The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
High-performance genetically targetable optical neural silencing by light-driven proton pumps
Open accessAbstract
The ability to silence the activity of genetically specified neurons in a temporally precise fashion would provide the opportunity to investigate the causal role of specific cell classes in neural computations, behaviours and pathologies. Here we show that members of the class of light-driven outward proton pumps can mediate powerful, safe, multiple-colour silencing of neural activity. The gene archaerhodopsin-3 (Arch) from Halorubrum sodomense enables near-100% silencing of neurons in the awake brain when virally expressed in the mouse cortex and illuminated with yellow light. Arch mediates currents of several hundred picoamps at low light powers, and supports neural silencing currents approaching 900 pA at light powers easily achievable in vivo. Furthermore, Arch spontaneously recovers from light-dependent inactivation, unlike light-driven chloride pumps that enter long-lasting inactive states in response to light. These properties of Arch are appropriate to mediate the optical silencing of significant brain volumes over behaviourally relevant timescales. Arch function in neurons is well tolerated because pH excursions created by Arch illumination are minimized by self-limiting mechanisms to levels comparable to those mediated by channelrhodopsins or natural spike firing. To highlight how proton pump ecological and genomic diversity may support new innovation, we show that the blue–green light-drivable proton pump from the fungus Leptosphaeria maculans (Mac) can, when expressed in neurons, enable neural silencing by blue light, thus enabling alongside other developed reagents the potential for independent silencing of two neural populations by blue versus red light. Light-driven proton pumps thus represent a high-performance and extremely versatile class of ‘optogenetic’ voltage and ion modulator, which will broadly enable new neuroscientific, biological, neurological and psychiatric investigations.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Correlated Bursts of Activity in the Neonatal Hippocampus in Vivo
Leinekugel, X., Khazipov, R., Cannon, R., Hirase, H., Ben-Ari, Y., & Buzsáki, G. (2002) · Science · doi:10.1126/science.1071111 · Cited by 362
Cited by
Independent optical excitation of distinct neural populations
Klapoetke, N. C., Murata, Y., Kim, S. S., Pulver, S. R., Birdsey-Benson, A., Cho, Y. K., Morimoto, T. K., Chuong, A. S., Carpenter, E. J., Tian, Z., et al. (2014) · Nature Methods · doi:10.1038/nmeth.2836 · Cited by 2,344
Self-citationOptogenetics in neural systems
Yizhar, O., Fenno, L. E., Davidson, T. J., Mogri, M., & Deisseroth, K. (2011) · Neuron · doi:10.1016/j.neuron.2011.06.004 · Cited by 1,881
The development and application of optogenetics
Fenno, L., Yizhar, O., & Deisseroth, K. (2011) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-061010-113817 · Cited by 1,822
A toolbox of Cre-dependent optogenetic transgenic mice for light-induced activation and silencing
Madisen, L., Mao, T., Koch, H., Zhuo, J.-M., Berenyi, A., Fujisawa, S., Hsu, Y.-W. A., Garcia, A. J., Gu, X., Zanella, S., et al. (2012) · Nature Neuroscience · doi:10.1038/nn.3078 · Cited by 1,398
Self-citationMattis, J., Tye, K. M., Ferenczi, E. A., Ramakrishnan, C., O'Shea, D. J., Prakash, R., Gunaydin, L. A., Hyun, M., Fenno, L. E., Gradinaru, V., et al. (2012) · Nature Methods · doi:10.1038/nmeth.1808 · Cited by 780
Optogenetic investigation of neural circuits underlying brain disease in animal models
Tye, K. M., & Deisseroth, K. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3171 · Cited by 745
Hippocampal–prefrontal input supports spatial encoding in working memory
Spellman, T., Rigotti, M., Ahmari, S. E., Fusi, S., Gogos, J. A., & Gordon, J. A. (2015) · Nature · doi:10.1038/nature14445 · Cited by 693
A neural circuit for spatial summation in visual cortex
Adesnik, H., Bruns, W., Taniguchi, H., Huang, Z. J., & Scanziani, M. (2012) · Nature · doi:10.1038/nature11526 · Cited by 702
Integration of optogenetics with complementary methodologies in systems neuroscience
Kim, C. K., Adhikari, A., & Deisseroth, K. (2017) · Nature reviews. Neuroscience · doi:10.1038/nrn.2017.15 · Cited by 690
Canales, A., Jia, X., Froriep, U. P., Koppes, R. A., Tringides, C. M., Selvidge, J., Lu, C., Hou, C., Wei, L., Fink, Y., et al. (2015) · Nature Biotechnology · doi:10.1038/nbt.3093 · Cited by 668
Parvalbumin-expressing interneurons linearly transform cortical responses to visual stimuli
Atallah, B. V., Bruns, W., Carandini, M., & Scanziani, M. (2012) · Neuron · doi:10.1016/j.neuron.2011.12.013 · Cited by 612
Latchoumane, C.-F. V., Ngo, H.-V. V., Born, J., & Shin, H.-S. (2017) · Neuron · doi:10.1016/j.neuron.2017.06.025 · Cited by 561
Activation of specific interneurons improves V1 feature selectivity and visual perception
Lee, S.-H., Kwan, A. C., Zhang, S., Phoumthipphavong, V., Flannery, J. G., Masmanidis, S. C., Taniguchi, H., Huang, Z. J., Zhang, F., Boyden, E. S., et al. (2012) · Nature · doi:10.1038/nature11312 · Cited by 593
Self-citationDistinct behavioural and network correlates of two interneuron types in prefrontal cortex
Kvitsiani, D., Ranade, S., Hangya, B., Taniguchi, H., Huang, J. Z., & Kepecs, A. (2013) · Nature · doi:10.1038/nature12176 · Cited by 516
Gain control by layer six in cortical circuits of vision
Olsen, S. R., Bortone, D. S., Adesnik, H., & Scanziani, M. (2012) · Nature · doi:10.1038/nature10835 · Cited by 539
Serotonin and the neuropeptide PDF initiate and extend opposing behavioral states in C. elegans
Flavell, S. W., Pokala, N., Macosko, E. Z., Albrecht, D. R., Larsch, J., & Bargmann, C. I. (2013) · Cell · doi:10.1016/j.cell.2013.08.001 · Cited by 467
Experience-dependent modification of a central amygdala fear circuit
Li, H., Penzo, M. A., Taniguchi, H., Kopec, C. D., Huang, Z. J., & Li, B. (2013) · Nature Neuroscience · doi:10.1038/nn.3322 · Cited by 497
Seizure detection, seizure prediction, and closed-loop warning systems in epilepsy
Ramgopal, S., Thome-Souza, S., Jackson, M., Kadish, N. E., Sánchez Fernández, I., Klehm, J., Bosl, W., Reinsberger, C., Schachter, S., & Loddenkemper, T. (2014) · Epilepsy & Behavior · doi:10.1016/j.yebeh.2014.06.023 · Cited by 469
Astrocytes regulate cortical state switching in vivo
Poskanzer, K. E., & Yuste, R. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1520759113 · Cited by 377
Definition of the hypothalamic GnRH pulse generator in mice
Clarkson, J., Han, S. Y., Piet, R., McLennan, T., Kane, G. M., Ng, J., Porteous, R. W., Kim, J. S., Colledge, W. H., Iremonger, K. J., et al. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1713897114 · Cited by 392
Distinct inhibitory circuits orchestrate cortical beta and gamma band oscillations
Chen, G., Zhang, Y., Li, X., Zhao, X., Ye, Q., Lin, Y., Tao, H. W., Rasch, M. J., & Zhang, X. (2017) · Neuron · doi:10.1016/j.neuron.2017.11.033 · Cited by 345
Self-citationAmygdala inputs to prefrontal cortex guide behavior amid conflicting cues of reward and punishment
Burgos-Robles, A., Kimchi, E. Y., Izadmehr, E. M., Porzenheim, M. J., Ramos-Guasp, W. A., Nieh, E. H., Felix-Ortiz, A. C., Namburi, P., Leppla, C. A., Presbrey, K. N., et al. (2017) · Nature Neuroscience · doi:10.1038/nn.4553 · Cited by 318
Remote Control of Neuronal Signaling
Rogan, S. C., & Roth, B. L. (2011) · Pharmacological Reviews · doi:10.1124/pr.110.003020 · Cited by 339
Hypothalamic CRH neurons orchestrate complex behaviours after stress
Füzesi, T., Daviu, N., Wamsteeker Cusulin, J. I., Bonin, R. P., & Bains, J. S. (2016) · Nature Communications · doi:10.1038/ncomms11937 · Cited by 316
Reversing behavioural abnormalities in mice exposed to maternal inflammation
Shin Yim, Y., Park, A., Berrios, J., Lafourcade, M., Pascual, L. M., Soares, N., Yeon Kim, J., Kim, S., Kim, H., Waisman, A., et al. (2017) · Nature · doi:10.1038/nature23909 · Cited by 303
Optogenetic inhibition of behavior with anion channelrhodopsins
Mohammad, F., Stewart, J. C., Ott, S., Chlebikova, K., Chua, J. Y., Koh, T.-W., Ho, J., & Claridge-Chang, A. (2017) · Nature Methods · doi:10.1038/nmeth.4148 · Cited by 276
Functions, Therapeutic Applications, and Synthesis of Retinoids and Carotenoids
Álvarez, R., Vaz, B., Gronemeyer, H., & de Lera, Á. R. (2014) · Chemical Reviews · doi:10.1021/cr400126u · Cited by 260
Sharp wave ripples during learning stabilize the hippocampal spatial map
Roux, L., Hu, B., Eichler, R., Stark, E., & Buzsáki, G. (2017) · Nature Neuroscience · doi:10.1038/nn.4543 · Cited by 229
Genetic Approaches to Neural Circuits in the Mouse
Josh Huang, Z., & Zeng, H. (2013) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-062012-170307 · Cited by 200
Daviu, N., Füzesi, T., Rosenegger, D. G., Rasiah, N. P., Sterley, T.-L., Peringod, G., & Bains, J. S. (2020) · Nature Neuroscience · doi:10.1038/s41593-020-0591-0 · Cited by 217
An acetylcholine-activated microcircuit drives temporal dynamics of cortical activity
Chen, N., Sugihara, H., & Sur, M. (2015) · Nature Neuroscience · doi:10.1038/nn.4002 · Cited by 210
Raphe GABAergic Neurons Mediate the Acquisition of Avoidance after Social Defeat
Challis, C., Boulden, J., Veerakumar, A., Espallergues, J., Vassoler, F. M., Pierce, R. C., Beck, S. G., & Berton, O. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.2383-13.2013 · Cited by 197
Hindbrain V2a neurons in the excitation of spinal locomotor circuits during zebrafish swimming
Kimura, Y., Satou, C., Fujioka, S., Shoji, W., Umeda, K., Ishizuka, T., Yawo, H., & Higashijima, S.-I. (2013) · Current Biology · doi:10.1016/j.cub.2013.03.066 · Cited by 186
Abbas, A. I., Sundiang, M. J. M., Henoch, B., Morton, M. P., Bolkan, S. S., Park, A. J., Harris, A. Z., Kellendonk, C., & Gordon, J. A. (2018) · Neuron · doi:10.1016/j.neuron.2018.09.029 · Cited by 183
Assembly-specific disruption of hippocampal replay leads to selective memory deficit
Gridchyn, I., Schoenenberger, P., O’Neill, J., & Csicsvari, J. (2020) · Neuron · doi:10.1016/j.neuron.2020.01.021 · Cited by 178
A common neuroendocrine substrate for diverse general anesthetics and sleep
Jiang-Xie, L.-F., Yin, L., Zhao, S., Prevosto, V., Han, B.-X., Dzirasa, K., & Wang, F. (2019) · Neuron · doi:10.1016/j.neuron.2019.03.033 · Cited by 173
Entorhinal cortex directs learning-related changes in CA1 representations
Grienberger, C., & Magee, J. C. (2022) · Nature · doi:10.1038/s41586-022-05378-6 · Cited by 171
Gene Therapy Tools for Brain Diseases
Ingusci, S., Verlengia, G., Soukupova, M., Zucchini, S., & Simonato, M. (2019) · Frontiers in Pharmacology · doi:10.3389/fphar.2019.00724 · Cited by 158
Optogenetic Control of Targeted Peripheral Axons in Freely Moving Animals
Towne, C., Montgomery, K. L., Iyer, S. M., Deisseroth, K., & Delp, S. L. (2013) · PLoS ONE · doi:10.1371/journal.pone.0072691 · Cited by 156
Optogenetic insights on the relationship between anxiety-related behaviors and social deficits
Allsop, S. A., Vander Weele, C. M., Wichmann, R., & Tye, K. M. (2014) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2014.00241 · Cited by 150
Controlling interneuron activity in Caenorhabditis elegans to evoke chemotactic behaviour
Kocabas, A., Shen, C.-H., Guo, Z. V., & Ramanathan, S. (2012) · Nature · doi:10.1038/nature11431 · Cited by 150
Optogenetics through windows on the brain in the nonhuman primate
Ruiz, O., Lustig, B. R., Nassi, J. J., Cetin, A., Reynolds, J. H., Albright, T. D., Callaway, E. M., Stoner, G. R., & Roe, A. W. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00153.2013 · Cited by 132
Optogenetic inactivation modifies monkey visuomotor behavior
Cavanaugh, J., Monosov, I. E., McAlonan, K., Berman, R., Smith, M. K., Cao, V., Wang, K. H., Boyden, E. S., & Wurtz, R. H. (2012) · Neuron · doi:10.1016/j.neuron.2012.10.016 · Cited by 124
Self-citationKim, W. B., & Cho, J.-H. (2017) · The Journal of Neuroscience · doi:10.1523/jneurosci.3579-16.2017 · Cited by 131
Mind-controlled transgene expression by a wireless-powered optogenetic designer cell implant.
Folcher, M., Oesterle, S., Zwicky, K., Thekkottil, T., Heymoz, J., Hohmann, M., Christen, M., Daoud El-Baba, M., Buchmann, P., & Fussenegger, M. (2014) · Nature Communications · doi:10.1038/ncomms6392 · Cited by 130
Near-infrared (NIR) up-conversion optogenetics
Hososhima, S., Yuasa, H., Ishizuka, T., Hoque, M. R., Yamashita, T., Yamanaka, A., Sugano, E., Tomita, H., & Yawo, H. (2015) · Scientific Reports · doi:10.1038/srep16533 · Cited by 126
Genetic dissection of GABAergic neural circuits in mouse neocortex
Taniguchi, H. (2014) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2014.00008 · Cited by 106
Huff, M. L., Miller, R. L., Deisseroth, K., Moorman, D. E., & LaLumiere, R. T. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1219593110 · Cited by 104
Approaches and Limitations in the Investigation of Synaptic Transmission and Plasticity
Glasgow, S. D., McPhedrain, R., Madranges, J. F., Kennedy, T. E., & Ruthazer, E. S. (2019) · Frontiers in Synaptic Neuroscience · doi:10.3389/fnsyn.2019.00020 · Cited by 100
A coaxial optrode as multifunction write-read probe for optogenetic studies in non-human primates
Ozden, I., Wang, J., Lu, Y., May, T., Lee, J., Goo, W., O'Shea, D. J., Kalanithi, P., Diester, I., Diagne, M., et al. (2013) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2013.06.011 · Cited by 97
Leroy, F., Brann, D. H., Meira, T., & Siegelbaum, S. A. (2017) · Neuron · doi:10.1016/j.neuron.2017.07.036 · Cited by 91
New Vision for Visual Prostheses
Farnum, A., & Pelled, G. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00036 · Cited by 58
Tools for Resolving Functional Activity and Connectivity within Intact Neural Circuits
Jennings, J. H., & Stuber, G. D. (2014) · Current Biology · doi:10.1016/j.cub.2013.11.042 · Cited by 54
Wester, J. C., & McBain, C. J. (2016) · The Journal of Neuroscience · doi:10.1523/jneurosci.4000-15.2016 · Cited by 46
Danskin, B., Denman, D., Valley, M., Ollerenshaw, D., Williams, D., Groblewski, P., Reid, C., Olsen, S., & Waters, J. (2015) · PLoS ONE · doi:10.1371/journal.pone.0144760 · Cited by 46
Haettig, J., Sun, Y., Wood, M. A., & Xu, X. (2013) · Learning & Memory · doi:10.1101/lm.027847.112 · Cited by 41
Noninvasive optical inhibition with a red-shifted microbial rhodopsin
Chuong, A. S., Miri, M. L., Busskamp, V., Matthews, G. A. C., Acker, L. C., Sørensen, A. T., Young, A., Klapoetke, N. C., Henninger, M. A., Kodandaramaiah, S. B., et al. (2014) · Nature Neuroscience · doi:10.1038/nn.3752 · Cited by 33
Self-citationA Flexible, Micro-Lens-Coupled LED Stimulator for Optical Neuromodulation
Bi, X., Xie, T., Fan, B., Khan, W., Guo, Y., & Li, W. (2016) · IEEE Transactions on Biomedical Circuits and Systems · doi:10.1109/tbcas.2016.2599406 · Cited by 24
Metadata
- Authors
- Chow, B. Y., Han, X., Dobry, A. S., Qian, X., Chuong, A. S., Li, M., Henninger, M. A., Belfort, G. M., Lin, Y., Monahan, P. E., & Boyden, E. S.
- Venue
- Nature
- Published
- 2010-01
- Volume
- 463
- Issue
- 7277
- Pages
- 98-102
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W2043358402
- Cited by
- 1,186
- References
- 1
- FWCI
- 32.67
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.