bioRxivCell Biology
Dynamic FRET-FLIM based screens of signal transduction pathways: a feasibility study
R. Harkes, O. Kukk, S. Mukherjee, J. Klarenbeek, B. van den Broek, K. Jalink
Abstract
Fluorescence Lifetime Imaging (FLIM) is an intrinsically quantitative method to screen for protein-protein interactions and frequently used to record the outcome of signal transduction events. With new highly sensitive and photon efficient FLIM instrumentation, the technique also becomes attractive to screen, with high temporal resolution, for fast changes in Forster Resonance Energy Transfer (FRET), such as those occurring upon activation of cell signaling. We studied the effects of siRNA-mediated individual knockdown of an extensive set of 22 different phosphodiesterases (PDEs) on baseline levels and agonist-induced changes of the second messenger cAMP. Using HeLa cells stably expressing our FRET-FLIM sensor we imaged many hundreds of cells at 5 second intervals for each condition. Following segmentation of cells by the deep-learning implementation Cellpose, FLIM time traces were calculated and fitted for dynamic analysis with custom-made Python scripts. Taking advantage of the quantitative FLIM data, we found very limited effects of PDE knockdown on baseline and agonist-induced peak levels of cAMP. However, cAMP breakdown in the decay phase was significantly slower when PDE3A and, to a lesser amount, PDE10A were knocked down, identifying these isoforms as dominant in HeLa cells. In conclusion, we present a robust platform that combines photon-efficient FLIM instrumentation with systematic gene knockdown and an automated open-source analysis pipeline. Our quantitative platform provides detailed kinetic analysis of cellular signals in individual cells with unprecedented throughput.
- organism: human
- assay: fluorescence / live-cell microscopy
- research focus: cell type annotation
- research focus: differential expression
- approach: deep learning
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