Transcript Document

International Genetically
Engineered Machines
Competition
M.I.T, Nov 7th-9th 2008
An introduction to the University of
Sheffield 2008 iGEM Team…
University Of Sheffield 2008 iGEM Team
What is iGEM?
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iGEM is a rapidly increasing international
competition for undergraduates in many different
specialisations
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Designed to involve undergraduates in research early in their
careers
Over 84 teams from all around the world this year
Premise is to expand on the principle of synthetic
biology
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Pieces of DNA are designed and standardised at each end, in the
hope of building novel organisms
Information made publicly available
‘Wiki’
Summer 2008
University Of Sheffield 2008 iGEM Team
Who are we?
Gosia Poczopko
1st year Molecular and
Cellular Biochemist
Eva Barkauskaite
1st year Biochemist
Rosie Bavage
1st
year Molecular
Biologist
Dmitry Malyshev
1st year Biomedical
Engineer
Hammad Karim
2nd year Engineer
Sam Awotunde
2nd year Engineer
Summer 2008
University Of Sheffield 2008 iGEM Team
The Idea
A biosensor for cholera in drinking water –
machine/test/kit
 We want to hijack a pathway in E.coli and
manipulate it to detect Vibrio cholerae
quorum sensing autoinducers
 GFP marker inserted downstream
 Proof of principle in fusion kinase
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Summer 2008
University Of Sheffield 2008 iGEM Team
BarA Pathway
• More than 20 target
genes for UvrY
• Includes glycogen
synthesis, glycolysis,
gluconeogenesis,
glycogen catabolism.
• Our target: PGA
operon – role in
biofilm formation
Summer 2008
University Of Sheffield 2008 iGEM Team
Fusion Receptor
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Expression of membrane bound
receptor sensing V. cholera
signalling molecule in E.coli
Novel approach – to fuse receiver
and transmitter domain from two
related receptors
Receptors are closely related and
have similar topology
Fused receptor:
 CqsS – V.cholerae
 BarA – E.coli
Summer 2008
University Of Sheffield 2008 iGEM Team
Fusion Receptor
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Sequences to be fused were found through multisequene allignment
and comparison with similar proteins
Summer 2008
University Of Sheffield 2008 iGEM Team
Fusion Receptor
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Pathways regulated via BarA are well characterised
Summer 2008
University Of Sheffield 2008 iGEM Team
GFP into genome
GFP will act as our reporter
 Inserted into the genome under the
promoter of PGA operon between PGAa
and PGAb
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Summer 2008
University Of Sheffield 2008 iGEM Team
Gene Knockout
To make sure native BarA doesn’t trigger
the production of GFP, we need to knock
out certain genes from our strain
 Using Datsenko and Wanner’s method for
speeding up recombination
 PCR products provide homology, λ Red
recombinase system provides faster
recombination.
 Marker gene removed later
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Summer 2008
University Of Sheffield 2008 iGEM Team
Gene Knockout
Summer 2008
University Of Sheffield 2008 iGEM Team
Problems
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We couldn’t get a knockout
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5 repeats, with varied condition
Various setbacks and little time
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Ampicillin
Summer 2008
University Of Sheffield 2008 iGEM Team
CAI-1 Synthesis
CqsA is the synthesis machine for CAI-1’s
in cholera
 Bonnie Basslers lab designed plasmid and
protocol for transferring CqsA into E.coli
and purify the CAI-1 product – it works
 Received and used
 Mass-spec to confirm been difficult to obtain
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Summer 2008
University Of Sheffield 2008 iGEM Team
Further ideas
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Re-usuable sensor
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Cleavable GFP/ housekeeping gene regulation – LVA
tag.
Provided by past iGEM project = criteria for an award
Threshold experiments
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Modelled
Summer 2008
BioBrick - Characterization
Plan: Insertion of GFP-LVA under pgaABCD
operon.
Why?
 Reporter
 GFP-LVA gene previous BioBrick = Criteria for
‘Silver Award’
 LVA tag attracts housekeeping protease –
degradation/reusable
 Lac promoter = inducible, for measurement of
fluorescence
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What has been done?
DH5-alpha transformed with an
uncharacterized GFP-LVA BioBrick
 Used Tecan® , with fluorescence
measurements every 15 minutes for 8
hours
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Results 1
5 repeated measurements, with consistent
lack of fluorescence
 Tried RFP-LVA (uncharacterized but made
by different team) and characterized, tested
RFP
 Transformation 1 failed, transformation 2 in
MBB failed despite successful positive
controls
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Conclusion
Not one successful transformation, despite
using tested BioBricks
 A lot of troubleshooting, from various
advisors
 Last attempt: carried out by PhD student,
which failed
 Conclusion: BioBrick booklet may have
been faulty. However has not been proven.
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Heath and Safety
Vibrio cholerae impossible to work on
 CAI-1s non-toxic themselves
 Repress Cholerae biofilm formation in
nature
 CqsA only produces CAI-1s
 Safe
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University Of Sheffield 2008 iGEM Team
Acheive: Bronze Award
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Register
Complete and submit a Project Summary form.
Create an iGEM wiki
Present a Poster and Talk at the iGEM Jamboree
Enter information detailing at least one new standard BioBrick Part or
Device in the Registry of Parts
– including nucleic acid sequence, description of function,
authorship, safety notes, and sources/references.
Submit DNA for at least one new BioBrick Part or Device to the
Registry of Parts
We’ve done all of these
Summer 2008
University Of Sheffield 2008 iGEM Team
Engineering - Sam
Synthetic biology is the application of
engineering principles and approach to
molecular biology
 Mathematical modelling of our BarA/UvrY
system , with fluorescence of GFP, allows
its dynamics and behaviour to be analysed
 The model is validated in a two steps:
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The signal transduction
The gene expression.
Summer 2008
A Two-component Signal Transduction System
Sensor kinase
Response regulator
BarA~p
Uvry.DNA
Uvry~p
R4
R1
R2
R3
DNAf
DNA binding
Uvry
BarA
Phosphoryl
transfer
dephosphorylation
The Chemical Reactions
Auto-phosphorylation:
ATP + BarA ↔ ADP + BarA~p --Reaction 1
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Phosphoryl group transfer :
BarA~p + UvrY ↔ BarA + UvrY~p - Reaction 2
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Dephosphorylation :
UvrY~p + BarA → UvrY + BarA (+ pi) -Reaction
3
• DNA binding :
2 UvrY~p + DNAƒ ↔ (UvrY – DNA)----Reaction 4
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Reaction Analyses
• In reaction R1, the stimulus enhances the kinase activity that
results in auto-phosphorylation of sensor kinase (BarA, BarA~p
state variable) by ATP
• In reaction R2 the phosphoryl group is transferred to th response
regulator (Uvry, Uvry~p state variable). Uvry~p contains the active
output domain.
• Reaction R3 describes the dephosphorylation of Uvry~p by
cognate sensor kinase BarA. (it has been shown through reference
that dephosphorylation is only dependent on BarA. Jung et.al.,
1997) so that other phosphatises are not considered in the model.
• In reaction R4 the activated response regulator forms a dimer and
is then binds to the free DNA (DNAf, state variable) to build a
transcription complex (Uvry-DNA, state variable), in presence of
RNA polymerase.
Differential Equations
Phosphorylation Rate of BarA
Phosphorylation Rate of UvrY
Rate of GFP Gene Expression
Parameter Values
In vitro parameters
K1 = o.oo29 1/h µM
DNA₀ = 100µM
k_1= 0.00088 1/hµM
BarA₀ = 1µM
K2= 108 1/hµM
Uvry₀ = 4µM
K_2= 1080 1/hµM
ATP = 100µM
Kь = 5400 1/hµM
ADP = 8µM
K_ь = 360 1/h
K3= 90 1/hµM
Conclusions
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The model and simulation was carried-out
in Matlab and the dynamics of the system
was studied.
The parameters with highest sensitivity
were k1, kb, k3, k_b.
The response of the autophosphorylation
and phosphorylation of the BarA, Uvry and
the expression of the gene respectively
show that the system is stable and under
any conditions it should respond well.
University Of Sheffield 2008 iGEM Team
Engineering – Hammad’s Probabilistic approach
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For simplicity, whole reaction is split into
two parts:
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CAI-1 interacting with Fusion Kinase
From response regulatory protein to GFP glow.
Mathematically,
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Summer 2008
University Of Sheffield 2008 iGEM Team
Engineering – Hammad’s Probabilistic approach
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Considering this as Poisson Process:
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The General form of probability is then given as:
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Also this interaction will follow law of diffusion (ideal case), thus
probability of reaction rate increasing with time can be given as
Gaussian distribution :
Summer 2008
University Of Sheffield 2008 iGEM Team
Engineering - The Probabilistic approach
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Implementation:
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As there are some other processes occurring at the same time (like
noise disturbance and various reactions) using Gaussian mixture
models :
Summer 2008
University Of Sheffield 2008 iGEM Team
Engineering - The Probabilistic approach
Probability curves of contact between molecules
Summer 2008
University Of Sheffield 2008 iGEM Team
Sponsors
idtDNA – £1000 gene, and 10 free primers
 iChemE - £1000 reimbursement for travel
 £2500 from Prof Poole MBB (covered all
flights and hotels)
 Printing and other minor costs from MBB
Funds
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Summer 2008
University Of Sheffield 2008 iGEM Team
Our many thanks go to…
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Prof Philip Wright
Dr Catherine Biggs
Esther Karunakaran
other ChELSI members
Dave Wengraff
Prof David Hornby
Prof Robert Poole
Prof Visakan Kadirkhamanatan
Prof David Rice
Prof Jeff Green
The Bassler, Stafford and Karolinska Institute labs for plasmid
provision.
Summer 2008
University Of Sheffield 2008 iGEM Team
References
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Datsenko & Wanner, 2000, ‘One-step inactivation of chromosomal genes in Escherichia
coli K-12 using PCR products’
Higgins, Bassler et al, 2007, ‘The major Vibrio cholerae autoinducer and its role in
virulence factor production’
Hammer & Bassler, 2007, ‘Regulatory small RNAs circumvent the conventional quorum
sensing pathway in pandemic Vibrio cholerae’
Jun Zhu, Melissa B. Miller, et al, 2001, ‘Quorum-sensing regulators control virulence
gene expression in Vibrio cholerae’
Tomenius, Pernestig et al, 2005, ‘Genetic and functional characterization of the E.coli
BarA-UvrY Two-componant system’
Suzuki et al, 2002, ‘Regulatory Circuitry of thr CsrA/CrsB and BarA/UvrY systems of
E.coli’
Sahu, Acharya et al, 2003, ‘The bacterial adaptive response gene, barA, encodes a
novel conserved histidine kinase regulatory switch for adaptation and modulation of
metabolism in E.coli
Andersen, J.B et al. 1998, ‘New Unstable Variants of Green Fluorescent Protein for
Studies of Transient Gene Expression in Bacteria’
Summer 2008