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The 9Th International Conference on Systems Biology ICSB2008 ICSB2008 ICSB2008 The 9th International Conference on Systems Biology The 9 th International Conference on Systems Biology on Systems Conference International Abstract book Abstract book www.icsb-2008.org www.informtrycket.se Table of Contents ICSB 2008 Abstract no Page Plenary Sessions 5 Opening session P-01 – P-02 6 Plenary session 1: Network biology P-03 – P-06 6 Plenary session 2: Understanding and curing diseases P-07 – P-10 7 Plenary session 3: Cell regulation P-11 – P-14 8 Plenary session 4: From cell to organ to organism P-15 – P-18 9 Plenary session 5: New approaches to biotechnology P-19 – P-22 9 Plenary session 6: Genetic variation and evolution P-23 – P-26 10 Plenary session 7: Future challenges P-27 – P-29 11 Dedicated Orals 13 Dedicated session 1-1: Cell-regulation – metabolism DS1-1-01 – DS1-1-08 14 Dedicated session 1-2: Standards and repositories DS1-2-01 – DS1-2-06 16 Dedicated session 1-3: Drug discovery DS1-3-01 – DS1-3-08 18 Dedicated session 1-4: Plant systems DS1-4-01 – DS1-4-06 20 Dedicated session 2-1: Cell-regulation – signalling DS2-1-01 – DS2-1-08 22 Dedicated session 2-2: Modelling approaches DS2-2-01 - DS2-2-08 25 Dedicated session 2-3: Diagnostic markers and complex diseases DS2-3-01 - DS2-3-08 27 Dedicated session 2-4: Microbial systems DS2-4-01 - DS2-4-08 29 Dedicated session 3-1: Cell-to-cell variation DS3-1-01 - DS3-1-09 32 Dedicated session 3-2: Synthetic biology DS3-2-01 - DS3-2-08 34 Dedicated session 3-3: Software tools DS3-3-01 - DS3-3-08 36 Dedicated session 3-4: Model driven experimental planning DS3-4-01 - DS3-4-08 39 Arenas 43 Arena A-01 - A-55 44 Dedicated Posters 61 Dedicated session 1-1: Cell-regulation – metabolism DS1-1-09 - DS1-1-70 62 Dedicated session 1-2: Standards and repositories DS1-2-08 - DS1-2-19 79 Dedicated session 1-3: Drug discovery DS1-3-12 - DS1-3-27 83 Dedicated session 1-4: Plant systems DS1-4-09 - DS1-4-33 86 Dedicated session 2-1: Cell-regulation – signalling DS2-1-09 - DS2-1-126 92 Dedicated session 2-2: Modelling approaches DS2-2-09 - DS2-2-153 125 Dedicated session 2-3: Diagnostic markers and complex diseases DS2-3-09 - DS2-3-24 163 Dedicated session 2-4: Microbial systems DS2-4-09 - DS2-4-45 167 Dedicated session 3-1: Cell-to-cell variation DS3-1-10 - DS3-1-19 176 Dedicated session 3-2: Synthetic biology DS3-2-10 - DS3-2-19 178 Dedicated session 3-3: Software tools DS3-3-09 - DS3-3-62 180 Dedicated session 3-4: Model driven experimental planning DS3-4-09 - DS3-4-25 195 Other session OS-02 - OS-50 200 Author Index 213 ICSB 2008 3 Plenary Sessions Plenary Sessions Opening session Plenary session 1: Network biology P-01 P-03 Networks from experiments: combinatorial perturbation of Understanding regulatory circuitry through expression- cancer pathways profile phenotypes Sander, Chris Holstege, Frank Computational and Systems Biology, Memorial Sloan Kettering University Medical Center Utrecht, Physiological Chemistry, Cancer Center, New York, United States Utrecht, Netherlands Sessions Plenary We present a novel method for deriving network models from The availability of whole genome sequences and the parallel molecular profiles of perturbed cellular systems. The network development of various high-throughput techniques is making models aim to predict quantitative outcomes of combinatorial it possible to analyze and understand regulatory processes perturbations, such as drug pair treatments or multiple genetic in a systematic manner. In the long-term, this will lead to the alterations. Mathematically, we represent the system by a set development of genome control maps, exhaustive wiring of nodes, representing molecular concentrations or cellular diagrams which describe in intricate detail the role of any processes, a perturbation vector and an interaction matrix. After regulatory factor towards regulation of every single gene. We are perturbation, the system evolves in time according to differential systematically generating DNA microarray mRNA expression- equations with built-in non-linearity, similar to Hopfield networks, profiles of targeted mutations in components of the signaling capable of representing epistasis and saturation effects. For a and transcription machinery in the yeast S. cerevisiae in order particular set of experiments, we derive the interaction matrix to uncover new regulatory mechanisms. A previous pilot study by minimizing a composite error function, aiming at accuracy of which focused on the coregulatory Mediator complex has prediction and simplicity of network structure. To evaluate the shown the feasibility of interpreting such expression-profiles for predictive potential of the method we performed twenty-one structure-function analyses, discovering new regulatory pathways, drug pair treatment experiments in a human breast cancer cell uncovering epistasis and pin-pointing the precise effects of line (MCF7) with observation of phospho-proteins and cell cycle regulatory protein modifications on transcription. We have markers. The best derived network model rediscovered known increased the throughput of this approach by extensive robotic interactions and contained interesting predictions. Possible automation and have improved the accuracy and precision of applications include the discovery of regulatory interactions, the microarray technology in various ways, using external control design of targeted combination therapies, and the engineering calibration standards to assess improvements. The results of of molecular biological networks. (Models from experiments: expression-profiling mutants in protein kinases, components of combinatorial drug perturbations of cancer cells, S Nelander, WQ the ubiquitin system as well as several global transcription factor Wang, B Nilsson, QB She, C Pratilas, N Rosen, P Gennemark, C complexes will be presented. Sander, MSB, in press). P-04 P-02 Global mapping of the yeast genetic interaction network Cryoelectron tomography: From molecules to systems Boone, Charlie Baumeister, Wolfgang University of Toronto, Banting and Best Department of Medical Max-Planck-Institute of Biochemistry, Martinsried, Germany Research, Toronto, Canada Electron Tomography (ET) is uniquely suited to obtain 3-D images Objective: To examine yeast genetic interactions quantitatively on of large pleiomorphic structures. While the principles of ET have a global scale, to generate a functional wiring diagram of the cell. been known for decades, its use has gathered momentum only Results: We are examining combinatorial genetic perturbations in recent years. Technological advances have made it possible on a global scale by Synthetic Genetic Array (SGA) analysis. to develop automated data acquisition procedures. This, in turn, We developed a strategy for deriving precise single and double allowed to reduce the total electron dose to levels low enough mutant fitness estimates from SGA genetic interaction screens. for studying radiation sensitive biological materials embedded in We demonstrate the utility of a whole genome catalog of single vitreous ice. As a result, we are now poised to combine the power mutant fitness estimates for assessing the global network of yeast of high-resolution 3-D imaging with the best possible preservation genetic interactions. of the specimen. Conclusions: We show that proper strategies for estimating ET of frozen-hydrated prokaryotic cells or thin eukaryotic cells fitness can yield quantitative genetic interactions on a large-scale. provides 3-D images of macromolecular structures unperturbed Clustering of quantitative genetic interaction profiles defines gene and in their functional environment at molecular resolution (2-4 and pathway function, complementing the information derived nm). Such tomograms contain vast amounts of information; from protein-protein interaction maps. The resultant network essentially they are 3-D images of the cell’s proteome and they provides global view of the pathways that buffer one another and should ultimately enable us to map the spatial relationships of a template for studying the conservation of genetic interactions. macromolecules in a cellular context. However, it is no trivial task to retrieve this information because of the poor signal-to- P-05 noise ratio of such tomograms and the crowded nature of the cytoplasm. Advanced pattern recognition methods are needed for Casting a net for kinases - systematic discovery of In Vivo detecting and identifying specific macromolecules based on their phosphorylation networks structural signature. Provided that high- or medium-resolution Linding, Rune1; Juhl Jensen, Lars2; Ostheimer, Gerry3; Bork, structures of the molecules of interest are available, they can Peer2; Yaffe, Mike3; Pawson, Tony4 be used as templates for a systematic interrogation of the 1ICR, Network & Systems Biology Team, London, United tomograms. Once the challenges of obtaining sufficiently good Kingdom; 2EMBL, Heidelberg, Germany; 3MIT, Boston, United resolution and comprehensive libraries of template structures States; 4SLRI, Toronto, Canada become available, we will be able to map the supramolecular landscape of cells systematically. Directionality in protein signalling networks is due to modulated protein-protein interactions and is fundamental for proper signal progression and response to external and internal cues. This property is in part enabled by linear motifs embedding post- translational modification sites. These serve as recognition sites, guiding phosphorylation by kinases and subsequent binding of modular domains (e.g. SH2 and BRCT). Characterisation
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