m.i.t, nov 7 th -9 th 2008 international genetically engineered machines competition an introduction...
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M.I.T, Nov 7th-9th 2008
International Genetically Engineered Machines
Competition
An introduction to the University of Sheffield 2008 iGEM Team…
Summer 2008
University Of Sheffield 2008 iGEM Team
What is iGEM? iGEM is a rapidly increasing international
competition for undergraduates in many different specialisations– 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– 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 downstreamProof of principle in fusion kinase
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 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 Sequences to be fused were found through multisequene
allignment and comparison with similar proteins
Summer 2008
University Of Sheffield 2008 iGEM Team
Fusion Receptor 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
Summer 2008
University Of Sheffield 2008 iGEM Team
Gene KnockoutTo 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
Summer 2008
University Of Sheffield 2008 iGEM Team
Gene Knockout
Problems
We couldn’t get a knockout– 5 repeats, with varied condition
Various setbacks and little time– Ampicillin
Summer 2008
University Of Sheffield 2008 iGEM Team
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 usedMass-spec to confirm been difficult to
obtain
Summer 2008
University Of Sheffield 2008 iGEM Team
Further ideas
Re-usuable sensor– Cleavable GFP/ housekeeping gene regulation –
LVA tag. – Provided by past iGEM project = criteria for an
award
Threshold experiments – Modelled
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
What has been done?DH5-alpha transformed with an
uncharacterized GFP-LVA BioBrickUsed Tecan® , with fluorescence
measurements every 15 minutes for 8 hours
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
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.
Heath and Safety
Vibrio cholerae impossible to work onCAI-1s non-toxic themselvesRepress Cholerae biofilm formation in
natureCqsA only produces CAI-1sSafe
Acheive: Bronze Award
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
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: • The signal transduction• The gene expression.
BarA~p
BarA
R1 R2
Uvry~p
Uvry
R3
R4
DNAf
Uvry.DNASensor kinase
Response regulator
Phosphory
l transfer dephosphorylation
DNA binding
A Two-component Signal Transduction System
The Chemical Reactions• Auto-phosphorylation:ATP + BarA ↔ ADP + BarA~p --Reaction 1• Phosphoryl group transfer :BarA~p + UvrY ↔ BarA + UvrY~p - Reaction 2• Dephosphorylation : UvrY~p + BarA → UvrY + BarA (+ pi) -
Reaction 3• DNA binding :2 UvrY~p + DNAƒ ↔ (UvrY – DNA)----Reaction
4
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• 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.
Summer 2008
University Of Sheffield 2008 iGEM Team
Engineering – Hammad’s Probabilistic approach
For simplicity, whole reaction is split into two parts:– CAI-1 interacting with Fusion Kinase– From response regulatory protein to GFP glow.
Mathematically,–
Summer 2008
University Of Sheffield 2008 iGEM Team
Engineering – Hammad’s Probabilistic approach
Considering this as Poisson Process:– The General form of probability is then given as:
– 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
Summer 2008
University Of Sheffield 2008 iGEM Team
Engineering - The Probabilistic approach
Implementation:• As there are some other processes occurring at the same
time (like noise disturbance and various reactions) using Gaussian mixture models :
Engineering - The Probabilistic approach
Summer 2008
University Of Sheffield 2008 iGEM Team
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
Summer 2008
University Of Sheffield 2008 iGEM Team
Our many thanks go to… 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 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’