Bioinspired nanoantennas for opsin sensitization in optogenetic applications: A theoretical investigation

被引:2
作者
Keck C.H.C. [1 ,3 ]
Rommelfanger N.J. [2 ,3 ]
Ou Z. [1 ,3 ]
Hong G. [1 ,3 ]
机构
[1] Department of Materials Science and Engineering, Stanford University, Stanford, 94305, CA
[2] Department of Applied Physics, Stanford University, Stanford, 94305, CA
[3] Wu Tsai Neurosciences Institute, Stanford University, Stanford, 94305, CA
来源
Multifunctional Materials | 2021年 / 4卷 / 02期
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
aluminum plasmonics; bioinspired materials; opsins; plasmonic enhancement; transcranial optogenetics;
D O I
10.1088/2399-7532/abf0f9
中图分类号
学科分类号
摘要
Opsins with high sensitivity are desired to reduce dependence on optical fibers and enable deep-brain optogenetic stimulation through the intact scalp and skull, while minimizing brain tissue heating and the associated biasing of neural activity. While optimized opsin engineering has produced ultrasensitive and red-shifted opsins suitable for transcranial optogenetic stimulation, further improvements in sensitivity are throttled by biological limitations. Nanostructures are capable of generating near-field intensity enhancements of over 104, but thus far nanomaterials have not been applied to amplify local light intensity for optogenetic applications. In this manuscript, we propose the use of bowtie nanoantennas for local enhancement of 470 nm light to sensitize channelrhodopsin (ChR2) to low light intensities. We begin with a comparison of the near-field intensity enhancement offered by different metals at 470 nm, before selecting aluminum as the optimal material. Next, we tune the geometric parameters of aluminum bowtie nanoantennas to maximize the intensity enhancement at 470 nm. We further optimize enhancement by constructing bowtie nanoantenna arrays inspired by patterns occurring in biology, obtaining intensity enhancements up to a factor of 5000. Monte Carlo simulations suggest that transcranial 470 nm illumination of only 50 mW mm-2 is capable of stimulating bowtie-sensitized ChR2 in the deep brain (5 mm) in mice, enabling minimally invasive deep-brain stimulation with opsins found in the traditional optogenetic toolbox. This computation-guided optical antenna engineering approach opens opportunities for designing multifunctional materials for enhancing the efficiency of optogenetic neuromodulation, optical neural activity imaging, and highly localized electrical microstimulation in the brain. © 2021 IOP Publishing Ltd and SISSA Medialab srl.
引用
收藏
相关论文
共 61 条
  • [1] Boyden E S, Zhang F, Bamberg E, Nagel G, Deisseroth K, Millisecond-Timescale, genetically targeted optical control of neural activity, Nat. Neurosci, 8, pp. 1263-1268, (2005)
  • [2] Deisseroth K, Optogenetics: 10 years of microbial opsins in neuroscience, Nat. Neurosci, 18, pp. 1213-1225, (2015)
  • [3] Doucette E, Merfeld E, Leblanc H, Monasterio A, Cincotta C, Grella S L, Logan J, Ramirez S, Social behavior in mice following chronic optogenetic stimulation of hippocampal engrams, Neurobiol. Learn. Mem, 176, (2020)
  • [4] Klapoetke N C, Et al., Independent optical excitation of distinct neural populations, Nat. Methods, 11, pp. 338-346, (2014)
  • [5] Wiegert J S, Mahn M, Prigge M, Printz Y, Yizhar O, Silencing neurons: Tools, applications, and experimental constraints, Neuron, 95, pp. 504-529, (2017)
  • [6] Owen S F, Liu M H, Kreitzer A C, Thermal constraints on in vivo optogenetic manipulations, Nat. Neurosci, 22, pp. 1061-1065, (2019)
  • [7] Tye K M, Deisseroth K, Optogenetic investigation of neural circuits underlying brain disease in animal models, Nat. Rev. Neurosci, 13, pp. 251-266, (2012)
  • [8] Sparta D R, Stamatakis A M, Phillips J L, Hovelso N, van Zessen R, Stuber G D, Construction of implantable optical fibers for long-Term optogenetic manipulation of neural circuits, Nat. Protocols, 7, (2012)
  • [9] Polikov V S, Tresco P A, Reichert W M, Response of brain tissue to chronically implanted neural electrodes, J. Neurosci. Methods, 148, (2005)
  • [10] Bedbrook C N, Yang K K, Robinson J E, Mackey E D, Gradinaru V, Arnold F H, Machine learning-guided channelrhodopsin engineering enables minimally invasive optogenetics, Nat. Methods, 16, pp. 1176-1184, (2019)