Photosynthesis and Phototrophic Growth: Modelling Life on Earth and elsewhere Ralf Steuer Humboldt-University Berlin, Germany Institute of Theoretical Biology (ITB) CzechGlobe Global Change Research Centre, Brno, CZ Fakulta informatiky MU pondělí 14. 5. 2012, 14:00 Part I News and Events on May 14, 2012 Part II Cyanobacteria: understanding phototrophic growth Dynamics of large-scale networks Applications to biotechnology outline May 14, 2012, 0am outline outline Water, water, everywhere, ... Bacterial abundance in in stratified oligotrophic waters can be high (> 105 cells ml  -1 ) May 14, 2012, 0am outline Water, water, everywhere, ... Bacterial abundance in in stratified oligotrophic waters can be high (> 105 cells ml  -1 ) But no primary productivity ... May 14, 2012, 0am May 14, 2012, a few hours later ... outline May 14, 2012, a few hours later ... outline May 14, 2012, a few hours later ... outline sunrise over pacific May 14, 2012, and so Life begins ... outline May 14, 2012, and so Life begins ... outline The light reactions the light reactions The light reactions the light reactions photosystem II The light reactions: photosystem II the light reactions The light reactions: photosystem II the light reactions The light reactions: photosystem II the light reactions The light reactions: photosystem II the light reactions 2 2 The light reactions: photosystem II the light reactions 2 2 The light reactions: photosystem II the light reactions 2 2 water splitting ... the waste product The light reactions: eating the sun the light reactions The light reactions: eating the sun the light reactions NADPH ATP The light reactions: eating the sun the light reactions NADPH ATP A view from theory/modelling: Very fast processes (sub-second) Combinatorial number of states Modelling: either ODE or transition matrices The system is inherently dynamic Several reasonable models are available Fixation of atmospheric CO2 by RuBisCO carbon fixation ribulose-1,5-bisphosphate (RuBP, 5 carbon) CO2 3-phosphoglycerate (3 carbon) Fixation of atmospheric CO2 by RuBisCO carbon fixation ribulose-1,5-bisphosphate (RuBP, 5 carbon) CO2 3-phosphoglycerate (3 carbon) A view from theory/modelling: RubisCo is slow and sloppy Only few interconversions per second A limiting factor in phototrophic growth. Low specificity to its substrate Modelling: usually ODE/enzyme kinetics The Calvin-Benson-Bassham (CBB) cycle: Regeneration carbon fixation From: R. Steuer and B. H. Junker. (2009) Computational Models of Metabolism: Stability and Regulation in Metabolic Networks. Advances in Chemical Physics, Volume 142 The Calvin-Benson-Bassham (CBB) cycle: Regeneration carbon fixation From: R. Steuer and B. H. Junker. (2009) Computational Models of Metabolism: Stability and Regulation in Metabolic Networks. Advances in Chemical Physics, Volume 142 The Calvin-Benson-Bassham (CBB) cycle: Regeneration carbon fixation From: R. Steuer and B. H. Junker. (2009) Computational Models of Metabolism: Stability and Regulation in Metabolic Networks. Advances in Chemical Physics, Volume 142 A view from theory/modelling: Timescale: seconds to minutes About 20 reactions with 100 parameters. Typically implemented as ODE model Q: are there alternative cycles? The Calvin-Benson-Bassham (CBB) cycle: Regeneration carbon fixation biomass NADPHATP 3-phosphoglycerate from: Knoop, Zilliges, Lockau, Steuer. Plant Physiology (2010) cyanobacteria: phototrophic growth Cellular metabolism: facilitated by a network of reactions from: Knoop, Zilliges, Lockau, Steuer. Plant Physiology (2010) cyanobacteria: phototrophic growth Cellular metabolism: facilitated by a network of reactions from: Knoop, Zilliges, Lockau, Steuer. Plant Physiology (2010) reconstruct validate analyze A view from theory/modelling: Large systems with hundreds of reactions Assumption of stationarity Flux-balance analysis (FBA) → Linear programming (LP) → optimization of objective functions More to come ... cyanobacteria: phototrophic growth Cellular metabolism: facilitated by a network of reactions from: Knoop, Zilliges, Lockau, Steuer. Plant Physiology (2010) cyanobacteria: phototrophic growth Cellular metabolism: facilitated by a network of reactions cyanobacteria: phototrophic growth Phototrophic growth and the environment: cyanobacteria: phototrophic growth Phototrophic growth and the environment: cyanobacteria: phototrophic growth May 14, 2012, 11:59pm, by the end of the day ... 1.1 × 1019 joule solar energy is absorbed by Earth's atmosphere, oceans and land masses per day … 600 000 000 tons of carbon fixed by photosynthesis 120 Gt carbon per year (land) 90 Gt carbon per year (ocean) Cyanobacteria: a hierarchy of processes We aim to understand the life and growth of cyanobacteria cyanobacteria: the CyanoNetwork Cyanobacteria: a hierarchy of processes We aim to understand the life and growth of cyanobacteria cyanobacteria: the CyanoNetwork The CyanoTeam and CyanoNetwork An association between several groups from EU, Israel, and USA to model and understand a cyanobacterial cell in silico. International team led by John Whitmarsh Coordinator local experimental team: Ladislav Nedbal Coordinator local modelling team: Ralf Steuer Cyanobacteria: a hierarchy of processes We aim to understand the life and growth of cyanobacteria cyanobacteria: the CyanoNetwork The CyanoTeam and CyanoNetwork An association between several groups from EU, Israel, and USA to model and understand a cyanobacterial cell in silico. International team led by John Whitmarsh Coordinator local experimental team: Ladislav Nedbal Coordinator local modelling team: Ralf Steuer Cyanobacteria: understanding phototrophic growth cyanobacteria phototrophic micro-organisms (prokaryotes) capable of oxygen-evolving photosynthesis Cyanobacteria: understanding phototrophic growth cyanobacteria phototrophic micro-organisms (prokaryotes) capable of oxygen-evolving photosynthesis globally extremely abundant The cyanobacterium Prochlorococcus is the numerically dominant phototroph in some oceans (up to half of the photosynthetic biomass). Cyanobacterial abundance in in stratified oligotrophic waters can be high (> 105 cells ml  -1 ) from: Sullivan et al. Nature (2003) Cyanobacteria: understanding phototrophic growth cyanobacteria phototrophic micro-organisms (prokaryotes) capable of oxygen-evolving photosynthesis globally extremely abundant first mass-producers of free molecular oxygen responsible for the Great Oxygenation Event (GOE) around 2.4 billion years ago. Cyanobacteria: understanding phototrophic growth cyanobacteria phototrophic micro-organisms (prokaryotes) capable of oxygen-evolving photosynthesis globally extremely abundant first mass-producers of free molecular oxygen ancestors of modern day chloroplasts relevant for the global carbon cycle Cyanobacteria: understanding phototrophic growth cyanobacteria phototrophic micro-organisms (prokaryotes) capable of oxygen-evolving photosynthesis globally extremely abundant first mass-producers of free molecular oxygen ancestors of modern day chloroplasts relevant for the global carbon cycle live as symbionts and in communities relevance for biotechnology (biofuels) Cyanobacteria: understanding phototrophic growth cyanobacteria relevance for biotechnology (biofuels) An open pond Spirulina farm: Cyanobacteria: understanding phototrophic growth cyanobacteria relevance for biotechnology (biofuels) Cyanobacteria: understanding phototrophic growth cyanobacteria relevance for biotechnology (biofuels) Cyanobacteria: a modular approach We aim to understand the life and growth of cyanobacteria cyanobacteria Cyanobacteria: a modular approach cyanobacteria Energy: ATP Redox: NADPH Cyanobacteria: a modular approach cyanobacteria Energy: ATP Redox: NADPH Cyanobacteria: a modular approach cyanobacteria Energy: ATP Redox: NADPH Cyanobacteria: a modular approach cyanobacteria Energy: ATP Redox: NADPH Cyanobacteria: a modular approach cyanobacteria DNA topology Energy: ATP Redox: NADPH Cyanobacteria: a modular approach cyanobacteria DNA topology Transcriptome Energy: ATP Redox: NADPH Cyanobacteria: a modular approach cyanobacteria DNA topology Transcriptome Energy: ATP Redox: NADPH CCM THE ENVIRONMENT Cyanobacteria: a hierarchy of processes Phototrophic growth and the environment cyanobacteria: from biology to ecology cyanobacteria: phototrophic growth Phototrophic growth and the environment: Cyanobacteria: a hierarchy of processes Phototrophic growth and the environment cyanobacteria: photobioreactor Cyanobacteria: a hierarchy of processes Phototrophic growth and the environment Stefan Mueller et al. An integrated model of photosynthetic growth in a bioreactor: gas-liquid mass transfer, carbonate chemistry, and cellular fluxes (to be completed soon). Traditional ODE model for gas-liquid mass transfer: plus carbonate chemistry and a light gradient. cyanobacteria: photobioreactor cyanobacteria: a hierarchy of processes Biophysics of photosynthesis and the light reactions ODE models of cellular metabolism and CCMs Integration of the cyanobacterial circadian clock Integration of gene expression and signalling Need to integrate diverse computational methodologies to describe sub-processes Necessitates a community approach: The international CyanoTeam Cyanobacteria: a hierarchy of processes We aim to understand the life and growth of cyanobacteria Modelling cellular metabolism Understanding phototrophic growth in a complex environment modelling metabolism Steuer, Knoop, Machne. Journal of Experimental Botany (2012) Modelling cellular metabolism Understanding phototrophic growth in a complex environment modelling metabolism Modelling cellular metabolism Mechanistic versus teleological models Based on mechanistic details of the underlying processes (bottom-up) modelling metabolism Modelling cellular metabolism Mechanistic versus teleological models Based on constraints and optimization principles (top-down). Widely applied to study flux distributions in metabolic network modelling metabolism Modelling cellular metabolism Mechanistic versus teleological models All results are based on a high-quality reconstruction of the underlying network of biochemical interconversions. modelling metabolism Modelling cellular metabolism Mechanistic versus teleological models All results are based on a high-quality reconstruction of the underlying network of biochemical interconversions. Metabolic reconstruction: a compendium of all biochemical interconversions of small molecules within a cell. modelling metabolism [1] Start with databases and genome sequence: Initial draft network [2] Identify gaps and inconsistencies: manual curation and literature mining [3] Convert to mathematical model: Include pseudo-reactions for cellular maintenance [4] Analyse the model using contraint-based optimization The whole process is iterative and is repeated several times! Modelling cellular metabolism A stoichiometric model of Synechocystis sp. PCC6803 modelling metabolism: network reconstruction Modelling cellular metabolism A stoichiometric model of Synechocystis sp. PCC6803 From: Steuer et al. JXB (2012) modelling metabolism: network reconstruction Modelling cellular metabolism A stoichiometric model of Synechocystis sp. PCC6803 Plot by H. Knoop (HU Berlin), see also Knoop et al. Plant Physiology (2010) modelling metabolism: network reconstruction Modelling cellular metabolism A stoichiometric model of Synechocystis sp. PCC6803 Plot by H. Knoop (HU Berlin), see also Knoop et al. Plant Physiology (2010) modelling metabolism: network reconstruction Modelling cellular metabolism A stoichiometric model of Synechocystis sp. PCC6803 Analyse the model using contraint-based optimization v1 v2 v3 Assuming stationary conditions: v1 – v2 – v3 = 0 modelling metabolism: FBA Modelling cellular metabolism A stoichiometric model of Synechocystis sp. PCC6803 Analyse the model using contraint-based optimization More general: 2nd assumptions: metabolic fluxes are organized such that a given (usually linear) objective function Z is maximized. modelling metabolism: FBA Modelling cellular metabolism A stoichiometric model of Synechocystis sp. PCC6803 Analyse the model using contraint-based optimization See: Steuer and Junker. Advances in Chemical Physics (2009) modelling metabolism: FBA Modelling cellular metabolism A stoichiometric model of Synechocystis sp. PCC6803 From: Steuer et al. JXB (2012) modelling metabolism: FBA A stoichiometric model of Synechocystis 6803 Applications of constraint-based optimization ● Optimal flux patterns (maximal biomass yield) ● Flux-variability analysis ● Gene essentiality analysis ● Reaction coupling (with A. Bockmayr, FU Berlin) modelling metabolism: FBA A stoichiometric model of Synechocystis 6803 Optimal flux patterns (maximal biomass yield) flux distribution: growth rate/yield: modelling metabolism: FBA A stoichiometric model of Synechocystis 6803 Gene essentiality analysis: network validation still viable? 126 (of 337) genes are classified as  essential for biomass formation: Comparison with CyanoMutants new hypotheses/questions! modelling metabolism: FBA A stoichiometric model of Synechocystis 6803 Applications of constraint-based optimization: Biofuels cyanobacteria: biofuels A stoichiometric model of Synechocystis 6803 The model as a platform for strain improvement cyanobacteria: biofuels Atsumietal.,2007 A stoichiometric model of Synechocystis 6803 The model as a platform for strain improvement cyanobacteria: biofuels product CO2 ATP NAD(P)H “photons” ethanol 2 8 6 24.33 ethylene 2.5 23.5 12 64.92 isobutanol 4 18 12 51 isoprene 5 22 13 60.66 cyanobacteria: biofuels From lab to applications: large-scale cultivation of Synechocystis sp. PCC 6803 cyanobacteria: biofuels From lab to applications: large-scale cultivation of Synechocystis sp. PCC 6803 Culture Duration: 79 days/Final EtOH Conc. : 0.15 %(v/v) A stoichiometric model of Synechocystis 6803 Applications of constraint-based optimization: Biofuels Introduce fuel pathways into the stoichiometric reconstruction www.directfuel.eu cyanobacteria: biofuels ­ contributions to host optimization and metabolic streamlining ­ identify main routes of synthesis for precursor metabolites ­ prediction of optimal knockout targets for product formation A stoichiometric model of Synechocystis 6803 CHALLENGES AND EXTENSIONS OF FBA ● Thermodynamic consistency ● The costs of pathways: minimum-cost flow problems ● Temporal coordination of metabolism modelling metabolism: beyond FBA A stoichiometric model of Synechocystis 6803 Temporal coordination of metabolism modelling metabolism: temporal coordination A stoichiometric model of Synechocystis 6803 Temporal coordination of metabolism Light metabolism Dark metabolism Storage modelling metabolism: temporal coordination A stoichiometric model of Synechocystis 6803 Temporal coordination of metabolism Circadian time Expressionofmetabolicgenes Indeed, cyanobacterial metabolism follows a complex circadian program Most genes expressed during light period Data: group of I. Axmann (ITB, Berlin) Clustering/Data analysis: Rob Lehmann, Rainer Machne submitted modelling metabolism: temporal coordination A stoichiometric model of Synechocystis 6803 Temporal coordination of metabolism A time-dependent objective function: modelling metabolism: temporal coordination modelling metabolism: summary Modelling cellular metabolism: summary Understanding phototrophic growth in a complex environment Biological systems typically involve multiple temporal and spatial scales: need for different methodologies. It is a conceptual and computational challenge to integrate diverse systems into a coherent whole. Of most interest are intermediate methods that allow to deal with incomplete and uncertain data. Large-scale predictive models of cells are possible: computational biology needs to integrate parts into a coherent whole The end Thanks for your attention! And thanks to the group in Berlin: Henning Knoop Sabrina Hoffmann Stefan Mueller Natalie Stanford Raik Otto Robert Lehmann (with I. Axmann) And other people involed Ilka Axmann (ITB) Rainer Machne (ITB, Wien) Wolfgang Lockau (HU) Ettore Murabito (Manchester) Hans Westerhoff (Manchester) Lada Nedbal (Brno, CZ) Wolfgang Hess (ALU-FR) Patrik Jones (Turku)