Engineering of Biological Processes Lecture 6: Modeling metabolism

1. Engineering of Biological ProcessesLecture 6: Modeling metabolism Mark Riley, Associate Professor Department of Ag and Biosystems Engineering The University of Arizona, Tucson, AZ 2007

2. Objectives: Lecture 6 • Model metabolic reactions to shift carbon and resources down certain paths • Evaluate branch rigidity

3. r1 = vmax1 S Low Km High Km Km1 + S Michaelis Menten kinetics Low Km will be the path with the higher flux (all other factors being equal). Low Km also means a strong interaction between substrate and enzyme. These two curves have the same vmax, but their Km values differ by a factor of 2.

4. Example: Enhancement of ethanol production • Want to decrease the cost • Cheaper substrates • Greater number of substrates • Not just glucose • Higher rates of production • Yp/s Yield of product per substrate consumed • Yp/x Yield of product per cell

5. Species used • Saccharomyces cerevisiae • Produces a moderate amount of ethanol • Narrow substrate specificity (glucose) • Zymomonas mobilis • Produces a large amount of ethanol • Narrow substrate specificity (glucose) • Escherichia coli • Broad substrate specificity • Low ethanol production • Much is known about its genetics

6. Goal Combine the advantages of ZM + EC

7. 1st attempt: amplify PDC activity Resulted in accumulation of acetaldehyde. No significant increase in EtOH. Increase in byproducts from acetaldehyde 2nd attempt: amplify PDC activity & ADH (alcohol dehydrogenase) Gave a significant increase in EtOH Ethanol production

8. Km = 0.4 mM Ethanol Km = 0.4 mM Acetate Km = 2.0 mM Lactate Km = 7.2 mM This approach worked because of the large differences in Km’s

9. F1 F2 + vmax2 S vmax2 S = Km2 + S Km2 + S Ftot = vmax1 S vmax1 S Km1 + S Km1 + S Some definitions Total flux Selectivity

10. Selectivity So, to enhance r1, we want a small value of Km1

11. Model conversion of pyruvate

12. Model conversion of pyruvate

13. Model production of ethanol

14. Ethanol Km = 0.4 mM

15. Ethanol Km = 1 mM

16. Ethanol Km = 10 mM

17. NADH NADH CO2+NADH GTP CO2+NADH GDP+Pi FADH2 2-Keto-3-deoxy-6- phosphogluconate Glucose Glucose 6-Phosphate Phosphogluconate Fructose 6-Phosphate Fructose 1,6-Bisphosphate Glyceraldehyde 3-Phosphate Glyceraldehyde 3-Phosphate + Pyruvate Glyceraldehyde 3-Phosphate Phosphoenolpyruvate Acetaldehyde Pyruvate Lactate Acetyl CoA Acetate Ethanol Citrate Oxaloacetate Isocitrate Malate a-Ketoglutarate Fumarate Succinate

18. Glucose Glucose 6-Phosphate Phosphogluconate Fructose 6-Phosphate Fructose 1,6-Bisphosphate Glyceraldehyde 3-Phosphate Phosphoenolpyruvate Pyruvate

19. v6 ADP ATP v7 ATP ADP v8 ATP + AMP 2 ADP Simplified metabolism - upstream end of glycolysis ADP ADP ATP ATP v1 v2 Glucose Glucose 6-Phosphate v3 Additional reactions Fructose 6-Phosphate ATP v4 ADP Fructose 1,6-Bisphosphate v5 Pyruvate

20. How do you model this? • What information is needed? • equations for each v • initial concentrations of each metabolite

21. Mass balances

22. Mass balances

24. Metabolite profiles

25. Rates of reaction

27. S I P1 P2 Reaction branch nodes Flux of carbon J1 J1 = J2 + J3 J2 J3 Product yields are often a function of the split ratio in branch points (i.e., 20% / 80% left / right).

28. Types of reaction branch nodes (rigidity) • Flexible nodes • Flux partitioning can be easily changed • Weakly rigid nodes • Flux partitioning is dominated by one branch of the pathway • Deregulation of supporting pathway has little effect on flux • Deregulation of dominant pathway has large effect on flux • Strongly rigid nodes • Flux partitioning is tightly controlled • Highly sensitive to regulation

29. S I - - P1 P2 Types of reaction branch nodes Regulation Negative feedback

30. Flexible nodes • The split ratio will depend on the cellular demands for the 2 products • Can have substantial changes in the flux partitioning

31. Rigid nodes • Partitioning is strongly regulated by end product activation and inhibition • Deregulation of such a node can be very difficult to perform

32. S S I - - I + - - P1 P2 Weakly rigid node P1 P2 Flexible node S I - - + + P1 P2 Strongly rigid node Regulation Negative feedback Regulation Positive feedback

33. Branch point effect Citrate Glyoxylate shunt (cells grown on acetate) For growth on acetate, Isocitrate = 160 mM Isocitrate Isocitrate Dehydrogenase (IDH) Km=8 mM Vmax=126 mM/min Lyase (IL) Km=604 mM Vmax=389 mM/min Glyoxylate a-Ketoglutarate

34. Flux is very sensitive to [isocitrate] first order in IL, zero order in IDH 160 mM When [S] = 50 uM, r IL = 110 uM/min r IDH = 20 uM/min When [S] = 160 uM, r IL = 120 uM/min r IDH = 60 uM/min

35. Branch point effect Citrate Glyoxylate shunt (cells grown on glucose) For growth on glucose, Isocitrate = 1 mM Isocitrate Dehydrogenase (IDH) Km=8 mM Vmax=625 mM/min Lyase (IL) Km=604 mM Vmax=389 mM/min Vmax had been =126 mM/min Glyoxylate a-Ketoglutarate

36. Flux is not sensitive to [isocitrate] first order (but very low) in IL, first order in IDH 1 mM Note that [S] is much lower than before.

38. Which path controls the branch ratio? Citrate Under growth by glucose, Isocitrate = 1 mM Glyoxylate shunt (cells grown on glucose) Isocitrate Dehydrogenase (IDH) Km=8 mM Vmax=625 mM/min Lyase (IL) Km=604 mM Vmax=389 mM/min Glyoxylate a-Ketoglutarate

39. Which path controls the branch ratio? • The one that adapts to the available substrate controls the branch. • This depends on the values of vmax, Km, and [S] for each reaction.