Optimization of FRET imaging in Arabidopsis protoplasts

Recent advancements in fluorescence-based biosensor technologies have enabled more precise and accurate Förster resonance energy transfer (FRET) imaging within Agrobacterium-mediated plant transformation systems. However, the application of FRET imaging in plant tissues remains hindered by significant challenges, particularly the time-intensive process of generating transgenic lines and the complications arising from tissue autofluorescence. In contrast, protoplast-based FRET imaging offers a rapid and efficient platform for functional screening and analysis, making it an essential tool for plant research. Nevertheless, conventional protoplast-based FRET approaches are often limited by background interference, inconsistent imaging conditions, and difficulties in quantitative analysis. Here, we present a systematic optimization of imaging conditions using the calcium biosensor D3cpv, addressing these limitations to improve both precision and efficiency in protoplast-based FRET imaging. This work serves as a practical guide for streamlining FRET imaging workflows and maximizing the utility of biosensors in plant cell studies.