Magnetoelectric nanodiscs enable wireless transgene-free neuromodulation.


Journal

Nature nanotechnology
ISSN: 1748-3395
Titre abrégé: Nat Nanotechnol
Pays: England
ID NLM: 101283273

Informations de publication

Date de publication:
11 Oct 2024
Historique:
received: 17 01 2024
accepted: 02 09 2024
medline: 12 10 2024
pubmed: 12 10 2024
entrez: 11 10 2024
Statut: aheadofprint

Résumé

Deep brain stimulation with implanted electrodes has transformed neuroscience studies and treatment of neurological and psychiatric conditions. Discovering less invasive alternatives to deep brain stimulation could expand its clinical and research applications. Nanomaterial-mediated transduction of magnetic fields into electric potentials has been explored as a means for remote neuromodulation. Here we synthesize magnetoelectric nanodiscs (MENDs) with a core-double-shell Fe

Identifiants

pubmed: 39394431
doi: 10.1038/s41565-024-01798-9
pii: 10.1038/s41565-024-01798-9
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : U.S. Department of Health & Human Services | National Institutes of Health (NIH)
ID : DP1-AT011991
Organisme : U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke (NINDS)
ID : R01-NS115576
Organisme : National Science Foundation (NSF)
ID : Graduate Research Fellowhsip

Informations de copyright

© 2024. The Author(s).

Références

Lozano, A. M. et al. Deep brain stimulation: current challenges and future directions. Nat. Rev. Neurol. 15, 148–160 (2019).
doi: 10.1038/s41582-018-0128-2 pubmed: 30683913 pmcid: 6397644
Klomjai, W., Katz, R. & Lackmy-Vallée, A. Basic principles of transcranial magnetic stimulation (TMS) and repetitive TMS (rTMS). Ann. Phys. Rehab. Med. 58, 208–213 (2015).
doi: 10.1016/j.rehab.2015.05.005
Violante, I. R. et al. Non-invasive temporal interference electrical stimulation of the human hippocampus. Nat. Neurosci. 26, 1994–2004 (2023).
doi: 10.1038/s41593-023-01456-8 pubmed: 37857775 pmcid: 10620081
Grossman, N. et al. Noninvasive deep brain stimulation via temporally interfering electric fields. Cell 169, 1029–1041.e1016 (2017).
Kennedy, J. E. High-intensity focused ultrasound in the treatment of solid tumours. Nat. Rev. Cancer 5, 321–327 (2005).
doi: 10.1038/nrc1591 pubmed: 15776004
Kennedy, J. E., ter Haar, G. R. & Cranston, D. High intensity focused ultrasound: surgery of the future? Br. J. Radiol. 76, 590–599 (2003).
doi: 10.1259/bjr/17150274 pubmed: 14500272
ter Haar, G. & Coussios, C. High intensity focused ultrasound: physical principles and devices. Int. J. Hyperth. 23, 89–104 (2007).
doi: 10.1080/02656730601186138
Marshel, J. H. et al. Cortical layer–specific critical dynamics triggering perception. Science 365, eaaw5202 (2019).
doi: 10.1126/science.aaw5202 pubmed: 31320556 pmcid: 6711485
Chen, R. et al. Deep brain optogenetics without intracranial surgery. Nat. Biotechnol. 39, 161–164 (2021).
doi: 10.1038/s41587-020-0679-9 pubmed: 33020604
Young, J., Wang, M.-T. & Brezovich, I. Frequency/depth-penetration considerations in hyperthermia by magnetically induced currents. Electron. Lett. 10, 358–359 (1980).
doi: 10.1049/el:19800255
Gregurec, D. et al. Magnetic vortex nanodiscs enable remote magnetomechanical neural stimulation. ACS Nano 14, 8036–8045 (2020).
doi: 10.1021/acsnano.0c00562 pubmed: 32559057 pmcid: 8592276
Su, C.-L. et al. Wireless neuromodulation in vitro and in vivo by intrinsic TRPC-mediated magnetomechanical stimulation. Commun. Biol. 5, 1166 (2022).
doi: 10.1038/s42003-022-04124-y pubmed: 36323817 pmcid: 9630493
Huang, H., Delikanli, S., Zeng, H., Ferkey, D. M. & Pralle, A. Remote control of ion channels and neurons through magnetic-field heating of nanoparticles. Nat. Nanotechnol. 5, 602–606 (2010).
doi: 10.1038/nnano.2010.125 pubmed: 20581833
Munshi, R. et al. Magnetothermal genetic deep brain stimulation of motor behaviors in awake, freely moving mice. eLife 6, e27069 (2017).
doi: 10.7554/eLife.27069 pubmed: 28826470 pmcid: 5779110
Chen, R., Romero, G., Christiansen, M. G., Mohr, A. & Anikeeva, P. Wireless magnetothermal deep brain stimulation. Science 347, 1477–1480 (2015).
doi: 10.1126/science.1261821 pubmed: 25765068
Lee, J.-H. et al. Exchange-coupled magnetic nanoparticles for efficient heat induction. Nat. Nanotechnol. 6, 418–422 (2011).
doi: 10.1038/nnano.2011.95 pubmed: 21706024
Rao, S. et al. Remotely controlled chemomagnetic modulation of targeted neural circuits. Nat. Nanotechnol. 14, 967–973 (2019).
doi: 10.1038/s41565-019-0521-z pubmed: 31427746 pmcid: 6778020
Park, J. et al. In situ electrochemical generation of nitric oxide for neuronal modulation. Nat. Nanotechnol. 15, 690–697 (2020).
doi: 10.1038/s41565-020-0701-x pubmed: 32601446 pmcid: 7415650
Zhang, E. et al. Magnetic-field-synchronized wireless modulation of neural activity by magnetoelectric nanoparticles. Brain Stim. 15, 1451–1462 (2022).
doi: 10.1016/j.brs.2022.10.004
Kozielski, K. L. et al. Nonresonant powering of injectable nanoelectrodes enables wireless deep brain stimulation in freely moving mice. Sci. Adv. 7, eabc4189 (2021).
doi: 10.1126/sciadv.abc4189 pubmed: 33523872 pmcid: 7806222
Chen, J. C. et al. A wireless millimetric magnetoelectric implant for the endovascular stimulation of peripheral nerves. Nat. Biomed. Eng. 6, 706–716 (2022).
doi: 10.1038/s41551-022-00873-7 pubmed: 35361934 pmcid: 9213237
Singer, A. et al. Magnetoelectric materials for miniature, wireless neural stimulation at therapeutic frequencies. Neuron 107, 631–643. e635 (2020).
doi: 10.1016/j.neuron.2020.05.019 pubmed: 32516574 pmcid: 7818389
Yu, Z. et al. Magnetoelectric bio-implants powered and programmed by a single transmitter for coordinated multisite stimulation. IEEE J. Solid-State Circuits 57, 818–830 (2021).
doi: 10.1109/JSSC.2021.3129993 pubmed: 36275505 pmcid: 9581110
Wang, P. et al. Colossal magnetoelectric effect in core–shell magnetoelectric nanoparticles. Nano Lett. 20, 5765–5772 (2020).
doi: 10.1021/acs.nanolett.0c01588 pubmed: 32639738
Odkhuu, D., Taivansaikhan, P., Yun, W. S. & Hong, S. C. A first-principles study of magnetostrictions of Fe
doi: 10.1063/1.4863811
Szymczak, H. & Żuberek, R. Surface magnetostriction. Acta Phys. Pol. A 83, 651–659 (1993).
doi: 10.12693/APhysPolA.83.651
Szewczyk, R. Model of the magnetostrictive hysteresis loop with local maximum. Materials 12, 105 (2018).
doi: 10.3390/ma12010105 pubmed: 30598008 pmcid: 6337399
Walther, T., Straube, U., Köferstein, R. & Ebbinghaus, S. G. Hysteretic magnetoelectric behavior of CoFe
doi: 10.1039/C6TC00995F
Yang, H., Zhang, G. & Lin, Y. Enhanced magnetoelectric properties of the laminated BaTiO
doi: 10.1016/j.jallcom.2015.05.020
Wang, W., Yang, H., Xian, T. & Yu, R. Observation of abnormal magnetoelectric behavior in 0-3 type CoFe
doi: 10.1016/j.cplett.2014.10.068
Neudorfer, C. et al. Kilohertz-frequency stimulation of the nervous system: a review of underlying mechanisms. Brain Stim. 14, 513–530 (2021).
doi: 10.1016/j.brs.2021.03.008
Jensen, A. L. & Durand, D. M. High frequency stimulation can block axonal conduction. Exp. Neurol. 220, 57–70 (2009).
doi: 10.1016/j.expneurol.2009.07.023 pubmed: 19660453 pmcid: 2761511
Kandel, E. R. et al. Principles of Neural Science Vol. 4 (McGraw-Hill, 2000).
Chu, C.-H. et al. Beyond the Debye length in high ionic strength solution: direct protein detection with field-effect transistors (FETs) in human serum. Sci. Rep. 7, 1–15 (2017).
doi: 10.1038/s41598-017-05426-6
Pfeiffer, C. et al. Interaction of colloidal nanoparticles with their local environment: the (ionic) nanoenvironment around nanoparticles is different from bulk and determines the physico-chemical properties of the nanoparticles. J. R. Soc. Interface 11, 20130931 (2014).
doi: 10.1098/rsif.2013.0931 pubmed: 24759541 pmcid: 4032524
Gunaydin, L. A. et al. Natural neural projection dynamics underlying social behavior. Cell 157, 1535–1551 (2014).
doi: 10.1016/j.cell.2014.05.017 pubmed: 24949967 pmcid: 4123133
Tsai, H.-C. et al. Phasic firing in dopaminergic neurons is sufficient for behavioral conditioning. Science 324, 1080–1084 (2009).
doi: 10.1126/science.1168878 pubmed: 19389999 pmcid: 5262197
Navarro-Zaragoza, J. et al. Naloxone-induced conditioned place aversion score and extinction period are higher in C57BL/6J morphine-dependent mice than in Swiss: role of HPA axis. Pharmacol. Biochem. Behav. 201, 173106 (2021).
doi: 10.1016/j.pbb.2021.173106 pubmed: 33444599
Goltseker, K. & Barak, S. Flood-conditioned place aversion as a novel non-pharmacological aversive learning procedure in mice. Sci. Rep. 8, 1–9 (2018).
doi: 10.1038/s41598-018-25568-5
Mahlknecht, P., Foltynie, T., Limousin, P. & Poewe, W. How does deep brain stimulation change the course of Parkinson’s disease? Mov. Disord. 37, 1581–1592 (2022).
doi: 10.1002/mds.29052 pubmed: 35560443 pmcid: 9545904
Meissner, W. et al. Deep brain stimulation of subthalamic neurons increases striatal dopamine metabolism and induces contralateral circling in freely moving 6-hydroxydopamine-lesioned rats. Neurosci. Lett. 328, 105–108 (2002).
doi: 10.1016/S0304-3940(02)00463-9 pubmed: 12133566
Papale, A. E. & Hooks, B. M. Circuit changes in motor cortex during motor skill learning. Neuroscience 368, 283–297 (2018).
doi: 10.1016/j.neuroscience.2017.09.010 pubmed: 28918262
Arcot Desai, S., Gutekunst, C.-A., Potter, S. M. & Gross, R. E. Deep brain stimulation macroelectrodes compared to multiple microelectrodes in rat hippocampus. Front. Neuroeng. 7, 16 (2014).
doi: 10.3389/fneng.2014.00016 pubmed: 24971060 pmcid: 4054883
Carafoli, E. Calcium pump of the plasma membrane. Physiol. Rev. 71, 129–153 (1991).
doi: 10.1152/physrev.1991.71.1.129 pubmed: 1986387
Jeffs, G. J., Meloni, B. P., Bakker, A. J. & Knuckey, N. W. The role of the Na
doi: 10.1016/j.jocn.2006.07.013 pubmed: 17430774
Lytton, J. in Handbook of Neurochemistry and Molecular Neurobiology: Neural Membranes and Transport. (eds Lajtha, A. & Reith, M. E. A) 225–241 (Springer, 2007).
Lyon, K. A. & Allen, N. J. From synapses to circuits, astrocytes regulate behavior. Front. Neural Circuits 15, 786293 (2022).
doi: 10.3389/fncir.2021.786293 pubmed: 35069124 pmcid: 8772456
Chai, H. et al. Neural circuit-specialized astrocytes: transcriptomic, proteomic, morphological, and functional evidence. Neuron 95, 531–549. e539 (2017).
doi: 10.1016/j.neuron.2017.06.029 pubmed: 28712653 pmcid: 5811312
Ball, J. B., Green-Fulgham, S. M. & Watkins, L. R. Mechanisms of microglia-mediated synapse turnover and synaptogenesis. Prog. Neurobiol. 218, 102336 (2022).
doi: 10.1016/j.pneurobio.2022.102336 pubmed: 35940391
Magee, J. C. Dendritic integration of excitatory synaptic input. Nat. Rev. Neurosci. 1, 181–190 (2000).
doi: 10.1038/35044552 pubmed: 11257906
Bazant, M. Z., Thornton, K. & Ajdari, A. Diffuse-charge dynamics in electrochemical systems. Phys. Rev. E 70, 021506 (2004).
doi: 10.1103/PhysRevE.70.021506
Mushtaq, F. et al. Magnetoelectrically driven catalytic degradation of organics. Adv. Mater. 31, 1901378 (2019).
doi: 10.1002/adma.201901378
Chen, L. et al. Continuous shape-and spectroscopy-tuning of hematite nanocrystals. Inorg. Chem. 49, 8411–8420 (2010).
doi: 10.1021/ic100919a pubmed: 20718439
Zhu, M., Wang, Y., Meng, D., Qin, X. & Diao, G. Hydrothermal synthesis of hematite nanoparticles and their electrochemical properties. J. Phys. Chem. C 116, 16276–16285 (2012).
doi: 10.1021/jp304041m
Pandey, P. et al. Single-entity approach to investigate surface charge enhancement in magnetoelectric nanoparticles induced by AC magnetic field stimulation. ACS Sens. 6, 340–347 (2020).
doi: 10.1021/acssensors.0c00664 pubmed: 32449356
Ramos, A., Morgan, H., Green, N. G. & Castellanos, A. Ac electrokinetics: a review of forces in microelectrode structures. J. Phys. D 31, 2338 (1998).
doi: 10.1088/0022-3727/31/18/021
Ramos, A., Morgan, H., Green, N. G. & Castellanos, A. AC electric-field-induced fluid flow in microelectrodes. J. Colloid Interface Sci. 217, 420–422 (1999).
doi: 10.1006/jcis.1999.6346 pubmed: 10469552
Green, N. G., Ramos, A., González, A., Morgan, H. & Castellanos, A. Fluid flow induced by nonuniform ac electric fields in electrolytes on microelectrodes. I. Experimental measurements. Phys. Rev. E 61, 4011 (2000).
doi: 10.1103/PhysRevE.61.4011
Shilov, V., Delgado, A., Gonzalez-Caballero, F. & Grosse, C. Thin double layer theory of the wide-frequency range dielectric dispersion of suspensions of non-conducting spherical particles including surface conductivity of the stagnant layer. Colloids Surf. A 192, 253–265 (2001).
doi: 10.1016/S0927-7757(01)00729-4
Abdelfattah, A. S. et al. Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator. Neuron 111, 1547–1563. e1549 (2023).
doi: 10.1016/j.neuron.2023.03.009 pubmed: 37015225 pmcid: 10280807
Abdelfattah, A. S. et al. Bright and photostable chemigenetic indicators for extended in vivo voltage imaging. Science 365, 699–704 (2019).
doi: 10.1126/science.aav6416 pubmed: 31371562
Chen, T. et al. Ultrasensitive fluorescent proteins for imaging neuronal activity. Nature 499, 295–300 (2013).
Keith, B., Franklin, M. & Paxinos, G. The Mouse Brain in Stereotaxic Coordinates, 3rd Edn (Elsevier Science Oxford, 2008).
Kim, Y. J. et al. Source data for ‘Magnetoelectric nanodiscs enable wireless transgene-free neuromodulation’. Figshare https://doi.org/10.6084/m9.figshare.26771680 (2024).
Kim, Y. J. et al. Source code for ‘Magnetoelectric nanodiscs enable wireless transgene-free neuromodulation’ Figshare https://doi.org/10.6084/m9.figshare.26778310 (2024).

Auteurs

Ye Ji Kim (YJ)

Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Noah Kent (N)

Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Emmanuel Vargas Paniagua (E)

Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Nicolette Driscoll (N)

Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Anthony Tabet (A)

Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Florian Koehler (F)

Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA.

Elian Malkin (E)

Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Department Engineering in Computation and Cognition, Massachusetts Institute of Technology, Cambridge, MA, USA.

Ethan Frey (E)

Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Marie Manthey (M)

Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Atharva Sahasrabudhe (A)

Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.

Taylor M Cannon (TM)

Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Keisuke Nagao (K)

Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.
Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

David Mankus (D)

Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Margaret Bisher (M)

Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Giovanni de Nola (G)

Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Abigail Lytton-Jean (A)

Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.

Lorenzo Signorelli (L)

Department of Chemistry and Pharmacy, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany.

Danijela Gregurec (D)

Department of Chemistry and Pharmacy, Friedrich-Alexander University of Erlangen-Nuremberg, Erlangen, Germany.

Polina Anikeeva (P)

Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. anikeeva@mit.edu.
Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, USA. anikeeva@mit.edu.
McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA, USA. anikeeva@mit.edu.
Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA. anikeeva@mit.edu.

Classifications MeSH