Literature DB >> 35188663

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

Jennifer Andres1, Matias D Zurbriggen2.   

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.
© 2022. Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Aux/IAAs; Auxin; Protoplasts; Quantitative biosensor; Synthetic biology tools

Mesh:

Substances:

Year:  2022        PMID: 35188663     DOI: 10.1007/978-1-0716-1791-5_11

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  20 in total

Review 1.  Designing cell function: assembly of synthetic gene circuits for cell biology applications.

Authors:  Mingqi Xie; Martin Fussenegger
Journal:  Nat Rev Mol Cell Biol       Date:  2018-08       Impact factor: 94.444

Review 2.  Quantitatively Understanding Plant Signaling: Novel Theoretical-Experimental Approaches.

Authors:  Sophia L Samodelov; Matias D Zurbriggen
Journal:  Trends Plant Sci       Date:  2017-06-28       Impact factor: 18.313

3.  In vivo gibberellin gradients visualized in rapidly elongating tissues.

Authors:  Annalisa Rizza; Ankit Walia; Viviane Lanquar; Wolf B Frommer; Alexander M Jones
Journal:  Nat Plants       Date:  2017-10-02       Impact factor: 15.793

4.  A novel sensor to map auxin response and distribution at high spatio-temporal resolution.

Authors:  Géraldine Brunoud; Darren M Wells; Marina Oliva; Antoine Larrieu; Vincent Mirabet; Amy H Burrow; Tom Beeckman; Stefan Kepinski; Jan Traas; Malcolm J Bennett; Teva Vernoux
Journal:  Nature       Date:  2012-01-15       Impact factor: 49.962

5.  StrigoQuant: A genetically encoded biosensor for quantifying strigolactone activity and specificity.

Authors:  Sophia L Samodelov; Hannes M Beyer; Xiujie Guo; Maximilian Augustin; Kun-Peng Jia; Lina Baz; Oliver Ebenhöh; Peter Beyer; Wilfried Weber; Salim Al-Babili; Matias D Zurbriggen
Journal:  Sci Adv       Date:  2016-11-04       Impact factor: 14.136

Review 6.  Programming Bacteria With Light-Sensors and Applications in Synthetic Biology.

Authors:  Zedao Liu; Jizhong Zhang; Jiao Jin; Zilong Geng; Qingsheng Qi; Quanfeng Liang
Journal:  Front Microbiol       Date:  2018-11-08       Impact factor: 5.640

7.  A quantitative ratiometric sensor for time-resolved analysis of auxin dynamics.

Authors:  Sabrina Wend; Cristina Dal Bosco; Michael M Kämpf; Fugang Ren; Klaus Palme; Wilfried Weber; Alexander Dovzhenko; Matias D Zurbriggen
Journal:  Sci Rep       Date:  2013       Impact factor: 4.379

8.  Abscisic acid dynamics in roots detected with genetically encoded FRET sensors.

Authors:  Alexander M Jones; Jonas Ah Danielson; Shruti N Manojkumar; Viviane Lanquar; Guido Grossmann; Wolf B Frommer
Journal:  Elife       Date:  2014-04-15       Impact factor: 8.140

9.  Synthetic hormone-responsive transcription factors can monitor and re-program plant development.

Authors:  Arjun Khakhar; Alexander R Leydon; Andrew C Lemmex; Eric Klavins; Jennifer L Nemhauser
Journal:  Elife       Date:  2018-05-01       Impact factor: 8.140

10.  Analysis of gibberellins as free acids by ultra performance liquid chromatography-tandem mass spectrometry.

Authors:  Terezie Urbanová; Danuše Tarkowská; Ondřej Novák; Peter Hedden; Miroslav Strnad
Journal:  Talanta       Date:  2013-03-31       Impact factor: 6.057

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