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Greedy Algorithms in the Libraries of Biology

Greedy Algorithms in the Libraries of Biology. P G P. 17-Apr-2008 3:30-3:45 PM Avogadro-Scale Computing MIT Bartos E15. Thanks to:. Is biology optimal?. Present 26720 km/h 4500m pm-Mm 3 o K 2000 yr . Human Past Locomotion 50 km/h Ocean depth 75m

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Greedy Algorithms in the Libraries of Biology

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  1. Greedy Algorithms in the Libraries of Biology PGP 17-Apr-2008 3:30-3:45 PM Avogadro-Scale Computing MIT Bartos E15 Thanks to:

  2. Is biology optimal? Present 26720 km/h 4500m pm-Mm 3oK 2000 yr Human Past Locomotion 50 km/h Ocean depth 75m Visible l .4-.7 m Cold 0oC Memory 20 yr

  3. 3 Exponential technologies1 to 18 month doubling times Computation & Communication Gb chips human tRNA urea B12 Synthetic chemistry telegraph Analytic tRNA Shendure J, Mitra R, Varma C, Church GM, 2004. Carlson 2003; Kurzweil 2002; Moore 1965.

  4. Avogadro scale, >>Yottaflops (from CMOS to sea moss) Ultra-parallel 1038 units (lab libraries:108 to 1015 25mers) Adaptable Evolution (years), Immune (days), Neural (seconds) Thermodynamic limit 2x1019 op/J (irreversible) 3 x1020 for polymerase (1010 for current computers) Memory density: Neural: (1012 op/s & 106 bits)/mm3, DNA: (103 op/s & 1 bit)/nm3 Error rate: DNA:10-9 ; RNA/protein: 10-4 Biofuel: 4x107 J/kg (~=$) Adleman 1994

  5. DNA error rates 3. Mismatch repair DNA Replication Fork 2. Proofreading exonuclease 3’to 5’ Ellis et al. PNAS 2001 Constantino & Court. PNAS 2003 1. Incorporation 5’to 3’

  6. Bionano – Inorganic-microfab interfaces • Metal-oxide-semiconductors • (sponge silicateins for Ti  & Ga oxides)  • Magnetic components • (magnetosomes in magnetotactic bacteria) • Optical fibers & lenses • (e.g. venus basket sponge) • Bacterial reduction of salts to metals • (e.g. Se, Au, Ag) • Reading and writing DNA

  7. Reading DNA : Open-source hardware, software, wetware Polonator G007 ~10 to $400/Gbp 1E-6 @ >3X redundancy

  8. Synthetic Biology: augmentation & combinatorics (not minimization) • Synthetic DNA: 1Mbp per month (Codon Devices) • New polymers in vitro– affinity selection (Vanderbilt) • Hydrocarbon & other chemical syntheses in E.coli (LS9) • Bacterial & stem cell therapies (SynBERC & MGH) • New codes: Viral resistant cells & new aminoacids (MIT) • Synthetic Ecosystems – Evolve secretion & signaling • Interfaces of Genomics & Society Hierarchical, modular, evolvable

  9. DNA origami -- highly predictable 3D nanostructures Rothemund Nature’06 Douglas, et al. PNAS’07 DNA-nanotube-induced alignment of membrane proteins for NMR structure determination

  10. 10 Mbp of DNA / $300 chip Spatially patterned chemistry 8K Atactic/Xeotron/Invitrogen Photo-Generated Acid 12K Combimatrix Electrolytic 44K Agilent Ink-jet standard reagents 380K Nimblegen/GA Photolabile 5'protection Amplify pools of 50mers using flanking universal PCR primers & 3 paths to 10X error correction Tian et al. Nature. 432:1050 Carr & Jacobson 2004 NAR Smith & Modrich 1997 PNAS

  11. Mirror world :resistant to enzymes, parasites, predators Mirror aptamers, ribozymes, etc. require mirror polymerases 352 aminoacid long Dpo4 Sulfolobus DNA polymerase IV 347 peptide bonds done; 4 to go. D-aminoacids L-nucleotides (Mirror-biopolymers) L-aminoacids D-nucleotides (current biosphere)

  12. Why synthesize (minimal) in vitro self-replication? • Molecular Biology Central Dogma • DNA > RNA > Protein • PCR, T7 RNA pol, in vitro translation. • Production of devices larger than or toxic to cells. • Directed evolution of drugs & affinity agents. • Mirror-image proteins Tony Forster (Vanderbilt) Duhee Bang (HMS)

  13. Pure in vitro translating & replicating system 113 kbp DNA 151 genes ideal for comprehensive atomic, ODE & stochastic models Forster & Church MSB ‘05 GenomeRes.’06Shimizu, Ueda et al ‘01

  14. Genome engineering CAD Recombination in human cells Recombination in vivo E.coli Polymerase in vitro 70b 15Kb 5Mb 250 Mb Error Correction MutS 1E-4 Human(Artificial) Chromosomes HACs Bacterial (Artificial) Chromosomes BACs Chemical Synthesis 1E-2 Sequencing 1E-7 Isaacs, Carr, Emig, Gong, Tian, Reppas, Jacobson, Church

  15. About 3 serial additive changes per 30 days vs 2^30 exhaustive search Native DNA computing : Lab Evolution Reppas/Lin Trp/Tyr exchange Tolonen Ethanol resistance Lenski Citrate utilization Palsson Glycerol utilization Edwards Radiation resistance Ingram Lactate production Marliere Thermotolerance J&J Diarylquinoline resistance (TB) DuPont 1,3-propanediol production

  16. Improved Recombination Frequency: 10-4 0.25 (> 3 log increase!) rE.coli Strategy #3: ss-Oligonucleotide Repair DNA Replication Fork Ellis et al. PNAS 2001 Constantino & Court. PNAS 2003 Obtain 25% recombination efficiency in E. coli strains lacking mismatch repair genes (mutH, mutL, mutS, uvrD, dam)

  17. Multiplex Automated Genome Engineering (MAGE) Wash with water & DNA pool (50) Concentrate O-ring membrane Resuspend, bubble, select Concentrate, electroporate Wang, Isaacs, Terry

  18. GEMASS Prototype H. Wang, Church Lab, Harvard, 2008

  19. Recombination-Cycling for Combinatorial Accelerated Evolution Mutation Distribution: 11 oligos, 15 cycles Mutation Distribution: 54 oligos, 45 cycles * Continuous cycling • Scaling & Automation • Increase Efficiency of Recombination Wang, Isaacs, Carr, Jacobson, Church

  20. Avogadro scale, >>Yottaflops (from CMOS to sea moss) Ultra-parallel 1038 units (lab libraries:108 to 1015 25mers) Adaptable Evolution (years), Immune (days), Neural (seconds) Thermodynamic limit 2x1019 op/J (irreversible) 3 x1020 for polymerase (1010 for current computers) Memory density: Neural: (1012 op/s & 106 bits)/mm3, DNA: (103 op/s & 1 bit)/nm3 Error rate: DNA:10-9 ; RNA/protein: 10-4 Biofuel: 4x107 J/kg (~=$) Adleman 1994

  21. .

  22. Multiplex Automated Genome Engineering (MAGE) syringe pump computer communication / data acquisition system electrically actuated valves OD sensor electroporation cuvette w/ membrane filter Wang, Isaacs, Terry

  23. Fab vs. Bio-fab • + Plays well with digital computers - No habla C++ • - Doesn’t get DNA + DNA is it’s native digital media • Needs us to replicate + We need them • Needs expensive Fab (e.g. ICs) + Simple or complex inputs • Intelligent Design + Evolution

  24. Cross-feeding symbiotic systems:aphids & Buchnera • obligate mutualism • nutritional interactions: amino acids & vitamins • established 200-250 million years ago • close relative of E. coli with tiny genome (618~641kb) MILKFTWV MILKFTWV HR Aphids http://buchnera.gsc.riken.go.jp

  25. Pink= enzymes apparently missing in Bucherna Shigenobu et al. Genome sequence of the endocellular bacterial symbiont of aphids Buchnera sp.APS. Nature 407, 81-86 (2000).

  26. Synthetic genome pair evolution Second Passage First Passage trp/tyrA pair of genomes shows best co-growth Reppas, Lin et al. ; Accurate Multiplex Polony Sequencing of an Evolved Bacterial Genome 2005 Science

  27. -12 -11 -10 -9 -8 -7 -6 Co-evolution of mutual biosensors/biosynthesissequenced across time & within each time-point Independent lines of TrpD & TyrD co-culture 5 OmpF: (pore: large,hydrophilic > small) 42R-> G,L,C, 113 D->V, 117 E->A 2 Promoter: (cis-regulator) -12A->C, -35 C->A 5 Lrp: (trans-regulator) 1bD, 9bD, 8bD, IS2 insert, R->L in DBD. Heterogeneity within each time-point . At late times Tyr- becomes prototroph! Reppas, Shendure, Porecca

  28. Reducing costs of open-sourcehardware & wetware • Factor • 30 Equipmentspeed: from 1 up to 30 Mpixels/sec camera • 4 Equipment cost: from $500K down to $150K (Danaher Inc) • 36 Parallelism: 36 flow-cells per camera, 2 billion beads • ------------------ • 75 Flow cell volume: 1.5 mm down to 0.0085 mm thin • 40 Kit costs: $2000 down to $50 at standard enzyme costs • 10 Enzymes: $4000/mg down to <$400 (Enzymatics Inc) • 50 Genomic subset (Exome – 1% genome)

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