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Synthetic Biology & Microbial Biofuels

Synthetic Biology & Microbial Biofuels. George Church, MIT/Harvard DOE GtL Center DuPont 13-Sep-2006. Our DOE Biofuels Center goals & strengths. 1. Basic enabling technologies: omics, models, genome synthesis, evolution, sequencing 2. Harnessing new insights from ecosystems.

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Synthetic Biology & Microbial Biofuels

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  1. Synthetic Biology & Microbial Biofuels George Church, MIT/Harvard DOE GtL Center DuPont 13-Sep-2006

  2. Our DOE Biofuels Center goals & strengths 1. Basic enabling technologies: omics, models, genome synthesis, evolution, sequencing 2. Harnessing new insights from ecosystems. 3. Improving photosynthetic and conversion efficiencies. 4. Fermentative production of alcohols & biodiesel.

  3. Synthetic Biology Engineering Research Center (SynBERC) $16M NSF, IGEM UC-Berkeley, Harvard, MIT, UCSF Keasling, Lim, Endy, Church, Prather, Voigt, Knight Parts, Devices, Chassis, Thrust in biochemical engineering Stress & parasite resistance

  4. Engineering a mevalonate pathway in Escherichia coli for production of terpenoids.Martin VJ, et al. Nat. Biotech 2003 Production of the antimalarial drug precursor artemisinic acid in engineered yeast. Ro DK, et al. Nature. 2006 8

  5. Programmable ligand-controlled riboregulators to monitor metabolites. OFF ON ON Bayer & Smolke; Isaacs & Collins 2005 Nature Biotech.

  6. Genome & Metabolome Computer Aided Design (CAD) • 4.7 Mbp new genetic codes new amino acids • 7*7 * 4.7 Mbp mini-ecosystems • biosensors, bioenergy, high secretors, • DNA & metabolic isolation • Top Design Utility, safety & scalability • CAD-PAM • Synthesis(chip & error correction) • Combinatorics • Evolution • Sequence

  7. (= 2 E.coli genomes or 20 Mycoplasmas /chip) How? 10 Mbp of oligos / $1000 chip Digital Micromirror Array ~1000X lower oligo costs 8K Atactic/Xeotron/Invitrogen Photo-Generated Acid Sheng , Zhou, Gulari, Gao (Houston) 12K Combimatrix Electrolytic 44K Agilent Ink-jet standard reagents 380K Nimblegen Photolabile 5'protection Amplify pools of 50mers using flanking universal PCR primers and three paths to 10X error correction Tian et al. Nature. 432:1050; Carr & Jacobson 2004 NAR; Smith & Modrich 1997 PNAS

  8. rE.coli: new in vivo genetic codes Freeing 4 tRNAs, 7 codons: UAG, UUR, AGY, AGR e.g. PEG-pAcPhe-hGH (Ambrx, Schultz) high serum stability 4 1 Isaacs Church Forster Carr Jacobson Jahnz Schultz 3 2

  9. Our DOE Biofuels Center goals & strengths 1. Basic enabling technologies: omics, models, genome synthesis, evolution, sequencing 2. Harnessing new insights from ecosystems. 3. Improving photosynthetic and conversion efficiencies. 4. Fermentative production of alcohols & biodiesel.

  10. Prochlorococcus40ºN - 40ºS Chisholm et al. Ocean chl a (Aug 1997 –Sept 2000) Provided by the SeaWiFS Project, NASA

  11. Light regulated Prochlorococcus metabolism glgA glgB glgC Central Carbon Metabol. a-Glc-1P ADP-Glc glycogen a-1,4-glucosyl-glucan glgX glgP Zinser et al. unpubl.

  12. HLIP D1 Photosynthetic Genes in Phage Podovirus P-SSP746 kb Myovirus P-SSM2255 kb PC PC HLIPs HLIPs Fd Fd D1 D1 12kb 24kb 12kb 24kb Myovirus P-SSM4 181 kb HLIPs HLIPs D1 D1 D2 D2 ~500 ~500 bp bp 6.4kb 6.4kb 2.8kb 2.8kb Lindell, Sullivan, Chisholm et al. 2004

  13. RNA Responses to Phage MED4 host psbA MED4-0682 (60 aa Conserved URF) Phage SSP7 psbA Lindell,Sullivan, Zinser, Chisholm

  14. Our DOE Biofuels Center goals & strengths 1. Basic enabling technologies: omics, models, genome synthesis, evolution, sequencing 2. Harnessing new insights from ecosystems. 3. Improving photosynthetic and conversion efficiencies. 4. Fermentative production of alcohols & biodiesel.

  15. Brazil’s Bioethanol Land use:45,000 km² Sugarcane:344 million tons Sugar: 23 million tons Ethanol:14 million m³ $0.26/L (feedstock 70%) yield increase 3.5%/yr Dry bagasse: 50 million tons Electricity: 1350 MW Bagasse ash 2.5% (vs 40% for coal), nearly no sulfur. Burns at low temperatures, so low nitrogen oxides. Saccharum officinarum

  16. Our DOE Biofuel Center Goals Miscanthus v Panicum (switchgrass)22 v 10 tons/ha Goals: 2kg Hybrid seeds v 2 tons rhizomes self-destruction to aid crop rotation, pretreatment $0.10/L goal (NEB >4, corn-EtOH:1.3 soy-diesel:1.93) Pretreatment $0.03/L Ammonia fiber explosion (AFEX), dilute acid Integrated cellulases & fermentation to ethanol, butanol, biodiesel, alkanes $0.02/L

  17. High Ethanol (low Lactate, Acetate)

  18. Butanol pathways

  19. Lab Evolution collaborations Sacharomyces Growth on cellulose (Lee Lynd) Ethanol resistance (Greg Stephanopoulos) Escherichia Radiation resistance (Edwards & Battista) Tyr/Trp production & transport (Lin & Reppas) Cutrate utilization (Rich Lenski) Lactate production (Lonnie Ingram) Thermotolerance (Phillipe Marliere) Glycerol utilization (Bernahard Palsson)

  20. Intelligent Design & Metabolic Evolution Fong SS, Burgard AP, Herring CD, Knight EM, Blattner FR, Maranas CD, Palsson BO. In silico design and adaptive evolution of Escherichia coli for production of lactic acid. Biotechnol Bioeng. 2005 91(5):643-8. Rozen DE, Schneider D, Lenski RE Long-term experimental evolution in Escherichia coli. XIII. Phylogenetic history of a balanced polymorphism. J Mol Evol. 2005 61(2):171-80 Andries K, et al. (J&J) A diarylquinoline drug active on the ATP synthase of Mycobacterium tuberculosis. Science. 2005 307:223-7. Shendure et al. Accurate Multiplex Polony Sequencing of an Evolved Bacterial Genome Science 2005 309:1728 (Select for secretion & ‘altruism’).

  21. Competition & cooperation • Cooperation between two auxotrophs • Overall fitness depends on secretion • Over-production, increase of export • Competition among each sub-population • The fastest growing one wins • Increase of uptake • Coupling between evolution of import and export properties? • Amplified genes • Transporter & pore genes

  22. Cross-feeding symbiotic systems:aphids & Buchnera • obligate mutualism • nutritional interactions: amino acids and vitamins • established 200-250 million years ago • close relative of E. coli with tiny genome (618~641kb) Internal view of the aphid. (by T. Sasaki) Bacteriocyte (Photo by T. Fukatsu) Buchnera (Photo by M. Morioka) Aphids http://buchnera.gsc.riken.go.jp

  23. Shigenobu et al. Genome sequence of the endocellular bacterial symbiont of aphids Buchnera sp.APS. Nature 407, 81-86 (2000).

  24. Shigenobu et al. Genome sequence of the endocellular bacterial symbiont of aphids Buchnera sp.APS. Nature 407, 81-86 (2000).

  25. ODE based simulation of population dynamics of cross-feeding ∆Trp-∆Tyr Questions: • When mixed in minimum medium, how do the cell population and the amino acid concentrations change over time? • What happens when the strains evolve? • improve on amino acid imports • improve on amino acid synthesis and/or exports

  26. Initial conditions: growth rate constant of ∆Trp ([(mmol/ml Trp)-hr]-1) growth rate constant of ∆Tyr ([(mmol/ml Tyr)-hr]-1) Tyr excretion rate constant of ∆Trp (mmol/gBM-hr) Trp excretion rate constant of ∆Tyr (mmol/gBM-hr) =0.05 Trp requirement of ∆Trp (mmol/gBM) =0.13 Tyr requirement of ∆Tyr (mmol/gBM) density of ∆Trp (gBM/ml) density of ∆Tyr (gBM/ml) conc. of Trp (mmol/ml) conc. of Tyr (mmol/ml) Governing ODE system

  27. density of ∆Trp (gBM/ml) density of ∆Tyr (gBM/ml) conc. of Trp (mmol/ml) conc. of Tyr (mmol/ml) growth rate constant of ∆Trp ([(mmol/ml Trp)-hr]-1) growth rate constant of ∆Tyr ([(mmol/ml Tyr)-hr]-1) Tyr excretion rate constant of ∆Trp (mmol/gBM-hr) Trp excretion rate constant of ∆Tyr (mmol/gBM-hr) =0.05 Trp requirement of ∆Trp (mmol/gBM) =0.13 Tyr requirement of ∆Tyr (mmol/gBM) “Steady-state” solution: Variables: Parameters:

  28. Invasion of advantageous mutants

  29. ‘Next Generation’ Technology Development Multi-molecule Our role Affymetrix Software 454 LifeSci Paired ends, emulsion Solexa/Lynx Multiplexing & polony AB/APG Seq by Ligation (SbL) Complete Genomics SbL Gorfinkel Polony to Capillary Single molecules Helicos Biosci SAB, cleavable fluors Pacific Biosci Advisor KPCB Agilent Nanopores Visigen Biotech AB

  30. Polony Sequencing EquipmentHMS/AB/APG microscope with xyz controls HPLC autosampler (96 wells) flow-cell syringe pump temperature control

  31. Synthetic combinatorics & evolution of 7*7* 4.7 Mbp genomes Second Passage First Passage trp/tyrA pair of genomes shows the best co-growth Reppas, Lin & Church ; Shendure et al. Accurate Multiplex Polony Sequencing of an Evolved Bacterial Genome(2005) Science 309:1728

  32. Why low error rates? Goal of genotyping & resequencing  Discovery of variants E.g. cancer somatic mutations ~1E-6 (or lab evolved cells) Consensus error rateTotal errors(E.coli)(Human) 1E-4 Bermuda/Hapmap 500 600,000 4E-5 454 @40X 200 240,000 3E-7 Polony-SbL @6X 0 1800 1E-8 Goal for 2006 0 60 Also, effectively reduce (sub)genome target size by enrichment for exons or common SNPs to reduce cost & # false positives.

  33. Mutation Discovery in Engineered/Evolved E.coli Shendure, Porreca, et al. (2005) Science 309:1728

  34. ompF - non-specific transport channel AAAGAT CAAGAT -12 -11 -10 -9 -8 -7 -6 Can increase import & export capability simultaneously • Glu-117 → Ala (in the pore) • Charged residue known to affect pore size and selectivity • Promoter mutation at position (-12) • Makes -10 box more consensus-like

  35. Sequence monitoring of evolution(optimize small molecule synthesis/transport) Sequence trp- Reppas, Lin & Church

  36. Co-evolution of mutual biosensors sequenced across time & within each time-point 3 independent lines of Trp/Tyr co-culture frozen. OmpF: 42R-> G, L, C, 113 D->V, 117 E->A Promoter: -12A->C, -35 C->A Lrp: 1bp deletion, 9bp deletion, 8bp deletion, IS2 insertion, R->L in DBD. Heterogeneity within each time-point reflecting colony heterogeneity.

  37. Our DOE Biofuels Center goals & strengths 1. Basic enabling technologies: omics, models, genome synthesis, evolution, sequencing 2. Harnessing new insights from ecosystems. 3. Improving photosynthetic and conversion efficiencies. 4. Fermentative production of alcohols & biodiesel.

  38. Synthetic Biology & Microbial Biofuels George Church, MIT/Harvard DOE GtL Center DuPont 13-Sep-2006

  39. .

  40. MI, OK, IL, IN, MN, KY, PA, MA, CA, NH. Because our GTL-Systems Biology Center renewal is a bit before the GTL-Bioenergy Research Centers, we're on target for an integrated SB-BRC including strengths in : A. Technology development, ecological & economical modeling: Franco Cerrina (U. Wisc EE), George Church (MIT/HMS), Ed DeLong (MIT BE), Chris Marx (Harvard OEB), Penny Chisholm (MIT Civil Eng). These basic enabling technologies feed into all of the other aims. We are improving our pipeline from 1. metagenomics (single cell sequencing) to 2. datamining to 3. combinatorial (semi)synthetic library formation, to 4. lab-evolution, then 5. sequencing. B. Innovative macromolecular production and structural studies. William Shih (DFCI), James Chou(Harvard), Phil Laible (ANL). William & James have made a breakthrough using DNA-nanotubes which greatly improves the NMR structures including membrane proteins. . We also have world leaders in high-resolution cryo-EM. Phil has developed an impressive what to produce large quantities of pure membrane proteins. My group is scaling-up DNA preps to the multi-gram levels. Membrane and ligno-cellulosic compartments are previous blind-spots for structural genomics which we are addressing. C. Synthetic & systems biology: Daniel Segre (BU BME) Nina Lin (MSU), Pam Silver (HMS SysBiol), Drew Endy (MIT), Jim Collins (BU BME), Anthony Forster (VUMC), Joseph Jacobson (MIT ML). We are proposing a BioFoundry in collaboration with Codon Devices) to bring the cost down of open-wetware and genome-engineering. This includes novel ways to improve accuracy of synthesis and in vivo homologous recombination especially organisms with previously 'challenging' genetics. Phage-, bacterial-, and in vitro- display systems for evolution of enzymes & subsystems. Ref:Building a Fab for Biology D. Phototrophs: Fred Ausubel (Harvard), Wayne Curtis (Penn State U ChE), Clint Chapple (Purdue) Arabidopsis lignins, Richard Dixon (Noble Plant Science Center, OK) Medicago lignins & digestability, Stephen Long, (U Ill Champaign) Mischanthus. It is clear that food crops can support only a tiny fraction of our energy needs, while plants growing in marginal lands (Miscanthus at 60 tons/ha), Panicum, and Populus tricocarpa offer the best starting points. We are engineering these to maximize yield, tolerate stress, and self-destruct when harvested. We also are engineering algae for higher yield/lower cost than grasses, and specialized applications including power plant gases with Greenfuel Tech Corp). E. Microbial metabolic engineering & fermentation, including ligno-cellulose to alcohols & alkanes: Greg Stephanopoulos (MIT ChE) E.coli & Saccharomyces, Lee Lynd (Dartmouth Eng) Clostridia, Lonnie Ingram (U FL) E.coli, Kristala Jones Prather (MIT ChE) E.coli, Thomas Jeffries (USDA, WI) Pichia. We are collecting/evolving enzyme systems to extend the range of input substrates and output fuels and specialty chemicals. .

  41. Smart therapeutics example: Environmentally controlled invasion of cancer cells by engineered bacteria. Anderson et al. J Mol Biol. 2006 Metabolic constraints Regulated Capsule TonB, DapD & new genetic codes for safety Optical imaging: bacteria, viruses, and mammalian cells encoding light- emitting proteins reveal the locations of primary tumors & metastases in animals. Yu, et al.Anal. Bioanal. Chem. 2003. accumulate in tumors at ratios in excess of 1000:1 compared with normal tissues. http://www.vionpharm.com/tapet_virulence.html

  42. LPS- Capsule+ Dap- for safety DapD 7

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