establishment of an alginate based 3d culture system for
TRANSCRIPT
Michael von Troyer, 01216463
Establishment of an alginate based 3D culture system for
the generation of dopaminergic neurons
MASTER THESIS
Submitted at the Faculty of Biology
Master's Program Molecular Cell and Developmental Biology
LEOPOLD-FRANZENS-UNIVERSITÄT INNSBRUCK
and
performed at the
Institute for Biomedicine – Neuromedicine group
Eurac Research, Bolzano
Supervisor:
Univ-Prof. Dr. Frank Edenhofer
Institute of Molecular Biology, Genomics, Stem Cell Biology and Regenerative Medicine
Faculty of Biology
External Supervisor
Dr. Alessandra Zanon
Institute for Biomedicine at Eurac Research
Innsbruck, 2020
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TABLE OF CONTENTS
TABLE OF CONTENTS ................................................................................................................................ I
1. ACKNOWLEDGMENTS ..................................................................................................................... 1
2. ABSTRACT ........................................................................................................................................ 2
3. INTRODUCTION ............................................................................................................................... 4
3.1. Parkinson’s disease (PD) .......................................................................................................... 4
3.1.1. Clinical and pathophysiological features of PD ............................................................... 4
3.1.2. Genetic causes of PD ....................................................................................................... 6
3.2. Modeling human neurological disease by using induced pluripotent stem cells (iPSCs) ....... 9
3.2.1. iPSCs and disease modeling............................................................................................. 9
3.2.2. Midbrain dopaminergic neuronal differentiation ......................................................... 10
3.3. 3D cell culture models and techniques ................................................................................. 12
3.3.1. Extracellular Matrices (ECM) and Hydrogels ................................................................. 14
3.3.2. Alginate .......................................................................................................................... 15
3.3.3. Applications of 3D cultures in vitro ............................................................................... 17
4. AIM OF THE STUDY ........................................................................................................................ 19
5. PATIENTS, MATERIALS AND METHODS ......................................................................................... 20
5.1. Patients .................................................................................................................................. 20
5.2. Materials ................................................................................................................................ 20
5.2.1. Chemicals ....................................................................................................................... 20
5.2.2. Western blot solutions .................................................................................................. 21
5.2.3. Cell culture reagents, differentiation factors, and coating materials ........................... 22
5.2.4. Cell culture media .......................................................................................................... 23
5.2.5. Kits ................................................................................................................................. 23
5.3. Methods ................................................................................................................................ 24
5.3.1. hiPSC culture and passaging .......................................................................................... 24
5.3.2. Harvesting and counting cells for neuronal in vitro differentiation .............................. 24
5.3.3. Monolayer midbrain dopaminergic differentiation of iPSCs ......................................... 24
5.3.4. Alginate bead midbrain dopaminergic differentiation of iPSCs .................................... 25
5.3.5. Preparation of alginate solution .................................................................................... 25
5.3.6. Alginate bead formation and culture ............................................................................ 26
5.3.7. Decapsulation and replating of differentiated cells from alginate beads ..................... 26
5.3.8. Cell viability assay .......................................................................................................... 26
5.3.9. Real-time quantitative PCR (RT-qPCR) .......................................................................... 27
II
5.3.10. Gel analysis of RT-qPCR products .................................................................................. 28
5.3.11. Western blot analysis .................................................................................................... 28
5.3.12. Mitochondrial superoxide detection ............................................................................. 30
5.3.13. Immunofluorescence staining ....................................................................................... 30
5.3.14. Vibratome sectioning of alginate beads/cell aggregates .............................................. 33
5.3.15. Electrophysiological characterization ............................................................................ 33
6. RESULTS ......................................................................................................................................... 34
6.1. Test of different matrix compositions ................................................................................... 34
6.1.1. Validation of the beneficial effect of Rho-associated kinase inhibitor treatment on
alginate encapsulated iPSCs .......................................................................................................... 34
6.1.2. Number of cell aggregates within alginate of different compositions .......................... 36
6.1.3. Size of cell aggregates within alginate of different compositions ................................. 36
6.2. Fibronectin supports cell viability during differentiation ...................................................... 38
6.3. Comparative RT-qPCR suggests enhanced mDA differentiation ........................................... 40
6.4. Molecular analysis of early mDA neural differentiation ....................................................... 42
6.4.1. Immunofluorescence staining ....................................................................................... 42
6.4.2. Western blot analysis .................................................................................................... 47
6.5. Electrophysiological analysis of the neuronal cultures ......................................................... 49
6.6. Mitochondrial reactive oxygen species (mROS) .................................................................... 51
6.7. Molecular analysis of long-term mDA neural differentiation on 3D platform ...................... 52
7. DISCUSSION ................................................................................................................................... 57
7.1. Patient-specific neuronal cell models for PD research ......................................................... 57
7.2. Setup of 3D system by encapsulation of hiPSCs with alginate hydrogels ............................. 57
7.3. mDA neuronal differentiation of hiPSCs in 3D alginate culture system ................................ 60
8. SUMMARY ..................................................................................................................................... 63
9. PERSPECTIVES ................................................................................................................................ 64
10. REFERENCES .................................................................................................................................. 65
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1. ACKNOWLEDGMENTS
At this point, I would like to thank all the people that supported me during the pursuit of the present
thesis. First, I would like to thank my supervisor at the Institute for Biomedicine at EURAC Research,
Dr. Alessandra Zanon, for her advice, constant motivation and great patience.
Special thanks go to Diana Riekschnitz, who was always ready to kindly provide me technical support
regarding the daily laboratory routine, Dr. Alexandros Lavdas for his dedication to the analysis of the
large number of images I produced, Dr. Luisa Foco for providing her expertise regarding the analysis
of RT-qPCR data, as well as Dr. Irene Pichler and Dr. Daniel Wojciechowski for their suggestions
regarding parts of the written thesis. I am also grateful to the Group Leader of the Neuromedicine
group, Dr. Andrew A. Hicks, for making it possible for me to perform this master thesis at the
Institute for Biomedicine at EURAC Research. I want to emphasize my gratitude to all the other
members of the Institute for Biomedicine that I had the pleasure of getting to know and thank them
for their professional support, interesting discussions and the enjoyable conversations during lunch
break which often brightened up my day. Furthermore, I want to thank my internal supervisor at the
Leopold Franzens University of Innsbruck, Univ-Prof. Dr. Frank Edenhofer for opening up the
possibility to perform this external thesis at the Institute for Biomedicine at EURAC Research.
Finally, I would like to give my special thanks to my girlfriend, family and friends for their love and
support.
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2. ABSTRACT
During the last century, the prevalence of chronic age-related neurodegenerative diseases increased
due to prolonged ageing. Parkinson’s disease (PD) is the second most common neurodegenerative
disorder, affecting 2-3% of the population over age 65 (Poewe et al. 2017). It is characterized by the
deterioration of melanin-containing midbrain dopaminergic neurons in the substantia nigra, which
leads to a set of motor dysfunctions accompanied by non-motor symptoms, both strongly affecting
the patient’s quality of life.
The use of induced pluripotent stem cells (iPSCs) enables the generation of patient-specific neuronal
subpopulations, posing a possibility to overcome the restricted accessibility to disease-affected tissue
for mechanistic studies on PD. However, standardized protocols are needed allowing highly efficient,
cell type specific differentiation. In fact, existing culture systems for neuronal differentiation show a
variable reproducibility and yield neurons with a relatively low degree of functional maturation.
Thus, in this work we attempted to evaluate a new in vitro cell culture model for the neuronal
differentiation of iPSCs within a three dimensional (3D) alginate hydrogel matrix in order to obtain a
cell population more enriched with terminally differentiated neurons relevant for the cellular
modeling of PD (midbrain dopaminergic neurons). We studied the suitability of alginate as 3D
biomaterial scaffold to support mDA differentiation of iPSCs in vitro. Therefore, we evaluated 1% and
2% alginate solutions alone and in combination with the extracellular matrix component fibronectin
in terms of their effect on cell viability and differentiation.
Our results show that iPSCs embedded in alginate proliferate and form cellular aggregates. We found
that the treatment with Rho associated kinase inhibitor Y-27632, previously reported to be essential
for embryonic stem cell survival after cell encapsulation in crosslinked alginate, is crucial also for iPSC
survival after encapsulation. Furthermore, we demonstrate that the addition of fibronectin
significantly increases the number and size of aggregates forming in the alginate scaffold.
By using RT-qPCR at day 10 and 20 of differentiation, we have found that overall neuronal as well as
mature dopaminergic neuron marker gene expression was significantly increased in 1% and 2%
alginate with fibronectin with respect to two-dimensional cultures. These findings are further
supported by immunofluorescence staining generated for a subset of neuronal markers.
To assess functional maturation, we evaluated the electrophysiological functionality of our
differentiated cells at day 30 via whole-cell patch clamp analysis. Active as well as passive
electrophysiological parameters support the increased functionality of neurons grown in alginate
scaffolds with respect to the 2D differentiated cells.
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Furthermore, we have shown that differentiated dopaminergic neurons can be cultured in our
alginate based 3D culture system for more than 200 days and have confirmed the presence of
synaptic connections via immunofluorescence staining for pre- and post-synaptic markers at this
stage.
In summary, we demonstrate that the described alginate based 3D cell culture system is a viable
alternative to conventional adherent culture methods.
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3. INTRODUCTION
3.1. Parkinson’s disease (PD)
3.1.1. Clinical and pathophysiological features of PD
Parkinson’s disease (PD) is known as the second most frequent neurodegenerative disorder affecting
2-3% of the population older than 65 years of age (Poewe et al. 2017). It is characterized clinically by
the cardinal motor symptoms resting tremor, bradykinesia (slow movements), rigidity (stiffness) and
postural instability (Lang and Lozano 1998) and pathologically by the selective degeneration of the
dopaminergic (DA) neurons residing in the substantia nigra pars compacta (SNpc) of the ventral
midbrain. Another PD hallmark is the occurrence of intracellular protein aggregates called Lewy
bodies (Wakabayashi et al. 2013; Damier et al. 1999). Even though the clinical picture of PD was
already known in the ancient indian medical system Ayurveda (from 4500-1000 B.C), it was first
described in modern times by James Parkinson, a british doctor and surgeon in 1817 (Manyam 1990;
Lang and Lozano 1998). Since then advances in treatment allow for the effective alleviation of
symptoms and management of the disease but none of the developed treatment methods is curative
(Poewe et al. 2017). In addition to the cardinal motor symptoms, PD patients may show secondary
motor symptoms such as gait disturbance, micrographia, precision grip impairment, and speech
problems. (Moustafa et al. 2016).
Besides these frequently cited motor symptoms, a variety of widespread non-motor symptoms
(NMSs) associated with PD have been described. An Italian study found that the most frequently
reported NMSs are of psychiatric nature. Less frequently, sleep symptoms, gastrointestinal
symptoms and pain are reported (Barone et al. 2009). NMSs are generally already present at disease
onset and some might be observable in the prodromal phase of the disease (Trinh and Farrer 2013).
Hyposmia, constipation, and sleep disorders might even be present up to 20 years before
manifestation of the characteristic motor symptoms (Ascherio and Schwarzschild 2016; Poewe 2017).
PD is assumed to be a multisystemic disorder caused by progressive death of selected but
heterogeneous populations of neurons. Among these neuronal populations, the dopaminergic, and
neuromelanin-containing neurons residing in the SNpc are thought to be highly susceptible.
Estimations indicate that 60-70% of such neurons have already been lost in the ventrolateral layer of
the SNpc at disease onset (Fig. 1). This results in dopamine depletion of the striatum (caudate
nucleus and putamen) as these neurons are forming the nigrostriatal pathway (Lang and Lozano
1998).
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At the cellular level, an important hallmark of PD is the presence of compact neuronal cytoplasmic
inclusions named Lewy bodies (LBs). The protein α-synuclein is the main component of LBs. α-
synuclein-oligomers and protofibrils are known to be cytotoxic. However, it is unclear whether the
formation of LBs causes cell death or, at least initially, represents a protective mechanism (Beyer et
al. 2009; Braak and Del Tredici 2017). More than 70 other proteins from a variety of classes were
described to contribute to these inclusions (Beyer et al. 2009; Deng et al. 2018). Notably, also other
gene products associated with familial PD, discussed in the following section, were found among the
components forming LBs (Beyer et al. 2009). Neither depletion of DA neurons in the SNpc nor the
presence of LBs alone are of diagnostic value for PD as the latter are found also in the context of
other neurodegenerative disorders, such as Alzheimer’s disease, in the absence of nigral
degeneration. However, their combination is specific for a definitive diagnosis of idiopathic PD
(Poewe et al. 2017; Corti et al. 2011).
FIGURE 1. Neuropathological hallmarks of PD. (a) Macroscopical (inset) and transverse sections of
the midbrain upon immunohistochemical staining for tyrosine hydroxylase (TH), the rate limiting
enzyme for the synthesis of dopamine, are shown. Depigmentation of the SNpc and selective loss of
the ventrolateral parts of the SNpc (right panel) are visible compared to control (left panel). (b-d)
Haematoxylin and eosin staining of the ventrolateral region of the SN showing a normal distribution
of pigmented neurons in a healthy control (part b) and diagnostically significant moderate (part c) or
severe (part d) pigmented cell loss in PD . (e-g) Immunohistochemical staining of α-synuclein shows
round, intracytoplasmic LBs (arrow in part e), more diffuse, granular deposits of α-synuclein (part e
and part f), deposits in neuronal cell processes (part f), extracellular dot-like α-synuclein structures
(part f) and α-synuclein spheroids in axons (part g ) (Poewe et al. 2017).
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3.1.2. Genetic causes of PD
Prior to 1997, epidemiological findings and twin studies led to the believe that the occurrence of PD
was merely determined by environmental factors (Farrer 2006). This assumption was supported by
the fact that a large number of parkinsonism cases were discovered to be linked with exposition to
pathogens or chemical substances. The term parkinsonism refers to a clinical syndrome found in PD
but also many other conditions. It is characterized by bradykinesia and rigidity and/or rest tremor
(Poewe et al. 2017).
However, beginning with the discovery of SNCA (also PARK1/4) mutations linked to PD in 1997 and
the demonstration that the corresponding presynaptic protein α-synuclein is a major component of
filamentous LBs, the link between genetic mutations and PD has become increasingly clear (Corti et
al. 2011).
TABLE 1. Gene loci and disease-causing genes in PD (Deng et al. 2018).
LOCUS LOCATION GENE SYMBOL
FULL GENE NAME INHERITANCE DISEASE ONSET
LEWY BODIES
PARK1/4 4q22.1 SNCA Alpha synuclein AD Early onset, late-onset*
C
PARK2 6q26 PRKN Parkin RBR E3 ubiquitin protein ligase AR Early-onset NC PARK3 2p13 Park3 Parkinson disease 3 AD Late-onset NC PARK5 4p13 UCHL1 Ubiquitin C-terminal hydrolase L1 AD Early-onset, late-
onset* NC
PARK6 1p36 PINK1 PTEN induced putative kinase 1 AR Early-onset NC PARK7 1p36.23 PARK7 (DJ-1) Parkinsonism associated deglycase AR Early-onset NC PARK8 12q12 LRRK2 Leucine rich repeat kinase 2 AD Late-onset C PARK9 1p36.13 ATP13A2 ATPase 13A2 AR Early-onset NC PARK10 1p32 PARK10 Parkinson disease 10 Unclear Late-onset NC PARK11 1q37.1 GIGYF2 GRB10 interacting GYF protein 2 AD Late-onset NC PARK12 Xq21-q25 PARK12 Parkinson disease 12 X-linked
inheritance Late-onset NC
PARK13 2p13.1 HTRA2 HtrA serine peptidase 2 AD Late-onset, early-onset*
NC
PARK14 22q13.1 PLA2G6 Phospholipase A2 group VI AR Early-onset NC PARK15 22q12.3 FBXO7 F-box protein 7 AR Early-onset NC PARK16 1q32 PARK16 Parkinson disease 16 Unclear Late-onset NC PARK17 16q11.2 VPS35 VPS35, retromer complex component AD Late-onset NC PARK18 3q27.1 EIF4G1 Eukaryotic translation initiation
factor 4 gamma 1 AD Late-onset NC
PARK19 1p31.3 DNAJC6 DnaJ heat shock protein family (Hsp40) member C6
AR Early-onset NC
PARK20 21q22.1 SYNJ1 Synaptojanin 1 AR Early-onset NC PARK21 20p13 TMEM230 Transmembrane protein family 230 AD Late-onset, early-
onset* C
PARK22 7p11.2 CHCHD2 Coiled-coil-helix-coiled-coil-helix domain containing 2
AD Late-onset, early-onset*
NC
PARK23 15q22.2 11p15.4
VPS13C RIC13
Vacuolar protein sorting 13 homolog C RIC3 acetylcholine receptor chaperone
AR AD
Early-onset Late-onset, early onset*
NC NC
AD: autosomal dominant. AR: autosomal recessive. *: few cases. C: confirmed. NC: not confirmed.
To date, 23 loci and 19 autosomal disease-causing genes linked to parkinsonism, including 10
dominant and 9 recessive genes were identified (Tab. 1). About 15% of PD patients have family
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history and 5-10% suffer from a monogenic form of the disease with Mendelian inheritance (Deng et
al. 2018). These findings led to the distinction between familial PD, which is thought to be caused by
single mutations in a variety of genes inherited in a dominant or recessive Mendelian manner, and
idiopathic (sporadic) PD, a multifactorial disease modulated by both environmental factors and
genetic susceptibility. Notably, the genetic aspect of idiopathic PD was highlighted by genome-wide
association studies, which detected a number of respective genetic risk loci and variants. Overall,
these molecular findings point to a series of pathological events involving deficits in synaptic
exocytosis and endocytosis, endosomal trafficking, lysosome‑mediated autophagy, mitochondrial
maintenance and kinase-signaling pathways (see Fig. 2; Trinh and Farrer 2013; Deng et al. 2018).
FIGURE 2. Molecular mechanisms involved in Parkinson disease. An overview of the major
molecular pathways implicated in the pathogenesis of Parkinson disease and their interactions
(Poewe et al. 2017).
Even though the familial cases of PD account only for a small part of the overall disease burden, they
deserve much attention. Their exploration may greatly enhance the understanding of the more
common idiopathic condition by revealing underlying molecular disease mechanisms (Trinh and
Farrer 2013).
SNCA was the first gene found to be associated with PD and encodes the presynaptic neuronal
protein α-synuclein. It contains 6 exons, spans 117 kb and is translated to a small, approximately 15
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kDa protein comprised of 140 amino acids. The PD-linked mutations in SNCA include dominantly
inherited amino acid substitutions and genomic multiplications (Trinh and Farrer 2013). Abnormal
aggregation of α-synuclein, a consequence of its misfolding, leads to the formation of toxic fibrils,
which are thought to affect cellular homeostasis and to cause neuronal death. Interestingly, an
overexpression of wildtype α-synuclein suffices to cause dose dependent disease phenotypes in
human carriers of SNCA multiplications (Fuchs et al. 2007; Corti et al. 2011). Several post-
translational modifications as well as impaired degradation by the ubiquitin-proteasome system
(UPS) and lysosomal pathways are influencing its propensity to aggregate (Fig. 2). Moreover, a prion-
like propagation has been proposed as mechanism of α-synuclein aggregation (Poewe et al. 2017).
This hypothesis suggests that aggregated α-synuclein can spread intra-axonally and seed aggregation
of endogenous α-synuclein upon endocytosis in new host cells.
The large 51-exon gene coding for the multi-domain protein leucine-rich repeat kinase 2 (LRRK2; also
PARK8) represents another important gene linked to autosomal dominantly inherited PD. The LRRK2
protein has well-defined GTPase and kinase functions and multiple biological roles in striatal
neurotransmission, neuronal arborization, endocytosis, autophagy and immunity. The clinical
phenotype of patients with mutations in this gene consists, in most cases, in a late-disease onset and
closely resembles idiopathic PD (Corti et al. 2011; Trinh and Farrer 2013). The pathology of LRRK2
related PD is heterogenous and characterized by incomplete penetrance. LRRK2 mutations usually
result in gain-of-function, with increased GTPase and kinase activity (Deng et al. 2018).
Less than 4% of PD cases in the community are classified as early-onset (≤45 years of age at
diagnosis) or juvenile parkinsonism (≤20 years of age at diagnosis). The majority of early-onset
autosomal recessive PD cases (about 15%) can be explained by parkin loss-of-function mutations
(Trinh and Farrer 2013). The PRKN gene (also PARK2) encodes for parkin, a 465 amino acid protein
which functions as an E3 ubiquitin ligase and is associated to mitochondrial quality control and
turnover. Parkin is primarily cytosolic but is recruited selectively and rapidly to the outer
mitochondrial membrane of depolarized mitochondria upon mitochondrial membrane dissipation to
act as a protective and anti-apoptotic factor by promoting mitophagy (Narendra et al. 2008). Parkin
activity is regulated by phosphorylation through the mitochondrial serine/threonine kinase PTEN-
induced putative kinase 1 (PINK1). In vitro findings demonstrated that PINK1-parkin signaling plays an
important role in mitochondrial quality control by regulating stimulus-induced mitochondrial
clearance (McWilliams and Muqit 2017).
Autosomal recessively inherited loss-of-function mutations in the PINK1 (also PARK6) gene represent
the second most frequent cause of autosomal recessively inherited early-onset PD. In normal
mitochondria, PINK1 transfers to the inner mitochondrial membrane were it is cleaved. In
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dysfunctional mitochondria, it accumulates in the outer mitochondrial membrane and, in
collaboration with parkin, facilitates the removal of damaged mitochondria. PINK1-KO rats and
PINK1-mutant Drosophila both show DA neuronal loss and motor dysfunctions while DA
neurodegeneration has been identified in homozygous PINK1-KO mice only upon induction of α-
synuclein or MPTP-toxicity (Deng et al. 2018).
The least common form of early-onset autosomal recessively inherited parkinsonism is caused by
mutations in the DJ-1 gene (also PARK7). DJ-1 codes for a 189 amino acid protein, which is a member
of the ThiJ/Pfp1 family of molecular chaperons. Like parkin, DJ-1 is predominantly cytosolic but it
translocates from the cytoplasm to the outer mitochondrial membrane in the presence of oxidative
stress. Thus, it is thought to be involved in neuroprotection. Interestingly, overproduction of DJ-1
partially rescues the phenotype caused by loss of PINK1 but not loss of parkin function in Drosophila.
This points to DJ-1 as acting in a parkin-independent pathway downstream of PINK1. There is no
possibility to distinguish between the clinical phenotypes of PRKN-, PINK1-, and DJ-1- linked PD (Corti
et al. 2011).
3.2. Modeling human neurological disease by using induced pluripotent stem
cells (iPSCs)
3.2.1. iPSCs and disease modeling
In 2006, Takahashi and Yamanaka were able to show the feasibility of cellular de-differentiation from
mouse embryonic fibroblasts (MEF) to iPSCs. They narrowed the selection of genes necessary for the
reprogramming process down to the four so-called Yamanaka factors Klf4, Oct4, Sox2 and c-Myc. The
resulting iPSCs were able to differentiate into derivatives of all three germ layers (ectoderm,
mesoderm, and endoderm) and hold the potential of unlimited capacity for self-renewal (Takahashi
and Yamanaka 2006).
Several approaches have been established for the delivery of the reprogramming factors including
integrating and non-integrating viral vectors, BAC transposons, episomal vectors, proteins and RNA
delivery (Hu and Li 2016). Additionally, during the last decade, substantial efforts have been made to
replace the protein reprogramming factors by small molecules. These are thought to be safer, more
effective and easier to apply (Ma et al. 2017).
The advent of iPSC technology in combination with subsequent differentiation into various cell-types,
such as neurons, cardiomyocytes, myocytes or hepatocytes, has been a breakthrough for the
biomedical field. It enabled patient specific cellular modeling of a large number of diseases and high
throughput drug validation in the context of personalized precision medicine. One of the greatest
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advantages of this approach is the generation of nearly unlimited numbers of tissue-specific cells
from autologous patient material, which allows for examination of disease specific cellular
phenotypes on the level of individual patients. This is especially important when the accessibility of
affected tissue is not given or linked to a high risk of collateral damage as in the case of neurological
diseases (Playne and Connor 2017).
Importantly, disease related cellular phenotypes could be observed for inherited and also idiopathic
forms of PD using cellular reprogramming technology in several studies (Jungverdorben et al. 2017;
Playne and Connor 2017). Byers et al. showed an increased expression of genes involved in oxidative
stress, protein aggregation and cell death in patient iPSC-derived DA neurons with an SNCA
triplication compared to controls (Byers et al. 2011).
Although the field of PD modeling has advanced with the help of cell-reprogramming, there remain a
number of challenges. iPSC lines can vary significantly regarding their disease-specific phenotype,
even if they are derived from the same individual (Jungverdorben et al. 2017). Even within a cell line,
cell-to-cell variability of the re-differentiated cells is high. Thus improving and choosing the
appropriate differentiation protocols will be essential for the validity of future studies.
3.2.2. Midbrain dopaminergic neuronal differentiation
The in vivo specification and differentiation of midbrain dopaminergic (mDA) neurons has been an
intense area of investigation during the last decades. This research has enabled the in vitro
generation of neurons as a potential cell source for cell replacement therapies, disease modeling,
drug discovery and other applications including the study of DA neuron physiology (Arenas et al.
2015).
DA neurons are characterized by the release of the catecholaminergic neurotransmitter dopamine
and the expression of tyrosine hydroxylase (TH), the rate limiting enzyme in the synthesis of
catecholamines. These neurons are found all over the mammalian central nervous system (CNS),
including the ventral midbrain, and can be divided into three distinct nuclei: the SNpc (A9 group), the
ventral tegmental area (A10 group) and the retrorubral field (A8 group) (Dahlstroem and Fuxe 1964;
Björklund and Hökfelt 1983). The A10 and A8 group neurons co-determine emotional behavior,
natural motivation, reward and cognitive function. In contrast, the A9 group neurons, residing in the
SNpc of the ventral midbrain, are intimately connected to the dorsolateral striatum forming the
nigrostriatal pathway, which predominantly influences motor function and is disrupted in PD.
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Protocols to induce the differentiation of DA neurons starting from iPSCs can rely on different
principles. One strategy is the blockage of activin/TGFb and BMP signaling pathways by dual SMAD
inhibition. These and other morphogenic signaling pathways are active in embryonic regions with a
mesodermal or endodermal fate and are inhibited by various inhibitors in regions destined to
become neuroectoderm (Alberts 2015; Sanes et al. 2012). However, endogenous inhibitors can be
replaced by small molecules such as LDN193189 for in vitro neural induction as shown in a number of
studies (Boergermann et al. 2010).
Once neural induction is initialized, cell fate has to be further specified in order to obtain the desired
cell-type corresponding to the DA neurons degenerating in the ventral midbrain of PD patients. This
can be achieved by exposition to the morphogen sonic hedgehog (SHH). SHH is expressed in the
notochord during embryogenesis which induces SHH expression in the most ventral region of the
neural tube, the floorplate (FP), which serves as a signaling center controlling ventral identities
(Placzek and Briscoe 2005; Sanes et al. 2012). Smoothened agonists like Purmorphamine and SAG can
be used to substitute or support recombinant human SHH for in vitro differentiation (Sinha and Chen
2006).
In addition to the exposition to SHH as a ventralizing factor, there has to take place specification
towards midbrain specific lineages. This can be attained by the exposition to recombinant Wnt1 and
FGF8, two signaling molecules that together play an important role in vivo in the formation of the
isthmic organizer (IsO), a signaling center defining the midbrain-hindbrain boundary. For in vitro
differentiation the small molecule GSK3-inhibitor CHIR99021 can be used to stimulate the canonical
Wnt signaling pathway and substitute recombinant Wnt1 (Reinhardt et al. 2013).
Interestingly, at a certain point SHH has to be downregulated in order to permit mDA neurogenesis.
The main factor repressing SHH seems to be Wnt1 (Joksimovic et al. 2009). However there is
evidence that BMP5 and BMP7 signaling, mediated by SMAD1 and SMAD5, may also be involved in
this process and promote mDA neurogenesis in vivo as well as in human iPSCs and neural stem cells
(Jovanovic et al. 2018).
The differentiation of mDA neurons after neurogenesis is regulated by early factors, which in turn
promote the activity of late transcription factors which regulate the production of appropriate
neurotrophic factors and neurotransmitters. A great collection of neurotrophic factors enhancing
mDA neuron survival in vitro has been identified including the transforming growth factor (TGFβ2/3),
brain-derived neurotrophic factor (BDNF) and members of the glial cell-line derived neurotrophic
factor (GDNF) family (Hegarty et al. 2013, 2014; Arenas et al. 2015). These neurotrophic factors
together with molecules shown to increase the yield of differentiation, such as ascorbic acid and
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cAMP, are added to the DA progenitors to induce the final differentiation (Volpicelli et al. 2004;
Michel and Agid 1996). The duration of this final step varies between protocols and significantly
influences the neuronal maturity (Hartfield et al. 2014; Sanes et al. 2012).
3.3. 3D cell culture models and techniques
The functionality and health of organs and tissues relies on the functionality of the cells, their
integrity within the tissue and the extracellular microenvironment. Techniques for ex-vivo culturing
single cells and tissues have been developed largely during the last century. The culture of cancerous
cell lines has been established to overcome limited cell division capacities of primary animal cells.
These achievements greatly expanded the knowledge about cellular and molecular biology and
enabled in vitro drug discovery and diagnostics (Dutta and Dutta 2018).
To date, adherent cells are mostly grown on rigid plastic surfaces of culture vessels were they form a
monolayer. Non-adherent cells are cultured suspended in growth medium. Although these methods
provided many insights and enabled the development of vaccines and production of recombinant
proteins, in the long run, these cells do not fully replicate the functionality of their in vivo
counterparts. The rigid plastic or glass surfaces and growth media supplemented with fetal serum
used for 2D cell culture create a non-natural environment (Dutta and Dutta 2018). Moreover,
mammalian cells are structurally supported by the extracellular matrix (ECM), a hydrated
composition of fibrous proteins and glycosaminoglycans. The local composition and properties of the
ECM were revealed to play important roles during embryonic development because they affect cell
growth, differentiation (Bissell and Barcellos-Hoff 1987; Frantz et al. 2010) and cell migration (Perris
and Perissinotto 2000). Consistently, it has been demonstrated that cells or tissues cultured on 2D
substrates do not recapitulate in vivo cell growth and expression of tissue-specific genes (Geckil et al.
2010).
Three dimensional (3D) cell culture methods were already established in the middle of the 20th
century (Dutta and Dutta 2018). Later it was shown in collagen gel cultures that tissue architecture
represents an important factor affecting growth and drug sensitivity (Miller et al. 1985). This
knowledge is well established by now, and modern 3D culture techniques in combination with
genome editing methods are important approaches enabling disease modeling, tissue engineering,
drug screening and ultimately cell replacement therapies (Fig. 3).
13
FIGURE 3. Different approaches for deriving human 3D cultures. Human pluripotent stem cells
(hPSCs) derived from a blastocyst or by reprogramming of somatic cells, adult stem cells or cancer
cells derived from primary tissue can be used to derive microfluidics-based organs-on-a-chip (top),
undirected organoids (middle), and region-specific brain organoids or organ spheroids (bottom).
These 3D cultures can be manipulated with CRISPR–Cas9 and other genome-editing technologies,
transplanted into animals or used for drug screening (Pașca 2018).
The behavior of stem cells is regulated by the mechanical properties of their microenvironment
independent of biochemical cues (Saha et al. 2008). More specifically, the early neurogenic
differentiation of human pluripotent stem cells (hPSCs) is supported by soft substrates with
stiffnesses comparable to neural tissue. When the optimal substrate modulus for neurogenic
differentiation is exceeded this support vanishes, while hPSC colony spread area increases (Keung et
al. 2012). Even cell geometrical cues seem to play an important role as they are thought to alter
various cellular characteristics and thereby cell fate (Bao et al. 2017).
In this context, it is worth noticing that neurons in 3D cultures, in contrast to those grown in two
dimensions, embed themselves in a secreted ECM network (Wang et al. 2005; Grayson et al. 2004;
Bonaventure et al. 1994). Besides cell-ECM contacts, also cell-cell interaction and communication are
thought to be important for in vitro cultured cells to acquire tissue like functionality (Pașca 2018;
Wang et al. 2009). This is highlighted by the study of modular brain spheroids used to model inter-
regional communication. While the migration of GABAergic interneurons towards glutamatergic
14
cerebral cortex neurons could be observed in 3D cultures, it was almost absent in 2D systems (Birey
et al. 2017).
Spheroids are generally defined as cellular aggregates not adhering to a culture substrate. Their
generation is achieved by non-adherent cell culturing methods and does not rely on a provided
scaffold or foreign materials. Typically, spheroids can be formed by dissociation and reaggregation
via culture in low cell adhesion plates, in hanging drops (Fennema et al. 2013) or by exposing the cells
to shear forces in spinner flasks as described by Sutherland et al., who employed the method for the
modeling of carcinoma tissue (Sutherland et al. 1971). However, more recent techniques enable the
increasingly reproducible fabrication of large numbers of complex organotypical spheroids (see Fig.
3; Fennema et al. 2013).
The growth and differentiation pattern of different progenitor cells was found to be greatly
enhanced by the formation of cellular aggregates. This is reflected in the initial steps of many cellular
differentiation protocols (Dutta and Dutta 2018).
3.3.1. Extracellular Matrices (ECM) and Hydrogels
The ECM functions as a network that physically connects cells and governs the functional mechanical
properties of many tissues such as bone, cartilage and skin. The immediate microenvironment of
cells is an important mediator of signals and stimuli, and the mechanical ECM properties alone can
support or inhibit the differentiation of certain cell lineages (Saha et al. 2008; Keung et al. 2012).
ECM components can also bind signaling molecules such as growth factors, cytokines or hormones
and alter their presentation via conformational changes. The characteristics of the ECM can in turn
be controlled by the residing cells. It has become apparent that cellular processes like migration,
adhesion, survival, proliferation and differentiation are altered through ECM modulation (Frantz et
al. 2010; Josephine C. Adams and Fiona M. Watt 1993).
The specific constituents of the ECM include a network of insoluble and soluble protein fibrils
surrounded by and embedded in a hydrated gel made of polysaccharides, glycoproteins,
proteoglycans, and other soluble factors. Collagen, elastin, laminin and fibronectin are some of the
major ECM proteins found in almost all vital organs.
Collagens are the most abundant fibrillary proteins constituting up to 30% of the protein mass of a
multicellular animal. Their fibrous nature is derived from a unique triple helix arrangement (Frantz et
al. 2010; Josephine C. Adams and Fiona M. Watt 1993). Elastin is a structural protein and a major
constituent of elastic fibers that allow tissues to endure repeated stretching and deformation.
Laminin and fibronectin are both glycoproteins, which interconnect ECM components with each
15
other or with cells. Fibronectin is a V-shaped protein consisting of two nearly identical subunits
joined by a pair of disulfide bonds. It has binding sites for both collagen and glycosaminoglycans
(GAGs), which enable it to crosslink these ECM components and facilitates the linking of ECM
components to cells. The proteoglycans are hetero-polymers composed of a protein core associated
to GAG side chains. GAGs are polymers of repeating disaccharide units in the form of a bottle brush
(Dutta and Dutta 2018).
Mechanical, structural and compositional cues of the ECM can drastically alter cell function (Caliari
and Burdick 2016). Cells lacking this extracellular microenvironment tend to display aberrant
behaviors like flattened shape, abnormal polarization, altered drug response and loss of
differentiated phenotype (Engler et al. 2006; Rowlands et al. 2008).
These problems motivated the development of well-defined biomaterials, which are able to partially
mimic the cues provided by the actual ECM. Particularly hydrogels, water swollen networks of
polymers, have proven to be useful for this purpose since they have mechanical properties similar to
many soft tissues and can support cell adhesion and protein sequestration (Geckil et al. 2010). The
advantageous properties of natural polypeptides such as collagen, fibrinogen and fibronectin include
the presence of cellular binding domains allowing for cell adhesion. Furthermore, natural
polysaccharide polymers like alginate, hyaluronic acid and chitosan, structurally resemble GAGs and
provide hydrogels with controlled permeability. However, their mechanical properties are generally
restricted to a certain range, they are often degraded enzymatically or hydrolytically in an
uncontrolled manner and their derivation from natural sources negatively influences the
reproducibility.
Synthetic polymers offer more systematically controllable properties. A prominent bio-compatible
synthetic polymer is poly(ethylene glycol) (PEG). PEG-based polymers are frequently used for 3D cell
culture studies and can be easily modified to hold various functional groups, bioactive epitopes and
biodegradable units. However, synthetic polymers are generally biologically inert, not biodegradable
and often rely on harsh gelation techniques (DeVolder and Kong 2012).
Of course, the possibilities to chemically or physically combine different natural or synthetic
polymers in order to tackle their individual disadvantages are nearly endless (Gribova et al. 2011).
3.3.2. Alginate
Alginate is a natural polymer widely used as biomaterial for 3D cell culture and tissue engineering.
Commercial alginates are extracted from marine brown algae (Pawar and Edgar 2012). Due to its high
water retention, cation binding, biocompatibility and non-immunogenicity, this FDA-approved
16
biomaterial has found numerous applications in biomedical science and engineering including food
industry. It is a linear polysaccharide with blocks of (1-4)-linked β-d-mannuronic acid (M) and α-l-
guluronic acid (G) monomers. The relative amount of each monomer can vary among different
sources. Furthermore, the monomers can be linked randomly or grouped in homo-polymeric blocks.
In order to obtain a hydrogel, the individual linear alginate polymer chains have to be crosslinked.
The most common crosslinking procedure is ionic crosslinking (Lee and Mooney 2012), which consists
in the exposure of the unmodified alginate to divalent cations. Typically, Ca2+ is the first choice, but
Sr2+ or Ba2+ may be used as well. During this process, the cations are bridging G residues on different
chains, which results in the formation of an insoluble alginate mesh.
The mechanical properties of alginate hydrogels such as viscosity, stiffness and degradability depend
on chemical characteristics and can be varied by altering composition, concentration, molecular
weight or gelation procedure. The ion type chosen for ionic crosslinking governs the strength and
uniformity of produced hydrogels. Two main gelation methods can be distinguished: for diffusion
gelation, ions are allowed to diffuse from a large outer reservoir (usually a CaCl2 solution) into an
alginate solution, which causes almost instantaneous gelation; internal gelation is based on the
controlled release of gelling ions from an inert ion source that is dissolved or suspended within the
alginate solution. This procedure usually results in a slower and more uniform gelation. As ionic
crosslinking depends on the presence of G blocks, a decreasing M/G-ratio results in stiffer hydrogels
with smaller pore size (Huang et al. 2012; Andersen et al. 2015; Kuo and Ma 2001). The gelation
procedure described in these publications makes scaffold fabrication simple and non-toxic to cells
(Rowley et al. 1999).
Alginates can be considered as inert, as they are not specifically recognized by cell receptors. Thus,
the behavior of cells is mainly influenced by mechanical properties of alginates and can be concerted
via addition of adhesive ligands, fibrous proteins or specific carbohydrates (Huang et al. 2012;
Andersen et al. 2015; Bozza et al. 2014). The tailoring of alginate derivative properties is possible in
principle but can be very challenging in practice due to the key alginic acid properties including
solubility, pH sensitivity, and complexity (Pawar and Edgar 2012).
Alginate hydrogels can be dissolved and cells can be recovered by several agents including chelating
agents such as EDTA, phosphate, citrate or non-gelling agents such as sodium or magnesium ions
(Huang et al. 2012). This also implies that initial mechanical properties will, in the long run, depend
on the environment surrounding the hydrogel (Sakai et al. 2004).
17
3.3.3. Applications of 3D cultures in vitro
One of the fields that adopted 3D cell culture methods is cancer research. Miller et al. compared the
growth properties and sensitivity to chemotherapeutic drugs of mouse mammary tumor
subpopulation cell lines when grown in a collagen matrix or as monolayer culture (Miller et al. 1985).
The growth of the 3D cell aggregates in the collagen matrix was reduced non-exponentially by
chemotherapeutic drugs. This resembled the in vivo behavior of tumor cells more closely than the
exponential growth reduction observed for monolayer cultures (Godugu et al. 2013).
3D cell culture is also routinely used for the support of stem cell growth and differentiation into
several lineages including chondrogenic (Olderøy et al. 2014), hepatic (Baharvand et al. 2006),
pancreatic (Wang et al. 2009) and neuronal lineages (Kim et al. 2013; Li et al. 2011).
Interestingly, 3D cell culture helped to investigate the role of tissue level elasticity as an important
contributor to the specification towards specific lineages in cell cultures. It was shown that
mesenchymal stem cells grown on polyacrylamide gels coated with collagen I commit to the lineage
specified by matrix elasticity. Matrix elasticities corresponding to brain, muscle and bone where
shown to be neurogenic, myogenic and osteogenic, respectively. Soluble induction factors were
found to be less selective than matrix stiffness in governing specification (Engler et al. 2006).
Barharvand et al. reported that the differentiation of human embryonic stem cells (hESCs) into
hepatocyte-like cells is accelerated when they are cultured in 3D collagen scaffolds compared to
collagen-coated dishes (Baharvand et al. 2006).
The study of the central nervous system (CNS) is particularly challenging due to its complexity and
poor accessibility. 2D cell cultures are still the method of choice for many applications such as large-
scale drug screening and imaging. However, cell morphology, direct cell-cell interactions as well as
the cross-talk between specific cell types, seem to be more informative and reminiscent of in vivo
neural tissue in 3D cultures (Pașca 2018; Centeno et al. 2018). Kim et al. proposed that a 3D
environment based on microencapsulation, meaning the embedding of cells in small alginate beads
facilitated the differentiation of human embryonic stem cells to DA neurons (Kim et al. 2013).
The adoption of 3D cell culture platforms suitable in terms of consistency, scale and cost could
greatly increase the relevance of results obtained from high throughput drug screenings. Particularly,
the integration of microfluidics technologies and microfabrication techniques, borrowed from the
microchip industry, holds great promise regarding disease modeling, drug development and
evaluation (Huh et al. 2011; Jackson and Lu 2016; McKee and Chaudhry 2017).
Stem cells, progenitor cells, and lineage-committed cells are considered to be possible drug depots
upon implantation in patients. They could offer sustained release of therapeutic biomolecules.
18
Hydrogels are often used to separate the implanted cells from the host in order to protect them from
the immune system (Schmidt et al. 2008; Wilson and Chaikof 2008). This principle has been applied
by Lim and Sun to correct the diabetic state of rats by the implantation of microencapsulated islets
(Lim and Sun 1980). An even longer lasting effect was obtained with a similar approach, using a more
stable alginate high in guluronic acid, by Soon-Shiong et al. in a spontaneous diabetic dog model
(Soon-Shiong et al. 1993).
Innumerable experimental manipulations are thinkable with 3D organ type cultures, as they could be
used to elucidate known or novel molecular signaling pathways. This enterprise relies naturally on 3D
cell culture and the modeling of an appropriate ECM environment. For instance, the formation of
contractile muscle tissue by neonatal rat cardiac cells was shown to be supported by the integration
of two adhesion peptides into an unmodified alginate scaffold (Sapir et al. 2011).
Engineered tissue is created by harvesting cells, expanding them in culture and subsequently on
scaffolds which could ultimately be used for implantation. Interestingly, alternative technologies
were investigated in which cells could be mixed with a crosslinkable biomaterial and minimal
invasively injected into specific tissues of model organisms. The gel crosslinking would then take
place in situ. This requires less cells, time and reagents and possibly even reduces the chance of
failure due to contaminations. The subcutaneous injection of murine fibroblasts along with a
combination of crosslinked hyaluronan and gelatin or chondroitin sulfate and gelatin into nude mice
for example resulted in viable and uniform soft tissue (Shu et al. 2006).
19
4. AIM OF THE STUDY
The aim of the present thesis was the evaluation of a new in vitro cell culture model system for the
mDA neuronal differentiation of iPSCs within a 3D alginate hydrogel matrix.
For this purpose, the following specific aims were addressed:
1. Testing of different alginate based scaffold biomaterial compositions for the differentiation
of iPSCs to mDA neurons in 3D culture.
2. Comprehensive characterization of the differentiated cells in terms of neuronal and mDA
marker gene expression as well as electrophysiological functionality.
3. Demonstration of long-term maintenance of differentiated mDA neurons with the presented
alginate based 3D culture system.
20
5. PATIENTS, MATERIALS AND METHODS
5.1. Patients
Two hiPSC lines from two control individuals (iPS-802 and iPS-SFC084-03-02), which do not carry any
mutations in known PD genes, were used. iPSC-802 was generated in the laboratory of the Institute
for Biomedicine by electroporation of the parental fibroblast line with non-integrating episomal
plasmids carrying OCT3/4, SOX2, KLF4, and L-MYC (Meraviglia, Zanon et al., 2015). iPSC-SFC084-03-02
was provided by Prof. Philip Seibler at the University of Lübeck. An iPSC line of a PD patient carrying a
heterozygous triplication of the SNCA gene (iPS-ND34391) was provided by the Coriell Institute
biobank. Phenotypic and genotypic data are listed in Table 2. The study was approved by the Ethics
Committee of the Azienda Sanitaria dell’Alto Adige (Italy). For all the experiments, either one or the
other control line was used.
TABLE 2. Genotypic and phenotypic characterization of PD patient and controls
ID Sex Age at biopsy (yr)
Mutation Zygosity Clinical status
Control 802 F 60 - - unaffected
Control SFC084-03-02 F 63 - - unaffected
Mutant ND34391 F 55 SNCA triplication heterozygous affected
5.2. Materials
5.2.1. Chemicals
1kb Plus DNA Ladder Invitrogen
All-In-One qPCR mix Genecopoeia
All-In-One qPCR mix Genecopoeia
Antioxidant Life Technologies
Blotting-Grade Blocker Bio-Rad
Bovine serum albumin (BSA) Sigma-Aldrich
cOmplete™ Protease Inhibitor Cocktail Roche
Ethanol (C2H5OH) J.T.Baker
Ethanol (C2H5OH) J.T.Baker
GelStar™ Nucleic Acid Gel Stain 10,000X Lonza
IGEPAL CA-630 (NP-40) ((C2H4O)nC14H22O) Sigma-Aldrich
21
Isopropanol Sigma-Aldrich
Isopropanol Sigma-Aldrich
Loading Buffer 5X Thermo Fisher Scientific
Methanol (CH3OH) Sigma-Aldrich
Methanol (CH3OH) Sigma-Aldrich
NuPage MES running buffer 20X Life Technologies
NuPage sample buffer 4X Life Technologies
NuPage transfer buffer 20X Life Technologies
Paraformaldehyde (HO(CH2O)nH) Sigma-Aldrich
Paraformaldehyde (HO(CH2O)nH) Sigma-Aldrich
PhosSTOP EASYpack Roche
Precision Plus Protein Western Blotting Standards Bio-Rad
Reducing agent 10X (DTT 500mM) Life Technologies
Sodium azide (N3Na) Sigma-Aldrich
Sodium azide (N3Na) Sigma-Aldrich
Sodium chloride (NaCl) Sigma-Aldrich
Sodium chloride (NaCl) Sigma-Aldrich
Sodium dodecyl suphate (SDS) Fluka
Triton X-100 Sigma-Aldrich
Triton X-100 Sigma-Aldrich
Trizima Base (NH2C(CH2OH)3) Sigma
TRIzol Reagent Thermo Fisher Scientific
TRIzol Reagent Thermo Fisher Scientific
Tween-20 Millipore
5.2.2. Western blot solutions
RIPA buffer 25 mM Tris-HCl pH 7.6, 150 mM NaCl, 1% IGEPAL, 1% sodium
deoxycholate, 0.1% SDS in ddH2O
22
Running buffer 50 NuPAGE MES Running buffer 20X (Thermo Fisher Scientific), 950
mL ddH2O
Transfer buffer 50 mL NuPAGE MES Transfer Buffer 20X (Thermo Fisher Scientific),
100 mL MeOH, 850 mL ddH2O
Ponceau Red 0.1% Ponceau S, 5% acetic acid in ddH2O
TBS 10X 200 mM Tris, 9% NaCl, pH 7.5 in ddH2O
TBS-T 1X 100 mL TBS 10X, 0.1% Tween20, ddH2O to 1 liter
Blocking buffer 5% Blotting-Grade Blocker in TBS-T 1X
5.2.3. Cell culture reagents, differentiation factors, and coating materials
Agarose Bio-Rad
Ascorbic acid Sigma-Aldrich
B-27 Plus Supplement 50X Thermo Fisher Scientific
CHIR99021 Stemgent
Collagenase type IV Thermo Fisher Scientific
DAPT Tocris Bioscience
Dibutyryl-cyclic-AMP EnzoLifescience
DMEM/F12 + GlutaMAX Thermo Fisher Scientific
Fibronectin Corning
KnockOut Serum Replacement Thermo Fisher Scientific
Laminin (LA) Sigma-Aldrich
LDN-193189 Stemgent
Matrigel Basement Membrane Matrix BD Biosciensces
MitoSox Life Technologies
Neurobasal Medium Life Technologies
Penicillin/Streptomycin (P/S) Life Technologies
Phosphate buffered saline (PBS) Life Technologies
23
Poly-D-lysine (PDL) Thermo Fisher Scientific
Purmorphamine Stemgent
Recombinant Human BDNF Peprotech
Recombinant Human FGF-8a R&D System
Recombinant Human GDNF Peprotech
Recombinant Human Sonic Hedgehog R&D System
Recombinant Human TGF-beta 3 Peprotech
SB-431542 Tocris Bioscience
StemMACS iPS-Brew XF Miltenyi
StemMACS Y27632 (RI) Myltenyi Biotech
TrypleExpress Life Technologies
5.2.4. Cell culture media
iPSC medium StemMACS iPS-Brew XF (Myltenyi) (includes iPS-Brew XF 50X
supplement), 1% penicillin/streptomycin (Life Technologies)
Neural differentiation medium Knockout DMEM (Life Technologies), 15% knockout serum (Life
Technologies), 1% L-glutamine (Life Technologies), 1% nonessential
amino acids (Life Technologies), 0.2% -mercaptoethanol (Life
Technologies).
Neural medium Neurobasal medium (Life Technologies), B27 Supplement 1X, 1% L-
glutamine (Life Technologies).
5.2.5. Kits
BCA Protein Assay Kit Pierce
Countess Cell Counting Chamber Slides Thermo Fisher Scientific
Fluo-4 Calcium Imaging Kit Thermo Fisher Scientific
Human Neural Stem Cell Immunocytochemistry Kit Thermo Fisher Scientific
LIVE/DEAD Viability/Cytotoxicity Kit, for mammalian cells Thermo Fisher Scientific
24
Pluripotent Stem Cell 4-Marker Immunocytochemistry Kit Thermo Fisher Scientific
5.3. Methods
5.3.1. hiPSC culture and passaging
hiPSCs were cultured under feeder-free conditions on Matrigel matrix (Corning) in StemMACS™ iPS-
Brew XF (Miltenyi Biotech) with 1% penicillin-streptomycin (Thermo Fisher Scientific). Cells were
maintained in a saturated humidified atmosphere at 37°C and 5% CO2, and medium was changed
every day. iPSC colonies were passaged enzymatically using 1 mg/ml Collagenase type IV (Thermo
Fisher Scientific) in DMEM/F12 (Thermo Fisher Scientific). Briefly, differentiated areas of the iPSC
colonies were removed by slow-vacuum aspiration under a stereomicroscope, and cells were
incubated with collagenase for 10 min at 37°C (approximately until the edges of the colonies are
visibly curling). Next, the enzymatic solution was replaced by DMEM/F12, and the colonies were
detached with a cell scraper and centrifuged at 200 xg for 5 min. The cell pellet was resuspended in
StemMACS iPS-Brew XF medium, and colony fragments were triturated in smaller pieces ( 5̴0-200
cells per fragment). The colony suspension was seeded at a ratio of 1:3-1:5 on Matrigel coated cell
culture plates.
5.3.2. Harvesting and counting cells for neuronal in vitro differentiation
When seeded for neuronal differentiation, cells were passaged at a maximum of 90% confluency
using TrypLE Express (Thermo Fisher Scientific) for 3-5 min at 37°C. Enzymatic detachment was
stopped by the addition of StemMACS iPS-Brew XF. Cells were suspended via pipetting, and the cell
suspension was centrifuged at 200 xg for 3 min. The cell pellet was resuspended in medium
supplemented with 10 µM ROCK inhibitor (RI). For counting, 10 µL of cell suspension were mixed
with 10 µL of Trypan Blue Stain (0.4%) (Thermo Fisher Scientific). 10 µL of this mixture were
transferred into the chamber ports of a Countess ™ Cell Counting Chamber Slide (Thermo Fisher
Scientific), and the cell number was determined using Countess® Automated Cell Counter (Thermo
Fisher Scientific).
5.3.3. Monolayer midbrain dopaminergic differentiation of iPSCs
Prior to 2D monolayer differentiation cells were harvested and counted as described in section 5.3.2.
105 cells/12 well were seeded on cell culture plates coated with 350µg/ml Matrigel (Corning) in
25
StemMACS iPS-Brew XF medium supplemented with 10 μM RI. Daily medium changes were
conducted in the following days with fresh medium without RI.
Once the cells reached 80-90% confluency, the differentiation of iPSCs into midbrain DA neurons was
initiated following the floor-plate-based neuron induction protocol established by Kriks et al., with
minor modifications (Kriks et al. 2011; Zanon et al. 2017). The timed exposure to differentiation
factors, meaning signaling proteins and small molecules, was started by supplying the cells with
knockout serum replacement (KSR) medium supplemented with SMAD pathway inhibitors SB431542
(SB, 10 µM, Tocris Bioscience) and LDN-193189 (LDN, 100nM, Stemgent). LDN was added on days 1-
10 while the supplementation with SB was stopped upon day 6. On days 2-7 Recombinant Human
Sonic Hedgehog (SHH, 100 ng/ml, R&D System), Recombinant Human FGF-8a (FGF8, 200 ng/ml, R&D
System) and Purmorphamine (Pu, 2 µM, Stemgent) were added to the medium. Furthermore, on
days 4-12 the Wnt pathway activator molecule CHIR99021 (CH, 3 µM, Stemgent) was added to the
differentiation medium.
During days 7–10 of differentiation, increasing amounts of Neurobasal medium (Life Technologies)
plus B27 supplement (Life Technologies) (referred to as NB-B27) were added to the KSR medium
(33%, 50%, and 66%). Thereafter it was completely shifted to NB-B27. From day 8, the medium was
changed every other day.
On day 12, maturation of DA neurons was initiated by adding Recombinant Human BDNF (20 ng/ml,
Peprotech), Recombinant Human GDNF (20 ng/ml, Peprotech) ascorbic acid (AA, 0.2 mM, Sigma),
Recombinant Human TGF-beta 3 (ß3, 1 ng/ml, Peprotech), dibutyryl-cyclic-AMP (dbcAMP, 0.5 mM,
EnzoLifescience) and DAPT (10 mM, Tocris) (together referred to as BAGTCD). On day 20 of
differentiation, cells were passaged as single cells and replated at 1.5x105 cells/cm2 on 12 well plates
with coverslips coated with PDL/LA (100 µg/ml; 10 µg/ml). The medium was supplemented with
BAGTCD maturation factors until day 35.
5.3.4. Alginate bead midbrain dopaminergic differentiation of iPSCs
The same differentiation conditions as described above in section 5.3.3 were applied for the 3D
cellular model system.
5.3.5. Preparation of alginate solution
Alginate solutions (1% and 2% w/v) were prepared freshly the day before cell encapsulation by
mixing alginic acid sodium salt (Sigma Aldrich) in a 0.025 M HEPES and 0.15 M NaCl buffer (pH 7.4).
26
The alginate solution was heated to dissolve alginate and subsequently autoclaved and sterile
filtered.
5.3.6. Alginate bead formation and culture
At the day of cell encapsulation, iPSCs were harvested and counted as described in section 5.3.2.
1.0x106 cells were gently mixed with 1 ml alginate solution (1% or 2% w/v) with or without
fibronectin (Fn) to a final concentration of 100 µM. Alginate beads were formed by slowly dripping
the prepared alginate-cell suspension in 0.1 M CaCl2 with a 19 gauge needle. The beads were
incubated for 20 min in the CaCl2 solution and then washed 3 times with 1x PBS pH 7.4 (Thermo
Fisher Scientific). Subsequently they were transferred to cell culture plates (15-20 beads/6 well) with
a cell scraper and supplied with StemMACS iPS-Brew XF medium supplemented with 10 μM RI.
Alginate beads were cultured with StemMACS iPS-Brew XF medium supplemented with 10 μM RI for
three days prior to differentiation if not otherwise stated.
5.3.7. Decapsulation and replating of differentiated cells from alginate beads
Prior to decapsulation alginate beads were washed inside the well with PBS without Calcium and
Magnesium. Subsequently, the beads were distributed to 1.5 ml Eppendorf tubes (3-4 per tube)
which were filled up with PBS without Calcium and Magnesium and shaken on a thermoblock at 37°C
and 700 rpm for 20 min. Then they were centrifuged at 300 xg for 5 min, the supernatant was
discarded, and they were seeded at an appropriate density on cell culture plates with round coverlips
coated with 1 mg/ml Matrigel.
5.3.8. Cell viability assay
The Live/Dead cell viability assay (Live/Dead cell viability assay kit, Life Technologies) was performed
at day 5, 10, and 20 of differentiation. For the assay, beads were collected and washed briefly twice
with PBS. Each bead was then placed in a live imaging chamber and incubated for 20 min with a 2 µM
Ethidium Homodimer-1 (EH-1) and 8 µM Calcein (AM) solution in PBS in dark conditions. Images were
acquired using a Leica SP8-X confocal microscope (Leica) and analyzed using Imaris software.
27
5.3.9. Real-time quantitative PCR (RT-qPCR)
Cells were directly lysed in 1 ml of TRIzol (Invitrogen) reagent at day 10, 20 and 35 of differentiation.
Total RNA isolation was conducted following manufacturer's instructions.
1-2 µg RNA were reverse-transcribed using the SuperScript® VILO™ cDNA Synthesis Kit (Invitrogen) in
a 20 µl reaction. The cDNA synthesis was carried out in a thermocycler following the manufacturers’
temperature protocol (10 min at 25°C, 60 min at 42°C and 5 min at 85°C). The cDNA was then diluted
to 10 ng/µl with RNAse free water. RT-qPCR was performed in triplicate on the 96CFX Manager (Bio-
Rad) in 20 µl, using 25 ng of reverse transcribed product, the All In One qPCR mix (Genecopoeia) and
0.2 µM of primers (Genecopoeia; Table 3).
The PCR program used was the following:
Number of Cycles Step Temperature Time
1 Pre-denature 95°C 10 min
40
Denature 95°C 10 sec
Annealing 60°C 20 sec
Extension 72°C 15 sec
Melting curve analysis was performed immediately after the amplification reactions.
Temperature range Rate of temperature change Duration
72°C ~ 95 °C 0.5°C/ step 6 sec/ step
30°C
30 sec
Relative gene expression was calculated using the ΔΔCt method and the Ct value of the target gene
was normalized to the Ct value of two reference genes (β-actin and RPL13) using the following
equation:
Fold change ≈ 2−ΔΔC𝑡 = 2[ΔC𝑡sample A (target−reference)− ΔC𝑡sample B (target−reference)]
Efficiencies and correlation coefficients (r2) were calculated for all primers.
28
TABLE 3. Overview of primers used for RT-qPCR
Gene Manufacturer Catalog Number
PAX6 Genecopoeia HQP012219
FOXA2 Genecopoeia HQP008906
TUJ1 Genecopoeia HQP057484
TH Genecopoeia HQP018064
DAT Genecopoeia HQP053961
GIRK2 Genecopoeia HQP010010
5.3.10. Gel analysis of RT-qPCR products
In order to check whether the set of primers used for the RT-qPCR experiments gave the correct and
expected amplicon, 5 µl of the PCR products were loaded on 1.5% agarose gel prepared with
Certified™ Molecular Biology Agarose (Bio-Rad) and 0.5X TBE buffer by heating it in a microwave.
GelStar™ Nucleic Acid Gel Stain 10,000X (Lonza) was added to the liquid agarose. Then, the solution
was poured into a casting tray for solidification at room temperature. A molecular weight standard
(Low Molecular Weight DNA Ladder, New England Biolabs) was loaded on the first lane for size
estimation. Electrophoresis was performed at 100 V for 20 min in 0.5 X TBE buffer. The gel was
analyzed using the ChemiDoc™ Touch Imaging System (Bio-Rad).
5.3.11. Western blot analysis
5.3.11.1. Sample preparation
For western blot analysis, whole cell homogenates were used. Cell pellets were resuspended in the
appropriate volume of cold RIPA buffer supplemented with protease inhibitors (cOmplete™ Protease
Inhibitor Cocktail, Roche) and phosphatase inhibitors (PhosSTOP EASYpack, Roche) and then
incubated 30 min on ice. After incubation, the cell lysate was centrifuged for 20 min at 14,200 x g at
4°C. The supernatant, containing the cell proteins, was transferred into a new tube. Protein
concentration was determined using BCA Protein Assay Kit (Thermo Fisher Scientific) according to the
manufacturer’s protocol. Absorbance was measured using VICTOR™ X3 Multilabel Plate Reader
(PerkinElmer) at 562 nm, and sample protein concentration was calculated using a standard
calibration curve (0-2.5 µg/µL). 10 µg of proteins were loaded per well on the SDS-PAGE gel. Protein
lysate was mixed with NuPAGE LDS Sample Buffer (ratio 1:4) and NuPAGE Sample Reducing Agent
29
(ratio 1:10) (Thermo Fisher Scientific). RIPA-Buffer was added in the amount needed to obtain an
equal volume for all samples. Next, the samples were denaturated by incubation for 5 min at 95°C.
5.3.11.2. SDS-PAGE and protein transfer
After denaturation, sample mixtures were loaded on a NuPAGE 4-12% Bis-Tris Gel (Thermo Fisher
Scientific). Molecular weight standard Precision Plus Protein WesternC Blotting Standards (Bio-Rad)
was run on the same gel. The electrophoresis was performed in Running buffer for 5 min at 100 V
and for 90 min at 150 V. After electrophoresis, proteins were transferred at 32 V for 70 min onto a
nitrocellulose membrane (Biorad) in a CellX Mini Blotting Module (Thermo Fisher Scientific) containing
Transfer buffer.
5.3.11.3. Antibody staining for western blot
The blots were blocked in Blocking buffer (see section 5.2.2). Primary antibodies were appropriately
diluted as reported in Table 4, and the blots were subsequently incubated overnight at 4°C on a
radial rotor. The next day, the membrane was washed three times with TBS-T for 5 min and then
incubated with a horseradish-peroxidase (HRP)-conjugated secondary antibody (Millipore) at a
dilution of 1: 10,000 for 1 h at room temperature. This was followed by other three washing steps in
TBS-T. Target proteins were detected by enhanced chemiluminescence using Clarity™ ECL Western
Kit (Bio-Rad), according to the manufacturers’ protocol. The chemiluminescence signal was detected
using the ChemiDoc™ Touch Imaging System (Bio-Rad). Equal loading was assessed by use of an
antibody against a housekeeping protein. The signal of the target protein was quantified by Image
Lab 5.2.1 analyzer software (BioRad) by normalizing the expression of the target protein in relation to
the housekeeping proteins.
30
TABLE 4. Overview of antibodies used for western blot analysis and their respective dilution factor
Primary antibodies Species Manufacturer Dilution factor
FOXA2 (#sc374376) Mouse SantaCruz 1:1000
LMX1A (#ab10533) Rabbit Millipore 1:1000
TUJ1 (#MMS-435P) Mouse Biolegend 1:1000
TH (#657012) Rabbit Callbiochem 1:1000
GAPDH (#MAB 374) Mouse SantaCruz 1:500
Secondary antibodies
Horseradish-peroxidase (HRP)-
conjugated antibody (#AP308P)
Mouse Millipore 1:10,000
Horseradish-peroxidase (HRP)-
conjugated antibody (#12-348)
Rabbit Millipore 1:10,000
5.3.12. Mitochondrial superoxide detection
At days 10, 20 and 35 one well of each differentiated cell line, replated as indicated in section 5.3.7,
was used for mitochondrial superoxide detection. Medium was removed by washing three times with
PBS and replaced by HBSS containing 5 µM MitoSox Red mitochondrial superoxide indicator (Thermo
Fisher Scientific). After an incubation of 15 min at 37°C and 5% CO2, the cells were washed for three
times with HBSS. Subsequently, the cells were fixed with 4% paraformaldehyde at room temperature
and the coverslips were mounted on an object slide as described for immunofluorescence staining.
Images were acquired using a Leica SP8-X confocal microscope (Leica) and analyzed using Imaris
software.
5.3.13. Immunofluorescence staining
Cells differentiated in alginate beads were replated at days 10, 20 and 35 of differentiation on 12 well
plates with Matrigel coated coverslips. Cells differentiated as monolayer were either replated at day
10 of differentiation on 12 well plates with 250 µg/ml Matrigel coated coverslips or at day 20 of
differentiation at 1.5x105 cells/cm2 on 12 well plates coated with PDL/LA (100 µg/ml; 10 µg/ml). Cells
were fixed in a 4% paraformaldehyde solution in PBS for 15 min at room temperature. Afterwards,
cells were washed three times with PBS.
31
All steps of the immunofluorescence stainings were performed on a shaker. If not stated otherwise,
cells were permeabilized for 5 min with 0.5% TritonX100 in PBS, then blocked for 1 h with 3% BSA in
PBS at room temperature and incubated overnight with primary antibodies in 3% BSA at 4°C. For all
stainings, cells were washed three times for 5 min with PBS the next day, incubated with secondary
antibodies for 1h at RT, washed three times for 5 min with PBS again and then mounted on an
object-slide using ProLong Diamond Antifade Mountant with DAPI (Thermo fisher scientific).
For FOXA2 and LMX1A co-stainings, blocking and primary antibody incubation was conducted in PBS
with 3% BSA and 0.05% TritonX100.
For TH and DAT and TH and GIRK2 co-stainings, cells were directly blocked in 10% FBS in PBS without
any permeabilization and primary antibody incubation was performed in 5% FBS in PBS. Images were
acquired using a Leica SP8-X confocal microscope (Leica) and analyzed using Imaris software. The
antibodies used are listed in Table 5.
32
TABLE 5. Overview of antibodies used for immunofluorescence stainings and
respective dilution factors
Primary antibodies Species Manufaturer Dilution factor
FOXA2(HNF-3ß(H-4)) (sc374376) Mouse Santa Cruz 1:50
LMX1A (ab31006) Rabbit Abcam 1:200
MAP2 (ab5392) Chicken Abcam 1:1000
TH (MAB318) Mouse Millipore 1:500
GIRK2 (ab65096) Goat Abcam 1:100
DAT (sc-32259) Rat Santa Cruz 1:50
LMX1A (AB10533) Rabbit Millipore 1:1000
TH (sc-25269) Mouse Santa Cruz 1:50
TUJ1 (MMS-435P) Mouse Covance 1:1000
TH (657012) Rabbit Millipore 1:200
PSD95(7E3) (36233S) Mouse Cell Signaling 1:150
Synapsin 1(D12G5) (52975) Rabbit Cell Signaling 1:100
Secondary antibodies
Alexa Fluor 488 Anti-Mouse IgG Goat Invitrogen 1:1000
Alexa Fluor 555 Anti-Rabbit IgG Goat Invitrogen 1:1000
Alexa Fluor 647 Anti-Mouse IgG Goat Invitrogen 1:1000
Alexa Fluor 488 Anti-Chicken IgG Goat Invitrogen 1:1000
Alexa Fluor 488 Anti-Rat IgG Goat Invitrogen 1:1000
Alexa Fluor 555 Anti-Mouse IgG Donkey Invitrogen 1:1000
Alexa Fluor 647 Anti-Goat IgG Donkey Invitrogen 1:1000
Alexa Fluor 555 Anti-Goat IgG Donkey Invitrogen 1:1000
Alexa Fluor 488 Anti-Mouse IgG Donkey Invitrogen 1:1000
33
5.3.14. Vibratome sectioning of alginate beads/cell aggregates
Cell aggregates of mDA-neurons differentiated and cultured in 1% alginate for more than 200 days
were fixed with 4% paraformaldehyde overnight at 4°C, washed three times with 1x PBS and
embedded in 3-4% agarose. The solid agarose block was sectioned into 80 µm slices using a Leica
VT1000 S vibratome. The sections were stored in 1X PBS at 4°C until used for experimental analysis.
Immunofluorescence stainings on these sections were carried out as indicated in section 5.3.13.
5.3.15. Electrophysiological characterization
Whole-cell recordings in current-clamp mode have been performed in a temperature-controlled
recording chamber (36-37°C) mounted on an inverted Eclipse-Ti microscope (Nikon, Tokyo, Japan)
and using a MultiClamp 700B amplifier (Molecular devices, LLC). Current-command protocols and
data acquisition have been performed using pClamp 10.0 software and the Digidata 1550 interface
(Molecular Devices, LLC). Data were lowpass-filtered at 3 kHz and sampled at 10 kHz. Patch
electrodes, fabricated from thick borosilicate glass capillaries, have been made using a Sutter P-1000
puller (Sutter Instruments) to a final resistance of 4-6 MΩ when filled with the intracellular solution
containing (in mM): 120 KGluconate, 25 KCl, 10 EGTA, 10 HEPES, 1 CaCl2, 4 Mg-ATP, 2 Na-GTP and 4
Na2-Phosphocreatine (pH 7.4, adjusted with KOH). Cells have been bath-perfused with a Krebs
solution composed by (in mM): 129 NaCl, 5 KCl, 2 CaCl2, 1 MgCl2, 30 D-glucose, 25 Hepes; pH 7.3 with
NaOH. Spontaneous action potentials have been recorded in a gap-free mode while the presence of
the Ih current was evaluated by applying long hyperpolarizing steps at different current intensities (-
30 pA increments). Series resistance value has been monitored along the experiment and recordings
with changes over 20% of its starting value have been discarded.
34
6. RESULTS
The present thesis describes the establishment and validation of a new in vitro cell culture model for
the neuronal differentiation of iPSCs within a 3D alginate hydrogel matrix to mimic the elastic
environment encountered in the developing brain. In the first part of the experimental work, it was
attempted to identify a hydrogel composition and initial culturing conditions, suitable to sustain cell-
viability and propagation. In the second part, iPSC control lines were differentiated into mDA neurons
and the expression of differentiation markers was examined via RT-qPCR and immunofluorescence
staining at different stages of the process. Additionally, the functionality of the differentiated cells
was assessed by electrophysiological characterization. At last the ability of the cells to recapitulate a
known mitochondrial dysfunctional phenotype was examined and they were kept in culture for more
than 200 days. .
6.1. Test of different matrix compositions
6.1.1. Validation of the beneficial effect of Rho-associated kinase inhibitor
treatment on alginate encapsulated iPSCs
Alginates are widely used hydrogels because of their easy gelation at physiological conditions, lower
batch-to-batch variations than provided for animal materials, the possibility of gentle dissolution,
transparency allowing microscopic observations and the formation of a pore network allowing
nutrient, synthesized product and waste diffusion. In addition, they can be considered to be inert as
they are not recognized by mammalian cell surface receptors (Andersen et al. 2015).
It has been reported previously that the treatment with Rho-associated kinase inhibitor (RI) prior to
differentiation is essential to sustain the cell viability of hESCs encapsulated in alginate microcapsules
(Chayosumrit et al. 2010; Kim et al. 2013). For this reason, we tested its beneficial effect also for
encapsulated human iPSCs.
IPSCs were encapsulated in 1% or 2% alginate with or without fibronectin. At the day of
encapsulation, iPSCs were treated with RI. The next day, cells were divided into two groups, one of
which was cultured in StemMACS medium with RI for three additional days, while the other group
was cultured without RI. Subsequently, mDA neuronal differentiation was induced in both conditions
(Fig. 4A). The proliferating cells formed aggregates within the alginate beads, which were counted
manually (Fig. 4B). As whole beads did not fit into the field of view, the counts refer to cell
aggregates per field of view (Fig. 4C). The number of aggregates was low when iPSCs were not
treated with RI for three days prior to differentiation and no significant difference in number of
35
aggregates between the different matrix compositions could be identified in this condition (Fig. 4B,
C). On the other hand, it was apparent that the number of aggregates in the RI pre-treated alginate
beads was significantly higher than in the non-pre-treated beads, with the only exception of 2%
alginate. In addition, there were significant differences between the numbers of aggregates per field
arising from cells encapsulated in different hydrogel compositions within this group (Fig. 4B, C).
FIGURE 4. RI is beneficial for iPSCs encapsulated in alginate beads. (A) Differentiation protocol
adapted from Kriks et al. 2011. SM, StemMACS medium; RI Rho associated kinase inhibitor; BAGTCD,
BDNF, L-Ascorbic Acid, GDNF, TGFß3, dbcAMP, DAPT. For details see methods section. Quantification
of cell aggregates of a control iPSC line encapsulated in alginate beads of different compositions (Alg,
alginate; Fn, fibronectin) at day 5 of neuronal differentiation, with and without pre-treatment with RI
in StemMACS medium (3 days RI versus no RI) immediately after encapsulation; at encapsulation, RI
was added in both conditions.
36
(B) Control iPSCs at day 5 of neuronal differentiation in alginate beads of different compositions
corresponding to the quantification in C. (C) Proliferating cells form aggregates inside the 3D
matrices, which vary in abundance and shape. The number of aggregates is quantified as cell
aggregates per field of view. Data from one differentiation experiment. Statistical differences were
calculated by one-way ANOVA followed by Tukey's post hoc test to correct for multiple comparisons
(n=3 to 11 fields of view per condition). Data is plotted as ± SEM. **** p ≤ 0.0001.
6.1.2. Number of cell aggregates within alginate of different compositions
To examine which alginate concentration would best support the survival and propagation of the
hiPSCs, we tested alginate concentrations of 1% or 2% w/v. Both concentrations have been indicated
as suitable for neuronal differentiation in previous publications (Li et al. 2011; Wang et al. 2009;
Bozza et al. 2014) as their elastic modulus has been found to be in the range resembling the stiffness
of neural tissue, which seems to have a strong impact on the lineage differentiation of pluripotent
stem cells (Keung et al. 2012; Saha et al. 2008; Engler et al. 2006).
Moreover, as alginate alone is thought not to provide adequate cell adhesion (Rowley et al. 1999), it
was tested whether cell survival and proliferation was enhanced by the addition of the glycoprotein
fibronectin, a prominent ECM component, which is known to be involved in neural development,
pathfinding and regeneration (Perris and Perissinotto 2000; Luckenbill-Edds 1997). This protein is
characterized by the presence of specific domains, which facilitate the interaction with other matrix
molecules as well as with cell surface receptors, most notably integrins (Colognato and Yurchenco
2000; Schwarzbauer and DeSimone 2011).
Because of the low number of cell aggregates in the beads not treated with RI, only the group, which
received the three day pre-treatment with RI was analyzed further. The cells were differentiated for
more than 20 days and images were taken at days 5, 10 and 20 (Fig. 5A). Even though the cell
aggregate number tended to be higher in 1% alginate, we could not observe a significant difference
at any time point in number of aggregates per field between 1% and 2% alginate in this experiment
(Fig. 5B). However, a significantly higher number of aggregates in both 1% and 2% alginate matrices
containing fibronectin was observed compared to alginate alone (Fig. 5A, B). The highest number of
aggregates was obtained for iPSCs encapsulated in 1% alginate with fibronectin (Alg+Fn) at day five
of differentiation (n=35 on average).
6.1.3. Size of cell aggregates within alginate of different compositions
To further investigate whether there was a difference in terms of growth of cell aggregates between
the various alginate compositions, the size of the aggregates was measured. The length of aggregates
37
was used as a proxy to measure their size as their shape was mostly non-spherical. At day 5, no
significant difference was detected between the different compositions. At day 10, the average size
of aggregates was higher in 2% Alg+Fn than in 1% Alg+Fn. This difference became highly significant at
day 20. Additionally, at this time point the average size of aggregates was significantly higher in 2%
Alg+Fn than in 2% alginate alone. Similarly, it was higher in 1% Alg+Fn than in 1% alginate alone (Fig.
5C). The largest aggregates were observed in the condition of 2% Alg+Fn (Fig. 5A, C).
B C
38
FIGURE 5. The number and size of aggregates increase by the addition of fibronectin. (A) Control
iPSCs differentiated into mDA-neurons in alginate beads of different compositions (Alg, alginate; Fn,
fibronectin) following the protocol outlined in Figure 4A. Proliferating cells form aggregates inside
the 3D matrices, which vary in abundance and size. D5, 10 and 20 refer to days after initiation of
differentiation (after 3 day treatment with Rho associated kinase inhibitor (RI) in StemMACS
medium). (B) Quantification of cell aggregates from differentiations shown in A. The number of
aggregates is given in cell aggregates per field of view. (C) Size of cell aggregates quantified in B.
Length of aggregates has been used for non-spherical cell aggregates as indicator of size. Data from
one (2% Alg, 2% Alg+Fn) or two differentiation experiments. Statistical differences were calculated by
one-way ANOVA followed by Tukey's post hoc test to correct for multiple comparisons (B: n=3 to 11
fields of view per condition; C: n=4-128 cell aggregates per condition). Data is plotted as ± SEM. * p ≤
0.05, **** p≤ 0.0001.
6.2. Fibronectin supports cell viability during differentiation
In order to examine the viability of cells within different matrix compositions, we performed a
Live/Dead two-color assay on the intact beads. For this purpose, we used a commercially available Kit
for mammalian cells (Thermo Fisher). The essential components of the Kit are Calcein-AM, marking
living cells with green fluorescence, and the Ethidium Homodimer-1 (EH-1) which shows red
fluorescence when it reaches the nuclei of dead cells passing through disrupted membranes. Cellular
viability was calculated as the green/red ratio. In most cases, the alginate beads remained roughly
spherically shaped and the first cellular aggregates were evaluated after 5 days of differentiation (Fig.
6A).
From day 0 to day 20 of differentiation the number of viable cells in 1% and 2% Alg+Fn was higher
compared to the other conditions in alginate alone. In addition, at day 20, almost all cells
encapsulated in 1% alginate alone resulted dead, and the cell viability within 2% alginate without
fibronectin was clearly decreased compared to the conditions with fibronectin (Fig. 6B).
Furthermore, we investigated the size of the aggregates formed by viable cells. The volume of
aggregates could be determined by 3D reconstruction (Fig. 6A). In line with the results obtained from
bright field microscopy (Fig. 5C), we found that the cells in 2% Alg+Fn formed the biggest aggregates
followed by the ones in 1% Alg+Fn. In both conditions, the aggregate size increased steadily over
time. In contrast, the cell aggregates in 1% and 2% alginate alone did not increase in size during the
examined differentiation period. These data support the crucial role of fibronectin in supporting cell
viability during the differentiation process.
39
B
C
40
FIGURE 6. Viability of iPSCs encapsulated and differentiated in alginate of different compositions.
The LIVE/DEAD assay kit for mammalian cells (Thermo Fisher) was used for the distinction of live and
dead cells. (A) Representative 3D reconstructions of cell aggregates stained with Calcein-AM (live)
and Ethidium Homodimer-1 (dead). Scalebar represents 100 µm. (B) Cell viability over time given as a
percentage of green/red ratio. (C) Average size of the observed cell aggregates given in number of
voxels.
6.3. Comparative RT-qPCR suggests enhanced mDA differentiation
The data collected so far highlighted the key role of fibronectin in supporting the differentiation
performance in terms of number, size and viability. Thus, we decided to further investigate the mDA
neuronal marker gene expression of the neurons cultured in alginate (1% and 2%) with fibronectin
using quantitative real-time PCR (RT-qPCR) and to compare it with the gene expression of neurons
differentiated in parallel using our conventional 2D protocol.
A number of well-defined marker genes were investigated at day 10 and 20 of differentiation. In
Figure 7 the normalized gene expression patterns of the 3D neuronal cultures (1% Alg+Fn and 2%
Alg+Fn) are compared to the gene expression observed in the 2D culture (set to 1).
At day 10, the early neuronal commitment marker Pax6 was expressed up to 10 times more in the 3D
conditions (Fig. 7A). This indicates a stronger neuronal induction under 3D conditions. Our analysis
further showed a stronger expression of FOXA2 at day 10 under 3D compared to 2D conditions (Fig.
7A), which points toward a floorplate derived midbrain identity (Kriks et al. 2011).
The class III member of the beta tubulin family TUJ1 is involved in axon guidance and frequently used
as a neuronal marker (Tischfield et al. 2010). We could detect an increased expression level of TUJ1
for both day 10 and 20 of differentiation under 3D conditions when compared to the 2D culture (Fig.
7A and B).
Interestingly, the expression of tyrosine hydroxylase (TH), the rate limiting enzyme in dopamine
production, was always higher under 3D conditions when compared to the 2D culture. Furthermore,
a noteworthy difference between the alginate compositions was observed for TH expression, which
was stronger for cells encapsulated in 1% Alg+Fn at both time points (Fig. 7A and B). The expression
of the dopamine transporter (DAT), investigated at day 20 of differentiation, was significantly higher
for both 1% and 2% Alg+Fn compared to the neurons generated using the 2D protocol.
41
A
B
FIGURE 7. Comparative gene expression analysis at day 10 (A) and 20 (B) of differentiation
between mDA neurons generated in alginate of different compositions (Alg, alginate; Fn,
fibronectin) and 2D culture (2D). Data are presented as the mean ± standard deviation from
triplicates normalized to the gene expression in 2D culture. Statistical differences were calculated by
two-way ANOVA followed by Tukey post hoc test to correct for multiple comparisons. * p ≤ 0.05, **p
≤ 0.01, **** p≤ 0.0001
Day 20
Day 10
42
In order to check whether the set of primers used for the RT-qPCR experiments gave the correct and
expected amplicon, we loaded the qPCR products on an agarose gel. The sizes of the PCR products
matched the expected amplicon lengths (Fig. 8).
FIGURE 8. Gel electrophoresis of qPCR products amplified in the RT-qPCR experiments.
6.4. Molecular analysis of early mDA neural differentiation
The alginate compositions (1% and 2%) with fibronectin performed consistently better than alginate
alone regarding cell aggregates number and size and cell viability (see Fig. 5 and 6). Furthermore,
gene expression analysis of cells encapsulated in 1% and 2% Alg+Fn showed that these two matrix
compositions resulted in comparable gene expression patterns, except for a higher TH expression in
1% Alg+Fn (Fig. 7). Additionally, the handling of 1% alginate was easier during cell encapsulation
compared to the 2% alginate. For these reasons, we chose to rely on 1% Alg+Fn as biomaterial
composition for the following experiments.
6.4.1. Immunofluorescence staining
To further demonstrate the ability of our matrix to sustain neural differentiation, we decided to
analyze the gene expression of early neuronal and mDA neuron marker genes via
immunofluorescence staining at day 10 and day 20 of differentiation. In order to quantify the signals,
we either counted positively stained nuclei (counts/nuclei) or measured the volume of positive
43
stained cells for each gene as well as the overlapping co-stained regions (voxels/nuclei) and
normalized them to the number of nuclei.
At day 10 of differentiation, no statistically significant difference in the expression of the neuronal
progenitor markers Pax6 and Nestin could be observed between 2D and 3D conditions (Fig. 9A and
B).
FIGURE 9. Immunofluorescence stainings for Pax6 and Nestin. (A) Representative
immunofluorescence images showing the neuronal progenitor markers Pax6 and Nestin at day 10 in
2D and 3D (1% Alg+Fn) cultures. (B) Quantification of Pax6 and Nestin immunofluorescence stainings
generated in 2D and 3D cultures.
The combined expression of the transcription factors FOXA2 and LMX1A is essential for formation of
a ventral midbrain identity (Arenas et al. 2015) and the in vitro generation of a floorplate derived
A
B
44
midbrain cell lineage (Kriks et al. 2011). Therefore, we quantified immunofluorescence stainings of
FOXA2 and LMX1A for neurons generated in 2D as well as 3D cultures at day 10 of differentiation.
Although the difference was not significant, we observed that the percentages of LMX1A+ and
FOXA2+ cells were increased in 1% Alg+Fn compared to cells generated using the 2D protocol.
Additionally, the signal from double positive LMX1A+/FOXA2+ neuronal cells was significantly
increased in our 3D platform compared to the conventional 2D model (Fig. 10A and B).
FIGURE 10. Immunofluorescence stainings for FOXA2 and LMX1A. (A) Representative
immunofluorescence images showing the expression of the transcription factors LMX1A and FOXA2
at day 10 in 2D and 3D (1% Alg+Fn) cultures. (B) Quantification of LMXA1 and FOXA2
immunofluorescence stainings/co-stainings in 2D and 3D cultures. Statistical differences were
calculated by one-way ANOVA followed by Tukey’s post hoc test to correct for multiple comparison*
p ≤ 0.05
A
B
45
To further characterize the extent of differentiation, we analyzed the co-staining of the DA neuron
marker TH together with the pan-neuronal marker TUJ1 and the mDA neuronal maturation marker
GIRK2 at day 20 of differentiation.
We were able to show that the proportion of both TH+ and TUJ1+ cells was significantly higher under
3D condition when compared with the 2D protocol. Furthermore, a more than three times higher
fraction of TH+/TUJ1+ double positive cells was observed under 3D conditions (Fig. 11A and B).
FIGURE 11. Immunofluorescence stainings for TH and TUJ+. (A) Representative immunofluorescence
images showing the co-staining of TH with the neuronal marker TUJ1 at day 20 of differentiation in
2D and 3D (1% Alg+Fn) cultures. (B) Quantification of TH and TUJ1 immunofluorescence stainings/co-
stainings in 2D and 3D cultures. Statistical differences were calculated by one-way ANOVA followed
by Tukey’s post hoc test to correct for multiple comparison * p ≤ 0.05, ***p ≤ 0.001
A
B
46
Next, we determined TH in co-staining with GIRK2. We were able to clearly identify GIRK2+ neurons
even though they were much less numerous than TH+ neurons (Fig. 12A). Also for this condition, we
were able to show that the proportion of both TH+ and GIRK2+ cells was significantly higher in the 3D
model system compared to the 2D system. Additionally, the fraction of TH+/GIRK2+ was again higher
under 3D conditions, although not significantly so (Fig. 12B).
FIGURE 12. Immunofluorescence stainings for TH and GIRK2. (A) Representative
immunofluorescence images showing the co-staining of TH with mDA neuronal maturation marker
GIRK2 at day 20 of differentiation in 2D and 3D (1% Alg+Fn) cultures. (B) Quantification of TH and
GIRK2 immunofluorescence stainings/co-stainings in 2D and 3D cultures. Statistical differences were
calculated by one-way ANOVA followed by Tukey’s post hoc test to correct for multiple comparison *
p ≤ 0.05
A
B
47
6.4.2. Western blot analysis
Western blot analysis was an additional method we used to further characterize the early mDA
neuronal differentiation of neurons in terms of marker gene expression. We found that the
expression levels of the transcription factors FOXA2 and LMX1A were markedly higher in the 3D
model system, compared to 2D differentiated cells at day 20 of differentiation.
In line with our immunofluorescence and RT-qPCR data, we observed a stronger upregulation in the
expression of the neuronal marker TUJ1 and the DA neuron marker TH in the neurons obtained using
the 3D platform at day 20 (Fig. 13).
FIGURE 13. Western blot analysis of whole cell lysates of control iPSC derived mDA neurons at day
20 of differentiation, cultured in 2D and 3D. Relative density values were normalized to the loading
control GAPDH.
48
When we analyzed the same markers at day 35 of differentiation, we could still observe an
upregulation in the transcription factors FOXA2 and LMX1A in the 3D culture system, but not as
strong as at day 20 of differentiation. The same was true also for the other two markers, TUJ1 and
TH. It is also important to note the high variability in the expression of key neuronal markers
observed in the 2D model system, which on the contrary was not present for the neurons generated
in the alginate microcapsules (Fig. 14).
FIGURE 14. Western blot analysis of whole cell lysates of control iPSC derived mDA neurons at day
35 of differentiation, cultured in 2D and 3D. Relative density values were normalized to the loading
control GAPDH.
49
6.5. Electrophysiological analysis of the neuronal cultures
Endogenous DA neurons in the human midbrain display spontaneous rhythmic firing of action
potentials from 2 to 10 Hz (Grace and Bunney 1984; Ramayya et al. 2014). The Ih current is an inward
depolarizing current mediated by the hyperpolarization-activated cyclic nucleotide-gated (HCN)
cation channels. It plays an essential role in regulating neuronal properties, synaptic integration and
plasticity, and synchronous activity in the brain. It is a typical characteristic of mature mesencephalic
DA neurons (Chu and Zhen 2010). Moreover, during neuronal maturation, the expression of Nav
channels increases and the cell becomes capable of generating APs spontaneously or following
depolarization.
In order to functionally assess the mDA neuronal maturation of our 2D and 3D cultures, we
performed electrophysiological recordings at day 30 of differentiation. Individual neurons were
recorded in whole-cell configuration in order to evaluate the presence of spontaneous firing activity
(APs) and the hyperpolarization-activated current (Ih).
At day 30 of differentiation, we observed that 35% of the recorded cells in the 3D neuronal culture
were able to generate spontaneous as well as evoked APs. The average spontaneous firing rate of
our 3D cultured neuronal cells was 2.7 ± 0.97 Hz (mean ± SEM; range 0.43-6.82 Hz, N=6; Tab. 6). This
frequency is in line with the values reported in relevant publications (Grace and Bunney 1984; Chu
and Zhen 2010; Ramayya et al. 2014; Hartfield et al. 2014). On the contrary, we could not record any
APs for the cells generated using our conventional 2D protocol at this stage of the differentiation
(Fig. 15A).
Moreover, 41% of the patched neurons, generated by the 3D system, displayed the voltage-sag
response upon hyperpolarizing current injections, which is a distinctive feature of DA neurons,
indicating the presence of the HCN-mediated currents in these cells (Fig. 15A). Again, none of the 2D
recorded neurons at day 30 was characterized by the presence of HCN-mediated currents.
Additionally, we examined the passive electrophysiological properties of our differentiated mDA
neurons. These properties are inherent to the cell membranes and could modulate neuronal
integration and firing patterns. We have found that the resting membrane potential (mV) was
significantly more negative in the cells of the 3D neuronal culture. Furthermore, membrane
capacitance (pF) was significantly higher in the same cells compared with cells cultured in 2D. We
could not observe a significant difference for the input resistance (MΩ).
50
FIGURE 15. Electrophysiological analyses of 2D and 3D cultures. (A) Representative traces from
whole cell patch clamp recordings of cells in 2D or 3D cultures at day 30. APs, Spontaneous action
potentials were observed only in cells cultured in 3D; Ih, the presence of the HCN-mediated current
was observed upon application of hyperpolarizing current steps at different intensities with -30 pA
increments. No spontaneous or evoked APs and no Ih could be recorded for the 14 recorded cells
cultured in 2D. In contrast, 35% of the 17 examined cells cultured in 3D showed spontaneous as well
as evoked APs, while the presence of Ih was recorded in 41% of these neurons. (B) Quantification of
passive electrophysiological properties of cells in 2D or 3D cultures at day 30. Statistical differences
were calculated by Mann-Whitney test * p ≤ 0.05
The passive and the active electrical properties, exhibited by the cells generated in the 2D and 3D
cultures, are summarized in Table 6.
TABLE 6. Summary of passive and active electrophysiological properties of the recorded neuronal cells generated in the 2D and 3D system.
Number of cells Vm (mV) Rm (M) Cm (pF) Spontaneous APs / Ih Evoked AP Na Currents K Currents
2D 14 -33 ± (-2) 848 ± 127 13 ± 1.4 0% / 0% 0/14 (0%) 86% 100%
3D 17 -41 ± (-2) 705 ± 78 19 ± 1.9 35% / 41% 6/17 (35%) 100% 100%
Values represent mean ± SEM, otherwise the percentage of cells is given. Vm, resting membrane potential; Rm, input resistance; Cm,
membrane capacitance; APs, spontaneous action potentials; Ih, Hyperpolarization-activated mixed cation current.
A
B
51
Overall, these data indicate that the DA neurons generated using the 3D model system reached
earlier a relatively advanced functional level of in vitro maturity when compared to neurons
generated using our conventional 2D protocol. Moreover, 3D neurons showed the two main
electrophysiological characteristics of mesencephalic DA neurons: the pacemaking firing capacity (i.e.
presence of spontaneous APs) and the functional expression of the Ih current.
6.6. Mitochondrial reactive oxygen species (mROS)
Oxidative stress, caused by disequilibrium between generation and detoxification of reactive oxygen
species (ROS), plays an important role in the cellular-damage and -death associated with
neurodegenerative diseases. The generation of ROS correlates with mitochondrial dysfunction, which
is a widely accepted pathogenic mechanism implicated in PD (Lin and Beal 2006; Dias et al. 2013).
Furthermore, increased oxidative stress is a well-known feature of iPSC-derived neurons with
mutations in PD related genes (Imaizumi et al. 2012; LaMarca et al. 2018).
We compared the mDA neurons differentiated with our 3D platform to those differentiated in 2D in
terms of mitochondrial superoxide (mROS) generation, as this phenotype could be the basis of future
experiments. For this purpose, we used the mitochondria targeted, superoxide sensitive, fluorogenic
dye MitoSox Red to detect mROS levels at day 10, 20 and 35 in both our healthy control line and an
iPSC-line carrying an α-synuclein (SNCA) triplication mutation.
Under both 2D and 3D conditions, we consistently observed higher mROS levels, indicated by
MitoSox fluorescence mean intensity, in the α-synuclein triplication mutant compared to the control
cell line. The difference was statistically significant for both 2D and 3D conditions at day 20 and day
35 of differentiation. The aberrant phenotype was observed already at day 10 of differentiation for
both conditions but at this time point it was significant only for the neurons generated using the 3D
alginate platform (Fig. 16).
These findings indicate that our 3D model system can recapitulate one important mitochondrial
phenotype observed in PD patients’-derived neurons and that this phenotype might be detectable
earlier during neuronal differentiation.
52
FIGURE 16. Mitochondrial superoxide levels (mROS) quantified with the fluorogenic dye MitoSox
Red. (A) Representative fluorescence images at different time points. (B) Quantification of MitoSox
intensity. The mean MitoSox intensity ± SEM is given as a measure of mROS levels. mDA neurons
differentiated from a control and an iPSC line carrying an α-synuclein triplication mutation (3x SNCA)
are compared at day 10, 20 and 35. Data are derived from two independent differentiation
experiments. Statistical differences were calculated by one-way ANOVA followed by Tukey's post hoc
test to correct for multiple comparisons * ≤ 0.05, ** p ≤ 0.01, **** p≤ 0.0001
6.7. Molecular analysis of long-term mDA neural differentiation on 3D
platform
PD is thought to be the consequence of damage accumulating progressively in the course of years,
possibly decades, in specific populations of post mitotic neurons. Thus, the finding that ageing is the
most important risk factor for PD is easy to explain. On the other hand, iPSCs represent rejuvenated
cells that lost the hallmarks imposed by ageing. This is bedeviling the development of a successful
iPSC-based cell culture system for the modeling of disease. Several approaches have been developed
Day 10 Day 20 Day 35 A
B
53
in order to deal with this complication. One of them is the long-term culture of differentiated mDA
neurons in order to recapitulate the ageing process in vitro. This is a challenging undertaking
considering that cells, especially neurons, cultured for long periods tend to lose viability.
Therefore, it was important to show that our 3D culture method is suitable also for long-term
maturation of iPSC-derived mDA neurons. For this reason, we kept mDA neurons differentiated both
in 2D or encapsulated in 1% Alg+Fn in culture for more than 200 days. At the end of this period, we
analyzed the expression of mature mDA neuronal and synaptic marker proteins in both groups via
RT-qPCR and immunofluorescence staining performed on cell aggregate sections.
The gene expression of the mature mDA marker proteins DAT, TH and GIRK2, as well as the pan-
neuronal marker TUJ1 was determined via RT-qPCR. We could observe significantly higher expression
levels of TH, GIRK2, and DAT in the neurons generated in the 3D model system in comparison to our
conventional 2D protocol (Fig. 17).
FIGURE 17. Comparative gene expression analysis via RT-qPCR between mDA neurons differentiated
in 1% Alg+Fn (3D) and 2D culture for more than 200 days. Data are presented as the mean ± standard
deviation from technical triplicates normalized to the gene expression in 2D culture. Statistical
differences were calculated by two-way ANOVA followed by Bonferroni post hoc test to correct for
multiple comparison * p ≤ 0.05, **p ≤ 0.01
In Figure 18A, we show that both mDA marker proteins DAT and TH are expressed in cells
encapsulated in alginate. The stained areas are partially overlapping indicating the co-expression of
both proteins. The most intense staining for both proteins was observed on the margins of the
54
sections. This could be due to a higher mDA neuron density overall or specifically in the periphery of
the cell aggregates (Fig. 18A-B).
Furthermore, we showed the formation of multiple synaptic connections in the neurons within the
aggregates, evaluating the expression of the presynaptic marker protein Synapsin 1 (Syn1) as well as
the postsynaptic density protein 95 (PSD95). While the Syn1 signal was located to neurites and
possibly cell bodies, the PSD95 staining resulted in a dotted pattern indicating a more confined
expression of the latter. In order to confirm their neuronal identity we costained the sections for the
neuronal marker microtubule associated protein 2 (MAP2) (Fig. 18B). In a 3D surface reconstruction
of synapse formation, we could illustrate the juxtaposed signals of Syn1 and PSD95 staining, which
might denote the presence of pre- and post-synaptic puncta and multiple synaptic connections (Fig.
18C).
55
FIGURE 18. Molecular analysis of long term mDA neural differentiation via immunofluorescence
staining. (A) Co-staining of TH and DAT. Magnified region shows overlapping staining. Scalebar
represents 100 µm (B) Co-staining for the presynaptic marker protein Synapsin1 (Syn1), the neuronal
marker microtubule associated protein 2 (MAP2) and the postsynaptic density protein 95 (PSD95). (C)
3D surface reconstruction of MAP2/Syn1/PSD95 staining showing formation of synaptic puncta
(white arrows).
A
B
C
56
Overall, it was confirmed that iPSC derived mDA neurons could be generated and sustained for at
least 200 days in our 3D culture system based on alginate as a biomaterial. The observed mDA
neuronal marker expression confirmed the successful maturation of the mDA neurons. The enhanced
expression of DAT, TH and GIRK2 in 3D culture may even indicate a favorable effect to the generation
of the respective cell lineage. However, the results have to be interpreted carefully, especially since
they derive from one experiment and have yet to be replicated.
57
7. DISCUSSION
7.1. Patient-specific neuronal cell models for PD research
The advent of iPSC technology enabled researchers for the first time to generate patient-specific
pluripotent cell lineages carrying virtually any genotype. These can be differentiated to potentially
any cell type to study the pathophysiology of disorders and identify novel therapeutic approaches.
However, the iPSC technology is limited by several factors. iPSC lines can retain epigenetic signatures
of their tissue of origin, and they sometimes do not gain a true pluripotent state (Cherry and Daley
2013). Thus, it is challenging to differentiate iPSCs into homogeneous neuronal populations for
disease modeling. Moreover, variations in the differentiation ability of different but also the same
cell lines have been reported (Choi et al. 2009). For this reason the correction of the disease
genotype via genetic engineering in patient’s iPSC lines is used to generate isogenic control lines
which are regarded as the best control for any disease model (Jungverdorben et al. 2017).
Furthermore, an inherent feature of iPSCs, the apparent reversal of cellular ageing occurring in the
course of reprogramming, poses a major challenge for the modeling of late onset disease. Efforts are
put into the development of techniques allowing the artificial induction of cellular ageing. One
promising approach is the ectopic expression of progeroid gene products, even though it is not clear
how closely normal ageing can be mimicked in such a way (Studer et al. 2015).
Protocols for the generation of mDA neurons have resulted in percentages of TH-positive neurons
ranging from 8% to 80%, implying that the generated cell populations remain heterogeneous (Engel
et al. 2016). One suitable possibility to produce more uniform cell populations may be the expansion
of relatively homogeneous midbrain FP progenitors, which has been reported to increase relative DA
neuron differentiation potential (Fedele et al. 2017). However, other studies reported much higher
DA neuron yields without progenitor expansion (Kriks et al. 2011; Reinhardt et al. 2013). In any case
the remaining heterogeneity gives room for further improvement in terms of DA neuron yield but
also maturity and functionality reached by different differentiation approaches. Thus, the goal of this
thesis was to present a multivariate picture of differentiation outcomes of our 3D culture system in
comparison with a 2D adherent culture system. This included the analysis of neuronal as well as early
and mature mDA neuron marker gene expression and electrophysiological characterization.
7.2. Setup of 3D system by encapsulation of hiPSCs with alginate hydrogels
The precise spatial organization and well timed cooperation and communication of cells allows for
the sustainment of complex living beings. The function of cells is profoundly influenced by their
extracellular microenvironment as well as by the cross-talk between different cell types (Alberts
58
2015). The ECM, in which cells are embedded, is an important part of this microenvironment. It helps
with tissue organization but can also be seen as a cellular extension and active participant in the
regulation of cellular function (Bissell and Barcellos-Hoff 1987). Furthermore, it has been shown that
cell size, volume and geometry constitute major cues altering gene expression (Bao et al. 2017). In
fact, several observations support the idea that cells cultured in 3D systems, where these factors can
be modelled to a certain extent, are more closely resembling their in vivo counterparts than cells
cultured in 2D on conventional rigid plastic or glass surfaces. As an example, the specification of
mesenchymal stem cells seems to be highly sensitive to three-dimensional matrix elasticity (Engler et
al. 2006). Another line of evidence is supported by the enhanced drug resistance of 3D tumor
cultures compared to more vulnerable single cell cultures of the same cells (Miller et al. 1985;
Hoffmann M.R. 1993). Also the restricted cell motility, tissue-like apoptosis and presence of cellular
ECM remodeling, observed under 3D but not 2D conditions, point towards a more in vivo like cell
behavior (Geckil et al. 2010). Furthermore, certain specific cellular phenotypes, such as the saltatory
migration of cortical interneurons, can be observed and studied in 3D cultures of brain assembloids
but not in 2D culture systems (Birey et al. 2017).
In the present thesis, we made use of ionically cross-linked alginate as a matrix for the 3D culture and
differentiation of iPSCs into mDA neurons. Alginate is a polysaccharide derived from brown algae
known for its ability to form hydrogels at physiological conditions enabling easy cell encapsulation
and retrieval. Biological functionality can be introduced to it by chemical modifications, for example
with ECM components or cell-binding peptides (DeVolder and Kong 2012; Andersen et al. 2015). It
has been reported that the stiffness of brain tissues changes significantly throughout developing
stages (Iwashita et al. 2014). Thus, during neuronal differentiation, there might be temporally
differential effects of alginate stiffness and fibronectin. However, cells embedded in a 3D matrix are
known to remodel their extracellular microenvironment, which may mask differential effects of initial
stiffness and matrix modifications at later differentiation stages (Geckil et al. 2010).
Our data show that the encapsulation of iPSCs in 1% and 2% Alg+Fn results in the formation of viable
cell aggregates. The significantly higher number of aggregates in 1% Alg+Fn suggests an increased cell
survival after encapsulation under this condition. The decreasing number of observed cell aggregates
over time may be explained by several factors: growing aggregates may fuse with others and be
counted as one or impede the sight of others underneath; furthermore, we observed that aggregates
in the periphery occasionally grew out of the alginate beads and were therefore not included in the
analysis. Some floating cell aggregates did attach to the bottom of the wells, showing a neuronal
morphology.
59
A form of dissociation-induced apoptosis referred to as anoikis is triggered upon dysplastic growth or
attachment to an inappropriate matrix of cells that normally exert their functions at well-defined
locations in vivo. The resulting poor survival of these cells in vitro represents an obstacle to research
(Taddei et al. 2012). A possibility to decrease the activation of anoikis related pathways is the
pharmacological inhibition of dissociation induced cell death. In this context, the RHO associated
kinase inhibitor Y27632 (RI) was shown to permit the survival of dissociated hESCs (Watanabe et al.
2007) and described as a crucial factor for the sustainment of hESC viability during the first three
days after encapsulation in alginate (Chayosumrit et al. 2010; Kim et al. 2013). We were able to show
the same for iPSCs encapsulated in alginate of different compositions. Very few cell aggregates were
observed after encapsulation without RI treatment under all conditions.
Based on the importance of proper cell-ECM interactions described in the literature (Bozza et al.
2014; Caliari and Burdick 2016; Andersen et al. 2015), we hypothesized that enhancing these
interactions could further support the viability and differentiation of our encapsulated iPSCs.
Therefore, we chose to add the glycoprotein fibronectin, a ubiquitous ECM component frequently
used to coat culture surfaces for diverse cell types, to the alginate matrix and examine its effect on
cell survival and growth. Our data show a highly significant increase in the observed numbers of cell
aggregates in 1% or 2% Alg+Fn. Further optimization of fibronectin concentration and testing of
other ECM components or modifications might lead to an additional increase in cell aggregate
numbers.
To examine cell viability more closely, we made use of a fluorescence staining method for the
discrimination between live and dead cells. This enabled the evaluation of cell viability within
individual aggregates. Overall, our results suggest that the treatment with RI, to inhibit disassociation
related cell-death, is crucial to sustain cell viability after encapsulation. Additionally, the introduction
of cell-ECM interactions by fibronectin further supported cell viability for the examined period.
Regarding the size of cell aggregates we observed minor differences between different conditions at
day 5 and 10. However, a highly significant increase in aggregate size for 1% and especially 2% Alg+Fn
became apparent at day 20 while aggregate size did not further increase in alginate alone. This
suggests a prolonged period of cell proliferation or a possible increase in cell volume and in cell
mobility due to cell-ECM contacts upon the addition of fibronectin.
The size of cellular aggregates, rather than the size of the microcapsules, has been reported as
limiting factor influencing the growth of encapsulated cells due to restricted nutrient and oxygen
diffusion (Huang et al. 2012). The strong increase in aggregate size in 2% Alg+Fn might therefore not
be an advantage as it could finally result in cellular necrosis in the aggregate core. It should be noted
60
that most analyzed aggregates did not have a spherical but rather a spindle- or lens-like shape. Thus,
as we used aggregate length as a proxy for size, the actual diffusion distances from aggregate surface
to aggregate core cannot be deduced from aggregate sizes.
7.3. mDA neuronal differentiation of hiPSCs in 3D alginate culture system
The cellular 3D microenvironment is an important determinant of gene expression, which in turn
influences cellular identity and function (Bissell and Barcellos-Hoff 1987; Engler et al. 2006; McKee
and Chaudhry 2017). Thus, we compared the gene expression of cells differentiated in 1% or 2%
Alg+Fn to that of cells differentiated in 2D culture. RT-qPCR showed that overall the expression of
early neuronal as well as mature mDA-neuron markers was stronger under 3D conditions. We
observed a slight advantage of 1% Alg+Fn as TH expression was highest under this condition at both
day 10 and 20 of differentiation.
The co-expression of the transcription factors LMX1A and FOXA2 is essential for the specification of
mDA neurons (Arenas et al. 2015; Engler et al. 2006). Additionally, it has been proven important for
the generation of high quality mDA neurons in vitro (Kriks et al. 2011). We showed the expression of
both LMX1A and FOXA2 under 2D and 3D conditions at day 10 via immunofluorescence staining.
Furthermore, we demonstrated, via western blot analysis, that LMX1A and FOXA2 expression levels
were significantly increased under 3D conditions at days 20 and 35 with respect to 2D culture.
The intermediate filament protein Nestin and the transcription factor Pax6 are frequently used as
markers for neural progenitors (Chambers et al. 2009; Reinhardt et al. 2013; Kim et al. 2013; Adil et
al. 2017). We were able to confirm the expression of both Nestin and Pax6 via immunofluorescence
staining at day 10 of our 3D differentiation in 1% Alg+Fn as well as in 2D culture. The numbers of
positive cells for both markers were not significantly different under 2D and 3D conditions. However,
RT-qPCR data indicated a significantly higher Pax6 expression level in 3D culture at day 10.
TH, the rate limiting enzyme in dopamine production, is crucial for mDA neuronal function and
commonly used as a marker for mature DA neurons. Thus, in order to assess the maturation state of
our cells at day 20, we analyzed the expression of TH by immunofluorescence co-staining with
different neuronal markers. We were able to show that TH and TUJ1 expression was significantly and
consistently stronger in cells cultured in 1% Alg+Fn than in 2D cultured cells, which was confirmed via
RT-qPCR at day 20 as well as at day 35. Additionally, GIRK2 expression could be shown in our
neuronal cultures at day 20 via immunofluorescence staining, with an increased expression in our 3D
model system. RT-qPCR showed increased DAT expression under 3D conditions but no significant
difference for GIRK2 between 2D and 3D culture at day 20. These findings indicate that the
61
differentiation process was already well defined at day 20. The overall low expression of GIRK2 and
DAT may be due to the relatively early time point of analysis. The consistent observation of double
positively stained cells is nevertheless supporting the notion that our cells underwent differentiation.
In order to further increase the reliability of our 3D culture system, it might be helpful to monitor the
stiffness of the alginate matrix via rheological measurement of the elastic moduli, as reported in the
literature, to ensure the consistency of this parameter found to be important for early neurogenic
differentiation (Saha et al. 2008; Keung et al. 2012).
Another realm for optimization could be the timing of exposition to differentiation factors. The
differentiation protocol we used has been developed for a 2D culture system. It might well be that
the dynamics of cellular responsiveness to these factors are different in our 3D culture. It is
conceivable that the 3D culture results in a more rapid differentiation, which is supported by the
higher expression levels of neural progenitor and mDA neuron markers at day 10 in our 3D culture
system. This would be in line with the findings of a hESC based study by Kim et al. (Kim et al. 2013). In
order to further explore these data, gene expression patterns should be analyzed at a higher
temporal resolution.
The in vitro generation of mature iPSC derived neuronal cells is challenging. iPSCs and their
derivatives usually do not reach a fully mature state due to the reversal of cellular ageing during
reprogramming. This poses a major obstacle for the modeling of late onset diseases. Many strategies
have been developed in order to face this problem (Studer et al. 2015; Jungverdorben et al. 2017).
The most basic may be the prolongation of culture periods up to several months (Ho et al. 2015),
even though post-mitotic neurons are difficult to keep in culture over long periods of time as they
are vulnerable and prone to detachment from culture surfaces.
We have shown that our iPSC derived neurons can be maintained in 3D culture for more than 200
days. Immunofluorescence analysis confirmed that these neurons co-expressed the mDA neuron
markers TH and DAT. Additionally, RT-qPCR experiments indicated an increased expression of the
mDA neuron markers TH, DAT and GIRK2 under 3D conditions. Moreover, using a 3D surface
reconstruction of synapse formation, we were able to reveal the presence of pre- and postsynaptic
puncta and multiple synaptic connections.
The problem of cell detachment upon long-term culture can be circumvented with our 3D culture
system but slow experiment turnaround remains an issue. Furthermore, we observed slow but
persistent growth of cell aggregates in this system, indicating still the presence of some proliferating,
immature cells and probably leading to insufficient nutrient and oxygen transport within aggregates.
This may alter cellular states, impede proper maturation and result in cellular necrosis.
62
The expression analysis of specific neuronal-, mature mDA- and synaptic marker- proteins is an
important way to assess the success of differentiation but the broader goal has to be the generation
of fully functional excitable mDA neurons. Thus, it is crucial to characterize the differentiated cells in
terms of electrophysiological activity. We did so by performing electrophysiological recordings in
whole-cell patch-clamp configuration in order to evaluate the presence of spontaneous APs and Ih
current. At a relatively early stage of differentiation (day 30), these characteristics were exclusively
observed in cells generated in 3D culture. The measured average firing rate of the recorded cells was
within the range reported for mDA neurons in the literature (Grace and Bunney 1984; Chu and Zhen
2010; Ramayya et al. 2014; Hartfield et al. 2014). This indicates that the 3D culture system better
supports the generation of mature functional mDA neurons, which is further emphasized by the
recorded passive electrophysiological properties.
With this thesis we aimed at providing a contribution to the improvement of a cellular model of PD
which can be used to advance the understanding of the mechanisms underlying the disease.
Oxidative stress plays a central role in the degeneration of DA neurons in PD. Several mechanisms
and sources of mROS production, including mitochondrial dysfunction, have been identified (Dias et
al. 2013; Imaizumi et al. 2012). In order to examine the utility of our 3D model system to recapitulate
known disease-related phenotypes, we chose to investigate mROS production in a 3D differentiated
α-synuclein triplication mutant cell line in comparison to a control cell line. Indeed, we were able to
demonstrate that the mROS levels were significantly higher in the mutant cell line under both 2D and
3D conditions at days 20 and 35. Intriguingly, at day 10 this difference was already significant under
3D but not under 2D conditions. This suggests that our 3D model might hold the potential for the
earlier detection of relevant disease phenotypes compared to 2D culture.
Overall, our data suggest that our alginate based 3D culture system is suitable for the directed in
vitro differentiation of mDA neurons. Several lines of evidence indicate an enhancing effect of 3D
compared to 2D culture in terms of the differentiation and maturation of the generated neurons,
although additional analyses need to be performed in order to get further insights on the quality of
the obtained neurons.
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8. SUMMARY
In this thesis we investigated the potential of an alginate based 3D culture system to improve the
performance of an established 2D protocol for the generation of mDA neurons from iPSCs. In the first
part, we identified a biomaterial combination that supported the short and long-term survival of
iPSCs embedded in alginate beads. In the second part, we focused on the comparison of early and
late marker gene expression patterns observed for neurons cultured in 2D and 3D conditions.
Additionally, we set out to probe the functional maturity of mDA neurons differentiated in our 3D
culture system by electrophysiological characterization and demonstrated that our 3D model was
able to recapitulate a known mitochondrial dysfunctional phenotype. Furthermore, we showed that
iPSC-derived mDA neurons differentiated in 3D can be kept in culture for more than 200 days.
The advent of cellular reprogramming and iPSC technology in combination with directed
differentiation protocols made it possible to generate patient specific disease affected cell types in
vitro. However, current culture systems for neuronal differentiation show a variable reproducibility
and yield neurons with low degrees of functional maturation. In this work, we tested different
scaffold biomaterial compositions and identified 1% alginate modified with fibronectin as the most
suitable scaffold for differentiation of iPSCs in 3D culture. Furthermore, we showed that the
treatment with RI is essential for the initial survival of iPSCs embedded in this biomaterial. We
demonstrated by RT-qPCR and western blot analyses that the expression levels of neuronal
commitment as well as mature mDA neuron markers, at day 10, 20 and 35, were higher in 3D with
respect to 2D cultures. By electrophysiological analysis at day 30, we found that a significant
proportion of our mDA neurons differentiated in 3D were able to generate spontaneous action
potentials. In contrast, no spontaneous action potentials could be recorded at day 30 for mDA
neurons differentiated in 2D. Additionally, we reported that mROS levels were significantly different
between mDA neurons differentiated from a control iPSC line and those differentiated from an α-
synuclein triplication mutant iPSC line in both 2D and 3D cultures at days 20 and 35. Interestingly, at
day 10 the difference was only significant for 3D cultured mDA neurons. We kept differentiated mDA
neurons in 3D culture for more than 200 days and showed that the mDA neuron marker expression
levels were increased compared to 2D culture at this time point. Further, we confirmed the presence
of synaptic connections formed by these neurons by immunofluorescence stainings.
These data indicate that our alginate based 3D culture system represents a tool for the reliable and
rapid derivation of more mature and functional mDA neurons from iPSCs with respect to
conventional 2D culture systems. However, the system has to be tested on other, especially patient-
derived, iPSC lines, and its potential for the analysis of disease-specific cellular phenotypes has to be
further validated.
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9. PERSPECTIVES
Most in vitro neurodegenerative disease modeling studies are so far based on conventional 2D cell
culture systems. However, 3D cell culture models are thought to better mimic the cell growth
encountered in vivo and support the expression of tissue-specific genes and proteins (Geckil et al.
2010). Therefore, we consider it important to investigate the potential of 3D culture to support the
generation of mature and functional iPSC-derived mDA neurons for PD modeling. In order to
emphasize and validate the results produced in this thesis, it will be crucial to expand and enrich the
collected data using additional technologies to further compare and characterize our 2D and 3D
neuronal cultures. A higher temporal resolution of gene expression, especially in the early phase of
differentiation, could help to optimize the differentiation schedule. Additionally, the gene expression
analysis is currently being extended to later time points in order to further characterize the mDA
neuron maturation. Moreover, RNAseq analysis is employed to generate an even more complete and
comprehensive picture of the gene expression patterns.
We have shown that cells differentiated with our 3D culture model were able to recapitulate the
increased mROS phenotype of an α-synuclein triplication mutant cell line. It will be interesting to
determine whether other major phenotypic differences between mDA neurons derived from patient
and control iPSCs differentiated with our 3D culture platform can be detected. Interesting PD-related
phenotypes include mitochondrial dysfunction characterized by altered electron transport complex I
activity, mitochondrial integrity, mitochondrial membrane potential, mitophagy, and respiration. In
this context, it would be ideal to introduce the use of isogenic iPSC controls. This would enable the
identification of more subtle phenotypic effects owed almost only to genetic differences.
Further optimization could be the functionalization of alginate with other extracellular matrix
components and factors. In order to increase the reproducibility, the use of an automated bead
formation and of 3D bioprinters might be ideal. In the long run, the use of novel rapidly evolving
technologies including microfabricated cell culture devices and microfluidics approaches will likely
provide the best way to create in vivo like microenvironments.
65
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