Difference between revisions of "Part:BBa K3431035"

Revision as of 16:27, 25 October 2020 (view source) Jerry252ray (Talk | contribs) ← Older edit		Latest revision as of 20:55, 13 October 2021 (view source) JYC (Talk | contribs)
(5 intermediate revisions by 3 users not shown)
Line 28:		Line 28:
	</html>		</html>
	<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>		<br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br><br>
		+
	===Characterization using invertase===		===Characterization using invertase===
Line 45:		Line 46:
	<b>Results</b><br>		<b>Results</b><br>
	The glucose concentration in the ON state with miR-146 is about 500 mg/dL, indicating the high sensitivity of the toehold switch. The ON/OFF ratio with miR-146 is 1.21, which suggested the regulatory function of the toehold switch. By contrast, the ON/OFF ratios with miR-191 and miR-223 are 0.82 and 1.00, respectively. These ratios are close to 1, meaning the zr146_B toehold switch has high specificity. As a result, zr146_B_ToeholdSwitch-Regulated Invertase has been proven to be useful for miR-146 detection.		The glucose concentration in the ON state with miR-146 is about 500 mg/dL, indicating the high sensitivity of the toehold switch. The ON/OFF ratio with miR-146 is 1.21, which suggested the regulatory function of the toehold switch. By contrast, the ON/OFF ratios with miR-191 and miR-223 are 0.82 and 1.00, respectively. These ratios are close to 1, meaning the zr146_B toehold switch has high specificity. As a result, zr146_B_ToeholdSwitch-Regulated Invertase has been proven to be useful for miR-146 detection.
		+
		+
		+	===Information contributed by City of London UK (2021)===
		+	[[File:ToeholdTools.png|x200px|center]]
		+
		+	This toehold switch was characterized <i>in silico</i> 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_K3431035_thtest.txt]]
		+	*[[Media:BBa_K3431035_crt.txt]]
		+
		+	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 <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 7 ± 50 % and an activation of 38 ± 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:
		+
		+	[[File:BBa_K3431035_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:'''
		+	*As per the above, we cannot confirm that this switch accurately detects the desired miRNA sequence.
		+
		+	We do not recommend this part for future usage.
Line 66:		Line 106:
	<!-- -->		<!-- -->
	<span class='h3bb'>Sequence and Features</span>		<span class='h3bb'>Sequence and Features</span>
−	<partinfo>BBa_K3431007 SequenceAndFeatures</partinfo>	+	<partinfo>BBa_K3431035 SequenceAndFeatures</partinfo>
	<!-- Uncomment this to enable Functional Parameter display		<!-- Uncomment this to enable Functional Parameter display
	===Functional Parameters===		===Functional Parameters===
−	<partinfo>BBa_K3431007 parameters</partinfo>	+	<partinfo>BBa_K3431035 parameters</partinfo>
	<!-- -->		<!-- -->

---

Latest revision as of 20:55, 13 October 2021

zr146_B Toehold Switch for miR-146 Detection

Introduction

zr146_B 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_B 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 )

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”.

Results
The glucose concentration in the ON state with miR-146 is about 500 mg/dL, indicating the high sensitivity of the toehold switch. The ON/OFF ratio with miR-146 is 1.21, which suggested the regulatory function of the toehold switch. By contrast, the ON/OFF ratios with miR-191 and miR-223 are 0.82 and 1.00, respectively. These ratios are close to 1, meaning the zr146_B toehold switch has high specificity. As a result, zr146_B_ToeholdSwitch-Regulated Invertase has been proven to be useful for miR-146 detection.

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_K3431035_thtest.txt
• Media:BBa_K3431035_crt.txt

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 7 ± 50 % and an activation of 38 ± 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:

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.

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