Team:USTC/Collaborations
Collaborations
Work together, cheer together
Leaders
The Background of Collaboration
It was in the NCKU IGEM Conference that we met BIT team. At first, we were just interested in the project they worked hard for. They built two separate circuits to produce two kinds of integrase. The integrase Bxb1 and FimE are seemed like two keys to open the “lock” which is referred to the terminators. Furthermore, their functions are series-wound. It was a coincidence that we have studied the modeling part of ETH:Zurich 2014 IGEM Team in the survey and investigate at the beginning of our modeling assignment. In the past studying, we had learned a lot of techniques of modeling from theirs and we were convinced that the project of BIT are very similar with that of ETH:Zurich 2014 IGEM Team. As we thought that we had known about some parts intheir ciucuits before, we proposed that we would like to assume some of their modeling work. And they accepted, also expressing that they would like to help our USTC Team with our device.
Figure 1：The Circuits of 2016 BIT IGEM Team’s Project
Method
In the modeling for BIT, as the two circuits are nearly the same, we choose one of these two circuits to model. We applied mass-action law to the whole biology process, and acquired several differential equations. We used MATLAB R2014a to solve these equations and we got the relationship between the rate of flipping the terminator from on state to another and the GFP final concentration.
Figure 2：The Relationship of kt and The Concentration of GFP
Also, we got the relationship between the Kmlac and the Proportion of terminators turned off.
Figure 3：The relationship between Kmlac and the proportion of terminator turned off
To show aintuitionistic relationship between the the regulateability of Lac and Bxb1, we gave out a a holistic view of relationship of [GFP] and Kmlac.
Figure 4：The Relationship between Kmlac and kt and The Final Concentration of GFP
Asymmetric Conditions
We build the regulating circuits of FimE in the same way, but it is a pity that it is hardly to find any references about the parameters of the chemical kinetics constant of FimE, so we just assumed that 𝑘𝑇2=1e5, and vary 𝑘𝑇1. So the system is not symmetric any more. Then we find that the tendency of change of [GFP] is almost the same as the case in which 𝑘 and 𝑘𝑇2 remain the same and change together.
Figure 5：The Relationship between GFP and 𝑘𝑇1 in the first condition
Here, we fix 𝑘𝑇1𝑘𝑇2=1e7, and vary both of them. So the system is not symmetric any more. Then we find that the GFP output changes with 𝑘𝑇1 in the way of the previous figure. We can conclude that in the symmetric condition we can get the maximal GFP output.
Figure 6：The Relationship between GFP and 𝑘𝑇1 in the second condition
Summary of Modeling
We not only finished modeling for our own project, but also assisted BIT with their modeling task. We give a complete description of their gene circuits. We tried to change the value of the undetermined parameters to get the trend of the variation of GFP under these conditions. The effect of varying a single is almost identical to the result in the case that km(lac) and km(tet) varies together. However, unlike 𝑘𝑇1, km has a smaller effect on the final output of GFP. As shown in the left figure, when km(lac) increases for 100 folds, the GFP output remain at the same order of magnitude.
The Feedback of BIT 2016 IGEM Team
"Our team (BIT team) attended in IGEM meeting held by University of Science and Technology of China in September 2016, and we had a meaningful communication with students of University of Science and Technology of China after meeting. We appreciated that the students of University of Science and Technology of China have assisted us to solve a problem in improving model. Not only because part of modeling in project not be able to continue if problem does not resolve, but we also obtained a new idea about modeling. Meanwhile, we sincerely hope that your team can get good resuts in IGEM contest."
References
[1] https://2014.igem.org/Team:ETH_Zurich
[2] Liang S. T., Ehrenberg M., Dennis P., Bremer H.,Decay of rplN and lacZ mRNA in Escherichia coli, Journal of molecular biology, 1999
[3] Basu S., Gerchman Y., Collins C.H., Arnold F.H., Weiss R., A synthetic multicellular system for programmed pattern formation, Nature, 2005
In this year, our IGEM team is in the need of a method to caculate the intensity of the green fluorescence produced by our device quantitatively. As it is convenient to communicate with the team in the same university as us, we consulted from USTC Software Team and applied their method to our data.
They provided us the code in Matlab and also explanation. We acquire the value of the intesity of green fluorescence in several steps: first, we reverse the contour figure, then, after we select only the bright part of the figure, we are able to caculate the average brightness of the illuinating area.
Figure 1. The Original Photo
Figure 2. Reverse the contour figure
Figure 3. Select only bright part of the figure and omit other parts
They helped us to convert the colours into the values that can compare with one another. We figured out "The concentration of GFP - The temperature of heat shock standard curve", so that we can predict the intensity of green fluorescence after giving a heat shock at a specific temperature for a period of time. Our caculated results are consistent with the observed results well. Thanks to the USTC Software Team, we gained the satisfying results and came to the final conclusion we expected.
