Here we present a fluctuation-based approach to biosensor Förster resonance energy transfer (FRET) detection that can measure the molecular flow and signaling activity of proteins in live cells. By simultaneous use of the phasor approach to fluorescence lifetime imaging microscopy (FLIM) and cross-pair correlation function (pCF) analysis along a line scanned in milliseconds, we detect the spatial localization of Rho GTPase activity (biosensor FRET signal) as well as the diffusive route adopted by this active population. In particular we find, for Rac1 and RhoA, distinct gradients of activation (FLIM-FRET) and a molecular flow pattern (pCF analysis) that explains the observed polarized GTPase activity. This multiplexed approach to biosensor FRET detection serves as a unique tool for dissection of the mechanism(s) by which key signaling proteins are spatially and temporally coordinated. T o dissect the mechanism by which a signaling pathway is regulated it is necessary to not only measure the localization of the key signaling proteins, but also their activation at different subcellular locations. This is most often accomplished via the use of genetically encoded biosensors (1, 2). Given that the great majority of biosensor designs use a Förster resonance energy transfer (FRET) interaction as a report of the activity being probed, there is great interest in the development of methods for biosensor FRET detection with high spatial and temporal resolution (1). For example, in a recent study by Machacek and coworkers, the spatiotemporal coordination of several Rho GTPases was probed on the second and micrometer scale at the leading edge of migrating cells, via the use of a series of FRET biosensors (3). Edge velocity was correlated with the changing activation of GTPase biosensors in defined regions adjacent to the edge. This revealed correlations of RhoA, Rac1, and Cdc42 activity with leading-edge dynamics that had not previously been detected using static or low temporal resolution imaging. Along this line, in an even more recent study, Kunida et al. developed an image processing algorithm to extract the FRET values and velocities from an entire cell periphery (4). With this analytical approach they revealed several feedback regulations between Rac1 and membrane protrusion, which could not have been observed without use of a global field of view and high spatial resolution imaging (micrometer scale).Determination of biosensor FRET in cells at a quantitative level is thought to be best achieved using the quenching of the donor lifetime, which directly detects the "on" and "off" state of the FRET biosensor. We recently demonstrated this property by applying the phasor approach to fluorescence lifetime imaging (FLIM) on the GTPase biosensors used by Machacek and coworkers (5). Using a frame mode acquisition we were able to spatially map and quantify the degree of Rac1 and RhoA activation in each pixel of an image as a function of time, independent of other sources of fluorescence for both single-and dual-chain designs....