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Rapidly characterizing the fast dynamics of RNA genetic circuitry with cell-free transcription-translation (TX-TL) systems.

Takahashi MK, Chappell J, Hayes CA, Sun ZZ, Kim J, Singhal V, Spring KJ, Al-Khabouri S, Fall CP, Noireaux V, Murray RM, Lucks JB - ACS Synth Biol (2014)

Bottom Line: We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade.We also show that this response time can be adjusted with temperature and regulator threshold tuning.Finally, we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo.

View Article: PubMed Central - PubMed

Affiliation: †School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14850, United States.

ABSTRACT
RNA regulators are emerging as powerful tools to engineer synthetic genetic networks or rewire existing ones. A potential strength of RNA networks is that they may be able to propagate signals on time scales that are set by the fast degradation rates of RNAs. However, a current bottleneck to verifying this potential is the slow design-build-test cycle of evaluating these networks in vivo. Here, we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA networks. We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade. We also show that this response time can be adjusted with temperature and regulator threshold tuning. Finally, we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo.

No MeSH data available.


Related in: MedlinePlus

Assessing batch-to-batch variation. (A) Fluorescence time coursesof TX-TL reactions in three different extract and buffer preparationswith 0.5 nM L1 and 15 nM no-antisense control DNA. Shaded regionsrepresent standard deviations of at least 11 independent reactionsover multiple days calculated at each time point. (B) Average maximumSFGFP production rates for the same three buffer and extract preparationsfrom reactions with 0.5 nM L1 and 0, 5, 10, 15, and 20 nM no-antisensecontrol DNA. Plots of maximum SFGFP production rates from which thesewere calculated can be found in Supporting InformationFigure S4. Error bars represent standard deviations from atleast 11 independent reactions.
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fig3: Assessing batch-to-batch variation. (A) Fluorescence time coursesof TX-TL reactions in three different extract and buffer preparationswith 0.5 nM L1 and 15 nM no-antisense control DNA. Shaded regionsrepresent standard deviations of at least 11 independent reactionsover multiple days calculated at each time point. (B) Average maximumSFGFP production rates for the same three buffer and extract preparationsfrom reactions with 0.5 nM L1 and 0, 5, 10, 15, and 20 nM no-antisensecontrol DNA. Plots of maximum SFGFP production rates from which thesewere calculated can be found in Supporting InformationFigure S4. Error bars represent standard deviations from atleast 11 independent reactions.

Mentions: There is known to be batch-to-batch variation inTX-TL preparations.28 In order to assessthe impact of batch-to-batch variation on RNA circuit characterization,we tested three different extract/buffer preparations by adding arange of concentrations of the no-antisense control plasmid to 0.5nM of the L1 plasmid. Since extra control DNA causes resource competition,this experimental design allowed us to assess the maximum amount ofDNA per reaction that each batch could support. As shown in Figure 3, we observed several important features. First,for a fixed concentration of L1 and control DNA, we observed significantdifferences in the fluorescence time courses between the batches (Figure 3A). The end point fluorescence of batch 2 is morethan twice that of batch 1 and 3. Second, batch 2 reaches constantSFGFP production faster than batch 1 and 3 for all conditions tested(Supporting Information Figure S4). Third,batch 1 had a lower fluorescence output than batch 3, but both reachedconstant SFGFP production at approximately the same time over allconditions.


Rapidly characterizing the fast dynamics of RNA genetic circuitry with cell-free transcription-translation (TX-TL) systems.

Takahashi MK, Chappell J, Hayes CA, Sun ZZ, Kim J, Singhal V, Spring KJ, Al-Khabouri S, Fall CP, Noireaux V, Murray RM, Lucks JB - ACS Synth Biol (2014)

Assessing batch-to-batch variation. (A) Fluorescence time coursesof TX-TL reactions in three different extract and buffer preparationswith 0.5 nM L1 and 15 nM no-antisense control DNA. Shaded regionsrepresent standard deviations of at least 11 independent reactionsover multiple days calculated at each time point. (B) Average maximumSFGFP production rates for the same three buffer and extract preparationsfrom reactions with 0.5 nM L1 and 0, 5, 10, 15, and 20 nM no-antisensecontrol DNA. Plots of maximum SFGFP production rates from which thesewere calculated can be found in Supporting InformationFigure S4. Error bars represent standard deviations from atleast 11 independent reactions.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4487224&req=5

fig3: Assessing batch-to-batch variation. (A) Fluorescence time coursesof TX-TL reactions in three different extract and buffer preparationswith 0.5 nM L1 and 15 nM no-antisense control DNA. Shaded regionsrepresent standard deviations of at least 11 independent reactionsover multiple days calculated at each time point. (B) Average maximumSFGFP production rates for the same three buffer and extract preparationsfrom reactions with 0.5 nM L1 and 0, 5, 10, 15, and 20 nM no-antisensecontrol DNA. Plots of maximum SFGFP production rates from which thesewere calculated can be found in Supporting InformationFigure S4. Error bars represent standard deviations from atleast 11 independent reactions.
Mentions: There is known to be batch-to-batch variation inTX-TL preparations.28 In order to assessthe impact of batch-to-batch variation on RNA circuit characterization,we tested three different extract/buffer preparations by adding arange of concentrations of the no-antisense control plasmid to 0.5nM of the L1 plasmid. Since extra control DNA causes resource competition,this experimental design allowed us to assess the maximum amount ofDNA per reaction that each batch could support. As shown in Figure 3, we observed several important features. First,for a fixed concentration of L1 and control DNA, we observed significantdifferences in the fluorescence time courses between the batches (Figure 3A). The end point fluorescence of batch 2 is morethan twice that of batch 1 and 3. Second, batch 2 reaches constantSFGFP production faster than batch 1 and 3 for all conditions tested(Supporting Information Figure S4). Third,batch 1 had a lower fluorescence output than batch 3, but both reachedconstant SFGFP production at approximately the same time over allconditions.

Bottom Line: We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade.We also show that this response time can be adjusted with temperature and regulator threshold tuning.Finally, we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo.

View Article: PubMed Central - PubMed

Affiliation: †School of Chemical and Biomolecular Engineering, Cornell University, Ithaca, New York 14850, United States.

ABSTRACT
RNA regulators are emerging as powerful tools to engineer synthetic genetic networks or rewire existing ones. A potential strength of RNA networks is that they may be able to propagate signals on time scales that are set by the fast degradation rates of RNAs. However, a current bottleneck to verifying this potential is the slow design-build-test cycle of evaluating these networks in vivo. Here, we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA networks. We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade. We also show that this response time can be adjusted with temperature and regulator threshold tuning. Finally, we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo.

No MeSH data available.


Related in: MedlinePlus