Systems biology the new scientific paradigm Lilia Alberghina

Systems biology: the new scientific paradigm Lilia Alberghina Dept. Biotechnology and Biosciences University of Milano-Bicocca, Milan, Italy Meeting FIRB 2003 Bisceglie 17 -19 Luglio 2005

Why systems biology? • Much of twentieth-century biology has been an attempt to reduce biological phenomena to the behaviour of molecules. Despite the enormous success of this approach, a discrete biological function can only rarely be attributed to an individual molecule. • In biological systems large numbers of functional diverse, and frequently multifunctional, sets of elements interact selectively and non linearly to produce coherent behaviour. • To describe biological functions, we need a vocabulary that contains concepts such as amplification, adaptation, robustness, insulation, error correction and coincidence detection. (Hartwell et al. , 1999; Kitano, 2002) 1

Why systems biology? Complex cellular processes, such as cell cycle, need to be analysed in a way to determine the logical and informational circuits that yield their behaviour. To do so the identification, characterization and identification of the logical and informational modules that operate in a cell is required. They include feed back loops, switches, thresholds, timers, amplifiers etc. The identification and characterization of interacting molecules and biochemical activities of each module will allow to test by modeling and simulation how a particular biological phenomenon is generated. (Nurse, Nature, 2002) 2

Systems biology has two distinct branches: Knowledge discovery and data mining, which extracts the hidden patterns from huge quantities of experimental data, forming hypothesis as result and simulation-based analysis, providing predictions to be tested by in vitro and in vivo studies. (Kitano, 2002) 3

Bioinformatics and Systems biology Bioinformatics aims to extract information from biological data: • • • prediction of 3 D structure from sequence data clustering of m. RNA expression data molecular evolution analysis Systems biology aims to define and understand control circuits and executive steps of the many complex processes that govern cell functions. It needs to integrate and structure “omics” data into regulatory circuits. It aims to understand the new properties that arise from interactions of molecules into networks. Both disciplines utilize biological data and computer methods, but Systems biology go further to biological control mechanisms that are non-linear and therefore often counter intuitive 4

Systems biology: the strategy A cell can be dissected into “modules”, subsystems of interacting molecules (proteins, DNA, RNA and small molecules) that perform a given task in a way largely independent from the context. For instance: • glycolysis and other metabolic pathways • signal transduction pathways • cell cycle • apoptosis 5 not so well known quite well known in molecular terms

The iterative steps of modular systems biology • Global functional analysis 1 • Determination of the major functional modules involved in the process under study and their regulatory connections. • Determination of a basic modular blueprint of the process and validation of its dynamics • Development of a molecular model of a given module • Validation of its plausibility • Refinement of the molecular model • Control analysis (robustness, bifurcation, connectivity, etc) • Predictions • Repeat Steps 4 and 6 till necessary • Repeat for all the other modules in 1 so to have the molecular model of the entire process 3 5 • 4 M Strategy to identify major components of a given module 2 • Extensive environmental (i. e. C and N source modulation) and genetic (i. e. gene dosage, deletion, point mutation) perturbations of the function of the module • Refinement of spatio-temporal analysis (localization, determination of kinetic constants, etc. ) 4 • Post-genomic analysis • Experimental verification of predictions 6 7 • Achievement of a complete molecular model of a given module 8 9 5

The iterative steps of modular systems biology • Global functional analysis 1 • Determination of the major functional modules involved in the process under study and their regulatory connections. • Determination of a basic modular blueprint of the process and validation of its dynamics • Development of a molecular model of a given module • Validation of its plausibility • Refinement of the molecular model • Control analysis (robustness, bifurcation, connectivity, etc) • Predictions • Repeat Steps 4 and 6 till necessary • Repeat for all the other modules in 1 so to have the molecular model of the entire process 3 5 The 4 M Strategy is: MINING of literature data, • 4 M Strategy to identify components MANIPULATION of major the module ofstructure a given module and function, 2 MEASUREMENT of regulatory components, • Extensive environmental (i. e. C and N MODELING and simulation. source modulation) and genetic (i. e. gene dosage, deletion, point mutation) perturbations of the function of the module • Refinement of spatio-temporal analysis (localization, determination of kinetic constants, etc. ) • Post-genomic analysis • Experimental verification of predictions 4 6 7 • Achievement of a complete molecular model of a given module 8 9 5

A case study: the cell cycle • In the budding yeast Saccharomyces cerevisiae cell cycle execution and control require the coordinated, time-dependent activity of at least 15 % of its 6000 genes • The coupling of cell growth to cell division is a universal but poorly understood feature of the cell cycle • The main regulatory event(s) takes place at START, when cells must reach a critical cell size (Ps) to enter into S phase. G 1 8 S G 2 M Ps

Circuits proposed to control Start in budding yeast Rupes I. , TIG (2002) 9 Jorgensen P. et al. , Science (2002) 3

Tyson & Novak’s model of budding yeast cell cycle Chen et al. , Mol Biol Cell (2004) • It accounts only for a few tens of molecular components against the hundreds involved • It does not offer satisfactory molecular explanations for the setting of the critical cell size Ps 4

From several rounds of experimental investigation Two growth regulated thresholds involving Cln 3/Far 1 and Clb 5, 6/Sic 1 control entrance into S phase and set the critical cell size Alberghina et al. , J. Cell. Biol. , 2004 Rossi et al. , manuscript in preparation 4

Work in progress in collaboration with Dr. Edda Klipp, MPI for Molecular Genetics, Berlin Key players in G 1/S transition • Compounds • Interactions Modeling of biochemical pathways • Basic elements of biochemical pathways • Control and Response in biochemical networks Data and Data Integration • Experimental Information • Determination of Kinetics Model of the G 1/S transition • Equations • Time Courses Experiment versus Simulation • Hypotheses 5

Model of the network controlling the G 1 to S transition 5

A few preliminary results Modeling glucose versus ethanol growth - 2 Concentration ( M) GLUCOSE Time (minutes) Concentration ( M) ETHANOL Time (minutes) 5

The Foresight • Systems biology addresses the analysis of entire biological systems. • This entails the investigation of all components and networks contributing to a systems. With dynamic computer modelling the properties of a cell, and ultimately the organism, can be simulated and altered. • The general strategy of systems biology employs iterative cycles of experimentations and predictions, which have been successfully applied in exact sciences, such as physics and chemistry. • Should they prove successful in systems biology, then biology will be transformed from an essentially descriptive discipline into an exact science. Concept paper of Systems X, Switzerland, 2004 15

What is happening in Europe? It all begins in 2004? International Systems Biology Conference 2004 in Heidelberg

Leading Countries – leading position of USA generally agreed – ranking reflects bibliometri c performan ce except Japan: low publication activities Source: EUSYSBIO survey by Fraunhofer ISI 2004 Introduction Actors Themes Organi. Training zation Frame- Con- work clusions

Leading Institutions – most leading institutes outside Europe – reflects advanced stage of USA, JP and IL Source: EUSYSBIO survey by Fraunhofer ISI 2004 Introduction Actors Themes Organi. Training zation Frame- Con- work clusions

What is happening now in Europe? • National programs – German Hepatocon: Systeme des Lebens (>20 M€) – Finland: System Biology and Bioinformatics (10. 5 M€) – UK: • BBSRC Integrative Biology 5 years program (>50 M€) • Three 9 M€ Centres in Manchester, Newcastle, London (yeast, aging, mammalian cells) • Three more to come – The Netherlands: • BCA; BCA Amsterdam research school on Systems Biology funding not yet settled • SBNL; SBNL set of organism focused programs (L. lactis, S. cerevisiae, E. coli, Silicon cell, . . . ), funding not yet settled • CMSB: CMSB Centre for Medical Systems Biology (Leiden, VUAmsterdam, Rotterdam): topdown – …. .

Publication forum Defining Systems Biology • • • • • Snoep, Jacky L. Goryanin, Igor Fell, David Eduardo Sontag Kummer, Ursula Ehrenberg, Måns Westerhoff, Hans V. Kholodenko, B. N. & Bruggeman, F. Wanner, B. , Finney, A. , Hucka, M. Sauer, U. Gilles, D. Reuss, M. Heinrich, R. Hohmann, S. Lauffenburger, D. Novak, B. Alberghina, Lilia Eils, R. Kitano, H.

The Grand Challenge: The interim report

The Grand Challenge:

Transnational initiatives • • German BMBF: Sys. Mo Preparing for microbial System Biology program Wants to go transnational Finnish, Dutch partners are goning to be involved • 2005/6: call for proposals • ERANET application (FP 6 support to organize this)

ESF forward look: Eurocore and more? • Various professorships in Systems Biology – Rostock – Manchester – Harvard – Bielefeld • European Master’s programs: See www. systembiology. net

The next appointment International Systems 6 International Conference on Biology Systems Biology Conference October 19 – 22, 2005 Boston, MA 2005 in Boston th

The team @ in Milan and Berlin Lilia Alberghina Marco Vanoni Edda Klipp Matteo Barberis Paola Coccetti Andrea Mastriani Lorenzo Querin Riccardo L. Rossi Vittoria Zinzalla 26 MAX PLANCK INSTITUT FÜR MOLEk. ULARE GENETIK Dip. di Biotecnologie e Bioscienze

ESF forward look: Eurocore and more? • Study to see if System Biology could be the ESF theme • This would then make ESF catalyze common research programs between national science foundations • Part of ESF ambitions to form a European Research Council • Aims for reporting Spring 2005