Chasses For All Farren Isaacs Harris Wang George Church September 21, 2008 SynBERC Retreat Church...
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Transcript of Chasses For All Farren Isaacs Harris Wang George Church September 21, 2008 SynBERC Retreat Church...
Chasses For All
Farren IsaacsHarris Wang
George Church
September 21, 2008SynBERC Retreat
Church LabDepartment of GeneticsHarvard Medical School
Genetic Engineering
1
2
3
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
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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 GoalDevelop enabling genome engineeringtechnologies 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. 10-4-10-7 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
30362 TCT
S
11495 TAT
Y
21999 TGT
C
7048
TTC 22516 TCC 11720 TAC 16601 TGC 8816
TTA
L
18932 TCA 9783 TAASTOP
STOP
2703 TGA STOP 1256
TTG 18602 TCG 12166 TAG 314 TGG W 20683
CTT
L
15002 CCT
P
9559 CAT
H
17613 CGT
R
28382
CTC 15077 CCC 7485 CAC 13227 CGC 29898
CTA 5314 CCA 11471 CAA
Q
20888 CGA 4859
CTG 71553 CCG 31515 CAG 39188 CGG 7399
ATT
I
41309 ACT
T
12198 AAT
N
24159 AGT
S
11970
ATC 34178 ACC 31796 AAC 29385 AGC 21862
ATA 5967 ACA 9670 AAA
K
45687 AGA
R
2896
ATG M 37915 ACG 19624 AAG 14029 AGG 1692
GTT
V
24858 GCT
A
20762 GAT
D
43719 GGT
G
33622
GTC 20753 GCC 34695 GAC 25918 GGC 40285
GTA 14822 GCA 27418 GAA
E
53641 GGA 10893
GTG 35918 GCG 45741 GAG 24254 GGG 15090
E. coliMG16554.7 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 withPeter Carr & Joe Jacobson (MIT)
Combining Small- & Large-Scale Genome Engineering (GE)to Convert All UAGs UAAs
wt E. coli Small-scale GE Large-scale GE rE. 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):10-6-10-4 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 Length RE vs. [Oligo]
Distribution of TAA Mutations/Clone
Observed Mutations/Clone
pools
05
10152025
0 1 2 3 4 5 6 7 8 9 10
N-mutant
% o
f P
op
ula
tio
n
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 mutations65%
Strain Muts Strain Muts Strain Muts Strain Muts
1 8 9 6 17 8 25 8
2 10 10 8 18 9 26 9
3 8 11 7 19 8 27 9
4 7 12 9 20 8 28 9
5 8 13 5 21 7 29 6
6 7 14 7 22 7 30 8
7 9 15 6 23 8 31 9
8 7 16 4/4 24 8 32 9
Avg Top Clone = 7.8 mutations78%
~35% Total RE/cycle
20% - Total RE/cycle (m*n) 2% - Loci RE/cycle (m)
Individual
246/314 Mutations
m
Strain Characterization & Completion of TAGTAA Codon Swaps
wt strain Cycled Strains
Growth Rate (30oC) 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
00.5
11.5
22.5
33.5
44.5
5
Total GenomeRegion
Oligo Regions
Mu
tati
on
Fre
qu
en
cy
(1
0-4)
Mutation Frequency
0-15Cycles
Large-Scale Genome Engineering:Genome Assembly via Conjugation
Step # strains # transfers Avg Size
1 32 16 143 KB
2 16 8 287 KB
3 8 4 575 KB
4 4 2 1.15 MB
5 2 1 2.3 MBF+/Hfr F-
ssDNA
10-3 – 10-2
10-6
Eff.
• 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: [email protected]
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+/Hfr F-
F pilus
ssDNA
F+, Genomic oriT in Donor
Combining Small & Large-Scale Genome Engineering
Microscale (bp) Engineering: Oligo RecombDivide genome into 2n regions-strains:
Macroscale (KB-MB) Engineering: ConjugationPairwise assembly of 2n mutated strains
Genome
n
Small to Large-Scale Genome Engineering
Oligo Pool containing UAG codon mutations
Pool of assembly oligos
I. De novo genomeassembly
II. Oligo-mediatedRecombination:
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:10-6-10-4 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 Length Recombination 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 15 7 7/11 ~2 days
54 45 23 23/54 ~5 days
***
***
*
E. ColiGenome
Fraction of Cells Containing Oligo-Mediated Mutation Pilot Electrocycling Recombination Experiments
* Continuous cycling, ~3 hrs/cycle
0
5
10
15
20
25
0 1 2 3 4 5 6 7
# mutations/cloneF
req
ue
nc
y
*
*
rE. coliMG16554.7 Mb
DNA Microchip“Oligo Source”
Mutated-Recoded Strain