Abstract
Numerous unimolecular, genetically-encoded Förster Resonance Energy Transfer (FRET) probes for monitoring biochemical activities in live cells have been developed over the past decade. As these probes allow for collection of high frequency, spatially resolved data on signaling events in live cells and tissues, they are an attractive technology for obtaining data to develop quantitative, mathematical models of spatiotemporal signaling dynamics. However, to be useful for such purposes the observed FRET from such probes should be related to a biological quantity of interest through a defined mathematical relationship, which is straightforward when this relationship is linear, and can be difficult otherwise. First, we show that only in rare circumstances is the observed FRET linearly proportional to a biochemical activity. Therefore in most cases FRET measurements should only be compared either to explicitly modeled probes or to concentrations of products of the biochemical activity, but not to activities themselves. Importantly, we find that FRET measured by standard intensity-based, ratiometric methods is inherently non-linear with respect to the fraction of probes undergoing FRET. Alternatively, we find that quantifying FRET either via (1) fluorescence lifetime imaging (FLIM) or (2) ratiometric methods where the donor emission intensity is divided by the directly-excited acceptor emission intensity (denoted Ralt) is linear with respect to the fraction of probes undergoing FRET. This linearity property allows one to calculate the fraction of active probes based on the FRET measurement. Thus, our results suggest that either FLIM or ratiometric methods based on Ralt are the preferred techniques for obtaining quantitative data from FRET probe experiments for mathematical modeling purposes.
Highlights
Over the past 10 years, the number of genetically encoded, Forster resonance energy transfer (FRET)-based sensors for monitoring various biochemical activities in live cells and real time has skyrocketed [1,2,3,4,5,6,7,8]
Our theoretical analysis supported by experimental data yields important guidelines for using FRET probe data with quantitative modeling
We have shown that only in rare circumstances will the fraction of molecules capable of FRET be linearly related to an upstream enzymatic activity
Summary
Over the past 10 years, the number of genetically encoded, Forster resonance energy transfer (FRET)-based sensors for monitoring various biochemical activities in live cells and real time has skyrocketed [1,2,3,4,5,6,7,8]. For quantitative modeling of biochemical processes, these probes offer huge advantages over other currently available technologies (which include for example western blotting, immunofluorescence, and flow cytometery): (i) quantities of interest can be assayed in living cells and tissues [9] and in real time; (ii) high frequency sampling is possible; (iii) three-dimensional spatial data can be obtained; and (iv) single-cell as opposed to population average responses are measured. These characteristics make the use of FRET probes attractive for quantitative modeling, it is largely unknown how such data might precisely be used for such purposes. Investigate how linear and quantitative FRET data obtained by these two methods are
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