A systems science view on cell death signalling [Elektronische Ressource] = Eine systemwissenschaftliche Betrachtung der Zelltod-Signaltransduktion / vorgelegt von Thomas Eißing

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• Biologie

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• Publié par: universitat_stuttgart
• Publié le: 01 janvier 2008
• Nombre de lectures: 12
• Langue: English
• Poids de l'ouvrage: 6 Mo

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A Systems Science View on Cell Death Signalling
Eine systemwissenschaftliche Betrachtung der
Zelltod-Signaltransduktion
Von der Fakultät Maschinenbau der Universität Stuttgart
zur Erlangung der Würde eines Doktoringenieurs (Dr.-Ing.)
genehmigte Abhandlung
vorgelegt von
Thomas Eißing
aus Dorsten-Wulfen
Hauptberichter: Prof. Dr.-Ing. Frank Allgöwer
Mitberichter: Dr. sc. techn. Eric Bullinger
Mitberichter: Prof. John Lygeros, Ph.D.
Mitberichter: Prof. Dr. rer. nat. Peter Scheurich
Eingereicht am: 18. Juni 2007
Tag der mündlichen Prüfung: 25. Oktober 2007
Institut für Systemtheorie und Regelungstechnik
Universität Stuttgart
2007iiiii
Preface and Acknowledgements
The results described in this thesis were developed during my time as a research assistant at the
Institute for Systems Theory and Automatic Control (IST) in Stuttgart. The work describes an
interdisciplinary approach to address and solve biological questions. Especially because of this
interdisciplinary character, it was very helpful to receive help and advise from experts in the re-
spective fields. Therefore, I would like to express my sincere thanks to the many colleagues who
contributed in various ways to this thesis, highlighting the following:
First of all, I would like to thank my teachers in the doctoral exam committee, not only for the in-
volved work as such. Frank Allgöwer, professor at and head of the IST, for giving me the opportu-
nity to work at his institute and explore scientific fields that were unfamiliar to me at the beginning
of my thesis. His blend of support, guidance and freedom were crucial for the development of the
thesis. Eric Bullinger, Habilitant at the IST and later on also lecturer at the Hamilton Institute at
the National University of Ireland and then Strathclyde University in Scotland, for advising and
helping me in many aspects, especially related to mathematical and computational issues. Further,
my time with him at the Hamilton Institute was very helpful in finishing the thesis. John Lygeros,
professor at the Institute of Automatic Control at ETH Zürich, for his interest in and excellent
input on my thesis. Peter Scheurich, professor at the Institute of Cell Biology and Immunology in
Stuttgart, for his full support and guidance throughout the years. Not only his advice on biological
aspects are much appreciated, and without him I would likely not have entered systems biology.
Several additional people were very helpful in the development of this thesis. These are graduate
students whom I (co-)supervised and colleagues from Stuttgart, which I would like to thank a
lot. Birgit Schöberl, and her supervisor Prof. Ernst-Dieter Gilles, were crucial in the initialization
of the project that also gave rise to my thesis. The contributions of Holger Conzelmann were
significant, especially in the early phase of my thesis. The joint work with Steffen Waldherr and
Madalena Chavez towards the end of my doctoral studies were pleasant and fruitful, opening up
new roads especially on the methodological side. The work of Monica Schliemann is providing
a great perspective for the project. Carla Cimatoribus, Christian Ebenbauer, Cedric Gondro, Kai
Heussen, Philipp Rumschinski, and Thomas Sauter contributed on interesting side aspects of this
thesis.
Further, I would like to thank all my colleagues and friends at the IST, for creating an excellent
and very enjoyable atmosphere to work (and partly live) in, and for all the “little” help on my way.
This thanks extends to the people from the SysBio group in Stuttgart.
I also would like to acknowledge the financial help of the funding agencies supporting the project
framework this thesis is part of, especially the Deutsche Forschungsgemeinschaft (DFG).iv PREFACE AND ACKNOWLEDGEMENTS
Abschließend möchte ich meiner Familie und meinen Freunden danken. Im Besonderen meiner
Freundin Britta für ihr Verständnis für ein doch leicht eingeschränktes Privatleben während der
Promotionszeit und ihren Beistand, sowie die ausgleichende und erfüllende Mitgestaltung der
verbliebenen Zeit. Meinen Eltern für ihr Vertrauen und ihre Unterstützung, die erst ein Studium er-
möglicht haben. Und meinen Schwestern, ohne deren Vorbildfunktion ich eventuell erst gar nicht
auf die Idee gekommen wäre zu studieren.
Stuttgart, January 2008 Thomas Eißing
“What is life?”
We must therefore not be discouraged by the difficulty of interpreting life
by the ordinary laws of physics. For that is what is to be expected from the
knowledge we have gained of the structure of living matter. We must be
prepared to find a new type of physical law prevailing in it. Or are we to term
it a non-physical, not to say a super-physical law?
– Erwin Schrödinger (1944)v
Contents
Abstract vi
Deutsche Kurzfassung (German summary) vii
1 Introduction 1
1.1 Systems biology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
1.2 About this thesis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2 Cell Death as a Robustly Bistable System 9
2.1 Apoptosis – programmed cell death . . . . . . . . . . . . . . . . . . . . . . . . . 9
2.2 Systems biology of apoptosis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.3 Summary and outline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
3 Modelling and Bistability of Simple Proteolytic Networks 23
3.1 Model overview and notation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
3.2 Steady state and bistability analysis . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.3 Summary and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4 Modelling and Bistability of the Direct Apoptotic Pathway 35
4.1 Models of receptor induced apoptosis . . . . . . . . . . . . . . . . . . . . . . . . 35
4.2 Bistability evaluation of the basic core model . . . . . . . . . . . . . . . . . . . . 40
4.3 Model extension and simulation studies . . . . . . . . . . . . . . . . . . . . . . . 44
4.4 Summary and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5 Sensitivity and Robustness Aspects 52
5.1 Sensitivity of the apoptosis model . . . . . . . . . . . . . . . . . . . . . . . . . . 52
5.2 A Monte Carlo approach to approximate a bistable region . . . . . . . . . . . . . . 60
5.3 Basic ultrasensitivity mechanisms are similarly robust . . . . . . . . . . . . . . . . 65
5.4 Model extension by CARPs increases robustness . . . . . . . . . . . . . . . . . . 69
5.5 Summary and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
6 Stochastic Influences 80
6.1 Stochastic simulations and inhibitors as noise filters . . . . . . . . . . . . . . . . . 80
6.2 Kinetic parameter and input distributions . . . . . . . . . . . . . . . . . . . . . . . 84
6.3 Summary and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
7 Conclusions 87
7.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
7.2 Perspective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
Bibliography 95Abstract
This thesis provides new insight into cellular signal transduction by integrating biological knowl-
edge into mathematical models, which are subsequently analysed using systems theoretic meth-
ods. Signal transduction has been dissected using molecular and genomic approaches providing
exciting insight into the biochemistry of life. However, a detailed understanding of its dynamic
properties remains elusive. The application of systems science ideas to biology is promising to
put the pieces of molecular information back together, as important properties of life arise at the
system level only. For example, certain signalling pathways convert graded input signals into all-
or-none output signals constituting biological switches. These are implicated in cellular memory
and decisions. One such decision is whether or not to undergo programmed cell death (apoptosis).
Apoptosis is an important physiological process crucially involved in the development and ho-
moeostasis of multicellular organisms. Switches, such as in apoptosis, can be represented by ordi-
nary differential equation models showing bistable behaviour. Different biochemical mechanisms
generating bistability in reaction schemes as encountered in apoptosis are presented and compared
in this thesis. Bifurcation studies reveal structural and parametric requirements for bistability. In
combination with reported kinetic information, inconsistencies in the literature view of apopto-
sis signalling in humans are revealed. An additional regulatory mechanism is proposed, which
is now supported by experimental evidence. Extended robustness analyses indicate that the cell
has achieved a favourable robustness-performance trade-off, imposed by network structure and
evolutionary constraints. On the one hand, inhibitors of apoptosis function as noise filters and re-
duce variability caused by the stochastic nature of reactions. Further, qualitative properties such as
bistability are comparably robust to parameter changes supporting proper decisions. On the other
hand, quantitative aspects are comparably sensitive. This allows for variability in a population,
as observed