Systems Biology: Today and Tomorrow; the WTEC visit to The Netherlands The Institute for Molecular...

Systems Biology: Today and Tomorrow; the WTEC visit to The NetherlandsThe Institute for Molecular Cell Biology, BioCentre Amsterdam, Free University Amsterdam

The WTEC visit to The Netherlands:the program11:45 Welcome address (Hans Westerhoff): 12:15 Marvin Cassman: Aims of the WTEC study12:30 lunch 13:15 Welcoming remarks by Pier Vellinga (Dean Faculty of Earth and Life Sciences)13:45-17:00 Examples of Dutch Systems Biology 16:40 Teaching Systems Biology16:50 Drinks 17:05 General discussion (chair: Roel van Driel): Systems Biology and its future 17:45 Departure for the restaurant (De Molen; Amstelveen)

System Biology: Where it matters

International developmentsEuropean developments/potentialDutch Systems Biology

What is/has been happening internationally?Institutes (ISB-Seattle) [BCA/IMC here]Conference (ICSB)Electronic cellsAlliances

BioCentre Amsterdam and its Institute for Molecular Cell BiologyBCA: From Entering the living cell to Molecular Systems BiologyIMC:

The 4th International Systems Biology Conference 2004 in Heidelberg

Electronic cellsE-cellVirtual cellSilicon cell

www.siliconcell.net:Computer replica of parts of living cells (NL, SA, USA)

Bottom up international alliancesIEcA (International E. coli Alliance)

YSBN (Yeast Systems Biology Network)

EGF Signalling network

www.ieca2004.caRound Table discussion 2: Developing a White Paper

IEcA status quoManifest being writtenGenome Canada supports workshop funding organizations plus scientists to put together an international prokaryotic SB programTo prepare concrete action planGenome Canada looks for European partners (e.g. German SysMo)US partner needed .

YSBN status quoWhite paper has been writtenCommittees have been formedFunding unclear

GF signalling allianceIn preparation onlyKholodenko, Goryanin (GSK)

What is happening in Europe?National programsGermany (BMBF):German Hepatocyte: Systeme des Lebens (20-50 ME); has begunSysMo (Systems Biology of Microorganisms (10 ME); call in 2005Finland: System Biology and Bioinformatics (10.5 ME); has begunThe Netherlands: SBNL; set of organism focused programs (L. lactis, S. cerevisiae, E. coli, Silicon cell, Signal transduction, Xomics, Cell Biophysics, ..); some funded (IOP) most still in limboUK: BBSRC Integrative Biology 10 years program: > 6 national centres 5ME? each; bids (for first round) are now in..Transnational programs:SysMO: Germany intends to have this as a transnational program (Germany, Austria, Netherlands, France?)ERANET: Brussels catalyzed transnational activity; inspired by SysMO?Paris meeting August 26 (joint with EUSYSBIO meeting)European programs:

Transnational initiatives; SysMoGerman BMBFPreparing for microbial System Biology programWants to go transnationalAustrian, Dutch ?partners2005: call for proposals

What is happening in Europe?National programsGermany (BMBF):German Hepatocyte: Systeme des Lebens (20-50 ME); has begunSysMo (Systems Biology of Microorganisms (10 ME); call in 2005Finland: System Biology and Bioinformatics (10.5 ME); has begunThe Netherlands: SBNL; set of organism focused programs (L. lactis, S. cerevisiae, E. coli, Silicon cell, Signal transduction, Xomics, Cell Biophysics, ..); some funded (IOP) most still in limboUK: BBSRC Integrative Biology 10 years program: > 6 national centres 5ME? each; bids (for first round) are now in..Transnational programs:SysMO: Germany intends to have this as a transnational program (Germany, Austria, Netherlands, France?)ERANET: Brussels catalyzed transnational activity; inspired by SysMO?Paris meeting August 26 (joint with EUSYSBIO meeting)European programs:

What is happening in Europe?European programs:EU: FP6 (Specific Support Action EUSYSBIO; Computational Systems Biology not in third call; Synthetic Biology in April 2004 call)EUREKA: (New Safe Medicines Faster) Virtual CellEMBO: SB in EMBL??ESF: Forward look, towards EUROCORE and more?

FP6: Specific Support Action EUSYSBIOGet science policy makers togetherHelp organize ICSB2004 (Heidelberg, October 9-13 2004)Organize SB course (FEBS): March 2005Set up ERANET: transnational funding possibilitiesSet up European SB organization/group

WP8 (Dutch WP) deliverablesD26: Platform of excellent Eur SB groups:-at ICSB form network of excellence?D27: Workshop devoted to standardsAt ICSB2004: October 10, Heidelberg (joint with ESF?)D28: Strategy paper discussing scientific basis science policy planningTo be written on request of WP6D29: Scientific journal A book on Defining Systems Biology for now

BioSim ( NoE): MosekildeModels for pharmaceuticals

BioSim ( NoE): Models only

FP6: FutureComputational Systems Biology:Call for IP on Computational Systems Biology with deadline November 2004 failed (STREPS and Coordination Action remain)Promises for 4th call and FP7Problem?: too dry ?..

What is happening in Europe?European programs:EU: FP6 (Specific Support Action EUSYSBIO; Computational Systems Biology not in third call; Synthetic Biology in April 2004 call)EUREKA: (New Safe Medicines Faster) InSysBioEMBO: SB in EMBL??ESF: Forward look, towards EUROCORE and more?

EUREKAs InSysBio: IMCs relevance for Biomed and Biotech

EUREKAs InSysBio: IMC connecting with European pharma & food industry

InSysBio:Eurekas virtual cell initiativeEuropean, industry driven researchAim: Making computer models of living organisms for drug development etc. and(now also:) for food production (biotech)BioinformaticsTool developmentModels for pharma and Models for food

ESF forward lookStudy to see if System Biology could be ESF themeThis would then make ESF catalyze common research programmes betweenNational science foundations

What is needed?Wet SB, not just dry (FP6, EUREKA)Try to get the national SFs to coordinate their SB programsConstruct mechanisms for transnational fundingBecome partners for USA, Japan, Canada, China, KoreaProvide funding anchors for the alliances

Dutch/EU SB: Integrative Systems BiologyLook at all the leaves individually2. The phenomena; top downDiagnosis; pattern recognition3. Get to the roots; bottom up;Understanding of the specialSystem properties/principles

Dutch Systems Biology:The AmbitionAmbition:Not just SB; aim is to now understand living organisms from molecule to cell, organ, and human organismPut a healthy man . on earthDutch Niche: mechanistic (bottom up SB)wet plus dryindustry plus academia Bring about common goal synergism between national programs (European countries are too small for SB)Generate superfund from Europe

What is happening in NL?National programsNWO (Dutch NSF) preludes (6 M$ each):BioinformaticsMolecule to CellComputational BiologyNational Genomics Centres (200 M$): Centre Medical Systems Biology (Leiden, VU, TNO; not really SB)Kluyver Centre (some SB)Plant Systems (not SB)Cancer (not SB)IBIVU: Integrative BioInformatics VU (3 M$)IOP-Genomics: Vertical Genomics (2 M$)Ecogenomics-BSIK (10 M$)

What is going to happen in NL?National programsSBNL; set of focused program proposals:L. lactis (Kuipers, Teusink, Siezen, Hugenholz. )S. cerevisiae (Bakker, Teixeira, Pronk, Heijnen)Silicon cell Amsterdam (-Stellenbosch, Blacksburg; Snoep)SBNL: Industrial platformPartner in Transnational SysMOPartner in EUREKAAttempt at National Program integrating top down with bottom up

WTEC study: Systems Biology, Network Behavior in Biological SystemsState of the art information on network behavior, also internationallyResearch opportunitiesIdentify potential interagency collaborationsIdentify potential international collaborationsPublish results of study

The WTEC visit to The Netherlands:the program11:15 Coffee, tea, cookies in G07611:45 Welcome address (Hans Westerhoff): Dutch and European Systems Biology; where it might matter12:15 Marvin Cassman: The aims of the WTEC study12:30 lunch 13:15 Welcoming remarks by Pier Vellinga (Dean Faculty of Earth and Life Sciences)13:20 Coffee + informal discussions

The WTEC visit to The Netherlands:the program13:45-16:40 Examples of Dutch Systems Biology 13:45 Barbara Bakker; Vertical genomics 14:00 Jurgen Haanstra: Network based drug design 14:15 Frank Bruggeman: Silicon cell as a tool for understanding regulation14:30 Jan Lankelma: Treating cancer: fighting a system14:45 Jorrit Hornberg: New principles of signal transduction15:00:Tea

The WTEC visit to The Netherlands:the program15:30 Systems Biology in Delft: Wouter van Winden16:30 Lactococcus lactis faster; a Systems Biology endeavor; Bas Teusink16:40 Teaching Systems Biology, Hans V. Westerhoff16:50 Drinks 17:05 General discussion (chair: Roel van Driel): Systems Biology and its future 17:45 Departure for the restaurant (De Molen; Amstelveen) 18:00 Dinner.19:45 Departure for the airport20:00 Check in; KLM; Schiphol airport21:05 flight to the UK......

Orchestration of cellular processes in a simple cell: making Systems Biology work for Lactococcus lactisBas TeusinkKluyver Centre (Hugenholtz, Heijnen) RUG (Kuipers, Kok, Jansen, Poolman) VU (Westerhoff, Bakker, Snoep) CMBI (Siezen,Teusink) WCFS (Kleerebezem, Molenaar, de Vos) UvA (Brul, Hellingwerf, Breit) TNO-Food (Van der Werf, Smilde)

Objective: use Systems Biology to understand the limits of growth of Lactococcus lactisLimits of growth (at a given condition): -biological and physico-chemical constraints

Reference state: the pH-auxostat- Possible to operate stably at maximal growth rate- Study pH stress

Overview of work packages

Overview of consortium members1. Kluyver Centre (Hugenholtz, Heijnen):metabolome, proteome, modelling, metabolic engineering, fermentations

2. RUG (Kuipers, Kok, Jansen, Poolman):transcriptome, protein, membrane proteome, protein interactions, bioinformatics, statistics, model building

3. VU (Westerhoff, Bakker, Snoep):kinetic modelling, integrative bioinformatics, metabolome, activity-proteome, transport, hierarchical control analysis

4. CMBI (Siezen, Teusink):bioinformatics, comparative genomics, genome mining, metabolic reconstruction

Overview of consortium members5. WCFS (Kleerebezem, Molenaar, de Vos):regulation, mining, bioinformatics, metabolic engineering, metabolomics

6. UvA (Brul, Hellingwerf, Breit):DNA-array technology, signal transduction, experimental design

7. TNO-Food (Van der Werf, Smilde): metabolome, data analysis, experimental design

Teaching Systems BiologyMastersPh D students

TopMasterBiomolecular Integration/Systems BiologyEnquiries:Prof. Dr. H.V. WesterhoffTelephone +31 20 444 7228E-mail: [email protected]

A Masters of the CRbCSCentre for Research on bioComplex SystemsUltrafast space- and time-resolved spectroscopy, single molecule biophysics and biochemistry, chemistry of complex molecules, molecular genetics in living cells, intracellular networks, hierarchical control analysis, Integrative bioinformatics, principles of Systems Biology, entering the living cell, Silicon Cell, Integrative genomics, confocal microscopy, tumor cell biology, medical Systems Biology, signal transduction, nanotechnology, computational biology, ecological control analysisTransnational student projectsCareer development supportInternational peer groupConnected Ph D studentshipsNature 427, 568The real cellThe silicon cellExperimentsCalculations

TOP-BMI/SB : Aims continued:obtain expertise in advanced conceptual and modeling methodologies for bioinformation and computing technologies, such as medical Systems Biology, signal transduction, computational biology, ecological control analysis, intracellular networks, hierarchical control analysis, Integrative bioinformatics, principles of Systems Biology, entering the living cell, Silicon Cellobtain insight in the most important biological and biomedical issues, and in how they might be addressed scientificallyinsight into what systems biology and integrative molecular biophysics may mean for societyunique and excellent profile for advanced interdisciplinary research between the physical sciences and the life sciences

TOP-BMI/SB : Curriculum structure (2 year, 120 ECTS credit points)

Portal course14 ECTS6 obligatory (5 ECTS) courses with each of the CRbCS professors30 ECTS1 international experts lecture course 6 ECTSorientation on future research project (including literature thesis)12 ECTSrefereeing of research proposal 3 ECTS8 months research project in Amsterdam and foreign laboratory40 ECTSscientific article about research project 5 ECTSfollowing and discussing, reporting on scientific seminars 2 ECTSscientific conference (co-organizing, participating, reporting) 3 ECTSpreparation for final comprehensive exam 5 ECTS

TOP-BMI/SB Obligatory courses:

Portal course: entry course of mathematics and physics for the biologist and biology for the physics/chemistry/mathematics bachelorBiomolecular dynamics (Van Grondelle)Single molecule biophysics and biochemistry (nanobiology) (Schmidt)Chemistry of complex biomolecules (Van der Vies)Looking at Integrating molecules (Lill)Intracellular networks (Westerhoff)Integrative bioinformatics (Heringa)Current topics in biomolecular integration and systems biology (international lecturers, e.g. Heinrich)

TOP-BMI/SBResearch projects: One research exchange project in two laboratories (partly in Amsterdam and partly in one of the collaborating International Centers of Excellence), on Biomolecular Integration / Systems Biology

SB teaching to Ph D studentsJoint graduate school with Humboldt U (Berlin); Heinrich et alNow extended with Goteborgh Yeast Center (Hohmann et al), EU fundedMany exchange projects alreadyAnnual joint courses

SB teaching/human capital problemsVery difficult field because of combination top experiments and top theoryLack of appreciation peer groups (Biologists look down upon physicists and mathematicians and vv)Lack of society appreciation (insufficient job opportunities)Insufficient interest young students in science


11:00am-12:00am Keynote Address IIwww.siliconcell.net: Bringing Bits and Chips to Life, Hans V. WesterhoffFree University, Amsterdam, University of Amsterdam and Stellenbosch Institute for Advanced StudyWith the rapid development of Systems Biology, it is more and more emphasized that biological function stems more from the nonlinear interactions between biomolecules than from those molecules individually. With the completion of more and more genome sequences it is becoming clear that the number of components is vast. The new functional genomics data bring home the message that life operates along many degrees of freedom, i.e. that expression space is multidimensional. Some of this is bad news, as it incapacitates the otherwise powerful traditional molecular biology vis-a-vis the challenge of understanding even the simpler forms of life, or at least understanding them with the existing methods. On the other side, mathematical biology, able to deal with complicated mathematics, has always shied away from true complexity, i.e. from complexity comprising more than 4 degrees of freedom. Core models would be used to understand the essence but not necessarily the reality of biological phenomena.We shall discuss how a new scientific community is now cutting the Gordian knot and combines molecular and mathematical biology in an almost trivial way, i.e. by making precise mathematical models as replica of substantial parts of living cells. Such computer replica are called silicon cells, and are collected and hopefully later connected on the wwweb. They serve to store kinetic data in a dynamic sense, and only those data matter for functioning living cells. They also serve to do computer experimentation with living cells, or in reality with their computer replica. We shall show how these can serve to discover system behavior of living organisms tdeductively, i.e. produce discoveries that do not always require experimental testing.11:00am-12:00am Keynote Address IIwww.siliconcell.net: Bringing Bits and Chips to Life, Hans V. WesterhoffFree University, Amsterdam, University of Amsterdam and Stellenbosch Institute for Advanced StudyWith the rapid development of Systems Biology, it is more and more emphasized that biological function stems more from the nonlinear interactions between biomolecules than from those molecules individually. With the completion of more and more genome sequences it is becoming clear that the number of components is vast. The new functional genomics data bring home the message that life operates along many degrees of freedom, i.e. that expression space is multidimensional. Some of this is bad news, as it incapacitates the otherwise powerful traditional molecular biology vis-a-vis the challenge of understanding even the simpler forms of life, or at least understanding them with the existing methods. On the other side, mathematical biology, able to deal with complicated mathematics, has always shied away from true complexity, i.e. from complexity comprising more than 4 degrees of freedom. Core models would be used to understand the essence but not necessarily the reality of biological phenomena.We shall discuss how a new scientific community is now cutting the Gordian knot and combines molecular and mathematical biology in an almost trivial way, i.e. by making precise mathematical models as replica of substantial parts of living cells. Such computer replica are called silicon cells, and are collected and hopefully later connected on the wwweb. They serve to store kinetic data in a dynamic sense, and only those data matter for functioning living cells. They also serve to do computer experimentation with living cells, or in reality with their computer replica. We shall show how these can serve to discover system behavior of living organisms tdeductively, i.e. produce discoveries that do not always require experimental testing.Abstract: Metabolic signal transduction in space and time. Facts, figures and principlesHans V. Westerhoff, Barbara M. Bakker, Nathan Brady, Frank Bruggeman, Joke Blom, Christof Francke, Mark Peletier, Boris N. Kholodenko, Karin A. Reijenga, and Jacky L. SnoepCentre for Research on BioComplex Systems, BioCentrum Amsterdam; Centre for Mathematics and Informatics, Amsterdam; Stellenbosch Institute for Advanced Study; and Thomas Jefferson University, PhiladelphiaGallia omnis divisa erat in partes tres..... and so was cell biology. There was metabolism, there was gene expression and there was signal transduction. The three parts were examined as if in isolation from each other. In this era of system biology, it is recognized that cells function by integrating processes rather than by keeping them apart, and that processes function differently when integrating with other processes. In this presentation we shall discuss three examples where we are beginning to understand the principles according to which the cellular dimensions of signal transduction and time are integrated with the physical dimensions of space and time. We shall also discuss a case where we have no inkling of how the integration proceeds.Estimations have suggested that signal transduction in mammalian cells should be subject to spatial gradients. We examined this point for the phosphotransferase system (PTS), which is a hybrid between a signal transduction pathway, a metabolic pathway and a transport system. Using the experiments based Silicon Cell (www.silioncell.net) as a tool, we calculated that flux should not, but signal transduction could well, be compromised in cells much larger than Escherichia coli. Perhaps this is why mammalian cells prefer kinase/phosphatase cascades.The control and regulation of metabolism has not only been a complex but also a confusing issue for a long time. How could several groups all claim to work on the rate-limiting step of a metabolic pathway, whilst they worked on different steps? Metabolic Control Analysis has clarified this issue, but it is little known that a corresponding analysis method exists for signal transduction pathways. One might be inclined to extrapolate from metabolic pathways that also signal transduction pathways tend to have a total control of 1 distributed over all steps in the pathway. This then should allow at most 1, but usually no step to be the rate limiting step. We shall demonstrate the principle that signal transduction is at the same time devoid of control and full of (absolute) control. The issue relates to the relative importance of kinases and phosphatases. The dynamics of signal transduction have been shown to be highly important, at least for calcium signaling. We shall derive principles that should govern the control of dynamics of the EGF response. Yeast cells can communicate with each other through the metabolic signal acetaldehyde. This signal appears to specialize in keeping the individual cells coordinated, rather than in controlling their oscillations per se. We shall show that a dynamic glucose signal can address gene expression in yeast such that the metabolic dynamics of the cells change.What we do not understand is how mitochondria in isolated cardiomyocytes appear to communicate energetically in a mitochondrial permeability-transition related mechanism. Does this betray a subtle spatio-temporal mechanism that ranges from total recovery through mitoptosis and apoptosis to necrosis?

Abstract: Metabolic signal transduction in space and time. Facts, figures and principlesHans V. Westerhoff, Barbara M. Bakker, Nathan Brady, Frank Bruggeman, Joke Blom, Christof Francke, Mark Peletier, Boris N. Kholodenko, Karin A. Reijenga, and Jacky L. SnoepCentre for Research on BioComplex Systems, BioCentrum Amsterdam; Centre for Mathematics and Informatics, Amsterdam; Stellenbosch Institute for Advanced Study; and Thomas Jefferson University, PhiladelphiaGallia omnis divisa erat in partes tres..... and so was cell biology. There was metabolism, there was gene expression and there was signal transduction. The three parts were examined as if in isolation from each other. In this era of system biology, it is recognized that cells function by integrating processes rather than by keeping them apart, and that processes function differently when integrating with other processes. In this presentation we shall discuss three examples where we are beginning to understand the principles according to which the cellular dimensions of signal transduction and time are integrated with the physical dimensions of space and time. We shall also discuss a case where we have no inkling of how the integration proceeds.Estimations have suggested that signal transduction in mammalian cells should be subject to spatial gradients. We examined this point for the phosphotransferase system (PTS), which is a hybrid between a signal transduction pathway, a metabolic pathway and a transport system. Using the experiments based Silicon Cell (www.silioncell.net) as a tool, we calculated that flux should not, but signal transduction could well, be compromised in cells much larger than Escherichia coli. Perhaps this is why mammalian cells prefer kinase/phosphatase cascades.The control and regulation of metabolism has not only been a complex but also a confusing issue for a long time. How could several groups all claim to work on the rate-limiting step of a metabolic pathway, whilst they worked on different steps? Metabolic Control Analysis has clarified this issue, but it is little known that a corresponding analysis method exists for signal transduction pathways. One might be inclined to extrapolate from metabolic pathways that also signal transduction pathways tend to have a total control of 1 distributed over all steps in the pathway. This then should allow at most 1, but usually no step to be the rate limiting step. We shall demonstrate the principle that signal transduction is at the same time devoid of control and full of (absolute) control. The issue relates to the relative importance of kinases and phosphatases. The dynamics of signal transduction have been shown to be highly important, at least for calcium signaling. We shall derive principles that should govern the control of dynamics of the EGF response. Yeast cells can communicate with each other through the metabolic signal acetaldehyde. This signal appears to specialize in keeping the individual cells coordinated, rather than in controlling their oscillations per se. We shall show that a dynamic glucose signal can address gene expression in yeast such that the metabolic dynamics of the cells change.What we do not understand is how mitochondria in isolated cardiomyocytes appear to communicate energetically in a mitochondrial permeability-transition related mechanism. Does this betray a subtle spatio-temporal mechanism that ranges from total recovery through mitoptosis and apoptosis to necrosis?

Abstract: Metabolic signal transduction in space and time. Facts, figures and principlesHans V. Westerhoff, Barbara M. Bakker, Nathan Brady, Frank Bruggeman, Joke Blom, Christof Francke, Mark Peletier, Boris N. Kholodenko, Karin A. Reijenga, and Jacky L. SnoepCentre for Research on BioComplex Systems, BioCentrum Amsterdam; Centre for Mathematics and Informatics, Amsterdam; Stellenbosch Institute for Advanced Study; and Thomas Jefferson University, PhiladelphiaGallia omnis divisa erat in partes tres..... and so was cell biology. There was metabolism, there was gene expression and there was signal transduction. The three parts were examined as if in isolation from each other. In this era of system biology, it is recognized that cells function by integrating processes rather than by keeping them apart, and that processes function differently when integrating with other processes. In this presentation we shall discuss three examples where we are beginning to understand the principles according to which the cellular dimensions of signal transduction and time are integrated with the physical dimensions of space and time. We shall also discuss a case where we have no inkling of how the integration proceeds.Estimations have suggested that signal transduction in mammalian cells should be subject to spatial gradients. We examined this point for the phosphotransferase system (PTS), which is a hybrid between a signal transduction pathway, a metabolic pathway and a transport system. Using the experiments based Silicon Cell (www.silioncell.net) as a tool, we calculated that flux should not, but signal transduction could well, be compromised in cells much larger than Escherichia coli. Perhaps this is why mammalian cells prefer kinase/phosphatase cascades.The control and regulation of metabolism has not only been a complex but also a confusing issue for a long time. How could several groups all claim to work on the rate-limiting step of a metabolic pathway, whilst they worked on different steps? Metabolic Control Analysis has clarified this issue, but it is little known that a corresponding analysis method exists for signal transduction pathways. One might be inclined to extrapolate from metabolic pathways that also signal transduction pathways tend to have a total control of 1 distributed over all steps in the pathway. This then should allow at most 1, but usually no step to be the rate limiting step. We shall demonstrate the principle that signal transduction is at the same time devoid of control and full of (absolute) control. The issue relates to the relative importance of kinases and phosphatases. The dynamics of signal transduction have been shown to be highly important, at least for calcium signaling. We shall derive principles that should govern the control of dynamics of the EGF response. Yeast cells can communicate with each other through the metabolic signal acetaldehyde. This signal appears to specialize in keeping the individual cells coordinated, rather than in controlling their oscillations per se. We shall show that a dynamic glucose signal can address gene expression in yeast such that the metabolic dynamics of the cells change.What we do not understand is how mitochondria in isolated cardiomyocytes appear to communicate energetically in a mitochondrial permeability-transition related mechanism. Does this betray a subtle spatio-temporal mechanism that ranges from total recovery through mitoptosis and apoptosis to necrosis?

Abstract: Metabolic signal transduction in space and time. Facts, figures and principlesHans V. Westerhoff, Barbara M. Bakker, Nathan Brady, Frank Bruggeman, Joke Blom, Christof Francke, Mark Peletier, Boris N. Kholodenko, Karin A. Reijenga, and Jacky L. SnoepCentre for Research on BioComplex Systems, BioCentrum Amsterdam; Centre for Mathematics and Informatics, Amsterdam; Stellenbosch Institute for Advanced Study; and Thomas Jefferson University, PhiladelphiaGallia omnis divisa erat in partes tres..... and so was cell biology. There was metabolism, there was gene expression and there was signal transduction. The three parts were examined as if in isolation from each other. In this era of system biology, it is recognized that cells function by integrating processes rather than by keeping them apart, and that processes function differently when integrating with other processes. In this presentation we shall discuss three examples where we are beginning to understand the principles according to which the cellular dimensions of signal transduction and time are integrated with the physical dimensions of space and time. We shall also discuss a case where we have no inkling of how the integration proceeds.Estimations have suggested that signal transduction in mammalian cells should be subject to spatial gradients. We examined this point for the phosphotransferase system (PTS), which is a hybrid between a signal transduction pathway, a metabolic pathway and a transport system. Using the experiments based Silicon Cell (www.silioncell.net) as a tool, we calculated that flux should not, but signal transduction could well, be compromised in cells much larger than Escherichia coli. Perhaps this is why mammalian cells prefer kinase/phosphatase cascades.The control and regulation of metabolism has not only been a complex but also a confusing issue for a long time. How could several groups all claim to work on the rate-limiting step of a metabolic pathway, whilst they worked on different steps? Metabolic Control Analysis has clarified this issue, but it is little known that a corresponding analysis method exists for signal transduction pathways. One might be inclined to extrapolate from metabolic pathways that also signal transduction pathways tend to have a total control of 1 distributed over all steps in the pathway. This then should allow at most 1, but usually no step to be the rate limiting step. We shall demonstrate the principle that signal transduction is at the same time devoid of control and full of (absolute) control. The issue relates to the relative importance of kinases and phosphatases. The dynamics of signal transduction have been shown to be highly important, at least for calcium signaling. We shall derive principles that should govern the control of dynamics of the EGF response. Yeast cells can communicate with each other through the metabolic signal acetaldehyde. This signal appears to specialize in keeping the individual cells coordinated, rather than in controlling their oscillations per se. We shall show that a dynamic glucose signal can address gene expression in yeast such that the metabolic dynamics of the cells change.What we do not understand is how mitochondria in isolated cardiomyocytes appear to communicate energetically in a mitochondrial permeability-transition related mechanism. Does this betray a subtle spatio-temporal mechanism that ranges from total recovery through mitoptosis and apoptosis to necrosis?11:00am-12:00am Keynote Address IIwww.siliconcell.net: Bringing Bits and Chips to Life, Hans V. WesterhoffFree University, Amsterdam, University of Amsterdam and Stellenbosch Institute for Advanced StudyWith the rapid development of Systems Biology, it is more and more emphasized that biological function stems more from the nonlinear interactions between biomolecules than from those molecules individually. With the completion of more and more genome sequences it is becoming clear that the number of components is vast. The new functional genomics data bring home the message that life operates along many degrees of freedom, i.e. that expression space is multidimensional. Some of this is bad news, as it incapacitates the otherwise powerful traditional molecular biology vis-a-vis the challenge of understanding even the simpler forms of life, or at least understanding them with the existing methods. On the other side, mathematical biology, able to deal with complicated mathematics, has always shied away from true complexity, i.e. from complexity comprising more than 4 degrees of freedom. Core models would be used to understand the essence but not necessarily the reality of biological phenomena.We shall discuss how a new scientific community is now cutting the Gordian knot and combines molecular and mathematical biology in an almost trivial way, i.e. by making precise mathematical models as replica of substantial parts of living cells. Such computer replica are called silicon cells, and are collected and hopefully later connected on the wwweb. They serve to store kinetic data in a dynamic sense, and only those data matter for functioning living cells. They also serve to do computer experimentation with living cells, or in reality with their computer replica. We shall show how these can serve to discover system behavior of living organisms tdeductively, i.e. produce discoveries that do not always require experimental testing.11:00am-12:00am Keynote Address IIwww.siliconcell.net: Bringing Bits and Chips to Life, Hans V. WesterhoffFree University, Amsterdam, University of Amsterdam and Stellenbosch Institute for Advanced StudyWith the rapid development of Systems Biology, it is more and more emphasized that biological function stems more from the nonlinear interactions between biomolecules than from those molecules individually. With the completion of more and more genome sequences it is becoming clear that the number of components is vast. The new functional genomics data bring home the message that life operates along many degrees of freedom, i.e. that expression space is multidimensional. Some of this is bad news, as it incapacitates the otherwise powerful traditional molecular biology vis-a-vis the challenge of understanding even the simpler forms of life, or at least understanding them with the existing methods. On the other side, mathematical biology, able to deal with complicated mathematics, has always shied away from true complexity, i.e. from complexity comprising more than 4 degrees of freedom. Core models would be used to understand the essence but not necessarily the reality of biological phenomena.We shall discuss how a new scientific community is now cutting the Gordian knot and combines molecular and mathematical biology in an almost trivial way, i.e. by making precise mathematical models as replica of substantial parts of living cells. Such computer replica are called silicon cells, and are collected and hopefully later connected on the wwweb. They serve to store kinetic data in a dynamic sense, and only those data matter for functioning living cells. They also serve to do computer experimentation with living cells, or in reality with their computer replica. We shall show how these can serve to discover system behavior of living organisms tdeductively, i.e. produce discoveries that do not always require experimental testing.11:00am-12:00am Keynote Address IIwww.siliconcell.net: Bringing Bits and Chips to Life, Hans V. WesterhoffFree University, Amsterdam, University of Amsterdam and Stellenbosch Institute for Advanced StudyWith the rapid development of Systems Biology, it is more and more emphasized that biological function stems more from the nonlinear interactions between biomolecules than from those molecules individually. With the completion of more and more genome sequences it is becoming clear that the number of components is vast. The new functional genomics data bring home the message that life operates along many degrees of freedom, i.e. that expression space is multidimensional. Some of this is bad news, as it incapacitates the otherwise powerful traditional molecular biology vis-a-vis the challenge of understanding even the simpler forms of life, or at least understanding them with the existing methods. On the other side, mathematical biology, able to deal with complicated mathematics, has always shied away from true complexity, i.e. from complexity comprising more than 4 degrees of freedom. Core models would be used to understand the essence but not necessarily the reality of biological phenomena.We shall discuss how a new scientific community is now cutting the Gordian knot and combines molecular and mathematical biology in an almost trivial way, i.e. by making precise mathematical models as replica of substantial parts of living cells. Such computer replica are called silicon cells, and are collected and hopefully later connected on the wwweb. They serve to store kinetic data in a dynamic sense, and only those data matter for functioning living cells. They also serve to do computer experimentation with living cells, or in reality with their computer replica. We shall show how these can serve to discover system behavior of living organisms tdeductively, i.e. produce discoveries that do not always require experimental testing.11:00am-12:00am Keynote Address IIwww.siliconcell.net: Bringing Bits and Chips to Life, Hans V. WesterhoffFree University, Amsterdam, University of Amsterdam and Stellenbosch Institute for Advanced StudyWith the rapid development of Systems Biology, it is more and more emphasized that biological function stems more from the nonlinear interactions between biomolecules than from those molecules individually. With the completion of more and more genome sequences it is becoming clear that the number of components is vast. The new functional genomics data bring home the message that life operates along many degrees of freedom, i.e. that expression space is multidimensional. Some of this is bad news, as it incapacitates the otherwise powerful traditional molecular biology vis-a-vis the challenge of understanding even the simpler forms of life, or at least understanding them with the existing methods. On the other side, mathematical biology, able to deal with complicated mathematics, has always shied away from true complexity, i.e. from complexity comprising more than 4 degrees of freedom. Core models would be used to understand the essence but not necessarily the reality of biological phenomena.We shall discuss how a new scientific community is now cutting the Gordian knot and combines molecular and mathematical biology in an almost trivial way, i.e. by making precise mathematical models as replica of substantial parts of living cells. Such computer replica are called silicon cells, and are collected and hopefully later connected on the wwweb. They serve to store kinetic data in a dynamic sense, and only those data matter for functioning living cells. They also serve to do computer experimentation with living cells, or in reality with their computer replica. We shall show how these can serve to discover system behavior of living organisms tdeductively, i.e. produce discoveries that do not always require experimental testing.11:00am-12:00am Keynote Address IIwww.siliconcell.net: Bringing Bits and Chips to Life, Hans V. WesterhoffFree University, Amsterdam, University of Amsterdam and Stellenbosch Institute for Advanced StudyWith the rapid development of Systems Biology, it is more and more emphasized that biological function stems more from the nonlinear interactions between biomolecules than from those molecules individually. With the completion of more and more genome sequences it is becoming clear that the number of components is vast. The new functional genomics data bring home the message that life operates along many degrees of freedom, i.e. that expression space is multidimensional. Some of this is bad news, as it incapacitates the otherwise powerful traditional molecular biology vis-a-vis the challenge of understanding even the simpler forms of life, or at least understanding them with the existing methods. On the other side, mathematical biology, able to deal with complicated mathematics, has always shied away from true complexity, i.e. from complexity comprising more than 4 degrees of freedom. Core models would be used to understand the essence but not necessarily the reality of biological phenomena.We shall discuss how a new scientific community is now cutting the Gordian knot and combines molecular and mathematical biology in an almost trivial way, i.e. by making precise mathematical models as replica of substantial parts of living cells. Such computer replica are called silicon cells, and are collected and hopefully later connected on the wwweb. They serve to store kinetic data in a dynamic sense, and only those data matter for functioning living cells. They also serve to do computer experimentation with living cells, or in reality with their computer replica. We shall show how these can serve to discover system behavior of living organisms tdeductively, i.e. produce discoveries that do not always require experimental testing.11:00am-12:00am Keynote Address IIwww.siliconcell.net: Bringing Bits and Chips to Life, Hans V. WesterhoffFree University, Amsterdam, University of Amsterdam and Stellenbosch Institute for Advanced StudyWith the rapid development of Systems Biology, it is more and more emphasized that biological function stems more from the nonlinear interactions between biomolecules than from those molecules individually. With the completion of more and more genome sequences it is becoming clear that the number of components is vast. The new functional genomics data bring home the message that life operates along many degrees of freedom, i.e. that expression space is multidimensional. Some of this is bad news, as it incapacitates the otherwise powerful traditional molecular biology vis-a-vis the challenge of understanding even the simpler forms of life, or at least understanding them with the existing methods. On the other side, mathematical biology, able to deal with complicated mathematics, has always shied away from true complexity, i.e. from complexity comprising more than 4 degrees of freedom. Core models would be used to understand the essence but not necessarily the reality of biological phenomena.We shall discuss how a new scientific community is now cutting the Gordian knot and combines molecular and mathematical biology in an almost trivial way, i.e. by making precise mathematical models as replica of substantial parts of living cells. Such computer replica are called silicon cells, and are collected and hopefully later connected on the wwweb. They serve to store kinetic data in a dynamic sense, and only those data matter for functioning living cells. They also serve to do computer experimentation with living cells, or in reality with their computer replica. We shall show how these can serve to discover system behavior of living organisms tdeductively, i.e. produce discoveries that do not always require experimental testing.11:00am-12:00am Keynote Address IIwww.siliconcell.net: Bringing Bits and Chips to Life, Hans V. WesterhoffFree University, Amsterdam, University of Amsterdam and Stellenbosch Institute for Advanced StudyWith the rapid development of Systems Biology, it is more and more emphasized that biological function stems more from the nonlinear interactions between biomolecules than from those molecules individually. With the completion of more and more genome sequences it is becoming clear that the number of components is vast. The new functional genomics data bring home the message that life operates along many degrees of freedom, i.e. that expression space is multidimensional. Some of this is bad news, as it incapacitates the otherwise powerful traditional molecular biology vis-a-vis the challenge of understanding even the simpler forms of life, or at least understanding them with the existing methods. On the other side, mathematical biology, able to deal with complicated mathematics, has always shied away from true complexity, i.e. from complexity comprising more than 4 degrees of freedom. Core models would be used to understand the essence but not necessarily the reality of biological phenomena.We shall discuss how a new scientific community is now cutting the Gordian knot and combines molecular and mathematical biology in an almost trivial way, i.e. by making precise mathematical models as replica of substantial parts of living cells. Such computer replica are called silicon cells, and are collected and hopefully later connected on the wwweb. They serve to store kinetic data in a dynamic sense, and only those data matter for functioning living cells. They also serve to do computer experimentation with living cells, or in reality with their computer replica. We shall show how these can serve to discover system behavior of living organisms tdeductively, i.e. produce discoveries that do not always require experimental testing.

Systems Biology: Today and Tomorrow; the WTEC visit to The Netherlands The Institute for Molecular...

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Transcript of Systems Biology: Today and Tomorrow; the WTEC visit to The Netherlands The Institute for Molecular...