研究目的
Developing a genetically encoded biosensor designed to report the activity of MAPKs in Arabidopsis thaliana.
研究成果
The development of SOMA, a genetically encoded biosensor for MAPK activity in Arabidopsis thaliana, represents a significant advancement in the ability to monitor kinase activity in living plant cells. The sensor dynamically reports MAPK activity in response to various stress treatments, with specificity demonstrated through genetic and chemical-genetic approaches. This tool opens new avenues for studying MAPK signaling pathways with single-cell resolution in living samples.
研究不足
The study is limited by the embryo lethality of mpk3 mpk6 double-mutants and the severe dwarf phenotype of mpk4 single mutants, complicating genetic testing. Additionally, the sensor's response may integrate the activities of kinases other than MAPKs, and the heterogeneity observed in cellular responses could have both technical and biological explanations.
1:Experimental Design and Method Selection:
The study involved the development of a genetically encoded MAPK activity sensor (SOMA) for Arabidopsis thaliana, incorporating yellow and blue fluorescent proteins, a phosphopeptide binding domain, a MAPK substrate domain, and a flexible linker. The design rationale was based on the expectation that phosphorylation would cause a conformational change increasing FRET efficiency.
2:Sample Selection and Data Sources:
Transgenic Arabidopsis lines expressing SOMA or its phosphosite mutant version (SOMAT679A) were generated. Detached cotyledons from these lines were used for live-cell imaging experiments.
3:List of Experimental Equipment and Materials:
Confocal microscopy (Zeiss LSM 510 Meta or Zeiss LSM 780), microfluidic devices for live-cell imaging, recombinant proteins expressed in E. coli, and various chemical treatments (NaCl, flg22, chitin, 1-NA-PP1).
4:1).
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: Live-cell imaging was performed on detached cotyledons mounted in a microfluidic device. Treatments were applied during imaging, and changes in FRET efficiency were monitored. In vitro kinase assays and FRET assays were conducted to validate the sensor's functionality.
5:Data Analysis Methods:
Image analysis was performed using Fiji software to process confocal microscopy data, measuring the ratio of YPet to Turquoise GL emission as an indicator of FRET efficiency.
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