RBS test of B0032 (BBa_K4814002), Strong (BBa_K4814013), and B0034 (BBa_K4814015)

After our first improved (For more details, refer to Engineering page) dosage dependent experiment of RecA(K3)-B0034-eGFP and RecA(K6)-B0034-eGFP, we plotted out the changes of the SFU (significant fluorescent unit, fl over OD600) of K3 in several time points: 1, 2, 3, 6, and 24 hours after the treatment.

As can be seen from the graphs, the level of SFU rises considerably with a upward trend when the dosage increases at the third hour (red points), which also confirms the data collecting time (2-3 hours after treatment) stated by team BIT 2019.

Figure 1. The three-dimensional (time, concentration/ intensity, SFU) graph of K3 treated with UVB and H2O2.

The results collected at the third hour indicates that K3 has a more significant performance concerning reoprting DNA damages.

Figure 2. The fluorescence of RecA(K3)-eGFP, RecA(K6)-eGFP with different intensity of UVB and concentrations of H2O2. Data is collected three hours after the treatment.
Figure 3. The fluorescence of RecA(K3)-eGFP, RecA(K6)-eGFP with different concentrations of Aspartame and Nalidixic acid. Data is collected three hours after the treatment.

We calculated the standard error (SE), with n=3.

Confirming the excellence of K3 reporter, we aimed to further improve the reporter by replacing RBS B0034 (our original design) with RBS B0032 and new RBS strong.

Strong (https://pubs.acs.org/doi/10.1021/acssynbio.2c00015)

To attempt to improve the RecA (K3) - B0034 - EGFP bioreporter (BBa_K4814015), we replaced the RBS with B0032 and a new RBS invented by Zhang, M. et al (2022). The researchers developed a machine learning model to predict the translation initiation rate of different RBS sequences. Then, the designed sequences were synthesized and experimentally tested for their translation initiation rates.

Sequence: TTTAAGAGGGGGCTATACAT

The following charts are the SFU (significant fluorescence units. fl over OD600) of DNA damage reporter with different RBS (Strong BBa_K4814013, B0032 BBa_K4814002, and B0034 BBa_K4814015). The RecA-eGFP design with B0034 RBS is the original design (K3). We replaced B0034 with B0032 and a new RBS generated by machine learning results by Zhang, M. et al (2022). This experiment aims to select the best design by comparing the fluorescence over OD600 when exposed to genotoxic agents (UV, H2O2, Aspartame, and Nalidixic acid).

Figure 4. The graphs of different RBS designs treated with UV, H2O2, Aspartame, and Nalidixic acid.

We calculated the Standard Error (SE) with n = 3:

where σ is the standard deviation, and n is the number of trials.

Overall, the SFU of all designs has an upward trend in UV and H2O2 groups. The results illustrate that while in both UV and H2O2 groups, the SFU of B0032 (BBa_K4814002) is three times of B0034 (BBa_K4814015), the Strong (BBa_K4814013) is only half of B0034.

However, when it comes to Aspartame, the SFU of all engineered bacteria decreases when the concentration of Aspartame increases. On the other hand, the SFU of Strong and B0034 rises from 0 to 10 ug/ml of Nalidixic acid, followed by a steep drop between 10 and 100.

References

Zhang, M., Holowko, M. B., Zumpe, H. H., & Ong, C. S. (2022). Machine Learning Guided Batched Design of a Bacterial Ribosome Binding Site. ACS Synthetic Biology, 11(7), 2314-2326. https://doi.org/10.1021/acssynbio.2c00015

https://parts.igem.org/Part:BBa_B0032 https://parts.igem.org/Part:BBa_K3020000