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Genetically Encoded Biosensors for the Quantitative Analysis of Auxin Dynamics in Plant Cells.

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Plants, as sessile organisms, possess complex and intertwined signaling networks to react and adapt their behavior toward different internal and external stimuli. Due to this high level of complexity, the… Click to show full abstract

Plants, as sessile organisms, possess complex and intertwined signaling networks to react and adapt their behavior toward different internal and external stimuli. Due to this high level of complexity, the implementation of quantitative molecular tools in planta remains challenging. Synthetic biology as an ever-growing interdisciplinary field applies basic engineering principles in life sciences. A plethora of synthetic switches, circuits, and even higher order networks has been implemented in different organisms, such as bacteria and mammalian cells, and facilitates the study of signaling and metabolic pathways. However, the application of such tools in plants lags behind, and thus only a few genetically encoded biosensors and switches have been engineered toward the quantitative investigation of plant signaling. Here, we present a protocol for the quantitative analysis of auxin signaling in Arabidopsis thaliana protoplasts. We implemented genetically encoded, ratiometric, degradation-based luminescent biosensors and applied them for studying auxin perception dynamics. For this, we utilized three different Aux/IAAs as sensor modules and analyzed their degradation behavior in response to auxin. Our experimental approach requires simple hardware and experimental reagents and can thus be implemented in every plant-related or cell culture laboratory. The system allows for the analysis of auxin perception and signaling aspects on various levels and can be easily expanded to other hormones, as for example strigolactones. In addition, the modular sensor design enables the implementation of sensor modules in a straightforward and time-saving approach.

Keywords: genetically encoded; analysis auxin; auxin; biology; plant

Journal Title: Methods in molecular biology
Year Published: 2022

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