Difference between revisions of "Part:BBa K3431011"

 
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<b>Results</b><br>
 
<b>Results</b><br>
 
As shown above, the glucose concentration rose as the miR-146 triggers increased, representing a positive correlation.
 
As shown above, the glucose concentration rose as the miR-146 triggers increased, representing a positive correlation.
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===Information contributed by City of London UK (2021)===
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[[File:ToeholdTools.png|x200px|center]]
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This toehold switch was characterized <i>in silico</i> using the ToeholdTools project that our team developed.
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See https://github.com/lkn849/thtools for more information.
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Metadata:
 +
*'''Group:''' City of London UK 2021
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*'''Author:''' Lucas Ng
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*'''Summary:''' Used our software ToeholdTools to investigate the target miRNA specificity and activation of this part.
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Raw data:
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*[[Media:BBa_K3431011_thtest.txt]]
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*[[Media:BBa_K3431011_crt.txt]]
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This contribution was autogenerated by the script '''contrib.py''', available at https://github.com/lkn849/thtools/tree/master/registry.
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----
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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 <i>Homo sapiens</i> miRNA in miRBase and our analysis shows that at this temperature it is best used to detect hsa-miR-146b-5p.
 +
 +
With hsa-miR-146b-5p at 37°C, the switch has a specificity of 3 ± 60 % and an activation of 29 ± 9 %.
 +
These values represent 95% confidence limits (z=1.96).
 +
 +
The temperature&ndash;activation&ndash;specificity relationship is shown here.
 +
CRT is an acronym for CelsiusRangeTest, the class in our Python library responsible for the following graph:
 +
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[[File:BBa_K3431011_graph.png|500px|center]]
 +
 +
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.
 +
 +
'''Caveats:'''
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*As per the above, we cannot confirm that this switch accurately detects the desired miRNA sequence.
 +
*The miRNA most targeted by this switch heavily fluctuates based on temperature.Therefore, we cannot confirm the reliability of this switch.
 +
 +
We do not recommend this part for future usage.
  
 
===References===
 
===References===

Latest revision as of 20:43, 13 October 2021


zr146_A Toehold Switch for miR-146 Detection


Introduction

zr146_A toehold switch is a regulatory part for the downstream reporter gene. With this part, the protein expression can be controlled by the miR-146. 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-146, 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 zr146_A toehold switch, we adopted the loop and linker structure from Green et al., 2016[7], and the linker structure is the random linker design by iGEM_CSMU_2020. 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”.

Figure. 3. The glucose productions of the zr146_A 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 450 mg/dL, indicating the high sensitivity of the toehold switch. The ON/OFF ratio with miR-146 is 2.07, which suggested the regulatory function of the toehold switch. By contrast, the ON/OFF ratios with miR-191 and miR-223 are 1.09 and 1.31, respectively. These ratios are close to 1, meaning the zr146_A toehold switch has high specificity. As a result, zr146_A_ToeholdSwitch-Regulated Invertase has been proven to be useful for miR-146 detection.

Characterization using invertase

To understand the correlation of the trigger amount and the glucose production, we added different amounts of miR-146 to the protein synthesis kit and produced the proteins at 37℃ for 2 hours. We would then add 5μl of 0.5M sucrose and measured the glucose concentration with the glucose meter after 30 minutes.

Figure. 4. The glucose productions of the zr146_A 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
As shown above, the glucose concentration rose as the miR-146 triggers increased, representing a positive correlation.


Information contributed by City of London UK (2021)

ToeholdTools.png

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:

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


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-146b-5p.

With hsa-miR-146b-5p at 37°C, the switch has a specificity of 3 ± 60 % and an activation of 29 ± 9 %. 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:

BBa K3431011 graph.png

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.

Caveats:

  • As per the above, we cannot confirm that this switch accurately detects the desired miRNA sequence.
  • The miRNA most targeted by this switch heavily fluctuates based on temperature.Therefore, we cannot confirm the reliability of this switch.

We do not recommend this part for future usage.

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
    INCOMPATIBLE WITH RFC[10]
    Illegal EcoRI site found at 9
  • 12
    INCOMPATIBLE WITH RFC[12]
    Illegal EcoRI site found at 9
  • 21
    INCOMPATIBLE WITH RFC[21]
    Illegal EcoRI site found at 9
  • 23
    INCOMPATIBLE WITH RFC[23]
    Illegal EcoRI site found at 9
  • 25
    INCOMPATIBLE WITH RFC[25]
    Illegal EcoRI site found at 9
  • 1000
    COMPATIBLE WITH RFC[1000]