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Systems of Life - Systems Biology

Systems of Life - Systems Biology. Network Activities on Systems Biology Hepato Sys International Initiatives. Presentation by Gisela Miczka 1 , Roland Eils 2 and Siegfried Neumann 3

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Systems of Life - Systems Biology

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  1. Systems of Life - Systems Biology • Network Activities on Systems Biology • Hepato Sys • International Initiatives Presentation by Gisela Miczka1, Roland Eils2 and Siegfried Neumann3 1Projektträger Jülich, Jülich, Germany  2German Cancer Research Center, Heidelberg, Germany 3MERCK KGaA, Chemical Section R+D, Darmstadt, Germany NiSIS Symposium, Portugal, October 2005

  2. Outline • Hepato Sys – The German Initiative on Systems Biology of Human Hepatocytes • The Design of the Programme • Goals, Structure and Projects • Coordination and Project Management, Websites • B. International Initiatives in System Biology • Systems Biology for Drug Research • International Crosslinks • Commercial Suppliers

  3. 2001: How to establish a BMBF funded national research network on Systems Biology Start of the „design-process“: Discussion forum with a multidisciplinary team of 9 leading scientists to develop a funding strategy. The key criteria are • medium to long term research programme • synergy with existing BMBF funded research programmes in Genomics and Proteomics • considers the international status of the art • reckognizes international standards and contributes to them

  4. Expert panel structuring thematic priority recommendations March 2001 May July September November December 2001 elicit thematic topic funding- strategies core expert panel (9) WS 1 WS 2 WS 3 WS 4 documentation informations external expert panel (>70) „Systems of Life - Systems Biology“ data-screening, conferences, interviews The Design-Process

  5. Goal of the Systems Biology Initiative on Hepatocytes (HepatoSys) The long-term goal of this systems biology approach is to understand the dynamic processes in a human cell and to build up mechanism-based mathematical models of these processes in order to predict the behaviour of the system under defined conditions.

  6. Aim to overcome the obstacles in order to do systems biology on a medically relevant cell type. ! Challenges • high complexity of mammalian cells • human diffentiated cells are not easy to handle and not easy to cultivate while keeping differentiation and metabolic properties simular to in vivo living cells • the mathematical tools for modelling of cellular dynamics and • systems analysis basically are not developed for complex systems

  7. The Approach • Set up an interdisciplinary competence network linking bioscience with computer science, mathematics and engineering sciences • Start with studies on defined biological functions • Establish standardized cells, methods, and tools

  8. Biology Tools (HTS) biological models generation of quantitative data, anlysis of functional relations; tool development modelling (study on regulation, structure, robustness, etc. of system) Systems Engineering Systemic Behaviour Algorithms Software Databases Bioinformatics Mathematics establishment of databases, development of in silico models and software Systems Biology

  9. Why Hepatocytes? Attractivity • central functions in metabolism (for lipids, carbohydrates, amino acids …) • central role in the uptake and conversion of drugs (transport, metabolic conversions, detoxification ...) • regeneration ability i. e. high impact on problems in pharmacology and pathophysiology

  10. Structure of the National Competence Network HepatoSys Steering Committee Collaborative Network “Detox/Dediff.” Collaborative Network “Regeneration” Coordinating Committee Project Management Platform Cell biology Platform Modeling

  11. Members of the Steering Committee Prof. Dr. Dieter Oesterhelt, MPI for Biochemistry Munich (chairman) Dr. Roland Eils, DKFZ Heidelberg Prof. Dr. Joseph Heijnen, Technical University of Delft, NL Prof. Dr. Karl Kuchler, Institute for Medical Biochemistry, University of Wien, AU Prof. Dr. Siegfried Neumann, Merck KGaA Darmstadt, Senior Consultant R+D Prof. Dr. Hans V. Westerhoff, Molecular Cell Physiology & Mathematical Biochemistry, BioCentrum Amsterdam, NL

  12. Facts on the Starting Phase • call for project proposals December 2001 • number of proposals 40 • start of the research work January 2004 • under this programme • first funding period 15 Mio. € /3 years • collaborative projects 2 • platform projects: • cell biology 3 • modeling 3 • number of partners 25

  13. The Project Committee on HepatoSys • Dr. Jens Timmer, University Freiburg (chairman) • Prof. Dr. –Ing. Matthias Reuss, University Stuttgart • Prof. Dr.-Ing. Ernst-Dieter Gilles, MPI for Komplex Technical Systems, Magdeburg • Prof. Dr. Augustinus Bader, Biomedizinisch- • Biotechnologisches Zentrum, Leipzig

  14. Main Objectives of HepatoSys Network on detoxification and dedifferentiation in hepatocytes (Speaker: Prof. Reuss, Univ. Stuttgart-Hohenheim) Network on regeneration of hepatocytes(Speaker: Dr. Jens Timmer, Univ. Freiburg) Platform Cell biology: Development of new cells, of optimized culture conditions, of high throughput technology and supply of cells for the projects in the national network (Speaker: Prof. Bader, Univ. Leipzig) Platform Modeling: Development of bioinformatics and mathematical tools for data management, data handling etc. and service for the projects of the national network(Speaker: Prof. Gilles, MPI Magdeburg)

  15. The Network on Detoxification / Dedifferentiation • Detoxification • Cytochrome P 450 isoforms • Molecular dynamics • Kinetic experiments • Polymorphisms • Dedifferentiation • Change of metabolic pathways during dedifferentiation

  16. The Network on Regeneration • Background • Liver regeneration is a highly regulated process • Goal • Understanding the pathways involved • Method • Data-based mathematical models • Long term goal • Support development of liver cell lines

  17. The Cell Biology Platform • Distributing Standardized Cell Material • Primary hepatocytes (man, mouse, rat) • Isolation protocol, culturing, starving & stimulation • following SOPs • Developing Human Cell Lines Based on • Conditionally immortalized cells • Somatic stem cells • Bioreactors with controlled microenvironment

  18. The Modeling Platform • Work out concepts on central data management • Develops algorithms and software for modeling • Supply project partners of the biology networks with project-specific tools in systems theory • Develop integrated systems biology research on their own concepts

  19. Geographic Distribution of the Projects

  20. Coordination of the Competence Network Systems Biologe • Secretarial office for the BMBF Funding Initiative „Systems • for Life – Systems Biology“ at University of Freiburg (Dr. Timmer‘s office) • Flyer, Brochures, Articles, Poster ... • Webpages, Internet Representation ... • Public Relation with Journalists and Media • Conference Visits and Reports • Scientific Coordination of Interdisciplinary Research • Groups

  21. Project Management for the Competence Network Systems Biology • Workshop – Partnering, Kick-Off Workshops, Annual Status • Workshops (last one on April 28 to 29, 2005, next in November 2005) • Conference Organization by DECHEMA e.V.– Conference Office for the 5th • International Conference on Systems Biology, October 9 –13, • 2004 in Heidelberg • Coordination of due diligance, contracting and implemen- • tation for a Central Data Management for the funding Initiative • Systems Biology • Organizing the Scientific Report Systems for PTJ, BMBF, and • Steering Committee

  22. Websites • Federal Ministry of Education and Research • www.bmbf.de • PTJ – the Project Management Organisation Jülich • www.fz-juelich.de/ptj/ • Competence Network Systems Biology • www.systembiologie.de • The Database for Systems Biology Researchers • http://www.bcc.univie.ac.at/cgi-bin/molg/sysbiol/SysBiol.pl

  23. Systems Biology – The Concepts Systems biology integrates the molecular parts list into quantitative models of biological functions Kitano, H. Science 295, 1662 (2002): “To understand biology at the system level, we must examine the structure and dynamics of cellular and organismal function, rather than the characteristics of isolated parts of a cell or organism.”

  24. Descriptional and analytical levels in Systems Biology Transcriptomics Genome Gene Regulation Expression Metabolism Proteins Whole Organism TissuesandCells Proteomics Metabolomics PhenotypeandPotential for Diseases Physiomics cit from Nicolson (2002), modified

  25. It is all dynamics in biological systems Measurements by the -omics technologies do not necessarily reflect real-world or endpoint observations Real world 'omics world Inputs:Signalsstressors etc Note: time differentials in all interaction stages Gene expression Time cell Time Time Protein profile Time Time Metabolic profile Outputs:Biological endpointspathologydegenerationregeneration Nicolson, J.K. at al. Nature Reviews Drug Discovery 1, 153 (2002)

  26. Current topics in systems biology Problems encountered when we try to understand life processes by simulation and modeling • Complexity • n Dimensionality • Holistic versus reductionistic working modes • Change, dynamics • Pleiotropy and redundancy in biology • Deterministic versus stochastic mathematics • Bioinformatics  System Engineering • Need to end in understanding physiology and disease processes

  27. Complexity and emergent properties in biology • Complex inputs that stimulate multiple pathways • Integrated networks respond to the inputs by multiple outputs • Interactions between multiple cell types in multi cellular organisms (like man) • Multiple contexts and environments for each cell type or combination of cell types To understand the effects of a target or a drug, data must be derived from cell responses in multiple environment. Butcher et al. Nature Biotechnol. 22, 1253 (2004)

  28. Computational biology Omics Cell systems • Hypothesis generation + + + • Target identification/validation (+) + (+) • Quantitative analysis of dynamic parameters - (+) + • Rational design of perturbanceof a system - (+) + • Systems connectivities - + + • Disease model properties - + - • Disease indication / trial design - +/- (+) Limitations: • Data quantity • Data quality • Need for functionalannotation work • Availability of all types • Limited modeling of systemic effects • Missing experimental data sets • Availability of suitable cell material • Very slow throughput • Computational limitations Deliverables and limitations of approaches by integrative biology to drug research and development

  29. Examples of computational models relevant to human disease biology (cit. Butcher, E. C. et al., Nature Biotechnol. 22, 1253 (2004), modified)

  30. Data-based mathematical modelling of the JAK2-STAT5 Pathway(Klingmueller, pers. commun,.)

  31. JAK2-STAT5 PathwayPredicting Steps Most Sensitive for Perturbation(Klingmueller, pers. commun.) Mathematical prediction: Dynamical parameters of nuclear import (k3), export (k4) and delay (t) most sensitive to perturbation Experimental verification of mathematical prediction

  32. Systems Biology: Selected commercial players

  33. Systems Biology: Selected commercial players ctd.

  34. Systems Biology at Work in Drug Discovery of Big Companies Lit. zit.: Littlehales, C.: Bio News Dec. 20047January 2005, p. 9, modified

  35. Markers Safety, Toxicity Efficacy Response/Non response Safety/Efficacy Diagnosis/Prognosis Disease Progression Drug Discovery Clinical Development Therapy Target - Identification, - Characterization, - Prioritization Animal ModelValidation Combination with Other Drugs Mode of ActionTrial Design DiseaseIndications Product Decision Pathway Elucidation, Network Analysis Targets The Multiple Input of Systems Biology into Molecular Medicine

  36. Research centers on systems biology in the USA (1) Institute for Systems BiologyIntegration of the different levels of biological information,(Hood et al.; Seattle) modeling of integral systems - microorganism models and yeast - immune system, cancer, hematopoeitic development The Molecular Science InstituteDevelopment of prediction biology (Brenner, Brent; Berkeley) - genomic, evolutionary studies on E. coli - protein/protein interactions - computational biology, instrumentation Dept. on BioengineeringSystematic analysis of genetic circuits (Palsson, UCSD) - coordinated activities of multiple gene products in metabolism and cell motility - in silico metabolic routing in E. coli CaltechModeling of nonlinear systems in E. coli (Simon, Doyle, Kitano, et al.) - Simulation systems for gene regulation and metabolism - Modeling and simulation of the cell cycle Biomolecular Systems Initiative (BSI) Studies on cellular networks (within cells and between cells) at Pacific Northwest Natl. Laboratory - in microbiological systems by(Wiley et al.) - quantitative and integrative cell biology

  37. Research centers on systems biology in the USA (2) Alliance for Cellular Analysis of G protein coupled or related signal Signaling (AfCS) transduction in mammalian cells (Gilman, Univ. Texas - identification of all involved proteins South Western) - analysis of kinetics of information fluxes - modeling cellular signaling MIT Computational and Systems• Quantitative biology of cellular functions by Biology Initiative (CSBI) experimentation, modeling and simulation in mammalian (Sorger, Tidor, Lauffenburger) cells and tissues - regulation of proliferation, adhesion, migration and transport• Education in SB Systems Biology Department• Bioinformatics, structural genomics, Quantitative Structure Harvard Medical School Activity Relationships in multicomponent complexes (Kirschner, Mitchison, Harvard) - Synthetic biological systems - Molecular understanding of physiological centre• Education in SB Princeton Integrative Genomics • Interdisciplinary research programmes on quantitative biology(Botstein et al.), University of • Education in SBMichigan Life Sciences Institute(Saltiel et al.), Stanford UniversityBiosciences Initiative (Bio-X, Scott et al.),Duke’s Institute for Genome Sciences andPolicy (Willard et al.)

  38. Recent Highlights in SB International Crosslinking • EU-Initiatives • EU SYSBIO, SYMBIONIC • EUREKA InSysBio Project • SYSMO (AU, DE, NL, GB, NO, SP) • WTEC/USA: http://wtec.org/sysbio Reports on US, EU and Japan activities • WTEC/USA: Workshop on setting up a repository for systems biology software, February 17-18, 2005, Washington, USA • 5. International Conference on Systems BiologyOctober 9-13, 2004, Heidelberg, Germany • 6. International Conference on Systems BiologyOctober 2005, Cambridge, USA, Org: Marc Kirschner, Harvardhttp://www.ICSB2005.org • Start of PanAsian electronic International Molecular Biology Laboratory (e IMBL)Seoul, July 12-13, 2005

  39. On SYSMO This is a website of SYSMO: SYSMO is a transnational funding program for the Systems Biology of MicroOrganisms, of The German BMBF, the Dutch NWO-ALW, and the Austrian bm:bmk. Additional countries have been invited to join soon. At present SYSMO is already active in supporting the training of scientists and students in Systems Biology. Its first activity is the strong support(in terms of travel fellowships) of the FEBS advanced course (see below). A second, much larger activity is a transnational research program for Systems Biology of Microorganisms. Countries are now asked to express their interest in participating in and supporting this program.

  40. See also: First FEBS Advanced Course on Systems Biology: From Molecules & Modeling To Cells March 12- 18, 2005, Gosau, Austria, EU Organized by: Roland Eils (Heidelberg), Karl Kuchler (Vienna), Anneke Koster (Amsterdam), and Hans V. Westerhoff (Amsterdam) Program and all informationFlyer (pdf) RegistrationPre-registration

  41. Systems Biology – How to implement into pharmaceutical research and development? (1) • Interdisciplinary approach needed, develop common conceptual understanding of biologists, mathematicians and bioinformatics experts • Define cellular models and experiments with reproducable properties - sampling - culture conditions - validated analytical technologies - exp. schedules • Iterative approaches needed between model builders and biological experimentators • Provide sufficient IT hardware resources and software tools

  42. Systems Biology – How to implement into pharmaceutical research and development? (2) • Drug researchers should join accademic initiatives for strategic cooperative projects • Drug R+D should form precompetitive R+D platforms for developing SB tools and informatics standards - Speak a common research language - Share IT resources - Train researchers on an integrative approach • Drug R+D should contribute views on strategic research priorities to academic research directors and share strategic concepts with national and cross-border research planning panels on precompetitive level • The potential of systems biology for drug discovery and development needs a major success story in industry (Ideker, 2004)

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