Subcellular imaging of lipids and sugars using genetically encoded proximity sensors
The lipid composition of cells varies widely across organelles and between individual membrane leaflets. Transport proteins are thought to generate this heterogeneity, but measuring their functions in vivo has been hampered by limited tools for imaging lipids at relevant spatial resolutions. Here we present fluorogen-activating coincidence encounter sensing (FACES), a chemogenetic tool capable of quantitatively imaging subcellular lipid pools and reporting their transbilayer orientation in living cells. FACES combines bioorthogonal chemistry with genetically encoded fluorogen-activating proteins (FAPs) for reversible proximity sensing of conjugated molecules. We first apply this approach to identify roles for lipid transfer proteins that traffic phosphatidylcholine pools between the ER and mitochondria. We then show that transmembrane domain-containing FAPs can reveal the membrane asymmetry of multiple lipid classes in the trans-Golgi network and be used to investigate the mechanisms that generate it. Lastly, we demonstrate FACES can be applied to measure other molecule classes, like sugars.