Issue 17, 2023

Bidirectional near-infrared regulation of motor behavior using orthogonal emissive upconversion nanoparticles

Abstract

Bidirectional optogenetic manipulation enables specific neural function dissection and animal behaviour regulation with high spatial–temporal resolution. It relies on the respective activation of two or more visible-light responsive optogenetic sensors, which inevitably induce signal crosstalk due to their spectral overlap, low photoactivation efficiency and potentially high biotoxicity. Herein, a strategy that combines dual-NIR-excited orthogonal emissive upconversion nanoparticles (OUCNPs) with a single dual-colour sensor, BiPOLES, is demonstrated to achieve bidirectional, crosstalk-free NIR manipulation of motor behaviour in vivo. Core@shell-structured OUCNPs with Tm3+ and Er3+ dopants in isolated layers exhibit orthogonal blue and red emissions in response to excitation at 808 and 980 nm, respectively. The OUCNPs subsequently activate BiPOLES-expressing excitatory cholinergic motor neurons in C. elegans, leading to significant inhibition and excitation of motor neurons and body bends, respectively. Importantly, these OUCNPs exhibit negligible toxicity toward neural development, motor function and reproduction. Such an OUCNP–BiPOLES system not only greatly facilitates independent, bidirectional NIR activation of a specific neuronal population and functional dissection, but also greatly simplifies the bidirectional NIR optogenetics toolset, thus endowing it with great potential for flexible upconversion optogenetic manipulation.

Graphical abstract: Bidirectional near-infrared regulation of motor behavior using orthogonal emissive upconversion nanoparticles

Supplementary files

Article information

Article type
Paper
Submitted
02 Jan 2023
Accepted
06 Mar 2023
First published
22 Mar 2023

Nanoscale, 2023,15, 7845-7853

Bidirectional near-infrared regulation of motor behavior using orthogonal emissive upconversion nanoparticles

J. Guo, L. Chen, F. Xiong, Y. Zhang, R. Wang, X. Zhang, Q. Wen, S. Gao and Y. Zhang, Nanoscale, 2023, 15, 7845 DOI: 10.1039/D3NR00009E

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