UPV-UV Valencia iGEM 2006 Alfonso Jaramillo Ecole Polytechnique, Paris & InterTech (UPV)
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UPV-UV Valencia iGEM 2006
Alfonso JaramilloEcole Polytechnique, Paris
& InterTech (UPV)
Summary of work plan
• April: Training lectures, promotion, team building and funding.
• May/June: Prototype design.• July/August: Parts & Devices construction
& characterization. Redesign prototype.• September/October: System
characterization.
Synthetic BiologySynthetic Biology
Outline
• Biological modules for engineering– Parts– Devices– Systems
• Design of parts
Biological modules for engineering
• Chassis: Bacterial strain that will receive the engineered systems.
• Parts: Fragment of DNA with a given functionality.
• Devices: Assembly of parts with a given functionality and given interface.– Specifications– I/O is given by proteins and signals
• Systems: Assembly of devices with a given functionality– I/O is given only by signals
‘I need a few DNA binding proteins.’
‘Here’s a set of DNA binding proteins, 1N, that each recognize a unique cognate DNA site, choose any.’ ‘Get me this DNA.’
‘Here’s your DNA.’
‘Can I have three inverters?’
‘Here’s a set of PDP inverters, 1N, that each send and receive via a fungible signal carrier, PoPS.’
TAATACGACTCACTATAGGGAGA DNA
Zif268, Paveltich & Pabo c. 1991
Parts
PoPSNOT.1PoPS PoPS Devices
PoPS NOT.2
PoPS NOT.3
PoPS NOT.1
Systems
• Decoupling– Rules insulating design process from details of fabrication
– Enable parts, device, and system designers to work together
– VLSI electronics, 1970s
• Standardization– Predictable performance
– Off-the-shelf
– ME, 1800s
• Abstraction– Insulate relevant characteristics from overwhelming detail
– Simple artifacts that can be used in combination
– From Physics to EE, 1800s
Biological Engineering
Parts
• Promoter• RBS• CDS• Terminator• Tag• Primer• Operator
I13453 B0034 I15008 B0034 I15009 B0015tetR
R0040 B0034 I15010 B0015
BBa_M30109 =
Notice that for the MIT registry, any combination of parts (e.g. devices and systems) is a part.
Parts Construction
• Simplified cloning procedure that allows to combine plasmids using a standardized approach.
• The construction of devices is reduced to the combination of parts (to generate new parts, in the MIT terminology).
• Careful with the maximum size of plasmids
Parts Construction
S PXE
Standard PCR and sequencing primers have been chosen for pSB103 to use for colony PCR for insert length selection, and for sequencing of inserts:
Verication Forward: 5' TTG TCT CAT GAG CGG ATA CA 3‘Verication Reverse: 5' ATT ACC GCC TTT GAG TGA GC 3’.
cut the green plasmid with EcoRI and XbaI enzymes.
cut the blue plasmid with EcoRI and SpeI,
A minimum number of bases (undetermined) between the EcoRI and XbaI sites and the SpeI and PstI sites may be required to allow complete cutting with both enzymes (NotI).
The vector and insert must not contain any other EcoRI, XbaI, SpeI, or PstI cut sites. This excludesthe following hexamer sequences:
•EcoRI: GAATTC•XbaI: TCTAGA•SpeI: ACTAGT•PstI: CTGCAG
And octameric recognition site for NotI, GCGGCCGC.
Devices
• They should be able to always produce the same ouput from the same input.– Need of specification of transfer functions and I/O
proteins/molecules.– The engineer will be able to model the devices from the
specifications without needing to know the internals. Encapsulation of data.
– Devices with interface with each other. Need of a standard.
– In the real world the devices will interact with the chassis.
Devices
LacI CI inverter
CILacI
Devices
cI-857OLac RBS T
CILacI
LacI
CI
Systems
Inverter.2 Inverter.3Inverter.1
Device-Level System Diagram
Parts- and Device-Level System Diagram
DNA Layout
Device Interface
cI-857OLac RBS T
cILacI
cI-857RBS T
cI
O
PoPSin
PoPSout
LacI
cIPoPSout
PoPSin
cIRBST
O
cI
PoPSIN
Polymerase Per Second = PoPS!
cIRBST
O
PoPSOUT
cIRBST
O
PoPSOUT
PoPSIN
cI
PoPSOUTPoPSIN
Polymerase Per Second = PoPS!
INVERTER
PoPSOUTPoPSINPoPSOUT
PoPS Source (Any)
Towards an Ideal Chassis
• We would like to have a chassis that will not interfere with our devices.
• We need a dedicated protein production.
Biological Virtual Machines
• Dedicated systems are a method to decouple the function of an engineered biological system from the function of its chassis.
• By separating the resources and machinery used to supply and power an engineered system from those of the chassis, then perturbations in the operation of one should have less effect on the other.
• These dedicated synthesis systems can then be used as the basis of Biological virtual machines.
General Translation VM Translation
General Transcription
I7101
I7102
VM Transcription
E7104
E7103
The T7 expression system developed by Studier and coworkers is essentially orthogonal from the E. coli transcription system. T7 RNAP does not recognize E. coli promoters and E. coli RNAP does not recognize T7 promoters.
Design of Parts
Gene Designhttp://slam.bs.jhmi.edu/gd/
Zinc-finger repressor system
Designed linker sequence TGEKP between E3 and F4.
natural linker peptides between F1 and F2 (TGQKP) and between F2 and F3 (TGEKP),
Barbas PNAS 97bind DNA containing the 18-nt site 5'-GCGTGGGCGGCGTGGGCG-3'.
http://www.scripps.edu/mb/barbas/zfdesign/zfdesignhome.php
•Codon Usage: there is little tRNA made for rare codons. In E. coli these are mainly AGA and AGG (Arg codons). The genes encoding the tRNAs can be co-overexpressed.
•Promoters used should be very tight. Tight promoters are for example arabinose (BAD), rhamnose and lactose (provided that lacIQ is co-overexpressed).
•RBS (Shine-Delgarno Sequence - serves to align the ribosome on the message in the proper reading frame.) Optimal: AGG AGG, the last G should be 9 bases upstream from the A of the AUG (start of translation) Start codons on mRNA are: AUG (90%, codon for Met), GUG (9%), UUG (1%) and CUG (0.1%). Avoid secondary structure involving SD sequence and the initiator AUG. In polycistronic mRNAs, the initiation site should be close to the termination codon of the upstream gene.
•Regulation of translation: is sometimes (not often) affected by sequences in the coding region: +5 and +10 should be A or T
•RNA Stability can be increased if stem-loop structures are cloned at the 3' end of the coding region
Factors that Influence Gene Expression
Expression Vectors•Low copy number plamids are better than high copy number plasmids (copy numbers of 5-40 is recommended).
•Yield of protein does not linearly correlate with copy number of a gene.
•Regulated promoter - the optimum is one that is induced by a substrate such as IPTG that diffuses into the cell because then induction levels can be more easily manipulated.
•Inducers that are a substrate of one or more active transport systems cannot be controlled at all. These inducers will be accumulated to mM levels even when added in very low concentrations to the growth medium.
•Co-overexpression of repressors of the promoter used can provide excellent control of transcription. Co-overexpression of activators guarantees that each promoter on the plasmids is activated.
•Place transcription terminator at the 3' end of target gene. This avoids formation of antisense RNAs from downstream promoters operating in reverse orientation with respect to the gene that should be expressed at high levels.
Getting folded proteins
• Broken protein domains don't fold
• Difficult to get folded in the cytoplasm a protein containing disulfide bonds.
• Coexpress other members of a hetero-oligomeric complex
• Inclusion body formation can often be reduced by growing cells at 200C (Note that 280C does not work nearly as well). If this is not successful, try adding 6% ethanol to rich medium when adding inducer. EtOH induces heat shock response which overexpresses chaperones and proteases. The latter are barely active at 200C.
E.Coli parameters:http://redpoll.pharmacy.ualberta.ca/CCDB/cgi-bin/STAT_NEW.cgi
Parameters
DNA and RNA molecular weights:http://www.ambion.com/techlib/append/na_mw_tables.html
Design of Devices
Example of devices: Regulatory, input, output, sensors, signaling, metabolic, etc…
The biological inverter
Modeling a Biochemical Inverter
input
output
repressor
promoter
Steady-State Behavior: Transfer Functions
“ideal” transfer curve: gain (flat,steep,flat) adequate noise margins
[input]
“gain”
0 1
[output]
This curve can be achieved using proteins that cooperatively bind dna!
This curve can be achieved using proteins that cooperatively bind dna!
Inverter
Measuring a Transfer Curve
• Construct a circuit that allows:– Control and observation of input protein levels– Simultaneous observation of resulting output levels
“drive” gene output gene
R YFPCFP
inverter
• Also, need to normalize CFP vs YFP
Flow Cytometry (FACS)
0
200
400
600
800
1,000
1,200
1,400
1 10 100 1,000 10,000
Fluorescence (FL1)
Eve
nts
Drive Input Levels by Varying InducerIPTG (uM)
0
250
1000
0
200
400
600
800
1,000
1,200
1,400
1 10 100 1,000 10,000
Eve
nts
0
200
400
600
800
1,000
1,200
1,400
1 10 100 1,000 10,000
Eve
nts
IPTGpINV-1024125 bp
Kan(r) lacI
EYFP
P(LAC)
P(lacIq)
p15A ori
T0 Term
T1 Term
(or ECFP)
plasmid
promoter
protein coding sequence
IPTG
YFP
lacI[high]
0(Off) P(LtetO-1)
P(R)
1.00
10.00
100.00
1,000.00
0.1 1.0 10.0 100.0 1,000.0 10,000.0
IPTG (uM)
FL
1 pINV-112-R1
pINV-102
Also use for yfp/cfp calibration
Controlling Input Levels
Measuring a Transfer Curve for lacI/p(lac)
EYFPlacIP(LAC)P(LtetO-1)
RBSIIRBSII
tetRLambda P(R-O12)
RBSII
aTc
ECFP
“drive”
output
aTc
YFPlacICFP
tetR[high]0
(Off) P(LtetO-1)
P(R)
P(lac)
measure TC
Transfer Curve Data Points
01 10
1 ng/ml aTc
0
200
400
600
800
1,000
1,200
1,400
1 10 100 1,000 10,000
Fluorescence (FL1)
Eve
nts
undefined
10 ng/ml aTc 100 ng/ml aTc
0
200
400
600
800
1,000
1,200
1,400
1 10 100 1,000 10,000
Fluorescence (FL1)
Eve
nts
0
200
400
600
800
1,000
1,200
1,400
1 10 100 1,000 10,000
Fluorescence (FL1)
Eve
nts
1
10
100
1000
1 10 100 1000
Input (Normalized CFP)
Ou
tpu
t (Y
FP)
lacI/p(lac) Transfer Curve
aTc
YFPlacICFP
tetR[high]0
(Off) P(LtetO-1)
P(R)
P(lac)
gain = 4.72gain = 4.72
Evaluating the Transfer Curve• Noise margins:
0
200
400
600
800
1,000
1,200
1,400
1 10 100 1,000
Fluorescence
Eve
nts
30 ng/mlaTc
3 ng/mlaTc
1
10
100
1,000
0.1 1.0 10.0 100.0
aTc (ng/ml)
Flu
ore
scen
ce
• Gain / Signal restoration (95%):
high gainhigh gain
* note: graphing vs. aTc (i.e. transfer curve of 2 gates)
FACS cell population data
Logic Circuits based on Inverters
• Proteins are the wires/signals• Promoter + decay implement the gates• NAND gate is a universal logic element:
– any (finite) digital circuit can be built!
X
Y
R1 Z
R1
R1X
Y
Z= gene
gene
gene
NAND NOT
The IMPLIES Gate
• Inducers that inactivate repressors:– IPTG (Isopropylthio-ß-galactoside) Lac repressor
– aTc (Anhydrotetracycline) Tet repressor
• Use as a logical Implies gate: (NOT R) OR I
operatorpromoter gene
RNAP
activerepressor
operatorpromoter gene
RNAP
inactiverepressor
inducerno transcription transcription
Repressor Inducer Output
0 0 10 1 11 0 01 1 1
RepressorInducer
Output
10
1
102
103
100
101
102
100
101
102
103
IPTG (mM)
aTc (ng/ml)
Me
dia
n F
LR
Transfer Curve of Implies
YFPlacI
aTcIPTG
tetR[high]
Device Optimization
Measure cI/P(R) Inverter
OR1OR2 structural gene
P(R-O12)
• cI is a highly efficient repressor
cooperativebinding
IPTG
YFPcI
CFPlacI[high]0
(Off) P(R)P(lac)
• Use lacI/p(lac) as driver
highgain
cI bound to DNA
lacI CI+CFP YFP
IPTG
Initial Transfer Curve for cI/P(R)
• Completely flat– Reducing IPTG no additional fluorescence
• Hard to debug!
• Process engineering:Is there a mismatch between inverters based on
lacI/p(lac) and cI/P(R)?
1.00
10.00
100.00
1,000.00
0.1 1.0 10.0 100.0 1,000.0
IPTG (uM)O
utp
ut
(YF
P)
Inverters Rely onTranscription & Translation
mRNA
ribosome
promoter
mRNAribosome
operator
translation
transcription
RNAp
Process Engineering I:Different Ribosome Binding Sites
BioSpice Simulations
RBS
translation
start
Orig: ATTAAAGAGGAGAAATTAAGCATG strongRBS-1: TCACACAGGAAACCGGTTCGATG RBS-2: TCACACAGGAAAGGCCTCGATGRBS-3: TCACACAGGACGGCCGGATG weak
1.00
10.00
100.00
1,000.00
0.1 1.0 10.0 100.0 1,000.0
IPTG (uM)
Ou
tpu
t (Y
FP
)
pINV-107/pINV-112-R1
pINV-107/pINV-112-R2
pINV-107/pINV-112-R3
Experimental Results forModified Inverter
Strong
Weak
Process Engineering II:Mutating the P(R)
orig: TACCTCTGGCGGTGATAmut4: TACATCTGGCGGTGATAmut5: TACATATGGCGGTGATAmut6 TACAGATGGCGGTGATA
OR1
Experimental Results for Mutating P(R)
1.00
10.00
100.00
1.000.00
0.1 1.0 10.0 100.0 1.000.0
IPTG (uM)
Ou
tpu
t (Y
FP
)
pINV-107-mut4/pINV-112-R3
pINV-107-mut5/pINV-112-R3
pINV-107-mut6/pINV-112-R3
Strong
Weak
Lessons for BioCircuit Design• Naive coupling of gates not likely to work• Need to understand “device physics”
– enables construction of complex circuits
• Use process engineering– modify gate characteristics
1.00
10.00
100.00
1,000.00
0.1 1.0 10.0 100.0 1,000.0
IPTG (uM)
Ou
tpu
t (Y
FP
)
RBS
RBS+O1
(a) Reducing the repressor/operator binding affinity
(b) Reducing the strength of the promoter
(c) Reducing the strength of the RBS
(d) Increasing the cistron count
(e) Adding autorepression
Other Gates
The Toggle Switch[Gardner & Collins, 2000]
pIKE = lac/tetpTAK = lac/cIts
Actual Behavior of Toggle Switch[Gardner & Collins, 2000]
promoter
protein coding sequence
Example of Devices
Input
• Membrane proteins (including ion channels)• Sensors (some of them membrane prots)
Sensors
• Using inducible promoters– IPTG, tetracycline, etc...– Temperature (sigma32)
• Using RNA• Design custom sensors
– Light detector (using phytochrome)
Genetic light switch• Phytochrome suffers a (reversible) conformational change
upon red light induction.• Tested in Yeast, but it can be implanted in any organism
able to synthesize the chromophore and assemble it.
Shimizu-Sato et al. Nat. Biotech. 2002
Chromophore Biosynthesis
Gambetta et al. PNAS 2001
Output
• Reporters– GFP, RFP, YFP– LacZ
GFP
• Highly resistant to temperature, pH, chemical denaturants, and proteases
• Intrinsic and independent fluorescence allows in vivo monitoring
• Easily measured by UV light, fluorescence microscopy, or FACS
• GFP fusion proteins retain biological activity (N and C-terminal)
• Applicable to many systems (E. coli, Drosophila, mammalian)
BBa_E0040
LacZ
• By addition of S-gal (3,4-cyclohexenoesculetin-D-galactopyranoside), LacZ catalyses the formation of a stable, insoluble,black precipitate from S-gal.
BBa_E0033
Signaling Devices
Signaling
• Senders• Receivers• Transmitters• Amplifiers
Intercellular Communications• Certain inducers useful for communications:
1. A cell produces inducer2. Inducer diffuses outside the cell3. Inducer enters another cell4. Inducer interacts with repressor/activator change signal
(1) (2) (3) (4)
mainmetabolism
Quorum Sensing
• Cell density dependent gene expression
Example: Vibrio fischeri [density dependent bioluminscence]
The lux Operon LuxI metabolism autoinducer (VAI)
luxR luxI luxC luxD luxA luxB luxE luxG
LuxR LuxI(Light)
hv(Light)
hvLuciferaseLuciferase
P
P
Regulatory Genes Structural Genes
Light organ
Eupryma scolopes
Density Dependent Bioluminescence
free living, 10 cells/liter<0.8 photons/second/cell
symbiotic, 1010 cells/liter 800 photons/second/cell
A positive feedback circuit
luxR luxI luxC luxD luxA luxB luxE luxG
LuxRLuxI
P
P
Low Cell DensityLow Cell Density
luxR luxI luxC luxD luxA luxB luxE luxG
LuxR LuxI
(Light)hv
(Light)hvLuciferaseLuciferase
P
P
High Cell DensityHigh Cell Density
LuxRO O
O
ONH
O OO
ONH
O OO
ONH
O OO
ONH
LuxR
(+)
O OO
ONH
O OO
ONH
O OO
ONH
O OO
ONH
O OO
ONH
O OO
ONH
O OO
ONH
O OO
ONH
O OO
ONH
O OO
ONH
O OO
ONH
O OO
ONH
(a) LuxI/R quorum sensing.(b) Peptide-mediated quorum sensing in development of competence.(c) Quorum sensing in V. harveyi.
Quorum Sensing Systems
ComD: histidine kinase
the periplasmic LuxP protein
that is involved in recogni-tion of AI-2 is not
shown for simplicity.
Similar Signalling SystemsN-acyl-L-Homoserine Lactone Autoinducers in Bacteria
Species Relation to Host Regulate Production of I Gene R Gene
Vibrio fischeri marine symbiont Bioluminescence luxI luxR
Vibrio harveyi marine symbiont Bioluminescence luxL,M luxN,P,Q
Pseudomonas aeruginosa Human pathogen Virulence factors lasI lasR
Rhamnolipids rhlI rhlR
Yersinia enterocolitica Human pathogen ? yenI yenR
Chromobacterium violaceum Human pathogenViolaceum production Hemolysin Exoprotease
cviI cviR
Enterobacter agglomerans Human pathogen ? eagI ?
Agrobacterium tumefaciens Plant pathogen Ti plasmid conjugation traI traR
Erwinia caratovora Plant pathogenVirulence factors Carbapenem production
expI expR
Erwinia stewartii Plant pathogen Extracellular Capsule esaI esaR
Rhizobium leguminosarum Plant symbiont Rhizome interactions rhiI rhiR
Pseudomonas aureofaciens Plant beneficial Phenazine production phzI phzR
Circuits for Controlled Sender & Receiver
pLuxI-Tet-8 pRCV-3
Fragment of pRCV-32038 bp (molecule 4149 bp)
GFP(LVA)
LuxR lux P(L)
lux P(R)
rrnB T1 rrnB T1
• Genetic networks:
• Logic circuits:
VAI VAI
Fragment of pLuxI-Tet-81052 bp (molecule 2801 bp)
LuxIP(LtetO-1) T1
aTc
luxI VAI
* E. coli strain expresses TetR (not shown)
*
VAI
LuxRGFP
tetR
aTc
00
receiverssenders
overlay
receivers senders
overlay
Remarks About Control Theory
Becskei & Serrano, Nature 2000
Model of tryptophan biosynthesis
0 5 10 15 200.8
0.85
0.9
0.95
1
1.05
Time (minutes)
[P]
h = 3
h = 0
0 2 4 6 8 10-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
Frequency
Lo
g(S
n/S
0)
h = 3
h = 0
Spectrum
Time response
Robust
Yet fragile
0 2 4 6 8 10-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
Frequency
Lo
g(S
n/S
0)
h = 3
h = 2
h = 1
h = 0
log )nxF(
Tighter steady-stateregulation
Transients, Oscillations
log )nx d constant F(
Theorem
log )nx d constant F(
log|S |
Tighter regulation
Transients, Oscillations
Biological complexity is dominated by the evolution of
mechanisms to more finely tune this robustness/fragility tradeoff.
This tradeoff is a law.
log )nx d constant F(
log|S |
Define log "fragility" ( )nS S x F
Conservation of “fragility”
Bacterial chemotaxis
Yi et al. PNAS 2000
Integral control
Integral Control
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