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Updated: May 20, 2025

Inducible, Cell Type-Specific Expression in Arabidopsis thaliana Through LhGR-Mediated Trans-Activation

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Published on: April 19, 2019

Genetic Toggle Switch in Plants.

Tessema K Kassaw¹, Wenlong Xu², Christopher S Zalewski¹

¹Department of Biology, Colorado State University, Fort Collins, Colorado 80523, United States.

ACS Synthetic Biology

|May 19, 2025

Summary

This summary is machine-generated.

Researchers developed programmable genetic devices for plants by using computational models to select and assemble genetic components. This approach ensures predictable function in stably engineered plants, advancing synthetic biology applications in sustainable systems.

Keywords:

Plant synthetic biology genetic toggle switch mathematical modeling predictable plant gene circuits transfer function

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Area of Science:

Synthetic biology
Plant biotechnology
Genetic engineering

Background:

Development of programmable genetic circuits for plants has lagged compared to other organisms.
Predictable genetic devices require quantitative characterization of genetic components.
Plant-specific attributes may impact genetic circuit predictability, necessitating robust modeling.

Purpose of the Study:

To develop a computational approach for designing predictable genetic devices in plants.
To address the challenge of verifying genetic circuit function in stably engineered plants.
To enable the engineering of plant traits for sustainable systems.

Main Methods:

Utilized quantitatively characterized plant genetic elements with defined transfer functions.
Developed in silico models to guide the assembly of genetic components into devices.
Employed computational selection and iterative refinement of genetic circuits.
Verified circuit function in stably engineered plants, including during differentiation.

Main Results:

Successfully designed and implemented a computationally selected genetic circuit (toggle switch) in plants.
Demonstrated that the genetic device functions as predicted in stably engineered plants.
Validated the computational approach for designing predictable plant genetic devices.

Conclusions:

Computational modeling and rigorous characterization enable the creation of predictable genetic devices in plants.
This methodology overcomes challenges posed by plant-specific attributes and long life spans.
Opens prospects for engineering plant abilities for sustainable human and environmental systems.