A red fluorescent genetically encoded biosensor for extracellular L-lactate
Nasu, Y.; Kamijo, Y.; Hashizume, R.; Sato, H.; Hori, Y.; Tomita, T.; Drobizhev, M.; Campbell, R. E.
Show abstract
L-Lactate, traditionally recognized as a waste product of metabolism, is now appreciated as a key intercellular energy currency in mammals. To enable investigations of intercellular shuttling of L-lactate, we have previously reported eLACCO1.1, a green fluorescent genetically encoded biosensor for extracellular L-lactate. eLACCO1.1 enables cellular resolution imaging of extracellular L-lactate in cultured mammalian cells and brain tissue. However, eLACCO1.1 spectrally overlaps with commonly used optical biosensors and actuators, limiting its application for multiplexed imaging or combined use with optogenetic actuators. Here, we report a red fluorescent extracellular L-lactate biosensor, designated R-eLACCO2. R-eLACCO2 is the end-product of extensive directed evolution and exhibits a large fluorescence response to L-lactate with high molecular specificity in vitro. We demonstrate that R-eLACCO2 with optimized leader and anchor sequences shows a large fluorescence change in response to extracellular L-lactate on the membrane of live mammalian cells. R-eLACCO2 should enable multicolor imaging of extracellular L-lactate in combination with other fluorescent probes and optogenetic actuators.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
Similar papers in this journal
- A bright and high-performance genetically encoded Ca2+ indicator based on mNeonGreen fluorescent protein 97%
- Visualizing PINK1 Activity Dynamics in Single Cells with a Phase Separation-Based Kinase Activity Reporter 94%
- iGIST - a kinetic bioassay for pertussis toxin based on its effect on inhibitory GPCR signaling 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.