synthetic biology and biodefense andrew d. ellington ......synthetic biology and biodefense andrew...
TRANSCRIPT
-
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