Algae and cyanobacteria in fluctuating (dynamic) light.

1. Algae and cyanobacteriain fluctuating (dynamic) light. LadislavNedbal Department of Biological Dynamics Institute of Systems Biology & Ecology CAS Zámek 136, 37333 Nové Hrady, Czech Republic

2. Solar biofuels from microorganisms, why not yet? 70% and 30% oil in wet biomass (adapted from Y.Chisti (2007) Biotechnology Advances 25: 294-306) 0 < (EFUEL –EM) /m2.year = (FE . Esolar - EM) /m2.year EM… construction, maintenance, fertilizers, pumping, harvesting, processing, refining, distribution…) EM … biological and technological constraint (≈ € !!!) Esolar … geographical constraint With yields ≈ 1-2 gal(oil) / m2 / year and oil price < $3 / gal: the capital cost depreciation < several $ / year

3. Solar biofuels from microorganisms … continued … 0 < (EFUEL –EM) /m2.year = (FE . Esolar - EM) /m2.year EM… construction, maintenance, fertilizers, pumping, harvesting, processing, refining, distribution…) EM … biological and technological constraint (≈ € !!!) Esolar … geographical constraint FE … thermodynamic, biological a technological constraint • Solutions: • Decrease the antenna • Dilute the light technologically in space • Dilute the light technologically in time Lost CO2 assimilation Used Irradiance

4. High density algal cultures

5. Cell light dynamics in dense algal cultures

6. Light dynamics in dense algal cultures B. A. C.

7. Constant mean irradiance, variable period & L:D ratio B Chlorella vulgaris 500 mE.m-2.s-1

8. Constant incident irradiance, variable period & L:D ratio A continuous Chlorella vulgaris I0=2000 mE.m-2.s-1 1ms 100ms 1s

9. Constant incident irradiance, variable L:D ratio 250 A 700 130 Chlorella vulgaris 10 ms period 1200 2400 mE.m-2.s-1

10. Constant incident irradiance, constant L:D, variable period 250 700 T 130 Chlorella vulgaris L:D=1:1, I0=2000 mE.m-2.s-1 1200 2400 mE.m-2.s-1

11. Rate of photoinhibition T= 10ms L:D=1:1, I0=2000 mE.m-2.s-1 Cont.I0=1000 mE.m-2.s-1

12. Electron transfer

13. Conclusions for flashing light effect in the ms-range:1) per area yield increase in dense cultures & high irradiance2) reduction of photoinhibition rates

14. Harmonic light forcing with periods > 1 s

15. Harmonic light forcing with periods > 1 s harmonic light input 2 amplitude non-linear output T offset

16. Simulation tool Nedbal et al.(2008) Biotechnology & Bioengineering 100: 902-910.

17. Non-linear fluorescence response Continuous light Oscillating light Nedbal et al. (2003) Biochim.Biophys.Acta: Bioenergetics 1607: 5-17 Nedbal, et al. (2005) Photosynth.Res. 84: 99–106

18. Non-linear response in dynamic light

19. Non-linear response caused by regulation

20. Non-linear response caused by regulation

21. Non-linear response caused by regulation

22. Non-linear response in growth Constant light Constant light T=10s T=100s

23. Diurnal light rhythm

24. Metabolic rhythms of the cyanobacterium Cyanothece sp. ATCC 51142 correlate with modeled dynamics of circadian clock.

25. Different L/D ratio.

26. Different L/D ratio.

27. Model prediction for circadian Kai clock confronted with metabolic dynamics in 12L: 12D

28. Model prediction for circadian Kai clock in 6L: 6D

29. Model prediction in 6L: 6D qualitatively confirmedby experiment

30. Modeling Tools

31. Models are able to simulate the non-linearity … poorly

32. Comprehensive modeling space, SBML, MIRIAM

33. …. soon to be continued

34. Collaborators: Photon Systems Instruments, Brno, CZ Jan Červený, Ondra Komárek, Víťa Březina from Nové Hrady, CZ Fusheng Xiong, Vláďa Tichý from Třeboň, CZ Johann Grobbelaar, UOFS Bloemfontain, S.Africa Himadri Pakrasi, WUSTL, St.Louis, USA Govindjee, UIUC, Urbana, USA Agu Laisk, Tartu, Estonia Conrad Mullineaux, London, UK Thank you for your attention!