Nature MethodsNeurosciencePeer-reviewed journal article
Genetically encoded biosensor for fluorescence lifetime imaging of PTEN dynamics in the intact brain
Tomer KaganiD, Matan GabayiD, Aasha Meenakshisundaram, Yossi Levi, Sharbel Eid, Nikol Malchenko, Maya Maman, Anat NitzaniD, Luca RavottoiD, Ronen Zaidel‐BariD, Britta Johanna EickholtiD, Maayan GaliD, Tal LaviviD
Abstract
The phosphatase and tensin homolog (PTEN) is a vital signaling protein which maintains an inhibitory brake that is critical for cellular metabolism, proliferation, and growth. The importance of PTEN signaling is evident from the broad spectrum of human pathologies associated with its loss of function. Moreover, loss or gain of PTEN function in animal models leads to aberrant cellular morphology, function, and metabolic regulation. However, despite the important role of PTEN signaling, there is currently no method to dynamically monitor its activity with cellular specificity within intact biological systems. Here, we describe the development of a novel PTEN biosensor, optimized for two-photon fluorescence lifetime imaging microscopy (2pFLIM). This biosensor is designed to measure PTEN activity within intact cells, tissues, and organisms. Our approach is based on monitoring FRET-dependent changes in PTEN conformation, which serves as a proxy for the activity state in living cells. We identify a point mutation that allow us to express this biosensor with minimal interference to endogenous PTEN signaling and cellular function. We demonstrate the utility of imaging PTEN signaling in cell lines, developing C. elegans, and in the living mouse brain. To complement this approach, we developed a red-shifted PTEN sensor variant that permits simultaneous imaging with GFP-based sensors. Finally, we use in vivo PTEN imaging in the mouse brain to identify cell-type specific dynamics of PTEN activity in excitatory and inhibitory cortical cells. In summary, our approach enables dynamic imaging of PTEN activity in vivo with unprecedented spatial and temporal resolution.
- organism: mouse
- assay: imaging
- research focus: protein structure prediction
- approach: experimental assay
- Citations
- 24
- FWCI
- 9.01
- Field percentile
- top 1%
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