Download Catching signals surfing the net

You are cordially invited to the (UvA/VU) Systems Biology seminar:
Catching signals surfing the net
By Dr. Boris N. Kholodenko
Systems Biology Ireland, University
College Dublin, Belfield, Dublin, Ireland
date:
Thursday 6 April 2017
time:
12h15–13h15
venue:
O|2-building, De Boelelaan 1108,
O|2 Auditorium 00E70
host:
Hans Westerhoff, [email protected]
Professor, Microbial Physiology, VU Amsterdam
Systems Biology Seminar series Coordinator: Matteo Barberis (UvA)
Abstract
The advancements in “omics” (proteomics, genomics, and metabolomics)
technologies have yielded large inventories of genes, transcripts, proteins,
and metabolites. The challenge is to find out how these entities work
together to regulate cellular responses to external and internal cues.
Computational models provide insight into the intricate relationships
between stimuli and responses, revealing mechanisms that enable networks to
amplify signals and reduce noise and generate discontinuous bistable
dynamics or oscillations. In this talk, I review experimental and
theoretical progress towards better understanding of how the cellular
functions are encoded by the dynamics of signalling and gene networks and
how the design features of networks specify biological decisions (1,2). I
focus on (i) how graded, analogue signals from growth factor receptors can
be converted into diverse patterns of mitogenic and survival signalling,
which are further decoded by transcriptional circuits to create discrete,
digital outputs leading to specific cell-fate decisions (3,4); and (ii) how
competing protein interactions with phosphorylation-controlled affinities
create switches between signalling fluxes through mitogenic RAF-1/MEK/ERK
and proapoptotic MST2/LATS/YAP pathways, which coordinate cell-fate
decisions (5). I show that drug resistance resulting from dimerization of
kinases, such as BRAF/CRAF, JAK2 and others can be explained by allosteric
inhibitor effects and the emergence of different drug affinities between
free kinase monomers versus dimers (6). This analysis extends to kinase
homo- and heterodimers, allows for their symmetric and asymmetric
conformations and predicts how thermodynamic factors influence dose-response
dependencies. I show how two inhibitors ineffective on their own when
combined can abolish drug resistance at lower doses than either inhibitor
applied alone (7).
Selected Literature
1. Kolch W, Halasz M, Granovskaya M, Kholodenko BN. The dynamic control of
signal transduction networks in cancer cells. Nature Reviews Cancer 15,
515-527 (2015).
2. Kholodenko BN. Cell-signalling dynamics in time and space, Nature Reviews
Molecular Cell Biology 7, 165-176 (2006).
3. Nakakuki T et al. Ligand-specific c-Fos expression emerges from the
spatiotemporal control of ErbB network dynamics, Cell 141, 884-896
(2010).
4. Kholodenko B, Yaffe MB, Kolch W. Computational approaches for analyzing
information flow in biological networks. Science Signaling 5, re1
(2012).
5. Romano D. et al. Protein interaction switches coordinate Raf-1 and
MST2/Hippo signalling. Nature Cell Biology 16, 673-684 (2014).
6. Kholodenko BN. Drug Resistance Resulting from Kinase Dimerization Is
Rationalized by Thermodynamic Factors Describing Allosteric Inhibitor
Effects. Cell Reports 12, 1939-1949 (2015).
7. Byrne KM et al. Bistability in the Rac1, PAK, and RhoA Signaling Network
Drives Actin Cytoskeleton Dynamics and Cell Motility Switches. Cell
Systems 2, 38–48 (2016).