Directly adopting inverse biosensors to image live cell enzyme activities in nanodomains

Many biochemical pathways can be monitored by outfitting molecular switches with reporting mechanisms such as fluorescence. The output of these biosensors can either increase or decrease upon target activation. Both types can report average relative changes in time. But a naïve imaging of inverse biosensors, which gives readout decrease, will form nonsensical images by giving low values to both the background and foreground. Thus, currently, superresolution enzyme activity imaging cannot follow the actions of those enzymes that require inverse biosensing. This is a significant obstacle for understanding the ways cells organize their signaling via nanodomains and compartments. We break this barrier and rationally develop a genetically encoded principle to quantify inverse biosensors at superresolution. We generate 3 distinct readout pairs and systematically illustrate previously hidden insights on 3 dynamic signaling hubs.