Team Accomplishments

CONTRIBUTIONS

We participated in the InterLab study, which helped to reduce the lab-to-lab variability around the world. We also put forward new ideas of the tandem expression of chromoproteins, to get new colors, which would greatly enrich the colors and the BioBrick parts in the Registry. Then using the RGB system[1] which was central to our project, we characterized the Red-, Green-,Blue light sensors (Cph8, YF1, CcaSR) which had already existed in the registry(BBa_K1886006, BBa_K1053210, BBa_K2598005), by exploring the relationship between the fluorescent intensity with the wavelengths and intensity of input light.

INTERLAB

Summary

Interlab is a global collaboration through which the Measurement Committee aim to improve the measurement tools available to both the iGEM community and the synthetic biology community as a whole. This year, the Committee along with teams all over the world aimed to reduce lab-to-lab variability in fluorescence measurements by normalizing to absolute cell count or colony-forming units (CFUs) instead of OD.

Procedure

In order to compute the cell count in samples, two orthogonal approaches were exploited. (detailed protocol was provided in https://2018.igem.org/Measurement/InterLab/Plate_Reader)

Results

Fig 1. Particle standard curve of Silica beads for Abs​600 calibration

Fig 2. Fluorescein standard curve for fluorescence calibration

TANDEM EXPRESSION OF CHROMOPROTEINS

We put forward a new concept—mixing color into bacterial cells. Unlike the mix of different bacterial cells which produce different colors as the previous iGEM teams have done, we used tandem expression and RGB system to control the ratios of the expression of different colors in bacterial cells, to achieve mixing color in bacterial cells, and to produce more colors from limited chromoproteins, which would greatly enrich the colors and the BioBrick parts in the Registry.

Figure 3. The color spectrum built from chromoproteins and their tandem expression products.

CHARACTERIZATION OF SENSORS

We used our RGB system to further characterize the red-, green-, blue-light sensors (BBa_K1886006, BBa_K1053210, BBa_K2598005), which had already existed in the registry, because the expression of red-, green-, blue-fluorescent proteins would change according to the excitation degrees of red-, green, blue-sensors. (More information, please see LIGHT TO COLOR)

Figure 4. The flow cytometry results shows the distribution of the cells in fluorescence intensity. BV421 represented the blue-fluorescence intensity, while the FITC-A represented the green-fluorescence intensity and Pe-TxR-A represented the red-fluorescence intensity. The horizontal axis shew the fluorescence intensity, while the vertical axis shew the number of bacteria cells.

Figure 5. The spectral response of the RGB system.

We firstly use flow cytometry[2] to measure the spectral response of the RGB system. From the figure 4 we could see the distribution of the cells in fluorescence intensity. BV421 represented the blue-fluorescence intensity, while the FITC-A represented the green-fluorescence intensity and Pe-TxR-A represented the red-fluorescence intensity. The horizontal axis shew the fluorescence intensity, while the vertical axis shew the number of bacteria cells. The figure demonstrated the variation of fluorescence intensity where cells were most concentrated with the wavelengths of light. And the figure 5 shew the relationship between total fluorescence intensity with the wavelengths of input light.

Figure 6. The curves show the relationship between the input light and fluorescent intensity.

We then controlled the intensity of the input light to see the change of the fluorescent intensity over time. The figure 6 demonstrated that the stronger the input light was, the less fluorescence would be. The phenomenon was probably because that under relatively low light, the light sensor could be induced and under relatively strong light, the light can aggravate the burden of the bacteria and thus harmed the growth of the bacteria and reduced the expression of fluorescent proteins. We modelled this result for further explanation.(For more information, please see MODEL)

References

[1]Fernandez-Rodriguez J, Moser F, Song M, et al. Engineering RGB color vision into Escherichia coli[J]. Nature Chemical Biology, 2017, 13(7):706-708.

[2]Davey H M, Kell D B. Flow cytometry and cell sorting of heterogeneous microbial populations: the importance of single-cell analyses[J]. Microbiol Rev, 1996, 60(4):641-696.