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Membrane potential sensing: Material design and method development for single particle optical electrophysiology

机译:Membrane potential sensing: Material design and method development for single particle optical electrophysiology

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We review the development of "single " nanoparticle-based inorganic and organic voltage sensors, which can eventually become a viable tool for "non-genetic optogenetics. " The voltage sensing is accomplished with optical imaging at the fast temporal response and high spatial resolutions in a large field of view. Inorganic voltage nanosensors utilize the Quantum Confined Stark Effect (QCSE) to sense local electric fields. Engineered nanoparticles achieve substantial single-particle voltage sensitivity (similar to 2% Delta lambda spectral Stark shift up to similar to 30% Delta F/F per 160 mV) at room temperature due to enhanced charge separation. A dedicated home-built fluorescence microscope records spectrally resolved images to measure the QCSE induced spectral shift at the single-particle level. Biomaterial based surface ligands are designed and developed based on theoretical simulations. The hybrid nanobiomaterials satisfy anisotropic facet-selective coating, enabling effective compartmentalization beyond non-specific staining. Self-spiking- and patched-HEK293 cells and cortical neurons, when stained with hybrid nanobiomaterials, show clear photoluminescence intensity changes in response to membrane potential (MP) changes. Organic voltage nanosensors based on polystyrene beads and nanodisk technology utilize Fluorescence (Forster) Resonance Energy Transfer (FRET) to sense local electric fields. Voltage sensing FRET pairs achieve voltage sensitivity up to similar to 35% Delta F/F per 120 mV in cultures. Non-invasive MP recording from individual targeted sites (synapses and spines) with nanodisks has been realized. However, both of these QCSE- and FRET-based voltage nanosensors yet need to reach the milestone of recording individual action potentials from individual targeted sites. (c) 2022 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license(http://creativecommons.org/licenses/by/4.0/).

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