Engineering of Genetically Encoded Bright Near-Infrared Fluorescent Voltage Indicator
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ijms-26-01442.pdf
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2.58 MB
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Author(s)
Xiao, Xian
Yang, Aimei
Zhang, Hanbin
Park, Demian
Wang, Yangdong
Szabo, Balint
Boyden, Edward S.
Piatkevich, Kiryl D.
Date Issued
February 8, 2025
Journal
Department of Brain and Cognitive Sciences
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Xiao, X.; Yang, A.; Zhang, H.; Park, D.; Wang, Y.; Szabo, B.; Boyden, E.S.; Piatkevich, K.D. Engineering of Genetically Encoded Bright Near-Infrared Fluorescent Voltage Indicator. Int. J. Mol. Sci. 2025, 26, 1442.
Version
Final published version
Abstract
Genetically encoded voltage indicators (GEVIs) allow for the cell-type-specific real-time imaging of neuronal membrane potential dynamics, which is essential to understanding neuronal information processing at both cellular and circuit levels. Among GEVIs, near-infrared-shifted GEVIs offer faster kinetics, better tissue penetration, and compatibility with optogenetic tools, enabling all-optical electrophysiology in complex biological contexts. In our previous work, we employed the directed molecular evolution of microbial rhodopsin Archaerhodopsin-3 (Arch-3) in mammalian cells to develop a voltage sensor called Archon1. Archon1 demonstrated excellent membrane localization, signal-to-noise ratio (SNR), sensitivity, kinetics, and photostability, and full compatibility with optogenetic tools. However, Archon1 suffers from low brightness and requires high illumination intensities, which leads to tissue heating and phototoxicity during prolonged imaging. In this study, we aim to improve the brightness of this voltage sensor. We performed random mutation on a bright Archon derivative and identified a novel variant, monArch, which exhibits satisfactory voltage sensitivity (4~5% ΔF/FAP) and a 9-fold increase in basal brightness compared with Archon1. However, it is hindered by suboptimal membrane localization and compromised voltage sensitivity. These challenges underscore the need for continued optimization to achieve an optimal balance of brightness, stability, and functionality in rhodopsin-based voltage sensors.
MIT Department
Massachusetts Institute of Technology. Center for Neurobiological Engineering
Program in Media Arts and Sciences (Massachusetts Institute of Technology)
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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DOI of Published Version
https://doi.org/10.3390/ijms26041442
