Systems biological analyses of intracellular signal transduction [Elektronische Ressource] / von Stefan Legewie

Stefan Legewie

Sujets

• Biologie

Informations

• Publié par: humboldt-universitat_zu_berlin
• Publié le: 01 janvier 2009
• Nombre de lectures: 12
• Langue: English
• Poids de l'ouvrage: 9 Mo

Extrait

Systems biological analyses
of intracellular signal transduction

D i s s e r t a t i o n

zur Erlangung des akademischen Grades

d o c t o r r e r u m n a t u r a l i u m

( Dr. rer. nat.)

im Fach Biophysik

eingereicht an der


Mathematisch-Naturwissenschaftlichen Fakultät I

der Humboldt-Universität zu Berlin



von

Herrn Diplom-Biochemiker Stefan Legewie
geboren am 31.10.1977 in Aachen



Präsident/Präsidentin der Humboldt-Universität zu Berlin
Prof. Dr. Christoph Markschies

Dekan/Dekanin der Mathematisch-Naturwissenschaftlichen Fakultät I
Prof. Dr. Christian Limberg






Gutachter: Prof. Dr. Hanspeter Herzel
Prof. Dr. Jens Timmer
Prof. Dr. Olaf Wolkenhauer


Tag der mündlichen Prüfung: 31. 10. 2008

































ii








für meine Eltern
















iiiiv Summary

Intracellular regulatory networks involved in the sensing of extracellular cues are crucial to all
living organisms. Signal transduction networks allow unicellular organisms sensing nutrient
availability, finding mating partners and responding to stress. Moreover, intercellular
communication is the fundamental basis for the functioning and homeostasis of multicellular
organisms. Accordingly, many diseases including cancer are caused by deregulation of
signal transduction networks. Extracellular signals are typically transmitted rapidly from the
cell membrane to the nucleus by activation of multi-level enzymatic cascades which
ultimately elicit slow changes in gene expression, and thereby affect the cell fate. These
signalling cascades are highly interconnected, thus giving rise to complex networks, that are
hard to understand intuitively. In this thesis, a combination of kinetic modeling and analysis of
quantitative experiments is applied to get insights into the principles of intracellular signalling.

In the first part, the dynamics of enzymatic signalling cascades involved in transducing
signals from the cell membrane to the nucleus are investigated. The Ras-MAPK cascade
plays a central role in various physiological processes such as cell cycle progression, cell
differentiation and cell death, and mutational cascade activation appears to be crucial for
cancer development. Overexpression of wildtype Ras is also frequently observed in tumours,
but its functional relevance remains unclear. By analysis of an experimentally validated
kinetic model of Ras signalling, it is shown in Chapter 2 that the basal state MAPK signalling
can be completely insensitive towards overexpression of the uppermost cascade member
Ras. Thus, the simulations reveal a “kinetic tumour suppression effect” inherent to the Ras
(de)activation cycle, and also explain experimental studies showing that overexpression
events within the MAPK cascade, though phenotypically silent in isolation, frequently
cooperate to bring about strong cellular deregulation (“oncogene cooperation”). In Chapter 3,
it is analysed how an experimentally validated MAPK cascade model responds to more
physiological, transient inputs and converts them into an all-or-none, irreversible cell fate
decision. More specifically, it is shown that bistability arises in the core MAPK cascade by a
previously unrecognised enzyme sequestration effect that establishes a hidden positive
feedback loop. Chapter 4 is focussed on the proteolytic caspase cascades controlling
apoptosis, a form of cell suicide activated in response to extracellular stress. The simulations
suggest an unanticipated role for inhibitors of apoptosis proteins (IAPs): Simultaneous
inhibition of multiple caspases by IAPs can result in strong positive feedback regulation, and
may thus be essential to establish all-or-none and irreversible initiation of cell death.

Cellular commitment to a new fate typically requires ongoing extracellular stimulation and/or
intracellular signalling for several hours, so that the long-term dynamics of signalling
cascades are important for cellular responses. In the second part of the thesis, it is
investigated how slow signal-induced changes in gene expression feed back into the
signalling network and modulate its dynamical activation pattern. In Chapter 5, the general
design principles underlying transcriptional feedback regulation of mammalian signalling
pathways are investigated by analysing the stimulus-induced gene expression profiles of 134
intracellular signalling proteins. It turns out that transcriptional feedback regulation occurs in
each of the five signalling cascades considered, and that negative feedback strongly
dominates over positive feedback. Moreover, negative feedback exclusively occurs by
transcriptional induction of a subgroup of signal inhibitors, termed rapid feedback inhibitors
(RFIs), while downregulation of signal transducers plays no role. Systematic analysis of
mRNA and protein half-lives reveals a remarkable separation of the signalling network into
flexible and static parts: transcriptionally regulated RFIs are unstable at the mRNA and
protein level, while other signalling proteins are generally stable. Kinetic modelling, also
presented in Chapter 5, is employed to get insights into the functional implications of RFI-
mediated transcriptional feedback regulation. In Chapter 6, transcriptional feedback
regulation of TGFβ signalling via Smad transcription factors is analysed in more detail in
primary hepatocytes to confirm the physiological relevance of transcriptional feedback
vregulation at the protein level. The TGFβ family of cytokines constitute major inhibitors of cell
growth, and accordingly they play important roles in various physiological and pathological
processes including development, tissue homeostasis, tissue regeneration, and cancer.
Genome-wide microarray analyses and protein measurements in response to TGFβ
stimulation (presented in Chapter 6) suggest that the SnoN oncoprotein is the central
transcriptional feedback regulator in primary mouse hepatocytes. A mathematical model
including TGFβ-induced Smad signalling and SnoN-mediated feedback is fitted to
experimental data obtained under various stimulation conditions, and predictions derived
from the model are then quantitatively confirmed in primary hepatocytes isolated from SnoN
knock-out mice. The modelling results in Chapter 6 mechanistically explain how a small pool
of SnoN proteins can efficiently regulate a much larger pool of Smad proteins, and further
support the relevance of transcriptional negative feedback regulation in signal transduction.

Cells face a specificity problem as different extracellular stimuli frequently engage the same
set of intracellular signalling pathways even though they elicit completely different biological
responses. Experimental evidence suggests that stimulus-specific biological information is
frequently encoded in the quantitative aspects of stimulus-specific activation kinetics (e.g.,
signal amplitude and/or duration). If biological information is encoded in the quantitative
characteristics of intracellular signals, proper cell fate decisions require that the downstream
gene expression machinery is able to accurately decode signal amplitude and/or duration.
Part III of this thesis deals with such decoding of upstream signals by the gene expression
machinery, and thus represents a first step towards more integrated systems biological
models that include both, upstream signal transduction and downstream phenotypic
responses such as cell growth. The results presented in Section 7 identify competitive
inhibition and regulated degradation as mechanisms that allow intracellular regulatory
networks to efficiently discriminate transient vs. sustained signals. More specifically, a
combination of mathematical modelling and quantitative experimental analyses reveals that a
recently discovered small non-coding RNA, IsrR, establishes a pronounced delay and
duration decoding in the cyanobacterial gene expression response towards iron stress. In
other words, it is shown that the small non-coding RNA, IsrR, restricts the potentially harmful
and costly expression of late-phase stress proteins to severe, prolonged and ongoing stress
conditions. Many of the downstream target genes induced by signalling pathways are
transcription factors, thus giving rise to a complex transcriptional regulatory network.
Therefore, signal decoding at the level of gene expression cannot be fully understood by
insights into the functioning of small transcriptional regulatory motifs, but additionally requires
integrated analyses of multiple transcription factors. In Chapter 8, a recently proposed
reverse engineering approach, called modular response analysis (MRA), is applied to derive
the topology of an oncogenic transcription factor network from high-throughput