Thanks to: DOE-HGP 1987-2002 DARPA 2001-3 (* Currently unfunded* ) 28-Jan-2004 DOE Synthesis of useful replicating biosystems.

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Presentation transcript:

Thanks to: DOE-HGP DARPA (* Currently unfunded* ) 28-Jan-2004 DOE Synthesis of useful replicating biosystems

DOE Synthetic Genomes: Why? Cheaper/faster "standard biology", hypothesis testing Systems Biology: Multiple simultaneous tests Viruses: Aid strain transfer; generate variants, new haplotypes Anti-viral vaccines and therapeutics (including variants) In vitro: Make products toxic in E.coli. Microbes: Interspecific hybrids (e.g. codon usage) Structural biology: variants Rapid vaccine response to engineered bioterrorism. Cell-mediated immunity + humoral. Fix mismatch between genome analysis & synthesis

DOE Synthetic Genomes: Why? In vitro Microbial & Human Antimutators Artificial ecosystems (laboratory scales) Energy aiding pathway improvement Instrustrial production: Enzymes, SingleCellProtein, Protein- drugs Remediation: Hybrid genomes (opt. codons), combinatorial pathway (Maxygen & Diversa). Xylose & Oil Pharmaceuticals: Combinatorial syntheses Nano science Combinatorial syntheses, Complex nanosystems, more general nanoassembly (in reach of polymerases and ribosome-like factories) Health research: 10X faster results per current $ (cost/benefit) Hypothesize & test unknown gene combinations Synthetic standards (arrays, MS, quantitation, etc) Agriculture: salt, cold, drought, pest tolerant hybrid genomes

DOE Synthetic Genomes I. Charge & Intro. David & Ray A. Follow on to genome project B. DOE role in tech development in Biology & HGP C. Thumbnail of DOE missions: bioremediation, energy, carbon sequestration II. State of the Art of Technology George III. New DOE technology. George A. What is new? B. Near and far future. 1&10 yr. IV. Benefits & Concerns 1&10 yr. A. GMO-gene escape (old tech) Jim B. Bioterrorism C. Ownership D. Patents/IP

DOE Synthetic Genomes IV. Benefits & Concerns: Generic, DOE, other A. GMO-gene escape (old tech) Eliminate allergenic (interspecies) pollen B. 10X greater yield for constant research $ (hypothesis testing & systems biology) C. Pharma throughput D. Vaccines variants F. Bioterrorism (access/regulation, biohacker/vandals) DEA model for tracking chemicals tracking bioprinter cell design output (is this to hard?) G. Ownership, Patents/IP, Research sociology, agenda H. spin-offs: e.g. I/O memory nm3 vs. micron3 I. Religion life (refer to Cho et al. 1999)

Energy & CO 2 Fluxes 4x10 13 kW of sunlight hits earth. We consume 2kW per person* 6x10 9 = kW. CO 2 >370 ppm = 730 x10 15 g globally, increase ~3 x10 15 /yr. Ocean productivity = ~100 x10 15 g/yr. Autotrophs: Prochlorococcus cells globally (10 8 per liter) Undone by Cyanophages & Heterotrophs: 2x10 28 SAR11 cells in the oceans Pseudomonas & Caulobacter in a variety of soils & aquatic environments Morris et al. Nature 2002 Dec 19-26;420(6917):

Synthetic Genomes: How? (examples) How to decrease cost? Chips, error correction, polony clone/sequence How to make new biopolymers? Altered translation, mirror proteins How to improve energy production/conservation? Eliminate predation How to increase safety? Eliminate DNA/RNA exchange In vivo vs in vitro? ribosome-display selection, in vivo assembly

Transition L-amino acids & D-ribose (rNTPs, dNTPs) Transition EF-Tu, peptidyl transferase D-amino acids & L-ribose (rNTPs, dNTPs)

Impact of mirror cells? Microbes Eliminate DNA exchange Energy Prochlorococcus resistant to phage & predators Remediation Engineer community resistant to predation Pharmaceuticals Expand "natural products" Nano science Enzyme resistant "bio"-polymers Health Mirror humans resistant to all? viruses ? Viruses see above Agriculture Pest resistance

Synthetic Biology Test or manipulate optimality Program minimal cells (105kbp) Nanobiotechnology - new polymers Manage complex systems e.g. stem cells & ocean ecology

Synthetic Genomes Molecular Biology depends on in vitro reactions (e.g. PCR, SP6, Roche) Utility of mirror-image & other unnatural polymers. Combine with homologous recombination to engineer larger genomes Toward these goals design a minimal chassis: 100kbp genome. All 3D structures known. Comprehensive functional data.

Known: in vitro assembly & 3D structure of prokaryotic ribosomes (e.g. Nomura et al.; Noller et al.)

A 105 kbp mini-genome

The least well-characterized components of the mini-genome Forester & Church

M DNA Template RNA Transcript All 30S-Ribosomal-protein DNAs & mRNAs synthesized in vitro Tian & Church

His-tagged ribosomal proteins synthesized in vitro RS-2,4,5,6,9,10,12,13,15,16,17,and 21 as original constructs. RS1 required deletion of a feedback motif in the mRNA. RS-3, 7, 8, 11, 14, 18, 19, 20 are still weakly expressed. Note that S1, S4, S7, S8, S20, L1, L4, L10 are known to repress their own translation (and are likely titrated by rRNA). Iteratively resynthesize all mRNAs (e.g. with less structure). Tian & Church

Custom Oligonucleotide Chips *Photo-Generated Acid Electrolytic acid/base Photolabile 5'protecting group Ink-jet with standard monomers and acids * Tian, Sheng, Gao & Church

Improving synthesis fidelity Method Total bp # Clones Trans- ition Trans- versionDeletionAddition Bp/error Hyb selection, PCR Gel selection, PCR No selection, ligation +PCR No selection, PCR

Why mismatch repair works for in vivo replication (& not for de novo synthesis) Desired (or original) base pair: AT ; Mutant bp: gc Heteroduplexes: Ac & gT. Mismatch repair (selecting original): At & aT Mismatch repair (no "original"): At, aT, gc, gc Solution: Select on majority (once or more) (1) Kinetic: + (AT) -(gc, AC, gT) (2) Equilibrium: + (AT, gc) -(Ac, gT)

Improving automated cost oligosseqfix5E+31.00E+06 Cello $1,000$2000$1,200$240,000 Smith0 $1,000$800,0000$801,000$160,200,000 Smith1 $1,000$20$40$1,060$212,000 Smith2 $1,000$200$24$1,224$244,800 Church1 $2,500$20$16$2,536$507,200 Church2 $45$20$16$81$16,129 Church0 $45$50$50$9,929