Focus on biosensors: Looking through the lens of quantitative biology

Abstract

In recent years, plant biologists interested in quantifying molecules and molecular events in vivo have started to complement reporter systems with genetically encoded fluorescent biosensors (GEFBs) that directly sense an analyte. Such biosensors can allow measurements at the level of individual cells and over time. This information is proving valuable to mathematical modellers interested in representing biological phenomena in silico, because improved measurements can guide improved model construction and model parametrisation. Advances in synthetic biology have accelerated the pace of biosensor development, and the simultaneous expression of spectrally compatible biosensors now allows quantification of multiple nodes in signalling networks. For biosensors that directly respond to stimuli, targeting to specific cellular compartments allows the observation of differential accumulation of analytes in distinct organelles, bringing insights to reactive oxygen species/calcium signalling and photosynthesis research. In conjunction with improved image analysis methods, advances in biosensor imaging can help close the loop between experimentation and mathematical modelling.

Fig. 1.

Different types of genetically encoded fluorescent biosensors and their molecular mechanisms. (a) The mechanism of action of the auxin reporter DR5::GFP, where the auxin receptor complex targets the AUX/IAA transcriptional repressors for degradation, allowing green fluorescent protein transcription and fluorescence in the presence of the hormone. (b) The mechanism of action of the auxin biosensor DII:VENUS, where a venus fluorescent protein (FP) fused to domain II (DII) from an AUX/IAA protein is targeted for degradation by the auxin receptor complex, causing loss of fluorescence in the presence of the hormone. (c) The mechanism of action of the direct abscisic acid biosensor ABACUS1, where hormone binding causes the interaction of two sensory domains of a single fusion protein. This conformational change causes increased Förster resonance energy transfer (FRET) between two FP domains (a FRET donor and acceptor) and an altered emission ratio upon donor excitation. (d) The mechanism of action of the direct glutathione redox potential biosensor roGFP. A disulphide bond on the barrel of roGFP is reversibly sensitive to oxidation, causing an altered absorption spectrum.

Fig. 2.

Example image processing pipeline for the nuclear localised ratiometric Förster resonance energy transfer sensor nlsABACUS1-2μ. Notes: Several image acquisition channels are used in FRET biosensor analysis. Here, the new FRETENATOR analysis pipeline for Fiji was used (Rowe et al., 2021). For segmentation, the following steps are performed: first a difference of Gaussian filter is applied to the acceptor-excited acceptor-emission channel to remove background and smooth noise, then Otsu’s method is used to threshold the filtered image based on signal intensity. A watershed algorithm is used to split touching objects in the threshold image, and a connected-component analysis is used to label all the individual objects, producing a label map. The quantification steps involve removing saturated voxels from the original images and then dividing the mean signal intensity of donor-excited acceptor-emission channel by the donor-exited donor-emission channel for each labelled ROI, which can be represented on the segmented image using false coloration (e.g., the Turbo lookup table used here).