Synthetic biology and biodefense

Andrew D. EllingtonCenter for Systems and Synthetic Biology

University of Texas at AustinAustin, TX

What is synthetic biology?

• Standardization of bioengineering?‡ Modular, composable, scalable,programmable parts, circuits, and systems

• Extended DNA synthesis capabilities?‡ Making more, longer, and more quickly

• Modification of the chemistry of living systems?‡ Chemical biology, except moreso

• Hype?

Synthetic Biology

Ref: Bromley EHC, Channon K, Moutevelis E et al. Peptide and protein building blocks for synthetic biology: from programming biomolecules to self-organized biomolecular systems. ACS Chem. Bio. 3(1): 38-50

Synthetic biology space

Module functionality in tectons

• For ‘parts’ to work, standardization must allow predictionindependent of the ‘chassis’ in which the parts are found; this is the myth of Biobricks

• Unfortunately the complexity of organisms dwarfs ourability to accurately model function‡ Parts are not orthogonal to their chassis, thereis extensive feedback‡ This was obvious well in advance of the inventionof the term ‘synthetic biology;’ it’s difficult to evenpredict optimum strain background and growth conditions for protein overproduction, much lesscircuit function

• For a true engineering discipline to emerge, there must be the ability to accurately model biological systems at a level commensurate with parts functionality (or buffering)

15 parameters(rate constants and concentrations)

Randomizing all 15 parameters‡ successful rate = 1.6%

Fix 1, randomize the other 14‡ examples:

(Template activation) (Annihilation) (RNaseH conc.)

Kim and Winfree, Mol Syst Biol (2011)

Circuits are possible, butidiosyncratic (even if iconic)

All hail Chris Voigt and AnselmLevskaya

JW3367c = 3-fold light repression JT2 = 10-fold light repression

model

experiment

Post-facto parameterization can help explain behavior, butmodel-based prediction is still a long way off …

All data from Jeff Tabor / Chris Voigt

… should we be encouraged that it works at all, or dauntedby the parameter spaces that must be conquered?

• As if that weren’t bad enough, organisms are evolutionarymachines

*noisiest variant

Jeff Tabor,Rice U.

Tabor et al. (2008), MolBiosys

What is synthetic biology?

• Standardization of bioengineering?‡ Modular, composable, scalable,programmable parts, circuits, and systems

• Extended DNA synthesis capabilities?‡ Making more, longer, and more quickly

• Modification of the chemistry of living systems?‡ Chemical biology, except moreso

• Hype?

http://www.kk.org/thetechnium/carlson_cost_per_base_nov_0.jpghttp://www.kurzweilai.net/articles/images/Carlson(PaceAndProliferation)figure1.gif

There is now a “Moore’s Law” equivalent in sequence acquisition

http://www.kk.org/thetechnium/carlson_cost_per_base_nov_0.jpghttp://www.kurzweilai.net/articles/images/Carlson(PaceAndProl

Gene FabricationTCATAGCTATGGAACTGGTCGAACCGGCTGAATTTAGACGTGTAGCGTCTCAT AGCTAAAGACGTGTAGCGTCTCAT AGCT ATGGAACTGGTCGAACCGGCTGAGGACACABreak down target

sequences intooverlaps; PCR assembly in two steps

Oligonucleotide databasing enables efficient manufacture of variants

100x 1 kb / week

Design of synthetic schemes, oligonucleotide synthesis and databasing, and generation of robotic operations scripts are all automated in custom software.

Gene fabrication facility (recently declassified)

Recode to use only:1) The most readily available aminoacylated tRNAs in its host (E. coli)2) The least readily available aminoacylated tRNAs in its host (E. coli)

Effect of codon usage on viral fitness

Bacteriophage Phi X 174

Single stranded, circular DNA genome Size: 5386 basesGenes: 11 Coding Sequences (CDSs)

First DNA genome to be sequenced.

1018 bp1636 bp2036 bp3054 bp4072 bp5090 bp

Φ-X

174

(hig

h-us

e co

dons

)

6108 bp

Φ-X

174

(low

-use

cod

ons)

There are many human viruses on the same scale(such as human parvoviruses: B19; Fifth’s disease)

Canine parvovirus was derived from feline panleukopenia virusvia a small number of point mutations in the viral capsid genes that expanded the host range to canine cells. Following its emergence in thelate 1970s, canine parvoviruscaused a pandemic that killed alarge fraction of world’s dogs

There’s more than enough threat to go around

It is so easy to do harm with the biologicals currently available, that anticipating / regulating synthetic biology is akin to worrying about nuclear issues arising fromthe predicted ‘island of stability’ in the periodic table.

exposed

buried

Replace surface charged/polar residues (DERKQN) to positively (RK) or negatively (DE) charged residues.

Synthetic biology and rapid prototyping: supercharging

➯ Mutations introduced inframework regions so as not to interfere with antigen binding

➯ Charge repulsion prevents aggregation at high T

Lawrence et. al., JACS 2007, 129(33), pp. 10110-10112

>interesting_proteinEVKLVESGGGLVDPGGSLKLECDASGFTFSSYAMSWVRQTPEKRLEWVATISTGGGYTYFPDSVKGRFTISRDNAKNALYLQMKSLRSEDTADYYCARQGDFGDWYFDVWGAGTTVTVSDVLMTQTPLSLPVELGDQASIECRSSQSLVHSNGNTYLHWYLQKPGQSPKLLIYKVSNRFSGVPDRFSGSGSGTDFTLKIDRVEAEDLGVYFCSQSTHVPWTFGGGTKLEIKRA

To take full advantage of rapid prototyping, combine it with computational design

LFr : 2cgr (100%id)

10-res H1: 1kfa (100%id)17-res H2: 1ifh (88%id)

16-res L1: 2h1p (100%id)7-res L2: 4fab (100%id)9-res L3: 4fab (100%id)

11-residue H3from 2dbl (70%id)medium difficulty

HFr: 2a77(93%id)

Build Framework

Graft canonical loops

Model H3 loop

Rosetta Antibody, Jeff Gray, JHU

Builds an antibody Fv model using as much existing structural data as possible, followed by H3 loop modeling and H:L orientation optimization David Baker, UW

Structure-Aware Supercharging with Rosetta Design

total energy = Σ( )van der waals + solvation + hydrogen bonding + torsions + steric repulsion + “reference”

Backbone10 homology models, Gray lab

SidechainsAllow Arg/Lys/nativeIf CDR, allow native only

Search through sequence and rotamer space in the

framework region for mutations to appropriately-charged residues which are

compatible with the structure.

Brian Kuhlmanand Bryan Der,UNC Chapel Hill

Name Charge Mutations

(#)

−2X -41.5 33

−X -34.5 24

−L -28.5 19

− -27.5 20

Kn4 -19.5 24

Kn3 -13.5 18

Kn2 -8.5 14

Kn1 -0.5 7

WT +7.5 0

PD +11.5 4

Kp1 +15.4 8

Kp2 +18.4 11

Kp3 +22.4 14

Kp4 +29.5 21

+L +31.4 14

Kp5 +33.4 25

+ +34.4 16

+X +38.4 20

+2X +44.4 27

Anti-MS2 scFv Expression and Characterization

Alex Miklos

Randy Hughes

Again, we can’t even predict overexpression circuits

WT 2 scFv

500 mM NaCl1.5 M NaCl

KP1 scFv

500 mM NaCl1.5 M NaCl

Cleared LysateColumn Flowthrough10 mM Imid. Wash100 mM Imid. WashWash Clear (1 ml)Elution (7 ml)Elution Clear (1 ml)

Buffer Optimization for scFv Purification

L KP3 KSD5 KSD4 KSD3

In addition to supercharging mutations,Rosetta Design was used to predict stabilizing mutations (no sequence restrictions or residue reference energy manipulation). This approach has yielded not only improvements in thermodynamic stability but also 2-5 fold increases in expression.

Wt Kp1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

147 nM 14.7 nM 1.47 nM 0.147 nM0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

147 nM 14.7 nM 1.47 nM 0.147 nM

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

147 nM 14.7 nM 1.47 nM 0.147 nM

+PD Kn3

OD

450

OD

450

OD

450

OD

450

OD

450

Binding Activity (ELISA) Following Incubation in PBS at 70o C for 1 hr

Kp1

-20

0

20

40

60

80

100

120

1 20 39 58 77 96 115 134 153 172 191 210 229 248 267 286 305 324 343 362 381 400

PD

-10

0

10

20

30

40

50

60

70

1 19 37 55 73 91 109 127 145 163 181 199 217 235 253 271 289 307 325 343 361 379 397

Kp3

-20

0

20

40

60

80

100

0 100 200 300 400 500 600 700

WT

-20

0

20

40

60

80

100

120

140

0 50 100 150 200 250 300 350 400 450

Kp1

scFv ka (M-1s-1) koff (s-1) KD (M)

WT 3.77e5 1.34e-2 3.55e-8

Kp1 2.2e6 3.71e-3 1.69e-9

PD 1.82e6 3.88e-3 2.14e-9

Kp3 2.17e3 6.1e-6 2.81e-9

20-fold lower KD

>1,000-fold lower koff

Add assembled gene to in vitro expression extract, incubate ~4 hrs.

Bind target protein to beads (immobilized metal

affinity purification)

Wash beads, Add reactive dye, wash again.

Distribute and assay on 96-well microplates

against target compounds and

controls

Cell-Free Screening of Synthetic Genes

Select positions for cysteinesWrite open reading framesExpress in vitro, label on beads,Screen for sensors.

Idea to results in about a week.

What is synthetic biology?

• Standardization of bioengineering?‡ Modular, composable, scalable,programmable parts, circuits, and systems

• Extended DNA synthesis capabilities?‡ Making more, longer, and more quickly

• Modification of the chemistry of living systems?‡ Chemical biology, except moreso

• Hype?

Synthesis is a research strategy, not afield. Synthesis sets forth a grand challenge:"Create an artificial chemical systemcapable of Darwinian evolution." … Attempting tomeet this challenge, scientists and engineersmust cross uncharted territory, where theymust encounter and solve unscripted problemsguided by theory.

Benner et al. (2010), Comptes Rendus Chimie

Methods for Unnatural Amino Acid Incorporation

Schultz Orthogonal Pair

Cross-linking with unatural amino acids

Chembiochem. 2009 May 25; 10(8): 1302–1304. doi:10.1002/cbic.200900127.

L-DOPA

Az-Phe UV (254 nm) cross-linking reagent

JACS 2002 124: 9026-7

Azidophenylalanine

MS2/anti-MS2 scFv Cross-linking Scheme

Rapid prototyping: anti-MS2 Amber Scans

BHJ Bielski et al. 1980 J. Phys. Chem. 84: 830-33

Detection of L-Dopa incorporation by NBT

Amber-scan L-Dopa X-linking Results

Hits: H1-5, H1-7, H3-4, L1-4, L1-5, L1-6, L1-11, L1-12, L1-13, L1-14, L2-3, L2-4, L2-5

AzoPhe RS Construction

MjYRS PDB: 1J1UH2N COOH

N3

AzoPhe

ÿ Engineered supercharged anti-MS2 scFvs displaying nearly no loss of binding affinity following incubation at 70 C

ÿ Supercharged scFv variants display 10-100 fold increased antigen bindingaffinity

ÿ Engineered “patch disruption” mutants that also display increased antigen binding affinity and stability to irreversible deactivation

ÿ Designed mutants displaying higher thermodynamic stability

ÿ Demonstrated irreversible antigen binding using antibodies containingunnatural amino acid in the CDRS

Quickly constructed, expressed and characterized over 70 scFv antibody genes

Positive impact of rapid prototyping on biodefense

However, to engineer organisms requires that we switch focus

Wang et al. (2009) Nature 460:894

Oligo shuffling into genomes

Circuits aren’t really orthogonal;therefore, the unit of engineering must be thegenome itself

Group II self-splicing introns for genomic editing

Guo et al., EMBO J. 16, 6835-6848, 1997

Testing in Lambowitz lab or in collaboration

Done in other labDone at Sigma

Pseudomonas aeruginosa

Clostridium perfringens

Burkholderia thailandesis

Lactococcus lactisBacillus subtilis

Staphylococcus aureus

Mycobacterium smegmatis

Escherichia coliSalmonella typhimurium

Shigella flexneri

Francisella tularensis

Agrobacterium tumefaciens

Validated organisms:

Agrobacterium tumefaciensAzospirillum brasilienseBacillus subtilis Clostridium acetylbutylicumClostridium botulinumClostridium difficile Clostridium perfringensClostridium sporogenesEscherichia coliFrancisella tularensisLactococcus lactisProteus mirabilisPseudomonas aeruginosaSalmonella typhimuriumSerratia marcescensShigella flexneriStaphylococcus aureus Xylella fastidiosa

Synechococcus sp.

A wide range of bacteria can be targeted

High efficiency insertion … without selection

Directionality of recombination via Lox site variants

Langer et al. Nucleic Acids Res. 30:3067 (2002)

Successfully put GFP and KanR into E. coli genome

Site-directed insertion of Cre sites for directed recombination

Peter Enyeart

Genome editing abets a variety of large-scale rearrangements

1200 bp

1200 bp

NC NC NC

NC NC

pQL269 on LB pQL269 on LB + glucose pCre liquid grown

pCre liquid grown pQL269 liquid grown

Sequenced-Matches sequence expected sequence for deletion

Genome editing: 121 kb deletion with high efficiency

Identifying recombination events by PCR

We can now also mass-produce Targetrons in our Fab

Doubling times for genome edited strains(with standard errors and 95% confidence intervals)

strain DT SE 95% CI comments

MG1655 24.94 0.10 0.20

MG1655DE3 24.44 0.16 0.32 base strain for E1-E11

E1 28.33 0.49 1.0 A-lacZ deletion

E2 33.25 0.62 1.2 E-lacZ inversion (reversible)

E3 22.03 0.14 0.28 A-lacZ inversion (irreversible)

E4 24.65 0.41 0.80 D-E inversion (reversible)

E5 30.5 1.2 2.3 E-lacZ inversion (irreversible)

E6 33.94 0.76 1.5 lacZ-A, D-E deletion

E7 25.24 0.49 1.0 lacZ-A region to E, reverse orientation

E8 23.65 0.41 0.80 lacZ-A region to E, forward orientation

E9 29.27 0.99 1.9 lacZ-A, D-E, B-C simultaneous deletion

E10 31.39 0.20 0.39 lacZ-A, D-E, B-C sequential deletion

E11 24.45 0.49 1.0 D-E del

The tst gene encodes toxic-shock syndrome toxin, the most common cause of toxic shock syndrome (though incidence of that has been decreasing since the issues with tampons in the early 80s). The sek and sel genes encode superantigen enterotoxins K and L, which are causative agents of staphylococcal food poisoning.

Genomic editing of a S. aureus pathogenicity island

lox66 lox71

lox72

+ Cre

Frankenbugs

Itaya et al. (2005) PNAS 102:15971

• It may prove possible to use computational design andrapid prototyping to make ‘parts’ with novel functionality.

• There are tools available to facilitate genomic engineering; rapid genome prototyping may eventually be possible.

• Neither of these advances makes possible the modular, composable, scalable, and programmable construction of circuitry with predictable functionality.

• This is because the parts and the circuits must rely on an underlying rationality that is not found in biology.

• Thus, we must recraft the basics of biology.

Protein ‘hybridization’

Parts Standardization via Nucleobase Amino Acids

Choice of synthetase:tRNA pairs

Rapid prototyping of tRNA synthetase:tRNA orthogonal pairs

Ade-Ala RS rational designs

H2N COOH

NH

TryptophanH2N COOH

NN

N

N

Adenyl-alanine

NH2

Adenyl alanine docked into the active site of tryptophanyl tRNA synthetase; mutationsIntroduced by rational design (eyeballing)

Raa2

Y>S106

I>S253

A>N256

E>Q141

Selection System

Nucleobase amino acids ‡ Proteins with nucleic acid-like properties ‡ Programming

FhuA-GAP

Programmable‘hormones’

Programmableconnections

The possibilities inherent in DNA computation are nicelyIllustrated by two young lions of the Wyss Institute:

William ShihPeng Yin

Basic circuit

Li, Ellington, Chen (submitted)

Xi Chen

Catalytic hairpin assembily

Positive image – Activating DNA circuit with UV

20 (min)0 Exposure time

Self-inhibited

Activeτ = c.a. 7 min

Positive image – Activating DNA circuit with UV

Edge detector – Dual response

Positive image Edge detection

'05 '06 '07 '08 '09 '10 '11

Programming E.coli(Date of publication)

(Date of experiment)

Programming DNA

3.5 years

0.5 year

Levskaya et al., Nature (2005)Tabor et al., Cell (2009)

The advantages of programmability

StevenChirieleison

Khalil and Collins (2010), Nat Rev Genetics

Into the future …

… which of these analogies is best suited to synthetic biology, whatever that is? Chemical ‘wires’ (Tamsir et al. (2011), Nature) aren’t really the same as electrical wires. Addressability, spatial inhomogeneity, and their relationship to mechanismare utterly different between electrical and chemical circuits.

Software, an esoteric concept, can be developed for electronic circuits becausedigital logic ‘fits’ immediate communication between gates with high fault tolerances. It is possible that biological software can and will be written, but only after we succeed in understanding and engineering reaction-diffusion dynamics (*not* parts) in a modular, composable, scalable, and programmable way.

And that will only be possible with nucleic acid (or nucleic acid-like) parts.

Acknowledgements

Center for Systems and Synthetic BiologyApplied Research Labs, UT-Austin

George Georgiou and his labAlan Lambowitz and his labGrant Willson and his lab

DARPADTRA

NSF Fellowship (Enyeart)NSF Sandpit

NSSEFFNIH TR01