1. M.I.T, Nov 7 th -9 th 2008 International Genetically Engineered Machines Competition An introduction to the University of Sheffield 2008 iGEM Team…

2. 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’

3. Summer 2008 University Of Sheffield 2008 iGEM Team Who are we? Gosia Poczopko 1 st year Molecular and Cellular Biochemist Eva Barkauskaite 1 st year Biochemist Rosie Bavage 1 st year Molecular Biologist Dmitry Malyshev 1 st year Biomedical Engineer Hammad Karim 2nd year Engineer Sam Awotunde 2nd year Engineer

4. 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

5. 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

6. 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

7. Summer 2008 University Of Sheffield 2008 iGEM Team Fusion Receptor  Sequences to be fused were found through multisequene allignment and comparison with similar proteins

8. Summer 2008 University Of Sheffield 2008 iGEM Team Fusion Receptor  Pathways regulated via BarA are well characterised

9. 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

10. 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

11. Summer 2008 University Of Sheffield 2008 iGEM Team Gene Knockout

12. 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

13. 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

14. 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

15. 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

16. What has been done? DH5-alpha transformed with an uncharacterized GFP-LVA BioBrick Used Tecan®, with fluorescence measurements every 15 minutes for 8 hours

17. 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

18. 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.

19. 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

20. 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

21. 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.

22. BarA~p BarA R1R2 Uvry~p Uvry R3 R4 DNAf Uvry.DNA Sensor kinaseResponse regulator Phosphoryl transfer dephosphorylation DNA binding A Two-component Signal Transduction System

23. 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

24. 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.

25. Differential Equations

26. Phosphorylation Rate of BarA

27. Phosphorylation Rate of UvrY

28. Rate of GFP Gene Expression

29. Parameter Values In vitro parameters K1 = o.oo29 1/h µM DNA ₀ = 100µM k_1= 0.00088 1/hµM BarA ₀ = 1µM K2= 108 1/hµM Uvry ₀ = 4µM K_2= 1080 1/hµM ATP = 100µM Kь = 5400 1/hµM ADP = 8µM K_ь = 360 1/h K3= 90 1/hµM

30. 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.

31. 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, –

32. 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 :

33. 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 :

34. Engineering - The Probabilistic approach Summer 2008 University Of Sheffield 2008 iGEM Team Probability curves of contact between molecules

35. 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

36. 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.

37. 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’