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.

Figure 1. Sterilization sequence.

Gene Construct of DenTeeth

We incorporate the whole part into E. coli BL21(DE3). We did colony PCR and digest to check its genotype.

Figure 2. Quorum sensing sequence + Restoration sequence + Sterilization sequence. M :1kb DNA ladder, 1 : Constitutive promoter + RBS + LuxR + Term. +Term. + Ptet + RBS + BMP2 + RBS + STATH + RBS + GFP + Term. + Term. + Plux + RBS + LL-37 + RBS + mRFP + RBS + tetR + Term. + Term. (4685 b.p.)</i>

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.

Figure 3. The simulated expression curve of mRFP

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.

Figure 4. The growth curve of E. coli and P. gingivalis

Figure 5. The growth curve of E. coli and P. gingivalis

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.

Table 1. Parameters of the sterilization system of LL37

Feeding Frequency Validation

Figure 6. A is the control group, and B is the experiment group

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.

Figure 7. The Validation of Efficiency Optimization Model

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.

Figure 8. The comparison of Reward from Policy 1 and Policy 2

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.

Figure 9. DenTeeth inhibition zone result in LB plates. ( The materials added in plate were in the following condition, and each total volume is 20μL. (A) 30% hydrogen peroxide, (B) E. coli (BL21) with pSB1K3, (C) DenTeeth, (D) E. coli (BL21) with pSB1K3 (Cell Lysate), (E) DenTeeth (Cell Lysate), (F) PBS, (G) E. coli (BL21) with pSB1K3 + PBS, (H) DenTeeth + PBS, (I) LB broth (Centrifuging E. coli (BL21) with pSB1K3 after liquid culturing ), (J) LB broth (Centrifuging E. coli (BL21) with pSB1K3 after liquid culturing ) )

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.

Figure 10. The Bar Chart of DenTeeth inhibition Functional Test.

Sequence and Features

Assembly Compatibility: