequent changes in
mitochondrial function. Indeed, many studies have shown that mitochondria become fragmented
as a consequence of mitochondrial dysfunction (Barsoum et al., 2006; Twig et al., 2008). To
address this possibility I performed TMRE experiments to examine the functional state of
mitochondria following over-expression of wild-type or mutant LRRK2. These studies showed
that there is no loss of mitochondrial function in cells over-expressing wild-type LRRK2 or
G2019S-LRRK2, suggesting that a secondary cell stress pathway is not activated by LRRK2
overexpression. Moreover, mitochondrial fragmentation is not a result of cell stress, but of
altered mitochondrial dynamics. This is consistent with studies where mitochondrial dynamics
altered mitochondrial function following over-expression of DJ-1 or α-synuclein (Kamp et al.,
2010; Wang et al., 2012a). Since cell stress does not precede mitochondrial fragmentation, it is
likely that altered mitochondrial dynamics induced by wild-type LRRK2 or G2019S-LRRK2
cause fragmentation, and could potentially cause mitochondrial dysfunction at later time points.
Indeed, measurements of mitochondrial fusion were taken at time points earlier than those of the
mitochondrial morphology and TMRE experiments. It is possible if TMRE measurements were
taken at time points later than those of the mitochondrial morphology experiments,
mitochondrial dysfunction could have been observed. Thus, altered mitochondrial dynamics
may cause fragmentation which promotes cell stress eventually causing cell death.
In the experiments examining mitochondrial morphology, it was shown that more fragmented
mitochondria were present in cells over-expressing wild-type LRRK2 or G2019S-LRRK2, while
less elongated mitochondria were present in cells expressing G2019S-LRRK2. These changes in
mitochondrial morphology can be attributed to either increased fission or decreased fusion, since
each would make mitochondria more fragmented or less elongated. Studies have shown the
involvement of PD related genes such as α-synuclein in mitochondrial fusion, and LRRK2 could
135
also participate in the fusion process (Kamp et al., 2010; Xie and Chung, 2012). Both wild-type
LRRK2 and G2019S-LRRK2 expressing cells have mitochondria that appear less likely to
undergo fusion. Thus, it appears wild-type LRRK2 and G2019S-LRRK2 directly inhibit
mitochondrial fusion. This finding is supported by a study that found LRRK2 interacts with
membranous and vesicular structures such as mitochondria and vesicles (Biskup et al., 2006).
Here we see equivalent reductions of fused mitochondria following over-expression of wild-type
LRRK2 and G2019S-LRRK2. However, it remains unclear why G2019S-LRRK2 has a more
severe effect on mitochondrial morphology than wild-type LRRK2. It could be that
mitochondria take longer to fuse in the presence of G2019S-LRRK2 than wild-type LRRK2.
This is supported by experiments in stable cells which show that G2019S-LRRK2 increases the
time required for mitochondria to fuse (Wang et al., 2012b). However, the effect of G2019S-
LRRK2 on elongated mitochondria may be caused by enhanced mitochondrial fission.
In cells over-expressing G2019S-LRRK2, increased mitochondrial fission could reduce
elongated mitochondria. Live imaging of mitochondria revealed no change in mitochondrial
number, suggesting wild-type LRRK2 and G2019S-LRRK2 do not alter fission. This is
contrasted by studies that show wild-type LRRK2 and G2019S-LRRK2 interact with DLP1,
however whether altered fission occurred was not determined (Niu et al., 2012; Wang et al.,
2012b). Although DLP1 is essential for fission, it’s interaction with LRRK2 alone may not be
sufficient to induce alterations of fission rates. Indeed, Fis1 was found to be an imperative
component of the complex required for mitochondrial fission in mammalian cells (James et al.,
2003; Stojanovski et al., 2004). Given that mitochondrial fragmentation was observed 48 hours
after transfection in the mitochondrial morphology experiments, if mitochondrial fission was
measured at a similar time point, a significant change in mitochondrial fission may have been
observed.
136
These experiments suggest wild-type LRRK2 plays an important role in mitochondrial fusion
and may play an equally important role in fission, and that G2019S-LRRK2 may further
exacerbate the effect of wild-type LRRK2 on fusion and fission which could potentially affect
mitochondrial function. Given the importance of mitochondria to the cell, mitochondrial
dysfunction induced by abnormal fusion could be linked to cell stress pathways which may
ultimately lead to cell death. This study suggests a new pathological process linked with a model
of PD, and in turn, suggests a potential therapeutic avenue for patients with PD since kinase
inhibitors of LRRK2 could be used to block the adverse effects of LRRK2 on mitochondrial
dynamics.
137
Chapter 5
Neuroprotective Actions of SIRT3 and RGM in Advanced In Vitro Models of Parkinson’s
Disease
138
5 Neuroprotective Actions of SIRT3 and RGM in Advanced In Vitro Models of Parkinson’s Disease
5.1 Introduction
In order to develop an effective neuroprotective treatment for PD, it is necessary to use a model
that mimics cell death mechanisms of PD as closely as possible. A number of in vivo and in
vitro models that mimic pathology of PD to different levels have been developed. Several in
vitro or cell models derived from human or animal tissue have been developed and include cell
lines, organotypic cultures and primary cultures. Toxin or genetic manipulation techniques are
used to generate cell models of sporadic and familial forms of PD (Sherer et al., 2003b; Testa et
al., 2005; Yong-Kee et al., 2012). Indeed, toxin and genetic models are useful for studying
cellular and biochemical mechanisms underlying pathology (Alberio et al., 2012). Furthermore,
human derived cell models benefit by having a human genetic background and may be more
useful for initial drug screening (Biedler et al., 1978). Various toxins have been applied to cells
to study the underlying mechanisms of sporadic and familial PD. Such toxins include MPTP and
rotenone which inhibit mitochondrial complex 1, proteasome inhibitors which cause UPS
dysfunction and 6-OHDA that causes oxidative stress (Hoglinger et al., 2003a; Mytilineou et al.,
2004; Hanrott et al., 2006). Genetic manipulation of α-synuclein and mutant variants represents
a classical model of familial PD, whilst manipulation of LRRK2 reproduces sporadic and
familial PD (Liu et al., 2005; Healy et al., 2008). While these models are advantageous for
examining individual mechanisms and for testing drugs in a high throughput methodology, they
lack the physiological environment provided by in vivo models.
139
As discussed in detail in the introduction (Chapter 2), many animal models of PD have been
generated. While earlier models, in particular 6-OHDA lesioned rat, replicate symptoms, such
models do not reproduce the mechanisms underlying pathology (Betarbet et al., 2002). The
discovery of genetic mutations associated with PD that were linked with genes encoding proteins
linked with mitochondrial function verified that the MPTP lesioned primate or mouse probably
mimics some of the cell death mechanisms associated with PD pathogenesis (Dauer and
Przedborski, 2003; Meredith et al., 2008). More recently genetic mouse models that induce
over-expression or knock-down of proteins linked with familial PD have been developed
(Chesselet et al., 2012). These animal models excel as tools for determining the effects of drugs
on PD physiology and for understanding the pathophysiology of PD because they better model
the human condition (Betarbet et al., 2002). Genetic manipulation allows for protein expression
over the life time of the animal model, which better mimics the progression of the disease state.
Animal models show variations in their ability to replicate disease pathology. The level of α-
synuclein expression in transgenic mice influences whether Lewy bodies form (Meredith et al.,
2008). Furthermore, rotenone rat models do not consistently display a loss of dopaminergic
terminals or loss of TH (Lapointe et al., 2004). Animal models excel at providing a
physiological environment for studying PD, however they are inconsistent at producing disease
pathology.
As has been shown in Chapter 2, and in previous studies, oxidative stress and mitochondrial
dysfunction play a pivotal role in the degeneration associated with PD. Indeed, various studies
reveal the effectiveness of ROS scavengers and mitochondrial rescuing drugs at protecting PD
models (Yang et al., 2009; Yong-Kee et al., 2011b). Mitochondrial complex 1 inhibitors such as
MPTP and rotenone, induce neurodegeneration by initiating mitochondrial dysfunction, which
leads to other downstream dysfunction, such as oxidative stress, impaired UPS function and
140
lysosome dysfunction (Perier et al., 2007). Oxidative stress and α-synuclein aggregation
activates cell death mechanisms in multiple cell lines (Hanrott et al., 2006). Thus, potential
neuroprotective agents require the ability to block oxidative stress and rescue mitochondria.
RGMa is a glyocosylphosphotidylinositol anchored protein involved in the collapse of growth
cones during retinal neuron development (Tassew et al., 2008). More recently, it was found to
interact with the dependence receptor, neogenin, during cell survival (Rajagopalan et al., 2004).
Neogenin receptors activate apoptosis when its ligand RGMa is unbound (Matsunaga et al.,
2004; Rajagopalan et al., 2004). In the presence of the RGMa, neuronal survival is promoted
(Matsunaga et al., 2004). Thus, RGMa may be an effective treatment in certain forms of PD.
SIRT3 is a member of the family of sirtuins that serve as NAD-dependent deacetylases and
ADP-ribosyl transferases (Onyango et al., 2002). SIRT3 is localized to the mitochondria where
it is involved in metabolism and biogenesis. Other functions include protein regulation through
PGC1α up-regulation, reduction of excitoxicity and modulation of stress response pathways
(Kong et al., 2010; Kim et al., 2011). The purported functions of SIRT3 make it a strong
candidate for a neuroprotective agent for PD.
Studies from previous chapters highlighted mitochondria as an important source of PD
pathology. Mitochondrial impairment by various toxins and mutations may impair energy
production and generate ROS which may result in apoptosis (Fig. 5.1). Given the potential cell
survival enhancing properties of RGMa and SIRT3, I hypothesized that these proteins may be
neuroprotective in models of PD, through the enhancement of energy production and prevention
of oxidative stress or apoptosis. The studies outlined in this chapter also describe the generation
of in vitro models that mimic key pathological processes known to occur in degenerating cells in
PD patients.
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Figure 5.1. The potential role of RGMa and SIRT3 in preventing PD cell death
mechanisms. Toxins and genetic mutations which directly or indirectly inhibit mitochondria
reduce energy production and increase ROS production. These processes may result in the
activation of apoptotic mechanisms which ultimately lead to cell death in PD. RGMa may
prevent mitochondrial induced cell death by directly blocking apoptosis. SIRT3 may prevent
reductions of ATP and block increases of ROS to protect cells from mitochondrial impairment
and subsequent cell death.
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5.2 Materials and Methods
5.2.1 SH-SY5Y cells
5.2.1.1 Generation and maintenance of SH-SY5Y cell lines
Human dopaminergic neuroblastoma SH-SY5Y cells (ATCC, USA) (P10-P25) were stored in
liquid nitrogen (-200oC) and quickly thawed in a water bath. SH-SY5Y cells were grown in
DMEM (6400 mg/L NaCl, 3700 mg/L NaHCO3, 400 mg/L KCl and 584 mg/L L-glutamine)
supplemented with 5% bovine calf serum in a sterile humidified chamber (37 oC, 5% CO2, 95%
O2) (Incubator: MCO-20AIC, Sanyo, USA) until confluent. Cells were passaged using 0.1%
trypsin for 5 min, then pelleted by centrifuging at 340xg for 5 min (Allegra 6R Centrifuge,
Beckman Coulter, USA).
5.2.1.2 Neuroprotective effect of repulsive guidance molecule A (RGMa)
SH-SY5Y cells were plated at 1.0x105 cells/ml in 96-well plates. Twenty four hours later,
RGMa (0.1 µM) was incubated with the cells for 5 minutes. Then dopamine hydrochloride (300
µM), naphthazarin (7.26 µM), PSI (40 µM) or rotenone (10 µM) were added. Twenty-four hours
following addition of toxin plus the redox-sensitive dye alamar blue (0.03% final volume) cell
viability was assessed. Mean fluorescent intensity units of three independent experiments are
expressed as a percentage of control ± SEM.
5.2.1.3 Assessment of the neuroprotective effect of SIRT3 in SH-SY5Y cells
SH-SY5Y cells were plated at 5.0x105 cells/ml. Twenty-four hours later, cells were transiently
transfected with ptracer-SIRT3-GFP (0.6 µg) using Lipofectamine 2000. Dopamine
hydrocholoride (30 µM), naphthazarin (2.17 µM), PSI (80 µM) or rotenone (40 µM) and the
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redox-sensitive dye, alamar blue, were added 48 hours after transfection (time 48 hrs). Cell
viability was measured 24 hours after toxin treatment (time 72 hrs) using a fluorescent plate
reader (FLUOstar OPTIMA, BMG Labtech, USA). Data from four independent experiments are
expressed as mean percentage of control (vehicle) ± SEM.
5.2.1.4 Assessment of the neuroprotective effect of SIRT3 in differentiated SH-SY5Y cells
SH-SY5Y cells were plated at 5.0x105 cells/ml. Twenty-four hours later, cells were
differentiated with retinoic acid (10 µM) (Sigma, Canada) for three days. Cells were then
transiently transfected with pcDNA3.1-3xFLAG-LRRK2 (5 µg) and ptracer-GFP (0.6 µg) or
pcDNA3.1-3xFLAG-LRRK2 (5 µg) and ptracer-SIRT3-GFP (0.6 µg) using Lipofectamine 2000.
After 48 hours, propidum iodide (1.5 µM) was incubated with the cells for 30 min and
fluorescence was measured (time 48.5 hrs) using a fluorescent plate reader. Data from two
independent experiments are expressed as mean percentage of control ± SEM.
5.2.2 Ventral mesencephalic primary cultures
5.2.2.1 Solutions
Borate buffer (0.1 M) consists of 0.05 M boric acid, 0.01 M sodium tetraborate, 400 ml H2O.
Plating medium was made by combining 460 ml Neurobasal media (Gibco, Invitrogen, Canada),
10 ml B27 Supplement (Gibco, Invitrogen, Canada), 25 ml bovine calf serum (Wisent, Canada),
and 5 ml 1 % L-glutamine (Sigma, Canada). Growth media consists of 475 ml Neurobasal
media, 10 ml B27 supplement and 15 ml BCS.
5.2.2.2 Generation of ventral mesencephalic primary cultures
Poly-D-lysine hydrobromide (0.1 mg/ml) (Sigma, Canada) in 0.1 M borate buffer was pipetted
onto the centre of each coverslip and incubated overnight at 37 oC. Twenty-four hours later,
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poly-D-lysine was removed and coverslips were soaked in sterile H2O for 1 hr followed by a 5
min rinse with sterile H2O. Immediately after aspirating the final wash, 2 ml of plating medium
was added to each dish.
Sprague Dawley rats (embryonic day 16) were anesthetised with isoflurane and euthanized by
cervical dislocation. The uterus was removed from the cavity and the embryos were transferred
to a Petri dish filled with Hank’s Buffered Salt Solution (HBSS) (Gibco, Invitrogen, Canada).
Brains were carefully removed and transferred to a Petri dish containing ice-cold HBSS. After
removing the meninges, the SNc was dissected. The SNc was transferred to a 15 ml falcon tube
containing 5ml of ice-cold HBSS. The tissue was incubated with 10% Trypsin/EDTA solution
(Gibco, Invitrogen, Canada) for 15 min at 37 oC. Plating medium was added to the tissue and
dissociated firstly using a 1000 µl pipette tip, followed by a 200 µl pipette tip. Dead cells were
excluded following addition of trypan blue. Cells were counted and plated at a density of
1.0x104 per 2 ml and maintained at 37oC with 5% CO2 in a humidified chamber. Cells were fed
every four days with growth media. To inhibit glia growth on division 4 (D4), 1 µm cytosine β-
D-arabinofuranoside (Sigma, Canada) was added to each dish.
5.2.2.3 Characterization of ventral mesencephalic primary cultures
Primary cultures were grown for three weeks before being fixed with 4% PFA, permeabilized
with 0.1% Triton-X, and blocked with 5% BCS. Cultures were incubated with the following
antibodies: tyrosine hydroxylase (TH) (1:200 µl) (Chemicon, USA), G protein-activated inward
rectifier potassium channel 2 (GIRK2) (Alomone Labs, Jerusalem) (1:200 µl), post-synaptic
density 95 (PSD95) (1:500 µl) (Affinity BioReagents, USA), synaptophysin (1:250 µl)
(Chemicon, USA), glial fibrillary acidic protein (GFAP) (1:500 µl) (Cell Signalling, USA) and
mitogen-activated protein kinase (MAPK) (1:500 µl) (Cell Signalling, USA). Secondary
146
antibodies, cy2 (1:1000 µl) and cy3 (1:2000 µl) (both Jackson ImmunoResearch Laboratories
Inc, USA) were incubated with cultures overnight at 4 oC. Images were captured using an
epifluorescent microscope at 40x magnification (Axiovert 200). Images are representative of
three independent experiments.
5.2.2.4 Generation of an in vitro α-synuclein model of PD
Primary ventral mesencephalic cultures were plated on glass coverslips and grown in vitro for
one week. AAV1/2-A53T α-syn, AAV1/2-empty vector and AAV1/2-GFP (all 3.4x109 gc/well)
were added to the cultures. After 6 weeks of virus exposure, fluorescent reactive dye (1 µl)
(Fixable Live/Dead Kit, Life Technologies, USA) was incubated with the cells for 30 min. This
was followed by fixation with 4% PFA, and permeabilization with 0.1% Triton-X and blocking
with 5% BCS. GIRK2 (1:500 µl) and ubiquitin (1:500 µl) (Santa Cruz Biotechnology, USA)
was incubated overnight at 4 oC. This was followed by a 1 hour incubation with cy3 (1:1000 µl)
and aminomethylcoumarin acetate (AMCA) (Jackson ImmunoResearch Laboratories Inc., USA).
Images were captured using an epiflourescent microscope equipped with a 63x objective
(Axiovert 200). Data consists of 30-40 cells in each of three independent experiments and is
expressed as mean percent positive cells ± SEM.
5.2.2.5 Assessment of the neuroprotective effect of SIRT3 in primary culture
Primary ventral mesencephalic cultures were maintained in vitro for three weeks (D21) prior to
transient transfection with ptracer-GFP (0.6 µg) or ptracer-SIRT3-GFP (0.6 µg). After 48 hours,
rotenone (20 nm) was incubated with the cells (time 48 hrs). After 48 hours of rotenone
exposure, propidum iodide (1.5 µM) was incubated with the cells for 30 min and fluorescence
was measured using a fluorescent plate reader (time 96.5 hrs). Data from two independent
experiments are expressed as mean percent change in cell death above control ± SEM.
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5.2.3 Nigro-striatal organotypic co-cultures
5.2.3.1 Generation of nigro-striatal organotypic co-cultures
Pregnant Sprague Dawley rats (Charles River, Canada) were obtained so that embryos would be
used at specific time points (E21-E23 and E14-E16). E21-E23 embryos were used for striatal
sections and E14-E16 embryos for SNc sections. A fourteen day pregnant rat was anesthetised
with isoflurane and euthanized by cervical dislocation. Embryos were quickly removed and
placed in a Petri dish containing ice cold F12 medium (Gibco, Invitrogen, Canada). Embryos
were decapitated and placed in a new Petri dish containing ice cold F-12 medium. The SNc was
isolated and placed in a new Petri dish containing ice cold F-12 medium. A twenty-one day
pregnant rat was anesthetised with isoflurane and cervical dislocation was performed. Embryos
were decapitated, brains removed, and placed in a Petri dish containing ice-cold F-12 medium.
Coronal brain slices (250 µM) were generated using a vibratome (VT1000S, Leica, USA).
Using a dissecting microscope, the striatum was removed from each coronal slice using a scalpel
and fine forceps and placed in a Petri dish containing ice-cold F-12 medium. The dorsolateral
area of the striatum was removed and incubated in a Petri dish containing ice-cold F-12 medium.
One dorsolateral area of striatum was then placed 1mm above hand-cut sections of SNc on PTFE
membranes (Millipore, USA). Cultures were incubated at 37 oC in 5% CO2 for 3 to 24 days.
Culture medium was changed every 3-4 days and treated at division 10 (D10) in vitro.
5.2.3.2 Characterization of cell types in nigro-striatal organotypic co-cultures
On D10, organotypic co-culture neurite outgrowth was examined. Sections were imaged in
phase contrast using an epifluorescent microscope equipped with a 20x long distance objective
(Axiovert 200, Carl Zeiss, Canada). For subsequent analysis, cultures were fixed and
immunostaining was performed. Co-cultures were excised by cutting around slices through
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PTFE membrane. Cells were fixed using 4% PFA/4% sucrose for 24 hrs at 4 oC. After fixation,
co-cultures were washed for 30 min and then incubated in 0.2% Triton-X for 30 min. Co-
cultures were incubated with 5% BCS for 2hrs. TH (1:200 µl), GIRK2 (1:200 µl) and PSD95
(1:500 µl) primary antibodies were diluted in 1% BCS and incubated with cultures overnight at 4
oC. Co-cultures were incubated with cy2 (1:1000 µL) or cy3 (1:2000 µL) secondary antibodies
diluted in 1% BCS for 1 hr at room temperature. Nuclei were stained by incubating co-cultures
with 4',6-diamidino-2-phenylindole (DAPI) (1:40000 µl) (Invitrogen, Canada) for 15 min. Phase
contrast images were captured using an epifluorescent microscope equipped with a 20x long-
distance objective (Axiovert 200, Carl Zeiss, Canada). Fluorescent images were captured using
an epifluorescent microscope equipped with an Apotome grid with a 63x objective (Axiovert
200) or without a deconvolution grid and 40x objective (IX81, Olympus, Canada). A total of
three replicates were generated for each experiment.
5.2.3.3 Assessment of cell death in organotypic co-cultures
To assess cell death, cultures were exposed to toxins that mimic cell death processes linked with
the pathogenesis of PD. Organotypic co-cultures (24 days in vitro) were treated with the
lysosome inhibitor, naphthazarin (60 µM, 80 µM), UPS inhibitor, PSI (80 µM, 100 µM) and
mitochondria complex 1 inhibitor, rotenone (50 µM, 70 µM) for 24 hrs. Propidium iodide (150
µM) (Invitrogen, Canada) was incubated with each co-culture for 1 hr, then removed from the
wells and replaced with fresh media. Propidium iodide fluorescence was then measured using a
plate reader (FLUOstar OPTIMA, BMG Labtech, USA). Mean fluorescence intensity units from
three independent experiments are expressed as mean percentage compared to control (vehicle-
no toxin) ± SEM.
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5.2.3.4 Assessment of TH/GIRK2 expression following exposure to toxins that mimic cell death processes in PD
Organotypic co-cultures (24 days in vitro) were treated with naphthazarin (60 µM, 80 µM) PSI
(80 µM, 100 µM) and rotenone (50 µM, 70 µM) for 24 hrs then fixed with 4% PFA/4% sucrose
for 24 hrs at 4 oC. After fixation, co-cultures were washed for 30 min and then incubated in
0.2% Triton-X in PBSx1 for 30 min. Co-cultures were blocked for 2 hrs using 5% BCS and
incubated with TH (1:200 µl) or GIRK2 (1:200 µl) antibodies overnight at 4 oC. Co-cultures
were incubated with cy2 (1:1000 µL) or cy3 (1:2000 µL) secondary antibodies diluted in 1%
BCS for 1 hr at room temperature. Nuclei were stained by incubating co-cultures with DAPI
(1:40000 µl) for 15 min. Co-cultures were imaged using an epifluorescent microscope with
attached Apotome grid and 40x objective (Axiovert 200). Images represent neurons from two or
three independent experiments.
5.2.4 Statistical analysis
A different cell passage was used for each replicate (n = 1). A minimum of two replicates were
used for each experiment. All data were analyzed used GraphPad Prism Version 5 (GraphPad
Software Inc, USA). The statistical tests used include one-way and two-way ANOVAs with
associated post-tests. Significance was assigned when P < 0.05.
5.3 Results
5.3.1 Assessment of the neuroprotective effects of RGMa and SIRT3
An intial screening of RGMa and SIRT3 was conducted to determine if there were any protective
effects of these proteins. Various toxins that mimic purported cell death mechanisms were
applied to SH-SY5Y cells and cell viability was measured in the presence of RGMa or SIRT3.
The presence of RGMa afforded significant protection to SH-SY5Y cells (Fig. 5.2). Pre-
150
treatment with RGMa led to a 40.25 ± 10.72% increase in cell viability when exposed to
dopamine (P < 0.05). The presence of RGMa during rotenone toxicity increased cell viability by
21.55 ± 6.55% (P < 0.05). Similarly, the effectiveness of SIRT3 at protecting cells was also
tested in SH-SY5Y cells. Over-expression of SIRT3 reduced rotenone (40 µM) induced toxicity
by 17.48 ± 6.29% (P < 0.01) (Fig. 5.3). Given SIRT3 protected cells in a model that mimics
idiopathic PD, it was necessary to determine whether SIRT3 could protect cells in a model that
recapitulates familial PD. A differentiated SH-SY5Y model expressing LRRK2 was used to
asses the effectivenes of SIRT3. Over-expression of LRRK2 increased cell death by 31.60 ± 0%
compared to control (P < 0.001) (Fig. 5.4). Interestingly, SIRT3 reduced cell death by 9.15 ±
0.85% compared to control (P < 0.01). It was necessary to further confirm the neurprotective
potential of SIRT3 by utilizing a neuronal model. Ventral mesencephalic primary cultures were
challenged with a toxic dose of rotenone, and the level of cell death in the presence of SIRT3
was determined. SIRT3 protected ventral mesencephalic primary cultures from cell death
induced by rotenone (20 nm). The presence of rotenone increased cell death by 21.70 ± 0%
compared to control (P < 0.01), however, over-expression of SIRT3 prevented rotenone induced
cell death by 19.07 ± 1.57% (P < 0.01) (Fig. 5.5).
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Figure 5.2. Effect of RGMa on toxin-induced reductions of cell viability. SH-SY5Y cells
were plated 24 hours before treatment with RGMa, toxins and alamar blue. A fluorescent plate
reader was used to measure alamar blue fluorescence. The effect of RGMa on dopamine
hydrochloride (300 µM), naphthazarin (7.26 µM), PSI (40 µM) and rotenone (10 µM) toxicity is
shown. Student’s t-test. * P < 0.05. Overall effect of RGMa on dopamine: F5,5 = 1.38, overall
effect of RGMa on rotenone: F5,5 = 1.86.
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CONTROLRGM
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Figure 5.3. Effect of SIRT3 in an SH-SY5Y cell model of PD. SH-SY5Y cells were plated 24
hours before being transiently transfected with ptracer-SIRT3-GFP (0.6 µg). Toxins were
incubated with the cells 24 hours prior to measuring cell viability. The effect of SIRT3 on cell
viability during rotenone (40 µM) toxicity is shown. Two-way ANOVA with Bonferroni post-
test. ** P < 0.05. Overall effect of SIRT3 on rotenone: F5,36 = 2.11.
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Media
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Figure 5.4. Effect of SIRT3 in differentiated SH-SY5Y cells. SH-SY5Y cells were
differentiated with retinoic acid then transiently transfected with pcDNA3.1-3xFLAG-LRRK2
and ptracer-SIRT3-GFP. Cell death was measured using propidium iodide 48 hours after
transfection. The effect of SIRT3 on cell death associated with LRRK2 over-expression is
shown. One-way ANOVA with Bonferroni multiple-comparison test post hoc. ** P < 0.05, ***
P < 0.001. Overall effect of SIRT3 on LRRK2: F2,5 = 10.98.
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Contro
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Figure 5.5. Effect of SIRT3 in primary cultures. Ventral mesencephalic primary cultures
were grown for 21 days before transient transfection with SIRT3. Rotenone (20 nm) was
incubated with cultures for 48 hours before measuring propidium iodide fluorescence. The effect
of SIRT3 on rotenone induced increases in cell death is shown. One-way ANOVA with
Bonferroni multiple-comparison test post hoc. ** P < 0.05. Overall effect of SIRT3 on rotenone:
F2,6 = 79.13
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5.3.2 Development of an in vitro α-synuclein model utilizing ventral mesencephalic primary cultures
In order to create a valid and effective in vitro model of PD, the characteristics of neurons that
degenerate in PD must be recapitulated. To this end, the relative expression of glia and neurons
in our ventral mesencephalic cultures were determined. Immuno-labelling was performed using
antibodies against MAPK and GFAP to distinguish between dendrites and glia. Ventral
mesencephalic primary cultures contain glia and neurons as demonstrated by strong GFAP and
MAPK expression (Fig. 5.6a,b). Since only SNc neurons from the ventral mesencephalon
degenerate in PD, it was necessary to determine if these cultures consist of SNc or VTA neurons.
Strong GIRK2 expression was found in these cultures, revealing the existence of SNc neurons
(Fig. 5.7a). Furthermore, these populations contain TH, indicating that these neurons are indeed
functional. These primary cultures also form synaptic connections as demonstrated by PSD95
and synaptophysin expression (Fig. 5.7b). Large puncta are seen at sites where processes contact
each other. There are a number of genetic mutations that lead to PD pathology. The most
thoroughly examined of which are mutations in the gene that encodes the protein, α-synuclein.
Thus, an in vitro model was generated by over-expressing a mutated form of α-synuclein that is
linked with PD. Ventral mesencephalic primary cultures were subjected to recombinant AAV
expressing mutant α-synuclein mutant gene expression. Six weeks after virus exposure, A53T
mutant α-synuclein expression caused a 58.54 ± 7.52% increase in cell death compared to
control (PBSx1 vehicle) (Fig. 5.8a,b). Ubiquitin expression was also examined in A53T α-
synuclein expressing cells. Ubiquitin aggregates did not increase in neurons exposed to the
A53T mutation (Fig. 5.8b).
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Figure 5.6. Determination of MAPK and GFAP expression in primary culture. Ventral
mesencephalic primary cultures (D21) were fixed and immuno-labelled with antibodies against
GFAP and MAPK. These cultures express both neurons and glia. (a) GFAP expression is
localized around the entire soma of glia. (b) Neurons strongly express MAPK within their cell
bodies and processes. Scale bars = 20 µm.
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GFAP DAPI Mergea
MAPK DAPI Mergeb
162
Figure 5.7. Determination of TH and GIRK2 expression in ventral mesencephalic primary
culture. Ventral mesencephalic primary cultures (D21) were fixed and immuno-labelled with
antibodies against TH and GIRK2. These neurons express both TH and GIRK2. (a) TH and
GIRK2 expression is localized in the neuronal bodies and processes. (b) Strong PSD95 and
synaptophysin expression is found in neuronal processes. Scare bars = 20 µm.
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GIRK2TH MergeDAPIa
SynaptophysinPSD95 MergeDAPIb
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Figure 5.8. Effect of mutant A53T α-synuclein expression in ventral mesencephalic primary
cultures. Cultures were transduced with recombinant AAV expressing mutant (A53T) α-
synuclein for 6 weeks. After 6 weeks exposure, cell death was assessed using a live/dead kit
which exhibits bright fluorescence upon binding internal/external amines of dead cells. Cells
were then fixed and immuno-labelled with antibodies against GIRK2 and ubiquitin. (a) Effect of
mutant A53T α-synuclein expression on cell death. Cell death is represented by positive staining
of the live/dead kit. (b) Representative images of GIRK2 cells with positive staining of
internal/external amines of dead cells by the live/dead kit. Scale bars = 20 µm. One-way
ANOVA with Tukey’s multiple comparison test post-hoc. ** P < 0.01. Overall effect of α-
synuclein A53T: F3,11 = 10.30.
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5.3.3 Development of a nigro-striatal organotypic co-culture model of PD
PD symptoms result from the dysregulation of complex neuronal networks that consist of
specialized cell types. Thus, it was necessary to identify synaptic connections and characterize
specific cell types in these nigro-striatal organotypic co-cultures. After 14 days, axons from SNc
neurons traverse the space between slices and innervate the striatal section (Fig. 5.9a). Synapse
formation is shown by the presence of synaptic markers, such as PSD95. Here, neurons from
these co-cultures express PSD95 within their projections (Fig. 5.9b). Degeneration of
dopaminergic neurons occurs selectively in the SNc, leaving the VTA intact. To determine
whether the neurons in our co-cultures were from the SNc or the VTA, we measured GIRK2
expression as this is expressed specifically in the SNc. As shown in Fig. 5.10a, a large
proportion of neurons in these cultures strongly express GIRK2. Since these neurons also
express TH (Fig. 5.10b), it appears that these neurons represent dopaminergic nigro-striatal
neurons, rather than neurons originating from the VTA or GABAergic interneurons which are
also found within the SNc. In order to generate a cell model that mimics PD, it was first
necessary to assess the effect of toxins that are believed to emulate cell death mechanisms in PD.
Nigro-striatal organotypic co-cultures were treated with naphthazarin (60 µM, 80 µM), PSI (80
µM, 100 µM) and rotenone (50 µM, 70 µM) for 24 hrs. Each toxin, at varying concentrations,
increased the number of dead cells. Naphthazarin concentrations of 60 µM and 80 µM increased
propidium iodide fluorescence by 67.54 ± 20.96% and 183.94 ± 23.42%, respectively (both P <
0.05) (Fig. 5.11a). Neurons exposed to PSI (100 µM) exhibited a 55.81 ± 16.57% increase in
propidium iodide fluorescence (P < 0.01) (Fig. 5.11b). Rotenone (70 µM) exposure increased
propidium iodide fluorescence by 66.58 ± 15.71% (P < 0.05) (Fig. 5.11c). Neurons of the SNc
experiencing dysfunctional sub-cellular mechanisms associated with PD often lose their
dopaminergic phenotype. Given cells degenerate when exposed to all three toxins, it was
168
necessary to determine if these neurons also loss their dopaminergic phenotype. Nigro-striatal
organotypic co-cultures were labelled with TH and GIRK2. Interestingly, neurons expressing
GIRK2 had reduced TH expression when exposed to naphthazarin, PSI and rotenone (Fig. 5.12).
169
Figure 5.9. Representative images showing axon outgrowth projecting from the SNc to
STR. SNc and STR slices were plated on day 0 (D0) and imaged 24 days later (D24) (a) Phase
contrast image to show multiple axons originating from the SNc (top-right) projecting to the STR
(bottom-left). (b) On D24, cultures were fixed and immunolabelled with the synaptic marker
PSD-95. Neurons forming networks have strong punctate expression of PSD95 in their
processes. Scale bars = 20 µm.
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Phase Contrasta
PSD95 DAPI Mergeb
SNc
STR
171
Figure 5.10. Expression of TH and GIRK2 in nigro-striatal cultures. Nigro-striatal co-
cultures were grown for 24 days before being fixed and immuno-labelled with antibodies against
GIRK2 and TH. (a) Nigral slices of the co-cultures strongly express GIRK2 within the soma.
Scale bar = 40 µm (b) Nigro-striatal co-cultures are fully functional as shown by the expression
of TH within the cell bodies and projections. Scale bars = 20 µm.
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aGIRK2 DAPI Merge
THb
DAPI Merge
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Figure 5.11. Effect of naphthazarin, PSI and rotenone on toxin-induced cell death. Co-
cultures (D24) were exposed to toxins for 24 hours. Cell death was measured using propidium
iodide (PI). PI fluorescence was measured using a fluorescent plate reader. (a) Effect of
naphthazarin (60 µM and 80 µM) on cell death. (b) Effect of PSI (80 µM and 100 µM) on cell
death. (c) Effect of rotenone (50 µM and 70 µM) on cell death. One-way ANOVA with
Dunnett’s multiple comparison test post-hoc. * P < 0.05, ** P < 0.01, *** P < 0.001. Overall
effect naphthazarin treatment: F2,1 = 6.01, PSI treatment: F2,11 = 8.10, rotenone treatment: F2,11 =
6.27.
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a b
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Figure 5.12. Effect of toxin exposure on TH expression in nigro-striatal organotypic co-
cultures. Co-cultures (D24) were incubated with toxins 24 hours prior to being fixed and
immunolabelled with antibodies against GIRK2 and TH. Images show the effect of naphthazarin
(80 µM), PSI (100 µM) and rotenone (70 µM) on TH expression in GIRK2 expressing cells.
Scale bars = 20 µm.
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DMSO
DAPIGIRK2 TH MergeNAP
PSI
ROT
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5.4 Discussion
Familial and sporadic PD are likely to have similar mechanisms underlying their pathology,
however a treatment that halts, slows or reverses PD has yet to be developed. To this end, I
developed and characterized cell models of PD that enable more rapid screening of potential
neuroprotective compounds in a relatively high throughput and cost effective manner. Whilst
these models are less physiological than in vivo models, I have shown that they are likely to have
clinical relevance.
Previously I validated an SH-SY5Y cell model of PD which proved to be effective in testing
potential neuroprotective agents (Yong-Kee et al., 2011b). Here, I utilized this same model to
test the neuroprotective effect of RGMa. Interestingly, RGMa was protective during dopamine
and rotenone toxicity, both highly relevant in PD pathology. Given that only rotenone and
dopamine toxicity was blocked, it is likely that RGMa protects cells by preventing ROS
generation. Here, the greatest protective effect of RGMa was during rotenone toxicity. Since
mitochondria are highly active organelles that generate large amounts of ROS, inhibition of
mitochondrial complex 1 would lead to a large rapid increase in ROS (Lin and Beal, 2006).
Preventing this increase may explain the higher protective effect seen during rotenone toxicity
than in dopamine toxicity. Studies revealed an interaction between RGMa and neogenin
receptors prevents the activation of proapoptotic pathways (Matsunaga and Chedotal, 2004). It
could be possible that RGMa blocks apoptosis given that toxic effects of dopamine and rotenone
are mediated by apoptotic processes (Hanrott et al., 2006; Imamura et al., 2006). However, a
study using neural precursor cells revealed the activation of apoptosis in response to lysosome
inhibition (Walls et al., 2010). Thus, if RGMa blocked apoptotic processes, it would be expected
that it would be effective during naphthazarin toxicity as well.
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The role of SIRT3 in mitochondria and cell survival made it a potential candidate for a
neuroprotective agent in PD. The effectiveness of SIRT3 as a neuroprotective agent was tested
in various in vitro models of PD. SIRT3 protected neuroblastoma and neurons from rotenone
toxicity. A study by Ahn et al. (2008) revealed the deacetylase activity of SIRT3 can enhance
the activity of mitochondrial complex 1. This in turn regulates the production of ATP levels in
the cell. Since mitochondrial activity at complex 1 is reduced by rotenone, it is feasible that the
actions of SIRT3 can reverse these effects on mitochondria. This explains how effective SIRT3
is at negating the effects of rotenone and not any of the other toxins tested. An alternative
function of SIRT3 can warrant the protective effect of SIRT3. A study in myotubes revealed the
SIRT3 dependent up-regulation of PGC1α leads to mitochondria biogenesis (Kong et al., 2010).
An up-regulation of mitochondria may compensate for damaged mitochondria which ultimately
prevents cell loss. These results prompted the examination of the effectiveness of SIRT3 during
LRRK2 induced toxicity. Given the effects of LRRK2 on mitochondria, SIRT3 would be a
prime candidate for neuroprotection in PD (Wang et al., 2012b). Indeed, SIRT3 prevented
LRRK2 induced cell death in differentiated SH-SY5Y cells. This necessitates further study of
SIRT3 to protect cells from dysfunction associated with mutant LRRK2. SIRT3 is effective at
protecting mitochondria which infers that it may be a valuable tool for other mitochondrial
disorders.
In vitro models utilizing cell lines are useful for high throughput experiments where multiple
compounds can be tested, but they lack physiological elements that are essential for more
rigorous testing of compounds. Thus, the more complex in vitro models, such as the organotypic
and primary cultures were characterized for various neuronal markers. Both the organotypic and
primary cultures used here express TH, which is a key component in the production of
dopamine. Other studies in ventral mesencephalic and organotypic cultures have shown the
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expression of TH and homovanillic acid, proteins involved in dopamine production (Lyng et al.,
2007; Zhang et al., 2007). Furthermore, these cultures are composed of neurons from the SNc,
as shown by prominent GIRK2 expression. Neurons that degenerate in the early stages of PD
are specific to the SNc and have a dopamine producing phenotype (Hornykiewicz, 1966; Obeso
et al., 2000). These findings make them an appropriate model, from a physiological standpoint,
to study PD. In vivo models benefit from the retention of synaptic networks when compared to
in vitro models. Indeed, the cultures used here form synaptic connections and have key
components of synapse formation. This is demonstrated by the expression of the synaptic
proteins PSD95 and synaptophysin. This model is in agreement with other studies that found
PSD95 and synaptophysin expression in organotypic and primary cultures (Buckby et al., 2004;
Wakita et al., 2010). The models studied here display characteristics similar to those of in vivo
models and benefit from relatively faster production. This in turn enables testing of various
compounds in an environment that is more physiological than those provided by cell lines, while
retaining easier production than animal models.
Toxin based in vitro and in vivo models have been used as tools to mimic the pathology seen in
sporadic PD. Most in vitro models lack the physiological environment that resembles PD, while
in vivo models are inconsistent at obtaining a complete loss of dopaminergic neurons (Betarbet et
al., 2000; Hoglinger et al., 2003b). It is apparent here that a variety of toxins produced a loss of
cells at specific concentrations in organotypic cultures. Cell death induced by naphthazarin, PSI
and rotenone is associated with a loss of TH specifically in SNc neurons. A similar study in
ventral mesencephalic cultures shows a loss of TH after MPTP exposure (Jakobsen et al., 2005).
Interestingly, rat models which fail to produce behavioural changes similar to those found in PD,
do not show a reduction in TH because these behavioural changes are associated with losses of
dopamine (Lapointe et al., 2004). A retraction of SNc axons and terminals occurs in patients, but
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the toxins used here do not lead to similar morphological changes. This could be a consequence
of the time cultures were exposed to the toxins, thus extended exposure times may allow for a
loss of axons. Indeed, multiple studies have shown axon degeneration in organotypic cultures
using rotenone incubation periods from three days to more than a week (Testa et al., 2005;
Ullrich and Humpel, 2009). This organotypic co-culture model is advantageous for studying
mechanisms related to PD because it employs toxins linked with PD pathology to consistently
produce a loss of dopaminergic neurons.
Current transgenic models suffer from the inability to consistently produce dopaminergic
degeneration (Meredith et al., 2008). Furthermore the only transgenic animals expressing α-
synuclein are mice; which makes it extremely difficult to dissect the nigra. Thus, I generated an
in vitro primary culture model that expresses α-synuclein. The α-synuclein primary culture
model used here repeatedly shows degeneration of GIRK2 expressing cells. This specificity is
important because it replicates the early stages of disease pathology, whereby nigral cells begin
to degenerate (Hornykiewicz, 1966; Obeso et al., 2000). Lewy bodies, which are composed of
α-synuclein and ubiquitin, do not form in these neurons. Lewy bodies are often associated with
PD linked with α-synuclein (Crowther et al., 2000; Saito et al., 2004). It is likely that increased
culture periods would allow for the formation of Lewy bodies because α-synuclein would have
more time to accumulate and aggregate. Since this model does not require transgenic animals, it
is a relatively cost-effective way to study pathology linked with PD.
These studies reveal that in vitro models are a valuable tool for studying PD because they are
easily produced and are similar to cells affected in PD. Furthermore, they display typical losses
of function and viability when presented with toxin and gene induced cell stressors. Granted
there are disadvantages to these models, their advantages are highly beneficial when used in a
181
high throughput environment. This is demonstrated by the elucidation of the protective effect of
RGMa and SIRT3. The rescue of cells from mitochondrial dysfunction caused by toxins and
genetic over-expression implies that PD could be a mitochondrial disorder. Furthermore, RGMa
and SIRT3 may be important agents for treating other mitochondrial disorders.
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Chapter 6
Summary and Future Directions
183
6 Summary and Future Directions
To conclude, following exposure to toxins that mimic PD pathology, UPS and lysosome function
are inhibited, consequently reducing mitochondrial function. Following genetic over-expression
of LRRK2 and G2019S-LRRK2, mitochondrial fusion becomes inhibited, resulting in
fragmentation of mitochondria. Compounds that primarily target mitochondrial function in
models that both mimic PD pathology and contain neurons that are similar to those which
degenerate in PD are essential for developing therapeutics to treat PD. The findings described
here suggest that alterations to mitochondria may be a central factor contributing to PD onset,
and that enhancing the function of mitochondria is a potential avenue for preventing
neurodegeneration causing PD.
Recently it has been shown that ROS production, as well as malfunctions to the UPS and
lysosome are causative factors of the disease (Cuervo et al., 2004; Betarbet et al., 2005). In
Chapter Two, studies reveal that malfunction of multiple sub-cellular systems inhibit
mitochondrial function early on during cell stress. More specifically, these experiments reveal a
tight link between the UPS, lysosomes and mitochondria, and that convergence of these
dysfunctional processes can be disastrous for cellular health. These experiments not only reveal
the convergence of multiple mechanisms, but they also present evidence that mitochondria are
sensitive to abnormalities in other sub-cellular systems, such as the UPS and lysosome. These
studies are the first to show a link between the mitochondria, UPS and lysosome. Moreover, the
link between the UPS and lysosome is further established here since prolonged inhibition of the
UPS or lysosome can impair the lysosome or UPS, respectively (Sherer et al., 2002). In future,
studies should examine the pathways leading to the interactions between the mitochondria, UPS
184
and lysosome. The regulation of mitochondrial protein quality control by the UPS and the
removal of dysfunctional mitochondria by lysosomes are possible pathways interconnecting
these sub-cellular domains. These pathways can be studied by measuring the accumulation of
ubiquitnated proteins in mitochondrial fractions from cell lysates during proteasomal inhibition
or by measuring the number of mitochondria encapsulated by autophagosomes during lysosomal
inhibition. However, it is still unclear why mitochondria are specifically affected and why
mitochondria are affected so early during cellular stress when processes such as fission and
fusion are in place to rescue mitochondria. Since mitochondria provide energy to the cell, it is
possible that slight perturbations to mitochondrial function can have profound effects on neurons
that have high energy demands. Moreover, nigral cells are highly susceptible to changes in
homeostasis because they are constantly metabolizing dopamine, which produces large quantities
of ROS, thus, further production of ROS by mitochondrial damage may bring imbalance to
nigral cell homeostasis. This would also account for nigral neurons being unable to quickly
compensate for losses of mitochondrial function and ROS production. Thus, future studies
should compare the function of mitochondria and their effects on ROS in nigral and non-nigral
neurons to determine if nigral cells are more susceptible to these changes. It is clear from these
studies that mitochondria play an important role in disease pathogenesis.
Since multiple sub-cellular mechanisms are responsible for disease pathogenesis, it is necessary
for a model to incorporate all of these mechanisms. Moreover, such a model can be deemed
representative of the condition, if when tested against a battery of potential neuroprotective
agents, has a high degree of similarity when correlated to the outcomes of clinical trials. Indeed,
the outcomes of the neuroprotective assay used in Chapter Three are very similar to the results of
clinical trials where various neuroprotective agents were tested. In particular, coenzyme Q10
was highly protective during stress induced by multiple mechanisms, such as mitochondrial, UPS
185
and lysosomal inhibition. A correlation between this study and clinical trials can be drawn since
coenzyme Q10 showed promise in clinical trials, thus validating the in vitro assay used here.
Substantial evidence for a causative role of mitochondria in PD pathology is provided by the
neuroprotective effect of coenzyme Q10. Since mitochondrial dysfunction results from UPS and
lysosomal inhibition, it is expected that a potential therapeutic which acts directly on
mitochondria would be highly protective, and indeed, coenzyme Q10 did protect cells from the
toxic effects of UPS and lysosomal inhibition. Coenzyme Q10 is an integral part of the electron
transport chain, and the protective effects seen here could be attributed to an increase in ATP
production. However, increased ROS production associated with inhibited respiratory activity
could be prevented when coenzyme Q10 restores oxidative phosphorylation. Thus, future
studies can examine if the aforementioned pathways are affected by blocking key molecules
essential for each pathway in the presence of coenzyme Q10 and then determine if cell viability
is enhanced. Alternatively, ATP and ROS levels can be measured when coenzyme Q10 is
present. These studies are the first to describe an in vitro model that is easy to produce and can
effectively test potential neuroprotective agents to treat PD. Moreover, it will enable rapid and
efficient testing of a wide range of compounds and make available more compounds for testing
in clinical trials. These studies suggest that for a therapeutic to have any potential to treat PD
patients it must enhance mitochondrial function or induce the biogenesis of mitochondria to
compensate for mitochondria that have lost function due to cell stress.
Recently research has redirected its focus back to the field of mitochondria by suggesting
mitochondrial dynamics is an important mechanism in neurodegenerative disease (Chen and
Chan, 2009). Thus, given the findings of my initial study, subsequent studies in my thesis
focused on elucidating the role of mitochondrial dynamics in PD. Mitochondrial dysfunction in
PD may arise from alterations to fission and fusion since these processes are imperative for
186
proper mitochondrial function (Otera and Mihara, 2011). This hypothesis is confirmed in
Chapter Four by finding that mitochondrial fusion becomes inhibited by LRRK2 and G2019S-
LRRK2 expression which ultimately fragments mitochondria. Furthermore, it appears that
mitochondrial fragmentation occurs before cell stress occurs. Although mitochondrial
dysfunction was not shown during LRRK2 and G2019S-LRRK2 expression, it may be that
altered fusion is the first step leading to reduced membrane potential, and hence, dysfunctional
mitochondria. Indeed, mitochondrial fragmentation is a prerequisite for mitochondrial
dysfunction and eventual cell death (Frank et al., 2001; Breckenridge et al., 2003). While
increased mitochondrial fission could lead to fragmented mitochondria, it was not observed in
this study. This result however, may be specific to the time point used. At later time points
fission may indeed play a role in the fragmentation caused by LRRK2 and G2019S-LRRK2.
Given the discovery of altered fusion, future studies should focus on elucidating the changes that
occur in fusion proteins. It is possible that changes in the activity of Mfn1, Mfn2 and Opa1 are
regulated by the kinase function of LRRK2. Moreover, the GTPase activity of LRRK2 could
limit the available GTP required for fusion protein function since LRRK2, which is located on
the outer mitochondrial membrane, would be situated close to Mfn1 and Mfn2. Future studies
can delineate if the kinase or GTPase domain of LRRK2 is responsible for the inhibition of
fusion protein activity by knocking down these specific domains of LRRK2 and subsequently
measuring fusion rates. While studies suggest mitochondrial fission is key to abnormal
mitochondrial function, this study is the first to suggest that inhibition of mitochondrial fusion by
LRRK2 could affect mitochondrial function. It is possible that patients having a LRRK2 genetic
background may suffer neurodegeneration caused by abnormal mitochondrial fusion.
It is imperative for in vitro models to replicate the pathology found in PD as precisely as possible
so as to foster the efficient production of therapeutics. Various studies, including the ones
187
described here, suggest compounds which target the mitochondria are highly effective at treating
PD. In Chapter Five, upon characterization of various in vitro models, neuronal cultures were
found to be very similar to the neurons that degenerate in the SNc of parkinsonian patients.
Moreover, the novel mitochondrial protein, SIRT3, protected neurons from degeneration
associated with cell stress induced by LRRK2 over-expression. The high therapeutic value of
SIRT3 can be concluded for two reasons. Firstly, the feasibility of SIRT3 as a neuroprotective
agent is confirmed since it was able to protect mature neurons having a dopaminergic phenotype
from degeneration. Secondly, since SIRT3 protected neurons from the toxic effects of LRRK2, a
genetic mutation that is common among PD patients, it has the potential to treat a broad
spectrum of patients with PD. The next logical study is to test SIRT3 in various animal models
that closely mimic the pathological mechanisms underlying PD. In addition to mitochondrial
dysfunction, these models should display ROS production and protein aggregation as these are
classical markers of PD pathology. Further studies should be conducted to examine the
mechanisms by which SIRT3 provides neuroprotection. Indeed two main roles of SIRT3 are
likely responsible for its therapeutic effect, one being the regulation of mitochondrial complex 1
function, and two being its role in mitochondrial biogenesis (Ahn et al., 2008; Cimen et al.,
2010; Kong et al., 2010). These pathways can be studied by measuring changes in ATP levels or
by quantifying levels of mitochondrial DNA during SIRT3 expression. These studies are the
first to show the protective effect of SIRT3 in a neuronal model that has a high degree of
similarity to the neurons that degenerate in the SNc. Furthermore, SIRT3 could have a broad use
in the clinic since it could be used to treat patients having either familial PD caused by LRRK2,
or idiopathic forms caused by environmental toxins.
188
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8 Appendices
A modified version of this appendix was previously published as:
Yong-Kee CJ, Warre R, Monnier PP, Lozano AM, Nash JE (2012) Evidence for synergism between cell death mechanisms in a cellular model of neurodegeneration in
Parkinson's disease. Neurotoxicity research 22(4):355-364.
My contributions to the following appendix include data analyses and design of the
figures listed in the text.
Abstract
Delineation of how cell death mechanisms associated with PD interact and whether they
converge would help identify targets for neuroprotective therapies. The purpose of this study
was to use a cellular model to address these issues. Catecholaminergic SH-SY5Y neuroblastoma
cells were exposed to a range of compounds (dopamine, rotenone, naphthazarin, and PSI) that
are neurotoxic when applied to these cells for extended periods of times at specific
concentrations. At the concentrations used, these compounds cause cellular stress via
mechanisms that mimic those associated with causing neurodegeneration in PD, namely
oxidative stress (dopamine), mitochondrial dysfunction (rotenone), lysosomal dysfunction
(naphthazarine), and proteasomal dysfunction (PSI). The compounds were applied to the SH-
SY5Y cells either alone or in pairs. When applied separately, the compounds produced a
significant decrease in cell viability confirming that oxidative stress, mitochondrial, proteosomal,
or lysosomal dysfunction can individually result in catecholaminergic cell death. When the
compounds were applied in pairs, some of the combinations produced synergistic effects.
Analysis of these interactions indicates that proteasomal, lysosomal and mitochondrial
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dysfunction is exacerbated by dopamine-induced oxidative stress. Furthermore, inhibition of the
proteasome or lysosome or increasing oxidative stress had a synergistic effect on cell viability
when combined with mitochondrial dysfunction, suggesting that all cell death mechanisms
impair mitochondrial function. Finally, we show that there are reciprocal relationships between
oxidative stress, proteasomal dysfunction, and mitochondrial dysfunction, whereas lysosomal
dysfunction appears to mediate cell death via an independent pathway. Given the highly
interactive nature of the various cell death mechanisms linked with PD, we predict that effective
neuroprotective strategies would target multiple sites in these pathways, for example oxidative
stress and mitochondria.
Introduction
The primary pathologies underlying PD are a loss of dopaminergic cells within the SNc as well
as additional catecholaminergic brain stem nuclei (Braak et al. 2003), combined with the
appearance of aggregates of protein, known as Lewy bodies, in affected brain regions (Goldman
et al. 1983). Upon diagnosis, patients are relatively mobile and are able to perform most motor
tasks. As the disease progresses, symptoms become severely disabling such that palliative care
is necessary. If, upon diagnosis of PD, it were possible to prescribe a treatment capable of
halting, slowing or even reversing the progression of degeneration of the SNc, patients would not
reach the advanced stages of the disease, and so could maintain a better quality of life (Olanow
2008).
The development of effective neuroprotective or neurorestorative agents requires an
understanding of the sub-cellular mechanisms underlying neurodegeneration in PD. To this end,
studies in animal and cell models of PD and post-mortem brain tissue from patients with PD
have shown that oxidative stress (Jenner 2003; Testa et al. 2005), malfunction of mitochondrial
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complex 1 (Lannuzel et al. 2003; Sherer et al. 2007; von Bohlen Und Halbach et al. 2004), and
dysfunction of the UPS contribute to neurodegeneration in PD. In addition, dysfunction of
trafficking within and between the endoplasmic reticulum and golgi network (Cooper et al.
2006), presynaptic function (Wislet-Gendebien et al. 2006; Wislet-Gendebien et al. 2008), and
chaperone mediated autophagy (CMA) have also been associated with cell death in PD (Ardley
et al. 2004; Caneda-Ferron et al. 2008; Li et al. 2004). These findings are confounded by the fact
that all mutated proteins linked with familial cases of PD cause at least one of the above
mechanisms to function aberrantly (Pan et al. 2008). Recent studies have shown that different
cell death mechanisms associated with PD are closely linked, whereby one cell stressor causes
abnormalities in at least one other cell death mechanism linked with PD (Betarbet et al. 2006;
Greenamyre and Hastings 2004; Hoglinger et al. 2003; Sherer et al. 2007; Testa et al. 2005).
While many studies in animal and cell culture models of PD have revealed the sub-cellular
mechanisms responsible for cell death, and indicated how these mechanisms interact, all of these
models are either difficult to produce or take months or years to develop the pathologies or
phenotypes reminiscent of PD (Nuber et al. 2008; Richfield et al. 2002). Because of this, the
discovery of potential novel targets as neuroprotective or neurorestorative therapies has been
significantly delayed. Previously we have used a heterologous catecholaminergic neuroblastoma
cell line, SH-SY5Y, which has both dopamine β-hydroxylase and dopamine transporter activity,
and thus may be used as a model of dopaminergic neurons, to show that inhibition of either
mitochondria complex 1 using rotenone, inhibition of the proteasome using PSI, inhibition of
lysosomes using naphthazarin, or the induction of oxidative stress using high concentrations of
dopamine causes a decrease in cell viability over a 24 hour time period (Yong-Kee et al. 2011).
215
The mechanisms underlying this increase in cell stress include early changes in mitochondrial
dysfunction followed by increased ubiquitin levels (Yong-Kee et al. 2012).
In the present study we extend our line of investigation by using combinations of these
compounds to study the interactions between the multiple cell-death mechanisms associated with
PD. The aim of the current study was to identify whether cell death mechanisms thought to be
responsible for neurodegeneration in PD converge. We show that proteasomal, lysosomal, and
mitochondrial dysfunction form independent cell death pathways. Furthermore, proteasomal and
mitochondrial dysfunction are exacerbated by oxidative stress. In addition there are reciprocal
links between oxidative stress, proteasomal dysfunction, and mitochondrial dysfunction, and also
between mitochondrial and lysosomal dysfunction. These findings suggest that the most
effective neuroprotective treatment strategies for PD should target multiple sites, for example
oxidative stress and mitochondria.
Materials and Methods
Materials
Dopamine hydrochloride, 5,8-dihydroxy-1,4-naphthoquinone (naphthazarin), rotenone and
dimethyl sulfoxide (DMSO) were purchased from Sigma (USA), Z-Ile-Glu(OBut)-Ala-Leu-al
(PSI) from BIOMOL (USA) and alamar blueTM from Biosource (Canada). SH-SY5Y cells were
purchased from ATCC, Dulbecco’s Modified Eagle’s Medium (DMEM), bovine calf serum,
trypsin and L-glutamine from Wisent (Canada).
Cell culture
Human catecholaminergic neuroblastoma SH-SY5Y cells (Imashuku et al. 1973) (P10 to P30)
were cultured in DMEM (6400 mg/L NaCl, 3700 mg/L NaHCO3, 400 mg/L KCl, and 584 mg/L
216
L-glutamine) supplemented with 5% bovine calf serum in a sterile humidified chamber (37 °C,
95% CO2, 5% O2) (MCO-20AIC, Sanyo, USA) until confluent. Cells were passed using 0.1%
trypsin for 5 min, then pelleted by centrifuging at 1400 rpm (Allegra 6R Centrifuge, Beckman
Coulter, USA).
Cell viability assays
Twenty four hours following addition to 96-well plates, SH-SY5Y cells were exposed to
concentration response curves of either, dopamine hydrochloride (0.1 µM–600 µM),
naphthazarin (0.1 µM–1 mM), PSI (0.1 µM–500 µM), or rotenone (0.1 µM–1 mM). Rotenone
and naphthazarin were dissolved in 0.1% DMSO and all other compounds were dissolved in cell
media for the concentration response curves. For the compound pair experiments naphthazarin
was dissolved in cell media instead of DMSO. Where DMSO was used, a vehicle control group
for the effect of DMSO on cell viability was included in the protocol. The redox sensitive dye
alamar blue (0.4% of final volume) was added, and cells were incubated for 24 hours. Cell
viability was assessed by measuring the change in fluorescence of alamar blue (ex. 544 nm, em.
590 nm) using a FLUOstar OPTIMA (BMG Labtech, USA) in comparison with control wells
containing SH-SY5Y cells, alamar blue and either media or 0.1% DMSO depending on the
compounds used. To determine the effect of combinations of compounds, cells were exposed to
a full concentration response curve of one compound in the presence of a concentration of the
second compound that produced 10 to 20% of its maximal effect (EC10–20%; see Results and Fig.
1). Cells were exposed to pairs of compounds for 24 hours and cell viability was measured as
described above. For all experiments n = 6, where each n is the mean of six replicates.
Statistical Analysis
217
For each replicate (n), fluorescence was expressed as the mean of 6 replicates in each
experiment. To determine EC10%, EC15%, and EC20% values, the concentration response data
were analysed using the least squares method of nonlinear regression to fit curves constrained by
a Hill slope of -1 and a curve bottom of 0. The top of the curve was unconstrained. Differences
in the means ± SEM for 6 experiments comparing the response to one compound with a pair of
compounds were analysed using two-way ANOVA and Bonferroni post hoc. All data were
analyzed using Graphpad Prism 5.0 statistical software (Graphpad Software Inc.).
Results
Determination of EC10–20% values
Concentration response curves for dopamine (0.01 µM–600 µM), rotenone (0.1 µM–1 mM), PSI
(0.1 µM–500 µM), and naphthazarin (0.1 µM–1 mM) were performed (Fig. 8.1). To investigate
potential synergism between cell death pathways, for each compound, an appropriate
concentration that could be applied to SH-SY5Y cells in combination with a range of
concentrations of a second compound was determined. The criteria for choosing the
concentration was that it was an active concentration, i.e., induced toxicity (as measured by a
decrease in cell viability), but not to such an extent that, when added in combination with a
second compound it would mask any possible synergistic effects, which would be the case if the
chosen concentration caused a large decrease in cell viability.
Following exposure of SH-SY5Y cells to a range of dopamine concentrations (0.1 µM – 600
µM), and measurement of cell viability, a curve fit generated an R2 value of 0.90 and indicated
that the EC20% of dopamine was 11.5 µM (logEC20% = 1.06 ± 0.06, 95% CI [0.94, 1.17]), thus a
concentration of 10 µM dopamine was used in combination with concentration response curves
218
of the other three compounds. The curves fitted to the rotenone and PSI concentration response
curves generated R2 values of 0.64 and 0.71, respectively, indicating a poorer fit than observed
with dopamine, and the need to err on the side of caution with any predicted EC values. Indeed,
visual inspection of the curves indicated that in contrast to dopamine, decreases in cell viability
induced by rotenone and PSI followed an ‘all or none’ pattern, in which there was either no
significant loss of cell viability or almost maximal loss of cell viability, rather than a
concentration-dependent effect. Thus, in the presence of rotenone or PSI, cell viability dropped
from approximately 80 to 90% when cells were exposed to 100 µM of either compound, to 30 to
45% when cells were exposed to 1000 µM. Therefore, in order to avoid causing a large decrease
in cell viability when pairing rotenone or PSI with a second compound, which would mask
synergistic effects, an EC10% concentration of rotenone and PSI was chosen, rather than an EC20%
as with dopamine. Analysis of the concentration response curves of rotenone and PSI indicated
that the EC10% values were 103.3 µM (logEC10% = 2.01 ± 0.09, 95% CI [1.83, 2.20]) and 42.4
µM (logEC10% = 1.63 ± 0.11, 95% CI [1.41, 1.84]) respectively, thus 100 µM rotenone and 50
µM PSI was used when cells were exposed to combinations of compounds. The concentration
response curve for naphthazarin had an R2 value of 0.95 and the EC20% concentration was
determined to be 4.5 µM (logEC20% = 0.65 ± 0.05, 95% CI [0.54, 0.76]). However, in order to
avoid the effects of adding extra DMSO to the cell cultures naphthazarin was dissolved in cell
media for the compound pair experiments. Problems with the solubility of naphthazarin in cell
media led us to use 3 µM naphthazarin in the paired compound experiments, which equates to an
approximate EC value of 15% (logEC15% = 0.50 ± 0.05, 95% CI [0.39, 0.60]).
219
Figure 8.1. Determination of EC10–20% concentrations of dopamine, rotenone, PSI, and
naphthazarin on cell viabililty in SH-SY5Y cells. SH-SY5Y cells were incubated with
dopamine (0.01 µM–600 µM), rotenone (0.1 µM–1 mM), PSI (0.1 µM–500 µM), or naphthazarin
(0.1 µM–1 mM) for 24 hours. Cell viability (% control) was assayed using alamar blue and the
resulting concentration response data were plotted (mean ± SEM). Curves were fitted to the data
using the using the least squares method constrained by a Hill slope of -1 and a curve bottom of
0. The top of the curve was unconstrained. The fitted curves were then used to determine the
EC values and concentrations indicated for each compound.
220
-2 -1 0 1 2 30
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Rotenone, EC10 = 103.3 µM, R2 = 0.64
PSI, EC10 = 42.4 µM, R2 = 0.71Naphthazarin, EC15 = 3.1 µM, R2 = 0.95
Dopamine, EC20 = 11.5 µM, R2 = 0.90
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Characterisation of interactions between cell death mechanisms
Concentration response curves were performed to assess cell viability in response to a dose
response curve of each compound (dopamine, rotenone, PSI, naphthazarin), either alone or in the
presence of an EC10–20% concentration of a second compound. The decrease in the percentage of
viable cells from 100% in the presence of a compound alone (compound 1) was compared with
the decrease in the percentage of viable cells from 100% in the presence of compound 1 plus an
approximate EC10–20% concentration of compound 2. As described above, the EC10-20%
concentrations used were 10 µM dopamine (EC20%), 100 µM rotenone (EC10%), 50 µM PSI
(EC10%), and 3 µM naphthazarin (EC15%).
As an EC20% of compound 2 should produce an additional decrease in cell viability of 20% if the
relationship is simply additive, synergism between the compounds was identified as an
additional decrease in the percentage of viable cells of greater than 25% in the presence of
compounds 1 and 2 in comparison with compound 1 alone for at least two points within the first
five on the concentration response curve. Similarly, where an EC10% or EC15% of compound 2
was added in combination with compound 1, an additive effect would be expected to decrease
cell viability by 10% and 15%, respectively. In these cases, synergism was defined as an
additional decrease in cell viability of 12.5% and 18.75%, respectively, for at least two points on
the concentration response curve for compounds 1 and 2 when compared with compound 1
alone.
Synergism is indicated in Figures 8.2 to 8.5 by diagonal shading. The occurrence of synergism
suggests that the two cell death mechanisms activated by the compounds are part of the same
pathway. An additive effect was defined when the decrease in the percentage of viable cells in
222
the presence of compound 1 and 2 was 20%, 15%, 10% or less depending on the identity of
compound 2, indicating that the compounds cause cell death by independent pathways. In some
cases the combination of compound 1 and 2 produced no additional decrease in cell viability
over compound 1 indicating that the effects of compound 1 occlude the effects of compound 2.
Effect of rotenone, PSI, or naphthazarin on dopamine-induced toxicity
SH-SY5Y cells were exposed to a range of dopamine concentrations (0.01 µM–600 µM) either
alone, or in the presence of an EC10% of rotenone, an EC10% of PSI, or an EC15% of naphthazarin.
Incubation with dopamine alone caused a concentration-dependent decrease in cell viability (Fig.
8.2). The combination of rotenone (100 µM) with dopamine caused a significant additional
decrease in the percentage of viable cells of 25.7%, 27.1%, and 26.2% for 0.1, 1, and 10 µM
dopamine (P < 0.01), respectively, indicating that dopamine and rotenone work synergistically
(Fig 8.2a). Similarly, the addition of PSI (50 µM) to the cells in the presence of dopamine also
caused a synergistic decrease in cell viability, which ranged from 19.0% to 32.6%, for all
concentrations of dopamine between 0.1 µM and 300 µM (P < 0.001) (Fig. 8.2b). In contrast, the
addition of naphthazarin (3 µM) to the dopamine dose response curve only caused an additive
effect with a significant additional decrease in the cell viability of 24.6% only observed for 1 µM
dopamine. For the remaining concentrations of dopamine in the concentration-response curve
the addition of naphthazarin caused additional decreases in the percentage of viable cells of
11.5% to 18.5% (Fig. 8.2c).
223
Figure 8.2. Effect of rotenone, PSI, or naphthazarin on dopamine-induced toxicity. SH-
SY5Y cells were incubated with dopamine (DA, 0.01 µM–600 µM), either alone, or in the
presence of approximate EC10–20% concentrations of (a) rotenone (ROT, 100 µM ≈ EC10%), (b)
PSI (50 µM ≈ EC10%), or (c) naphthazarin (NAP, 3 µM ≈ EC15%) for 24 hours. Cell viability (%
control) was assayed using alamar blue and concentration-response curves were plotted (mean ±
SEM). Diagonal shading indicates a difference of greater than 25% between the two curves for
dopamine and rotenone (a) and a difference of greater than 12.5% between the two curves for
dopamine and PSI (b), which indicates the presence of synergy between the pairs of compounds.
The effect of naphthazarin in combination with dopamine was additive (c). Differences between
the curves were analyzed using two-way ANOVA with Bonferroni’s multiple comparison test
post-hoc. * indicates P < 0.05, ** P < 0.01, and *** P < 0.001. Overall effect of rotenone
treatment: F1,70 = 28.11, P < 0.0001, PSI treatment: F1,70 = 123.9, P < 0.0001, and napthazarin
treatment: F1,70 = 18.20, P < 0.0001.
224
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Effect of dopamine, PSI, or naphthazarin on rotenone-induced
mitochondrial dysfunction
SH-SY5Y cells were exposed to a range of rotenone concentrations (0.01 µM–1000µM) either
alone, or in the presence of an approximate EC20% of dopamine, an EC10% of PSI, or an EC15% of
naphthazarin. Incubation with rotenone alone caused a concentration-dependent decrease in cell
viability (Fig. 8.3). The addition of dopamine (10 µM) to the rotenone concentration-response
curve caused a significant additional decrease in cell viability at all concentrations of rotenone
between 0.01 µM and 100 µM (P < 0.01). The additional decrease in the percentage of viable
cells ranged from 24.8% to 34.0% for the concentrations of rotenone between 0.01 µM and 100
µM indicating that the effects of dopamine and rotenone were synergistic (Fig. 8.3a). The
addition of PSI (50 µM) (Fig. 8.3b) or naphthazarin (3 µM) (Fig. 8.3c) to the rotenone
concentration-response curve both produced a synergistic effect at 1 µM and 10 µM rotenone
producing a decrease in cell viability of 18.5% and 15.8%, respectively with PSI, and 20.3% and
22.6%, respectively with naphthazarin (P < 0.01) (Fig. 8.3 b,c).
226
Figure 8.3. Effect of dopamine, PSI, or naphthazarin on rotenone-induced mitochondrial
dysfunction. SH-SY5Y cells were incubated with rotenone (ROT, 0.01 µM–1000 µM), either
alone, or in the presence of approximate EC10–20% concentrations of (a) dopamine (DA, 10 µM ≈
EC20%), (b) PSI (50 µM ≈ EC10%), or (c) naphthazarin (NAP, 3 µM ≈ EC15%) for 24 hours. Cell
viability (% control) was assayed using alamar blue and concentration-response curves were
plotted (mean ± SEM). Diagonal shading indicates a difference of greater than 25% between the
two curves for rotenone and dopamine (a), a difference of greater than 12.5% between the two
curves for rotenone and PSI (b), and a difference of greater than 18.75% between the two curves
for rotenone and naphthazarin (c), which indicates the presence of synergy between the pairs of
compounds. Differences between the curves were analyzed using two-way ANOVA with
Bonferroni’s multiple comparison test post-hoc. * indicates P < 0.05, ** P < 0.01, and *** P <
0.001. Overall effect of dopamine treatment: F1,70 = 84.01, P < 0.0001, PSI treatment: F1,70 =
16.41, P = 0.0001, and naphthazarin treatment: F1,70 = 37.89, P < 0.0001.
227
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Effect of dopamine, rotenone, or naphthazarin on PSI-induced proteasome
dysfunction
SH-SY5Y cells were exposed to a range of PSI concentrations (0.1 µM–500 µM) in combination
with an approximate EC20% of dopamine, an EC10% of rotenone, or an EC15% of naphthazarin.
Incubation with PSI alone caused a concentration-dependent decrease in cell viability (Fig. 8.4).
Incubation of PSI with dopamine (10 µM) caused a significant additional decrease in cell
viability compared to PSI alone at all concentrations of PSI between 0.1 µM and 500 µM (P <
0.01 for 0.1 µM–10 µM, P < 0.05 for 50 µM and 150 µM, P > 0.05 for 500 µM). The additional
decrease in the percentage of viable cells ranged from 15.5% to 29.8% indicating that PSI and
dopamine act synergistically (Fig. 8.4a). The combination of PSI and rotenone (100 µM) also
produced a synergistic decrease in the percentage of viable cells that ranged from 19.1% to
25.0% for the concentrations of PSI between 0.1 µM and 150 µM (Fig. 8.4b). The addition of
naphthazarin (3 µM) to the PSI concentration-response curve produced additional decreases in
the percentage of viable cells of 16.7% to 19.6% between 0.1 µM and 10 µM PSI indicating that
the effects of napthazarin and PSI were additive, rather than synergistic as the additional
decrease in cell viability was not sustained at 18.75% or greater (Fig. 8.4c).
229
Figure 8.4. Effect of dopamine, rotenone, or naphthazarin on PSI-induced proteasomal
dysfunction. SH-SY5Y cells were incubated with PSI (PSI, 0.1 µM–500 µM), either alone, or
in the presence of approximate EC10–20% concentrations of (a) dopamine (DA, 10 µM ≈ EC20%),
(b) rotenone (ROT, 100 µM ≈ EC10%), or (c) naphthazarin (NAP, 3 µM ≈ EC15%) for 24 hours.
Cell viability (% control) was assayed using alamar blue and concentration-response curves were
plotted (mean ± SEM). Diagonal shading indicates a difference of greater than 25% between the
two curves for PSI and dopamine (a) and a difference of greater than 12.5% between the two
curves for PSI and rotenone (b), which indicates the presence of synergy between the pairs of
compounds. The effect of naphthazarin in combination with PSI was additive (c). Differences
between the curves were analyzed using two-way ANOVA with Bonferroni’s multiple
comparison test post-hoc. * indicates P < 0.05, ** P < 0.01, and *** P < 0.001. Overall effect of
dopamine treatment: F1,70 = 71.06, P < 0.0001, rotenone treatment: F1,70 = 31.73, P < 0.0001, and
naphthazarin treatment: F1,70 = 32.62, P < 0.0001.
230
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Effect of dopamine, rotenone, or PSI on naphthazarin-induced lysosome
dysfunction
SH-SY5Y cells were incubated with a range of naphthazarin concentrations (0.01 µM–1000
µM), either alone, or in combination with an approximate EC20% of dopamine, an EC10% of
rotenone, or an EC10% of PSI. Incubation of the cells with naphthazarin alone caused a
concentration-dependent decrease in cell viability (Fig. 8.5). The addition of dopamine (10 µM)
to the naphthazarin concentration-response curve caused a significant additional decrease in cell
viability at all concentrations of naphthazarin between 0.01 µM and 30 µM (P < 0.001). For 0.01
µM and 0.1 µM naphthazarin the addition of dopamine (10 µM) caused an additional decrease in
the percentage of viable cells of 49.8% and 25.6%, respectively, indicating that the two
compounds were acting synergistically. Although the difference between the concentrations
curves for 1 µM naphthazarin with and without dopamine (10 µM) was only 18.5%, an
additional decrease in the percentage of viable cells of 23.4% was observed for dopamine (10
µM) combined with 10 µM naphthazarin, which suggests that there is synergism between
naphthazarin and dopamine (Fig. 8.5a). The addition of either rotenone (100 µM) or PSI (50
µM) to the naphthazarin concentration-response curve had little effect on the naphthazarin-
induced decrease in cell viability indicating the effects of rotenone and PSI are occluded by the
presence of naphthazarin (Fig. 8.5b,c).
232
Figure 8.5. Effect of dopamine, rotenone, or PSI on naphthazarin-induced lysosomal
dysfunction. SH-SY5Y cells were incubated with naphthazarin (NAP, 0.01 µM–1000 µM),
either alone, or in the presence of approximate EC10–20% concentrations of (a) dopamine (DA, 10
µM ≈ EC20%), (b) rotenone (ROT, 100 µM ≈ EC10%), or (c) PSI (PSI, 50 µM ≈ EC10%) for 24
hours. Cell viability (% control) was assayed using alamar blue and concentration-response
curves were plotted (mean ± SEM). Diagonal shading indicates a difference of greater than 25%
between the two curves and the presence of synergy between naphthazarin and dopamine (a).
The effect of rotenone or PSI was occluded by the presence of naphthazarin, (b) and (c).
Differences between the curves were analyzed using two-way ANOVA with Bonferroni’s
multiple comparison test post-hoc. * indicates P < 0.05, ** P < 0.01, and *** P < 0.001. Overall
effect of dopamine treatment: F1,70 = 247.4, P < 0.0001, rotenone treatment: F1,70 = 2.377, P =
0.1276, and PSI treatment: F1,70 = 1.121, P = 0.2934.
233
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Discussion
Many studies have shown that dysfunction of the mitochondria, proteasome, and lysosome, as
well as increased oxidative stress and elevated protein aggregate formation contribute to cell
death in PD (Hoglinger et al. 2003; Rideout et al. 2001; Sherer et al. 2003). Furthermore, these
studies showed that some of these sub-cellular processes interact to accelerate
neurodegeneration. While previous studies have enabled a better understanding of the
mechanisms underlying neurodegeneration in PD, all the models used require lengthy
preparation times. In order to address this issue we developed a cell model that is simple and
quick to produce with characteristics that appear to mimic those in more sophisticated chronic
models of PD (Yong-Kee et al. 2011). However, due to the cellular nature of this model, caution
should be used in the extrapolation of results to processes underlying neurodegeneration in
patients with PD. Nonetheless, we predict that this simplified system is a useful method for
understanding interactions between intracellular mechanisms that are difficult to study in the
whole animal.
In this study we used our cell model to further characterise the interactions between the various
cell death mechanisms that destroy catecholaminergic neurons. In particular we were interested
in any potential synergistic relationships between different compounds that activate cell death
mechanisms associated with PD. As an EC10–20% of a second compound was added to a full
concentration response curve of the first compound, we defined an additive effect as an
additional decrease in cell viability of 10% to 20% or less, and synergism as an additional
decrease in cell viability of 12.5% to 25% or more for at least two points on the concentration
response curve, depending on the EC value of the second compound. According to this
definition, when combined the two compounds needed to produce an effect that was at least 25%
235
greater than a simple addition of the effects of the two compounds to be identified as synergistic.
The definition also required that the synergistic effect be present for at least two points within the
first five of the concentration curve. Thus, we were able to identify pairs of compounds where
there was synergism, and also whether this synergism was reciprocally mediated.
The results of this study indicate that oxidative stress has synergistic effects on all other cell
death mechanisms, causing a greater decrease in cell viability than would be expected from
combining the individual effects of activating each pathway. For mitochondrial and proteasomal
dysfunction the synergism with oxidative stress was reciprocal but the relationship between
lysosomal dysfunction and oxidative stress was only unidirectional (Fig. 8.6), with an EC20%
concentration of dopamine enhancing cellular impairment caused by naphthazarin, but not vice
versa. A possible explanation for this is that, as well as being involved in protein degradation,
the lysosome also accumulates free radicals, to reduce oxidative stress. Thus, when the
lysosome is inhibited, addition of even low levels of dopamine may have a more dramatic effect
because the cells have less ability to remove the quinones and reactive oxygen species generated
through dopamine metabolism, enhancing the sensitivity of the cell to dopamine. This finding
also suggests that oxidative stress may occur as a consequence of lysosomal dysfunction. The
uni-directionality of the effect indicates that lysosomal-independent oxidative stress through
addition of dopamine does not affect lysosome function. This lack of reciprocality is probably
due to the ‘all or nothing’ effect of naphthazarin on cell death, meaning that once the lysosome is
significantly damaged, the cell has probably reached a point of no return, with regards to loss of
cell viability, thus inhibition of proteasomal or mitochondrial function will have relatively little
impact. Thus, whilst there appears to be close relationships between mitochondrial and
proteasomal dysfunction and oxidative stress, decreased cell viability as a consequence of
lysosome dysfunction is a relatively independent cell death pathway.
236
Figure 8.6. Schematic diagram to show the interactions between the different mechanisms
in relation to changes in cell viability. Proteasomal, lysosomal, and mitochondrial dysfunction
form independent cell death pathways. Furthermore, proteasomal, lysosomal and mitochondria
dysfunction are exacerbated by oxidative stress. In addition there are reciprocal links between
oxidative stress, proteasomal dysfunction, and mitochondrial dysfunction.
237
Mitochondriadysfunction(rotenone)
Proteasome dysfunction
(PSI)
Oxidative stress
(dopamine)
Lysosomedysfunction
(naphthazarin)
238
Previous studies have shown that cell death caused by mitochondrial and proteasomal
dysfunction, as well as oxidative stress synergise to further enhance cell death (Hoglinger et al.
2003; Rideout et al. 2001; Sherer et al. 2003). The current studies take our understanding of cell
death mechanisms in PD further to show the relationship between these cell death mechanisms
and lysosomal dysfunction. Based on these studies, it appears that oxidative stress enhances
mitochondrial, lysosomal and proteasomal dysfunction in a synergistic manner. Furthermore, as
we have previously described, whether the site of the primary insult is the lysosome, proteasome,
mitochondria or increased oxidative stress, the mitochondria always become impaired (Yong-
Kee et al., 2012). Thus, all cell death mechanisms appear to converge on mitochondrial
dysfunction (Greenamyre and Hastings, 2004; Yong-Kee et al., 2012).
These studies suggest that an effective neuroprotective therapy in PD would need to target
multiple cell death pathways. Given that oxidative stress has a universal synergistic effect, and
that mitochondria are affected by all cell death mechanisms, perhaps decreasing oxidative stress
combined with enhancing mitochondrial health may prove to be the two most effective targets
for neuroprotective agents. Exposure of SH-SY5Y cells to a battery of compounds that
recapitulate the cell death mechanisms in PD, as was done here, in combination with potential
neuroprotective therapies may be a rapid and reliable method for screening such compounds.
239
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