Departments of Bioengineering Rice University Houston, Texas

1. Metabolic Engineering and Systems Biotechnology Ka-Yiu San Departments of Bioengineering Rice University Houston, Texas

2. What is metabolic engineering? Metabolic engineering is referred to as the directed improvement of cellular properties through the modification of specific biochemical reactions or the introduction of new ones, with the use of recombinant DNA technology

4. Recombined plasmid Restriction cleavage mRNA Gene of interest Translation Restriction sites Ligation Transcription Protein Restriction cleavage Transformation Cloning vector Host cell Cloning for rProtein production

5. Recombinant proteins by microorganisms Some early products Year Products Disease Company 1982 Humulin Type 1 diabetes Genetech, Inc. (synthetic insulin) 1985 Protropin Growth hormone Genetech, Inc. Deficiency

6. Examples of a few biopharmaceutical products in 1994 Source: Biotechnology Industry Organization, Pharmaceutical Research and Manufacturers of America, company results, analyst reports

7. NADH (Reduced) NAD+ (Oxidized) Current projects • Cofactor engineering of Escherichia coli • Manipulation of NADH availability • Manipulation of CoA/acetyl-CoA • Plant metabolic engineering • 3. Quantitative systems biotechnology • A. Rational pathway design and optimization • Metabolic flux analysis based on dynamic genomic information • Design and modeling of artificial genetic networks • Metabolite profiling • Genetic networks – architectures and physiology

8. Protein/ enzyme Gene mRNA transcription Modern biology – central dogma translation

9. Protein/ enzyme Gene mRNA transcription translation • Current metabolic engineering approaches • Amplification of enzyme levels • Use enzymes with different properties • Addition of new enzymatic pathway • Deletion of existing enzymatic pathway Genetic manipulation

10. Cofactor engineering

11. Motivations and hypothesis • Motivations • Existing metabolic engineering methodologies include • pathway deletion • pathway addition • pathway modification: amplification, modulation or use of isozymes (or enzyme from directed evolution study) with different enzymatic properties • Cofactors play an essential role in a large number of biochemical reactions Hypothesis Cofactor manipulation can be used as an additional tool to achieve desired metabolic engineering goals

12. Enzymes + Cofactors Substrate Products Importance of cofactor manipulation

13. Cofactor engineering • NAD+/NADH • CoA/acetyl-CoA

14. NADH (Reduced) NAD+ (Oxidized) NADH/NAD+ Cofactor Pair • Important in metabolism • Cofactor in > 300 red-ox reactions • Regulates genes and enzymes • Donor or acceptor of reducing equivalents • Reversible transformation • Recycle of cofactors necessary for cell growth

15. Coenzyme A (CoA) • Essential intermediates in many biosynthetic and energy yielding metabolic pathways • CoA is a carrier of acyl group • Important role in enzymatic production of industrially useful compounds like esters, biopolymers, polyketides etc.

16. Acetyl-CoA • Entry point to Energy yielding TCA cycle • Important component in fatty acid metabolism • Precursor of malonyl-CoA, acetoacetyl-CoA • Allosteric activator of certain enzymes

17. Biopolymer production Poly(3-hydroxybutyrate- co-3-hydroxyvalerate) (PHB/PHV block copolymer) Glycerol Propionate Acetyl-CoA Propionyl-CoA Acetyl-CoA 3-Ketothiolase (PhaA) HSCoA Acetoacetyl-CoA 3-Ketovaleryl-CoA NADPH Acetoacetyl-CoA Reductase (PhaB) NADP+ 3-Hydroxybutyryl-CoA 3-Hydroxyvalery-CoA PHA Synthase (PhaC) HSCoA HSCoA P(HB-co-HV)

18. Polyketide production • Complex natural products • > 10,000 polyketides identified • Broad range of therapeutic applications • Cancer (adriamycin) • Infection disease (tetracyclines, erythromycin) • Cardiovascular (mevacor, lovastatin) • Immunosuppression (rapamycin, tacrolimus) 6-deoxyerythronolide B

19. Polyketide production Precursor supply - example Ref: Precursor Supply for Polyketide Biosynthesis: The Role of Crotonyl-CoA Reductase, Metabolic Engineering 3, 40-48 (2001)

20. Approach Systematic manipulation of cofactor levels by genetic engineering means Results • increased NADH availability to the cell • increased levels of CoA and acetyl CoA • significantly change metabolite redistribution

21. Metabolic engineering of plant tissue

22. Motivations To improve the production of some important plant compounds though metabolic engineering

23. Catharanthus roseus • Vincristine & Vinblastine • lymphomas • breast cancer • testicular cancer • Ajmalicine & Serpentine • anti-hypertension Hairy Roots • model for metabolic engineering • increased genetic stability over cell cultures • fast differentiated growth • higher alkaloid productivity than cell cultures

24. Transgenic C. roseus Work • Cell Culture • 35S Expression of ORCA3, STR, TDC AS • Indole Pathway • Feedback Resistant AS • TDC overexpression TDC • Terpenoid Pathway • Appears limiting in most cases • DXS used to increase terpenoid flux in E. coli • G10H hypothesized to be rate limiting • TIA Pathway • Developmental and Environmental Reg. • Hairy Roots produce large amounts of Tab and derivatives • Vindoline is desired goal

25. Clone Generation Adapt to Liquid Media (16 weeks) Plasmid Construction in E. coli ATCC 15834 A. rhizogenes Desired gene Ri Sterile Grown Plants (5 weeks) Infection (6 weeks) Selection Media (6 weeks)

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29. Transgenic C. roseus Work • Cell Culture • 35S Expression of ORCA3, STR, TDC AS • Indole Pathway • Feedback Resistant AS • TDC overexpression TDC • Terpenoid Pathway • Appears limiting in most cases • DXS used to increase terpenoid flux in E. coli • G10H hypothesized to be rate limiting • TIA Pathway • Developmental and Environmental Reg. • Hairy Roots produce large amounts of Tab and derivatives • Vindoline is desired goal

30. Artemisia annua • Sweet wormwood, sweet annie • Wormwood is a hardy perennial herb native to Europe but now found throughout the world. The wormwood bush can grow to a height of 2 meters, and produces a number of bushy stems that are covered with fine, silky grey-green hairs. Wormwood produces small yellow-green flowers from Summer through to early autumn or fall

31. Motivation • The malaria parasite has developed resistance to most current anti-malaria drugs • Artemisinin – kills the parasite with no observed resistance so far, cures 90% of the people within days, and has few side effects • Only half of the 60 million doses of new anti-malaria drugs anticipated to be needed in Africa will be delivered in 2005 • Plants grown on Chinese and Vietnamese farms have not kept up with demand • Result cost is 10-20 times more expensive than existing drugs • GOOD TARGET for Metabolic Engineering (SCIENCE VOL 307 7 JANUARY 2005 p33)

32. 3-Acetyl-CoA Pyruvate + G3P DXS HMG-CoA 1-Deoxy-D-Xylulose-5-Phosphate HMGR DXR Mevalonate 2-C-Methyl-D-erythritol-4-phosphate DMAPP IPP ? IPP ? CYTOSOL FPPS IPP DMAPP FDP PLASTID SQS SQC GPP Squalene Sesquiterpenes Monoterpenes, diterpenes, carotenoids, etc. Artemisinin Sterols (Souret et al. 2003) Amorpha-4,11-diene Artemisinic Acid FDP Artemisinin

34. Strategy for ME m/z spectra for artemisinin • Detect artemisinin in hairy roots using LCMS Artemisinin (283.1)

35. 3-Acetyl-CoA Pyruvate + G3P DXS HMG-CoA 1-Deoxy-D-Xylulose-5-Phosphate HMGR DXR Mevalonate 2-C-Methyl-D-erythritol-4-phosphate DMAPP IPP ? IPP ? CYTOSOL FPPS IPP DMAPP FDP PLASTID SQS SQC GPP Squalene Sesquiterpenes Monoterpenes, diterpenes, carotenoids, etc. Artemisinin Sterols (Souret et al. 2003) Amorpha-4,11-diene Artemisinic Acid FDP Artemisinin

36. Quantitative systems biotechnology

37. Projects • Metabolic flux analysis based on dynamic genomic information • Rational pathway design and optimization • feasible and realizable new network design • Design and modeling of artificial genetic networks

38. Metabolic Network (From http://www.genome.ad.jp/kegg/pathway/map/map00020.html)

39. Metabolic Pattern (Illustration) 1.0 0.8 0.2 0.8: Metabolic rates (From http://www.genome.ad.jp/kegg/pathway/map/map00020.html)

40. Genome Database Pathway Database FBA Metabolic Pattern Metabolic Network A priori Knowledge Traditional flux balance analysis (FBA)

41. genotype phenotype environmental genetic perturbations perturbations (mutant strains) Cellular Responses Transcription Translation Metabolic Flux Analysis OR Metabolite Patterns Protein/ enzyme Gene mRNA Stimuli traditional metabolic engineering study

42. ? Genome Database Pathway Database Genetic Structure Expression Patterns Genetic Network A priori Knowledge FBA Metabolic Network Metabolic Patterns Gene Regulation Knowledge Gene Chip (Array) Data Proposed New Approach Environmental Conditions

43. Model System • Oxygen and redox sensing/regulation system • Sugar utilization regulatory network

44. Simplified schematic of E. coli central metabolic pathways Glucose PEP Pyruvate Lactate ldhA [1.1.1.28] NAD+,CoA ppc [4.1.1.31] NADH, CO2 pdh [1.2.4.1] CoA pfl [2.3.1.54] H2 + CO2 Formate CO2 Acetyl- CoA Ethanol gltA [4.1.3.7] Acetate Citrate Oxaloacetate aspC [2.6.1.1] NADH acnB [4.2.1.3] mdh [1.1.1.37] NADH NAD+ NAD+ Isocitrate Aspartate Malate aspA [4.3.1.1] fumB [4.2.1.2] fumA [4.2.1.2] icd [1.2.4.2] NADP+ NADPH Fumarate sdhCDAB [1.3.99.1] CO2 NADH frdABCD [1.3.1.6] 2-ketoglutarate NAD+ sucAB [1.2.4.2] Succinate sucCD [6.2.1.5] NAD+ NADH Succinyl-CoA CO2 Simplified schematic of E. coli central metabolic pathways

45. e- transport Cytoplasmic membrane ArcB P FNR FNR Redox, metabolites Aer Redox? Dos ArcA O2 O2 CheW,A,Y ArcA-P Transcription unknown Energy taxis Transcription Schematic showing selected oxygen and redox sensing pathways in E. coli (adopted from Sawers, 1999)

46. Some example of available pathway information FNR active in the absence of oxygen; ArcA is activated in the absence of oxygen  Ref 1: “Reg of gene expression in fermentative and respiratory systems in Escherichia coli and related bacteria”, E.C.E. Lin and S. Iuchi, . Annual Rev. Genet, 1991, 25:361-87Ref 2: Ref 2 “O2-Sensing and o2 dependent gene regulation in facultatively anaerobic bacteria”, G. Unden, S. Becker, J. Bongaerts, G.Holighaus, J. Schirawski, and S. Six, Arch Microbi. (1995) 164:81-90 Ref 3: “Regualtion of gene expression in E. coli” E.C.C. Lin and A.S. Lynch eds. (1996) Chapman & Hall, New York (p370) Ref 4: “Regualtion of gene expression in E. coli” E.C.C. Lin and A.S. Lynch eds. (1996) Chapman & Hall, New York (p322)

47. ldhA aspA fumB frdABCD pfl cyd cyo ArcB aceB mqo ArcA FNR fumC aceEF acnB sdhCDAB fumA mdh gltA icd sucAB sucCD We have 3 sensing/regulatory components whose activity evolves according to the Boolean mapping coded in the figure. Here red denotes repress and green denotes activate. When two components regulate a third we suppose their action to be an “and”. These regulatory components determine the state of 19 structural genes via the specified Boolean net.

48. Biosystems • Systems biology is the study of living organisms at the systems level rather than simply their individual components • High-throughput, quantitative technologies are essential to provide the necessary data to understand the interactions among the components • Computation tools are also required to handle and interpret the volumes of data necessary to understand complex biological systems

49. Analytic tools

50. Functional Genomics