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Extracellular Matrix- and
Pluripotent Stem Cell-based
Tissue Engineering of the Kidney
vorgelegt von
Dipl.-Ing.
Iris Fischer
an der Fakultät III - Prozesswissenschaften
der Technischen Universität Berlin
zur Erlangung des akademischen Grades
Doktor der Ingenieurwissenschaften
- Dr.-Ing. -
genehmigte Dissertation
Promotionsausschuss:
Vorsitzender: Prof. Dr. Jens Kurreck
Gutachter: Prof. Dr. Roland Lauster
Gutachter: Dr. Andreas Kurtz
Tag der wissenschaftlichen Aussprache: 27.11.2019
Berlin 2020
„Indes sie forschten, röntgten, filmten, funkten,
entstand von selbst die köstlichste Erfindung:
der Umweg als die kürzeste Verbindung
zwischen zwei Punkten.“
Erich Kästner
I
Zusammenfassung
Komplexe, dreidimensionale (3D) Organmodelle sind neuartige biotechnologische
Werkzeuge für die Erforschung von Regenerations- und Krankheitsmechanismen sowie für
die Medikamentenentwicklung. Ein solches Modell der Niere könnte die jahrzehntelange
Stagnation in der Entwicklung neuer Behandlungsmethoden für Patienten mit chronischem
Nierenversagen durchbrechen, sowie die hohe Durchfallrate neuer Medikamente in
klinischen Tests durch nephrotoxische Effekte reduzieren. Ziel der vorliegenden Arbeit war
daher die Entwicklung eines humanen 3D Nierenmodelles.
Ein funktionsfähiges Nierenmodell sollte die Architektur und die Zelltypen der Niere, sowie
die mechanischen Eigenschaften und die Zusammensetzung der extrazellulären Matrix
nachahmen und zudem perfundiert sein. Daher wurde ein Scaffold-basierter Ansatz der
Gewebezüchtung auf der Basis von dezellularisierten ganzen Rattennieren gewählt, die mit
humanen Nierenvorläuferzellen und Endothelzellen, differenziert aus induzierten
pluripotenten Stammzellen, rezellularisiert werden sollten.
Dieser Ansatz machte die Entwicklung eines Perfusionsbioreaktors und einer
Steuerungssoftware nötig, die die De- und Rezellularisierung der Nieren sowie die
darauffolgende In-vitro-Kultivierung erst ermöglichten.
Dezellularisierung ist die Entfernung aller Zellen eines Organs, bei der die extrazelluläre
Matrix (EZM) in ihrer nativen Architektur und Zusammensetzung erhalten bleibt. In dieser
Arbeit wurde durch den Vergleich des Einflusses verschiedener Detergenzien sowie
Temperaturen gezeigt, dass für die Dezellularisierung von Nierengewebsstücken das
Untertauchen in dem milden ionischen Detergens Natriumdesoxycholat (SDC) bei 4 °C
optimal ist. Für die Dezellularisierung ganzer Nieren durch Perfusion ist jedoch das starke
ionische Detergens Natriumdodecylsulfat (SDS) nötig. Sowohl die Minimierung der SDS-
Konzentration und -Anwendungsdauer als auch der Temperatur während der
Dezellularisierung verbessern dabei die Qualität der dezellularisierten EZM. Alle Ergebnisse
wurden mittels eines punktebasierten Bewertungssystems, welches ebenfalls im Rahmen
dieser Arbeit entwickelt wurde, objektiv und standardisiert beurteilt.
Um eine effiziente Rezellularisierungsstrategie zu identifizierten wurden Zellen mit oder
ohne Hochdruck durch die Nierenarterie, mit oder ohne Vakuum durch den Ureter oder
II
durch eine direkte Injektion in die dezellularisierten Nieren eingesät. Der Gefäßbaum konnte
erfolgreich mit Endothelzellen, die durch die Nierenarterie eingesät wurden, rezellularisiert
werden. Die Rezellularisierung des Parenchyms mit Nierenvorläuferzellen resultierte jedoch
mit allen getesteten Rezellularisierungsstrategien in geringen Wiederbesiedlungs-
effizienzen. So konnten maximal 1% des Parenchyms wiederbesiedelt werden, zudem
entstanden Schäden in der Architektur und die Anordnung der Zellen entsprach nicht den
physiologischen renalen Strukturen.
Parallel dazu wurde der Einfluss der mechanischen und biochemischen Eigenschaften der
EZM auf die Ausreifung der Nierenvorläuferzellen untersucht. Dazu wurden diese auf
Oberflächen verschiedener Steifigkeiten und EZM-Beschichtungen kultiviert. Mit
steigender Steifigkeit reifen die Nierenvorläuferzellen zunehmend in renale
Tubulusepithelzellen aus, wohingegen sich die Podozytenausreifung invers verhält. Zudem
wurde nachgewiesen, dass das EZM-Protein Laminin, im Gegensatz zu Collagen IV, die
Ausreifung der Nierenvorläuferzellen in renale Tubulusepithelzellen fördert, wobei
zwischen den Laminin-Isoformen 511 und 521 kein Unterschied besteht.
Auch wenn mit den gewählten Methoden kein Nierenmodell generiert werden konnte, so
markieren doch die technischen Entwicklungen und die Erkenntnisse, die in dieser Arbeit
gewonnen worden, einen weiteren Schritt in Richtung eines humanen 3D Nierenmodells.
III
Abstract
Complex, three-dimensional (3D) organ models are novel biotechnological tools for
research on regeneration and disease mechanisms as well as drug development. An organ
model of the kidney is urgently needed to break through decades of stagnation in the
development of new treatment methods for patients with chronic kidney disease and to
reduce the high failure rate of drugs in clinical tests due to nephrotoxic effects. The aim of
this thesis was therefore the development of a human 3D kidney model.
A functional kidney model should emulate the architecture and cell types of the kidney, as
well as the mechanical properties and composition of the extracellular matrix. In order to
emulate the function of the kidney, the model must be perfused. Therefore, a scaffold-based
tissue engineering approach was chosen on the basis of decellularized whole rat kidneys,
which should be recellularized with human renal precursor cells and endothelial cells
differentiated from induced pluripotent stem cells.
This approach required the development of a perfusion bioreactor and control software,
which enabled the de- and recellularization of the kidneys as well as the subsequent in vitro
cultivation.
Decellularization is the process of removing all cells of an organ while preserving the
extracellular matrix (ECM) in its native architecture and composition. The influence of
different detergents and temperatures was analyzed, and the results showed that for the
decellularization of tissue pieces immersion in the mild ionic detergent sodium deoxycholate
(SDC) at 4 °C is optimal. However, decellularization of whole kidneys by perfusion required
the strong ionic detergent sodium dodecyl sulfate (SDS). To improve the quality of the
decellularized ECM it is beneficial to minimize the SDS concentration and application time
as well as the temperature. All results were evaluated objectively and standardized by
applying a point-based scoring system, which was also developed in the course of the thesis.
Next, an efficient recellularization strategy had to be identified. The tested strategies
included cell seeding through the renal artery with or without high pressure, seeding through
the ureter with or without vacuum and direct injection into the parenchyma with a syringe.
The vascular tree of the decellularized kidney was successfully recellularized with
endothelial cells seeded via the renal artery. However, recellularization of the parenchyma
with renal progenitor cells resulted in low seeding efficiencies in all applied seeding
IV
approaches. A maximum of 1% of the parenchyma could be repopulated by recellularization.
In addition, the recellularization caused damage to the scaffold architecture and the
arrangement of the cells did not correspond to the physiological renal structures.
In parallel, the influence of mechanical and biochemical properties of the ECM on the
maturation of renal progenitor cells was investigated. The cells were cultivated on surfaces
of different stiffnesses and ECM coatings. With increasing stiffness, the renal progenitor
cells increasingly matured into renal tubular epithelial cells, whereas podocyte maturation
behaved inversely. In addition, the analysis revealed that the ECM protein laminin, in
contrast to collagen IV, promotes the maturation of renal progenitor cells into renal tubular
epithelial cells, although no difference was detected between the laminin isoforms 511 and
521.
Although no kidney model could be generated with the investigated methods, the technical
developments and the findings of this thesis mark a further step on the way to a human 3D
kidney model.
V
Content
1 INTRODUCTION................................................................................................ 1
1.1 The need for better in vitro kidney models .......................................................................................... 1
1.2 The kidney .............................................................................................................................................. 2
1.2.1 Functions, cell types and architecture of the kidney ....................................................................... 2
1.2.2 Extracellular matrix of the kidney .................................................................................................. 5
1.2.3 Renal organogenesis ..................................................................................................................... 12
1.3 Tissue engineering of the kidney ......................................................................................................... 13
1.3.1 Cell source .................................................................................................................................... 14
1.3.2 Architecture and perfusion ........................................................................................................... 16
1.3.3 De- and recellularization .............................................................................................................. 18
2 AIM ................................................................................................................. 22
3 MATERIALS AND METHODS ............................................................................ 23
3.1 Materials ............................................................................................................................................... 23
3.1.1 Cells .............................................................................................................................................. 23
3.1.2 Reagents ....................................................................................................................................... 23
3.1.3 Consumables ................................................................................................................................ 25
3.1.4 Kits ............................................................................................................................................... 26
3.1.5 Antibodies and fluorescent dyes ................................................................................................... 27
3.1.6 qPCR gene expression assays ....................................................................................................... 27
3.1.7 Instruments ................................................................................................................................... 27
3.1.8 Software and data bases ............................................................................................................... 29
3.2 Methods ................................................................................................................................................ 30
3.2.1 Cell culture ................................................................................................................................... 30
3.2.2 Decellularization of porcine kidney tissue by immersion and agitation ....................................... 34
3.2.3 Decellularization of whole rat kidneys by perfusion .................................................................... 35
3.2.4 Characterization of decellularized kidneys ................................................................................... 38
3.2.5 Recellularization of immersion-decellularized porcine kidney scaffolds ..................................... 40
3.2.6 Recellularization of perfusion-decellularized whole rat kidneys.................................................. 40
3.2.7 Characterization of recellularized kidneys ................................................................................... 42
3.2.8 Tuning of the pressure and pH controllers ................................................................................... 43
3.2.9 PDMS gel assay ........................................................................................................................... 44
3.2.10 Quantitative polymerase chain reaction ....................................................................................... 45
3.2.11 Histology and immunofluorescence staining................................................................................ 46
3.2.12 Flow cytometry ............................................................................................................................ 48
3.2.13 Statistical analysis ........................................................................................................................ 49
4 RESULTS ........................................................................................................... 50
4.1 Development of a perfusion bioreactor for de- and recellularization of whole kidneys ................ 50
4.1.1 Setup ............................................................................................................................................. 50
4.1.2 Software development for the control of the perfusion bioreactor ............................................... 53
4.1.3 Tuning the controllers of the perfusion bioreactor ....................................................................... 57
VI
4.2 Identification of an optimal decellularization strategy for kidney tissue using factor screening in
an immersion and agitation setting .................................................................................................... 66
4.2.1 Analysis of histology and composition after decellularization by immersion and agitation ........ 67
4.2.2 Biocompatibility testing of immersion-decellularized kidney tissue by recellularization with
intermediate mesoderm cells ........................................................................................................ 72
4.2.3 A scoring system facilitates the comparison of immersion-decellularization strategies .............. 75
4.3 Decellularization of kidneys by perfusion .......................................................................................... 77
4.3.1 Analysis of histology and composition after decellularization by perfusion ................................ 78
4.3.2 Biocompatibility testing of perfusion-decellularized kidneys by reendothelialization with human
umbilical vein endothelial cells .................................................................................................... 80
4.3.3 Applying the scoring system for the comparison of perfusion-decellularization methods ........... 83
4.4 Recellularization of perfusion-decellularized kidneys ...................................................................... 86
4.4.1 Reendothelialization with hiPSC-derived endothelial cells .......................................................... 87
4.4.2 Recellularization of the kidney parenchyma with hiPSC-derived renal progenitor cells ............. 90
4.5 The effect of stiffness and ECM composition on renal progenitor cell maturation ....................... 97
4.5.1 Optimization of PDMS gels for cell culture ................................................................................. 98
4.5.2 Investigation of renal progenitor cell maturation ......................................................................... 99
5 DISCUSSION ................................................................................................. 103
5.1 The perfusion bioreactor enables kidney de- and recellularization .............................................. 104
5.2 Kidney decellularization .................................................................................................................... 107
5.2.1 The decellularization scoring system standardizes the evaluation of decellularization results .. 107
5.2.2 The effect of the detergent on kidney decellularization by immersion....................................... 108
5.2.3 The effect of the temperature on kidney decellularization by immersion .................................. 111
5.2.4 Decellularization outcomes by perfusion differ to decellularization outcomes by immersion ... 112
5.3 Generation of an in vitro kidney model by recellularization of decellularized kidneys ............... 115
5.3.1 Successful reendothelialization of the renal vascular tree .......................................................... 115
5.3.2 Inefficient recellularization of the renal parenchyma ................................................................. 117
5.4 Stiffness and composition of the cell culture surface influence renal progenitor cell maturation ....
............................................................................................................................................................. 120
6 OUTLOOK ...................................................................................................... 123
7 REFERENCES .................................................................................................. 125
8 APPENDIX ..................................................................................................... 136
8.1 Supplemental information ................................................................................................................. 136
8.2 Abbreviations ..................................................................................................................................... 138
8.3 List of figures ...................................................................................................................................... 140
8.4 List of tables ....................................................................................................................................... 142
8.5 Acknowledgements ............................................................................................................................ 143
Introduction
1
1 Introduction
1.1 The need for better in vitro kidney models
The kidney is the main excretory organ of the human body. It eliminates not only metabolic
waste products, such as urea, uric acid or ammonia, but also toxins and drugs via the urine.
Furthermore, it regulates water, mineral and acid-base homeostasis and acts as an important
endocrine organ. It produces the hormones erythropoietin and thrombopoietin and thereby
stimulates the generation of erythrocytes and platelets. Additionally, the kidney secretes the
hormones renin and angiotensin-converting enzyme, which regulate blood pressure via the
renin-angiotensin-aldosterone system1.
Despite its extensive functions and great importance for the human body, the human kidney
possesses a strictly limited capacity to regenerate after injury. Although cellular regeneration
can reconstitute injured portions of existing nephrons, the kidney’s functional units, repeated
kidney injury will eventually lead to the loss of this repair capacity. Moreover, there is no
neonephrogenesis after birth in humans. Thus, no new nephrons arise after injury to
compensate for the damage. Fortunately, under normal circumstances, the number of
nephrons at birth is sufficient to maintain kidney function throughout the human lifetime,
despite the lack of kidney regeneration. At the age of 60, however, their number has halved2–
4.
When, in addition to the normal aging process, diseases, such as diabetes, hypertension or
glomerulonephritis, damage the kidney, chronic kidney disease (CKD) can develop. CKD
progresses gradually and culminates in complete renal failure, called end-stage renal disease
(ESRD). Around 10% of the population suffer from CKD of which 90% are older than 65
years. The CKD prevalence is expected to rise dramatically with the ongoing aging of the
population5,6.
The treatment of renal failure has hardly changed in the last decades and dialysis and
transplantation are still the only two treatment options. Hemodialysis is an artificial blood
filtration system that substitutes the excretory function of the kidney. In the European Union
about 400,000 patients rely on this treatment. However, these patients suffer from side
effects, such as fatigue, headaches or low blood pressure, are vulnerable to infections and
Introduction
2
have to attend three 4-hour sessions weekly to survive, and still have a reduced life
expectancy5,7. A better long-term survival and quality of life can be achieved by kidney
transplantation. However, there is a dramatic shortage of donor organs. Moreover, transplant
patients rely on immunosuppressive treatment to prolong the transplant’s function, which
increases their risk to develop cancer or diabetes. Since the underlying kidney damaging
disease is often still active after transplantation, transplants will only stay functional for an
average of 10 years, despite this immunosuppressive treatment and human leukocyte antigen
matching before donor selection5.
The need for new therapies for kidney failure is therefore evident. However, countless
studies in human patients, in animal models or in two-dimensional (2D) cell culture models
have not achieved this goal8.
Moreover, these models too often fail when they are applied in preclinical screenings, since
about 7% of drug candidates entering a clinical trial fail due to drug-induced nephrotoxicity.
Only 8% of drugs pass these extremely expensive and time-consuming clinical trials8,9.
Thus, a novel 3D human kidney model that facilitates the study of disease mechanisms, the
development of new drugs, cell therapies or organ replacement strategies is urgently needed.
To date no human kidney model has been developed that includes all renal cell types and
shows the correct renal architecture and functions, yet the medical need demands a fast
implementation. The development of such a model is therefore the major aim of this thesis.
1.2 The kidney
Before attempting to build a kidney model in vitro, it is necessary to fully understand
function, architecture, composition and organogenesis of the kidney in vivo.
1.2.1 Functions, cell types and architecture of the kidney
The kidney is a paired, bean-shaped organ with a highly specialized architecture. These
complex structures and the more than 20 different renal cell types are essential for the
manifold renal functions10.
Introduction
3
The functional unit of the kidney is the nephron, consisting of a glomerulus and renal tubule
that drains into the collecting duct. A human kidney contains approximately 1 million
nephrons11.
Figure 1: Anatomy of the human kidney. (A) The human kidney is a multilobular, bean-shaped organ.
Macroscopically it is subdivided into cortex, medulla and pelvis, as marked. (B) Magnification of one lobule,
showing one nephron, collecting duct and the vascular network, as labeled. * indicate sections that are part of
the loop of Henle. Figure adapted from Westphal 201212, images reproduced from CellFinder database13.
Glomeruli are the filtration units of the kidney and are located in the cortex. The glomerulus
is composed of a capillary bundle surrounded by the double-walled epithelial Bowman's
capsule. The filtration barrier is formed from three layers. The first layer is formed by
specialized endothelial cells that line the capillary’s lumen. Their cell bodies are highly
fenestrated and covered in a thick glycocalyx14,15. Their basal side is attached to the unique
glomerular basement membrane (GBM), the second filtration layer. The third layer of the
filtration barrier is built by podocytes that line the opposite side of the GBM. Podocytes are
a highly specialized epithelial cell type. Their interdigitated foot processes form the slit
diaphragm. All layers are highly negatively charged by the deposition of the polyanionic
glycoprotein podocalyxin16,17. When blood flows from the afferent arteriole through the
capillary bundle and out through the efferent arteriole, these three layers work like a filter
through which only molecules smaller than 50 kDa can pass.
This filtration process produces 150 l of primary urine daily in an average adult human. The
primary urine drains into the tubular part of the nephron. The task of the tubule is to reabsorb
Introduction
4
99% of the filtered water and 90% of the solutes of the primary urine to generate the 1,5 l of
final urine daily1,18.
The proximal tubule is the first part of the tubule system after the glomerulus. It is convoluted
and lined with cuboidal epithelium. The apical surface of the epithelium displays a
characteristic brush boarder surface and the basal side is characterized by interdigitating
basolateral folds. Both properties multiply the surface area of the cells and permit the fast
reabsorption of water, glucose, NaCl and amino acids and secretion of drugs and ammonia
into the primary urine. Basolaterally located, the sodium potassium-pump (Na+/K+-ATPase)
produces the ion gradient that powers the secondary active transport on the apical side by
symporters for Na+, glucose, amino acids etc.19. Water reabsorption is a passive process.
Water follows the Na+ gradient that is maintained by the Na+/K+-ATPase through the water
channel aquaporin 1 (AQP1). Tubular epithelial cells secrete the reabsorbed substances into
the basolaterally located renal interstitium. The tubules are surrounded by peritubular
capillaries that absorb these substances and reintroduce them into the bloodstream20,21.
Next, the loop of Henle dips down into the medulla. It is lined by thin epithelial cells without
a brush boarder. The descending part of the loop is water permeable whereas the ascending
part is water impermeable. Only in the ascending part the Na+/K+-ATPase powers the ion
uptake by the Na-K-Cl cotransporter. The ions pass into the interstitial space through
basolateral channels, making the medulla salty. This drives the passive water reabsorption
and further concentration of the urine in the descending loop of Henle1,18,22.
The fluid passes next through the distal tubule, where the urine composition is fine-tuned.
More ions are resorbed but in contrast to the earlier tubule parts, here the resorption is
regulated. For example, the Ca2+ resorption is regulated by the parathormone (PTH).
Furthermore, the distal tubule is part of the juxtaglomerular complex, a structure close to the
glomerulus that senses the blood pressure and releases the hormone renin in response1,18,23.
Renin triggers the renin-angiotensin-aldosterone system (RAAS), a hormone system that
regulates the systemic blood pressure and volume.
Multiple distal tubules drain into one collecting duct that regulates the final water resorption.
Like the distal tubule, the collecting duct is susceptible to aldosterone and the antidiuretic
hormone (ADH), two hormones that are part of the RAAS. Aldosterone, produced in the
adrenal gland, increases the amount of Na+/K+-ATPase, thereby causing Na+ reabsorption
which is followed by passive water reabsorption. ADH, produced in the pituitary gland,
increases the expression of the water channel aquaporin 2 in the collecting duct. Both
Introduction
5
hormones therefore decrease the amount of water that is otherwise lost with the urine and
hence raise the blood pressure1,18,24. Erythropoietin is produced by interstitial renal
fibroblasts that surround the nephrons25.
The final urine is drained from the collecting ducts into the renal pelvis, through the ureter
into the bladder.
In conclusion, a functional in vitro kidney model can only be achieved, when the architecture
of the nephron is fully emulated, when all renal cell types are arranged correctly and when
the nephron is perfused.
1.2.2 Extracellular matrix of the kidney
The extracellular matrix (ECM) surrounds cells with a complex network of approximately
300 different proteins, glycosaminoglycans, ECM-binding growth factors and ECM-
modifying enzymes26.
Figure 2: Interactions of cells with their surrounding ECM. Cells and ECM exist in dynamic reciprocity.
The ECM provides structure and stability to tissues. Moreover, it provides mechanical and biochemical stimuli
to the cells, thus activating intracellular signaling cascades and influencing gene expression. Cells secrete ECM
components and matrix metalloproteinases (MMPs) to remodel the existing matrix and to release matrix bound
vesicles (MBV), growth factors and cryptic peptides carrying epidermal growth factor-like (EGF) domains.
Figure reproduced from Hussey et al.27.
Introduction
6
The ECM is well-known for its role to provide structural support for organs and tissues. In
the last years, however, it became clear that this drastically underestimated the extent of its
functions. The ECM also signals to the cells in various mechanisms, as depicted in Figure
2, and thereby influences cell survival, differentiation, proliferation, polarity, shape and
motility26,28.
Firstly, the ECM provides biochemical signals to the cells. Signaling molecules, such as
ECM-bound growth factors, matrix bound vesicles (MBVs) and cryptic epidermal growth
factor (EGF)-like domains, are released upon ECM degradation with matrix
metalloproteinases (MMPs). Hence, the ECM acts as a reservoir for signaling molecules,
regulates their distribution, activation and presentation to cells and establishes crucial growth
factor gradients that pattern the developmental processes28,29. Moreover, the ECM
macromolecules provide biochemical signals to the cells. Cells in different segments of the
nephron receive different signals from these molecules, since the ECM composition in the
kidney is specific for every segment, as discussed in more detail in 1.2.2.130,31.
Secondly, the ECM provides mechanical stimuli to the cells. Mechanical characteristics of
the cell-surrounding environment, such as stiffness, shape or shear stress, influence
proliferation, apoptosis, differentiation and migration, as described in more detail in
1.2.2.232.
The importance of the ECM is highlighted by the manifold diseases that are caused by ECM
defects. Mutations, degradation, hyperproduction or compositional changes of the ECM
cause or accompany numerous renal pathologies.
Genetic diseases of the ECM in the kidney include the Alport syndrome or the Pierson
syndrome. Both diseases affect the integrity of the GBM and lead to proteinuria33. Mutations
in ECM proteins that are irreplaceable for proper ECM assembly result in embryonic
lethality34.
Non-genetic dysregulation of the kidney ECM composition, stiffness or structure contributes
to renal fibrosis and invasive cancer35. Interstitial kidney fibrosis is the main driver of kidney
failure in end-stage renal disease. In kidney fibrosis, myofibroblasts produce large amounts
of fibrillar collagen and replace thereby the functional parenchyma of the organ36,37. The
progression of cancer is also influenced by the state of the ECM, a concept pioneered by
Mina Bissell. Cell transplantation experiments revealed that healthy ECM provides tumor-
suppressive signals and can prevent malignant phenotypes even in cells with multiple
Introduction
7
genomic abnormalities. Conversely, an altered ECM microenvironment can act as a potent
tumor promotor38,39.
1.2.2.1 Composition of the extracellular matrix of the kidney
The renal ECM can be divided into interstitial ECM and basement membranes35, as shown
in Figure 3A.
Figure 3: Structure and composition of renal basement membranes (A) The two main types of ECM.
Interstitial matrix is a loose fibrillar network surrounding the cells, composed of mainly collagen I and
fibronectin. The more compact basement membranes (BM) underline epithelia. Reproduced from Bonnans35.
(B) Model of the molecular structure of the BM. Laminin and collagen IV form independent networks that are
interconnected by nidogen and the HSPGs agrin and perlecan (black double-headed arrows). The epithelial
cells are anchored to the BM through integrins, α-dystroglycans and sulfated carbohydrates. Reproduced from
Hohenester40. (C) The composition of the basement membranes of the nephron is segment-specific. GBM,
glomerular basement membrane; MM, mesangial matrix; BC, Bowman’s capsule; PT, proximal tubule; LH,
loop of Henle; DT, distal tubule; CD, collecting duct. Reproduced from Miner31.
The interstitial ECM is a fibrillar network that fills the zones between glomeruli, tubules,
ducts and vessels. For instance, mesangial cells located between the glomerular capillary
loops produce the mesangial ECM. Its main components are fibrillar collagens, fibronectin,
proteoglycans, GAGs, tenascin C and elastin35. In a healthy kidney this ECM compartment
is less prominent than the basement membrane compartment.
Introduction
8
A basement membrane (BM) is a thin sheet of extracellular matrix that is located at the basal
side of every epithelium; it also ensheathes cardiac, smooth and skeletal muscle fibers and
outlines Schwann and vascular endothelial cells. In the glomeruli, the glomerular basement
membrane is part of the filtration barrier. The Bowman’s capsule is covered by a basement
membrane. In the tubulointerstitium, all tubules are lined with segment-specific tubular
basement membranes and also peritubular capillaries are covered by a basement
membrane31,37. Importantly, the BM composition differs depending on the part of the
nephron, as depicted in Figure 3C. This contributes to the functional specificity in distinct
nephron segments31. BMs are mainly composed of laminin, collagen IV, nidogen, and
heparan sulfate proteoglycans41:
Laminin is a large multidomain glycoprotein consisting of one α, β and γ chain. 16 different
laminin isoforms have been identified to date, each with a characteristic tissue
distribution42,43. The molecule self-assembles into polymers that build layered sheets,
anchors the BM to the cells and is crucial in the organization and assembly of the BM40,43,44
(see Figure 3B).
Laminin 111 (Lam-1, L111) is the most abundant laminin type in the human body. It is
composed of the α1, β1 and γ1 chain, as encoded in the name. It is the first laminin trimer
that arises during kidney development44–47. In the adult nephron, laminin 111 is part of the
mesangial matrix as well as of the BMs in the proximal tubule, the loop of Henle and the
Bowman’s capsule31.
Laminin 511 (Lam-10, L511) is the most abundant laminin trimer in the adult kidney and is
part of the BM of all tubules and collecting ducts but not of the mature GBM31. A deficiency
of the α5 chain leads to a defect in GBM assembly during glomerulogenesis44–46.
In the kidney, the β2 chain is solely expressed in the GBM. Laminin 111 and 511 trimers are
eliminated during organogenesis, hence laminin 521 (Lam-11, L521) is the only laminin
type present in the GBM. A null mutation in the coding gene LAMB2 leads to the
development of the Pierson syndrome. Newborns carrying this mutation die within two
weeks after birth due to renal failure. This early onset of proteinuria strongly suggests that
laminin 521 is crucial for the correct function of the filtration barrier48–50.
Collagen IV (ColIV) forms a second network in the basal membrane that is crucial for BM
stability. The ColIV molecule is formed by three α chains, twisted into a triple helix. There
Introduction
9
are six genetically distinct α chains. They trimerize into (α1)2α2 (IV), α3α4α5 (IV) or
(α5)2α6 (IV) protomers that assemble into a felt-like network, see Figure 3B31,42,45,49,51–53.
(α1)2α2 (IV) is ubiquitous in BMs throughout the body and the nephron, see Figure 3C. The
Bowman’s capsule additionally contains the (α5)2α6 (IV) molecule. Interestingly, during
GBM development (α1)2α2 (IV) is gradually replaced by α3α4α5 (IV) which is solely
synthesized by podocytes31,45,47,49. α3α4α5 (IV) contains more cysteine than (α1)2α2 (IV)
and is therefore more densely cross-linked. It is consequently more resistant to proteolytic
attack and has a superior stability. Mutations in COL4A3, COL4A4 or COL4A5 lead to the
development of Alport syndrome. Since proteinuria develops only gradually in Alport
patients, α3α4α5 (IV) is not essential for the glomerular filtration itself but rather reduces
the susceptibility of the GBM to damage50,54,55.
Collagen I is a fibrillar collagen. It is the most abundant ECM protein in mammals and is
responsible for maintaining the structural integrity of the tissue. Comparable to its relative
collagen IV, it is composed of three α chains, twisted into a triple helix. In contrast to
collagen IV, collagen I forms a long fibril instead of a network and is not part of the basement
membranes but of the interstitial matrix56,57.
Nidogen is a ubiquitous basement membrane glycoprotein. It is present in all BMs of the
kidney, as depicted in Figure 3C. It serves as an important linker between the laminin and
collagen networks in the BM58,59.
Heparan sulphate proteoglycans (HSPGs) are large polyanionic molecules consisting of a
core protein coupled with long heparan sulfate side chains. Heparan sulfate (HS) is a
glycosaminoglycan (GAG) of repeating, enzymatically modified glucuronic acid and
N-acetylglucosamine units60–62. HSPGs link the BM components, as depicted in Figure 3B,
and bind the growth factors basic fibroblast growth factor (bFGF), vascular endothelial
growth factor (VEGF), platelet-derived growth factor (PDGF) to the ECM. The HSPG
Perlecan is part of all BMs of the kidney, except of the GBM where Agrin is the dominant
HSPG, as shown in Figure 3C31. A deletion of either of these genes is lethal for the
embryo60,63,64.
In conclusion, for the generation of an in vitro kidney model it has to be taken into
consideration that the function of the kidney goes hand in hand with the correct composition
of the ECM. The segment-specific ECM composition provides specific microenvironments
to every renal cell type and should be emulated in a functional in vitro kidney model.
Introduction
10
1.2.2.2 Mechanical forces direct cell behavior
Cells are highly sensitive to the mechanical properties of the surrounding ECM and to
mechanical stimuli, such as shear stress or tensile and compressive forces, from their
neighboring cells. Mechanical stimuli influence cell proliferation, apoptosis, differentiation
and migration26,65,66.
Cells sense their mechanical environment through their primary cilium, mechanosensitive
ion channels, cell-cell and cell-ECM connections, as shown in Figure 4A.
Figure 4: The effect of extracellular matrix properties on the cell (A) Cells sense extrinsic forces, Fe, such
as shear and tensile or compressive forces, through their primary cilium, mechanically gated ion channels,
through integrin-mediated cell-ECM adhesion and cadherin-mediated cell-cell adhesion. The cell generates
intrinsic forces, Fi, and transfers these onto the ECM or neighboring cells. The cells translate these mechanical
forces into biochemical signals, using multiple signaling pathways, or transmit the force via actin filaments
and the LINC complex onto lamins in the nucleus, or react to nucleus deformations directly with changes in
gene expression and in cell behavior and function. Adapted from Vining & Mooney66. (B) Tissues exhibit a
range of stiffness, quantified by the elastic modulus (E modulus). The E modulus of kidney tissue compares to
fat tissue. Reproduced from Discher et al.67.
The primary cilium is a microtubule based, slender cell protuberance present on most cells
of the human body. In the kidney, the primary cilium is the mechanosensing receptor for
fluid flow in the tubules. The flow exerts shear stress onto the cells that is crucial for a
physiological cell morphology and function. Defects in this mechanosensing mechanism
lead to the development of polycystic kidney disease. The replication of fluid flow in the in
vitro model is therefore critical to achieve a native cell phenotype and to model diseases 68–
70.
Introduction
11
Cells also sense the mechanics of the ECM they attached to. They connect to the ECM via
integrins. Integrins are ECM binding receptors that are organized in clusters, called focal
adhesions. They link the ECM to the actin filaments of the cytoskeleton via a set of linker
proteins71,72. Through this connection the cells probe the stiffness of the ECM. To this end,
they apply a force onto the ECM by pulling with myosin II mini-filaments on the actin
filaments that transfer the force to the integrins and then onto the ECM. A stiff ECM will
resist that force and the integrins will not move. However, a soft ECM will deform, the
bound integrins move and reduce the loading rate on the cytoskeletal force-bearing
elements32,73–75.
Upon that stimulus the integrins activate a number of signaling molecules intracellularly that
initiate multiple mechanosensitive signaling pathways and result in activation of
transcription factors and changes in gene expression32,66,76.
Another major pathway of mechanotransduction is the direct physical linkage of the ECM
to the deoxyribonucleic acid (DNA) via the cytoskeleton. Cytoskeletal fibers transmit the
force via the LINC complex through the nuclear membrane onto the intermediate filaments
of the nucleus, the lamins. Lamins bind directly to DNA and transcription factors,
completing thus the force transmission77–79.
Moreover, the nucleus itself also acts as a mechanosensor. Nucleus deformation, for example
in stretched cells on convex surfaces80 or stiff substrates81, increases the lamin expression
and regulates ECM directed differentiation.
The mechanical properties of a tissue, ECM or cell culture scaffold are described by various
terms. Materials can behave in a plastic, elastic or viscous manner or a combination of these.
ECM is a viscoelastic material. For materials with elastic properties the elastic modulus (E
modulus) measures the resistance to being elastically deformed when a stress is applied. It
is defined as the ratio of stress and strain. Stress is given as force per area. Strain is a
normalized measure of deformation after a stress was applied. The stiffer a material, the
higher is the elastic modulus. Soft tissues like brain, kidney, lung and muscle have an E
modulus of up to 15 kPa. The higher the content of fibrillar collagen in a tissue, the stiffer it
becomes. For example, fibrotic tissues, cartilage or precalcified bone have an E modulus of
around 20-70 kPa. Calcified cortical bone reaches an E modulus of 14 GPa (Figure 4B)82,83.
In standard 2D cell culture, cells are grown on tissue culture plastic made from polystyrene
which has an E modulus of around 3 GPa. In contrast, the human kidney has an E modulus
Introduction
12
of around 2,5 kPa, approximately 6 orders of magnitude lower than plastic82,83. Considering
the impact of mechanical forces on cell behavior, it is not surprising that cells originating
from the kidney, cultured on tissue culture plastic, show a different or even artificial behavior
than in vivo.
In conclusion, an accurate, functional kidney model has to mimic the natural mechanical
properties of the kidney and cannot rely on 2D cell culture on tissue culture plastic without
flow.
1.2.3 Renal organogenesis
The mammalian kidney arises from the mesoderm. After neurulation, the trunk mesoderm is
subdivided into chorda-mesoderm, paraxial mesoderm, intermediate mesoderm, and lateral
plate mesoderm. The intermediate mesoderm (IM) develops into the urogenital system,
including the kidneys and the gonads84.
The anterior IM develops into the nephric duct (ND). Starting at the level of the sixth somite
it elongates caudally and undergoes mesenchymal to epithelial transition (MET). The ND
then buds and forms the ureteric bud (UB), initiating thereby the formation of the
metanephros. Meanwhile the posterior IM differentiates into the metanephric mesenchyme
(MM) that condenses around the branching UB tips into the SIX homeobox 2 (SIX2) positive
cap mesenchyme (CM). UB and CM are in a reciprocal signaling relationship that causes
further branching of the UB, and self-renewal and differentiation in the CM. After multiple
rounds of branching, elongation and differentiation, the UB triggers the CM into MET. The
CM develops into the renal vesicle (RV), a simple epithelial structure with a lumen, and after
further elongation and segmentation into the S-shaped body (SSB). Finally, endothelial cells
invade the proximal end of the SSB, and podocytes develop, thereby forming the mature
nephron. The UB develops into the collecting ducts of the mature kidney (Figure 5)85–89.
For the generation of an in vitro kidney model, the renal progenitor cells from MM and UB
could be the ideal starting cell population, as these two cell types will give rise to all renal
cell types in a self-organized differentiation process.
Introduction
13
Figure 5: Development of the mammalian kidney. The ND buds into the UB, triggering the condensation of
the MM into CM. Reciprocal signaling between CM and UB induces branching in the UB and the formation
of epithelial RV in the CM. The RV elongates and differentiates via the SSB state into the mature nephron.
The UB develops into the collecting ducts. ND, nephric duct; MM, metanephric mesenchyme; UB, ureteric
bud; CM, cap mesenchyme; RV, renal vesicle; SSB, S-shaped body. Adapted from Takasato and Little88,89
1.3 Tissue engineering of the kidney
Tissue engineering is a multidisciplinary approach to generate functional tissue in vitro.
Tissue engineering requires the arrangement of the tissue-specific cell types into the tissue-
specific architecture. To achieve this goal, scaffolds or self-organizational strategies are
usually applied90,91.
To date, engineered tissues are already being applied as 3D in vitro models in drug
development, disease modeling or in the investigation of cell-matrix interactions. Simple
tissues, for example a tissue engineered bladder, have even reached clinical application92.
Considering the ongoing progress in tissue engineering, it will most likely be possible to
produce fully functional complex organs for transplantation in the future.
The kidney’s elaborate architecture and exceptionally diverse functions makes tissue
engineering of the kidney an extremely complex task.
As highlighted in the previous chapters, three criteria have to be met to engineer a functional
in vitro kidney model. Firstly, an appropriate cell source has to be identified that gives rise
to all renal cell types. Secondly, the nephron architecture, as well as the composition and
Introduction
14
mechanical properties of the ECM have to be replicated to ensure proper cell function and
phenotype. And thirdly, the in vitro model has to be perfusable to enable glomerular
filtration, to apply shear stress and to supply nutrients.
1.3.1 Cell source
The kidney comprises more than 20 different kidney cell types10. One way to obtain all these
cell types would be to isolate primary adult human kidney cells. However, human kidneys
are a rare resource and urgently needed for transplantation. Moreover, primary adult kidney
cells have naturally a high donor-to-donor variability, a limited proliferative capacity and
they dedifferentiate upon prolonged cultivation, which makes it impossible to generate the
cell numbers needed for kidney tissue engineering70,93,94.
Cell lines have a stable phenotype, are proliferative and easily available. Hence, the majority
of current kidney models are based on renal cell lines. Cell lines such as the MDCK cells
have been used for decades but are of non-human origin. The human immortalized renal
epithelial line HK2 line has also been excessively tested. However, it was found that HK2
cells only show limited proximal tubular functions and markers and that their response to
nephrotoxins differs from in vivo data. First studies of newer immortalized human renal
epithelial lines, such as NKi-2 or RPTEC/TERT1, hint towards a better-preserved
functionality. Nevertheless, an immortalized cell line does not exist for every renal cell
type8,70.
Human induced pluripotent stem cells (hiPSCs) are a novel source of human somatic cells
for disease modeling and drug screenings, see Figure 695. hiPSCs were discovered in 2006
by the Japanese Nobel prize winner Shinya Yamanaka. hiPSCs are reprogrammed from
human adult fibroblasts that were transduced with the reprogramming factors OCT3/4,
SOX2, KLF4, and c-MYC. hiPSCs can differentiate into all three germ layers and generally
behave similar to embryonic stem cells (ESCs)96,97. ESCs are harvested from the inner cell
mass of the blastocyst. The developing embryo is destroyed in this process resulting in the
ethical dilemma surrounding the use of ESCs98. hiPSCs are not afflicted with these concerns.
The reprogramming technique enables the generation of patient-specific hiPSCs and opens
Introduction
15
the door for autologous tissue engineering or cell
therapies99. For example, hiPSC lines from PKD
patients or genetically engineered lines carrying the
same mutations show the cystic disease phenotype in an
organoid culture100.
The differentiation of hiPSCs is classically directed by
the variation of their chemical environment. Signaling
processes during embryogenesis in vivo are
recapitulated in vitro by the addition of growth factors
and small molecules to a diverse range of cell culture
media and by coating tissue culture plastic plates with
a thin layer of ECM molecules. However, for many cell
types current hiPSC differentiation protocols lead to
immature or fetal phenotypes in standard in vitro
culture systems101. To generate more mature
phenotypes in vitro, the research field currently focuses
on improving the mechanical cell environment67,102.
Providing natural shear stress, geometry and stiffness
improved many differentiations, such as hepatocyte103
and cardiomyocyte104 differentiations. Huge improvements in self-organization and
maturation were already achieved, when cells were cultured in hydrogels105, decellularized
scaffolds106 or in organoids107.
In the last years impressive progress was made in the differentiation of hiPSCs into the renal
lineage. Multiple protocols for the differentiation into renal progenitor cells (RPCs) were
published. These protocols mimic the signaling during renal organogenesis, as described in
1.2.3. MM or UB cells are derived via mesoderm induction. These RPCs have the potential
to differentiate into all renal tubular epithelial cells, podocytes and also mesenchymal cells
and to self-organize into nephron-like structures when they are cultured in 3D and were
therefore chosen as the cell source for the tissue engineering approach in this thesis108.
Moreover, endothelial cells (ECs) can be differentiated from hiPSCs through mesoderm
induction, followed by an endothelial specification step. These cells will be used to engineer
the vascular compartment of the kidney model109.
Figure 6: Human induced
pluripotent stem cells
(hiPSCs)
are
reprogrammed
from human
somatic
cells
. hiPSCs can
serve as a cell source
for kidney tissue engineering, as they
can proliferate and differentiate into
renal progenitor cells (RPCs) and
endothelial cells (ECs).
Introduction
16
1.3.2 Architecture and perfusion
2D cultures of human cell lines on tissue culture plastic are classically applied as in vitro
kidney models. These models are simple, cost-effective, well-established and high-
throughput and therefore ideally suited for large-scale compound screens. However, the
application of these models did not result in the improvement of kidney failure treatments
and too often do not detect drug-induced nephrotoxicity in preclinical studies, as already
mentioned before. This poor predictivity is caused by the lack of physiological relevance of
these simple 2D models8,70.
Microfluidic models improve the physiological relevance by including shear stress. In
microfluidic models the cells are cultured in confluent monolayers within perfused channels
on microfluidic chips. Shear stress increases the expression of functional relevant
transporters and ion channels in proximal tubular cells and provokes the formation of
primary cilia and microvilli. Hence, the phenotype of the cultured proximal tubular cells
improves and consequently it was found that the responses of these cells to nephrotoxins like
cisplatin are closer to in vivo responses than from cells in static 2D kidney models. The
microfluidic chip design facilitates parallelized, high-throughput screenings of drug
candidates. However, these models are essentially still 2D systems. Moreover, they mostly
incorporate only one cell type in an artificial architecture on plastic or silicone of artificial
stiffness8,70,110,111.
Figure 7: Differences between 2D and 3D in vitro tissue models. 3D cell culture provides in vivo like
conditions to the cultured cells, whereas cells cultured in 2D are exposed to artificial conditions. Figure
reproduced from Hussey et al.27.
Introduction
17
Tissue engineered 3D in vitro models have already been proven to be more accurate than 2D
in vitro models112. The dilemma of 2D cell culture is the lack of ECM and thus the lack of
3D cell-ECM and cell-cell interactions and the artificial stiffness of the culture surfaces, see
Figure 7. Cells grown in 2D are therefore hindered in developing a native cell morphology
and function. Cells grown in 3D conditions, however, are able to establish cytokine gradients
and to self-organize into tissue-like structures, called organoids27,66.
When hiPSC-derived renal progenitor cells are brought into a 3D environment, they replicate
the renal organogenesis. They self-organize into S-shaped bodies that mature further into
nephrons. These kidney organoids are therefore a very promising approach to build a
functional kidney model. They incorporate a big spectrum of renal cells that produce their
own ECM in a nephronal architecture85,113–117. At present however, only 50% of the cells
inside these organoids are tubule cells or podocytes and the organoids lack the high ordered
organization of kidneys. The nephrons are randomly scattered throughout the organoid and
neither an organized connection of the nephrons to a collecting duct system nor an organized
vascular network is present. Therefore, no perfusion is possible. Hence, cells lack the
exposure to shear stress and single cell analysis revealed consequently already that none of
the kidney cell types inside the organoids are fully mature108. Moreover, without
vascularization the center of the organoid is poorly supplied with nutrients and oxygen. And
most importantly, the organoid model cannot emulate the perfusion-based function of the
kidney.
The complex anatomy of the kidney is hard to recreate. Therefore, a rational starting point
for kidney tissue engineering is to provide a scaffold to the cells that already defines the
architecture. To date, there is no technology that can copy that delicate structure. The
resolution of 3D printing, for example, is not high enough. Only isolated parts of the nephron
have been reproduced with 3D printing as yet118.
Kidney ECM based scaffolds would not only provide the correct architecture but due to the
natural stiffness and segment-specific composition also the specific microenvironments to
every renal cell type. These microenvironments could provide important differentiation and
maturation signals to RPCs. Furthermore, it is of great advantage that kidney ECM based
Introduction
18
scaffolds preserve the native vascular network. It is therefore possible to perfuse the kidney
models that were created with these scaffolds.
Importantly, ECM proteins are highly conserved among different taxa. All bilaterians share
the proteins that make up the core of the basement membrane26,119,120. Moreover, all
mammalian kidneys have the same basic nephron structure. At the macroscopic level the
kidney architecture varies, as shown in Table 1, but these differences do not impact the
functionality121,122. It is therefore possible to generate ECM scaffolds from rats or pigs and
to repopulate them with human cells.
Table 1: Species differences in renal structure121
Parameter
Rat
Pig
Human
Renal organization
Unilobular
Multilobular
Multilobular
Single kidney weight [g]
0,75
77
157
Number of nephrons
3*104
1*106
1*106
Glomerular radius [µm]
61
83
100
Tubule radius [µm]
29
n/a
36
Proximal tubule length [mm]
12
n/a
16
In 2013, a promising proof of concept study was published by Song et al.123. They reported
the generation of a whole organ in vitro kidney model that produced rudimentary urine, by
decellularization of a rat kidney and recellularization of that scaffold with primary rat
neonatal kidney cells and human endothelial cells. The same approach could be upscaled to
produce kidneys for transplantation, when using a porcine kidney as a scaffold. Based on
this study the approach of whole organ kidney tissue engineering with decellularized whole
rat kidneys and hiPSC-derived RPCs was chosen in this thesis. Whether the decellularized
kidney scaffold promotes full, site-specific maturation of the reseeded RPCs needs to be
investigated.
1.3.3 De- and recellularization
Decellularization is the process of removing all cells from a cell culture, tissue or whole
organ, while retaining the extracellular matrix. Decellularized ECM is a suitable biological
scaffold for numerous tissue engineering approaches124.
Decellularized porcine small intestinal submucosa and urinary bladder matrix are acellular
biologic surgical meshes that have been used in millions of patients without evidence of
Introduction
19
adverse immunological reactions against these
xenogenic biomaterials27. Building on this work, the
decellularization of whole organs was developed in
2008 when Harald Ott first decellularized whole
porcine hearts125. Whole organ decellularization
requires the perfusion of decellularization agents
through the native vasculature. The scaffold retains
the organ’s complex geometry and can be reseeded
with patient-derived cells for whole organ tissue
engineering93.
Decellularization is achieved by initial lysis of cell
membranes, followed by the removal of all cellular
debris. A combination of physical, chemical and
enzymatic treatments is necessary to achieve full
decellularization. To provoke the rupture of the cell
membrane, sonication or freeze–thaw cycles are
usually applied. Another common cell lysis treatment is osmotic shock with hypotonic or
hypertonic solutions. After cell lysis, it is necessary to solubilize the cell membranes and to
remove cytoplasmic components. Detergents are chemical surfactants that are usually
applied in this second phase of decellularization126,127. These amphiphilic substances
comprise a lipophilic hydrocarbon tail and a hydrophilic polar head group. They are
therefore able to form micelles and to dissolve lipids in aqueous solutions. The hydrophilic-
lipophilic balance (HLB) of a detergent is a measure for the balance of size and strength of
the opposing hydrophilic and hydrophobic groups. Increasing HLB values correspond to an
increasing hydrophilic character. Ionic detergents, such as sodium deoxycholate (SDC) and
sodium dodecyl sulfate (SDS), are harsher and have a higher HLB than zwitterionic
detergents, such as CHAPS, or non-ionic detergents, such as Triton X-100 (TX-100). The
HLB of SDS, SDC and TX-100 are 40, 16 and 13, respectively128,129. Chemicals less
commonly applied for decellularization are alkaline or acidic substances, e.g. peracetic acid
(PAA), and chelating agents, e.g. ethylenediaminetetraacetic acid (EDTA) and egtazic acid
(EGTA). Enzymatic treatment with proteases, such as trypsin, are normally avoided since
they decrease the mechanical strength of the tissue and randomly digest ECM proteins.
Nucleases, particularly DNase, facilitate nucleic acid removal126,127. α-galactosidase
Figure 8: Decellularization of whole rat
or pig kidneys removes the cells and
retains the extracellular matrix of the
organ. The
decellularized kidney
serves as
a scaffold for
3D kidney
tissue
engineering.
Introduction
20
removes the Gal epitope that is known to cause xenorejection in humans130. The sequence,
duration and temperature in which these steps are performed are essential for the outcome.
Agitation or perfusion facilitates the transport of decellularization agents through the tissue
or whole organ to the cells and the removal of cellular debris. Agitation is sufficient for
decellularization of cell culture monolayers or simple, thin tissues. For whole organ
decellularization, however, perfusion through the vascular network is necessary and
extremely effective93,131. An effective decellularization is important for later reseeding with
cells or transplantation into patients since cellular antigens and nucleic acids are targets for
immune cells126,132,133.
The native composition, ultrastructure, and macroscopic 3D architecture of organ-derived
ECM scaffolds provide the necessary microenvironment to support attachment,
proliferation, and differentiation of reseeded cells, as discussed before. However, every
decellularization technique invariably disrupts the ECM to some degree. One goal of this
thesis was therefore to identify a decellularization protocol that maximizes cell removal and
minimizes ECM loss and damage93,131. It was hypothesized that the damage to the ECM
could be reduced by applying a milder detergent than SDS and by decreasing the temperature
from the usually applied room temperature to 4°C.
Recellularization is the process of
seeding cells into a previously
decellularized organ or tissue. If the
aim is to restore the functionality of
the decellularized organ, the
success of a recellularization can be
measured by the same criteria as the
regeneration after organ damage:
Firstly, the cell number must be
close to the number present prior to
decellularization134. A pig kidney comprises approximately 7,7*1010 cells. A single rat
kidney comprises approximately 7,5*108 cells121,135. Hence, the cells applied for kidney
tissue engineering must have an extensive proliferative capacity. Cells must proliferate either
after seeding inside the scaffold or in a mass expansion process before seeding.
Figure 9: Recellularization. Decellularized rat kidneys will
be recellulariz
ed with hiPSC-
derived renal progenitor cells
and endothelial cells
to generate a tissue engineered 3D
kidney model.
Introduction
21
Secondly, to achieve functionality, the reseeded cells must be positioned in the exact
compartment as they existed prior to decellularization134. Reseeding can be performed by
perfusing cells into the kidney through three different seeding ports. The artery and the vein
grant access to the vascular compartment, the ureter to the tubular compartment. Injection
with a canula into the parenchyma is a fourth option136. Whether the seeded RPCs migrate
inside the scaffold and thereby repopulate every compartment or whether the seeding
strategy has to push the cells into every niche, has to be investigated.
Cell engraftment, proliferation, maturation and application of the model in, for example,
nephrotoxicity studies may necessitate a culturing time spanning many weeks. During this
period the seeded cells require the supply of nutrients and oxygen for cell survival and
function. Recellularization is therefore performed in a perfusion bioreactor93,136,137
Aim
22
2 Aim
The aim of this thesis was to establish a whole organ model of the human kidney on the basis
of hiPSC-derived renal progenitor cells and decellularized rat kidney scaffolds.
To achieve this goal, the minor aims were:
i. To develop a perfusion bioreactor system including a control software and automated
pressure and pH control to allow whole organ de- and recellularization.
ii. To optimize a decellularization protocol for kidneys that maximizes cell removal and
minimizes ECM loss and damage.
iii. To reendothelialize the vascular compartment of the decellularized kidney with
hiPSC-derived endothelial cells.
iv. To recellularize the whole rat kidney scaffold with hiPSC-derived renal progenitor
cells, to test the hypothesis that the decellularized kidney matrix promotes their site-
specific differentiation and maturation by preserved architectural, mechanical and
biochemical features.
v. To determine which of these mechanical and biochemical features influence the
maturation of hiPSC-derived renal progenitor cells.
Materials and Methods
23
3 Materials and Methods
3.1 Materials
3.1.1 Cells
Table 2: Cells
Name
hiPSC lines
BCRTi005-A
Rossbach et al.138
BIHi004-A
Hossini et al.139
WISCi004-B (GFP+)
140
Primary cells
HUVEC
3.1.2 Reagents
Table 3: Reagents
Name
Manufacturer
Buffers
DPBS
Thermo Fisher Scientific
DPBS, calcium, magnesium
Thermo Fisher Scientific
TRIS-base
Sigma-Aldrich
Cell culture media
Advanced RPMI 1640
Thermo Fisher Scientific
DMEM w/o phenol red
Biochrom
DMEM/F-12
Thermo Fisher Scientific
EGM-2
Lonza
Essential 8 Medium
Thermo Fisher Scientific
Knockout DMEM
Thermo Fisher Scientific
Neurobasal medium
Thermo Fisher Scientific
PFHMII
Thermo Fisher Scientific
REGM
Lonza
STEMdiff APEL 2
StemCell Technologies
StemPro-34 SFM
Thermo Fisher Scientific
Cell culture media supplements
Activin A, recombinant human
Peprotech
Amphotericin B, 100x
Biochrom
Antibiotic-Antimycotic, 100x
Thermo Fisher Scientific
B-27 supplement without Vitamin A, 50x
Thermo Fisher Scientific
bFGF, recombinant human
Peprotech
BMP4, recombinant human
Peprotech
Materials and Methods
24
Name
Manufacturer
CHIR99021
StemCell Technologies
FCS Superior
Biochrom
Forskolin
Abcam
GDNF, recombinant human
Peprotech
GlutaMAX
Thermo Fisher Scientific
N-2 supplement, 100x
Thermo Fisher Scientific
PenStrep, 100x
Biochrom
Retinoic acid
Stemgent
ROCK inhibitor Y26732
WAKO Chemicals
SB431542
Sigma-Aldrich
VEGF 165, recombinant human
Peprotech
Cell culture surface coatings
Collagen IV (Col (α1)2α2 (IV)), human placenta
Sigma-Aldrich
Fibronectin, human plasma
Corning
Geltrex LDEV-free hESC-qualified
Thermo Fisher Scientific
Laminin 511, recombinant human
BioLamina
Laminin 521, recombinant human
BioLamina
Ultrapure water with 0,1% gelatin
Millipore
Chemicals
Citrate
Sigma-Aldrich
Cysteine-HCl
Sigma-Aldrich
DMSO
Sigma-Aldrich
Dopamine
Sigma-Aldrich
EDTA, 0,5 M
Thermo Fisher Scientific
HCl, 6 M
Carl Roth
Heparin, 5000 U/ml
Biochrom
NaCl
Sigma-Aldrich
NaOH, 1 M
Carl Roth
Trypan Blue stain, 0,4%
Thermo Fisher Scientific
Roti-Phenol/Chloroform/Isoamyl alcohol, 25:24:1
Carl Roth
Roti-Chloroform/Isoamyl alcohol, 24:1
Carl Roth
Resazurin
Sigma-Aldrich
SDC
Sigma-Aldrich
SDS
Sigma-Aldrich
Sodium acetate
Sigma-Aldrich
TritonX-100
Sigma-Aldrich
Enzymes
DNase I
Roche
Papain
Sigma-Aldrich
Proteinase K
Sigma-Aldrich
StemPro Accutase cell dissociation reagent
Thermo Fisher Scientific
Trypsin, 0,25%
Thermo Fisher Scientific
Trypsin/EDTA, 0,05 %/0,02 %
Biochrom
Histology/Immunofluorescent staining
Albu Max II lipid rich bovine serum albumin
Thermo Fisher Scientific
Bovine albumin fraction V, 7,5% solution
Thermo Fisher Scientific
Cytofix
BD
Donkey serum
Merck Millipore
Eosin Y
Carl Roth
Ethanol, ≥99.8%
Carl Roth
FcR blocking reagent, human
Miltenyi
Formaldehyde buffered solution, 4%, pH 7,5
Herbeta
Immunoselect mounting medium DAPI
Dianova
Mayer’s acid hemalum
Carl Roth
Permeabilizing Solution 2
BD
Roti-Histokitt
Carl Roth
Materials and Methods
25
Name
Manufacturer
Surgipath paraplast plus
Leica
Xylol
Carl Roth
3.1.3 Consumables
Table 4: Consumables
Name
Manufacturer
Cell culture
Serological pipette, 5 ml, 10 ml, 25 ml, 50 ml
Corning
Medium bottle, 100 ml, PET, sterile
Greiner Bio-One
MS MACS columns
Miltenyi
Falcon tissue culture treated flasks, vented ,75 cm², 175 cm²
Corning
Falcon tissue culture treated microplates, 6-, 12-, 24-, 96-wells
Corning
Falcon tubes, 15 ml, 50 ml
Corning
Cell scraper, 25 cm
Sarstedt
Cell strainer, 40 µm
Corning
Countess cell counting chamber slides
Thermo Fisher Scientific
CryoTubes, 1,8 ml
Nunc
General consumables
Biopsy punch, 4 mm
Pfm medical
Cannula, 27 G
BD
Combitips advanced, 0,1 ml, 0,5 ml, 2,5 ml, 5 ml, 10 ml, 25 ml
Eppendorf
Eppendorf tubes, 0,5 ml, 1,5 ml, 2 ml
Eppendorf
Falcon FACS tubes, 5 ml
Corning
MACSQuant washing solution
Miltenyi
PCR plate, 384-well, MicroAmp EnduraPlate optical
Thermo Fisher Scientific
PCR strips, 0,2 ml
Biozym
Pipette tips, 10 µl
Eppendorf
Pipette tips, 1000 µl
Greiner Bio-One
Pipette tips, 200 µl
Sarstedt
Pipette tips, SafeSeal professional, 10 µl, 20 µl, 200 µl, 1000 µl
Biozym
Syringe, 1 ml
B. Braun Medical AG
Syringe, 3 ml, Luer-Lock
BD
Syringe, 50 ml, Luer-Lock
BD
Syringe, GASTIGHT, #1710, 100 µl
Hamilton
Histology
Cassettes, Q Path MacroStar II
VWR
Microscope slide, 75x25 mm, SuperFrost Plus
Langenbrinck
Glass cover slip, 24x60 mm
Langenbrinck
ImmEdge hydrophobic barrier PAP pen
Vector Laboratories
Perfusion bioreactor
3-way stopcock
Smiths medical
Bubble stones, AS30
Tetra
Combifix adapter, Luer female/female
B. Braun Medical AG
Combifix adapter, Luer male/male
B. Braun Medical AG
DURAN GL 45 blue PP screw cap with 3x GL 14 ports
SCHOTT DURAN
DURAN Hose connection screw cap blue PP, GL 14
SCHOTT DURAN
DURAN Insert for hose connection screw cap, GL 14, 3,2mm
SCHOTT DURAN
DURAN Laboratory bottle, GL 45, 1000 ml
SCHOTT DURAN
DURAN Laboratory bottle, GL 45, 2000 ml
SCHOTT DURAN
DURAN Laboratory bottle, GL 45, 50 ml
SCHOTT DURAN
DURAN Laboratory bottle, GL 45, 500 ml
SCHOTT DURAN
Materials and Methods
26
Name
Manufacturer
DURAN Neck thread GL 14, red PBT cap with lip seal
SCHOTT DURAN
DURAN pressure equalization set, GL14, 0,2 μm membrane filter
SCHOTT DURAN
Female Luer-Lock to barb connector, 1/16”
Quosina
Female Luer-Lock to barb connector, 1/8”
Quosina
Female Luer-Lock to barb connector, 5/32”
Quosina
Gas tubing, TUS, softpolyurethane
SMC
Luer stopper
Fresenius Kabi
Male Luer-Lock to barb connector, 1/16”
Quosina
Male Luer-Lock to barb connector, 1/8”
Quosina
Perfusor Line, 150 cm, 1,0x2,0 mm, PE
B. Braun Medical AG
Perfusor Line, 150 cm, 1,5x2,7 mm, PVC
B. Braun Medical AG
Perfusor Line, 50 cm, 1,5x2,7 mm, PVC
B. Braun Medical AG
pH sensor flow through cell
Presens
Plastic ring, M3
Suki
pO
2
sensor flow through cell
Presens
Pressure sensor dome
Memscap
Pump tubing, PharMed BPT, ID 0,89 mm
IDEX Health&Science
Pump tubing, PharMed, ID 3,2 mm, WS 1,6 mm
IDEX Health&Science
Rotilabo syringe filter, PTFE
Carl Roth
Surgery
Scalpel, sterile, disposable, #11
Schreiber Instrumente
Wooden applicators with cotton head, 150x2,2 mm
Karl Hecht GmbH
Swabs, non-woven
Charité
Feeding needle, 24 G
Agntho's
Neoflon, 26 G
BD
Disposable cup, 100ml
Sarstedt
Silk, 7/0 USP, 100m
Resorba
Tissue culture dishes, 100 mm
VWR
3.1.4 Kits
Table 5: Kits
Name
Manufacturer
Blyscan GAG assay
Biocolor
CD144 MicroBead Kit, human
Miltenyi
ELISA Kit, hbFGF
R&D Systems
ELISA Kit, hVEGF
Ani Biotech Oy
RNeasy Plus Mini Kit
Qiagen
Sylgard 184 silicone elastomer kit
Dow Corning
Sylgard 527 A&B silicone dielectric gel
Dow Corning
TaqMan Fast Advanced Master Mix
Thermo Fisher Scientific
TaqMan Reverse Transcription Reagents
Thermo Fisher Scientific
Total Collagen Assay Kit
Quickzyme
Materials and Methods
27
3.1.5 Antibodies and fluorescent dyes
Table 6: Primary and secondary antibodies and nucleic acid dyes
Name
Clone
Species of origin
Manufacturer
Primary antibodies
CD31
EPR3094
rabbit
Abcam
Collagen I
COL-1
mouse
Abcam
Collagen IV
polyclonal
rabbit
Abcam
Fibronectin
polyclonal
rabbit
Abcam
Laminin
polyclonal
rabbit
Abcam
LHX1
OTI2D5
mouse
Novus Biologicals
PAX2
polyclonal
rabbit
Thermo Fisher Scientific
Conjugated antibodies
CD144-FITC
REA199
human
Miltenyi Biotec
CD31-APC
AC128
human
Miltenyi Biotec
mouse IgG-AlexaFluor 647
polyclonal
donkey
Thermo Fisher Scientific
rabbit IgG-AlexaFluor 647
polyclonal
donkey
Thermo Fisher Scientific
Nucleic acid dyes
DAPI
Thermo Fisher Scientific
Live/Dead Blue
Thermo Fisher Scientific
PI
Sigma-Aldrich
3.1.6 qPCR gene expression assays
Table 7: TaqMan gene expression assays
Gene name
TaqMan Ref number
Manufacturer
AQP1
Hs01028916_m1
Thermo Fisher Scientific
ATP1A1
Hs00167556_m1
Thermo Fisher Scientific
PODXL
Hs01574644_m1
Thermo Fisher Scientific
SIX2
Hs00232731_m1
Thermo Fisher Scientific
SLC12A2
Hs00169032_m1
Thermo Fisher Scientific
SLC12A3
Hs01027568_m1
Thermo Fisher Scientific
SYNPO
Hs00702468_s1
Thermo Fisher Scientific
WT1
Hs01103751_m1
Thermo Fisher Scientific
GAPDH
Hs03929097_g1
Thermo Fisher Scientific
RNA18S5
Hs03928990_g1
Thermo Fisher Scientific
3.1.7 Instruments
Table 8: Instruments
Name
Manufacturer
Cell culture
Aspiration system, Vacusafe and Vacuboy
IBS Integra Biosciences
CountessII automated cell counter
Thermo Fisher Scientific
Incubator, 11-13625
Binder
Incubator, Heracell 240i CO
2
Thermo Fisher Scientific
Laminar flow hood, Herasafe KS9
Thermo Fisher Scientific
Laminar flow hood, L226 IVF
K-Systems
Materials and Methods
28
Name
Manufacturer
MiniMACS separator
Miltenyi
Mr. Frosty freezing container
Nalgene
Pipetboy
IBS Integra Biosciences
Vortex-2-Genie
Scientific Industries Inc.
Water bath, DC10
Thermo Fisher Scientific
Centrifuges
Centrifuge, Allegra X22
Beckman Coulter
Centrifuge, Combi-Spin FVL-2400N
bioSan
Centrifuge, Heraeus Fresco
Thermo Fisher Scientific
Centrifuge, Heraeus Multifuge X3R
Thermo Fisher Scientific
Centrifuge, Micro
Carl Roth
General
Heating and drying oven, FED 56
Binder
Heating and drying oven, VENTI-Line
VWR
Magnetic stirrer, D-6010
neoLab
Multipette Xstream
Eppendorf
PCR FlexCycler
Analytik Jena
Pipette Research plus, 2,5 µl, 10 µl, 20 µl, 200 µl, 1000 µl
Eppendorf
Platform shaker, Titramax 1000
Heidolph
Roller mixer, SRT9D
Stuart
Thermomixer comfort
Eppendorf
Ultrasonic processor, UP100H
Hielscher Ultrasound Technology
Vacuum concentrator, 5301
Eppendorf
Vacuum desiccator, DURAN DN200
SCHOTT DURAN
Vacuum pump, DUO 2.5
Pfeiffer Vacuum
Histology
Flattening table for clinical histopathology, HI1220
Leica
Heating and drying oven, Heraeus function line
Thermo Fisher Scientific
Heating plate
Rommelsbacher
Microtome blade, S35
Feather
Microtome, RM2255
Leica
Paraffin dispenser
MEDAX
Paraffin tissue floating bath
MEDAX
Pressure cooker, ASH22-4.5
Krüger
Tissue processor, TP1020
Leica
Imaging and Quantification
ABL 700 series, blood gas analyzer
Radiometer Medical
AFM, MFP3D-Bio
Asylums Research
Bose Test Bench, LM 1 ElectroForce
Bose
Flow cytometer, LSR-II Fortessa
BD
Flow cytometer, MACS Quant VYB
Miltenyi
Microscope, Axiovert 40CFL
Zeiss
Microscope, Leica DMi8
Leica
NanoDrop 1000
NanoDrop Technologies
Operetta high content imaging system
Perkin Elmer
pH-meter, PB 11
Sartorius
Plate reader, Mithras LB 940
Berthold Detection Systems
Plate reader, SpectraMax 340PC-384
Molecular Devices
Precision balance
Sartorius
qPCR cycler, QuantStudio 6 Flex
Thermo Fisher Scientific
Perfusion bioreactor
Amplifier for pressure sensor SP844
HJK Sensoren + Systeme
CompactDAQ chassis, NIcDAQ-9174
National Instruments
Gas blender, GB-103
MCQ
Incubator, ICP260, compressor-cooled
Memmert
Membrane oxygenating chamber
Radnoti
Materials and Methods
29
Name
Manufacturer
NI-9201, C Series voltage input module
National Instruments
NI-9217, C Series temperature input module
National Instruments
Peristaltic pump, IP65
Ismatec
pH sensor, pH-1 mini v2
Presens
pO
2
sensor, Fibox 3
Presens
Pressure sensor, SP844
Memscap
Pump head, MS/CA 4-12
Ismatec
Surgery
Forceps, Dumont #5
Fine Science Tools
Forceps, Dumont #7b
Fine Science Tools
Halogen cold light source, KL 1500 compact
Leica
Scissors, extra fine bonn, 13mm
Fine Science Tools
Scissors, student vannas spring, 5 mm
Fine Science Tools
Sealing machine, EM20
Entrhal medical
Stereomicroscope, MZ75
Leica
3.1.8 Software and data bases
Table 9: Software and data bases
Name
Reference / Manufacturer
Columbus image analysis server
PerkinElmer
FCS Express 5 Plus
Denovo Software
FlowJow 8.8.2
TreeStar
GraphPad Prism 5.0
GraphPad Software, Inc.
Harmony high-content imaging and analysis software
Perkin Elmer
LabVIEW 2013
National Instruments
Leica Application Suite X
Leica
Mendeley Desktop 1.19.3
Mendeley
Microwin 2000
Associated with Mithras LB 940
MS Office 2010
Microsoft
NCBI
http://www.ncbi.nlm.nih.gov/
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/
QCapture Pro 6.0
QImaging
Quant studio real-time PCR software
Thermo Fisher Scientific
SoftMax Pro 7.0
Molecular Devices
Materials and Methods
30
3.2 Methods
3.2.1 Cell culture
3.2.1.1 Standard work and culture conditions
Cell culture handling was performed at room temperature under sterile conditions in class II
laminar flow hoods. Cells were cultured at 37 °C, 5% CO2 and 95% air humidity.
3.2.1.2 Coating of cell culture surfaces
Cell culture surfaces were coated with various ECM molecules, depending on the
application.
Geltrex stock vials were thawed at 4 °C overnight and diluted 1:10 in Knockout Dulbecco's
Modified Eagle's Medium (DMEM), these working solutions were stored at -20 °C. At the
time of use the working solutions were further diluted 1:6 in Knockout DMEM, added to the
tissue culture plate and incubated at 37 °C for 30 min.
Fibronectin was prediluted in distilled water (diH20) and stored as a 1 mg/ml stock solution
at -20 °C. At the time of use the stock solution was diluted 1:40, 2 µg/cm² fibronectin were
added to the tissue culture plate and incubated for 30 min at 37 °C. Ready-made 0,1% gelatin
solution was added to the tissue culture plastic ware for 30 min at 37 °C.
8 µg/cm² collagen IV (Col (α1)2α2 (IV)), diluted in PBS (Mg²+, Ca²+) was incubated for 24 h
at 4 °C.
Ready-made 0,1 mg/ml stock solutions of laminin 511 and 521 were diluted in PBS (Mg²+,
Ca²+) to the working concentration. 1 µg/cm² was added to the tissue culture for 24 h at 4 °C.
The coating solutions were removed, and the culture surface was washed with PBS once
prior to cell seeding.
3.2.1.3 hiPSC culture
Human induced pluripotent stem cells were cultured in E8 medium under hypoxic
conditions. The medium was changed daily. hiPSC cultures were checked daily for
differentiated regions under the microscope. These were mechanically removed with the
scraping tool.
The cells were routinely split 1:6 every 5 to 7 days. The well was washed once with
0,5 mM EDTA. To detach the cells 1 ml 0,5 mM EDTA was added for 3-5 min at 37 °C.
Materials and Methods
31
Once the borders of the colonies started to roll up the EDTA was aspirated and 3 ml of
E8 medium was added. The colonies were dislodged with a cell scraper and broken into
smaller colonies by pipetting them up and down three times with a 5 ml pipette. 500 µl cells
suspension was then transferred to a new Geltrex-coated well prefilled with fresh
E8 medium.
3.2.1.4 hiPSC single cell harvest with Accutase
hiPSCs were washed with 1 ml Knockout DMEM. Next, 1 ml Accutase was added per
6-well. After 5 min incubation at 37 °C, 1 ml of E8, 10 μM Rho-associated protein kinase-
inhibitor (ROCKi) was added. Cells were flushed off the culture surface and the cell
suspension was homogenized by pipetting the solution carefully up and down a couple of
times. The cell suspension was centrifuged for 5 min at 300 g and the pellet was resuspended
in 2 ml E8, 10 μM ROCKi. The cell number was determined using the Countess II
Automated Cell Counter.
3.2.1.5 hiPSC-derived intermediate mesoderm cells
The GFP positive hiPSC line WISCi004-B was differentiated into intermediate mesoderm
cells (IMCs) using a modified protocol by Lam et al.113. In brief, hiPSC were harvested as
single cells using Accutase, as described in 3.2.1.4, and 4x105 cells seeded into each well of
a Geltrex coated 6-well plate in E8 medium. Medium was changed at day 3 to advanced
RPMI, 1x GlutaMAX, 5 μM CHIR99021, 100 U/ml penicillin and 100 µg/ml streptomycin
for 36 h. For the next 72 h, the differentiation media was changed to advanced RPMI, 1x
GlutaMAX, 100 ng/ml bFGF, 2 µM retinoic acid, 100 U/ml penicillin and 100 µg/ml
streptomycin. Subsequently, the cells were cultured for 24 h in advanced RPMI, 1x
GlutaMAX, 100 U/ml penicillin and 100 µg/ml streptomycin. The cells were harvested as
single cell suspension using Accutase.
3.2.1.6 hiPSC-derived renal progenitor cells
hiPSCs BIHi004-A were differentiated into renal progenitor cells (RPCs) using the protocol
by Hariharan et al.117. hiPSC colonies were grown to 90% confluence. Then the medium was
changed to AB4RA medium (APEL2 medium, 5% PFHMII, 10 ng/ml Activin A, 30 ng/ml
bone morphogenic protein 4 (BMP4), 1 µM retinoic acid and 100 U/ml penicillin and
Materials and Methods
32
100 µg/ml streptomycin). Medium changes were repeated on day one and two of the
differentiation. On day 4 the medium was changed to GDNF medium (APEL2 medium, 5%
PFHMII, 150 ng/ml glial cell-derived neurotrophic factor (GDNF), 100 U/ml penicillin and
100 µg/ml streptomycin). The GDNF medium was changed every second day. The cells
were harvested on day 8 as single cell suspension using Trypsin.
For cryopreservation the cells were transferred into a 15 ml falcon and centrifuged at 300 g
for 5 min. The supernatant was removed, and the pellet was resuspended in fetal calf serum
(FCS) containing 10% DMSO. 5x106 cells were transferred into each cryo-vial. The vials
were slowly cooled down to -80 °C using a Mr. Frosty freezing container overnight. The
next day the vials were transferred to liquid N2 tanks and stored at -196 °C.
3.2.1.7 hiPSC-derived renal tubular epithelial cells
Renal tubular epithelial cells (RTECs) were differentiated in 6 days from hiPSC-derived
RPCs. RPCs were thawed or freshly harvested on day 8 of differentiation, see 3.2.1.6. The
frozen vials were thawed in a 37 °C water bath. The cell suspension was then transferred
into cold DMEM, 10% FCS and centrifuged at 300 g for 5 min. The supernatant was
removed, and the cell pellet resuspended in renal epithelial growth medium (REGM)
medium.
hiPSC-derived RPCs were seeded onto 1µg/cm² laminin-521 coated cell culture plates with
a cell density of 1,25x105 fresh cells/cm² or 2,25x105 thawed cells/cm². Cells were cultured
for six days with medium changes every other day.
3.2.1.8 hiPSC-derived endothelial cells
Endothelial cells were differentiated from the hiPSC lines BIHi004-A or BCRTi005-A
according to a protocol by Patsch et al.109. hiPSCs were harvested as single cells with
Accutase, as described in 3.2.1.4. 5x104 cells/cm² were seeded into Geltrex coated T175 cell
culture flasks in E8 medium, 10 μM ROCKi. The next day, day 0 of the differentiation, the
medium was changed to 120 ml priming medium made from DMEM/F-12:Neurobasal 1:1,
2% B-27 without Vitamin A, 1% N-2, 25 ng/ml BMP4 and 7 µM CHIR99021. At day 3 and
4 the medium was exchanged with 60 ml endothelial cell induction medium consisting of
StemPro-34 serum free medium, StemPro-34 nutrient supplement, 1% GlutaMAX,
200 ng/ml VEGF, 2 µM forskolin and 100 U/ml penicillin and 100 µg/ml streptomycin.
Materials and Methods
33
At day 5 the cells were harvested, sorted with magnetic-activated cell sorting (MACS) and
reseeded into expansion medium. First, the cell layer was washed with 10 ml PBS. Next,
5 ml prewarmed 0,05% Trypsin-EDTA were added for 4 min at 37 °C. The digestion was
stopped by adding 10 ml MACS buffer made from PBS, 0,5% FCS, 2 mM EDTA. The cell
suspension was centrifuged for 5 min at 300 g, the cell pellet was resuspended in
80 µl MACS buffer/107 cells. 20 µl MicroBeads conjugated to monoclonal anti-human
CD144 antibodies/107 cells were added and the cells were incubated for 15 min at 4 °C, to
magnetically label the CD144+ cells. Then, the cells were washed with 2 ml MACS buffer,
resuspended in 500 µl MACS buffer and transferred onto an MS MACS-column that was
rinsed with 500 µl MACS buffer and placed into the magnetic field before. The column was
washed thrice with 500 µl MACS buffer to wash out unlabeled CD144- cells. To collect the
magnetically bound CD144+ cells, the column was removed from the magnetic field and
flushed with 1ml MACS buffer.
For endothelial cell maturation and expansion, the sorted cells were seeded onto 0,1% gelatin
or 2 µg/cm² fibronectin coated plates and cultured in either EGM-FCS-SB medium, EC-SFM
or StemPro-34 medium, as listed in Table 10. Medium was changed every other day. Cells
were splitted with Trypsin approximately every 6 days, when they reached 80% confluence.
Differentiation and sorting efficiency as well as phenotype stability were checked by flow
cytometry before and after MACS and at every cell split, see 3.2.12.
Table 10: List of the expansion media for hiPSC-derived endothelial cells
EC expansion medium
Composition
Seeding density
Reference
EGM-FCS-SB
EGM-2 without hydrocortisone
20 % FCS
10 mM SB431542
1% P/S
5000 cells/cm²
Ren et al. 2015141
EC-SFM
EC serum free medium
1% human serum
30 ng/ml VEGF
20 ng/ml bFGF
5000 cells/cm²
Orlova et al. 2014142
StemPro-34
StemPro-34 serum free medium
StemPro-34 supplements
1% GlutaMAX
50 ng/ml VEGF
1% P/S
26000 cells/cm²
Patsch et al. 2015109
Materials and Methods
34
3.2.1.9 Human umbilical vein endothelial cells
Human umbilical vein endothelial cells (HUVECs) were cultured in T175 cell culture flasks
in 15 ml endothelial growth medium 2 (EGM-2) supplemented with 10% FCS,
100 U/ml penicillin and 100 µg/ml streptomycin. The medium was changed every other day.
HUVECs were seeded with a density of 7000 cells/cm² and were splitted with Trypsin
approximately every 6 days, when they reached 80% confluence. Cells until passage eight
were used for experiments.
3.2.2 Decellularization of porcine kidney tissue by immersion and agitation
3.2.2.1 Organ preparation
Cadaveric porcine kidneys were collected from infant (1-3 months) piglets and stored
at -20 °C for at least 24 h. All animal experiments were performed under the guidelines of
the German Animal Protection Law with approval of the local responsible authorities
(Landesamt für Gesundheit und Soziales Berlin). Decellularization of kidneys was
performed by immersion and agitation of tissue samples in decellularization solutions.
Frozen porcine kidneys were thawed, and the renal cortex was sampled into cubes with the
size of approximately 0,5 x 0,5 x 0,5 cm.
3.2.2.2 Decellularization procedure
The tissue cubes were washed three times for 5 min in DMEM w/o phenol red. After
incubation for 24 h in diH20, which was changed once after 4 h, the tissue samples were
immersed in three different detergents: 1% (w/v) SDS, 1% (v/v) TX-100 or 1% (w/v) SDC
for 7-10 days. The decellularization solutions were initially changed after 8 h and thereafter
every 48 h. Agitation was applied by using a shaker at 50 rpm throughout the incubation.
Decellularization was carried out at 4 °C, at room temperature (RT; 22-24 °C) or at 37 °C to
examine the influence of the temperature. The decellularization was terminated when no
further changes in transparency and macroscopic appearance were observed for 48 h. The
transparent tissue samples were washed three times in DMEM, then incubated in 350 IU/mL
DNase I in DMEM for 18 h at 37 °C and finally washed again three times in DMEM
supplemented with 100 U/ml penicillin and 100 µg/ml streptomycin and
2,5 mg/ml amphotericin B (AntiAnti) for 18 h at RT.
Materials and Methods
35
To assess cell attachment and the elastic modulus, 50 µm frozen kidney sections were
mounted on poly[octadecene-alt-(maleic anhydride)] (POMA)-coated glass-coverslips30 and
decellularization performed at 4 °C as described above.
Table 11: Overview of decellularization by immersion and agitation conditions
Wash
Decellularization
Wash
Temperature
RT
4 °C, RT, 37 °C
37 °C
RT
Duration
0,25 h
24 h
168-240 h
18 h
18 h
Reagents DMEM diH20
1% SDC
DMEM +
350 IU/ml DNase I DMEM
1% SDS
1% TX-100
diH20, distilled water; DMEM, Dulbecco's Modified Eagle's Medium w/o phenol red; RT, 22-24°C; SDS, sodium dodecyl
sulfate; SDC, sodium deoxycholate; TX-100, Triton X-100
3.2.3 Decellularization of whole rat kidneys by perfusion
3.2.3.1 Organ preparation
Kidneys were collected from cadaveric 12-week-old Wistar rats that were injected with
500 U heparin prior to sacrifice. After disinfecting the abdominal fur, the abdomen was
opened by cutting the skin and abdominal muscles. The intestine was carefully removed
from the abdominal cavity and placed at the left side of the rat, without disrupting the
intestinal wall. Both ureters were cleared from fat with cotton swabs and cut close the
bladder.
Next, the renal arteries were prepared for cannulation. Abdominal fat and connective tissue
were removed. The renal vein was detached from the renal artery and cut close to the kidney.
The aorta was cut between the superior mesenteric artery and the right renal artery, between
right and left renal artery and below the left renal artery, as depicted in Figure 10A. The
resulting aorta sections were cut open to produce patches attached to the renal arteries. These
patches facilitate the insertion of the cannula into the renal arteries. A sterile feeding needle
was used as the artery cannula. It was prefilled with PBS, 50 U/ml Heparin, 1% AntiAnti
and pushed into the renal artery. The ball-head of the feeding needle was placed between the
inferior suprarenal artery and the branching of the renal artery, see Figure 10B. The cannula
was fixed, and the cannulation sealed by placing a ligature directly behind the ball-head of
the feeding needle with a double surgical knot with a 7-0 silk suture. The cannulated kidney
was removed from the abdomen by cutting away the adipose capsule and the adrenal gland.
Materials and Methods
36
The released kidney was flushed with 5 ml PBS, 50 U/ml Heparin, 1% AntiAnti to remove
blood from the vessels inside the organ.
Figure 10: Organ preparation for decellularization of whole rat kidneys by perfusion (A) Schematic
overview of the anatomy of the urinary tract and the abdominal blood vessels of a rat. Black lines indicate the
cutting sites during the cannulation procedure. (D) A photograph of the same area. Arrows indicate the prepared
left and right renal arteries and the ureter. (E) The arteries were cut into patches, as indicated by white arrows.
The patches could easily be cannulated with a ball-headed feeding needle. (B,F) The cannulated kidney was
removed from the body, to this end the vein and ureter were cut. (C) After decellularization by perfusion
through the artery, the ureter was cannulated for recellularization via the ureter.
Materials and Methods
37
3.2.3.2 Assembly of the decellularization perfusion bioreactor
The perfusions system was assembled under
sterile conditions in class II laminar flow hoods.
All parts were sterile prior to assembly. Two
kidneys were decellularized in one perfusion
bioreactor.
Therefore, two kidneys were placed into one
decellularization chamber, a 1000 ml laboratory
bottle with a hose connection screw cap and
connected via the cannulated arteries to one
perfusor line each. The perfusor lines were
threaded through the IN-ports 1 and 2 of the hose
connection screw cap and connected to the pump
tubing. The pump tubing was then connected via
a 3-way stopcock to the OUT-port of the decellularization agent reservoir. The
decellularization agent reservoir was also assembled from a 1000 ml laboratory bottle with
a hose connection screw cap.
All connections were made with Luer-Lock components. The system was prefilled with
decellularization agents before perfusion start.
3.2.3.3 Decellularization procedure
The perfusion bioreactor was either placed at room temperature or in 4 °C to examine the
influence of the temperature. The pump tubing was clamped into the perfusion pump and
the perfusion was started with a flow rate of 0,5 ml/min. The kidneys were first perfused
with PBS containing 50 U/ml Heparin and 1% AntiAnti for 30 min to remove residual blood.
Next, kidneys that were decellularized according to the SDC protocol were perfused for
120 h with 1% SDC and then washed with PBS, 1% AntiAnti for 36 h (Table 12). Kidneys
that were decellularized according to the SDS/TX-100 protocol (adapted from Song et al.123)
were perfused with 1% SDS, diH20 and 1% TX-100 for 16 h, 30 min and 30 min, respectively
(Table 13). Fully filled decellularization chambers and empty decellularization agent
reservoirs were exchanged under the sterile flow hood. Decellularized kidneys were stored
at 4 °C in PBS, 1% AntiAnti.
Figure 11: Schematic setup of the
decellularization perfusion bioreactor
Figure
11
: Schematic setup of the
: Schematic setup of the
Materials and Methods
38
Table 12: SDC protocol conditions for decellularization by perfusion
Wash
Decellularization
Wash
Temperature
4 °C, RT
4 °C, RT
4 °C, RT
Duration
0,5 h
120 h
36 h
Reagents
PBS,
50 U/ml heparin,
1% AntiAnti
1% SDC PBS,
1% AntiAnti
diH20, distilled water; PBS, phosphate buffered saline; RT, 22-24°C; SDC, sodium deoxycholate; AntiAnti, mixture of
penicillin, streptomycin and amphotericin B
Table 13: SDS/TX-100 protocol conditions for decellularization by perfusion
Wash
Decellularization
Wash
Temperature
4 °C, RT
4 °C, RT
4 °C, RT
Duration
0,5 h
16 h
0,5 h
0,5 h
36 h
Reagents
PBS,
50 U/ml heparin,
1% AntiAnti
1% SDS diH20 1% TX-100 PBS,
1% AntiAnti
diH20, distilled water; PBS, phosphate buffered saline; RT, 22-24°C; SDS, sodium dodecyl sulfate; TX-100, Triton X-100;
AntiAnti, mixture of penicillin, streptomycin and amphotericin B
3.2.4 Characterization of decellularized kidneys
3.2.4.1 DNA quantification
Samples were snap frozen and pulverized by grinding in a precooled mortar, then dried for
1,5 h using a vacuum concentrator and digested in 0,2 mg/ml proteinase K solution (in
100 mM Tris, 5 mM EDTA, 0,2% SDS, 0,2 M NaCl) overnight at 55 °C. After inactivating
the proteinase K for 10 min at 96 °C, the DNA was extracted by phenol-chloroform
extraction. DNA concentration was quantified using a Nanodrop spectrometer and
normalized to the tissue dry weight.
3.2.4.2 Glycosaminoglycan quantification
Sulfated GAGs were quantified in native and decellularized kidneys using the Blyscan GAG
assay. 30 mg of pulverized sample was digested with 125 μg/ml papain solution (in
0,1 M sodium acetate, 5 mM cysteine-HCl, 50 mM EDTA, pH 6,0) for 16 h at 65 °C. GAGs
were precipitated with dimethylmethylene blue dye and dissolved in the dye dissociation
reagent. The absorbance at 595 nm was measured using a microplate reader and compared
to a chondroitin-4-sulfate standard.
Materials and Methods
39
3.2.4.3 Collagen quantification
Total collagen was quantified by measuring the hydroxyproline content with the Total
Collagen Assay Kit. 5 mg of pulverized sample was hydrolyzed with 6 M HCl at 95 °C
overnight. Hydroxyproline residues were oxidized and stained according to the
manufacturer’s instructions. The absorbance was measured at 570 nm and compared to a
hydrolyzed collagen I standard.
3.2.4.4 Cytokine quantification
230 mg sample powder was lyophilized, the dry weight determined and then dissolved in
1 ml RIPA buffer (150 mM NaCl, 50 mM Tris, 1% TX-100, 0,5% SDC, 0,1% SDS). Lysates
were sonicated for 20 s, incubated for 20 h at 4 °C on a shaker and centrifuged at 13000 g
for 10 min. The VEGF and bFGF content in the supernatants were determined with the
hVEGF ELISA Kit and the hbFGF ELISA Kit. Both kits were used according to the
manufacturer’s instructions. The absorbance was measured at 450 nm and 650 nm. Cytokine
concentrations were normalized to the tissue dry weight.
3.2.4.5 Elastic modulus
The elastic modulus of glomerular structures in decellularized and native porcine kidney
ECM was determined with atomic force microscopy (AFM), as published earlier143. In short,
the frozen tissue was mounted and decellularized on a glass cover slip (see 3.2.2.2). The
glomerular ECM was probed by force measurements with an MFP3D-Bio AFM using a
spherical probe with a radius of 3,35 μm and an indentation depth of ∼300 nm.
The bulk elasticity of the PDMS gels was assessed in an unconfined compression experiment
with the Bose test bench LM 1 ElectroForce. 4 mm punch biopsies were compressed at a
rate of 1 mm/min with a 225 N load cell. The displacement was set to 10% of the biopsy’s
height and the displacement data were sampled at 100 Hz. The elastic bulk modulus was
calculated as the best-fit slope of the resulting stress/strain curve.
Materials and Methods
40
3.2.5 Recellularization of immersion-decellularized porcine kidney scaffolds
Intermediate mesoderm cells were suspended in advanced RPMI, 1x GlutaMAX,
100 U/ml penicillin and 100 µg/ml streptomycin. 3x105 cells/cm2 were seeded on the
decellularized ECM mounted on a glass cover slip (see 3.2.2.2). Glass coverslips and cell
culture treated polystyrene were used as controls. Experiments were performed in triplicates.
24 h after seeding the cells on the matrix, the cumulative cell viability was assessed with the
resazurin reduction assay (see 3.2.7.1).
3.2.6 Recellularization of perfusion-decellularized whole rat kidneys
3.2.6.1 Assembly of the recellularization perfusion bioreactor
The perfusions bioreactor was assembled under sterile conditions in class II laminar flow
hoods. All parts were sterile prior to assembly. The bioreactor was assembled from a 50 ml
laboratory bottle, filled with 20- 50 ml medium, and a hose connection screw cap providing
three ports. The gas-port was connected to a 0,2 µm gas filter. The end of a 150 cm perfusor
line dipped into the medium. The other end of the same line was threaded through the
OUT-port of the screw cap and connected to a 3-way stopcock, which served as a sample
port to draw medium samples for glucose, lactate and lactate dehydrogenase (LDH)
measurements (see 3.2.7.1). The 3-way stopcock was connected to the pump tubing, which
was connected to the membrane oxygenator. A 50 cm perfusor line was used to connect the
membrane oxygenator to the pH sensor, pO2 sensor, pressure sensor and a second
3-way stopcock in series. The 3-way stopcock was connected to the IN-port of the screw cap
to which the decellularized kidney was attached via the cannulated artery after all hoses were
prefilled with medium. The assembled bioreactor was placed inside an incubator, where the
gas inlet of the oxygenator was connected to a humidifier and then to a gas mixing device,
the pump tubing was clamped into the perfusion pump and all sensors were connected to the
measuring instruments. The incubator heated to 37 °C. The perfusion bioreactor was
controlled via the control software. All connections were made with Luer-Lock components.
Materials and Methods
41
3.2.6.2 Recellularization strategies
Decellularized rat kidneys were preconditioned for recellularization by perfusion with
30 ml medium in the recellularization-perfusion bioreactor for several hours. Cells were
either seeded via the artery, the ureter or via injection into the cortex with a syringe.
For arterial seeding with low pressure 3x107 RPCs, 5x107 HUVECs or 5x107 ECs were
harvested, resuspended in 1 ml REGM or EGM-2, respectively, and filled into a syringe.
Bubbles were pushed out of the syringe and the renal cannula was filled with medium to
ensure no bubble would be pushed into the decellularized kidney. Next, the cell suspension
was injected through the cannula in the renal artery into the decellularized kidney with a
speed of approximately 2 ml/min. Swelling of the kidney was observed if no leakage
occurred. The kidney was then placed into the bioreactor and the artery cannula was
connected via Luer-Lock to the IN-port perfusor line. The bioreactor was placed overnight
in the incubator without perfusion to facilitate cell attachment. The perfusion culture was
started the next morning.
Kidneys were partially digested with trypsin before cell seeding to facilitate the cell
migration from the vascular tree into the renal tubules. Therefore, 1 ml 0,25% trypsin in
REGM and 1% AntiAnti were injected into the renal artery followed by 1 h incubation at
37 °C. The digest was stopped by injecting 1 ml DMEM, 10% FCS and subsequent perfusion
with PBS at 0,5 ml/min for 30 min to remove residual trypsin. Next, the preconditioning and
arterial seeding with low pressure was performed.
For arterial seeding with high pressure 3x107 RPCs were harvested, resuspended in
2 ml REGM and filled into a syringe. The decellularized kidney was placed into the
bioreactor and the cells were injected into the cell seeding port. The perfusion was started
immediately with 25 ml/min for 15 min.
For seeding via the ureter without vacuum, the ureter was cannulated using a 26-gauge
Neoflon catheter, as illustrated in Figure 10C. The decellularized ureter is very thin,
therefore the tip of the catheter was beveled without producing a sharp tip that would tear
the ureter easily. An incision was made in the proximal ureter, the cannula inserted and fixed
with a ligature. 3x107 RPCs resuspended in 1 ml REGM were injected slowly into the kidney
through the ureter cannula. The kidney was connected via the arterial cannula to the
perfusion bioreactor and cultured under static conditions overnight before perfusion culture
started.
Materials and Methods
42
When the cells were seeded via the ureter with vacuum, 3x107 RPCs in 100 µl REGM were
injected into the ureter cannula. The decellularized kidney was then placed in the
recellularization bioreactor and connected via the ureter cannula to the IN-port perfusor line.
The gas-port was connected to a vacuum pump and 100 mbar vacuum was applied to suck
500 µl REGM from the cell seeding port into the ureter. The perfusion culture was started
after overnight static culture.
In the syringe seeding process 3x107 RPCs were resuspended in 1 ml or 100 µl REGM and
filled into a 1ml or 100 µl syringe. Cells were injected into the cortex with 10x 100µl or
20x 5 µl injections using a 27-gauge needle. The perfusion culture was started the next
morning.
3.2.6.3 Perfusion culture
Recellularized kidneys were cultured for three to six days in the perfusion bioreactor.
20-50 ml medium was circulated with 0,25-0,5 ml/min. The arterial high pressure seeding
experiment was perfused with 4 ml/min according to the protocol by Caralt et al.144. The
medium was exchanged every second day. RPCs were cultured in REGM, HUVECs were
cultured in EGM-2 and hiPSC-ECs were cultured in EGM-FCS-SB medium. 5% CO2 and
95% air were perfused through the membrane oxygenator for pH control. pH and pressure
were constantly monitored with the LabView control software. Medium samples were drawn
at the sample port with a 1 ml syringe for glucose, lactate and LDH quantification every
12-24 h, see 3.2.7.1. Before terminating the perfusion culture, the resazurin reduction assay
was performed, see 3.2.7.2.
3.2.7 Characterization of recellularized kidneys
3.2.7.1 Glucose, lactate, LDH measurement in the culture medium
600 µl medium were drawn from the sample port of the recellularization perfusion
bioreactor. 250 µl were injected into the ABL 700 for glucose and lactate quantification.
350 µl were sent to Labor Berlin for the determination of the LDH concentration.
Materials and Methods
43
3.2.7.2 Resazurin reduction assay
Resazurin is a soluble dye that is reduced to resorufin
by cells, proportional to their metabolic activity and
number. Resorufin is highly fluorescent and servers
as a noninvasive tool to measure cellularity and
growth within ECM scaffolds145.
Resazurin was added to a final concentration of
44 µM to the culture medium. Perfusion or static cell
culture was continued for 90 min. The relative
fluorescent units (RFU) of the fluorescent resorufin
were measured by excitation at 535 nm and readout
at 615 nm in a multiplate reader.
3.2.7.3 Quantification of cells by image analysis
Cell attachment on immersion-decellularized porcine kidneys was assessed by scanning the
samples with the Operetta high content imaging system after 30 h and 72 h. Attached
GFP-positive cells were distinguished from non-attached GFP-positive cells and counted by
running the analysis sequence “Count attached GFP+ cells” with the Columbus image
analysis server (see Figure S1).
The cell number in recellularized rat kidneys was determined after the termination of the
perfusion culture. 4',6-diamidino-2-phenylindole (DAPI) stained paraffin sections of the
recellularized kidneys (according to 3.2.11) were scanned with the Operetta high content
imaging system and analyzed with the Columbus image analysis server using the analysis
sequence “Count DAPI-nuclei on kidney sections” (see Figure S2). The counted cells were
normalized to the scanned images per kidney section.
3.2.8 Tuning of the pressure and pH controllers
To tune the pressure and the pH controller the system was first characterized by recording
the step response. Therefore, the control variable (CV) was changed and the process variable
(PV) recorded.
Figure 12: Resazurin is reduced to the
fluorescent resorufin by metabolically active
cells
145
.
Materials and Methods
44
With these data the controller was tuned. The reference-variable response was recorded to
check the tuning. Therefore, the setpoint was changed and the control variable and process
variable recorded. With these data the control deviation and the control settling time was
determined. Additionally, the disturbance response for the pressure controller was recorded.
All settings are shown in Table 14.
Table 14: System settings for controller tuning
Response
Action
Pressure controller
pH controller
step response CV change 5 rpm 10 rpm or 40 rpm 0% CO2 10% CO2
reference-variable response
SP change
10 mmHg

30 mmHg
pH 7,4

pH 7,2
disturbance response disturbance 3-way stopcock of cell
seeding port closed
300 mg Citrate bolus and
300 mg NaOH bolus
3.2.9 PDMS gel assay
PDMS gels of three different stiffnesses were produced. Sylgard kit 527 or 184 were used
in distinct silicone base to curing agent ratios according to the desired stiffness of the PDMS,
as shown in Table 15. The base and curing agent were thoroughly mixed, degassed and
200 µl gel were poured into each well of a 12-well plate. The PDMS was cured for 12 h at
55°C. The bulk E modulus of the cured gels were determined as described in 3.2.4.5.
Table 15: PDMS preparations
E modulus
Product
Base
Curing agent
Ratio
4 kPa
SYLGARD 527 A&B Silicone Dielectric Gel
9,81 g
10,19 g
0,96
200 kPa
SYLGARD 527 A&B Silicone Dielectric Gel
2,03 g
17,93 g
0,115
2 MPa
SYLGARD 184 Silicone Elastomer Kit
18,19 g
1,81 g
10
PDMS requires a polydopamine coating to reduce hydrophobicity to and improve cell
attachment. Therefore, the PDMS was treated with 0,01% dopamine in 10 mM Tris-HCl,
pH 8,5, for 24 h at RT. Residual dopamine was removed by washing with PBS for 7 days.
The polydopamine coated PDMS was then coated in another step with extracellular matrix
proteins. 1 µg/cm² laminin 511, 1 µg/cm² laminin 521 and/or 8 µg/cm² collagen IV in PBS
including Mg2+ and Ca2+ were added to well plate for 24 h at 4°C.
Materials and Methods
45
Cryopreserved hiPSC-derived renal progenitor cells were thawed and seeded onto the PDMS
surfaces and differentiated into hiPSC-derived renal tubular epithelial cells, as described in
3.2.1.7. Six days after cell seeding, the ribonucleic acid (RNA) was harvested for qPCR
analysis.
3.2.10 Quantitative polymerase chain reaction
RNA isolation from cells was performed using the RNeasy Plus Mini kit according to the
manufacturer’s instructions. The RNA concentration was determined with the NanoDrop
and the RNA was stored at -80 °C. Next, the RNA was reverse transcribed into
complementary DNA (cDNA) using the TaqMan Reverse Transcription Reagents cDNA kit
following the manufacturer’s instructions. The reverse transcription polymerase chain reaction
(RT-PCR) reaction mix and cycling conditions are displayed in Table 16 and Table 17. The
cDNA was diluted 1:1 with diH2O and stored at 4 °C.
Table 16: TaqMan RT Reaction Mix
Component
Concentration
Volume
RT Buffer
10x
2,0 µl
MgCl
2
25 mM
1,4 µl
dNTP mix
10 mM
4,0 µl
Random hexamer primer
50 µM
1,0 µl
RNase Inhibitor
20 U/μL
1,0 µl
MultiScribe RT
50 U/μL
1,0 µl
Template RNA
<1 µg/rxn
9,6 µl
Table 17: RT-PCR cycling conditions
Temperature
Time
25 °C
10 min
37 °C
30 min
95 °C
5 min
4 °C
indefinitely
Quantitative polymerase chain reaction (qPCR) was performed using the TaqMan Fast
Advanced Master Mix and TaqMan Gene Expression Assays for AQP1, ATP1A1, PODXL,
SIX2, SLC12A2, SLC12A3, SYNPO and WT1. According to the manufacturer’s instructions
1 µl cDNA was used per reaction in a total volume of 10 µl, as shown in Table 18. The assay
was conducted in 384-well PCR plates in the QuantStudio 6 Flex Real-Time PCR System.
Materials and Methods
46
Cycling conditions are shown in Table 19. GAPDH and RNA18S5 were used as
housekeeping genes. Relative gene expression was calculated with the 2-ΔΔCt method.
Table 18: TaqMan qPCR Reaction Mix for a 384-well plate
Component
Concentration
Volume
TaqMan Fast Advanced Master Mix
2x
5 µl
TaqMan Gene Expression Assay
20x
0,5 µl
Nuclease-free water
3,5 µl
cDNA template
1 µl
Table 19: qPCR cycling conditions
Temperature
Time
50 °C
2 min
95 °C
20 s
95 °C
1 s
40 cycles
60 °C
20 s
3.2.11 Histology and immunofluorescence staining
3.2.11.1 Paraffin embedding and sectioning
Native and decellularized kidney tissues were fixed in 4% phosphate-buffered formaldehyde
solution for 24 h at RT. The fixed samples were then dehydrated in 12 steps in a tissue
processor, as shown in Table 20, and embedded in paraffin.
Table 20: Dehydrating steps before embedding of tissue in paraffin blocks
Step
Reagent
Time
Step
Reagent
Time
1
70% EtOH
1 h
7
100% EtOH
2 h
2
80% EtOH
1 h
8
100% EtOH
3 h
3
80% EtOH
2 h
9
Xylol
1 h
4
96% EtOH
2 h
10
Xylol
1,5 h
5
96% EtOH
2 h
11
Paraffin, 65 °C
2 h
6
100% EtOH
2 h
12
Paraffin, 65 °C
2 h
Total time
21,5h
Paraffin blocks were cut into 5 µm sections using a microtome and stored at RT. Before HE
or immunofluorescence staining the sections were deparaffinized and rehydrated according
to the protocol depicted in Table 21.
Materials and Methods
47
Table 21: Rehydration of paraffin sections
Step
Reagent
Time
1
Xylol I
10 min
2
Xylol II
10 min
3
100% EtOH I
2 min
4
100% EtOH II
2 min
5
96% EtOH
2 min
6
80% EtOH
2 min
7
70% EtOH
2 min
8
diH
2
O
10 s
3.2.11.2 HE staining
Hematoxylin and eosin (HE) staining was performed on rehydrated paraffin sections
according to the protocol shown in Table 22. In short, sections were stained for 5 min in
Mayer’s acid hemalum, washed 15 min in tap water and stained for 2 min in Eosin Y.
Sections were then dehydrated again and mounted with Roti-Histokitt. Imaging was
performed using an inverse microscope.
Table 22: HE staining on rehydrated paraffin sections
Step
Reagent
Time
1
Mayer’s acid hemalum
5 min
2
Running tap water
15 min
3
Eosin Y
2 min
4
diH
2
O
10 s
5
96% EtOH
1 min
6
100% EtOH I
2 min
7
100% EtOH II
2 min
8
Xylol I
10 min
9
Xylol II
10 min
3.2.11.3 Immunofluorescence staining
Immunofluorescence staining on paraffin sections requires antigen retrieval treatment before
the staining. Table 23 displays the applied antigen retrieval treatments for each antibody
used. Thereafter, samples were permeabilized with 20 mM Tris-Base, 500 mM NaCl,
0,1% TX-100, pH 7,5 (T-TBS) three times for 5 min.
The samples were then blocked for 10 min with 1% bovine serum albumin (BSA) in 20 mM
Tris-Base, 500 mM NaCl, pH 7,5 (TBS) and for 30 min with 5% donkey serum and 1% BSA
in TBS before immunostaining. Primary antibodies were applied overnight at 4 °C. All
Materials and Methods
48
antibodies were diluted in 5% donkey serum and 1% BSA in TBS as listed in Table 23. After
washing with T-TBS, slides were incubated with the secondary antibody
Alexa647-conjugated polyclonal donkey anti-rabbit IgG in 1:500 dilution for 1h at RT.
Finally, after washing in T-TBS for 5 min, sections were mounted with immunoselect
antifading mounting medium including DAPI.
The same protocol was adapted to stain non-paraffin embedded samples, e.g. cells from cell
culture experiments. Cells were fixed for only 10 min in 4% phosphate-buffered
formaldehyde solution. No antigen retrieval treatment is necessary for these samples. These
samples were not mounted, therefore staining with DAPI for 5 min and washing with diH2O
twice for 5 min was added to the end of the staining protocol.
For negative staining controls, the primary antibody was omitted.
Imaging was performed using either an inverse microscope or the Operetta high content
imager and Columbus image analysis server.
Table 23: Antigen retrieval treatments for immunofluorescence staining on paraffin sections
Antibody
Dilution
Antigen retrieval
anti-fibronectin
1:300
TE buffer, pH 8, 10 min in pressure cooker
anti-laminin
1:100
TE buffer, pH 8, 10 min in pressure cooker
anti-collagen IV
1:200
TE buffer, pH 6, 10 min in pressure cooker
anti-collagen I
1:100
TE buffer, pH 8, 10 min in pressure cooker
anti-CD31
1:100
Dako Target Retrieval Solution, 20 min at 95 °C in water bath
3.2.12 Flow cytometry
Flow cytometric analysis of LHX1 and PAX2 was used to quantify the differentiation
efficacy of hiPSC-derived IM cells. Cells were stained with LIVE/DEAD Fixable Blue Dead
Cell Stain Kit for 30 min, permeabilized with BD FACS Permeabilizing Solution 2 for
15 min and blocked in 10% donkey serum for 30 min. Thereafter, cells were incubated for
30 min at RT with the anti-PAX2 and anti-LHX1 at 1:50 dilutions. After washing with
2% FCS in PBS, cells were incubated with 1:1000 AlexaFluor 647-conjugated donkey
anti-rabbit IgG or AlexaFluor 647-conjugated donkey anti-mouse IgG for 30 min in the dark.
Stained cells were analyzed using an LSR-II Fortessa flow cytometer and data analysis was
conducted in FlowJo Version 9.
Flow cytometric analysis of CD31 and CD144 was used to check the differentiation efficacy
of hiPSC-derived EC cells. 50000 cells were resuspended in 40 µl MACS buffer (PBS,
Materials and Methods
49
0,5% FCS, 2 mM EDTA), 10 µl FcR Blocking Reagent, 2 µl anti-CD31-APC and
1 µl anti-CD144-FITC and stained for 10 min at 4 °C. After washing in 2 ml MACS buffer,
the stained cells were resuspended in 200 µl MACS buffer and 0,5 µl Propidium Iodid,
measured with MACSQuant VYB and analyzed with FCS Express 5 Plus software.
3.2.13 Statistical analysis
Quantitative results are reported as means ± standard error of the mean (SEM). Data were
tested for normal distribution using the D’Agostino-Pearson omnibus K2 normality test.
Data sets with normal distribution were analyzed for significant differences with the
unpaired t-test or one-way analysis of variance (ANOVA) followed by Tukey’s post test.
Non-parametric tests were applied to data sets without normal distributed. The Mann-
Whitney test or Kruskal-Wallis and Dunn’s post test were utilized. All statistical testing was
performed using GraphPad Prism 5. The significance level was set to 0,05.
Results
50
4 Results
4.1 Development of a perfusion bioreactor for de- and
recellularization of whole kidneys
4.1.1 Setup
For de- and recellularization of whole rat kidneys it is compulsory to perfuse the organ with
either decellularization reagents or cells and cell culture medium. Therefore, a perfusion
bioreactor that permits de- and recellularization in the same system was developed (Figure
13 and Figure 14).
For recellularization, cell culture conditions have to be provided. Therefore, sterility has top
priority. Thus, the system was designed to be assembled under a class II laminar flow hood
and to minimize reopening during the whole culture period. The kidney is placed in a
bioreactor and via Luer-Lock attached with the cannulated artery to sterile tubing. The cell
culture medium is also filled into the bioreactor and circulated with a peristaltic pump using
sterile pump tubing. The medium is perfused into the renal artery, then drains through ureter,
renal vein and decellularized parenchyma back into the bioreactor.
The perfusion speed influences the pressure applied to the kidney. To avoid damage to the
delicate kidney structures or to the reseeded cells by an exceedingly high pressure, the
pressure has to be monitored and the perfusion speed has to be controlled. Therefore, a
pressure sensor was included into the perfusion circuit.
Another factor to ensure cell culture conditions is to maintain a physiological pH of the
perfusion medium. Most cell culture media contain a bicarbonate buffer system. This permits
control of the pH via CO2 gassing. Therefore, an optical flow through pH sensor and an
oxygenator were integrated into the perfusion circuit. The oxygenator contains 1 m gas
permeable silicone tubing that is perfused with culture medium and surrounded by gas. The
oxygenator is aerated by a gas mixing device that controls the CO2 percentage.
In first test runs of the system, excessive medium evaporation that led to an increase in
medium osmolarity could be observed, caused by low humidity of the used gas mixture. This
problem was solved by the installation of a gas humidifier between oxygenator and gas
Results
51
mixing device. Additionally, an oxygen flow through sensor was integrated into the
perfusion bioreactor. Lastly, for temperature control, the whole system was placed inside an
incubator, set to 37 °C. The system is equipped with two ports. One port for cell seeding and
one for medium sampling.
All sensors, the peristaltic pump and the gas mixing device are connected to a computer
running the control software. The exact specifications are listed in Table 24.
Figure 13: Schematic setup of the recellularization perfusion bioreactor. The perfusion bioreactor is placed
inside an incubator for temperature control. The cannulated kidney is connected to the perfusion tubing inside
a sterile chamber. Decellularization agents or cell culture medium are circulated via a peristaltic pump whose
speed is controlled to attain the required perfusion pressure. A membrane oxygenator is used to adjust the pH
of the medium via the CO2 content in the gas flow. The gas is humidified before entering the membrane
oxygenator to reduce evaporation. Ports are installed for medium sampling and cell seeding. A LabVIEW based
control software monitors and controls the perfusion bioreactor.
Table 24: Overview over the technical background of the perfusion bioreactor
Pressure controller
pH controller
Control variable
Pump speed
CO
2
Control element
Peristaltic pump, connected to a PC via serial
interface, communication via a provided
LabVIEW driver
Gas mixing device, connected to a PC via USB,
communication protocol provided and
implemented in LabVIEW via VISA elements
Process variable
Pressure
pH
Sensor
Pressure sensor, amplifier connected to the
voltage input module NI9201 in the NIcDAQ-
9174 chassis, communication via DAQmx
elements in LabVIEW
Fiber optic pH sensor, connection to the PC via
serial interface, communication protocol provided
and implemented in LabVIEW via VISA elements
Setpoint
Pressure setpoint
pH setpoint
Results
52
Figure 14: Setup of the perfusion bioreactor. (A) The bioreactor is installed in an incubator. (B) The fully
assembled and running system. The peristaltic pump pumps the medium from the bioreactor through the
oxygenator and the flow through sensors back into the kidney inside the bioreactor. (C) The bioreactor harbors
the cannulated, decellularized kidney. The PT100 temperature sensor is located close to the bioreactor. (D) A
more detailed view of the seeding port, the flow through pressure dome connected to the pressure transducer
and the optical flow through pH sensor connected to the optical fiber of the fiber optic pH transmitter, from
left to right. (E) A detailed view of the oxygenator with medium perfused silicone tubing and the gas humidifier
in the back. (F) The fiber optic oxygen transmitter, the fiber optic pH transmitter and the amplifier of the
pressure transducer. (G) The PT100, pressure sensor amplifiers and incubator are connected via a cDAQ system
to the PC. (H) The gas mixing device mixes CO2 and air and gasses the oxygenator.
Results
53
4.1.2 Software development for the control of the perfusion bioreactor
The control software allows full control of the perfusion bioreactor. After software start the
user is asked to enter the experiment title. Thereafter the first user interface opens, the setup
tab (Figure 15A). Here, the system check can be followed by the user. The software
establishes the communication with all connected devices, namely the pH sensor, oxygen
sensor, temperature sensor, pressure sensor, peristaltic pumps and the gas mixing device.
Successful establishment of the connections is visualized by green indicators and for the pH
and oxygen sensors by displaying system status reports from the connected hardware (see
Figure 15A). In case the connection cannot be established, the software flashes red
indicators, and offers the possibility to change the communication (COM) port settings, as
demonstrated in Figure 15A for the oxygen sensor. The setup tab also includes the functions
for calibrating the pH, oxygen and pressure sensors. Oxygen and pH sensors are disposables
and each new batch of sensors requires updating of the calibration with the calibration data
provided by the supplier. For the calibration of the pressure sensor, the user is requested to
apply five defined pressures to the sensor and the software records the resulting voltage
signals from the sensor, calculates a regression line and saves these calibration data in a
calibration file. The user can set the path to the directory where the calibration file is saved.
Once the system check is complete the user can change to the measurement tab and start the
measurement by pressing the start button (Figure 15B). By ticking the according boxes, the
user can choose which parameters will be measured and saved. Moreover, the intervals in
which pressure and pH are measured can be set independently. The pH does not fluctuate in
a matter of seconds like the pressure. Therefore, it is not necessary to measure the pH in the
same interval as the pressure. Furthermore, the pH measurement works with an optical
sensor that drifts if too often illuminated. The measured values are displayed numerically
and graphically. The measurement tab also contains the control interface. The user can
decide between manual and automatic control of pressure and pH. In the manual control
mode, the user directly adjusts the control variables (CV) pump speed or CO2 percentage
and total gas flow. In the automatic control mode, the user defines setpoints for the process
variables (PV) pressure and pH, and the system adjust the control variables accordingly. All
variables, settings and measurement data are saved in an excel file. Additionally, the
software allows to write comments into that file, e.g. “medium change”. Errors in the soft-
and hardware are displayed. The software can be stopped immediately by a button or after a
given time by a timer.
Results
54
Figure 15: User interface of the control software for the perfusion bioreactor. (A) After starting the
software, the Setup-tab opens. The system runs through an initializing procedure. The user can adjust COM
ports and file paths and calibrate the sensors. A successful system check is indicated by green indicators and
appearing reports. (B) The measurement can be started on the Measure-tab. The user can choose if pH, oxygen,
pressure and temperature will be measured and at which interval. These data are displayed in the charts on the
right side that additionally also display the data for pump speed and CO2. All data are also saved as excel
sheets. In the control area the user can set the perfusion speed manually or set a pressure setpoint in the
automatic control tab. The gas composition for the membrane oxygenator can also be set manually, or
automatically by defining a pH setpoint. System errors are displayed, and the software can be stopped manually
or by a timer after a given time.
Results
55
The software was written in LabVIEW. The code was structured as a queued state machine.
A state machine is optimal for preprogrammed sequential processes but fails when user input
is required. A producer consumer architecture on the other hand is the adequate structure for
handling user interface events but fails at preprogrammed sequential tasks. The queued state
machine combines these two architectures. It follows preprogrammed sequences like a state
machine, but user inputs can interrupt the state machine at any time and insert more
important tasks into the workflow. The workflow is managed by a queue. Tasks can be added
to the front or end of the queue, depending on their importance.
The perfusion bioreactor control software runs two sequential processes in parallel. One
producer loop feeds the queues of two consumer loops that work as independent state
machines. Consumer loop 1 handles the pump and pressure control. Consumer loop 2
handles the gas and pH control. Implementing the process in two consumer loops enables
the pH and pressure measurement at different intervals, as described earlier.
Figure 16: Architecture of the control software for the perfusion bioreactor. The software is programmed
as a queued state machine. Two producer consumer structures run in parallel. Consumer loop 1 handles the
pump and pressure control. Consumer loop 2 handles the gas and pH control. (A) Initialization sequence. After
software start, an initializing sequence is started in which 5 states that initialize and check the system are
executed. Thereafter, the software is ready to start the measurement. (B) Measurement sequence. The
parameters pressure, temperature, pump speed, pH, O2 and oxygenation gas composition are read, according
to the user’s selection. The data handling state saves and plots the data and hands them to the control state in
which either the automated controller or manual control settings are executed. A new measurement cycle is
started after the interval has elapsed. (C) Additional states that are solely activated by user input. * indicates
states that can be called independently.
Results
56
After software start, the state machine enters the initializing state that establishes the
connection between the hardware and the control software via the VISA and DAQmx
functions of LabVIEW, resets variables, and creates the excel sheet for saving the measured
data. The initializing state directly calls the check system state that then calls the check
pressure, temperature and pump or the check pH, O2 and GasMix states, depending on the
consumer loop. These states test the connection to these hardware components by reading
out data. No further state is executed automatically thereafter (Figure 16A).
A user input, pressing the start button, is necessary to start the preprogrammed measurement
process (Figure 16B). The read state is executed first. It calls read temperature, pressure and
pump speed, or read pH, O2 and GasMix data, depending on the consumer loop and the
user’s selection. Thereafter, the data handling states are executed. Data are bundled, saved
in excel sheets and displayed on the user interface. Subsequently, the control states are
called. The pump and gas mixing device can either be controlled manually or the software
determines the error between the process variable and setpoint and adjusts the control
variable automatically (Table 24). Next, the software enters the wait state and pauses until
the set interval has elapsed. Then the measurement process is started from the beginning.
Using the advantage of the queued state machine, states that are part of the state machine
and additional states can be called independently from the preprogrammed measurement
process (Figure 16C). For example, the shutdown state can be called anytime to stop the
software.
Results
57
4.1.3 Tuning the controllers of the perfusion bioreactor
4.1.3.1 Tuning of the pressure controller
Pressure control in the perfusion bioreactor works via pump speed regulation. The de- or
recellularization processes are subject to the impact of disturbances, for example a clogged
vessel in the kidney, or an accidentally closed valve in the perfusion bioreactor. Therefore,
the process pressure has to be constantly compared to the pressure setpoint. In case of a
deviation, the resulting control error (E) is translated by the controller into a control variable
change. The pump speed is adjusted until the pressure setpoint is met (Figure 17).
Figure 17: Block diagram of the pressure feedback loop. The process variable (PV), the actual pressure in
the system, is compared with the pressure setpoint (SP). The control error (E) is used by the controller to adjust
the control variable (CV), the pump speed. The process, the perfusion bioreactor, reacts to the new pump speed
and the resulting pressure is again sent as a feedback to the controller. Disturbances (D) can influence the
pressure and have to be compensated by an appropriate controller reaction.
To ensure an accurate reaction of the controller, the controller had to be specifically tuned
for this process. First, the process was characterized by recording a step response. The CV
pump speed was changed, and the response of the PV pressure was recorded. Since
decellularized kidneys are a biological material that naturally shows high variability, the step
response was recorded for three kidneys. Figure 18 shows that every kidney reacted
differently to the pump speed change. All three step responses classified the process as a
first-order system (PT1 element). That means the pressure reacts to the pump speed change
without any dead time, but the process variable reaches the new steady state with a delay.
The speed of the PV change reaches its maximum right after CV change and decreases
thereafter. PT1 elements are characterized by two parameters, the time constant T and the
proportional action coefficient Ks.
Results
58
-0.05 0.00 0.05 0.10 0.15 0.20
0
10
20
30
40
50
60
70
80
0
10
20
30
40
50
T=0,025 min
∆CV=35 rpm ∆PV=44,3 mmHg
time [min]
Pressure [mmHg]
pump speed [rpm]
-0.05 0.00 0.05 0.10 0.15 0.20
0
10
20
30
40
50
60
70
80
0
10
20
30
40
50
T=0,015 min
∆CV=35 rpm
∆PV=35,8 mmHg
time [min]
Pressure [mmHg]
pump speed [rpm]
-0.1 0.0 0.1 0.2 0.3 0.4 0.5
0
5
10
15
20
4
5
6
7
8
9
10
11
T=0,170 min
∆CV=10 rpm ∆PV=10,0 mmHg
time [min]
Pressure [mmHg]
pump speed [rpm]
pressure
pump speed
A
B
C
Figure 18: Step response to pump speed change. The control variable pump speed (CV) was changed while
the response of the process variable pressure (PV) was recorded for three different kidneys (A,B,C). The step
response categorized the system as a PT1 element. The time constant and proportional action coefficient varied
for every kidney.
The intersection of the tangent at the steepest part of the PV curve and the final PV value
defines the process time constant. The time constant is a measure for the speed in which the
process reacts to the CV change. Every tested kidney reacted with a characteristic time
constant T:
𝑻𝑻𝑨𝑨=𝟎𝟎,𝟏𝟏𝟏𝟏𝟎𝟎 𝒎𝒎𝒎𝒎𝒎𝒎 𝑻𝑻𝑩𝑩=𝟎𝟎,𝟎𝟎𝟎𝟎𝟎𝟎 𝒎𝒎𝒎𝒎𝒎𝒎 𝑻𝑻𝑪𝑪=𝟎𝟎,𝟎𝟎𝟏𝟏𝟎𝟎 𝒎𝒎𝒎𝒎𝒎𝒎
Results
59
The proportional action coefficient Ks describes the correlation of PV change after CV
change. Again, all three tested kidneys reacted to the CV change with a different Ks:
𝐾𝐾𝑠𝑠𝑠𝑠 =∆𝑃𝑃𝑃𝑃
𝑠𝑠
∆𝐶𝐶𝑃𝑃
𝑠𝑠
=10,0 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
5,0 𝑟𝑟𝑟𝑟𝑚𝑚 = 2,0 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
𝑟𝑟𝑟𝑟𝑚𝑚
𝐾𝐾𝑠𝑠𝑠𝑠 =∆𝑃𝑃𝑃𝑃𝑠𝑠
∆𝐶𝐶𝑃𝑃𝑠𝑠
=44,3 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
35,0 𝑟𝑟𝑟𝑟𝑚𝑚 = 1,3 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
𝑟𝑟𝑟𝑟𝑚𝑚
𝐾𝐾𝑠𝑠𝑠𝑠 =∆𝑃𝑃𝑃𝑃𝑠𝑠
∆𝐶𝐶𝑃𝑃𝑠𝑠
=35,8 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
35,0 𝑟𝑟𝑟𝑟𝑚𝑚 = 1,0 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
𝑟𝑟𝑟𝑟𝑚𝑚
Since T and Ks were different for every tested kidney, the perfect controller tuning would
require the identification of T and Ks for every kidney placed inside the bioreactor. As this
is not feasible, a compromise had to me made and universally working tuning parameters
had to be identified. Therefore, the mean time constant and the mean proportional action
coefficient of the three step responses were calculated:
𝐾𝐾𝑠𝑠
�
�
�
= 1,4 𝑚𝑚𝑚𝑚𝑚𝑚𝑚𝑚
𝑟𝑟𝑟𝑟𝑚𝑚 and 𝑇𝑇
�= 0,070 𝑚𝑚𝑚𝑚𝑚𝑚
These two process characteristic parameters are the basis for the identification of the
controller tuning parameters. The PID controller is the most widely used control algorithm.
It is defined by three main control effects. The proportional action, P, changes the CV
proportional to the control error. The integral action, I, changes the CV proportional to the
integrated control error and is applied to eliminate the control offset. Lastly, the derivative
action, D, changes the CV proportional to the derivative of the control error. D speeds up
the response but is less commonly used. The PID controller output is the sum of these three
terms. The corresponding adjustable PID tuning parameters are the proportional gain Kp, the
integral time Ti and the derivative time Td146. The process characteristic parameters Ks and
T were translated into the controller tuning parameters Kp, Ti and Td by applying the T-sum
tuning rule, also called KUHN tuning method147, which is displayed in Table 25.
Table 25: Tuning methods used for adjusting the pressure and pH controller147
Controller
𝑲𝑲
𝒑𝒑
𝑻𝑻
𝒎𝒎
𝑻𝑻
𝒅𝒅
PID KUHN 2
𝐾𝐾𝑠𝑠
0,8𝑇𝑇 0,194𝑇𝑇
PI KUHN 1
𝐾𝐾𝑠𝑠
0,7𝑇𝑇
Results
60
The tuning parameters for the PID controller are:
𝐾𝐾𝑟𝑟= 1,4 𝑇𝑇𝑖𝑖= 0,056 𝑇𝑇𝑑𝑑= 0,014
The tuning parameters for the PI controller are:
𝐾𝐾𝑟𝑟= 0,7 𝑇𝑇𝑖𝑖= 0,049
Additionally, a setting for a slow PI controller was selected manually:
𝐾𝐾𝑟𝑟= 0,05 𝑇𝑇𝑖𝑖= 0,05
012345678910 11 12 13 14 15 16 17 18 19 20 21 22
0
20
40
60
80
100
120
time [min]
pump speed [rpm]
0
20
40
60
pressure [mmHg]
PI KUHNPID KUHNPI manual slow
A
T
s
T
s
T
s
PI Manual PID KUHN PI KUHN
0
10
20
30
40
Pump speed deviation [rpm]
PI Manual PID KUHN PI KUHN
0
2
4
6
8
Pressure deviation [mmHg]
PI Manual PID KUHN PI KUHN
0.0
0.2
0.4
0.6
0.8
1.0
1
2
3
4
5
Control settling time [min]
C DB
Figure 19: Reference-variable response of the control system. (A) The reaction to a pressure setpoint change
of a manually tuned, slow PI, PI KUHN and PID KUHN controller were recorded. The manually tuned
controller reacts slow but stable, the system is overdamped. The PID controller reacts very fast but leads to
high deviations in pump speed and pressure, the system is underdamped. The PI KUHN controller reacts fast
and results in a stable process, the system is critically damped. (B) The control settling time, (C) the average
absolute deviation from the mean pump speed and (D) the average absolute deviation from the mean pressure
were identified from the responses.
Results
61
These controller settings were tested in a reference-variable response. The pressure setpoint
was changed from 10 to 30 mmHg. The pump speed change by the controller and the
response of the process pressure were recorded (Figure 19A). The control settling time Ts
describes the time required by the controller to adjust the PV to the new setpoint. The higher
the tuning parameters are, the faster reacts the controller. The PID KUHN controller
therefore has the shortest Ts with 0,2 min. The PI KUHN controller requires 0,3 min, only
slightly longer. The manually tuned PI controller needs nearly 4 min (Figure 19B). However,
the PID controller constantly changes the pump speed in a very wide range, whereas the
manual PI and the PI KUHN controllers have way less fluctuation in the CV. Therefore, the
absolute deviation from the mean pump speed is much higher in the PID controller (Figure
19C). Hence, the pressure oscillates much more around the setpoint in the PID controlled
system (Figure 19D). The manual PI controller results in an overdamped system and the
PID KUHN controller in an underdamped system. The PI KUHN controller results in a
critically damped system, it is fast and stable. Therefore, this is the preferred controller
tuning for stable yet fast pressure control.
Next, the PI KUHN tuned system was tested on how it reacts to a disturbance. Therefore,
the valve that is used as the seeding port was closed to simulate a clogged vessel (Figure 20).
The pressure in the system rises immediately from 20 to 100 mmHg. The PI controller
required only 0,6 s to stop the pump completely. This reaction will prevent damage to the
recellularized kidney due to too high perfusion pressures. When the valve was reopened the
pressure was released and the pump started again.
In conclusion, the PI KUHN controller handles the pressure control satisfactory.
valve closed
0,6 s
0 2 4 6 8 10 12 14 16 18 20 22 24
0
20
40
60
80
100
120
140
160
180
0
10
20
30
40
50
pressure setpoint
pressure measured
pump speed
valve reopened
time [s]
Pressure [mmHg]
pump speed [rpm]
Figure 20: Disturbance response of the pressure control system. The PI KUHN controller stops the pump
0,6 s after the pressure rises due to a closed valve in the perfusion bioreactor.
Results
62
4.1.3.2 Tuning of the pH controller
The pH is a critical factor for cell culture. A physiological pH of 7,4 has to be maintained in
the cell culture medium for optimal cell viabilty. In most cell culture media a bicarbonate
buffer system permits the control of the pH by adjusting the CO2 concentration in the
medium. However, fixing the CO2 contentration at 5%, as it is applied in standard cell culture
incubators, cannot compensate for any disturbances, such as lactic acid that is secreted by
viable cells and lowers the pH of the cell culture medium. To stablilze the pH at a constant
physiological level during the recellularization culture, a pH controller was implemented.
The percentage of CO2 used for gassing the medium is the control variable of this process
control system (Figure 21).
Figure 21: Block diagram of the pH feedback loop. The process variable (PV), the actual pH in the system,
is compared with the pH setpoint (SP). The control error (E) is used by the controller to adjust the control
variable (CV), the CO2 content in the gas that flows through the membrane oxygenator. The process, the
perfusion bioreactor, reacts to the new CO2 content and the resulting pH is again sent as a feedback to the
controller. Thereby pH disturbances (D) can be compensated.
To identify the optimal controller setting, the process was characterized by a step response
first (Figure 22). Therefore, the CO2 percentage in the gas mixture that flows through the
oxygenator was changed from 0 to 10%, and the change of the pH was recorded. The pH
decreased by 0,61 with increasing CO2 concentration. The step response characterized the
process as a second-order system (PT2 element). PT2 elements are defined by a delayed
reaction of the PV to the CV change. In contrast to PT1 elements the speed of the PV change
is not highest immediately after the CV change. Instead it rises slowly, reaches the maximum
in an inflection point and declines until the PV reaches its new steady state. The intersection
of the tangent at the inflection point and the starting PV value defines the process dead time
Tu=8,9 min. The intersection of the tangent at the inflection point and the final PV value
defines the process time constant Tg=8,6 min. The tangent at the inflection point simplifies
the process to a PT0T1 element, a PT1 element with dead time.
Results
63
-10 010 20 30 40 50 60 70 80
6.7
6.8
6.9
7.0
7.1
7.2
7.3
7.4
7.5
7.6
7.7
0
1
2
3
4
5
6
7
8
9
10
11
pH measured
CO
2
T
u
T
g
∆CV ∆PV=-0,61
T
u
=8,9 min
T
g
=8,6 min
time [min]
pH
CO
2
[%]
Figure 22: Step response to CO2 change. The control variable CO2 [%] (CV) was set from 0 to 10% while
recording the response of the process variable pH (PV). The step response categorized the system as a PT2
element.
The controllability of a PT2 process is defined by the ratio:
𝑇𝑇
𝑚𝑚
𝑇𝑇𝑢𝑢
=8,6 𝑚𝑚𝑚𝑚𝑚𝑚
8,9 𝑚𝑚𝑚𝑚𝑚𝑚 = 0,96
Ratios smaller than 3 define systems that are hard to control due to the high dead time. Ratios
higher than 10 define systems with a good controllability. The pH in the perfusion bioreactor
is therefore a process variable that is difficult to control.
The time constant of the system is the sum:
𝑇𝑇=𝑇𝑇𝑢𝑢+𝑇𝑇
𝑚𝑚=17,5 𝑚𝑚𝑚𝑚𝑚𝑚
The proportional action coefficient of the controlled system results from:
𝐾𝐾𝑆𝑆=∆𝑃𝑃𝑃𝑃
∆𝐶𝐶𝑃𝑃 =6,88 −7,49
10,0% −0,0 % = −0,06
% 𝐶𝐶𝐶𝐶2
�
By applying the tuning rules of KUHN, which are displayed in Table 25, the resulting tuning
parameters for the PID controller are:
𝐾𝐾𝑃𝑃=−32,8 𝑇𝑇𝑖𝑖=14,0 𝑇𝑇𝑑𝑑= 3,4
The tuning parameters for the PI controller are:
𝐾𝐾𝑃𝑃= −16,4 𝑇𝑇𝑖𝑖=12,3
Results
64
Both settings were tested in the perfusion bioreactor in a reference-variable response, as
shown in Figure 23. The pH setpoint was changed from 7,4 to 7,2 and back and the responses
of the CV and PV were recorded. The PI controller reacted fast and adjusted the CV without
much fluctuation. The setpoint was reached without PV offset or oscillation. However, due
to its poor controllability the new setpoint was only met after 74 min. The PID algorithm
was 7 min faster than the PI algorithm and the PV reached the new setpoint without any
constant offset. However, the CV was fluctuating more, and the PV oscillated around the
setpoint. Therefore, the PID settings did not control the pH stably. Hence, the PI algorithm
is more suitable for pH control in the perfusion bioreactor.
7.2
7.3
7.4
T
s
T
s
pH
7.2
7.3
7.4
T
s
T
s
pH
0 60 120 180 240
0
2
4
6
8
10
12
time [min]
CO
2
[%]
0 60 120 180 240
0
2
4
6
8
10
12
time [min]
CO2 [%]
PI KUHNPID KUHN
pH setpoint
pH measured
CO2
PID KUHN PI KUHN
0
20
40
60
80
100
Control settling time [min]
AB
Figure 23: Reference-variable response of the pH control system. (A) The reference-variable response to a
setpoint change was recorded for PI and PID controllers tuned by the KUHN method. Both controllers adjusted
the PV to the new setpoint, but the PID controller showed a higher fluctuation in the CV and the PV oscillated
around the setpoint; whereas the PI algorithm controlled the pH more stably. (B) The PID controller achieved
a shorter control settling time.
Next, the tuned PI controller was tested for its reaction to a disturbance in the process. Here
a change in the pH was provoked by adding 300 mg citrate or NaOH into the medium of the
bioreactor. Citrate reduced the pH to 7,23. The system required 55 min to restore the pH to
the setpoint of 7,30. Although an overshoot was not observed in any of the reference-variable
responses, here a small overshoot had to be compensated. The system reached the pH
setpoint after a further 73 min. NaOH increased the pH to 7,58. The controller restored the
pH to 7,40 after 59 min. However, the overshoot was bigger than in the citrate disturbance
and the system needed 102 min more to fully compensate the disturbance (Figure 24). The
Results
65
overshoot was most likely generated by a longer dead time than in the step and
reference-variable responses. In these experiments the dead time was shorter because only
the time that the medium needed to be pumped from the membrane oxygenator to the pH
sensor influenced the dead time. Here, the time that the medium needed from the bioreactor
to the membrane oxygenator is added to the total dead time. Therefore, the pH controller
calculated with a lower integral time Ti, than required, leading to higher integral action and
a too rapid controller reaction in the disturbance response. This proves again the bad
controllability of this process. By increasing Ti the overshoot could be decreased. However,
metabolite secretion during perfusion culture only changes the pH gradually, not as fast and
profound as it was provoked in the disturbance response. Additionally, variing pump speeds
during the perfusion culture also influence the pH control. Due to these possible variations
and the bad controllability no perfect tuning parameters for the pH controller will be
identified. Nevertheless, the identified parameters are satisfactory for most scenarios.
060 120 180
7.2
7.3
7.4
7.5
7.6
0
2
4
6
8
10
NaOH Bolus
59 min 102 min
16 min
time [min]
pH
CO
2
[%]
060 120 180
7.20
7.22
7.24
7.26
7.28
7.30
7.32
0
2
4
6
8
10
Citrate Bolus
55 min 73 min
14 min
time [min]
pH
CO
2
[%]
A
B
pH setpoint pH measured CO
2
Figure 24: Disturbance response of the pH control system. (A) 300 mg citrate or (B) NaOH were added to
50 ml cell culture medium in the bioreactor. The response of the pH control system was recorded. Both
disturbances provoke an overshoot. The pH is fully restored to the setpoint after 2 to 3 h.
Results
66
4.2 Identification of an optimal decellularization strategy for
kidney tissue using factor screening in an immersion and
agitation setting
Decellularization is a procedure in which cells of an organ or tissue are removed while the
ECM remains. This is achieved by chemical and physical treatments that lyse the cells and
solubilize and remove cell debris. In a process called recellularization the decellularized
tissue is used as a scaffold and reseeded with cells. To achieve a successful recellularization
the scaffold has to be of high quality. Ideally, the cellular material should be removed
completely, and the ECM should stay in its native state. Therefore, the identification of a
decellularization protocol that balances these two criteria is of utmost importance.
Decellularization of tissue cubes by immersion and agitation offers the opportunity to test
many different protocols in parallel in a factor screening approach.
Here, cubes from porcine kidneys were treated by immersion and agitation in different
detergents, namely 1% SDC, 1% SDS or 1% TX-100, and at different temperatures, either
4 °C, RT (22-24 °C) or 37 °C, to investigate which decellularization strategy produces
scaffolds in top quality for recellularization. It was hypothesized that less harsh detergents
and lower temperatures would better preserve the ECM. To that end, cell removal, ECM
composition and biocompatibility were investigated after decellularization (Figure 25).
Figure 25: The experimental process of the de- and recellularization of porcine kidneys by immersion
and agitation. Porcine kidney cubes were decellularized by immersion and agitation in SDC, SDS or TX-100
at 4 °C, RT or 37 °C. Sections of the decellularized cubes were recellularized with hiPSC-derived intermediate
mesoderm cells (IMCs) under static culture conditions to investigate the scaffold’s biocompatibility.
Results
67
4.2.1 Analysis of histology and composition after decellularization by
immersion and agitation
Upon decellularization the macroscopic appearance of the kidney cubes changed from brown
to milky yellow and finally to white and transparent indicating the increasing cell removal.
Differences in the decellularization efficacy were reproducibly observed between the
different temperatures and detergents.
SDC treated tissues became most transparent at 4 °C (Figure 26), and remained milky at RT
and 37 °C. Hematoxylin and eosin (HE) staining of paraffin sections confirmed that the most
effective, although still incomplete, removal of cell components was achieved at 4 °C, while
RT and 37 °C samples showed substantial amounts of cellular residues, especially in the
core of the immersed tissue cube. Thus, SDC poorly penetrates the center of the cubes. DAPI
staining, which labels double stranded DNA (dsDNA), confirmed the absence of intact
nuclear structures, but cellular debris and parts of the scaffold were stained with DAPI,
especially in the 4°C and RT samples. Thus, dsDNA fragments are still present in the debris
or adhere to the ECM. Interestingly, the intensity of the DAPI stain does not correlate with
the remaining cellular material. Although there is more cellular material left in the 37 °C
samples, less DAPI staining is detected than in the 4 °C sample. Immunofluorescence
staining of the ECM components laminin, collagen IV and fibronectin showed their
preservation at all temperatures. Compared to native tissue, merely tubular laminin is
reduced, whereas it is preserved in the glomeruli.
Kidney tissue treated with SDS shrank about 10% - 20% in volume. 4 °C and RT samples
appeared translucent, whereas the 37 °C samples were still yellow after decellularization
(Figure 27). HE staining proved the complete decellularization of 4 °C and RT samples, but
only the 4 °C sample had a well-preserved architecture, whereas the RT sample showed
zones of collapsed glomeruli and tubules. Histology confirmed also the incomplete
decellularization of the 37 °C sample as they contained cellular debris, which was also
confirmed by DAPI staining. Comparable to the SDC samples, and all stained ECM proteins
were well preserved apart from tubular laminins. The nephron architecture was not impaired.
After decellularization with TX-100, all treated tissue cubes appeared macroscopically
yellow/whitish regardless of the applied temperature (Figure 28). HE and DAPI staining
revealed intact nuclei throughout the cube, especially in the 37 °C sample. Cytoplasmic
components were only marginally reduced in comparison to native tissue. The architecture
and ECM proteins laminin, collagen IV and fibronectin are undamaged, as shown by
Results
68
immunofluorescent analysis. Therefore, TX-100 alone is not able to break up the majority
of cells and to separate them from the ECM.
In summary, SDS at 4 °C performed best regarding cell and dsDNA removal. SDC at 4 °C
also clears the tissue of most of the cellular material, however, zones exist where cellular
debris and dsDNA are still present. Therefore, a DNase digest was added after detergent
treatment. TX-100 insufficiently decellularized the kidney tissue.
Figure 26: Macroscopic and histological analysis of native and SDC-decellularized porcine kidney cubes
at 4 °C, RT and 37 °C. Native porcine kidneys appeared brown. Native vessels, tubules and glomeruli are
filled with epithelial and endothelial cells, as shown by HE and DAPI staining. The ECM molecules laminin,
collagen IV and fibronectin were detected in the ECM lining the tubules and blood vessels. SDC at 4 °C gave
the best results. At RT and 37 °C, SDC showed poor penetration into the center of the cubes, which were not
completely decellularized. DAPI-stained dsDNA was detected in zones filled with cellular debris and on the
ECM. Only laminin staining was reduced in the tubules. The architecture was preserved. Scale bar: 50 μm.
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69
Figure 27: Macroscopic and histological analysis of SDS-decellularized porcine kidney cubes at 4 °C, RT
and 37 °C. SDS-decellularization at 4 °C and RT resulted in translucent tissue. The cubes shrank during
decellularization. Neither HE-stained cell debris, nor DAPI-stained dsDNA was detected. At RT, wide areas
of the architecture were collapsed. Decellularization at 37 °C was incomplete, since dsDNA and cellular
material were detected. Only laminin staining was reduced in the tubules. Scale bar: 50 μm.
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70
Figure 28: Macroscopic and histological analysis of TX-100-decellularized porcine kidney cubes at 4 °C,
RT and 37 °C. No decellularization condition using TX-100 yielded in fully decellularized scaffolds. The
higher the applied temperature the more cellular debris remained, corroborated by strong DAPI signals. Tissue
cubes therefore appeared milky white. Scale bar: 50 μm.
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71
To further quantify the maintenance of critical ECM components after decellularization,
total collagen, GAG, VEGF and bFGF were quantified (Figure 29). In addition, remaining
DNA was analyzed, as an indicator for cell removal. The TX-100 group was omitted from
these analyses as the histological analysis already revealed poor decellularization and DNA
removal (Figure 28). All amounts were normalized to the dry weight after decellularization.
Quantification of total DNA after DNase treatment in the SDC and SDS groups showed that
DNA was efficiently removed from the tissue in all conditions (Figure 29A), even in the
SDC 4 °C samples that showed residual DNA in the DAPI stain before DNase treatment.
The highest collagen/ dry weight ratios were measured after decellularization for both
detergents at 4 °C, whereas the lowest ratios were measured in the 37 °C samples. Generally,
higher collagen/ dry weight ratios were measured in SDS treated samples than in SDC
treated samples when comparing the individual temperatures, although these differences are
not significant. Therefore, the samples with poorer removal of cellular material retained
more non-collagenous structural and cytoplasmic components (Figure 29A, D, E). This
resulted in a lower relative amount of collagen per total mass, even if the absolute amount
might be similar.
In contrast to collagens, GAG maintenance in decellularized tissues was not influenced by
the temperature, hence there was no correlation between decellularization efficacy and GAG
levels (Figure 29C). Strikingly, there was a significantly lower ratio of GAG in SDC-
decellularized samples than in SDS-decellularized samples, indicating a profound loss of
GAGs during decellularization with SDC, or a superior maintenance of GAGs in SDS-
decellularized matrix.
SDC-decellularized samples contained more VEGF and bFGF than SDS-decellularized
samples (Figure 29D, E), although both these cytokines have a strong binding affinity to
GAG chains in proteoglycans. Therefore, the data suggest that SDC treatment removed more
GAG from the ECM but dissociated less GAG-bound cytokines compared to SDS.
Next to the composition, the stiffness is an important property of the ECM. The elastic
modulus of native glomeruli and SDC- and SDS-decellularized glomeruli was determined
using atomic force microscopy. The native glomeruli and the SDC-decellularized glomeruli
showed a comparable E modulus of approximately 0,5 kPa. Whereas SDS-decellularized
glomeruli were stiffer, having an E modulus of 2 kPa. For the comparison it has to be
considered, that the samples of native kidney tissue contain cells and had to be frozen for
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72
sample preparation, therefore the E modulus of the native ECM alone could not be measured
(Figure 29F).
In summary, DNA was removed efficiently after DNase treatment. Decellularization with
SDS at 4 °C yielded the highest collagen/dry weight ratio and second highest GAG/dry
weight ratio, whereas preservation of VEGF and bFGF was superior in SDC at 4 °C.
Collagen
Native
SDC 4 °C
SDC RT
SDC 37 °C
SDS 4 °C
SDS RT
SDS 37 °C
0
100
200
300
400
500 *
Collagen/dry weight [µg/mg]
GAG
Native
SDC 4 °C
SDC RT
SDC 37 °C
SDS 4 °C
SDS RT
SDS 37 °C
0
10
20
30
40
50 *
GAG/dry weight [µg/mg]
A CB
VEGF
Native
SDC 4 °C
SDC RT
SDC 37 °C
SDS 4 °C
SDS RT
SDS 37 °C
0
20
40
60
80 *
VEGF/dry weight [pg/mg]
bFGF
Native
SDC 4 °C
SDC RT
SDC 37 °C
SDS 4 °C
SDS RT
SDS 37 °C
0
10
20
250
300
bFGF/dry weight [pg/mg]
D E Elastic modulus
Native
SDC 4 °C
SDS 4 °C
0.0
0.5
1.0
1.5
2.0
2.5
*
E [kPa]
F
DNA
Native
SDC 4 °C
SDC RT
SDC 37 °C
SDS 4 °C
SDS RT
SDS 37 °C
0
10
20
30
40
*
*
*
*
DNA/dry weight [µg/mg]
Figure 29: Composition analysis of immersion-decellularized matrices. Quantitative analysis of (A) DNA,
(B) total collagen, (C) GAG, (D) VEGF and (E) bFGF content after decellularization by immersion of porcine
kidney fragments using the indicated conditions. The specific amounts are given as the ratio of the target
substance (in μg or pg) to the dry weight of the sample after decellularization (mg). (F) Atomic force
microscopy was used to determine the elastic modulus E of native and decellularized kidney matrix. Values
are expressed as mean± SEM, * indicates a significant difference in means, p<0.05.
4.2.2 Biocompatibility testing of immersion-decellularized kidney tissue by
recellularization with intermediate mesoderm cells
Human iPSC-derived intermediate mesoderm cells (IMCs) were used to examine the
biocompatibilty of the most promissing immersion-decellularized ECM scaffolds.
Therefore, cell attachment and viability were analyzed. IMCs give rise to all renal cell
types89, and are therefore a realistic cell source for kidney recellularization.
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73
The hiPSC-derived IMCs were differentiated in 5,5 days from a constitutive GFP-expressing
hiPSC line. GFP expressing hiPSCs were chosen for easier visualization of the cells on the
scaffold. The differentiated cell population contained 62.5% LHX1 and 69% PAX2 positive
cells, indicative of efficient IMC generation (Figure 30).
Figure 30: Differentiation scheme of hiPSC-derived intermediate mesoderm cells. (A) Intermediate
mesoderm cells were differentiated from the constitutive GFP-expressing hiPSC line WISCi004-B (GFP+) in
a 5,5-day protocol. (B) Brightfield and fluorescence images show the morphology and GFP-expression of
IMCs. Scale bar: 100 μm (C) Expression of intermediate mesoderm markers LHX1and PAX2 was shown by
flow cytometry in 62% and 69% of the differentiated cells, respectively.
IMCs were seeded on renal ECM, mounted as 50 μm sections on POMA-coated glass
coverslips. The ECM was prepared by immersion-decellularization with SDC or SDS at
4 °C, as these conditions gave the best results in the analysis of histology and composition.
As controls, TX-100-ECM, glass coverslips and tissue culture treated polystyrene (TCPS)
were used.
The coverslips were scanned 30 and 76 h post seeding using the Operetta high content
screener. Represantative pictures are shown in Figure 31A. Attached cells were
morphologically enlarged and integrated into the scaffold, whereas non-attached cells
appeared small and round. Higher proportions of IMCs attached on the decellularized renal
ECM structures than on the glass or TCPS surfaces. Interestingly, more cells attached on
SDC- compared to SDS- or TX-100-treated ECM. These observed trends were quantified
with the Harmony High-content imaging software on the entire coverslip scan. The applied
image analysis sequence is depicted in Figure S1. The total cell number was set to 100% at
each time point. The quantification confirmed the higher attachment of cells over time on
renal ECM compared to glass or TCPS and the significantly higher attachment on SDC- than
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74
on SDS-decellularized ECM. The number of attached cells as a fraction of all cells increased
over time, hence the percentage of attached IMCs was highest at 76 h, indicating a survival
advantage of cells attached to ECM (Figure 31B). Additionally, the metabolic activity
measured in the resazurin assay confirmed the observation of the attachment data.
In summary, IMCs attached less effective and were less vital on TX-100-ECM, SDS-ECM,
glass or TCPS than on SDC-ECM.
Attachment
30h post seeding
SDC
SDS
TX-100
glass
TCPS
0
20
40
60
80
100
*
*
*
*
Attached cells [%]
Attachment
76h post seeding
SDC
SDS
TX-100
glass
TCPS
0
20
40
60
80
100
**
*
Attached cells [%]
Viability
24h - 48h post seeding
SDC
SDS
TX-100
glass
TCPS
0
20000
40000
60000
80000
100000
**
*
*
*
RFU
B C
Figure 31: Analysis of IMC viability and attachment on immersion-decellularized kidney sections. 3×105
iPSC-derived IMCs cm−2 were seeded on 50 μm thick SDS-, SDC- and TX-100-decellularized kidney sections,
glass cover slips or tissue culture polystyrene (TCPS). (A) GFP-positive cells were imaged at 30 and 76 h post
seeding. The cells attached best on SDC-ECM, indicated by a spread-out morphology; whereas cells attached
worse on SDS and TX-100-ECM, indicated by a small, round cell morphology. Laminin staining of
decellularized cover slips, performed at the end of the experiment, confirmed persistent maintenance of ECM
structures. Scale bar: 100 μm. (B) Attached and non-attached GFP-positive cells were counted at 30 and 76 h
post seeding and the total cell number was set to 100% at each time point. Quantification of attached cells was
performed using the Operetta high content screener. (C) Cumulative cell viability was determined using the
metabolic resazurin assay from 24 to 48 h post seeding. Values are given as relative fluorescence units (RFU).
* indicates a significant difference in means, p<0.05.
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75
4.2.3 A scoring system facilitates the comparison of immersion-
decellularization strategies
Selecting the most suitable decellularization approach from histology, quantification and
recellularization data is difficult, since for that purpose qualitative and quantitative results
have to be compared and condensed. Moreover, the comparison of the results of this study
to other decellularization studies is even more difficult.
Therefore, a scoring system was developed that allows an unbiased comparison of all
examined parameters and the calculation of a total score that can easily be compared. The
scoring system translates all quantitative results into values from 1 (worst result) to 4 (best
result). Moreover, the qualitative data, e.g. histological data, are translated into semi-
quantitative values by defining scores from 1 to 4. To minimize subjective errors, clearly
defined and whenever possible quantitative criteria are used to score preservation of
characteristic renal ECM structures and cell removal. The values of the best results were
derived from native tissue data. Overall, the three top level categories histology, ECM
composition and cell performance were defined that can contain one or more subcategories
of related analysis results. Subtotal scores were calculated for each subcategory by
calculating the mean of the individual scores. These subtotal scores allowed the application
of a weight function when calculating a total score and thus permit the adjustment of the
overall influence of individual categories. Higher weight was applied to all categories
containing quantitative data and to cell performance.
This scoring system was applied to compare the immersion-decellularization data after
DNase treatment. The ECM decellularized with 1% SDS at 4 °C achieved the highest scores
for histological and compositional maintenance, with scores of 3,67 and 3,19, respectively.
Whereas ECM decellularized with 1% SDC at 4 °C achieved the highest score for cell
viability and attachment, with a score of 3,33. Moreover, 1% SDC at 4 °C achieved the best
total score of 3,23, due to the higher weight for cell performance. Surprisingly, the cell
performance, considering IMC attachment and viability, did not correlate with collagen and
GAG ratios, which were lower in the SDC scaffold compared to the SDS scaffold. Nor did
it correlate with the remaining cytoplasmic material. Instead it did correlate with the cytokine
content.
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76
Table 26: Scoring table of immersion-decellularized porcine kidneys
4 °C RT 37 °C 4 °C RT 37 °C 4 °C RT 37 °C
Remaining cytoplasmic material
322442111
Absence of nuclear structures
444444221
Shrinking
344333444
subtotal
3,33 3,33 3,33 3,67 3,67 3,00 2,33 2,33 2,00 1
Tubules
323324434
Glomeruli
322424423
Vessels
444434444
subtotal
3,33 2,67 3,00 3,67 2,33 4,00 4,00 3,00 3,67 1
3,33 3,00 3,17 3,67 3,00 3,50 3,17 2,67 2,83
1
Laminin
222222223
CollagenIV
444444444
Fibronectin
444444444
subtotal
3,33 3,33 3,33 3,33 3,33 3,33 3,33 3,33 3,67 1
DNA content
444444
subtotal
4,00 4,00 4,00 4,00 4,00 4,00 2
Collagen content
332434
Glycosaminoglycan content
111443
subtotal
2,00 2,00 1,50 4,00 3,50 3,50 2
basic Fibroblast Growth Factor (bFGF)
111111
Vascular Endothelial Growth Factor (VEGF)
444211
subtotal
2,50 2,50 2,50 1,50 1,00 1,00 2
2,90 2,90 2,76 3,19 2,90 2,90
1
Cell attachment 30h
322
Cell attachment 76h
322
Cell viability
413
3,33 1,67 2,33
2
3,23 2,55
weight
Histology
Quantification
of absolute
composition
Condition/ Parameter
SDC
SDS
TX-100
General
appearance
Detailed
analysis of
specific
structures
Histology-Score
Composition
Matrix proteins
(histology
based)
Composition-Score
Cell pe rformance
Attachment and
viability
Cell pe rformance -Score
Total Score
Score s (1-4 points, highest score is best):
1234max value
Remaining cytoplasmic material cytoplasm intact
cytoplasm only
marginally
reduced
cytoplasm mainly
removed, only
fragments
no cytoplasm
remaining
Absence of nuclear structures
(Masson’s Trichrome + DAPI)
nuclei intact
few nuclei, high
amount of
released DNA
no nuclei, but
DNA detected
no nuclei, no
DNA detected
Shrinking strong medium low none
Tubules, Glomeruli, Vessels
not visible/
detectable
disrupted and/or
collapsed
architecture
moderate
disruption of
architecture
architecture
intact
Matrix proteins absent strongly reduced slightly reduced fully preserved
DNA content (µg/mg) 20,0 15,0 10,0 5,0 20,0
Collagen content (µg/mg) 97,8 195,5 293,3 391,0 391,0
Glycosaminoglycan content (µg/mg) 8,3 16,7 25,0 33,3 33,3
bFGF (pg/mg)
63,7 127,4 191,1 254,8 254,8
VEGF (pg/mg)
14,4 28,9 43,3 57,7 57,7
Cell attachment (%) 25,0 50,0 75,0 100,0 100,0
Cell viability (RFU)
16027,5 32055,0 48082,5 64110,0 64110,0
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4.3 Decellularization of kidneys by perfusion
Perfusion-decellularization allows the decellularization of whole organs. These scaffolds
provide a true 3D environment to reseeded cells. Moreover, they provide the organ-specific
architecture, ECM and mechanical stimuli, such as shear stress and stiffness. Perfusion-
decellularized rat kidneys were therefore chosen as a scaffold to generate the human 3D
kidney model.
The optimal decellularization parameters that were identified by the factor screening in the
immersion and agitation setting were now transferred to the perfusion setting. Perfusion-
decellularization was thus performed with 1% SDC, the decellularization agent that gave the
best results in immersion-decellularization of kidney tissue cubes, and a combination of
1% SDS and 1% TX-100, a protocol that was published before for perfusion-
decellularization of rat kidneys by Song et al.123. Both protocols were tested at 4 °C and RT.
Perfusion-decellularization was performed in the perfusion bioreactor developed in this
thesis, see 4.1. Cell removal and composition of the scaffold were investigated after
decellularization, analogous to the analysis of the immersion-decellularization. The
scaffold’s biocompatibility was investigated by reendothelialization of the vascular
compartment with human umbilical vein endothelial cells.
Figure 32: The experimental process of kidney decellularization by perfusion and biocompatibility
testing of the scaffold by reendothelialization. Rat kidneys were cannulated and placed into the perfusion
bioreactor. The kidneys were decellularized by perfusion with SDC or SDS/TX-100 at either 4°C or RT.
Human umbilical vein endothelial cells (HUVECs) were seeded into the vascular compartment of the scaffold
via the renal artery (RA) to investigate its biocompatibility. The reseeded kidneys were cultured under
perfusion conditions with pH, pressure and temperature control.
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78
4.3.1 Analysis of histology and composition after decellularization by
perfusion
The color of the kidneys lightened during decellularization, indicating the cell removal in
the tissue. The SDC-decellularized rat kidneys appeared macroscopically yellow, whereas
the SDS/TX-100-decellularized kidneys lost their color completely and appeared white and
translucent. No macroscopic pictures for the 4 °C samples are available (Figure 25).
HE staining of the native rat kidney revealed cell lined glomerular, tubular and vascular
structures and a high density of round, intact nuclei.
Figure 33: Macroscopic and histological analysis of native and perfusion-decellularized rat kidneys at
4 °C and RT. Native rat kidneys appeared brown. HE staining showed vessels, tubules and glomeruli filled
with epithelial and endothelial cells with intact nuclei, confirmed by DAPI staining. The ECM molecules
laminin, collagen I and IV and fibronectin were detected in the BM that line the tubules and glomerular
capillaries. SDC-decellularized kidneys appeared yellow. HE and DAPI showed remaining cellular material,
especially at 4°C. The architecture was intact. SDS/TX-100-decellularized kidneys appeared white. HE and
DAPI did not detect cellular residues. Tubules were collapsed. All decellularized samples stained positive for
the ECM molecules. Scale bar: 50 μm.
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79
Surprisingly and in contrast to the immersion data, the perfusion-decellularization with SDC
at 4 °C showed very poor cell removal. The scaffold remained filled with cellular debris,
although the cells and nuclei were not intact anymore, as shown by HE staining. DAPI
staining detected residual dsDNA in the cell debris.
Cell debris was also still present in the SDC RT scaffold, although not as abundant as in the
4 °C sample. DAPI staining did not detect any residual dsDNA. The architecture was not
negatively affected; all tubular, glomerular and vessel structures were intact.
In contrast, the decellularization with SDS/TX-100 at 4°C and RT removed all cellular debris
completely, therefore, no DAPI signal was detectable. However, the SDS/TX-100-treated
scaffolds showed an impairment of the architecture, as many tubules were collapsed.
The immunofluorescence staining of the ECM proteins laminin, collagen I, collagen IV and
fibronectin showed that these ECM proteins were well preserved in all decellularization
conditions with the exception of laminin in the SDC samples. In these samples the laminin
staining was instead detected in the cellular debris. This is either an unspecific staining or
an indication of a massive loss of laminin.
The composition of the decellularized kidney was further characterized by quantification of
DNA, total collagens and total glycosaminoglycans.
Quantification of DNA in the decellularized scaffolds revealed a significantly higher DNA
content in SDC 4 °C than in any other condition. Similarly, SDS/TX-100 4 °C showed
slightly elevated DNA levels in comparison to the RT samples. Since SDC RT contained
more cellular debris but less DNA/dry weight than SDS/TX-100 4 °C, the DNA content
correlated not only with the degree of decellularization but also with the temperature. So,
more cellular debris might have been flushed out, but the DNA did not degrade and stuck to
the ECM instead. A DNase digest after the SDC 4 °C treatment, like it was also performed
on all immersion samples, reduced the amount of DNA/dry weight significantly.
Comparable to the immersion data, a higher degree of decellularization led to an enrichment
of collagen and hence to a higher collagen/ dry weight ratio. Therefore, both SDS/TX-100
conditions showed a higher collagen/ dry weight ratio than the SDC-treated samples.
The GAG/dry weight ratio results from perfusion-decellularization are contrary to the
immersion data. In perfusion-decellularization, the SDC 4 °C sample did not contain the
lowest but the highest GAG/dry weight ratio. All other samples had a similar
GAG/dry weight ratio to the native sample, even the SDS samples that showed an elevated
Results
80
GAG/dry weight ratio in immersion-decellularization. Therefore, the GAGs were not
enriched like the collagens by the removal of cellular material but reduced as perfusion-
decellularization progressed.
In summary, SDS/TX-100 at RT showed the best results in removing the cellular material
and DNA. SDC was not able to remove the cellular material successfully in perfusion
conditions, contrary to the immersion-decellularization results.
DNA
Native
SDC 4 °C
SDC 4 °C DNase
SDC RT
SDS/TX-100 4/15 °C
SDS/TX-100 RT
0
5
10
15
20
25 *
DNA/dry weight [µg/mg]
Collagen
Native
SDC 4 °C
SDC RT
SDS/TX-100 4/15 °C
SDS/TX-100 RT
0
50
100
150
200
250 *
Collagen/dry weight [µg/mg]
GAG
Native
SDC 4 °C
SDC RT
SDS/TX-100 4/15 °C
SDS/TX-100 RT
0
10
20
30
40
50 *
GAG/dry weight [µg/mg]
A CB
Figure 34: Composition analysis of perfusion-decellularized matrices. Quantitative analysis of DNA (A),
total collagen (B) and GAG (C) content after decellularization by perfusion of whole rat kidneys using the
indicated conditions. The specific amounts are given as the ratio of the target substance (in μg or pg) to the dry
weight of the sample (mg). Values are expressed as mean± SEM, * indicates a significant difference in means,
p<0.05.
4.3.2 Biocompatibility testing of perfusion-decellularized kidneys by
reendothelialization with human umbilical vein endothelial cells
Human umbilical vein endothelial cells (HUVECs) were used to examine the qualification
of SDC RT and SDS/TX-100 RT perfusion-decellularized rat kidney scaffolds for
recellularization. HUVECs are primary endothelial cells that are therefore a suitable cell
source for reendothelialization of the vascular tree. Additonally, they are easily expandable
and robust.
Figure 35: Characterization of human
umbilical vein endothelial cells. (A)
Human umbilical vein endothelial cells
(HUVECs) exhibited
the typical
morphology with large nuclei. Scale bar:
200 μm. (B) Expression of the endothelial
markers CD31 and CD144 was shown by
flow cytometry.
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81
HUVECs were expanded until passage 7. These cells showed a uniform morphology and
72% were double positive for the endothelial cell markers CD31 and CD144 (Figure 35).
5x107 HUVECs were injected into the renal artery of an SDC RT-decellularized rat kidney
which was then placed inside the recellularization perfusion bioreactor (Figure 36A). After
a static overnight (O/N) attachment phase the perfusion was started (day 0) and continued
for 3 days. Culture medium samples were drawn regularly from the perfusion bioreactor
during the course of the experiment. Glucose consumption and lactate production rates were
highest at the first measurement after cell seeding. These rates decreased constantly during
the culture period, indicating a constant decrease of cellular activity. Additionally, the lactate
dehydrogenase (LDH) release, a marker for cell death, increased to 2,5 U/d after the static
overnight attachment phase, then rose to 4,1 U/d after the first 7 h of perfusion and decreased
thereafter. This indicated a massive cell loss in the first phase of the recellularization,
corroborating the glucose and lactate measurements (Figure 36E). The kidney appeared
brownish after the culture (Figure 36D). Histology showed that the cells were located in the
vascular compartment, but many cells clogged the vessels rather than lining them. Moreover,
many cell nuclei were fragmented and a DAPI signal could be observed throughout the
scaffold, which indicates free dsDNA that was released by dying cells (Figure 36B,C).
Figure 36: Reendothelialization of perfusion-decellularized kidneys by SDC at RT. (A) HUVECs were
injected into the renal artery (RA) of the SDC-decellularized rat kidney. Perfusion culture was started after an
overnight attachment period and then continued for 3 days. (B,C) DAPI stained cross-section after 3 days of
perfusion culture. Bright DAPI staining in the scaffold and the presence of fragmented nuclei indicated cell
death. Viable cells were present, but they did not line the vessels. (D) Picture of the fixed kidney after perfusion
culture. Brown discoloration indicated cellular material inside the kidney. (E) Glucose, lactate and LDH
consumption/production during the culture period. LDH values, a marker for cell death, increased rapidly after
perfusion start, and dropped after the first day of culture.
A B D
E
C
A
1 mm
100 µm
SDC RT
-1 0 1 2 3
-1
0
1
2
3
-2
-1
0
1
2
3
3
5
7
Glucose
Lactate
LDH
Day
Glucose, lactate [mmol/d]
LDH [U/d]
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82
The SDS/TX-100 RT-decellularized scaffold was also tested by recellularization with
HUVECs via the artery (Figure 37A). Histology showed a successful reendothelialization of
the vascular compartment. Many intact cell nuclei, detected by DAPI staining, lined the
vessels. Many more nuclei were detected than in the SDC scaffold. The resazurin assay
proofed high cell viability; the purple resazurin was metabolized to pink resorufin, staining
the kidney bright pink after the assay (Figure 37D). Moreover, the lower LDH release than
in the SDC reendothelialization, it only reached 2,0 U/d, confirmed the superior cell viability
in the SDS/TX-100-decellularized kidney scaffold (Figure 37E).
Figure 37: Reendothelialization of perfusion-decellularized kidneys by SDS/TX-100 at RT. (A) HUVECs
were injected into the renal artery (RA) of the SDS/TX-100-decellularized rat kidney. Perfusion culture was
started after an overnight attachment period and then continued for 3 days. (B,C) DAPI stained cross-section
after 3 days of perfusion culture. High numbers of HUVECs were spread over the whole tissue, lining
specifically bigger blood vessels and glomerular capillaries. (D) Viable cells reduced resazurin to the pink
resorufin, throughout the whole recellularized kidney. (E) Glucose, lactate and LDH consumption/production
during the culture period. Cells consumed glucose and produced lactate during the whole culture, although
with decreasing levels. LDH values, a marker for cell death, were highest after perfusion start, but did only
reach values of 2,0 U/d.
The cell number, metabolic activity and LDH release of the reseeded cells were quantified
to further facilitate the decision for the best scaffold. Counting the intact nuclei on DAPI
stained sections and normalization to 1 mm² revealed that SDS/TX-100 scaffolds hold 70%
more intact nuclei than SDC scaffolds. Moreover, the metabolic resazurin assay shows a
17 times higher metabolic activity in the SDS/TX-100 scaffold. The higher cumulative LDH
release in SDC scaffolds corroborates these data. Interestingly, this striking difference could
not be seen in the cumulative glucose consumption nor in the lactate production (Figure 38).
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83
Taken together, only the SDS/TX-100 RT scaffold was successfully reendothelialized by
HUVECS. It supported higher cell attachment and survival.
SDC
SDS/TX-100
0
20
40
60
Nuclei/mm²
SDC
SDS/TX-100
0
5000
10000
15000
RFU
A B C
SDC
SDS/TX-100
0
1
2
3
Glucose consumption [mmol]
SDC
SDS/TX-100
0
1
2
3
Lactate production [mmol]
SDC
SDS/TX-100
0
2
4
6
8
10
LDH [U]
ED
Figure 38: Comparative biocompatibility testing of perfusion-decellularized kidneys. Cell number and
metabolic activity were quantified to compare the biocompatibility of SDC- and SDS/TX-100-decellularized
rat kidneys. (A) More HUVEC nuclei were counted on DAPI stained sections of SDS/TX-100-decellularized
than on SDC-decellularized kidneys. (B) Resazurin assay results, given in relative fluorescence units (RFU),
quantify the metabolic activity of the reseeded cells. Cells reduced considerably less resazurin in SDC- than
cells in SDS/TX-100-decellularized kidneys. No significant differences in (C) cumulative glucose consumption
or (D) cumulative lactate production over 3 culture days. (E) HUVECs in SDC-decellularized kidneys had a
higher cumulative LDH release, a maker for cell death.
4.3.3 Applying the scoring system for the comparison of perfusion-
decellularization methods
4.3.3.1 Intra-study comparison
By applying the scoring system to the perfusion-decellularization data, the differences
between the protocols were easily uncovered and summarized.
The SDC-decellularized samples achieved higher histology scores than the SDS/TX-100
samples, although they contained more cellular debris, because they preserved the
architecture better. The SDC RT sample achieved the highest histology score with 3,83.
However, the highest composition score was achieved by the SDS/TX-100 samples with
3,60, whereas the SDC samples, especially the 4 °C sample, got lower composition scores
due to remaining DNA. Moreover, the SDS/TX-100 RT sample achieved with 4,00 a much
better cell performance score than the SDC RT sample. Contrary to the superior cell
performance of the SDC immersion samples.
In total, SDS/TX-100 RT achieved with 3,73 a clearly higher total score than SDC with a
total score of 2,74. The decellularization with SDS/TX-100 at RT and was therefore chosen
for the generation of the scaffold for the human kidney model.
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84
Table 27: Scoring table of perfusion-decellularized rat kidneys
4.3.3.2 Inter-study comparison
To compare the intra-study results to these of other published studies, three studies on kidney
decellularization were scored (Table 28). The published data were directly transferred into
the scoring table to avoid bias by third party assessment of these data.
In the study by He et al.148 SDS perfusion was applied to decellularize whole rat kidneys The
effect of different SDS concentrations (1%, 0,5%, 0,25%, 0,125% w/v) and incubation times
4 °C RT 4 °C RT
Remaining cytoplasmic material
2344
Absence of nuclear structures
3434
Shrinking
4423
subtotal
3,00 3,67 3,00 3,67 1
Tubules
4423
Glomeruli
4423
Vessels
4433
subtotal
4,00 4,00 2,33 3,00 1
3,50 3,83 2,67 3,33 1
Laminin
3344
Collagen IV
4444
Fibronectin
4444
subtotal
3,67 3,67 4,00 4,00 1
DNA content
1444
subtotal
1,00 4,00 4,00 4,00 2
Collagen content
2244
Glycosaminoglycan content
4222
subtotal
3,00 2,00 3,00 3,00 2
2,33 3,13 3,60 3,60 1
Cell count 76h
3 4
Cell viability 76h
1 4
2,00 4,00 2
2,74 3,73
General
appearance
Condition/ Parameter
SDC
SDS/TX-100
weight
Histology
Cell pe rformance
Attachment
and viability
Cell pe rformance -Score
Total Score
Detailed
analysis of
specific
structures
Histology-Score
Composition
Matrix
proteins
(histology
based)
Quantification
of absolute
composition
Composition-Score
Score s
(1-4 points, highest score is best)
:
1234
max value
Remaining cytoplasmic material cytoplasm intact
cytoplasm only
marginally
reduced
cytoplasm mainly
removed, only
fragments
no cytoplasm
remaining
Absence of nuclear structures
(Masson’s Trichrome + DAPI)
nuclei intact
few nuclei, high
amount of
released DNA
no nuclei, but
DNA detected
no nuclei, no
DNA detected
Shrinking strong medium low none
Tubules, Glomeruli, Vessels
not visible/
detectable
disrupted and/or
collapsed
architecture
moderate
disruption of
architecture
architecture
intact
Matrix proteins absent strongly reduced slightly reduced fully preserved
DNA content (µg/mg) 17,6 13,2 8,8 4,4 17,6
Collagen content (µg/mg) 37,0 74,0 111,0 147,9 147,9
Glycosaminoglycan content (µg/mg) 8,2 16,4 24,6 32,8 32,8
Cell count (nuclei/image) 3,8 7,6 11,4 15,2 15,2
Cell viability (RFU)
2409,5 4819,0 7228,5 9638,1 9638,1
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85
(4 h and 8 h) was examined. The scoring system easily visualized the strong impact of
incubation time as well as concentration on the ECM composition. The optimal condition in
this set of experiments, with a total score of 3,33, turned out to be the mildest condition
utilizing 0,125% w/v SDS for 4 h. This treatment was sufficient to remove all cellular
material while best preserving total collagen, GAG and cytokines. Only quantitative data
were used for scoring as the authors described no differences in the histology and the
published image data could not be scored.
Table 28: Scoring table of perfusion-decellularized rat and porcine kidneys
Caralt et al.144 compared the effect of TX-100 alone or in combination with SDS or
trypsin/EGTA on whole rat kidney decellularization. In Caralt’s study TX-100 alone did not
yield in a complete cell removal. The histology score of 3,67 was therefore lower than the
scores for SDS/TX-100 and trypsin-EGTA/TX-100 of 3,83. This is in line with the results
of this thesis, which yielded lower histology scores for TX-100 than SDC or SDS.
Interestingly, the combination of TX-100 with trypsin/EGTA resulted in a good removal of
cellular material but also degraded nearly completely the examined cytokines. Thus, the
combination of TX-100 with SDS was the optimal condition in these set of experiments,
with a total score of 3,37.
Poornejad et al.149 compared next to TX-100, SDS and Trypsin-EDTA also the less
commonly used decellularization reagents sodium hydroxide (NaOH) and peracetic acid
(PAA). In contrast to the other two studies, the cell performance of the different
decellularized ECMs was examined. Decellularization with trypsin-EDTA resulted in the
lowest scores for histology and composition, analogous to the results by Caralt et al. The
other examined decellularization reagents yielded in rather similar histology and
composition scores, with PAA and NaOH performing slightly better compared to TX-100
and SDS. Only the cell performance assessment fully revealed the differences between these
scaffolds and, comparable to this study, the cell performance results could not be concluded
0,125% 0,25% 0,50% 1,00% 0,125% 0,25% 0,50%
3,67 3,83 3,83 2,08 2,75 2,63 2,67 1,25
1
3,33 2,67 2,50 2,67 2,00 2,00 1,83 2,70 2,90 2,30 2,71 2,71 2,38 2,24 1,90
1
4,00 4,00 3,00 1,00 1,00
2
3,33 2,67 2,50 2,67 2,00 2,00 1,83 3,18 3,37 3,07 2,71 2,71 2,38 2,24 1,90
Condition/ Parameter
He et al.
Caralt et al.
Histology-Score
Composition-Score
Ce ll performance-Score
Total Score
Poornejad et al.
weight
SDS 4h
SDS 8h
1%
TX-100
1%
TX-100
/ 0,1%
SDS
0,02%
Typsin-
EGTA /
TX-100
0,1 N
NaOH
1%
PAA
3%
TX-100
1%
SDS
0,05%
Trypsin-
EDTA
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86
from the results of the other examined parameters. Interestingly, also in Poornejad’s study
TX-100 derived ECM showed a better cell performance than SDS despite the incomplete
removal of cellular material. Altogether PAA achieved the best total score of 3,37 in
Poornejad’s study.
These comparisons confirmed that SDS seems to be the optimal detergent for
decellularization of kidneys by perfusion.
4.4 Recellularization of perfusion-decellularized kidneys
The scaffolds generated by perfusion-decellularization of whole rat kidneys with
SDS/TX-100 were now recellularized to generate the human in vitro 3D kidney model.
Figure 39: Generation of the kidney model by de- and recellularization of rat kidneys. Rat kidneys were
decellularized by perfusion with SDS/TX-100 at RT. The scaffold was reendothelialized with hiPSC-derived
endothelial cells (ECs) via the RA. The kidney parenchyma was planned to be recellularized with hiPSC-
derived renal progenitor cells (RPCs). Three different seeding routes, such as seeding via the renal artery (RA),
via the ureter (U), or by injections into the cortex with a syringe, were assessed. The recellularized kidneys
were cultured under perfusion conditions with pH, pressure and temperature control.
Therefore, hiPSC-derived endothelial cells (ECs) were seeded into the vascular compartment
of the decellularized kidney via the renal artery (RA). The recellularization of the
decellularized renal parenchyma with hiPSC-derived renal progenitor cells (RPCs) was
assessed by seeding the cells via the renal artery, the ureter (U) or via injection into the cortex
with a syringe. The recellularized kidneys were cultured in the perfusion bioreactor with pH,
pressure and temperature control.
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4.4.1 Reendothelialization with hiPSC-derived endothelial cells
The EC differentiation protocol was adapted from Patsch el al.109. In five days the hiPSCs
differentiated into a confluent layer of 50,68% CD144 positive endothelial cells. The
CD144 positive cells were magnetically sorted and expanded for six more days. During this
time the cells matured to CD31/CD144 double positive ECs (Figure 40).
Figure 40: Differentiation scheme of hiPSC-derived endothelial cells. Endothelial cells were differentiated
from hiPSCs in a 5-day protocol. At day 5, 50,68% of the cells were CD144+, as shown by flow cytometry.
The CD144+ cells were magnetically sorted and reseeded into expansion medium. After 6 days of expansion,
on day 11, 98,54% of the cells matured into CD31/CD144 double positive endothelial cells. Brightfield images
show the morphological changes during the differentiation process. Scale bar: 200 μm.
Special focus was laid on the expansion phase of the ECs, since millions of cells are needed
to recellularize a whole rat kidney. The criteria for a successful expansion are cell
proliferation, measured in population doublings (PDL), and EC marker stability, measured
in the proportion of CD144/CD31 double positive cells. Furthermore, the cost of the
expansion medium was considered. Patsch et al. proposed the expansion in StemPro-34
medium on fibronectin coating. StemPro-34 medium costs about 500€/l. Although the EC
maturation and phenotype stability were excellent, this condition was not suitable for the
expansion, since the cells did not proliferate. Additionally, gelatin coating was included as
a comparison, since it is much less costly than fibronectin. The marker stability and PDL are
comparable to fibronectin coating. EC-SFM medium142 also stabilized the phenotype over
the whole tested period of 36 days and supported 11 PDL on fibronectin and costs only about
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300 €/l. Notably, the PDL curve flattened over time, indicating a decreasing proliferation
rate over time. EGM-FCS-SB medium141 stabilized the phenotype for 26 days. Thereafter,
the percentage of double positive ECs dropped from 93% to 77%. However, the cell
proliferation is higher than with any other tested medium; 16 PDL on fibronectin and 12 PDL
on gelatin over the course of 36 days. Therefore, 26 days on gelatin will be sufficient to
produce the number of cells needed for reendothelialization. Moreover, EGM-FCS-SB
medium is with about 200 €/l by far the cheapest medium and was therefore chosen for the
expansion of the hiPSC-derived ECs for the human kidney model.
010 20 30 40
0
20
40
60
80
100
Day
% CD144+ CD31+
010 20 30 40
0
20
40
60
80
100
Day
% CD144+ CD31+
010 20 30 40
0
20
40
60
80
100
Day
% CD144+ CD31+
10 20 30 40
-5
0
5
10
15
20
Day
PDL
10 20 30 40
-5
0
5
10
15
20
Day
PDL
10 20 30 40
-5
0
5
10
15
20
Day
PDL
Fibronectin Gelatin
StemPro-34 EC-SFM EGM-FCS-SB
Figure 41: Optimization of hiPSC-ECs expansion conditions. At day 5 of hiPSC-EC differentiation, the
ECs were sorted for CD144 and seeded into three different expansion media with fibronectin or gelatin coating.
The expansion rate, given as population doubling (PDL), and the endothelial phenotype stability, given as the
percentage of CD144 and CD31 double positive cells, were analyzed to identify the optimal expansion medium.
The phenotype was stable for 26 days in all conditions. The expansion was highest in EGM-FCS-SB medium
on fibronectin coating.
To reendothelialize the rat kidney scaffold, 5x107 hiPSC-derived ECs were injected into the
renal artery, analogous to the reendothelialization with HUVECs. The perfusion culture was
commenced after an overnight attachment phase and continued for six days.
As already observed in the HUVEC reendothelialization, LDH release was highest shortly
after seeding and decreased thereafter. Hence, cells died during seeding but survived
thereafter. Glucose and lactate measurement were fluctuating around 0 mmol/d. These
measurements are impaired by the high medium volume to cell ratio. The perfusion with
resazurin detected a high cell viability in the scaffold, especially in the interlobar and arcuate
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89
arteries. These data were corroborated by the histological analysis. The vessels were densely
populated with ECs lining the vessel walls (Figure 42).
In comparison to the HUVEC experiment, however, slightly less cell nuclei and metabolic
activity were detected. Therefore, it appears that hiPSC-derived ECs are not as robust as
HUVECs. Nevertheless, a good reendothelialization result was achieved with hiPSC-derived
ECs.
Figure 42: Arterial seeding of hiPSC-ECs. (A) hiPSC-ECs were injected through the IN port of the perfusion
bioreactor into the renal artery of the decellularized rat kidney. Perfusion culture started after O/N static culture.
(B) DAPI stained cross-section after 6 days of perfusion culture. ECs were spread over the whole tissue, lining
specifically the bigger blood vessels (white arrows), as shown in more detail in (C). (D) The resazurin-assay
detected viable cells in the vascular tree. (E) LDH release was highest shortly after perfusion culture start.
Glucose, lactate metabolism was hardly detectable, due to the high medium volume.
CD31 staining on sections of a native human kidney, a HUVEC recellularized kidney and
an hiPSC-EC recellularized kidney revealed the exact localization and morphology of the
endothelial cells. In the native human kidney, CD31 positive ECs were detected lining the
segmental, interlobar, arcuate and interlobular arteries and veins, the afferent and efferent
arterioles and the delicate glomerular and peritubular capillaries. The recellularized rat
kidneys showed similar staining patterns, which suggests an effective reendothelialization.
The cells did not migrate out of the vascular compartment. They lined the vessels walls, only
some cell plugs were found inside the vessels. Merely the microstructure in the glomerular
capillaries was not as well formed as in the native kidney.
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90
Figure 43: CD31+ endothelial cells lined the blood vessels and the glomerular capillaries in the
recellularized kidneys. The delicate structure of the human kidney glomerulus was not achieved in the
recellularized kidneys. No differences between HUVEC and hiPSC-EC recellularizations were prominent.
Scale bar: 100 μm.
4.4.2 Recellularization of the kidney parenchyma with hiPSC-derived renal
progenitor cells
The kidney parenchyma was planned to be recellularized with hiPSC-derived RPCs. It was
hypothesized that the preserved architectural, mechanical and biochemical features of the
decellularized kidney scaffold promote site-specific maturation of the RPCs and the
generation of a functional 3D kidney model.
Figure 44: Differentiation scheme of hiPSC-derived RPCs. Renal progenitor cells were differentiated from
over confluent hiPSCs. At day 3, hollow domes emerged from the confluent cell monolayer. At day 4, IMCs
were formed. The domes collapsed after the change to GDNF containing medium. At day 8, hiPSC-derived
RPCs could be harvested. To generate renal tubular epithelial cells, RPCs were cultured for 6 more days in
REGM. Brightfield images show the cell morphology during the differentiation process. Scale bar: 200 μm.
RPCs were differentiated from hiPSC using a protocol developed in our lab by
Hariharan et al.117. The protocol differentiates hiPSCs after four days into dome forming
intermediate mesoderm cells and after eight days into RPCs, as shown in Figure 44. The
hiPSC-derived RPCs can differentiate into various mature renal cell types, for example into
renal tubular epithelial cells (RTECs) when cultured for six more days in REGM.
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The most efficient way to seed the cells into the decellularized parenchyma was investigated
next.
4.4.2.1 Arterial seeding
The arterial seeding was successfully applied for the endothelial cells. Therefore, arterial
seeding was also tested for RPCs, although in contrast to the endothelial cells, the RPCs
should not settle in the vascular tree but should populate the renal tubules and glomerular
structures.
When 3x107 RPCs were seeded into the renal artery with the same seeding protocol that was
used for the endothelial cells, rarely any cells survived the five days of perfusion culture.
The DAPI staining showed cell debris located in the vascular compartment. No cells were
detected in the tubular structures. Also, the metabolic activity measured by the resazurin
assay or the glucose and lactate metabolism was only minimal (Figure 45). Therefore, the
RPCs seem to be much more fragile and sensitive than HUVECs which survived the same
recellularization procedure without difficulty. Additionally, the RPCs did not migrate out of
the vascular tree, analogous to the endothelial cells before. A simple arterial seeding is hence
not sufficient for parenchymal recellularization.
Figure 45: Arterial seeding of RPCs. (A) RPCs were injected through the IN port of the perfusion bioreactor
into the renal artery of the decellularized rat kidney. Perfusion culture started after O/N static culture.
(B,C) DAPI stained cross-section after 5 days of perfusion culture. Fragmented nuclei indicated cell death of
the majority of cells. Cells were located in the vascular compartment, no migration into the tubular
compartment was observed. (D) No color change from purple to pink in the resazurin-assay indicated low cell
survival. (E) Low glucose consumption and lactate production corroborated the low cell viability.
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Since no cells migrated into the tubular compartment with the standard arterial seeding, high
pressure seeding was applied next, as described by Caralt et al.144. The RPCs were injected
into the renal artery. Medium perfusion was started immediately afterwards with 25 ml/min
for 15 min, without an overnight attachment phase. Histology revealed cavities in the
scaffold that were most likely ripped into the scaffold during this high-pressure seeding
phase. These holes were surrounded by many living cells. Also, other areas of the scaffold
showed successful recellularization, mainly parts of the renal cortex but also some tubules
in the medulla. However, in total only a small fraction of the scaffold was repopulated.
Resazurin perfusion stains the denser populated side of the kidney pink, corroborating the
histology data. The glucose, lactate and LDH values were very low and peak shortly after
perfusion culture start. This is again due to the very low total number of cells that attached
in the scaffold (Figure 46). Thus, high pressure seeding slightly improved the efficiency of
the arterial seeding, at the expense of the scaffold’s integrity. However, the efficiencies
described by Caralt et al.144 were not reproducible.
Figure 46: High-pressure arterial seeding of RPCs. (A) RPCs were injected through the IN port of the
perfusion bioreactor into the renal artery of the decellularized rat kidney. Immediately followed by a high-
pressure perfusion for 15 min to push the cells from the vascular compartment into the tubular compartment.
(B,C) DAPI stained cross-sections after 5 days of perfusion culture. Cavities in the cortex indicate scaffold
ruptures due to the high-pressure perfusion. Cells reached the tubules around the cavities (white arrows).
(D) Color change from purple to pink in the resazurin-assay in the areas where the cavities and cells are
detected in (B) indicated successful cell seeding and survival. (E) LDH release peaked shortly after perfusion
start, indicating cell death. Too less cells populate the scaffold thereafter to generate measurable glucose and
lactate values.
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93
Next, another approach was analyzed that could improve the tubular repopulation in an
arterial seeding. This approach included a short trypsin digest to weaken the vascular basal
membrane. Hypothetically, the RPCs could migrate easier into the tubular compartment
through a weakened basal membrane. However, arterially injected trypsin probably diffuses
out of the decellularized vascular tree into the parenchyma. Therefore, this technique most
likely sacrifices functional and structural proteins in the tubular basement membranes that
were carefully preserved during decellularization. Trypsin was injected into the artery,
incubated for 1 h and washed out carefully before cell seeding.
Histology showed that RPCs were able to reach the tubular compartment in the cortex but
mostly died as mainly cell debris is detectable. The structure of the bigger arteries, e.g. the
interlobar and arcuate arteries, were well preserved. Therefore, the RPCs must have passed
the vascular basal membrane at smaller vessels with less pronounced vessel walls, e.g. the
interlobular vessels, arterioles or capillaries. Whether the cells migrated actively and
subsequently died or died first and were only passively washed into the tubular structures
remains unclear. Metabolic measurements confirmed the low cell viability in the scaffold
(Figure 47). Consequently, trypsin pretreatment of the scaffold did not improve arterial
seeding.
Figure 47: Arterial seeding of RPCs into partly trypsin-digested scaffolds. (A) Decellularized kidneys
were partly digested with trypsin for 1 h to facilitate cell migration from the vascular tree into the tubular
compartment. RPCs were injected into the renal artery of the decellularized rat kidney. (B,C) DAPI stained
cross-sections after 5 days of perfusion culture show primarily degraded nuclei (white arrows). (D,E) No
metabolic activity was detected.
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4.4.2.2 Ureter seeding
The ureter is the direct seeding port into the tubular compartment. For seeding RPCs through
the ureter, it was cannulated with a beveled catheter. To allow the undisturbed drainage of
the decellularization agents and cell debris during the decellularization, the ureter was
cannulated after decellularization.
3x107 RPCs were injected in 1ml REGM via the ureter cannula. A dilation of the renal pelvis
and compression of the renal papilla due to the ureter seeding was revealed by histological
analysis. The dilated pelvis was lined with cells, but the cells rarely advanced into the renal
ducts and tubules of the parenchyma. Thus, the resazurin perfusion showed metabolic
activity only in the center of the kidney. Glucose consumption and lactate production were
low but detectable, confirming the low cell count (Figure 48). A simple infusion of RPCs
through the ureter did not recellularize the parenchyma.
Figure 48: Ureter seeding of RPCs without vacuum. (A) RPCs were injected into the cannulated ureter of
the decellularized rat kidney. Perfusion culture started after O/N static culture. (B,C) DAPI stained cross-
sections after 6 days of perfusion culture revealed a dilated renal pelvis with cells lining the cavity. Only the
minority of cells reached the tubules of the medulla or cortex (white arrow). (D) Therefore, the resazurin-assay
only showed metabolically active cells in the center of the scaffold and (E) only low levels of glucose and
lactate metabolism were detected.
To enhance the transfer of the seeded cells from the pelvis into the tubular structures a
seeding protocol published by Song et al.123 was tested. After cell injection into the ureter,
100 mbar vacuum were applied to the bioreactor to pull the RPCs into the ducts and tubules.
The analysis revealed a slightly improved seeding success in comparison to the ureter
seeding without vacuum. Again, histological analysis showed an enlarged, cell lined pelvis
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and only some areas where cells advanced into the cortex. However, the cells did not line
the tubules in a closed epithelial layer, they were rather scattered through the scaffold or
clumped together. The pelvis was even more enlarged than in the simple ureter seeding
approach. The resazurin perfusion showed more metabolically active cells than in the ureter
seeding without vacuum. The pink stain, which indicates viable cells, was again mainly
located in the center of the kidney, although cortex areas were stained too. LDH release, a
marker for cell death, was detected in the first two days of the perfusion culture. Low glucose
and lactate metabolism were detected over the full culture period and corroborates the low
cell number detected in the DAPI stain (Figure 49). Therefore, the ureter seeding was
improved by the vacuum application, but the scaffold was still not sufficiently recellularized
for further analysis of the cell maturation. Hence, the results by Song et al. could not be
reproduced.
Figure 49: Ureter seeding of RPCs with vacuum. (A) RPCs were injected into the cannulated ureter of the
decellularized rat kidney, followed by applying 100 mbar vacuum to the bioreactor to facilitate the cell passage
from the pelvis into the tubules. Perfusion culture started after O/N static culture. (B,C) DAPI stained cross-
sections after 6 days of perfusion culture revealed an enlarged renal pelvis with cells lining the cavity. In some
parts the cells reached the tubules of the medulla or cortex (white arrow). (D) Therefore, the resazurin-assay
shows metabolically active cells in the center and on one side of the scaffold. (E) Due to the low number of
cells only low levels of glucose and lactate metabolism were detected.
4.4.2.3 Syringe seeding
Another option to recellularize the kidney parenchyma is to inject the cells directly with a
syringe into the cortex. When 100 µl cell suspension were injected in one shot, the scaffold
ripped as shown in Figure 50B. These holes were lined with cells that did not advance into
the surrounding tubular structures. When 5 µl cell suspension were injected per shot, the
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scaffold rupture was much smaller, but again, cells did not migrate away from the injection
site. Zones where cells were flushed from the site of the injection into the surrounding
tubules and glomeruli were rarely found (Figure 50C). Resazurin perfusion showed low
metabolic activity in the kidney. LDH release, glucose consumption and lactate production
were low during the whole culture period.
Figure 50: Injection of RPCs into the cortex of perfusion-decellularized kidneys with a syringe. (A) RPCs
were injected into the cortex of decellularized rat kidney with a 27-gauge needle. Perfusion culture started after
O/N static culture. (B,C) DAPI stained cross-sections after 6 days of perfusion culture revealed cell lined
cavities. The majority of the cortex and medullary regions were cell free. Cells in the cavities did not migrate
away from the site of the injection (white arrows). (D) Due to the low cell number, rarely any metabolic activity
was detected with the resazurin-assay. (E) Also, only low levels of glucose and lactate metabolism were
detected.
4.4.2.4 Seeding strategy comparison
A clear comparison of the RPC seeding efficiencies was achieved by counting the nuclei on
DAPI stained cross-sections and normalizing the cell count to one mm². The highest counts
were achieved with high-pressure arterial seeding and syringe seeding, followed by low-
pressure arterial and vacuum-assisted ureter seeding strategies. The lowest counts were
achieved with the artery with trypsin and ureter without vacuum approaches. However, all
approaches reached merely between 4 and 26 nuclei/mm² and are therefore in the range of
1% of the native kidney cell density of 2364 nuclei/mm² (Figure 51A). This observation is
corroborated by the quantification results of the resazurin assay (Figure 51B). Additionally,
RPCs that were seeded successfully into the scaffold did not form tubular structures but were
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rather scattered across the scaffold (Figure 45-Figure 50). Therefore, no further analysis of
the maturation of the RPCs was possible.
In conclusion, none of the recellularization approaches did reach a cell density or cell
arrangement required to generate a human kidney model.
Native
Artery low pressure
Artery high pressure
Artery Trypsin
Ureter no vacuum
Ureter vacuum
Syringe
0
10
20
30
40
1000
2000
3000
4000
*
*
*
Nuclei/mm²
Native
Artery low pressure
Artery high pressure
Artery Trypsin
Ureter no vacuum
Ureter vacuum
Syringe
0
1000
2000
3000
4000
10000
20000
30000
40000
RFU
A B
Figure 51: Quantitative analysis and comparison of seeding strategies. (A) RPCs were counted on DAPI
stained sections of recellularized kidneys. Counted nuclei were normalized to the area of the analyzed images,
to compensate for differing section sizes. (B) Resazurin assay quantification results given in relative
fluorescence units (RFU). Viable cells reduced resazurin to the highly fluorescent resorufin. Best seeding
results were achieved by seeding RPCs into the renal artery with high pressure. However, none of the seeding
approaches reached cell densities or metabolic activities comparable to native organs. * indicates a significant
difference in means, p<0.05.
4.5 The effect of stiffness and ECM composition on renal
progenitor cell maturation
The segment-specific architecture and ECM composition of the nephron create specific
microenvironments for every cell type of the kidney. The decellularized kidney scaffold
provides these site-specific architectural, mechanical and biochemical stimuli to the reseeded
cells. In consideration of the theoretical impact of these factors on the phenotype and
differentiation of cells, as described in 1.2.2, it was hypothesized that these
microenvironments would promote full, site-specific maturation of the reseeded
hiPSC-derived RPCs. Cells inside the kidney scaffold are exposed to a combination of all
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these stimuli. To investigate the singular effect of any of these stimuli on RPC maturation, a
parallel approach to the recellularization was established.
The effect of stiffness and ECM composition on RPC maturation was investigated on
polydimethylsiloxane (PDMS), an easily moldable silicone with tunable elastomeric
properties that can be coated with numerous ECM proteins.
First, the PDMS was optimized for RPC culture. Next, the effect of stiffness and ECM
coating on RPC maturation was investigated.
4.5.1 Optimization of PDMS gels for cell culture
The elastic modulus of PDMS can be tuned by adjusting the ratio of the base and the curing
agent. Three different PDMS mixtures were produced with elastic modules of 4 kPa, 189 kPa
and 2230 kPa (Figure 52A).
PDMS Mix 1 PDMS Mix 2 PDMS Mix 3
1
10
100
1000
10000
2230
4
189
E [kPa]
-L511 +L511 -L511 +L511
0
2000
4000
6000
8000
10000 *
-Dopamine +Dopamine
RFU
A B
Figure 52: PDMS gel properties. (A) PDMS gels were produced from different Sylgard mixtures resulting in
different stiffness, quantified by the E modulus. (B) PDMS is highly hydrophobic, therefore RPCs seeded on
PDMS mix 1 cannot attach. Hence no metabolic activity in the resazurin assay was detectable. L511 coating
alone could not improve the attachment sufficiently. Only dopamine pretreatment and L511 coating improved
the attachment significantly.
PDMS is highly hydrophobic, without any pretreatment no RPCs can attach, resulting in no
measurable metabolic activity in the resazurin assay. When PDMS was coated with
laminin 511 the attachment and survival was only slightly higher. Earlier experiments with
plasma treated PDMS did not yield in a reliable long-term cell attachment (data not shown).
Therefore, the polydopamine coating was established as an alternative to the plasma
pretreatment. The cell attachment improved drastically when PDMS was pretreated with
Results
99
dopamine at pH 8,5. The polydopamine surface can be coated with ECM proteins. L511
coating on the polydopamine pretreated PDMS improved the cell attachment significantly
(Figure 52B).
ECM coated, polydopamine pretreated PDMS was used for all further experiments.
4.5.2 Investigation of renal progenitor cell maturation
RPC maturation was investigated by differentiating RPCs into RTECs, as described in
section 4.4.2. The effect of the stiffness of the culture surface on RPC differentiation was
investigated by culturing the cells on PDMS with an E modulus of approximately 4 kPa,
200 kPa or 2 MPa. The effect of the ECM composition on RPC maturation was investigated
by coating these PDMS culture surfaces with L511, L521, ColIV and mixtures of these three
renal ECM components. As a control the standard RTEC differentiation on L521 coated
TCPS was conducted. RPC maturation was assessed by morphological analysis and
quantification of renal marker expression by qPCR.
Clearly stiffness and ECM coating both affected the cell morphology (Figure 53). Cells in
all conditions exhibited an epithelial-like cell morphology comparable to the L521 TCPS
control (Figure 44). Cells on 4 kPa PDMS showed brighter cell-cell connections in phase
contrast than cells on 2 MPa. Cells on 2 MPa PDMS appeared bigger and with higher
contrast. Also, cells in most conditions showed signs of deterioration, indicated by
cytoplasmic vacuolation. Less cells survived on ColIV coated 4 kPa gels. The combination
of L511, L521 and ColIV induced a similar morphology on 4 kPa gels and on 2 MPa gels.
Effects of stiffness and ECM-coating were also detected in the marker expression of RTECs
(Figure 54). Aquaporin 1 (AQP1), a water channel protein on proximal tubular epithelial
cells, was highly upregulated during RTEC differentiation. Interestingly, the AQP1
expression was increasing with PDMS stiffness. Moreover, the coating had a clear impact
on the AQP1 expression. Both laminins supported a high expression, whereas ColIV coated
cell culture surfaces yielded in a significantly lower AQP1 expression. The highest
expression was achieved on the stiffest PDMS coated with a mixture of L511, L521 and
ColIV. The AQP1 expression correlates with the cell morphology. Cells with higher AQP1
expression displayed darker cell-cell connections in phase-contrast.
Results
100
Figure 53: Renal tubular epithelial cell morphology on ECM-coated PDMS of 4 kPa and 2 MPa stiffness.
Cells in all conditions exhibit an epithelial morphology. On 4 kPa PDMS cell-cell connections appear brighter
in phase contrast than on 2 MPa.
The alpha subunit of the Na+/K+-ATPase (ATP1A1), found in most renal tubular cells was
highly expressed in RPCs as the 𝛥𝛥𝐶𝐶𝐶𝐶 to the housekeeping genes is -10. The expression
slightly decreased during differentiation. Neither stiffness nor coating of the PDMS had
major impact on the expression. ATP1A1 expression is therefore not a good marker for RPC
maturation, since it is already highly expressed on the progenitor cell population.
Similarly, only low effects of stiffness and ECM on the expression pattern of the
sodium-chloride symporter (SLC12A3), a marker on renal distal tubular cells, were detected.
Notably, contrary to the AQP1 expression, the podocyte markers podocalyxin (PODXL) and
synaptopodin (SYNPO) were significantly higher expressed on 4 kPa PDMS than on stiffer
PDMS gels. The ECM composition did not induce major PODXL expression differences. In
contrast, SYNPO expression was decreased on ColIV coating. Wilms tumor protein (WT1),
a transcription factor found in the glomerulus, was highest expressed in cells cultured on
200 kPa PDMS.
Results
101
AQP1
RPC CTR
L521 CTR
L511
L521
ColIV
L511:L521
L511:ColIV
L521:ColIV
L511:L521:ColIV
0
20
40
60
80
100
-15
**
*
*
RQ
ATP1A1
RPC CTR
L521 CTR
L511
L521
ColIV
L511:L521
L511:ColIV
L521:ColIV
L511:L521:ColIV
0.0
0.5
1.0
1.5
-10
*
RQ
PODXL
RPC CTR
L521 CTR
L511
L521
ColIV
L511:L521
L511:ColIV
L521:ColIV
L511:L521:ColIV
0.0
0.5
1.0
1.5
-8
*
*
*
*
**
* *
*
RQ
SLC12A2
RPC CTR
L521 CTR
L511
L521
ColIV
L511:L521
L511:ColIV
L521:ColIV
L511:L521:ColIV
0.0
0.5
1.0
1.5
-10
*
***
*
*
*
*
* * * *
*
*
RQ
SYNPO
RPC CTR
L521 CTR
L511
L521
ColIV
L511:L521
L511:ColIV
L521:ColIV
L511:L521:ColIV
0
1
2
3
4
-14
*
*
*
*
*
*
*
RQ
SIX2
RPC CTR
L521 CTR
L511
L521
ColIV
L511:L521
L511:ColIV
L521:ColIV
L511:L521:ColIV
0.0
0.5
1.0
1.5
-17
*
*
*
*
RQ
WT1
RPC CTR
L521 CTR
L511
L521
ColIV
L511:L521
L511:ColIV
L521:ColIV
L511:L521:ColIV
0.0
0.5
1.0
1.5
-15 **
*
*
*
RQ
SLC12A3
RPC CTR
L521 CTR
L511
L521
ColIV
L511:L521
L511:ColIV
L521:ColIV
L511:L521:ColIV
0.0
0.1
0.2
0.3
0.4
0.5
0.5
1.0
1.5 -15
RQ
4 kPa 200 kPa 2 MPacontrol
RTEC marker Glomerular marker
RPC marker Other epithelia
A B
C D
Figure 54: RPC and RTEC gene expression on ECM-coated PDMS of 4 kPa, 200 kPa and 2 MPa
stiffness. (A) The RTEC marker AQP1 is highest expressed on stiff, laminin coated PDMS, (B) whereas the
glomerular markers are highest expressed on soft PDMS. Stiffness provokes greater differences in marker
expression than the ECM coating. Expression values are given as relative quantification (RQ) to the RPC
control (RPC CTR). The numbers on top of the RPC CTR bars indicate the ΔCt to the housekeeping genes. *
indicates a significant difference in means between stiffnesses (black) or coatings (grey), p<0.05.
The Na-K-Cl cotransporter 1 (SLC12A2) is not found in the kidney but throughout the body’s
exocrine epithelia. Its expression was influenced similar to the podocyte markers. Highest
expression rates were detected in the lowest stiffness. Interestingly the expression on ColIV
coated 4 kPa PDMS was significantly higher than on laminin.
Results
102
SIX2 expression, a transcription factor active in renal development, decreases during RTEC
differentiation, indicating a maturation of the renal progenitor cells.
Discussion
103
5 Discussion
The aim of this thesis was to develop a human kidney model by decellularization of whole
rat kidneys and recellularization of these ECM scaffolds with hiPSC-derived endothelial and
renal progenitor cells.
A controllable perfusion bioreactor was developed that facilitates de- and recellularization
of rat kidneys. A control software was programmed in LabView that allows constant control
and monitoring of the bioreactor. Perfusion bioreactors as advanced as the one developed in
this thesis are not commercially available and have not been used in any other published
kidney de- and recellularization study.
A decellularization protocol was identified that balances effective cell removal and
preservation of the ECM. The decellularized kidney is more than a simple scaffold that
provides architecture and stability to the cells. It also provides important biochemical and
mechanical stimuli.
As a next step, the decellularized vascular tree of the ECM scaffold was successfully
reendothelialized. The recellularization of the parenchyma with RPCs, however, was very
ineffective. Despite extensive testing, no recellularization strategy could be identified that
repopulated the scaffold with the number and arrangement of cells that would be necessary
to generate a human kidney model.
In parallel, a PDMS assay was established, to unravel how the biochemical and mechanical
stimuli provided by the decellularized kidney affect RPC maturation. It was found that both
substrate stiffness and ECM composition influence the maturation of renal progenitor cells
into renal tubular epithelial cells and podocytes.
Discussion
104
5.1 The perfusion bioreactor enables kidney de- and
recellularization
The vascular tree of the kidney is naturally designed to ensure optimal supply of nutrients
and oxygen to the entire organ as well as to provide perfusion through the nephron. The
possibility to use that distribution system is a clear advantage of the de- and recellularization
technique over any other kidney tissue engineering approaches to date. For example, the
biggest hurdle for the organoid technology is currently the integration of a vascular network
to improve nutrient and oxygen supply as well as to include shear forces into the model150.
By using whole kidneys, however, decellularization agents or cell culture medium can
simply be perfused by a peristaltic pump via the cannulated renal artery through the vascular
tree of the scaffold.
For this purpose, a perfusion bioreactor is required. Simple kidney perfusion bioreactors
exist since the late 1970s, for ex vivo isolated perfused organ studies and are commercially
available since then151,152. Recently, this technique has been adapted for kidneys prior to
transplantation. Hypothermic machine perfusion improved the graft survival significantly
over simple cold storage153–155. However, these commercially available bioreactors are
designed for short term kidney survival, not for long term culture. They neither offer proper
control over cell culture conditions nor facilitate cell seeding. Over the last years, numerous
studies on whole organ recellularization have been published, most utilized a simple
perfusion pump placed in a standard cell culture incubator148,156–159. Others set up perfusion
bioreactors that monitored the pressure and facilitated cell seeding123,160–162. Only the
minority of these studies used advanced perfusion bioreactors that automatically control
pressure and pH and include a control software163,164. However, none of these advanced
perfusion bioreactors were applied in kidney de- and recellularization to date. In addition,
these advanced bioreactors are not commercially available as they are all custom build.
Therefore, a perfusion bioreactor was developed that enables de- and recellularization of
whole rat kidneys. It was designed to meet all requirements for long term organ culture.
Accordingly, the developed perfusion bioreactor ensures sterility, temperature control, pH
control, pressure control, non-invasive monitoring of cell viability and pO2 and most
importantly perfusion with cell culture medium, to provide nutrition and oxygen and to
deplete excreted products.
Discussion
105
The perfusion also provides mechanical stimuli to the reseeded cells that are necessary for
maturation and functionality. In microfluidic chip experiments it was shown that
physiological shear stress improves the phenotype of proximal tubular cells as it leads to
enhanced polarization, glucose reabsorption and primary cilia formation165,166. In contrast,
slightly elevated shear stress resulted in dramatic damage to podocytes in vitro167. In vivo,
high blood pressure is a leading cause for kidney failure5. Moreover, high perfusion pressure
might easily disrupt the decellularized scaffold. On the other hand, when the pressure in the
renal artery drops below 60 mmHg, the renal perfusion decreases and the tissue is at risk of
necrosis168. The tight regulation of flow and pressure in the perfusion bioreactor is therefore
an important aspect.
A control software programmed in LabVIEW enables the manual and automatic control of
all crucial process variables. LabVIEW is a well-established programming language for
process control applications. The code was structured as a queued state machine, a flexible
and powerful producer consumer architecture that is one of the most frequently used design
patterns in LabVIEW169.
In the perfusion bioreactor, pressure control was realized by adjusting the pump speed. In a
step response experiment the process was identified as a first-order system (PT1 element)
with a mean time constant of 4 s. The pressure reacts to the pump speed change without any
dead time, but the new steady state is only reached with a delay. This delay can be explained
by the time the pump needs to accelerate or a slight dilation of the kidney.
To guarantee optimal process control, the choice of the controller type and tuning parameters
is of utmost importance and is in most cases a compromise between slow but stable and
dynamic but instable controller behavior. It also needs to be kept in mind that the
decellularized kidney scaffolds are natural products, hence, each kidney differs in its arterial
branching morphology and other morphologic characteristics170. Thus, every tested kidney
responded differently in the step response. The controller was tuned in a way that it worked
for all kidneys likewise. In the reference-variable response and the disturbance response it
was shown that the PI controller tuned after the KUHN rules147 handles the pressure control
satisfactory.
On this basis a pulsatile flow profile could be implemented to mimic the fluctuating blood
pressure in the human body171.
Discussion
106
The pH in cell culture medium is regulated via a bicarbonate buffer and CO2 gassing. In
static cell culture the medium is normally gassed with 5 % CO2 to adjust the pH to 7,4, the
same pH as blood1. In order to react to pH disturbances such as the secretion of acidic
metabolites, it is necessary to dynamically adjust the CO2 concentration in the bioreactor.
Additionally, pH control enables modelling of alkalosis or acidosis and investigations on
how these affect renal tubular epithelial cells (RTECs), which are responsible for the acid-
base homeostasis172. Therefore, the pH control was implemented in the perfusion bioreactor.
The pH control was realized by adjusting the CO2 concentration in the oxygenator. The step
response characterized the process as a second-order system (PT2 element). It is defined by
a delayed reaction composed of the process dead time that varies between 9 and 15 min and
the process time constant that adds another 9 min. The dead time is caused by the time the
CO2 needs to diffuse through the silicone tubing into the medium in the oxygenator, plus the
time the medium needs to travel from the bioreactor through the oxygenator to the sensor,
which can vary according to the pump speed and the tube length. The ratio of the process
time constant and the process dead time is a measure for the controllability of the system. It
defines the pH control in the perfusion bioreactor as hardly controllable.
Despite this hurdle, a PI controller was tuned that sufficiently controls the pH for smaller
disturbances that appear during normal metabolic activity. For strong sudden disturbances,
the control settling time lies between one and two hours. Therefore, it is advisable to pre-gas
the medium with CO2 before medium changes to avoid drastic pH drops.
The same setup that is used for CO2 control, including the gas mixing device and the
oxygenator, provides the basis for the control of oxygen levels in the culture medium.
Moreover, a pO2 sensor is integrated into the perfusion circuit. In future, the control software
can easily be expanded to enable oxygen control and to facilitate thus the investigation of
hypoxia on the kidney model.
Electrical or mechanical stimulation, such as stretching, are beneficial for lung173 or
heart163,174 recellularization cultures. However, the kidney is naturally not exposed to these
stimuli and it was therefore not necessary to implement these stimuli into the perfusion
bioreactor for the kidney.
Discussion
107
5.2 Kidney decellularization
Decellularization is the removal of cellular material from a cell culture, tissue or whole organ
by a series of physical and chemical treatments. Applications of decellularized ECM
scaffolds range from in vitro applications in basic research that address questions of cell-
matrix interactions, disease or tissue development and regeneration, up to clinical
applications of the scaffolds as such or after recellularization27,127. An optimal ECM quality
is of utmost importance for all these applications, the aim was therefore to identify a
decellularization protocol for kidney tissue that maximizes cell removal and minimizes ECM
loss and damage.
Several strategies for decellularization of kidney tissue cubes by immersion and
agitation149,175 and decellularization of whole kidneys by perfusion123,144,156,157,162 have been
published in the last years. However, all these protocols use SDS, which is known to disrupt
protein structures and to dissolve some ECM components127,129. Moreover, most of these
manuscripts lack the comparison between multiple decellularization conditions.
Furthermore, in studies that did compare multiple conditions, it is mostly impossible to
identify the isolated effect of a specific protocol step on the scaffold quality. Systematic,
controlled studies that compare multiple decellularization protocols in their cell removal
efficacy and their effect on the ECM scaffold composition and biocompatibility are missing.
Therefore, a comprehensive comparison was carried out in this thesis, to identify the optimal
protocol for kidney decellularization.
5.2.1 The decellularization scoring system standardizes the evaluation of
decellularization results
A standardized, unbiased evaluation of the ECM scaffolds and the definition of critical
parameters for scaffold quality become increasingly important as the field moves towards
clinical application. Results from histology, composition and biocompatibility analysis of
decellularized ECM scaffolds represent qualitative and quantitative data and often underlie
subjective success criteria.
The scoring system developed in this study is the first attempt to standardize the quality
assessment of decellularized ECM scaffolds. It condenses qualitative and quantitative results
into normalized scores. Therefore, it provides the opportunity to carry out intra- and
Discussion
108
inter-study comparisons of decellularization strategies and ECM scaffold quality. Designed
as an easily scalable system it can be expanded by additional parameters and categories.
Depending on the application, scoring weights can also be modified. Analysis of tissue-
specific parameters in the three primary categories histology, composition and
biocompatibility is mandatory to derive a reliable quality score. For example, the
biocompatibility scores for cell attachment and viability were not directly predictable from
the scores of the other parameters. When a clinical application of the ECM scaffolds is
considered, the scoring system can be easily extended with a category for clinically relevant
data, such as immune compatibility. In this study, the system was applied to decellularization
of kidney tissue; however, it is equally suitable for other tissues. Furthermore, the scoring
system supports the identification of critical parameters by summarizing and visualizing
study outcomes. A template of the scoring table was provided to the international research
community as an interactive Excel sheet in Fischer et al. 2017176.
5.2.2 The effect of the detergent on kidney decellularization by immersion
Immersion and agitation technologies for decellularization of tissues are useful to screen and
compare decellularization protocols. This method was applied to porcine kidney tissue to
compare the isolated effects of the detergents SDC, SDS and TX-100. Theoretically, mild,
non-ionic detergents, such as TX-100, are the most desirable detergents to preserve the ECM
during decellularization. However, especially for decellularization of dense organs like
kidneys, non-ionic detergents might not be strong enough to remove the cells. Mild, ionic
detergents, such as SDC, might provide a solution but have not been investigated
thoroughly126,127.
Cell lysis was provoked in 0,125 cm³ porcine kidney cubes by freezing and thawing and
subsequent osmotic shock by diH20 treatment. The samples were then immersed in 1% SDC,
1% SDS or 1% TX-100 for 7 to 10 days under constant agitation to solubilize and remove
cellular debris. Lastly, the samples were extensively washed to remove any residual
detergent and analyzed for cell removal and architectural integrity by histology.
Histological analysis revealed that TX-100 only removed a fraction of the cellular material;
it is therefore not suitable as sole detergent for kidney decellularization. TX-100 is a
non-ionic detergent. With an HLB of 13,5 its uncharged hydrophilic head group and
Discussion
109
hydrophobic tail, TX-100 can break lipid–lipid and lipid–protein interactions. It dissolves
cell membranes and membrane proteins by association with their hydrophobic parts, a
micelle-like interaction that mimics the lipid environment of the protein and thereby even
supports its continued activity. However, TX-100 cannot dissolve protein-protein
interactions. It neither penetrates into proteins nor denatures them127,129. Therefore, it is clear
that TX-100 hardly penetrates through the porcine kidney cube, as it was confirmed in other
studies144,156,177. Surprisingly, three other studies on kidney immersion-decellularization
reported successful decellularization with TX-100. In these studies, however, the immersed
tissue pieces were smaller and the detergent was applied in higher concentration, or for up
to two weeks149,175,178. In general, TX-100 is only suitable, when applied during
decellularization of thin tissues, such as heart valves179.
Immersion with SDS at 4 °C resulted in completely decellularized tissue. SDS is a strong
ionic detergent with an HLB of 40. It not only disrupts cell membranes forming mixed
micelles, its monomers also bind cooperatively to proteins, which are thereby forced into
drastic conformational changes and denaturation. Hence, SDS is effective in dissociating
protein-protein interactions and solubilizing cytoplasmic compounds127,129. SDS is widely
used as a decellularization agent, due to its excellent cell clearing properties.
Also, the SDC 4 °C samples were predominantly cleared of cellular material. However,
small zones with DAPI stained cellular debris were still observable. A DNase digest was
added after the detergent treatment that reduced the total DNA amount drastically. Although
SDC is categorized as an ionic detergent, it has an HLB of 16. Its hydrophilic properties and
behavior are therefore much closer to TX-100 than to SDS. Comparable to TX-100, SDC
does not induce protein denaturation. This complements its natural function as a bile acid in
the gut, where it dissolves lipids to assist fat digestion129,180. However, the ionic head group
explains the better cell removal efficiency of SDC than TX-100.
The composition analysis of decellularized ECM scaffolds is challenging. ECM proteins are
essentially insoluble in standard detergent based lysis buffers as they have a high molecular
mass and are abundantly covalently cross-linked. Exactly this property is utilized in
decellularization but hinders the proteomic analysis. Dot blot and western blot analyses (data
not shown), did not result in robust quantifications. Mass spectrometry approaches face the
same hurdles. Only very recently, a chemical digestion with hydroxylamine for insoluble
extracellular matrix characterization was identified181. Hence, in this study the composition
Discussion
110
was analyzed by immunofluorescent staining of ECM proteins, bulk collagen and GAG
quantifications, as well as enzyme-linked immunosorbent assay (ELISA) for bFGF and
VEGF.
Decellularization with SDS resulted in slightly higher collagen content per dry weight than
with SDC, though the difference was not significant. This finding is probably due to a higher
fraction of cellular remnants in the dry weight of SDC-decellularized scaffolds and not due
to the removal of collagen by SDC, since SDC as a mild detergent cannot dissolve highly
crosslinked collagen molecules. The normalization to dry weight after decellularization
impedes the clear interpretation of the quantification results if the samples still contain a
considerable amount of cellular debris. However, it is the gold standard in decellularization
studies to date123,149,156. In future, it would be advisable to normalize quantification results
to wet weight of the tissue samples before decellularization instead, to facilitate the
comparison of absolute quantification results.
Also, decellularization with SDS resulted in a higher GAG per dry weight ratio than SDC
treatment. On the contrary, the cytokines bFGF and VEGF are much better preserved with
SDC than with SDS. Both cytokines are mainly bound to the ECM by GAGs. Therefore, it
seems that although SDC removes GAG chains from the scaffold, it does not strip the
cytokines from the remaining chains. On the other hand, SDS might not deplete the GAG
chains, but denature or remove the bound cytokines.
The data from recellularization with human iPSC-derived intermediate mesoderm cells113
suggest that the cytokines retain their biological activity after SDC treatment, since the SDC
treated samples harbor the highest levels of growth factors and achieved the best results for
cell attachment and viability. No negative effect of minor cellular remnants was observed in
the recellularization experiment. Moreover, the recellularization data indicate that high GAG
and total collagen contents do not sufficiently predict cell performance in decellularized
ECM. A test for biocompatibility should therefore always be included in the evaluation of
decellularization strategies.
SDS-decellularized scaffolds have an increased stiffness in comparison to
SDC-decellularized scaffolds, quantified by measuring the E modulus, which again is an
indication of alterations and denaturation in the SDS-treated ECM.
Discussion
111
In conclusion, the initial hypothesis that SDS treatment produces ECM scaffolds of minor
quality was confirmed for decellularization of porcine kidneys by immersion.
SDC-decellularization leads to more native, biologically active porcine kidney scaffolds.
5.2.3 The effect of the temperature on kidney decellularization by immersion
Cell lysis during decellularization disrupts cellular compartments and releases endogenous
proteases and nucleases127. In earlier studies, Nakayama et al. observed better structural
conservation at 4 °C than at 37 °C during decellularization of rhesus monkey kidneys by
immersion in SDS175. Moreover, Higami et al. described higher collagen levels at 4 °C in
the decellularized carotid artery182. It was thus hypothesized that low temperature during
decellularization improves the conservation of cytokines and other functional ECM
components. To evaluate this hypothesis, decellularization was conducted at 4 °C, RT and
37 °C.
Decellularization with SDC or SDS at 4 °C resulted in much higher preservation of the tissue
architecture and improved cell removal compared to RT or 37 °C. RT and 37 °C samples
showed cellular residues especially in the core of the tissue cube, whereas the peripheral area
was decellularized, but the ECM structures were collapsed. In accordance to that,
decellularization approaches using TX-100 led to better results in cell removal at 4 °C than
at RT or 37 °C.
In immersion-decellularization, the peripheral zones of the tissue cubes are naturally
exposed the longest to the detergent. Therefore, ECM damage is highest in these areas. When
the damage is too severe the structures collapse and block the tubes and vessels through
which the detergent can penetrate through the cube, leaving the cores undecellularized. Two
possible modes of action increase the damage at RT and 37 °C in comparison to 4 °C. Firstly,
the Brownian molecule movement increases with temperature and enhances the action of the
detergent183. Secondly, the activity of human enzymes rises with increasing temperature,
peaking at 37 °C184, resulting in a higher activity of endogenous proteases. Proteases, such
as MMPs185–188, digest the ECM, resulting in collapsed peripheral areas. This theory is
supported by the finding, that the content of the proteins collagen, bFGF and VEGF decrease
in the decellularized scaffolds with increasing temperature.
DNA levels decrease with increasing temperatures in SDC, but increase in SDS samples,
when the tissue cubes are not treated with DNase. This effect cannot be solely explained by
Discussion
112
higher detergent action at higher temperatures because the DNA levels do not correlate with
the amount of remaining cellular material. Again, a higher enzyme activity, in this case of
nucleases, is the most probable explanation for the decreasing DNA levels with increasing
temperature. SDS treatment, however, might denature the nucleases. After DNase treatment,
no differences in DNA levels are observable anymore. Ross et al. even utilized these
endogenous nucleases by activating them during decellularization by perfusing rat kidneys
with calcium chloride and magnesium sulfate162.
Summarizing, higher temperatures activate endogenous enzymes that are released during
cell lysis. Nuclease activity supports the decellularization process, however, protease activity
harms the ECM. Decellularization at 4 °C therefore results in better ECM and cytokine
preservation, but in higher DNA levels. Since the preservation of ECM structure and
composition is crucial for later applications of the scaffold, the decellularization by
immersion should be carried out at 4 °C. Lower DNA levels can be achieved by adding a
short DNase digestion step at 37 °C after detergent treatment. This prevents the necessity of
performing the whole decellularization at 37 °C for several days.
5.2.4 Decellularization outcomes by perfusion differ to decellularization
outcomes by immersion
Whole organ decellularization is the basis for whole organ tissue engineering. The vascular
tree of the organ can be utilized to perfuse the decellularization solutions through the organ.
Porcine kidneys are the ideal basis for kidney tissue engineering for transplantation, due to
their similar size compared to human kidneys. Rat kidneys, however, are superior for the
generation of human 3D kidney models, as they require less cells and reagents for
recellularization.
The best condition identified for decellularization of porcine kidney tissue by immersion and
agitation, 1% SDC at 4 °C, was therefore tested in whole organ perfusion-decellularization
of rat kidneys. Additionally, an already published protocol for perfusion-decellularization of
rat kidneys by Song et al.123, based on perfusion at RT with 1% SDS and 1% TX-100, was
applied as comparison. Both protocols were conducted at 4 °C and RT.
Discussion
113
The experiments showed that SDC is not suitable for perfusion-decellularization of whole
rat kidneys. Perfusion with SDC at 4 °C did not completely remove cells and DNA from the
ECM. Increasing the temperature to RT led to better, albeit still incomplete
decellularization., and to less remnant DNA. Hence, the observations of immersion-
decellularization regarding the temperature were confirmed. Perfusion with SDS/TX-100
resulted in complete decellularization and architectural integrity at 4 °C and RT.
Biocompatibility was tested by injecting HUVECs into the renal artery of scaffolds that were
decellularized at RT with SDC or SDS/TX-100. SDS/TX-100 RT scaffolds support higher
cell viability than SDC scaffolds, as shown by histological and metabolic analysis.
Remaining cell debris inside the SDC scaffold possibly hampered perfusion and therefore
the nutrient supply. Moreover, the cell debris could be a reservoir of residual detergents that
harmed the reseeded cells, or the cell debris itself had a negative effect on the cells189,190.
The SDS/TX-100 RT protocol was therefore chosen for all subsequent whole organ
recellularization experiments.
The question arises, why the immersion-decellularization protocol cannot be transferred to
perfusion-decellularization.
Firstly, cell lysis in perfusion-decellularization was not preceded by freezing, thawing and
osmotic shock, as it was carried out with the immersion samples127.
Secondly, immersion-decellularization was optimized with porcine kidneys, while rat
kidneys were used for perfusion-decellularization. As pointed out in 1.3.2, the general
architecture of mammalian kidneys is conserved, however, the tubules and glomeruli are
smaller in rat than in pig. Rat renal tubules have a mean radius of 29 µm121,122. The spherical
SDS micelles have a radius of only 1,5 nm191. Bile salts form even smaller, disc-shaped
micelles129,192. Hence, tubule size is not the direct problem. However, the fluidics for the
transport of decellularization agents and cell debris changed, amplified by the different
techniques the decellularization agents were delivered with193,194.
Lastly, the detergents were applied for 168-240 h in immersion-decellularization, but only
16 h or 120 h for SDS or SDC in perfusion, respectively. Perfusing the detergents through
the vascular tree has the advantage of their highly effective distribution. Therefore, the
exposure to SDS can be drastically shortened in comparison to immersion-decellularization,
which resulted in less damage to the scaffold. In the study by He et al. it was confirmed that
shorter SDS incubation leads to improved kidney scaffold characteristics148, as clearly
Discussion
114
visualized by the scoring system. For SDC, however, the shorter incubation time limited the
clearing of the tissue. To prolong the SDC treatment further is logistically not feasible, as
perfusion-decellularization is a low-throughput system.
Conflicting results regarding the effects of SDS and SDC on decellularization have also been
described in literature126. SDC was successfully applied in the decellularization of heart
valves195,196 or liver177,197,198. For kidney perfusion-decellularization, however, Wang et al.
concluded that SDS is the prefered detergent over SDC177. Ross et al. decellularized rat
kidneys with 4% SDC and 1-10% TX-100 and found that although a higher SDC
concentration increases the cell removal efficiency, it still leads to inconsistent
decellularization results162. In this thesis, further inter-study comparisons for kidney
perfusion-decellularization data were conducted by applying the scoring system to data from
He et al.148 and Caralt et al.144. These comparisons confirmed that SDS is necessary for
perfusion-decellularization of kidneys. Moreover, it was shown that a low SDS
concentration of 0,125% is favorable over higher concentrations.
In conclusion, the optimal conditions for kidney decellularization by immersion and
agitation are not transferable to perfusion. As a result of the comparison conducted in this
study, SDS appears to be the only detergent that effectively decellularizes organs with a high
cell density, such as the kidney, in perfusion conditions. To reduce the inevitable damage to
the ECM by SDS, the conditions of SDS exposure should be carefully chosen. Altogether,
SDS applied at low concentration, for a relatively short period of time and at a low
temperature is advisable.
SDC preserves a more native kidney ECM composition than SDS, but because SDC is less
effective in clearing tissues from cellular material, it can only be applied for decellularization
of thin tissue slices or tissues with low cell densities. Also, when a decellularization
technique is applied that requires long exposure to the decellularization agents, milder
detergents, such as SDC, should be preferred.
Discussion
115
5.3 Generation of an in vitro kidney model by recellularization of
decellularized kidneys
When decellularized kidney scaffolds are transplanted, they are not simply repopulated with
resident cells in vivo. It was shown that cells only scarcely migrate into decellularized kidney
scaffolds that were surgically implanted into a kidney178,199. It is therefore necessary to
recellularize these scaffolds with human cells in vitro. To generate a 3D human kidney model
from decellularized whole rat kidneys, an adequate cell type and cell number has to be seeded
and the cells have to integrate into the scaffold at the correct position.
5.3.1 Successful reendothelialization of the renal vascular tree
The kidney contains three main endothelial cell (EC) populations, each with distinct
phenotypes and functions. ECs in medium and large vessels form a continuous layer.
Especially in arteries the cells are elongated in the direction of the blood flow. Glomerular
endothelial cells, part of the glomerular filtration barrier, are highly fenestrated and covered
by a thick glycocalyx. The endothelial cells of the peritubular capillaries are also fenestrated
and specialized in the reabsorption of solutes from the adjacent tubules200,201. The
incorporation of ECs is thus compulsory for a functional kidney model. Furthermore,
transplantation without a fully repopulated vascular tree triggers blood coagulation even with
anticoagulation treatment, shown in transplantation studies by Orlando et al. and Baptista et
al.202,203. Reendothelialization of the renal vascular tree is therefore an important step in
recellularization.
Human umbilical vein endothelial cells (HUVECs) are primary ECs and a commonly used
in vitro experimental system as they are easy to culture and highly proliferative204,205.
Therefore, HUVECs were seeded into the renal artery of the decellularized kidney and
cultured under perfusion for three days. The perfusion bioreactor successfully supported
their viability as the cells showed metabolic activity over the whole culture period. After
three days, the seeded HUVECs lined the large vessels and capillaries, comparable to the
vessels of native kidneys. However, the fine structure especially in the glomerular capillaries
was not as delicate as in native kidneys. HUVECs, as a venous EC type, might not be the
Discussion
116
best cell type to repopulate these capillaries. Wolburg et al. showed that although HUVECs
were able to form fenestrations in vitro after VEGF stimulation, the magnitude of their
response to that stimulation was much weaker than in ECs that were isolated from
fenestrated capillaries206.
hiPSC-derived cell types often only reach a fetal phenotype in classical 2D cell culture101.
Hence, hiPSC-derived ECs are more plastic than HUVECs and can potentially mature inside
the decellularized scaffold.
Several protocols for EC differentiation from hiPSC have been published142,207,208. The
protocol by Patsch et al. was chosen in this thesis because it is fast, reliable and highly
efficient109. After mesoderm induction, the cells specify into ECs. 98% of the differentiated
cells are double positive for CD31 and CD144, EC marker proteins that are part of the
junctional mechanosensory complex209.
Special focus was laid on the mass expansion of hiPSC-derived ECs, since millions of cells
are needed for recellularization. The highest proliferation rate, stable endothelial marker
expression and cost-effectiveness was achieved in an expansion medium composed of a
commercially available endothelial cell culture medium supplemented with 20% FCS and a
transforming growth factor β (TGFβ) inhibitor that has been shown to maintain the
proliferation and vascular identity of ESC-derived ECs141,210.
hiPSC-derived ECs were seeded via the renal artery into the decellularized kidney. They
successfully reendothelialized the vascular three, since in histology, ECs were found to line
the large vessels, but also the capillaries. The results were comparable to the HUVEC
experiments, although less cells were detected, and to studies by Song et al.123 and Caralt et
al.144.
To date, no kidney recellularization study proved the development of endothelial
fenestrations or the endothelial barrier function. However, an extensive reendothelialization
study in lung hinted that kidney reendothelization could be further improved by fibronectin
coating of the decellularized vessels, combined arterial and venous seeding, co-seeding of
ECs with mesenchymal cells and longer perfusion culture in FCS reduced medium141.
Discussion
117
5.3.2 Inefficient recellularization of the renal parenchyma
hiPSC-derived renal progenitor cells were chosen for the recellularization of the
decellularized kidney parenchyma as they are proliferative and can differentiate into a broad
spectrum of highly specialized kidney cell types. It was hypothesized that the scaffold’s
architecture, mechanical properties, segment-specific ECM composition and the perfusion
culture would induce site-specific maturation of the RPCs, leading to a native-like cell
arrangement and to a functional tissue engineered kidney model.
Renal progenitor cells were differentiated from hiPSCs according to a protocol established
in our lab117. hiPSCs exposed to Activin A, BMP4 and retinoic acid for four days
differentiate into intermediate mesoderm cells. These develop further into renal progenitor
cells after a four-day GDNF treatment. The differentiation is highly efficient as 70-80% of
the cells express SIX2 at day 8. SIX2 is a transcription factor characteristic for the cap
mesenchyme, which is the tissue the nephron develops from. The generated RPCs can be
further directed into various renal cell types including mesangial, proximal tubular, distal
tubular and collecting duct epithelial cells as well as into podocyte precursors117,211. RPCs
were injected into the decellularized kidney scaffold and cultured for 6 days under perfusion
conditions.
RPCs injected into the renal artery did not migrate from the vascular compartment into the
parenchyma as already observed in the reendothelialization experiments. Caralt et al.
published an arterial high-pressure seeding approach. Their work was based on a highly
proliferative, immortalized, human renal tubular epithelial cell line that achieved the highest
cell density in recellularized rat kidneys published to date144. Application of this method
resulted in a higher RPC seeding efficiency but damaged the scaffold. A short trypsin digest
of the vascular tree that was expected to facilitate cell migration from the vascular
compartment into the parenchymal compartment, did not improve the seeding efficiency.
The vascular compartment is separated from the parenchyma by the ECM of the vessels.
Glomerular and peritubular capillaries are only covered by a thin basement membrane, but
the bigger arteries and veins are surrounded by robust ECM layers212. Without an attractant,
the cells will not take on the tremendous effort to migrate through these structures.
Discussion
118
Similarly, cells seeded by injection into the parenchyma with a syringe did not migrate into
the surrounding tubular structures. Moreover, the scaffold structure was disrupted by the
punctures.
Injecting the cell suspension into the ureter dilated the renal pelvis and compressed the renal
papilla, indicating that the cell suspension could neither penetrate into the collecting ducts,
nor further up the nephron. Applying vacuum as published by Song et al.123 only slightly
improved the RPC seeding efficiency.
Coming from the ureter, the nephron is a liquid filled dead end, sealed by the glomerular
basement membrane at the end. Although decellularized ECM is permeable for liquids213,
the injected suspension cannot drain fast enough and dilates the pelvis instead. Moreover,
the tubules in the rat kidney have an average diameter of only 29 µm121. Notably, a paper on
bioprinting proximal tubules confirmed recently that seeding cells into channels below
200 μm in diameter is very challenging111. Hence, the complex architecture of the kidney
makes cell seeding into the scaffold highly inefficient.
Moreover, in contrast to the reendothelialization, all approaches to recellularize the
parenchyma with RPCs resulted in a very low number of attached cells, low viability, low
metabolic activity and detectable cellular debris, hinting at a high sensitivity of
hiPSC-derived RPCs.
Sensitive cell types could be harmed by traces of residual decellularization agents, as it was
shown that these exert a toxicological effect on reseeded cells189,190. Although decellularized
tissues have been extensively washed after detergent treatment, White et al. were able to
detect residual fragments of TX-100, SDC and SDS in decellularized urinary bladder
matrix214. In the here applied SDS/TX-100 perfusion-decellularization protocol, SDS is
efficiently removed from the scaffold by the TX-100 perfusion step129,177. However, traces
of TX-100 could have been still be present in the scaffold and harmed the RPCs.
Shear stress during seeding and perfusion culture is another potentially damaging factor.
Endothelial cells are naturally exposed to high shear stress. Epithelial cells of the kidney are
naturally exposed to much lower shear stress. It is therefore a wrong assumption to perfuse
a not fully reendothelialized scaffold with the same shear stress or flow rate that it would
withstand in the native form. Caralt et al. perfused recellularized rat kidneys with 4 ml/min
and did not observe any shear stress induced damage to the seeded immortalized RTECs144,
although they applied the same flow rate as found in rat kidneys in vivo215,216. In this study,
Discussion
119
the cells were seeded into the scaffold with 2 ml/min and the recellularized rat kidney was
perfused with approximately 0,5 ml/min. Thus, although shear stress was deliberately
minimized in this thesis a damaging effect on the RPCs cannot be excluded, especially in
the syringe seeding experiments.
Lastly, a deficient supply with nutrients or oxygen could have provoked cell death in RPCs.
Arterially seeded HUVECs were located in the vascular tree and therefore had a direct supply
of nutrients and oxygen. RPCs seeded into the parenchyma relied on diffusion of nutrients
and oxygen through the scaffold.
In conclusion, none of the seeding strategies resulted in successful recellularization of the
kidney scaffold. Two possible reasons are the complex architecture of the kidney, which is
characterized by narrow tubules that end in dead ends, and the sensitivity of the hiPSC-
derived RPCs. Neither the cell number, nor their position and arrangement were comparable
to the conditions in the native organ. Even the most efficient seeding strategy only yielded
in 1% of the cell density found in rat kidneys. Moreover, the cells did not arrange in epithelial
structures, but were rather scattered throughout the scaffold. Since the function of the kidney
is highly dependent on its structure, the recellularized scaffolds are not functional. Due to
these poor results, the analysis of the site-specific cell maturation, was not possible.
Song et al. published in 2013 a promising paper on de- and recellularization of rat kidneys.
The bioengineered kidney was produced by seeding primary rat neonatal kidney cells with
vacuum support into the ureter of decellularized rat kidney. Song et al. stated to have
engineered a matured functional kidney construct that excretes rudimentary urine. This
raised the hope of rapid progress in whole organ kidney tissue engineering and fast clinical
translation and laid the base for this thesis123.
Since then, several kidney recellularization studies from other groups followed. Only one
study has reported the repopulation with hiPSC-derived RPCs159, all other studies have used
inadequate cell types for kidney tissue engineering, such as pluripotent stem cells,
immortalized cell lines or primary renal cells of animal origin. Notably, all these studies,
including the above-mentioned work from Song et al.123, were facing the same problems that
were also observed in this study. In general, only fractions of the scaffold were repopulated
in all studies, even when highly proliferative cell types, such as immortalized RTECs144 or
ESCs157,162,217, were seeded. The cells were not uniformly distributed but confined to focal
Discussion
120
areas. Moreover, the cells did rarely arrange in a native-like morphology. Cells were either
scattered over the scaffold or cell masses clogged glomeruli and tubules. Recently, Remuzzi
et al. compared several published recellularization strategies, similar to this study, by seeding
mouse ESCs and confirmed the here described findings213.
Since all the above-mentioned studies worked with different bioreactor setups, cell sources
and seeding conditions, the architecture of the scaffold seems to be the common,
fundamental problem of kidney recellularization.
Song et al. have not published a follow-up paper since 2013, instead their research focus was
retrieved from kidney and transferred to lung and whole limb de- and recellularization106,218.
Furthermore, the Orlando group219 and the Remuzzi group220, two well established research
groups in the field of de- and recellularization, independently published two reviews
recently. Both these reviews conclude that the recellularization of decellularized kidney
scaffolds is still in its early stages and a seemingly impossible task.
It remains to be seen whether it will be possible to further develop the recellularization
method in such a way that it enables the generation of a human kidney model.
5.4 Stiffness and composition of the cell culture surface influence
renal progenitor cell maturation
Classically, hiPSC differentiation protocols rely on the variation of soluble factors in the cell
culture medium. The influence of the ECM on cell differentiation is often disregarded,
although its composition influences the chemical environment of the cells as well. Different
ECM molecules bind to specific integrins, which trigger specific signaling pathways inside
the cell. For example, cells seeded onto a laminin coated cell culture surface maintain a
apical–basal polarity67,102.
Moreover, changes in the mechanical environment influence the phenotype and
differentiation of cells. Engler et al. demonstrated that the ECM elasticity, quantified as
E modulus, directs the lineage specification of mesenchymal stromal cells. Matrices with an
E modulus similar to brain tissue of 1 kPa were found to be neurogenic, whereas matrices
with an E modulus of 100 kPa, were osteogenic221.
Discussion
121
The perfused decellularized kidney provides all these stimuli to the reseeded RPCs. To study
the isolated effects of stiffness and ECM composition on RPC maturation a parallel approach
to the recellularization was established.
hiPSC-derived RPCs were seeded onto PDMS gels with E moduli of 4 kPa, 200 kPa or
2 MPa. The gels were coated with L511, L521 and/or Col (α1)2α2 (IV), three typical
components of the tubular and glomerular basement membranes in the kidney31. The cells
were cultured for six days in renal epithelial cell growth medium, corresponding to the
standard 2D protocol to differentiate RPCs into renal tubular epithelial cells117. The SIX2
expression decreased significantly during these six days, corroborating the ongoing RPC
maturation.
The E modulus of the culture surface showed a clear effect on the differentiation. The AQP1
expression, a marker for RTECs, increased with the stiffness of the culture surface. Whereas
the expression of the podocyte markers PODXL and SYNPO decreased.
Interestingly, collagen IV coating resulted in the lowest AQP1 expression. Laminin coating
proved to be of much higher efficiency for RTEC differentiation than collagen IV.
Narayanan et al. observed a similar trend in their differentiation towards proximal tubular
cells222.
L511 is part of the BM in all renal tubules, whereas L521 is solely expressed in the
glomerular basement membrane. Although the β1 and β2 chain are structurally homologue,
the null mutation of the β2 chain leads to severe proteinuria, which is the leading symptom
of Pierson syndrome. This supported the idea that the β1 and β2 chain must be functionally
distinct and may affect the maturation of glomerular cells50. However, the variation of the
laminin β chain did not affect the RPC maturation. No significantly different marker
expression patterns, nor morphological differences were identified between the L511 and
L521 coatings. This finding is supported by the fact, that the laminin α chain defines, which
integrin binds to the laminin trimer, not the β chain223. Moreover, Suh et al. demonstrated
that the L511 trimer can replace the function of L521 in the GBM. The β1 and β2 chains are
hence not functionally distinct. In vivo, however, β1 cannot compensate for the loss of β2
since its expression is downregulated in podocytes. Therefore, the severe phenotype of the
Pierson syndrome is provoked by a loss of laminin in the GBM in general. The GBM is
Discussion
122
impaired, not the maturation of the cells of the glomerular filtration barrier. Suh et al.’s
results corroborate our data and validate our model224.
The most beneficial condition to enhance renal progenitor cell differentiation into renal
tubular epithelial cells is culturing the cells on a surface with an E modulus of 2 MPa that is
coated with L511, L521 or any combination containing L521. The condition that induces
preferably glomerular cells is culturing the cells on a surface with an E modulus 4 kPa that
is coated with L511 or L521.
These findings prove that it is essential to provide the correct microenvironments to cells in
order to generate a kidney model with mature renal cell types and will help to further improve
differentiation protocols for RPC maturation.
Outlook
123
6 Outlook
The numerous attempts presented in this thesis to recellularize decellularized rat kidneys did
not lead to the generation of a human kidney model; however, firstly, the perfusion
bioreactor that was developed in this thesis supports fully controlled perfusion culture and
decellularization conditions, the decellularization techniques developed and tested in this
thesis produce an ECM based scaffold of highest quality and these scaffolds were
successfully reendothelialized. These technologies can be applied in many other research
approaches.
And secondly, the insights gained in this study, on how difficult cell seeding into highly
complex scaffolds is and on how to steer RPC maturation, will help to identify an alternative
and ultimately successful kidney tissue engineering approach.
Alternative applications of the decellularized kidney ECM include the reseeding of sections
of decellularized kidney tissue by immersion in a cell suspension. These can be applied as a
simple, static model to investigate ECM directed cell differentiation, or the effect of diseased
ECM on cells225.
The reendothelialization of decellularized kidneys can be applied to study the effects of ECM
and perfusion on endothelial cells. Longer culture periods, pulsatile perfusion and co-seeding
with smooth muscle cells and pericytes can be investigated in this system. The functionality
of the endothelium should be verified by proving the impermeability to dextran and by
visualizing the continuous and fenestrated endothelial cell morphologies with electron
microscopy.
Furthermore, the decellularized ECM can be dissolved and used to form hydrogels or surface
coatings. The composition of these hydrogels is much more diverse than mimicked in the
PDMS assay in this study. Therefore, in future studies it is planned to coat the PDMS
surfaces with the decellularized ECM to investigate its effect on RPC maturation. By
separating glomeruli and tubules before decellularization it would be possible to generate
nephron segment-specific hydrogels and to investigate whether the renal ECM promotes full,
site-specific maturation of RPCs. Additionally, the PDMS assay was further developed into
PDMS based geography chips to study the effect of surface curvature and geometry onto
Outlook
124
RPCs. Concave and convex tubular and spherical structures of different sizes on these chips
mimic the tubular and glomerular structures of the kidney. Preliminary results show that it
is possible to steer the RPC maturation with the geometry of the culture surface.
In consideration of the experience gained in this thesis and the assessment of external studies
on kidney de- and recellularization, alternative tissue engineering approaches for the
generation of a human kidney model should also be considered.
3D bioprinting arranges cells, biocompatible materials and supporting components in
complex 3D structures and could one day produce living, functional tissues. The dissolved,
decellularized ECM can also be utilized as a bioink for 3D bioprinting. To date the resolution
of bioprinters is not high enough to print a complex, vascularized kidney model, however,
advances in this technology might facilitate this in the future226.
An alternative to bioprinting and probably the most promising non-scaffold-based kidney
tissue engineering approach are strategies that rely on self-organization of cells.
Self-organization of cells in vivo is used in the blastocyst complementation method. This
method could allow to grow human organs in pigs in the future. Currently, this technique is
still in its early stages and human-animal chimeras face ethical concerns227,228.
Self-organization of cells in vitro is used in the organoid technology. hiPSC-derived renal
progenitors have been able to form tubular and glomerular structures inside organoids.
However, as mentioned before, these structures are to date rather unorganized. The
organoids lack organization since they are solely derived from a metanephric mesenchymal
cell population. Recently it was shown that incorporating ureteric bud cells, which generate
the collecting duct system and organize the kidney geometry, drastically improves these
organoids229,230. If research succeeds in engineering a vasculature in these organoids, for
example by placing the organoids in the perfused, reendothelialized decellularized kidney,
perfusion and cultivation in an advanced perfusion bioreactor, like the one developed in this
thesis, could then mature these organoids into perfusable human kidney models or even into
functional, fully grown human kidneys.
With the ongoing rapid improvements in renal hiPSC differentiation, tissue engineering
techniques and bioreactor design, the successful generation of kidney models for preclinical
testing and even of whole kidneys for transplantation might become reality within the next
decades. The findings of this thesis are an important step towards achieving this goal.
References
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8 Appendix
8.1 Supplemental information
Figure S1: Analysis sequence “Count attached GFP+ cells” in Harmony High-content imaging software
Appendix
137
Figure S2: Analysis sequence “Count DAPI-nuclei on kidney sections” in Harmony High-content
imaging software
Appendix
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8.2 Abbreviations
2D
two-dimensional
3D
three-dimensional
ADH
antidiuretic hormone
AQP1
aquaporin 1
ATP1A1
sodium potassium-pump, subunit alpha-1
bFGF
basic fibroblast growth factor
BM
basement membrane
BMP4
bone morphogenetic protein 4
BSA
bovine serum albumin
cDNA
complementary DNA
CKD
chronic kidney disease
ColIV
collagen IV
COM
communication
CTR
control
CV
control variable
DAPI
4',6-diamidino-2-phenylindole
diH20
distilled water
DNA
deoxyribonucleic acid
dsDNA
double stranded deoxyribonucleic acid
E
error
E modulus
elastic modulus
ECM
extracellular matrix
ECs
endothelial cells
EDTA
ethylenediaminetetraacetic acid
EGF
epidermal growth factor-like
EGM-2
endothelial growth medium 2
EGTA
egtazic acid
ESRD
end stage renal disease
FCS
fetal calf serum
GAG
glycosaminoglycan
GAPDH
glyceraldehyde 3-phosphate dehydrogenase
GBM
glomerular basement membrane
GDNF
glial cell-derived neurotrophic factor
HE
hematoxylin and eosin
hiPSCs
human induced pluripotent stem cells
HLB
hydrophilic-lipophilic balance
HSPG
heparan sulphate proteoglycan
Appendix
139
HUVECs
human umbilical vein endothelial cells
IMCs
hiPSC-derived intermediate mesoderm cells
Lam-1, L111
laminin 111
Lam-10, L511
laminin 511
Lam-11, L521
laminin 521
MBVs
matrix bound vesicles
MMPs
matrix metalloproteinases
Na+/K+-ATPase
sodium potassium-pump
O/N
overnight
PAA
peracetic acid
PDGF
platelet-derived growth factor
PDMS
polydimethylsiloxane
PODXL
podocalyxin like
POMA
poly[octadecene-alt-(maleic anhydride)]
PV
process variable
qPCR
quantitative polymerase chain reaction
RA
renal artery
REGM
renal epithelial growth medium
RNA
ribonucleic acid
RNA18S5
18S ribosomal 5
ROCKi
Rho-associated protein kinase-inhibitor
RPCs
hiPSC-derived renal progenitor cells
RTECs
renal tubular epithelial cells
RT-PCR
reverse transcription polymerase chain reaction
RV
renal vein
SIX2
SIX homeobox 2
SLC12A2
Na-K-Cl cotransporter 1, solute carrier family 12 member 2
SLC12A3
sodium-chloride symporter, solute carrier family 12 member 3
SP
setpoint
SYNPO
synaptopodin
TGFβ
transforming growth factor β
U
ureter
VEGF
vascular endothelial growth factor
WT1
Wilms tumor protein
Appendix
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8.3 List of figures
Figure 1: Anatomy of the human kidney. .............................................................................. 3
Figure 2: Interactions of cells with their surrounding ECM. ................................................. 5
Figure 3: Structure and composition of renal basement membranes..................................... 7
Figure 4: The effect of extracellular matrix properties on the cell ...................................... 10
Figure 5: Development of the mammalian kidney. ............................................................. 13
Figure 6: Human induced pluripotent stem cells ................................................................. 15
Figure 7: Differences between 2D and 3D in vitro tissue models. ...................................... 16
Figure 8: Decellularization of whole rat or pig kidneys ...................................................... 19
Figure 9: Recellularization .................................................................................................. 20
Figure 10: Organ preparation for decellularization of whole rat kidneys by perfusion ...... 36
Figure 11: Schematic setup of the decellularization perfusion bioreactor .......................... 37
Figure 12: Resazurin ............................................................................................................ 43
Figure 13: Schematic setup of the recellularization perfusion bioreactor. .......................... 51
Figure 14: Setup of the perfusion bioreactor. ...................................................................... 52
Figure 15: User interface of the control software for the perfusion bioreactor. .................. 54
Figure 16: Architecture of the control software for the perfusion bioreactor. .................... 55
Figure 17: Block diagram of the pressure feedback loop. ................................................... 57
Figure 18: Step response to pump speed change. ................................................................ 58
Figure 19: Reference-variable response of the control system............................................ 60
Figure 20: Disturbance response of the pressure control system. ....................................... 61
Figure 21: Block diagram of the pH feedback loop. ........................................................... 62
Figure 22: Step response to CO2 change. ............................................................................ 63
Figure 23: Reference-variable response of the pH control system. ..................................... 64
Figure 24: Disturbance response of the pH control system. ................................................ 65
Figure 25: The experimental process of the de- and recellularization of porcine kidneys by
immersion and agitation. ..................................................................................................... 66
Figure 26: Macroscopic and histological analysis of native and SDC-decellularized porcine
kidney cubes at 4 °C, RT and 37 °C. ................................................................................... 68
Figure 27: Macroscopic and histological analysis of SDS-decellularized porcine kidney
cubes at 4 °C, RT and 37 °C. ............................................................................................... 69
Appendix
141
Figure 28: Macroscopic and histological analysis of TX-100-decellularized porcine kidney
cubes at 4 °C, RT and 37 °C. ............................................................................................... 70
Figure 29: Composition analysis of immersion-decellularized matrices ............................ 72
Figure 30: Differentiation scheme of hiPSC-derived intermediate mesoderm cells. .......... 73
Figure 31: Analysis of IMC viability and attachment on immersion-decellularized kidney
sections. ............................................................................................................................... 74
Figure 32: The experimental process of kidney decellularization by perfusion and
biocompatibility testing of the scaffold by reendothelialization. ........................................ 77
Figure 33: Macroscopic and histological analysis of native and perfusion-decellularized rat
kidneys at 4 °C and RT. ....................................................................................................... 78
Figure 34: Composition analysis of perfusion-decellularized matrices. ............................. 80
Figure 35: Characterization of human umbilical vein endothelial cells .............................. 80
Figure 36: Reendothelialization of perfusion-decellularized kidneys by SDC at RT. ........ 81
Figure 37: Reendothelialization of perfusion-decellularized kidneys by SDS/TX-100 at RT
............................................................................................................................................. 82
Figure 38: Comparative biocompatibility testing of perfusion-decellularized kidneys. ..... 83
Figure 39: Generation of the kidney model by de- and recellularization of rat kidneys. .... 86
Figure 40: Differentiation scheme of hiPSC-derived endothelial cells. .............................. 87
Figure 41: Optimization of hiPSC-ECs expansion conditions. ........................................... 88
Figure 42: Arterial seeding of hiPSC-ECs. ......................................................................... 89
Figure 43: CD31+ endothelial cells lined the blood vessels and the glomerular capillaries in
the recellularized kidneys. ................................................................................................... 90
Figure 44: Differentiation scheme of hiPSC-derived RPCs. ............................................... 90
Figure 45: Arterial seeding of RPCs.................................................................................... 91
Figure 46: High-pressure arterial seeding of RPCs. ............................................................ 92
Figure 47: Arterial seeding of RPCs into partly trypsin-digested scaffolds. ....................... 93
Figure 48: Ureter seeding of RPCs without vacuum. .......................................................... 94
Figure 49: Ureter seeding of RPCs with vacuum. ............................................................... 95
Figure 50: Injection of RPCs into the cortex of perfusion-decellularized kidneys with a
syringe. ................................................................................................................................ 96
Figure 51: Quantitative analysis and comparison of seeding strategies. ............................. 97
Figure 52: PDMS gel properties. ......................................................................................... 98
Figure 53: Renal tubular epithelial cell morphology on ECM-coated PDMS .................. 100
Appendix
142
Figure 54: RPC and RTEC gene expression on ECM-coated PDMS ............................... 101
8.4 List of tables
Table 1: Species differences in renal structure .................................................................... 18
Table 2: Cells ....................................................................................................................... 23
Table 3: Reagents ................................................................................................................ 23
Table 4: Consumables ......................................................................................................... 25
Table 5: Kits ........................................................................................................................ 26
Table 6: Primary and secondary antibodies and nucleic acid dyes ..................................... 27
Table 7: TaqMan gene expression assays............................................................................ 27
Table 8: Instruments ............................................................................................................ 27
Table 9: Software and data bases ........................................................................................ 29
Table 10: List of the expansion media for hiPSC-derived endothelial cells ....................... 33
Table 11: Overview of decellularization by immersion and agitation conditions ............... 35
Table 12: SDC protocol conditions for decellularization by perfusion ............................... 38
Table 13: SDS/TX-100 protocol conditions for decellularization by perfusion ................. 38
Table 14: System settings for controller tuning .................................................................. 44
Table 15: PDMS preparations ............................................................................................. 44
Table 16: TaqMan RT Reaction Mix .................................................................................. 45
Table 17: RT-PCR cycling conditions ................................................................................ 45
Table 18: TaqMan qPCR Reaction Mix for a 384-well plate.............................................. 46
Table 19: qPCR cycling conditions ..................................................................................... 46
Table 20: Dehydrating steps before embedding of tissue in paraffin blocks ...................... 46
Table 21: Rehydration of paraffin sections ......................................................................... 47
Table 22: HE staining on rehydrated paraffin sections ....................................................... 47
Table 23: Antigen retrieval treatments for immunofluorescence staining .......................... 48
Table 24: Overview over the technical background of the perfusion bioreactor ................ 51
Table 25: Tuning methods used for adjusting the pressure and pH controller .................... 59
Table 26: Scoring table of immersion-decellularized porcine kidneys ............................... 76
Table 27: Scoring table of perfusion-decellularized rat kidneys ......................................... 84
Table 28: Scoring table of perfusion-decellularized rat and porcine kidneys ..................... 85
Appendix
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8.5 Acknowledgements
Ich möchte mich ganz herzlich bei allen bedanken, die mich während der Durchführung
meiner Doktorarbeit unterstützt haben.
Der größte Dank gilt meinen drei Betreuern am BCRT. Herzlichen Dank an
Dr. Harald Stachelscheid, der mein Dissertationsprojekt ins Leben gerufen hat und mir
immer unterstützend zur Seite stand. Des Weiteren gilt mein Dank Dr. Andreas Kurtz für
die Möglichkeit, in seiner Arbeitsgruppe forschen zu können, sowie seine fachliche
Unterstützung. Frau Prof. Dr. Petra Reinke möchte ich ebenfalls herzlich für ihre
Betreuung danken, insbesondere für das Einbringen der klinischen Perspektive.
In zahlreichen richtungsweisenden, fachlichen Diskussionen, wöchentlichen
Arbeitsgruppenmeetings sowie konstruktiven Mentoring Meetings habe ich durch meine
Mentoren viel Unterstützung erfahren. Sie haben somit entscheidend zum Fortschritt und
Erfolg meiner Arbeit beigetragen und mich in den letzten Jahren zu der Wissenschaftlerin
ausgebildet, die ich heute bin. Herzlichen Dank.
Des Weiteren möchte ich mich bei Prof. Dr. Roland Lauster für seine Betreuung von
universitärer Seite bedanken. Auf den alljährlichen Tagen der Biotechnologie hat er immer
wieder frische Ideen in das Projekt eingebracht.
Großer Dank gilt Michael Westphal, der mit seiner Arbeit den Grundstein für mein
Dissertationsprojekt gelegt hat und mich in viele der verwendeten Methoden eingearbeitet
hat. Ebenso möchte ich mich bei Dr. Ansgar Petersen bedanken, dessen Expertise
essenziell war für die PDMS-Experimente. Su-Jun Oh sowie Cornelia Heckmann danke
ich für die Einführung in die Operationstechniken. Johannes Hellwig und
Dr. Aarón Xerach Herrera Martín möchte ich für die Unterstützung bei den
biomechanischen Messungen danken. Dr. Nora Freyer gilt mein Dank für die technische
Hilfe bei den Glucose- und Lactatmessungen. Herzlichen Dank auch an die Mitglieder der
BIH Stem Cell Core Facility Judit Küchler, Kristin Fischer, Tanja Fisch und Janine
Cernoch für die Bereitstellung der hiPSCs, die Einweisung ins FACSen und die Aushilfe
Appendix
144
mit Materialien, wenn mal etwas gefehlt hat. Des Weiteren danke ich Christian Hennig und
David Holst für die ausgezeichneten LabVIEW Kurse und Hilfestellungen.
Herzlichen Dank an die Mitglieder meiner Arbeitsgruppe Dr. Laura Hildebrand,
Dr. Bella Roßbach, Dr. Krithika Hariharan, Su-Jun Oh, Dr. Nancy Mah, Dr. Imran
Ullah, Ngo Thi Thanh Thao, Enrico Fritsche, Dr. Raed Abu Dawud, Alexandra Lasch
und Lilas Batool. Sie haben mir nicht nur fachlich zur Seite gestanden, konstruktiv
Ergebnisse mit mir diskutiert, Zellfütterungen am Wochenende übernommen oder bei
Misserfolgen ein offenes Ohr für mich gehabt, sondern auch immer den Laboralltag mit
Leben und Freude gefüllt. Ihr habt die letzten Jahre zu einer so schönen Zeit für mich
gemacht.
Es war ein großer persönlicher Gewinn die Promotion als Mitglied der Graduiertenschule
Berlin-Brandenburg School for Regenerative Therapies (BSRT) zu absolvieren. Daher
gilt mein Dank Dr. Sabine Bartosch, der Koordinatorin der BSRT. Die Teilnahme an
zahlreichen Kursen und Retreats, die Möglichkeit dank BSRT-Reisestipendien an
internationalen Kongressen teilzunehmen, sowie die Erfahrung ein eigenes Symposium zu
organisieren hat mich nicht nur wissenschaftlich, sondern auch persönlich wachsen lassen.
Besonderer Dank gilt meinen „BSRT-Klassenkameraden“ Dr. Maria Schneider,
Christos Nikolaou, Dr. Stefan Sieber, Dr. Leila Amini und Constantin Thieme, in deren
Gesellschaft die Kurse, Retreats und Konferenzen zu besonderen Erlebnissen wurden.
Zu guter Letzt möchte ich mich ganz besonders bei meiner Familie und meinen Freunden
bedanken. Ein riesiges Dankeschön geht an meine Eltern Sabine Fischer und
Joachim Fischer, sowie an Dr. Karl Schlumbach, Sebastian Fischer, Alfonso
López Alloza und Vera Florian. Euch allen danke ich dafür, dass ihr mich immer wieder
ermutigt und bestärkt und für wunderbare Ablenkung gesorgt habt. Gemeinsames Wühlen
im Garten am Wochenende oder ackern auf dem Weinberg in Spanien haben mich im
wahrsten Sinne des Wortes immer wieder geerdet. Ich bin euch so dankbar für eure
unermüdliche Unterstützung. Ohne euch wäre es nicht möglich gewesen!