Temporal Metabolite, Ion, and Enzyme Activity Profiling Using Fluorescence Microscopy and Genetically Encoded Biosensors

Abstract

Living cells employ complex and highly dynamic signaling networks and transcriptional circuits to maintain homeostasis and respond appropriately to constantly changing environments. These networks enable cells to maintain tight control on intracellular concentrations of ions, metabolites, proteins, and other biomolecules and ensure a careful balance between a cell's energetic needs and catabolic processes required for growth. Establishing molecular mechanisms of genetic and pharmacological perturbations remains challenging, due to the interconnected nature of these networks and the extreme sensitivity of cellular systems to their external environment. Live cell imaging with genetically encoded fluorescent biosensors provides a powerful new modality for nondestructive spatiotemporal tracking of ions, small molecules, enzymatic activities, and molecular interactions in living systems, from cells, tissues, and even living organisms. By deploying large panels of cell lines, each with distinct biosensors, many critical biochemical pathways can be monitored in a highly parallel and high-throughput fashion to identify pharmacological vulnerabilities and combination therapies unique to a given cell type or genetic background. Here we describe the experimental and analytical methods required to conduct multiplexed parallel fluorescence microscopy experiments on live cells expressing stable transgenic synthetic protein biosensors.

Keywords: FRET; Fluorescence microscopy; Fluorescent biosensor; Mechanism of action; Profiling.

Fig. 1

A schematic diagram of the EKAR biosensor for ERK kinase activity developed by Svoboda and colleagues. In the presence of high ERK kinase activity within a cell, the synthetic protein adopts a constrained conformation that increases FRET between the CFP and YFP fluorophores

Fig. 2

A diagram describing the steps required to convert raw images into a single value of activity (FRET ratio) for each well, for each timepoint. These steps included flat-field correction, background correction, and pixel by pixel calculations. W1 = wavelength 1, W2 = wavelength 2, FFC = flat-field corrected, BC = background corrected

Fig. 3

A graphical output of an experiment utilizing 17 biosensors. SK-N-BE(2) biosensor-expressing cells were exposed to either vehicle, ouabain, or phorbol myristate acetate (PMA). Each tile represents a heatmap of a time-dependent plot of the relative changes in FRET ratio of each sensor within the dynamic range observed for that sensor throughout the experiment (fraction saturation) (see Note 8)