Preprint Subcellular imaging of lipids and sugars using genetically encoded proximity sensors, 2024, Moore et al.

Subcellular imaging of lipids and sugars using genetically encoded proximity sensors
William M. Moore; Roberto J. Brea; Caroline Knittel; Ellen Wrightsman; Brandon Hui; Jinchao Loui; Christelle F. Ancajas; Michael D. Best; Neal K. Devaraj; Itay Budin

Live cell imaging of lipids and other metabolites is a long-standing challenge in cell biology. Bioorthogonal labeling tools allow for the conjugation of fluorophores to several phospholipid classes, but cannot discern their trafficking between adjacent organelles or asymmetry across individual membrane leaflets.

Here we present fluorogen-activating coincidence 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 validate this approach for quantifying discrete phosphatidylcholine pools in the ER and mitochondria that are trafficked by lipid transfer proteins. We then show that transmembrane domain-containing FAPs can be used to reveal the membrane asymmetry of multiple lipid classes that are generated in the trans-Golgi network. Lastly, we show that FACES is a generalizable tool for subcellular bioorthogonal imaging by measuring changes in mitochondrial N-acetylhexosamine levels.

These results demonstrate the use of fluorogenic tags for spatially-defined molecular imaging.


Link | PDF (Preprint: BioRxiv) [Open Access]

 

https://en.wikipedia.org/wiki/Flippase
https://en.wikipedia.org/wiki/Phospholipid_scramblase