Difference between revisions of "Part:BBa K3431008"

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===Design===
 
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The design of the toehold switch was mainly based on the previous research.1 2 3 4 5 6 For the zz31 toehold switch, we adopted the loop and the linker structure from Green et al., 20167. Using NUPACK analysis and Vienna binding models, we designed the sequence of the toehold switch. (See our model page: https://2020.igem.org/Team:CSMU_Taiwan/Model)
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The design of the toehold switch was mainly based on the previous research<sup>[1][2][3][4][5][6]</sup>. For the zz31 toehold switch, we adopted the loop and the linker structure from Green et al., 2016<sup>[7]</sup>. Using NUPACK analysis and Vienna binding models, we designed the sequence of the toehold switch. (See our model page: https://2020.igem.org/Team:CSMU_Taiwan/Model)
  
 
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<span class='h3bb'>Sequence and Features</span>
 
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<partinfo>BBa_K3431008 SequenceAndFeatures</partinfo>
  
  
 
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===Functional Parameters===
 
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Latest revision as of 06:23, 27 October 2020


zz31 Toehold Switch for miR-31 Detection

Introduction

zz31 toehold switch is a regulatory part for the downstream reporter gene. With this part, the protein expression can be controlled by the miR-31. The sequence of the toehold switch can be separated into the following 5 regions from its 5' end: TBS (trigger binding site), stem region, loop region with RBS (ribosome binding site), complimentary stem region with a start codon, and linker. Upon binding with miR-31, its hairpin structure can be opened up and the ribosomes can bind with its RBS (ribosome binding site), triggering the translation of the downstream reporter.

Design

The design of the toehold switch was mainly based on the previous research[1][2][3][4][5][6]. For the zz31 toehold switch, we adopted the loop and the linker structure from Green et al., 2016[7]. Using NUPACK analysis and Vienna binding models, we designed the sequence of the toehold switch. (See our model page: https://2020.igem.org/Team:CSMU_Taiwan/Model)


Figure 1. NUPACK analysis result
Figure. 2. ViennaRNA Package result

















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”.

Fig. 3. The glucose productions of the zz31 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-31 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 ON/OFF ratio with miR-31 is 4.30, which suggested the regulatory function of the toehold switch. By contrast, the ON/OFF ratios with miR-191 and miR-223 are 1.50 and 0.10, respectively. These ratios are close to 1, meaning the zz31 toehold switch has high specificity. As a result, zz31_ToeholdSwitch-Regulated Invertase has been proven to be useful for miR-31 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.

Sequence and Features


Assembly Compatibility:
  • 10
    COMPATIBLE WITH RFC[10]
  • 12
    COMPATIBLE WITH RFC[12]
  • 21
    COMPATIBLE WITH RFC[21]
  • 23
    COMPATIBLE WITH RFC[23]
  • 25
    COMPATIBLE WITH RFC[25]
  • 1000
    COMPATIBLE WITH RFC[1000]