Team:JiangnanU China/Description

JiangNan

For us human, , we get vaccinated in order to avoid being infected by virus. So, we thought about introducing a protein gene into the Escherichia coli BL21, enabling it to protect itself from the phage attack.
If we can successfully construct this gene circuit and make it work, we can greatly reduce the possibility of Escherichia coli BL21 being killed during the experiment as well as help the factories to save money and time. To conclude, we build this gene circuit to reduce the mortality of Escherichia coli BL21 to help the biological researchers and factories.
What is The Main Problem?

As phages have a high rate of mutant and a high degree of specificity, it is hard to protect the Escherichia coli BL21 from all kinds of phage attack. So, we can only choose T4 phages which killed our bacteria before and reduce its impact on the Escherichia coli BL21 . Besides, there is not so much literature focusing on the anti-phage mechanism of Escherichia coli BL21. We try to protect the Escherichia coli BL21 from the gene level. And luckily, according to the reference, we have found abpA and abpB, which are both anti-phage genes that can show resistance to the attack from the T4 phages.
What Do We Do?

We connect anti-protein with an inducible promoter putA. For fear that the anti-protein could not work successfully, we connect kill switch with the inducible promoter glcF, to avoid the replication and release of phages. Before that, we have proved that the inducible promoter putA and glcF can work efficiently by using report gene gfp and rfp. According to the reference, we have found anti-phage gene abpA and abpB, but they didn’t work well. We introduced phages into the medium and let them attack phages. Finally , we found six anti-phage genes according to its mutant sites and connect gntR with abpA and abpB. To our surprise, the gene circuit shows great resistance to the phage attack. Meanwhile, as the stakeholders adviced, our strain should grow as robust as the original strain or it could not be applied under current fermentation condition, so we applied an Gray Relation Analysis model with EWM weights and weights advised by experts, to analyse the correlation of growth curve between our strains and original strain in order to select the most suitable strain. Besides, due to the potential problems such as the promoter leakage and inclusion body ,we developed a quantitative design method for phage-induced promoters based on strength prediction using artificial neural network, which allows us to choose or design promoter with desired strength in our circuit without extra experiments.
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