CAD for Synthetic Microbial Biofuels

1. CAD for Synthetic Microbial Biofuels Morten Sommer, MIT/Harvard DOE GtL Center Novozyme 30-Jun-2006

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

3. 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

4. (= 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

5. 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

6. Programmable ligand-controlled riboregulators to monitor metabolites. OFF ON ON Bayer & Smolke 2005Nature Biotech.

7. 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

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

9. 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

10. 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

11. Cross-feeding symbiotic systems:aphids & Buchnera • obligate mutualism • nutritional interactions: amino acids and vitamine • 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

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

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

14. 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

15. 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

16. 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:

17. Invasion of advantageous mutants

18. 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’).

19. ‘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

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

21. 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

22. 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.

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

24. 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

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

26. 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.

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

28. 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.

29. 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

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

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

32. CAD for Synthetic Microbial Biofuels Morten Sommer, MIT/Harvard DOE GtL Center Novozyme 30-Jun-2006

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