Overview
In the proof of concept, we designed a closed-loop experimental design and verified it by modules. The experimental results jointly proved the feasibility of the system. In addition, we build a population growth model by measuring the growth rate and other data, predict the effect of the platform in future applications, and prove the effectiveness of the platform. Moreover, we also simulated the use of the hardware ——strain genetic stability monitoring kit we designed, and successfully constructed the engineering bacteria to further ensure the success rate of users.
Module function verification
Our experiment is divided into three parts, connected with each other, which jointly proves the feasibility of the platform. The first is to verify that after the worker becomes a cheater, the killing module can be started (including generating signal factors and mCherry receptors). In the first part of the experimental proof, we verify two mechanisms for users to choose to monitor cheaters. We use GFP instead of the killing system to prove that the killing module can be started after the cheater is generated(Figure 1,2).
Figure 1 Initiation of killing pathway by workers and cheaters with the choice of araC inhibitor pathway
(expression level of GFP with Arac induced by IPTG)
Figure 2 Initiation of killing pathway by workers and cheaters with the choice of mRNA binding pathway
(using GFP as characterization signal,12bp mRNA as example)
In the second part of the experiment, we prove that the cheaters can accept the mCherry signal to commit suicide(Figure 3).Through comparison, we can get that our killing efficiency can reach more than 90%.
Figure 3 Comparison of growth of cheaters with and without mCherry
(No mCherry added on the left, mCherry added on the right)
In the third part of the experiment, we prove that the guard can accept the AIP signal to generate mCherry(Figure 4).
Figure 4 The amount of mCherry produced by guards under the influence of different concentrations of AIP
In addition, we prove that the cheaters can produce AIP by mixing the cheaters' culture medium with the guard(Figure 5). The three parts are connected to complete the verification of the platform function.
Figure 5 Comparison of mCherry produced by guards after adding cheaters' culture medium and pure culture medium
The three parts are connected to complete the verification of the platform function.
Model prediction
Due to the limited time, it is difficult to mix the three types of bacteria. We use modeling to predict the mixed effect and the optimal ratio of guard. By establishing the model, we prove the effectiveness of the platform. At the same time, we are preparing to carry out the experimental verification of the guard's optimal ratio and further optimize our model.
See more about the modelApplication of hardware
In order to facilitate the use of users, we designed a strain genetic stability monitoring kit(Figure 6). In order to ensure the normal use of the kit. According to our protocol, we carried out experimental operation, and finally successfully constructed our engineering bacteria(Figure 7). Through experiments, we summarized our experience and adjusted some details of the protocol, such as the selection of enzyme digestion sites, so as to further facilitate users.
See more about the hardware
Figure 6 The strain genetic stability monitoring kit we design
Figure 7 The picture taken during our using of the kit
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Email：igem_bnu_china2021@163.com
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