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From 2011.igem.org

Collaboration

The Imperial College London team collaborated with Wits CSIR iGEM team. Aspects that were similar in both projects included rewiring of the chemotaxis E. coli, however the design was different for both projects. WE have tried to rewire chemotaxis of E. coli using structurally similar chemoreceptors that then use endogenous molecular mechanism of chemotaxis, whereas WITS - CSIR team used novel concept of riboswitches to modify the functioning of the chemotaxis pathway in E. coli. Collaboration was performed in both wetlab and modeling aspects.

Wet Lab collaboration

Chemotaxis assays are complex number

I. MODELLING RESULTS

Regarding to modeling, the modeling team from Imperial College London had several skype meetings with Witz CSIR iGEM team to discus the design of chemotaxis modeling, and theories behind our models. In order to share our modeling ideas and exhchange some of our models, we modeled the chemotaxis pathway for Witz CSIR for team. The modeling results were shown in the results session below.

I. MODELLING RESULTS

Witz CSIR iGEM intend to use ribostwith to reprogram the chemotactic behavior of E.coli. The project includes engineering the attraction of the bacteria to theophylline[1]. CheZ is an important protein controlling the chemotaxis of bacteria. They used a theophylline riboswitch to control the expression of CheZ in CheZ mutants in order to engineer the bacteria's movement towards theophylline[1]. We're using a riboswitch sensitive to theophylline to control the expression of CheZ. In the absence of theophylline, the start codon is covered so the translation of the strand cannot occur. In the presence of theophylline, the shape of the aptamer (riboswitch) changes and the start codon is exposed[1].Thus, the higher the concentration of the theophylline, the more will enter the cell and the higher the expression of CheZ and the higher the level of directed movement[1].

The theophylline riboswithch can be modeled in three differential equations (Equation 1). [2]

M, CheZ and T respectively stands for the concentration of CheZ mRNA, the concentration of protein CheZ and the concentration of theophylline. The constants α,β,γ,ξ and δ are all positive, and respectively denote the CheZ-promoter transcription rate, the CheZ-mRNA translation rate and the mRNA, CheZ and theophylline degradation-plus-dilution-rates. ζ(Text) is the theophylline transport rate per unit CheZ concentration. It is a function of number of theophylline receptors and external theophylline concentration. The function ϕ(T) and Θ(T) denote the theophylline-governed regulation ay the transcriptional and translation levels respectively (equation below [2]). KΦ is the equilibrium constant at transcriptional level and KΘ is the equilibrium constant at translation level.

Varying the parameter ζ(Text) of above model could help us to understand how the number of receptors and external theophylline concentration effect the intracellular concentration of theothyline and hence the expression level of CheZ. The results are shown in Fig.1(a) and Fig.1(b) below. In addition, the response curve of CheZ against theophylline concentration with different theophylline transport rate was illustrated in Fig.1(c).

Fig.1(a) Expression of CheZ VS time

Fig.1(b) Intracellular Theophyline concentration VS time

Fig.1(c) Response curve of CheZ concentration VS intracellular concentration

Both the expression of CheZ and intracellular concentration increases with increase of transport rate. The bacteria will produce more CheZ and therefore higher level of directed movement. The CheZ response curve shown that the transport rate can be used to tune CheZ response, the threshold intracellular concentration of theophylline required to trigger CheZ response increases with transport rate.

II. PARAMETERS

III. REFERENCE

[1] S. Topp , Justin P. Gallivan (2007) ‘Guiding bacteria with small molecules and RNA’, J. AM. CHEM. SOC. 2007, 129,6807-6811. VOL. 129, NO. 21,2007

[2] M. Santillan , M. C. Mackey (2005)’Dynamic behavior of the B12 riboswitch’ Phys. Biol 2(2005) 29-35. Doi: 10.1088/1478-3967/2/1/004

[3] Beisel CL, Smolke CD (2009) ‘Design Principles for Riboswitch Function.’ PLoS Comput Biol 5(4): e1000363. doi:10.1371/journal.pcbi.1000363 Parameters: