Difference between revisions of "Part:BBa K3431036"

Characterization using invertase

The 2020 iGEM CSMU-Taiwan characterized the toehold switch with invertase (BBa_K3431000) reporter protein. The plasmid would be transcribed and translated with the protein synthesis kit at 37℃ for 2 hours. We would then add 5μl of 0.5M sucrose and measured the glucose concentration with RightestTM GS550 glucose meter after 30 minutes. In our experiments, the ON state refers to the conditions with miRNA triggers; while the OFF state means that there was no miRNA in the environment. We calculated the ON/OFF ratio of the toehold switch, which is defined as “the glucose concentration of the ON state/ the glucose concentration of the OFF state”.

Figure. 3. The glucose productions of the zz146_B toehold switch-regulated invertase in different states. The blue bar refers to the OFF state (not added with miRNA). The green bar refers to the ON state (added with miR-146 trigger). The yellow bar refers to the state with non-related RNAs (added with miR-191). The pink bar refers to the state with non-related RNAs (added with miR-223).

Results
The glucose concentration in the ON state with miR-146 is about 20 mg/dL, indicating the sensitivity of the toehold switch is quite low. The ON/OFF ratio with miR-146 is 2.44, which suggested the regulatory function of the toehold switch. By contrast, the ON/OFF ratios with miR-191 and miR-223 are 1.56 and 1.89, respectively. These ratios are close to 1, meaning the zz146_B toehold switch has high specificity. As a result, zz146_B_ToeholdSwitch-Regulated Invertase has been proven to be useful for miR-146 detection.

References

1. Green, A. A., Silver, P. A., Collins, J. J., & Yin, P. (2014). Toehold switches: de-novo-designed regulators of gene expression. Cell, 159(4), 925–939. https://doi.org/10.1016/j.cell.2014.10.002

2. Green, A. A., Kim, J., Ma, D., Silver, P. A., Collins, J. J., & Yin, P. (2017). Complex cellular logic computation using ribocomputing devices. Nature, 548(7665), 117–121. https://doi.org/10.1038/nature23271

3. Pardee, K., Green, A. A., Takahashi, M. K., Braff, D., Lambert, G., Lee, J. W., Ferrante, T., Ma, D., Donghia, N., Fan, M., Daringer, N. M., Bosch, I., Dudley, D. M., O'Connor, D. H., Gehrke, L., & Collins, J. J. (2016). Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components. Cell, 165(5), 1255–1266. https://doi.org/10.1016/j.cell.2016.04.059

4. Chappell, J., Westbrook, A., Verosloff, M., & Lucks, J. B. (2017). Computational design of small transcription activating RNAs for versatile and dynamic gene regulation. Nature communications, 8(1), 1051. https://doi.org/10.1038/s41467-017-01082-6

5. Sadat Mousavi, P., Smith, S. J., Chen, J. B., Karlikow, M., Tinafar, A., Robinson, C., Liu, W., Ma, D., Green, A. A., Kelley, S. O., & Pardee, K. (2020). A multiplexed, electrochemical interface for gene-circuit-based sensors. Nature chemistry, 12(1), 48–55. https://doi.org/10.1038/s41557-019-0366-y

6. Hong, F., Ma, D., Wu, K., Mina, L. A., Luiten, R. C., Liu, Y., Yan, H., & Green, A. A. (2020). Precise and Programmable Detection of Mutations Using Ultraspecific Riboregulators. Cell, 180(5), 1018–1032.e16. https://doi.org/10.1016/j.cell.2020.02.011

7. Pardee K, Green AA, Takahashi MK, et al. Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components. Cell 2016; 165(5): 1255-66.

Information contributed by City of London UK (2021)

This toehold switch was characterized in silico using the ToeholdTools project that our team developed. See https://github.com/lkn849/thtools for more information.

Metadata:

• Group: City of London UK 2021
• Author: Lucas Ng
• Summary: Used our software ToeholdTools to investigate the target miRNA specificity and activation of this part.

Raw data:

• Media:BBa_K3431036_thtest.txt
• Media:BBa_K3431036_crt.txt

This contribution was autogenerated by the script contrib.py, available at https://github.com/lkn849/thtools/tree/master/registry.

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This switch was designed to detect the miRNA hsa-miR-146a-5p at a temperature of 37°C. We tested it against every mature Homo sapiens miRNA in miRBase and our analysis shows that at this temperature it is best used to detect hsa-miR-146a-5p.

With hsa-miR-146a-5p at 37°C, the switch has a specificity of 2 ± 100 % and an activation of 13 ± 7 %. These values represent 95% confidence limits (z=1.96).

The temperature–activation–specificity relationship is shown here. CRT is an acronym for CelsiusRangeTest, the class in our Python library responsible for the following graph:

Error bars represent the standard deviation. The line of best fit was calculated using a univariate cubic spline weighted inverse to each point's standard error.

Sequence and Features