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Fluorescent biosensors are a valuable means to report the spatiotemporal dynamics of protein activities in live cells and animals. However, biosensors affect the activities they are reporting. This can be ameliorated by increasing sensitivity, to use lower biosensor concentrations, or by choosing designs that minimize undesirable interactions. For biosensors in which fluorescent components interact to produce Forster Resonance Energy Transfer (FRET), perturbation is often due to interaction of biosensor components with nonfluorescent, endogenous proteins, rather than productive interactions that lead to FRET. Here we engineer the interface between biosensor components using charge swap and ‘knob into hole’ mutations to reduce all but desired interactions. Novel biosensors for Rac1 and Cdc42 showed reduced interactions with endogenous GTPases and effectors, normal activation by guanine nucleotide exchange factors (GEFs), and correctly reproduced previous reports of GTPase activation dynamics. Assaying concentration-dependent effects on cell motility showed substantially reduced perturbation of normal cell behavior. Computational models indicated that minimal perturbation could be achieved over a broader range of concentrations using the new ‘orthogonal’ biosensors. 

The accuracy of biosensor ratio imaging is limited by signal/noise. Signals can be weak when biosensor concentrations must be limited to avoid cell perturbation. This can be especially problematic in imaging of low volume regions, e.g., along the cell edge. The cell edge is an important imaging target in studies of cell motility. We show how the division of fluorescence intensities with low signal-to-noise at the cell edge creates specific artifacts due to background subtraction and division by small numbers, and that simply improving the accuracy of background subtraction cannot address these issues. We propose a new approach where, rather than simply subtracting background from the numerator and denominator, we subtract a noise correction factor (NCF) from the numerator only. This NCF can be derived from the analysis of noise distribution in the background near the cell edge or from ratio measurements in the cell regions where signal-to-noise is high. We test the performance of the method first by examining two noninteracting fluorophores distributed evenly in cells. This generated a uniform ratio that could provide a ground truth. We then analyzed actual protein activities reported by a single chain biosensor for the guanine exchange factor (GEF) Asef, and a dual chain biosensor for the GTPase Cdc42. The reduction of edge artifacts revealed persistent Asef activity in a narrow band (∼640 nm wide) immediately adjacent to the cell edge. For Cdc42, the NCF method revealed an artifact that would have been obscured by traditional background subtraction approaches.