Abstract
We have developed a novel method for multi-color spectral FRET analysis which is used to study a system of three independent FRET-based molecular sensors composed of the combinations of only three fluorescent proteins. This method is made possible by a novel routine for computing the 3-D excitation/emission spectral fingerprint of FRET from reference measurements of the donor and acceptor alone. By unmixing the 3D spectrum of the FRET sample, the total relative concentrations of the fluorophores and their scaled FRET efficiencies are directly measured, from which apparent FRET efficiencies can be computed. If the FRET sample is composed of intramolecular FRET sensors it is possible to determine the total relative concentration of the sensors and then estimate absolute FRET efficiency of each sensor. Using multiple tandem constructs with fixed FRET efficiency as well as FRET-based calcium sensors with novel fluorescent protein combinations we demonstrate that the computed FRET efficiencies are accurate and changes in these quantities occur without crosstalk. We provide an example of this method’s potential by demonstrating simultaneous imaging of spatially colocalized changes in [Ca2+], [cAMP], and PKA activity.
Highlights
Molecular biosensors based on intra-molecular FRET have become indispensible tools for monitoring the spatial and temporal regulation of signaling processes in living tissue
Rather than filtering the signal to maximize the specificity of an emission channel to a select fluorophore, spectral overlap is welcomed in order to maximize photon collection, with bleed-through negated through linear unmixing
We have provided a theoretical framework under which multiple FRET efficiencies may be measured
Summary
Molecular biosensors based on intra-molecular FRET have become indispensible tools for monitoring the spatial and temporal regulation of signaling processes in living tissue. A number of FRET-based genetically encoded sensors quantifying second messenger concentration, phosphorylation state, and GTPase activity have been developed and improved throughout the last decade [1] These sensors have already proven to be invaluable at probing individual processes [2], it is becoming increasingly apparent that in order to better understand the complex interaction networks responsible for signal transduction that the ability to monitor the activity and spatial localization of multiple processes simultaneously is required [3]. Information about the individual processes is combined to build a broader picture of the signaling network Such approaches, termed computational multiplexing, have been applied in reconstructing the spatiotemporal relationship of signaling events measured with respect to, for example, the timing of ligand application, changes in membrane potential, or changes in membrane shape [5,6]. The interdependence of seemingly stochastic events is an interesting feature and by its nature cannot be studied by computation multiplexing
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
