Genetically encoded biosensors based on the principle of Förster resonance energy transfer comprise two major classes: biosensors based on fluorescence resonance energy transfer (FRET) and those based on bioluminescence energy transfer (BRET). The FRET biosensors visualize signaling-molecule activity in cells or tissues with high resolution. Meanwhile, due to the low background signal, the BRET biosensors are primarily used in drug screening. Here, we report a protocol to transform intramolecular FRET biosensors to BRET-FRET hybrid biosensors called hyBRET biosensors. The hyBRET biosensors retain all properties of the prototype FRET biosensors and also work as BRET biosensors with dynamic ranges comparable to the prototype FRET biosensors. The hyBRET biosensors are compatible with optogenetics, luminescence microplate reader assays, and non-invasive whole-body imaging of xenograft and transgenic mice. This simple protocol will expand the use of FRET biosensors and enable visualization of the multiscale dynamics of cell signaling in live animals.
ABSTRACT. Genetically-encoded biosensors based on Förster/fluorescence resonance energy transfer (FRET) are versatile tools for studying the spatio-temporal regulation of signaling molecules within not only the cells but also tissues. Perhaps the hardest task in the development of a FRET biosensor for protein kinases is to identify the kinase-specific substrate peptide to be used in the FRET biosensor. To solve this problem, we took advantage of kinase-interacting substrate screening (KISS) technology, which deduces a consensus substrate sequence for the protein kinase of interest. Here, we show that a consensus substrate sequence for ROCK identified by KISS yielded a FRET biosensor for ROCK, named Eevee-ROCK, with high sensitivity and specificity. By treating HeLa cells with inhibitors or siRNAs against ROCK, we show that a substantial part of the basal FRET signal of Eevee-ROCK was derived from the activities of ROCK1 and ROCK2. Eevee-ROCK readily detected ROCK activation by epidermal growth factor, lysophosphatidic acid, and serum. When cells stably-expressing Eevee-ROCK were time-lapse imaged for three days, ROCK activity was found to increase after the completion of cytokinesis, concomitant with the spreading of cells. Eevee-ROCK also revealed a gradual increase in ROCK activity during apoptosis. Thus, Eevee-ROCK, which was developed from a substrate sequence predicted by the KISS technology, will pave the way to a better understanding of the function of ROCK in a physiological context.
Two decades have passed since the development of the first calcium indicator based on the green fluorescent protein (GFP) and the principle of Förster resonance energy transfer (FRET). During this period, researchers have advanced many novel ideas for the improvement of such genetically encoded FRET biosensors, which have allowed them to expand their targets from small molecules to signaling proteins and physicochemical properties. Although the merits of "genetically encoded" FRET biosensors became clear once various cell lines were established and several transgenic organisms were generated, the road to these developments was not necessarily a smooth one. Moreover, even today the development of new FRET biosensors remains a very laborintensive, trial-and-error process. Therefore, at this junction, it may be worthwhile to summarize the progress of the FRET biosensor and discuss the future direction of its development and application.
Abbreviations: H&E, hematoxylin and eosin; BAC, bacterial artificial chromosome; FRET, Förster resonance energy transfer; TPEM, two-photon excitation microscopy; FP, fluorescent protein; WPRE, woodchuck hepatitis virus (WHP) posttranscriptional regulatory element; DCGAN, deep convolutional generative adversarial networks. AbstractFor more than a century, hematoxylin and eosin (H&E) staining has been the de-facto standard for histological studies. Consequently, the legacy of histological knowledge is largely based on H&E staining. Due to the recent advent of multi-photon excitation microscopy, the observation of live tissue is increasingly being used in many research fields. Adoption of this technique has been further accelerated by the development of genetically encoded biosensors for ions and signaling molecules. However, H&E-based histology has not yet begun to fully utilize in-vivo imaging due to the lack of proper morphological markers. Here, we report a genetically encoded fluorescent marker, NuCyM (Nucleus, Cytosol, and Membrane), which is designed to recapitulate H&E staining patterns in vivo. We generated a transgenic mouse line ubiquitously expressing NuCyM by using a ROSA26 bacterial artificial chromosome (BAC) clone. NuCyM evenly marked the plasma membrane, cytoplasm and nucleus in most tissues, yielding H&E staining-like images. In the NuCyM-expressing cells, cell division of a single cell was clearly observed as five basic phases during M phase by three-dimensional imaging. We next crossed NuCyM mice with transgenic mice expressing an ERK biosensor based on the principle of Förster resonance energy transfer (FRET). Using NuCyM, ERK activity in each cell could be extracted from the FRET images. To further accelerate the image analysis, we employed machine learning-based segmentation methods, and thereby automatically quantitated ERK activity in each cell. In conclusion, NuCyM is a versatile cell morphological marker that enables us to grasp histological information as with H&E staining.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.