Difference between revisions of "Part:BBa K3736002"
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   We inserted mRFP into our biobrick to detect the expression of the sterilization sequence in DenTeeth. The following graph was the simulated expression curve of mRFP. |    We inserted mRFP into our biobrick to detect the expression of the sterilization sequence in DenTeeth. The following graph was the simulated expression curve of mRFP. | ||
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+ |   we considered the expression of RFP and fit the model with experimental data as before. We found that the environment of the Erlenmeyer Flask was different from the paper. The degradation of RFP was lower than expected. Thus, we lowered the degradation rate and verified it with the experimental results again. The following picture is the result. | ||
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[[File:T--NCTU Formosa--mRFP prediction.png|500px|thumb|center|'''Figure 3. The simulated expression curve of mRFP | [[File:T--NCTU Formosa--mRFP prediction.png|500px|thumb|center|'''Figure 3. The simulated expression curve of mRFP |
Revision as of 23:33, 21 October 2021
Plux promoter + RBS + LL37 + RBS + mRFP + RBS + Terminator*2
Plux promoter + RBS + LL-37 + RBS + mRFP + RBS + Terminator*2
Sterilization sequence in DenTeeth
Inhibition is the key to periodontal disease. In wet lab, we first expect the LL-37 could attain the mission. To observe the expression of DenTeeth’s biobrick, the RFP would be inserted behind the LL37. Because DenTeeth would be killed by LL-37 peptide, we added a composite part in the front of the LL-37 producing sequence, preventing engineered bacteria died before entering the mouth.
As stated before, LL-37 can inhibit E. coli. If the DenTeeth could not exist with LL-37 in a proper proportion, the DenTeeth wouldn't attain the mission of solving the periodontal disease. Therefore, we decided to use the prediction model to predict whether DenTeeth could grow and express under the effect of LL-37. To confirm the feasibility of DenTeeth.
Gene Construct of DenTeeth
We incorporate the whole part into E. coli BL21(DE3). We did colony PCR and digest to check its genotype.
mRFP Model
We inserted mRFP into our biobrick to detect the expression of the sterilization sequence in DenTeeth. The following graph was the simulated expression curve of mRFP.
we considered the expression of RFP and fit the model with experimental data as before. We found that the environment of the Erlenmeyer Flask was different from the paper. The degradation of RFP was lower than expected. Thus, we lowered the degradation rate and verified it with the experimental results again. The following picture is the result.
LL-37 Model
Through the modeling built with substituting parameters from published articles, the growth of E. coli and P. gingivalis under the effect of LL-37 would be inhibited significantly. However, the figure also shows that E. coli could still live with LL-37. Simply speaking, we successfully test the feasibility of DenTeeth and find that we can improve the DenTeeth with both biobrick design and efficiency optimization model.
Because P. gingivalis was in the RG2, so we could not do the LL-37 functional test by inhibiting the growth of P. gingivalis. After reading some related papers, we found that the killing rate of E. coli was similar to that of P. gingivalis [4]. Based on these data, we determined to make E. coli, DH5α with pET32A, as the bacteria killed by DenTeeth in the LL-37 functional test.
Feeding Frequency Validation
In order to validate the efficiency optimization model usable in any environment, we use E. coli with pSB1K3, hydrogen peroxide, and glucose to simulate as P. gingivalis, feeding dental bones and eating foods. As a result of the different environments of the experiment and the dog's mouse. We modified the environment reaction function to meet requirements.
The above figure shows that the prediction value is very close to the experimental data, and the prediction is very accurate and precise by observing the R-square and RMSE.
After validating the accuracy and precision of the model, we further compare the reward of two dental bone feeding policies. Policy 1 (control group) is feeding dental bone with a fixed time interval. Policy 2 (experimental group) is feeding dental bone with RL prediction results.
Through calculating the reward of policy 1 and policy 2 by reward function, we can claim the reward of policy 2 is statistically higher than policy 1. Simply speaking, through the validation experiment, we successfully proved the optimization ability of this model.
Functional Test
After finishing the design of DenTeeth, we wanted to know whether its inhibition ability can have a function, so we designed the following experiment.
By taking the method of dish culture and sticking up the filter paper, we dropped the DenTeeth on the filter paper in the center of the E. coli, DH5α with pET32a, plate. After twelve hours, a circular area around the spot of the DenTeeth formed, in which the bacteria colonies did not grow. Inhibition zone proved that the LL-37 produced by DenTeeth could successfully secrete out and inhibit the growth of E. coli, DH5α with pET32a.
Finally, we chose antimicrobial peptides, LL-37 play the part of bacteria-inhibition. Human cathelicidin-derived LL-37 is a 37-residue cationic, amphipathic α-helical peptide. It is an active component of mammalian innate immunity. LL-37 not only can inhibit P. gingivalis but can also inhibit Escherichia coli itself, preventing DenTeeth from overgrowing after entering the canine mouth.
Sequence and Features
- 10COMPATIBLE WITH RFC[10]
- 12COMPATIBLE WITH RFC[12]
- 21COMPATIBLE WITH RFC[21]
- 23COMPATIBLE WITH RFC[23]
- 25INCOMPATIBLE WITH RFC[25]Illegal NgoMIV site found at 1650
Illegal NgoMIV site found at 1771
Illegal AgeI site found at 778
Illegal AgeI site found at 890 - 1000COMPATIBLE WITH RFC[1000]