Chasses For All Farren Isaacs Harris Wang George Church September 21, 2008 SynBERC Retreat Church Lab Department of Genetics Harvard Medical School

Genetic Engineering n  Serial, inefficient introduction or mutation of DNA  Single-few genetic changes Cell Genome Genomic Engineering  Parallel, site-specific, efficient introduction or mutation of DNA  Explore combinatorial genomic sequence space … … … … … … ……

Goals of Whole Genome Engineering Biosynthesis of new proteins –Nonnatural Amino Acids –Tagged proteins, drugs Optimal codons Combinatorial genetic diversity across whole genomes Genome stability  Safer Bio-isolation Virus-resistant strains? Engineered Cells with New Properties & Functionality Technological Goal Develop enabling genome engineering technologies for small- (bp) & large-scale (KB-MB) changes to the genome Biological Goals Change the genetic code of E. coli Strain-Pathway Engineering Immutable & Stable Genomes Therapeutic-Optimized Safe Strains Cloning-Optimized Strains Tagged Protein Systems

Genome Engineering Technologies: Small to Large Scale High Efficiency -Red Homologous Recombination High Efficiency Conjugation and Transfer of Large DNA Fragments Versatile Engineering of Gene Elements NUCLEOTIDES (1-10s bps) GENOMES (kbs-Mbs) GENES (10s-1000s bps) Important Features Very Efficient: >25% vs of standard methods) Fast: 3 hr turnaround time (vs. 1-2 days traditionally) Versatile: prokaryotic and eukaryotic Applications Synthetic Biology Metabolic/pathway Engineering Metagenomic Engineering Rapid Directed Evolution Synthetic Ecosystems Protein/enzyme evolution Safe Organisms

Recoding E.coli: rE.coli TTT F 30362TCT S 11495TAT Y 21999TGT C 7048 TTC22516TCC11720TAC16601TGC8816 TTA L 18932TCA9783TAASTOP 2703TGASTOP1256 TTG18602TCG12166TAG314TGGW20683 CTT L 15002CCT P 9559CAT H 17613CGT R CTC15077CCC7485CAC13227CGC29898 CTA5314CCA11471CAA Q 20888CGA4859 CTG71553CCG31515CAG39188CGG7399 ATT I 41309ACT T 12198AAT N 24159AGT S ATC34178ACC31796AAC29385AGC21862 ATA 5967ACA9670AAA K 45687AGA R 2896 ATGM37915ACG19624AAG14029AGG1692 GTT V 24858GCT A 20762GAT D 43719GGT G GTC20753GCC34695GAC25918GGC40285 GTA14822GCA27418GAA E 53641GGA10893 GTG35918GCG45741GAG24254GGG15090 E. coli MG Mb Well understood Fully sequenced Genetic, Biochemical & Metabolic Research Host for commercial utility Robust Remove RF1 - one codon available for unnatural amino acids - new genetic code: 63 codons 1. TAG stop > TAA stop - three codons “free” - 61 codons 2. AGR (R) > CGR (R) tRNAs: AGY (S) > AGY (L) 3. AGY (S) > TCX (S) tRNAs: UUR (L) > UUR (S) 3. TTR/CTX (L) > AGY (S) In collaboration with Peter Carr & Joe Jacobson (MIT)

Combining Small- & Large-Scale Genome Engineering (GE) to Convert All UAGs  UAAs wt E. coliSmall-scale GELarge-scale GErE. coli

Small-Scale Genome Engineering: Oligonucelotide (ssDNA)-mediated Red Recombination Obtain 25% recombination efficiency in E. coli strains lacking mismatch repair genes (mutH, mutL, mutS, uvrD, dam) Costantino & Court. PNAS (2003) DNA Replication Fork Improved Recombination Efficiency (RE):  0.25 (> 3 log increase!) –Oligo length: 90mers –Increase oligo half-life: 2 phosphorothioate bonds at 5’ & 3’ oligo ends –Conc. of oligo: > 25uM –Conc. of cells: 0.5 to 1 billion cells –DNA target: lagging strand –Minimize secondary structure (  G) –Oligo pool complexity –Genetic Diversity: mismatches, insertions, deletions –CAD-oligo Design Oligo Optimization RE vs. Oligo LengthRE vs. [Oligo]

rE.coli Electrocycling Experimental Pipeline Small-scale TAG  TAA codon changes

Distribution of TAA Mutations/Clone Observed Mutations/Clone  pools M ~ 3, Avg muts/clone n = 10, # loci c = 18, # cycles M = n(1-(1-m) c ) Predicted Mutations/Clone Avg Top Clone = 6.5 mutations 65% StrainMutsStrainMutsStrainMutsStrainMuts / Avg Top Clone = 7.8 mutations 78% ~35% Total RE/cycle 20% - Total RE/cycle (m*n) 2% - Loci RE/cycle (m) Individual 246/314 Mutations mm

Strain Characterization & Completion of TAG  TAA Codon Swaps wt strainCycled Strains Growth Rate (30 o C)42’43’ +/- 1.2’ Auxotrophy Rate-2.6% Recombination Efficiency 23%21.6% +/-2.5% 246/314: 78 % TAG  TAA Conversion 314/314: 100 % TAG  TAA Conversion Confirm Codon changes by direct Sanger Sequencing of loci regions ~1% of genome Mutation Frequency 0-15 Cycles

Large-Scale Genome Engineering: Genome Merging via Conjugation

Large-Scale Genome Engineering: Genome Assembly via Conjugation Step# strains# transfersAvg Size KB KB KB MB MB F+/HfrF- ssDNA – Eff.

Genome Engineering Multiplex Automation (GEMA): Integration, automation, & standardization of tools

GEMA Prototypes

Recoding Genomes Strain-Pathway Engineering and Optimization Immutable & Stable Genomes Therapeutic-Optimized Safe Strains Cloning-Optimized Strains Tagged Protein Systems … & more Harnessing Genetic Diversity for Evolution & Engineering Applications

Acknowledgments NSF – SynBERC, DOE George Church (Harvard) Harris Wang (Harvard)Peter Carr (MIT) Andy Tolonen (Harvard)Bram Sterling (MIT) Nick Reppas (Harvard)Joe Jacobson (MIT) Resmi Charalel (Harvard) Zachary Sun (Harvard) Laurens Kraal (Harvard) George Xu (Harvard) Duhee Bang (Harvard) Craig Forest (GA. Tech) ________________________________________ Farren Isaacs:

Conjugation: Large-Scale Gene Transfer Mechanism for horizontal gene transfer –Lederberg & Tatum, CSHSQB (1946) –e.g., antibiotic resistance, metabolic functions DNA transfer is driven by F plasmid from an F+ Donor (D) Cell to an F- Recipient (R) Cell Transfer of ssDNA from D  R is converted to duplex DNA by synthesis of complementary strand in the recipient cell ds donor DNA: –F’ transfer: circularized –Hfr transfer: incorporated into recipient chromosome via RecA- dependant HR or degraded by RecBCD Probability of transferring a specific marker decreases exponentially with its distance from the origin of transfer (oriT) –Smith, Cell (1991) “Direct Visualizatin of Horizontal Gene Transfer” shows much higher recombination frequencies (96.7%) than those measured with genetic markers (10-30%). Conjugational recombination is extremely efficient when donors and recipients are essentially gentically identical strains. –Babic et al., Nature (2008) F+/HfrF- F pilus ssDNA F+, Genomic oriT in Donor

APPLICATIONS

Combining Small & Large-Scale Genome Engineering Microscale (bp) Engineering: Oligo Recomb Divide genome into 2 n regions-strains: Macroscale (KB-MB) Engineering: Conjugation Pairwise assembly of 2 n mutated strains Genome n

Small to Large-Scale Genome Engineering Oligo Pool containing UAG codon mutations Pool of assembly oligos I. De novo genome assembly II. Oligo-mediated Recombination: Small-scale III. Engineered Conjugation: Large-scale DNA microchip

Small-Scale Genome Engineering: Oligonucelotide (ssDNA)-mediated Red Recombination Obtain 25% recombination efficiency in E. coli strains lacking mismatch repair genes (mutH, mutL, mutS, uvrD, dam) Costantino & Court. PNAS (2003) DNA Replication Fork Improved Recombination Efficiency:  0.25 (> 3 log increase!) Exo: 5’  3’ dsDNA exonuclease Beta: ssDNA binding protein binds to ssDNA > 35bps Gam: inhibits RecBCD attL int xis hin exo bet gam kil T N pL cI857 Exo Beta Gam

Oligo-mediated Recombination Experiments  90mer oligos are optimal  Two oligos exhibit synergistic effect  High recombination frequencies are maintained from 0.25 to > 25  M of oligo Recombination Efficiency vs. Oligo LengthRecombination Efficiency vs. [Oligo]  Scaling: Multiplex Oligo-mediated Recombination –Oligo length: 90mers –Increase oligo half-life: 2 phosphorothioate bonds at 5’ & 3’ oligo ends –Conc. of oligo: up to 25uM –Conc. of cells: 0.5 to 1 billion cells –DNA target: lagging strand –Minimize secondary structure (  G) –Oligo pool complexity Optimized variables

Oligo Pool containing TAG codon mutations Cyclical Recombination of Oligonucleotide Pool Oligo Pool # cycles Best Clone (98 %tile) Fraction of mutated sites Time* /11~2 days /54~5 days * * * * * * * E. Coli Genome Fraction of Cells Containing Oligo-Mediated MutationPilot Electrocycling Recombination Experiments * Continuous cycling, ~3 hrs/cycle * * rE. coli MG Mb DNA Microchip “Oligo Source” Mutated-Recoded Strain

Large-Scale Genome Engineering: Genome Assembly via Conjugation Step# strains# transfersAvg Size KB KB KB MB MB F+/HfrF- ssDNA