SynBERChassis_FI_21Sep08.ppt - Church Lab

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12 Δεκ 2012 (πριν από 4 χρόνια και 4 μήνες)

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Chasses For All

Farren Isaacs

Harris Wang

George Church


September 21, 2008

SynBERC Retreat


Church Lab

Department of Genetics

Harvard 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

















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

-
剥R

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

Reco
ding

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

TAA

STOP


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. coli

MG1655

4.7 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 with

Peter Carr & Joe Jacobson (MIT)

Combining Small
-

& Large
-
Scale Genome Engineering (GE)

to Convert All UAGs


啁䅳

wt
E. coli

Small
-
scale GE

Large
-
scale GE

rE. coli

Small
-
Scale Genome Engineering:

Oligonucelotide (ssDNA)
-
mediated


剥搠剥捯浢楮慴楯m

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㔠5⠾″潧 楮捲敡獥!)




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 (
D
G)


Oligo pool complexity


Genetic Diversity:


mismatches, insertions, deletions


CAD
-
oligo Design

Oligo Optimization

RE vs. Oligo Length

RE vs. [Oligo]

rE.coli

Electrocycling Experimental Pipeline

Small
-
scale

TAG


TAA

codon changes

Distribution of TAA Mutations/Clone

Observed Mutations/Clone

S
pools

0
5
10
15
20
25
0
1
2
3
4
5
6
7
8
9
10
N
-
mutant
% of Population
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%

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
mutations

78%

~35% Total RE/cycle

20%
-

Total RE/cycle (m*n)


2%
-

Loci RE/cycle (m)

Individual

246/314 Mutations

D
m

Strain Characterization
&
Completion of TAG

呁䄠䍯摯C 卷慰a

wt strain

Cycled 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 䍯Cv敲獩潮

㌱㐯㌱㐺3㄰〠1 TAG


TAA 䍯Cv敲獩潮



Confirm Codon changes by direct Sanger


Sequencing of loci regions ~1% of genome

0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
Total
Genome
Region
Oligo Regions
Mutation Frequency (10
-4
)
Mutation Frequency

0
-
15

Cycles

Large
-
Scale Genome Engineering:

Genome Merging via Conjugation

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 MB

F+/Hfr

F
-

ssDNA

10
-
3



10
-
2

10
-
6

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: farren@genetics.med.harvard.edu


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

APPLICATIONS

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


剥搠剥捯浢楮慴楯m

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㔠5⠾″潧 楮捲敡獥!)

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
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 (
D
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. Coli

Genome

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/clone
Frequency
*

*

rE. coli

MG1655

4.7 Mb


DNA Microchip

“Oligo Source”

Mutated
-
Recoded Strain

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 MB

F+/Hfr

F
-

ssDNA