Magnetic Nanoparticle-Based Mechanical Stimulation for Restoration

Jan 17, 2017 - Techniques offering remote control of neural activity with high spatiotemporal resolution and specificity are invaluable for decipherin...
1 downloads 14 Views 4MB Size
Letter pubs.acs.org/NanoLett

Magnetic Nanoparticle-Based Mechanical Stimulation for Restoration of Mechano-Sensitive Ion Channel Equilibrium in Neural Networks Andy Tay†,‡ and Dino Di Carlo*,†,§,∥ †

Department of Bioengineering, University of California, Los Angeles, California 90025, United States Department of Biomedical Engineering, National University of Singapore, Singapore 117583 § California Nanosystems Institute, University of California, Los Angeles, California 90025, United States ∥ Jonsson Comprehensive Cancer Center, University of California, Los Angeles, California 90025, United States ‡

S Supporting Information *

ABSTRACT: Techniques offering remote control of neural activity with high spatiotemporal resolution and specificity are invaluable for deciphering the physiological roles of different classes of neurons in brain development and disease. Here, we first confirm that microfabricated substrates with enhanced magnetic field gradients allow for wireless stimulation of neural circuits dosed with magnetic nanoparticles using calcium indicator dyes. We also investigate the mechanism of mechano-transduction in this system and identify that N-type mechano-sensitive calcium ion channels play a key role in signal generation in response to magnetic force. We next applied this method for chronic stimulation of a fragile X syndrome (FXS) neural network model and found that magnetic force-based stimulation modulated the expression of mechano-sensitive ion channels which are out of equilibrium in a number of neurological diseases including FXS. This technique can serve as a tool for acute and chronic modulation of endogenous ion channel expression in neural circuits in a spatially localized manner to investigate a number of disease processes in the future. KEYWORDS: Magnetic stimulation, mechano-sensitive ion channels, neurons, magnetic nanoparticles

A

of magnetogenetics that utilizes magnetic forces to trigger Ca2+ influx by opening mechano-sensitive TRPV4 ion channels.8 Nonetheless, TRPV4 ion channel is sensitive to many stimuli such as heat, light and mechanical forces and it can be challenging to ensure that set-ups are consistent across experiments to generate reproducible results using this method. In addition, although the authors indicated that ferritin protein crystallized to exert mechanical forces on TRPV4 ion channels, it is expected that the exerted force would be small, raising questions about the origin of this effect (Table S1).9 Previously, we described a method for neural stimulation using microfabricated magnetic substrates with high local field gradients and MNPs that generated forces several orders of magnitude higher compared to reported approaches.10 Here, we performed a series of experiments to provide evidence supporting our previous hypothesis that MNPs transduced magnetic forces into mechanical opening of N-type mechanosensitive Ca2+ channels. Making use of the property of neural networks to regulate their ratio of excitatory to inhibitory ion channels/receptors following stimulation, we also demonstrated the utility of the magnetic platform for MNP-mediated restoration of mechano-sensitive ion channel equilibrium

s calcium (Ca2+) signaling is known to affect processes such as gene expression and synaptic plasticity,1 there has been significant interest to modulate Ca2+ influx for the study of neural communication. Electrodes, chemicals, and ultrasound are conventional tools for global neural stimulation and are unsuitable to study specific classes of neurons.2 Progress in optogenetics can now enable remote and targeted neural network activation/inhibition although optical approaches are still limited by poor penetration of visible light into deep tissues.3 Recently, it has also been discovered that acute and chronic manipulation of neural circuits with light surprisingly produced different behavioral changes in rats and zebra finches possibly due to network compensation, thus complicating interpretations of data obtained via optogenetics.4 To address the limitations of existing techniques, new methods are being developed to capitalize on the sensitivity of ion channels to heat and/or mechanical forces, especially induced through magnetic field driven stimuli, to perform noninvasive neuro-stimulation.5,6 Stanley et al. demonstrated the use of alternating magnetic field to generate heat for opening TRPV1 ion channels to induce/inhibit feeding behaviors in mice.7 It remains a concern, however, that thermogenetics can damage tissue due to sustained heating, heating from internalized magnetic nanoparticles (MNPs), and heat diffusion to nontargeted sites at noxiously high temperatures of 43 °C. Wheeler et al. recently introduced the concept © XXXX American Chemical Society

Received: October 6, 2016 Revised: January 10, 2017 Published: January 17, 2017 A

DOI: 10.1021/acs.nanolett.6b04200 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

Figure 1. Magnetic technique and mechanism for acute stimulation of neural networks. (a) Schematic of the technique. Two week old neurons seeded beside magnetic elements with high local field gradients are stimulated with MNPs and a permanent magnet to induce calcium influx. (b) Time-lapse images show an increase in calcium fluorescence signals in (i) the cell body and (ii) axonal boutons where presynaptic terminals are located. (c) Magnetic stimulation leads to influx of calcium primarily from the extracellular environment. (d) Magnetic forces increased calcium spiking in the presence of bicuculline, suggesting that this technique is not neurotransmitter-mediated and does not inactivate inhibitory ion channels for calcium influx. (e) The amplitude of the magnetic force/neuron shared a sigmoidal relationship to the peak ΔF/F0, suggesting the possibility of controlling stimulation dosage by changing the probability of ion channel opening with different force magnitudes. Magnetic stimulation induced ∼20% increase in average ΔF/F0 even in the presence of (f) TTX, showing that voltage-gated ion channels were not activated. (g) Inhibition with ωconotoxin GVIA quenched calcium influx even after washing, supporting that mechano-sensitive N-type calcium channels were involved. (h) Magnetic stimulation was not temperature-sensitive, hence ruling out the possibility of activating TRP ion channels that are heat/mechano-sensitive. (i) Three week old neurons experience less calcium influx with magnetic stimulation.

B

DOI: 10.1021/acs.nanolett.6b04200 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

Figure 2. Magnetic forces reduce the expressions of excitatory N-type Ca2+ channels in an FXS neural network model following chronic stimulations. (a) FXS model neurons express more N-type calcium ion channels and with age, there is a decrease in channel expression. (b) Confocal images show immunostained N-type calcium ion channels in the FXS model and control neurons. (c) Schematic shows the sequence of chronic stimulation. (d) FXS model neurons chronically stimulated with magnetic forces experience decrease in N-type calcium ion channel expression and the effects are sustainable for at least 4 days (day 8−12). Confocal images showing (e) FXS model neurons and (f) FXS model neurons after chronic stimulation. An evident decrease in N-type calcium ion channel florescent intensity is observed in the latter.

intracellular sources.12 To further confirm, we also performed magnetic stimulation in the presence of 3 μM of bicuculline (EC50) (Figure S5a), an inhibitor of γ-aminobutyric (GABAA) receptor that is expressed widely in the brain, and still observed high Ca2+ spiking frequencies in the neurons upon magnetic stimulation (Figure 1d). These two experiments show that magnetically induced Ca2+ influx was not modulated by Gprotein and GABAA antagonist. We rationalized that if magnetic forces were able to increase ΔF/F0 (change in fluorescence over background fluorescence) in the presence of bicuculline, it would also mean that magnetic stimulation did not inactivate this major class of inhibitory receptor. Next we determined whether magnetic forces activated excitatory ion channels. We found that the amplitude of the magnetic forces (see method in Figure S6) shared a skewed sigmoidal relationship to the Ca2+ fluorescence signals (Figure 1e). The amplitude of Ca2+ fluorescence signals is a product of the conductance (g), number density (N), and open probability (Popen) of ion channels. In order to change the conductance of the ion channel, the permeation pore that is a highly conserved structure must be modified and structural changes usually result in blocking that enhanced permeability.13 We also did not expect and observe any changes in the ion channel number density from acute stimulation as the time scale during stimulation (∼5−10 min) is much less than the time (∼1 hr)

following chronic mechanical stimulation in fragile X syndrome model (FXS) neural networks, which initially had elevated density of N-type mechano-sensitive Ca2+ channels. Remote Control of Calcium Influx Using Magnetic Forces. Neurons were grown on microfabricated substrates that produce high local magnetic field gradients and stimulated with starch-coated MNPs attracted by a neodymium magnet (Figure 1a, see reason for choice of MNPs in Figure S1). We identified, using flow cytometry (Figure S2h) and confocal imaging (Figure S2i), that starch-coated MNPs preferentially localized at the cell membrane rather than being internalized. Magnetic stimulation was found to trigger Ca2+ influx in cell bodies (Figure 1bi) and axons/boutons (Figure 1bii, Video S1) with a temporal resolution on the second scale (Figure S3b). The ability to stimulate neural networks and not just individual neurons is crucial as the network paradigm gains traction in the study of the brain.11 Mechanism of Stimulation. We first investigated the source of Ca2+ influx and found that when extracellular Ca2+ was depleted with EGTA or when there was no extracellular Ca2+, the fluorescence signal was quenched, whereas when intracellular Ca2+ was depleted with thapsigargin there was only a delay in the increase in fluorescence intensities (Figure 1c). This suggests that magnetically induced Ca2+ influx was not Gprotein mediated, which typically involves release of Ca2+ from C

DOI: 10.1021/acs.nanolett.6b04200 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters needed for ion channel transcription/translation. Hence, we reasoned that the applied forces enhanced the open probability of the ion channels, thereby facilitating Ca2+ influx that is also supported by previous studies.14 The sigmoidal relationship between force amplitude and calcium fluorescence signals has been previously observed in mechano-sensitive ion channels,14 suggesting to us that magnetic forces might have activated mechano-sensitive Ca2+ channels. This hypothesis was also motivated by our observation that starch-coated MNPs preferentially localized to the membrane, rather than being internalized (Figure S2h,i), where the membrane-bound MNPs could stretch the lipid membrane to increase Popen for mechano-sensitive ion channels. To investigate whether our method of stimulation was voltage-dependent, we first added 1 μM tetrodotoxin (TTX), a highly specific inhibitor of voltage-gated sodium channels involved in action potential propagation. We observed apparent stimulatory effects due to magnetic forces even with TTX (Figure 1f). As neurons express many types of mechanosensitive ion channels (Table S2), we thus attempted to identify the type of known channel that contributed most to the Ca2+ influx. We first inhibited the N-type mechano-sensitive calcium ion channels with a highly specific inhibitor, the is, ω-conotoxin GVIA (1 μM) and found that this completely quenched the stimulatory effects of magnetic forces (Figure 1g). As L-type Ca2+ channel is reportedly mechano-sensitive but undergoes rapidly reversible inhibition by ω-conotoxin GVIA,15 we also performed a wash step, followed by subsequent monitoring of Ca2+ fluorescence signals. We did not observe any restoration of stimulatory effects of magnetic fields 15 min after washing away the neurotoxin (Figure 1g), suggesting that neural stimulation did not involve L-type Ca2+ channels. We next performed magnetic stimulation at different temperatures and found that the ΔF/F0 was not significantly dependent on temperature (Figure 1h), hence ruling out that we are activating temperature-sensitive TRP ion channels that are also a major class of mechano-sensitive ion channel. This finding is also aligned with the knowledge that static magnetic fields do not generate heat. The slightly lower calcium influx at lower temperatures could be due to lower metabolism for uptake and intracellular trafficking of calcium indicators. On the basis of the literature review summarized in Table S2, there are also a few other reasons why we believe we did not perturb TRP ion channels with magnetic stimulation: (1) TRP ion channels are mostly located on neurons in the dorsal root ganglion (DRG) where they play a role in touch/pain sensation while we cultured cortical neurons; (2) Chen et al. have shown that without genetically transfecting neurons to significantly increase their expression of TRPV ion channels, there was no Ca2+ influx even with thermal stimulation;16 (3) TRP ion channels possess intracellular Ankyrin domains that allow mechano-sensing by tethered channels and not the lipid bilayer model that we proposed.17 One other class of mechano-sensitive ion channel that the magnetic forces might have perturbed is PIEZO218 which is a newly discovered ion channel without any specific inhibitor yet.19 However, we reasoned that as they are mostly located on DRG neurons and have much lower expression in the cortices as compared to mechano-sensitive N-type calcium channels, their contribution to Ca2+ influx would be insignificant even if they were activated. Lastly, we wanted to understand whether the age of neurons, which we have found to affect their interactions with MNPs20

(Figure S7), could impact neural response to magnetic stimulation. We found that ΔF/F0 was lower for older neurons (Figure 1i), possibly due to differences in ion channel expression such as reduction in expression of mechano-sensitive N-type Ca2+ channel with age (Figure 2a).21 Collectively, our results support a mechanism whereby magnetic stimulation induced calcium influx through mechanically activating N-type excitatory Ca2+ channels that are mechano-sensitive. Our hypothesis is that the preferential location of starch-coated MNPs at the cell membrane could have led to membrane stretching and activation of these channels that are concentrated at the presynaptic terminals. We, however, do not rule out the possibility that other mechano-sensitive ion channels might have contributed to the Ca2+ influx as there could be unknown ion channels or undiscovered properties of known ion channels. Furthermore, mechano-sensing either by conformational changes in the lipid membrane or by tethered channels might not be mutually exclusive17 as magnetic forces might also indirectly induce cytoskeletal movements. Our argument is hence similar to thermo/magneto-genetics where it is expected that the applied heat or mechanical stimuli might also activate endogenous/ nontargeted heat/mechano-sensitive ion channels.7,8,22,23 Although there is a possibility that other mechano-sensitive ion channels might be activated by magnetic force-induced stretching of lipid membrane, we showed that the contribution by N-type Ca2+ channels was the largest (Figure 1g). We understand that there is a possibility that the applied magnetic forces could activate excitatory mechano-sensitive TRPV4, PIEZO1, and NMDA receptors. Future work is needed to apply a consistent method to quantify the force sensitivity of these different channels/receptors to compare or construct a model. It has been shown that a force of 3 pN could enhance the opening probability of mechano-sensitive ion channels in the hair cells of ears through mechanical amplification,24 suggesting that larger forces of 200−350 pN without amplification could be sufficient to generate the same effects on N-type Ca2+ channels present on each neuron. Therefore, based on the expression density, location, and responsive stimuli of the ion channels, we reasoned that it was most likely that magnetically induced Ca2+ influx was largely through the N-type Ca2+ channels. Modulation of Excitatory/Inhibitory Ion Channel Ratio in Neurons with Magnetic Stimulation. It is wellestablished that neurons in networks actively regulate their ratio of excitatory (such as N-type calcium channels) to inhibitory (such as GABA) ion channels/receptors to maintain activity homeostasis.25−27 A suppression of activity leads to an increased number of excitatory ion channels/receptors in neurons while an enhancement of activity reduces the number of excitatory ion channels/receptors. An off-balance ratio of excitatory to inhibitory ion channels/ receptors has been observed in various neurological diseases28 such as chronic pain and FXS, a human intellectual disability classified under the autism spectrum disorder.29 The fragile X mental retardation protein (FMRP) increases the density of Ntype Ca2+ channels, causing hyperexcitability.30 The disease is also characterized by a deficiency of GABA receptors at the cortices of Fragile X mice,31 contributing to epilepsy.32 We hypothesized that if our magnetic platform could activate excitatory N-type Ca2+ channels chronically, the neural networks might compensate by reducing the expression of D

DOI: 10.1021/acs.nanolett.6b04200 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

Figure 3. Magnetic forces enhance the expression of inhibitory GABAA receptors in a day 12 FXS neural network model following chronic stimulation. Chronically stimulated FXS model neurons have lower (a) average and (b) peak ΔF/F0 and (c) calcium spiking frequencies than nonstimulated counterparts. This can be at least partially explained by enhanced expression of inhibitory GABAA receptors in the former that reduce excitability (magnitude and frequency of calcium spikes) of FXS neural networks in response to bicuculline (1.2 μM). “S” refers to chronically stimulated.

days.33 After chronic stimulation, we either immunostained the neurons immediately or continued culturing them for 4 more days to observe whether the effects of neural networks were sustainable. We found no significant difference in the expression of Ntype Ca2+ channel among control neurons, control neurons treated with MNPs, and magnetically stimulated control neurons although a decrease was observed in the latter (Figure 2d). This could be because the N-type Ca2+ channels are essential for a range of neural functions and a minimum level of expression is needed for normal development.33 Next, we found that stimulated FXS neurons had channel expression that was significantly lower (Figure 2f) than FXS neurons that were not chronically stimulated (Figure 2e), demonstrating that chronic mechanical stimulation could affect the expression of mechanosensitive ion channel.

these channels and increasing the expression of inhibitory ion channels/receptors. We first showed that neurons treated with anti-FMR1 antibody had enhanced expression of N-type Ca2+ channels as expected from the findings of Ferron et al.,30 and with age there was a reduction in the expression of these channels (Figure 2a,b). (Here, we will refer to these neurons with elevated expression of N-type Ca2+ channels as FXS neurons.) Figure 2c shows the experimental setup for chronic stimulation. We cultured the neurons for 4 days before magnetically stimulating them for the next 4 days with increasing force daily (see rationale in Figure S7). The first 4 days gave the neurons sufficient time to establish their axonal and dendritic polarities. As neurite branching is highly regulated by N-type calcium channels, the first 4 days also allowed the expression of the ion channels to stabilize before activating them over the next 4 E

DOI: 10.1021/acs.nanolett.6b04200 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

is observed in FXS. It may be possible to combine our technology that has specific ion channel targeting, once significant challenges for in vivo use are addressed, with transcranial magnetic inhibition that is currently being employed to reduce cortical excitability in patients.36 The combined technology may also find utility as a noninvasive therapy in other neurological diseases by modulating the expression of endogenous mechano-sensitive ion channel density in cases like abnormal nociception where there is enhanced expression of N-type Ca2+ ion channels37 and patients have to undergo highly invasive spinal injections with modified conotoxin.38 We also want to highlight that one advantage of our technique over other emerging techniques is that it does not require genetic manipulations, which still face the challenge of consistent transfection efficacy and heterogeneous expression (Figure S9), as N-type Ca2+ channels are relatively abundant on different classes of neurons as compared to TRPV ion channels. Nonetheless, as N-type Ca2+ channels are involved in many important neural activities (although N-type gene knockout mice develop healthily with normal lifespan, behavior and motor functions39) and its expression reduces with age, more work is needed to enhance calcium influx with our technique for use in in vitro neural culture of different ages and in vivo brain study. Lastly, this technology can also be employed to investigate the effects of biomechanical forces on mechanosensitive ion channel expression during neuronal development.40

Remarkably, we observed that chronic magnetic stimulation brought the expression of N-type Ca2+channels in FXS neurons down to a level similar to that of control neurons (Figure 2d), supporting our hypothesis of magnetic force-mediated restoration of mechano-sensitive ion channel equilibrium. We also observed that the expression of N-type Ca2+ channels was similar in stimulated FXS neurons at day 8 and 12 (Figure 2d), showing that the effects of chronic magnetic stimulation were sustainable for at least 4 days. Next, we monitored the expression of TRPV4 which is the only type of mechanosensitive ion channel other than N-type calcium channel that has been reported for neural stimulation.8 However, chronic stimulation did not affect the expression of TRPV4 (Figure S10b). We propose a biophysical model to describe the mechanical sensitivity of different ion channels and how the application of different force magnitudes may specify the types of mechano-sensitive ion channels being stimulated (Figure S10c). Patients with FXS typically have reduced expression of GABAA receptors,29 resulting in network hyper-excitability as characterized by higher magnitude and frequency in calcium spikes (Figure 3) in the presence of bicuculline. We wanted to investigate whether chronic magnetic stimulation could also modulate the expression of GABAA receptors. Although GABAA receptors are not mechano-sensitive, it has been shown that when excitatory (such as mechano-sensitive N-type Ca2+) ion channels are chronically stimulated, the neural networks can compensate by increasing the expression of GABAA inhibitory ion receptors.27 Interestingly, we found that FXS neurons that underwent chronic magnetic stimulation did not have statistically significant different average (Figure 3a) and peak ΔF/F0 (Figure 3b) as compared to control neurons. The number of spikes per neuron at a given time was also reduced for chronically stimulated FMRP treated neurons compared to the nonstimulated FXS neurons (Figure 3c). These results show that magnetic force stimulation could have enhanced the expression of GABAA receptors, thus reducing the excitability (magnitude and frequency in calcium spikes) of FXS neural networks in response to bicuculline (1.2 μM). Conclusions. Here, we show that our platform with high magnetic field gradients and magnetically induced forces can be used with MNPs for acute neural stimulation. This technique with its suitable spatiotemporal resolution, controllable dosage and use of magnetic fields with deep tissue penetration, can also be further developed for noninvasive in vivo brain stimulation. To do so, a high magnetic gradient implant has to be created such as using an endovascular stent−magnetic array.34 Through extensive experiments, we also demonstrated that magnetic forces most likely induced Ca2+ influx by mechanically stretching the lipid membrane to modulate the open probability of mechano-sensitive N-type Ca2+ channels. One of our future planned experiments is to perform single ion channel patch clamping with a customized nonmagnetic recording apparatus to eliminate electrical noise from the magnetic field to better understand the effects of magnetic forces on channel conductance and probability of channel opening. One way to increase the specificity of acute stimulation with this technique is to coat the MNPs with antibodies targeting the N-type calcium ion channel as proposed by Souze et al.35 although this might be incompatible with chronic stimulation as the functions of the ion channels might be adversely affected. We also showed that our technology can be employed to modulate/restore N-type Ca2+ ion channel disequilibrium that



ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.nanolett.6b04200. Nanoparticle characterization and force characterization (PDF) Magnetic stimulation triggering Ca2+ influx axons/ boutons (AVI)



AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. ORCID

Andy Tay: 0000-0003-3652-9515 Notes

The authors declare no competing financial interest.



ACKNOWLEDGMENTS This work was performed with funding from U.S. National Institutes of Health Director’s New Innovator Award (1DP2OD007113). Flow cytometry was performed in the UCLA Jonsson Comprehensive Cancer Center (JCCC) and Center for AIDS Research Flow Cytometry Core Facility that is supported by National Institutes of Health awards P30 CA016042 and 5P30 AI028697, and by the JCCC, the UCLA AIDS Institute, the David Geffen School of Medicine at UCLA, the UCLA Chancellor’s Office, and the UCLA Vice Chancellor’s Office of Research. Chip fabrication and confocal laser scanning microscopy was performed at the CNSI Center for Micro- and Nanofabrication and Advanced Light Microscopy/Spectroscopy Shared Resource Facility at UCLA, F

DOI: 10.1021/acs.nanolett.6b04200 Nano Lett. XXXX, XXX, XXX−XXX

Letter

Nano Letters

(22) Stanley, S. a; Gagner, J. E.; Damanpour, S.; Yoshida, M.; Dordick, J. S.; Friedman, J. M. Science 2012, 336 (6081), 604−608. (23) Stanley, S. a; Sauer, J.; Kane, R. S.; Dordick, J. S.; Friedman, J. M. Nat. Med. 2014, 21 (1), 92−98. (24) Hudspeth, A. J. Neuron 2008, 59, 530−545. (25) Borodinsky, L. N.; Root, C. M.; Cronin, J. a; Sann, S. B.; Gu, X.; Spitzer, N. C. Nature 2004, 429 (6991), 523−530. (26) O’Leary, T.; Williams, A. H.; Caplan, J. S.; Marder, E. Proc. Natl. Acad. Sci. U. S. A. 2013, 110 (28), E2645−54. (27) O’Leary, T.; Williams, A. H.; Franci, A.; Marder, E. Neuron 2014, 82 (4), 809−821. (28) Beck, H.; Yaari, Y. Nat. Rev. Neurosci. 2008, 9 (5), 357−369. (29) Contractor, A.; Klyachko, V. A.; Portera-Cailliau, C. Neuron 2015, 87 (4), 699−715. (30) Ferron, L.; Nieto-Rostro, M.; Cassidy, J. S.; Dolphin, A. C. Nat. Commun. 2014, 5, 3628. (31) Liu, B.; Li, L.; Chen, J.; Wang, Z.; Li, Z.; Wan, Q. Int. J. Physiol. Pathophysiol. Pharmacol. 2013, 5 (3), 169−176. (32) Hagerman, P. J.; Stafstrom, C. E. Epilepsy Curr. 2009, 9 (4), 108−112. (33) Weiss, N. J. Neurosci. 2008, 28 (22), 5621−5622. (34) Oxley, T. J.; Opie, N. L.; John, S. E.; Rind, G. S.; Ronayne, S. M.; Wheeler, T. L.; Judy, J. W.; McDonald, A. J.; Dornom, A.; Lovell, T. J. H.; Steward, C.; Garrett, D. J.; Moffat, B. A.; Lui, E. H.; Yassi, N.; Campbell, B. C. V; Wong, Y. T.; Fox, K. E.; Nurse, E. S.; Bennett, I. E.; Bauquier, S. H.; Liyanage, K. A.; van der Nagel, N. R.; Perucca, P.; Ahnood, A.; Gill, K. P.; Yan, B.; Churilov, L.; French, C. R.; Desmond, P. M.; Horne, M. K.; Kiers, L.; Prawer, S.; Davis, S. M.; Burkitt, A. N.; Mitchell, P. J.; Grayden, D. B.; May, C. N.; O’Brien, T. J. Nat. Biotechnol. 2016, 34 (3), 320−327. (35) Carvalho-de-Souza, J. L.; Treger, J. S.; Dang, B.; Kent, S. B. H.; Pepperberg, D. R.; Bezanilla, F. Neuron 2015, 86 (1), 207−217. (36) Oberman, L.; Ifert-Miller, F.; Najib, U.; Bashir, S.; Woollacott, I.; Gonzalez-Heydrich, J.; Picker, J.; Rotenberg, A.; Pascual-Leone, A. Front. Synaptic Neurosci. 2010, 2 (June), 26. (37) Snutch, T. P. NeuroRx 2005, 2 (4), 662−670. (38) Hannon, H. E.; Atchison, W. D. Mar. Drugs 2013, 11, 680−699. (39) Ino, M.; Yoshinaga, T.; Wakamori, M.; Miyamoto, N.; Takahashi, E.; Sonoda, J.; Kagaya, T.; Oki, T.; Nagasu, T.; Nishizawa, Y.; Tanaka, I.; Imoto, K.; Aizawa, S.; Koch, S.; Schwartz, A.; Niidome, T.; Sawada, K.; Mori, Y. Proc. Natl. Acad. Sci. U. S. A. 2001, 98 (9), 5323−5328. (40) Tay, A.; Schweizer, F. E.; Di Carlo, D. Lab Chip 2016, 16 (11), 1962−1977.

respectively, supported with funding from NIH-NCRR shared resources Grant (CJX1-443835-WS-29646) and NSF Major Research Instrumentation Grant (CHE-0722519). The authors acknowledge the use of instruments at the Electron Imaging Center for NanoMachines supported by NIH (1S10RR23057 to ZHZ). The authors thank Coleman Murray for chip fabrication and Anja Kunze for magnetic force calculation and chip design. The authors also thank Felix Schweizer and Carlos Portera-Cailliau for the useful discussions on neural network regulation and FXS, respectively. A.T. also thank Tiago Branco and Ian Duguid on insights on ion channels and neurophysiology. A.T. performed experiments and analyzed data. A.T. wrote the manuscript and both authors revised the manuscript.



REFERENCES

(1) Berridge, M. J.; Bootman, M. D.; Lipp, P. Nature 1998, 395, 645−648. (2) Banghart, M.; Borges, K.; Isacoff, E.; Trauner, D.; Kramer, R. H. Nat. Neurosci. 2004, 7 (12), 1381−1386. (3) Sparta, D. R.; Stamatakis, A. M.; Phillips, J. L.; Hovelsø, N.; van Zessen, R.; Stuber, G. D. Nat. Protoc. 2011, 7 (1), 12−23. (4) Otchy, T. M.; Wolff, S. B. E.; Rhee, J. Y.; Pehlevan, C.; Kawai, R.; Kempf, A.; Gobes, S. M. H.; Ö lveczky, B. P. Nature 2015, 528 (7582), 358−363. (5) Liu, Z.; Liu, Y.; Chang, Y.; Seyf, H. R.; Henry, A.; Mattheyses, A. L.; Yehl, K.; Zhang, Y.; Huang, Z.; Salaita, K. Nat. Methods 2015, 13, 143−146. (6) Seo, D.; Southard, K. M.; Kim, J. W.; Lee, H. J.; Farlow, J.; Lee, J. U.; Litt, D. B.; Haas, T.; Alivisatos, A. P.; Cheon, J.; Gartner, Z. J.; Jun, Y. W. Cell 2016, 165 (6), 1507−1518. (7) Stanley, S. A.; Kelly, L.; Latcha, K. N.; Schmidt, S. F.; Yu, X.; Nectow, A. R.; Sauer, J.; Dyke, J. P.; Dordick, J. S.; Friedman, J. M. Nature 2016, 531, 647−650. (8) Wheeler, M. A.; Smith, C. J.; Ottolini, M.; Barker, B. S.; Purohit, A. M.; Grippo, R. M.; Gaykema, R. P.; Spano, A. J.; Beenhakker, M. P.; Kucenas, S.; Patel, M. K.; Deppmann, C. D.; Güler, A. D. Nat. Neurosci. 2016, 19, 756. (9) Meister, M. eLife 2016, DOI: 10.7554/eLife.17210. (10) Tay, A.; Kunze, A.; Murray, C.; Di Carlo, D. ACS Nano 2016, 10, 2331. (11) Yuste, R. Nat. Rev. Neurosci. 2015, 16 (8), 487−497. (12) Patel, J. C.; Witkovsky, P.; Avshalumov, M. V.; Rice, M. E. J. Neurosci. 2009, 29 (20), 6568−6579. (13) Dworakowska, B.; Dołowy, K.; Tyson, J. R.; Snutch, T. P.; Piontkivska, H.; Hughes, A. L.; Bidaud, I.; Mezghrani, A.; Swayne, L. A.; Monteil, A.; Lory, P.; Zamponi, G. W. Wiley Interdiscip. Rev. Membr. Transp. Signal 2013, 2 (3), 181−206. (14) Calabrese, B.; Tabarean, I. V.; Juranka, P.; Morris, C. E. Biophys. J. 2002, 83 (5), 2560−2574. (15) McCleskey, E. W.; Fox, A. P.; Feldman, D. H.; Cruz, L. J.; Olivera, B. M.; Tsien, R. W.; Yoshikami, D. Proc. Natl. Acad. Sci. U. S. A. 1987, 84 (12), 4327−4331. (16) Chen, R.; Romero, G.; Christiansen, M. G.; Mohr, A.; Anikeeva, P. Science 2015, 347 (6229), 1477−1480. (17) Sabass, B.; Stone, H. A. Phys. Rev. Lett. 2016, DOI: 10.1103/ PhysRevLett.116.258101. (18) Coste, B.; Mathur, J.; Schmidt, M.; Earley, T. J.; Ranade, S.; Petrus, M. J.; Dubin, A. E.; Patapoutian, A. Science 2010, 330 (6000), 55−60. (19) Zhao, Q.; Wu, K.; Geng, J.; Chi, S.; Wang, Y.; Zhi, P.; Zhang, M.; Xiao, B. Neuron 2016, 89 (6), 1248−1263. (20) Tay, A.; Kunze, A.; Jun, D.; Hoek, E.; Di Carlo, D. Small 2016, 12, 3559. (21) Chameau, P.; Lucas, P.; Melliti, K.; Bournaud, R.; Shimahara, T. Neuroscience 1999, 90 (2), 383−388. G

DOI: 10.1021/acs.nanolett.6b04200 Nano Lett. XXXX, XXX, XXX−XXX