Team:OUC-China
To visualize the process in fermentation tank by the dynamic simulation. Because of the time, our project did not go to the last step to test the complete circuit, so we wanted to utilize the idea of the cellular automaton to perform a dynamic simulation of our project and visualize it. As there are three situations that can cause engineering bacteria die, the first is a decrease in the copy number of the plasmid, the engineering bacteria die as they cannot synthesize enough PFK to support their growth. Secondly, some intracellular reactions leading to reduced production, engineering bacteria die due to YopE protein. Finally, it may be due to problems with the RNA transport delivery, resulting in a sudden decrease in intracellular products, so that YopE protein expressed to cause them die. Therefore we utilize a judge matrix to describe. For Pij describes the possibilities of the survive or death of engineering bacteria. If j = 1, it stands for that the bacteria can survive otherwise it die. Pro stands for the production of the bacteria in each unit of time. Whatever the kind of the plasmid, the engineering bacteria will die after 8 times division. For ordinary engineering bacteria, the judge matrix is also added, but there are only two cases, one is the mutations, resulting in no yield, the second is that there is a problem in the engineering bacteria, resulting in reduced production. First of all, engineering bacteria, wild bacteria and dead bacteria are needed to be defined. In view of that it can ensure that there is no bacterial contamination in the fermentation tank, when engineering bacteria mutate into wild bacteria, it cannot have the production which is useless,。Therefore, it is only necessary to demonstrate the engineered bacteria and their yields in the animation. What’s more, the number of engineered bacteria will not increase significantly during the initial period of fermentation and also there will be no high yield. Therefore in the visualization process, the initial period is omitted and only the exponential, stable and decay periods are presented. In view of that if the number of engineering bacteria is too large, it will cause the demonstration results to be unintuitive in the presentation, so the maximum number of engineering bacteria is set to 100 during the demonstration(fig 1A-B). Changing the maximum number of engineering bacteria to 1000, simulating for 100 units of time and collecting the yield of each group of engineering bacteria to analyze(fig2). It is found that the output of engineering bacteria carrying CHIP is significantly higher than the ordinary engineering bacteria under the same fermentation conditions, which can characterize that the function of CHIP components to a certain extent. According to the literature[1], the experiment is tested by liposome, not cell membrane which does not have the membrane protein on it. It is not quite sure that this element can be used on the cell membrane. Therefore, we built another system that simulated engineering bacteria that carry CHIP elements but don't have RNA transports(fig3). Record the yield and analyze it with the previous two groups(fig4). Record the yield and analyze it with the previous two groups(fig4). From fig4, it is shown despite the absence of RNA transport, the yield of engineering bacteria with CHIP is also significantly higher than the ordinary engineered bacteria. What’s more, it can be clearly found that the highest point of CHIP element production is basically the same as that of CHIP element without RNA transport, which can prove that the advantages of CHIP element have a lot to do with RNA transport to some extent. Because RNA transport can transport the product out of the cell, it can reduce the pressure on engineered bacteria and extract the product without breaking the cell. Comparing fig5(A-E), it can be seen that when the fermentation tank is large enough, the production of engineered bacteria carrying CHIP will be much higher than that of ordinary engineered bacteria. Even if CHIP does not have RNA transport, its expression yield will be higher than that of ordinary engineered bacteria. It is concluded that larger the scale of fermentation, the more obvious advantages of CHIP components(fig6).
This is enough to prove the superiority of the system, which is a fermentation platform with excellent performance. Due to the epidemic situation, our partner NJU-China did not have enough time to to detect the performance of RNA transport utilizing exosome. We believe that we can enrich our wikis and parts after verifying the performance of RNA transport after the competition, which will inspire the following iGEM teams to flexibly apply RNA in different aspects.
Cellular automata
In this process, we simulated two groups, which are the expression of engineering bacteria carrying CHIP elements and ordinary engineering bacteria in a fermentation cycle, the colors of different ‘bacteria’ in the demonstration animation represent the yield of engineering bacteria.
Given that the environment that CHIP facing in the future is the fermentation tank which is required for industrial production. Therefore the effect of different fermentation level on the expression of CHIP needs to be simulated. Changing the upper limit of engineering bacteria in different fermentation tanks(fig5 A-E).
