Team:SDU CHINA/Model
We modelled how the concentration of CcdB changes over time. In the figure below, we used k_i to refer to the rate of the reaction i and [A] to refer to the concentration of the material A.After experimental verification, we found that the light intensity had little effect on the reaction process, so we did not take it into consideration when modelling.
First, we built a dynamics model for the light control part. With the assumption that the rate of OmpR1 reaction generation was constant, we established an ordinary differential equation.
Similarly, we established another ordinary differential equation for the above formulas and solved it.
We found that this equation was a model similar to the natural growth of EsaI. Then we used this model to try to fit the experimental results of the first generation hardware, only to find that the deviation was large, and the graph did not match the expected model. After analyzing the reasons, we realized that the reason was that the light width used by the first generation hardware was too large, causing the leakage of the optocouplers. Therefore, after the exchange with UCAS_CHINA, we decided to use the monochromatic light with only one wavelength, which ensured the smooth progress of the later experiments.
Then, after looking up the literature, we learned that the production of the Esal proteins was constitutively expressed. That meant that ignoring the reactions during its growth and the time that 3OC6HSL spent in entering and exiting the cell membrane, the concentration of 3OC6HSL changed linearly with time.
Besides, the production of Trah was also constitutively expressed. We could get the production rate of C6 Complex by combing the production of Trah and 3OC6HSL.
Based on the production of C6 Complex, according to the following equation, we can get the way CedB changes with time.
Reference
[1] T. Danino, O. Mondragón-Palomino, L. Tsimring, J. Hasty, A synchronized quorum of genetic clocks. Nature 463, 326–330 (2010). doi:10.1038/nature08753 pmid:20090747
[2] A. Prindle, J. Selimkhanov, H. Li, I. Razinkov, L. S. Tsimring, J. Hasty, Rapid and tunable post-translational coupling of genetic circuits. Nature 508, 387–391 (2014). doi:10.1038/nature13238 pmid:24717442
[3] K. Brenner, D. K. Karig, R. Weiss, F. H. Arnold, Engineered bidirectional communication mediates a consensus in a microbial biofilm consortium. Proc. Natl. Acad. Sci. U.S.A. 104, 17300–17304 (2007). doi:10.1073/pnas.0704256104 pmid:17959781
[4] https://2018.igem.org/Team:UCAS-China/Model