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Options to engineer higher photosynthetic energy conversion efficiency

Options to engineer higher photosynthetic energy conversion efficiency. Xinguang Zhu 1,2 1.Plant Systems Biology Group, Partner Institute of Computational Biology, Chinese Academy of Sciences/Max Planck Society 2. Institute of Genomic Biology, University of Illinois at Urbana Champaign.

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Options to engineer higher photosynthetic energy conversion efficiency

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  1. Options to engineer higher photosynthetic energy conversion efficiency Xinguang Zhu1,2 1.Plant Systems Biology Group, Partner Institute of Computational Biology, Chinese Academy of Sciences/Max Planck Society 2. Institute of Genomic Biology, University of Illinois at Urbana Champaign Solar Biofuels from Microorganisms

  2. Road Map • The rationale behind increasing energy conversion efficiency • Realizing the maximal energy conversion efficiency • Maintaining the energy conversion efficiency

  3. Total solar energy Conversion efficiency  S i c Partitioning efficiency Interception efficiency What determines harvested yield? Wh = For modern cultivars of the major food crops i = 90% and  = 60%; but c = ca. 0.5% Harvested yield Monteith (1977) Philosophical Transactions of the Royal Society of London

  4. 6% 4.6% Zhu et al (2008) Current Opinion in Biotechnology

  5. What ec is achieved in the field? • The highest ec over a whole growing season: • C3: 2.4% • C4: 3.7% • Common ec over a whole growing season: • < 0.5% Reviewed in: Zhu et al (2008) Current Opinion in Biotechnology

  6. e-Plant concept

  7. Photosynthetic energy conversion efficiency Long et al (1994) ARPPPMB

  8. Realizing the maximal energy conversion efficiency • Nitrogen redistribution in the photosynthetic carbon metabolism • Manipulations of Rubisco kinetics • Design new pathway • Transforming C3 photosynthesis into C4 photosynthesis

  9. Model of carbon metabolism 13 Ru5P Ru5P Ru5P Ru5P Ru5P Ru5P ATP ATP ADP ADP 11 11 12 12 Ri5P Ri5P Xu5P Xu5P 10 10 Starch Starch S7P S7P 12 12 Pi Pi 9 9 25 25 PPi PPi Pi Pi RUBP RUBP SBP SBP Stroma 23 23 CO CO 8 8 2 2 ATP ATP E4P E4P Xu5P Xu5P ADPG ADPG O O 2 2 1 1 7 7 G1P G1P 111 111 22 22 21 21 PGCA PGCA F6P F6P G6P G6P PGA + PGA PGA + PGA Pi Pi 6 6 PGA PGA ATP ATP 112 112 FBP FBP 2 2 ADP ADP 5 5 GAP GAP DHAP DHAP GAP GAP NADPH NADPH Pi Pi NADP+Pi NADP+Pi +H +H 113 113 ADP ADP DHAP DHAP GAP GAP DHAP DHAP DPGA DPGA ATP ATP GAP GAP GCA GCA 4 4 3 3 GCEA GCEA Pi Pi Pi Pi Pi Pi 101 31 31 33 32 101 Pi Pi GCEA GCEA GCA GCA Pi Pi Pi Pi O O Sink DHAP DHAP GAP GAP 2 2 PGA PGA NADH NA 121 121 123 123 H H O O 2 2 2 2 + NAD OP GOA GOA HPR HPR 57 F6P SUCP SUC GLY GLY GLU GLU 122 122 124 124 62 56 KG KG GOA GOA 52 53 54 Sink FBP F6P G6P G1P UDPGlu SER SER GLY GLY UDP 131 131 UDP + + GLY + NAD GLY + NAD CO CO + NADH + NADH OP 2 2 ATP 55 55 58 59 60 61 61 OPOP 2OP UTP ADP Cytosol, mitochondria, and peroxisome F26BP Drawn based on Zhu et al (2007) Plant Physiology 145: 513-526

  10. Construct the rate equations Develop the ordinary differential equations (ODE) Solve the system of ODEs Yes Algorithm ? No Stable Solution ? No Yes No Realistic ? Numerical experiments Finished Yes Algorithms for building dynamic systems models Establish the reaction diagram Drawn based on Zhu et al (2007) Plant Physiology 145: 513-526

  11. Validations Zhu et al (2007) Plant Physiology

  12. Evolutionaryalgorithm at work 400 % of beginning 300 200 100 0 PGA Kinase Photosynthesis GCEA Kinase HPR reductase Aldolase Transketolase cFBP aldolase Rubisco FBP aldolase FBPase SBPase PRK ADPGPP GOA Oxidase GSAT GGAT GDC cFBPase F26BPase PGCAPase SPS UDPGP SPP GAPDH Zhu et al (2007) Plant Physiology

  13. Theoretical optimal concentrations of enzymes in carbon metabolism Zhu et al (2007) Plant Physiology

  14. Raines (2003)Photosynthesis Research

  15. Zhu et al (2004) Plant Cell Environ

  16. RuBP-limited Photosynthesis t CO2 uptake Rubisco-limited Photosynthesis kcc Steady State Photosynthesis Model CO2 + H2O + Light Energy  CH2O + O2 Light Farquhar et al (1980) Planta

  17. Zhu et al (2004) Plant Cell Environ

  18. IPCC 2001 Rubisco http://www.biochimie.univ-montp2.fr/licence/qabs/alfa_beta/tonneau/rubisco/rubisco_rub10.gif

  19. Species Ac' (mmol m-2 day-1) Ac' (% increase) Asat (mmol m-2 s-1) Current average C3 crop (kcc = 2.5, t = 92.5) 1040 0 14.9 Griffithsia monilis (kcc = 2.6, t = 167) 1430 27 21.5 Amaranthus edulis (kcc = 7.3, t = 82) 1250 17 28.3 Amaranthus edulis/current (kcc = 7.3, t = 82) (kcc = 2.5, t = 92.5) 1360 31 28.3 Zhu et al (2004) Plant Cell Environ; Long et al (2006) Plant Cell Environ

  20. New Pathways Design Kebeish et al 2007 Nature

  21. Engineering photorespiratory bypass leading to substantial increase in photosynthesis • The saving of ATP from decreased release of NH4+ release did not contribute to the increase in photosynthesis. • Releasing CO2 in chloroplast is key to successfully engineer photorespiratory bypass. Kebeish et al 2007 Nature

  22. Maintaining Efficiency • Photo-protection • Temperature Stresses • Water stress

  23. Photoprotective state changes light response curve Asat  Non-Photoprotective CO2 uptake Photoprotective  Light Level

  24. Asat  CO2 uptake  High Light Low Light Light

  25. A Light Level 12% ↓ 0.2% ↓

  26. Case 2 Case 1 The Reverse Ray Tracing Algorithm Zhu et al (2004) J. Exp. Botany

  27. Zhu et al (2004) J. Exp. Botany

  28. Zhu et al (2004) J. Exp. Botany

  29. Options to engineer higher photosynthetic energy conversion efficiency (ec)

  30. Why hasn’t evolution already maximized photosynthetic production ?

  31. Wild plants versus designed crops (1) The Calvin Cycle Photo-respiratory pathway Photo-respiratory pathway The Calvin Cycle Designed final leaf Beginning leaf 25 oC Well watered

  32. Wild plants versus designed crops (2) The Calvin Cycle Photo-respiratory pathway Photo-respiratory pathway The Calvin Cycle Designed final leaf Beginning leaf 45 oC Drought

  33. Wild plants versus designed crops (3)

  34. Systems Biology and Synthetic Biology Systems Biology:Resource use efficiency, optimality, plasticity, environmental stochasticity and heterogeneity, genetic constraints … … Mathematical Models + Evolutionary algorithms Synthetic Biology:New pathway design, new genetic regulatory network design , redesign existing parts, devices, systems etc … …

  35. Conclusions • There is much potential to further increase energy conversion efficiency. • The photosynthetic energy conversion efficiency can be increased by both realizing the maximal energy conversion efficiency and maintaining higher energy conversion efficiency under stress conditions. • It is time now to use rationale design to engineer higher photosynthesis.

  36. ACKNOWLEDGEMENTS PICB Vincent Devloo Danny Tholen GuiLian Zhang FuQiao Xu LinYing Lu Caroline Tholen ChangPeng Xin YuJing Sun Xin Yan Li Kai Chang Xiao HongBo Lei Roman SU Collaborators Prof. Steve Long (Plant Biology/UIUC) Prof. Donald Ort (Plant Biology/UIUC) Prof. Archie Portis (Plant Biology/UIUC) Prof. Eric de Sturler (Math/VT) Prof. Govindjee (Plant Biology/UIUC)

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