1
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Sharma AK, Randi F, Kumar S, Dvali S, Leifer AM. TWISP: a transgenic worm for interrogating signal propagation in Caenorhabditis elegans. Genetics 2024; 227:iyae077. [PMID: 38733622 PMCID: PMC11228852 DOI: 10.1093/genetics/iyae077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Revised: 02/11/2024] [Accepted: 04/11/2024] [Indexed: 05/13/2024] Open
Abstract
Genetically encoded optical indicators and actuators of neural activity allow for all-optical investigations of signaling in the nervous system. But commonly used indicators, actuators, and expression strategies are poorly suited for systematic measurements of signal propagation at brain scale and cellular resolution. Large-scale measurements of the brain require indicators and actuators with compatible excitation spectra to avoid optical crosstalk. They must be highly expressed in every neuron but at the same time avoid lethality and permit the animal to reach adulthood. Their expression must also be compatible with additional fluorescent labels to locate and identify neurons, such as those in the NeuroPAL cell identification system. We present TWISP, a transgenic worm for interrogating signal propagation, that addresses these needs and enables optical measurements of evoked calcium activity at brain scale and cellular resolution in the nervous system of the nematode Caenorhabditis elegans. In every neuron we express a nonconventional optical actuator, the gustatory receptor homolog GUR-3 + PRDX-2, under the control of a drug-inducible system QF + hGR, and a calcium indicator GCAMP6s, in a background with additional fluorophores from the NeuroPAL cell ID system. We show that this combination, but not others tested, avoids optical crosstalk, creates strong expression in the adult, and generates stable transgenic lines for systematic measurements of signal propagation in the worm brain.
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Affiliation(s)
- Anuj Kumar Sharma
- Department of Physics, Princeton University, Princeton, NJ 08544, USA
| | - Francesco Randi
- Department of Physics, Princeton University, Princeton, NJ 08544, USA
| | - Sandeep Kumar
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Sophie Dvali
- Department of Physics, Princeton University, Princeton, NJ 08544, USA
| | - Andrew M Leifer
- Department of Physics, Princeton University, Princeton, NJ 08544, USA
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
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2
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Sakamoto M, Yokoyama T. Probing neuronal activity with genetically encoded calcium and voltage fluorescent indicators. Neurosci Res 2024:S0168-0102(24)00076-2. [PMID: 38885881 DOI: 10.1016/j.neures.2024.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Revised: 04/09/2024] [Accepted: 06/08/2024] [Indexed: 06/20/2024]
Abstract
Monitoring neural activity in individual neurons is crucial for understanding neural circuits and brain functions. The emergence of optical imaging technologies has dramatically transformed the field of neuroscience, enabling detailed observation of large-scale neuronal populations with both cellular and subcellular resolution. This transformation will be further accelerated by the integration of these imaging technologies and advanced big data analysis. Genetically encoded fluorescent indicators to detect neural activity with high signal-to-noise ratios are pivotal in this advancement. In recent years, these indicators have undergone significant developments, greatly enhancing the understanding of neural dynamics and networks. This review highlights the recent progress in genetically encoded calcium and voltage indicators and discusses the future direction of imaging techniques with big data analysis that deepens our understanding of the complexities of the brain.
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Affiliation(s)
- Masayuki Sakamoto
- Graduate School of Biostudies, Kyoto University, 53 Shogoin Kawara-cho, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Tatsushi Yokoyama
- Graduate School of Biostudies, Kyoto University, 53 Shogoin Kawara-cho, Sakyo-ku, Kyoto 606-8507, Japan
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3
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Brooks FP, Davis HC, Park P, Qi Y, Cohen AE. Photophysics-informed two-photon voltage imaging using FRET-opsin voltage indicators. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.01.587540. [PMID: 38617370 PMCID: PMC11014499 DOI: 10.1101/2024.04.01.587540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Microbial rhodopsin-derived genetically encoded voltage indicators (GEVIs) are powerful tools for mapping bioelectrical dynamics in cell culture and in live animals. Förster resonance energy transfer (FRET)-opsin GEVIs use voltage-dependent changes in opsin absorption to modulate the fluorescence of an attached fluorophore, achieving high brightness, speed, and voltage sensitivity. However, the voltage sensitivity of most FRET-opsin GEVIs has been reported to decrease or vanish under two-photon (2P) excitation. Here we investigated the photophysics of the FRET-opsin GEVIs Voltron1 and 2. We found that the voltage sensitivity came from a photocycle intermediate, not from the opsin ground state. The voltage sensitivities of both GEVIs were nonlinear functions of illumination intensity; for Voltron1, the sensitivity reversed sign under low-intensity illumination. Using photocycle-optimized 2P illumination protocols, we demonstrate 2P voltage imaging with Voltron2 in barrel cortex of a live mouse. These results open the door to high-speed 2P voltage imaging of FRET-opsin GEVIs in vivo.
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Affiliation(s)
| | | | - Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University
| | - Yitong Qi
- Department of Chemistry and Chemical Biology, Harvard University
| | - Adam E. Cohen
- Department of Chemistry and Chemical Biology, Harvard University
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4
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Han Y, Yang J, Li Y, Chen Y, Ren H, Ding R, Qian W, Ren K, Xie B, Deng M, Xiao Y, Chu J, Zou P. Bright and sensitive red voltage indicators for imaging action potentials in brain slices and pancreatic islets. SCIENCE ADVANCES 2023; 9:eadi4208. [PMID: 37992174 PMCID: PMC10664999 DOI: 10.1126/sciadv.adi4208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 10/20/2023] [Indexed: 11/24/2023]
Abstract
Genetically encoded voltage indicators (GEVIs) allow the direct visualization of cellular membrane potential at the millisecond time scale. Among these, red-emitting GEVIs have been reported to support multichannel recordings and manipulation of cellular activities with reduced autofluorescence background. However, the limited sensitivity and dimness of existing red GEVIs have restricted their applications in neuroscience. Here, we report a pair of red-shifted opsin-based GEVIs, Cepheid1b and Cepheid1s, with improved dynamic range, brightness, and photostability. The improved dynamic range is achieved by a rational design to raise the electrochromic Förster resonance energy transfer efficiency, and the higher brightness and photostability are approached with separately engineered red fluorescent proteins. With Cepheid1 indicators, we recorded complex firings and subthreshold activities of neurons on acute brain slices and observed heterogeneity in the voltage‑calcium coupling on pancreatic islets. Overall, Cepheid1 indicators provide a strong tool to investigate excitable cells in various sophisticated biological systems.
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Affiliation(s)
- Yi Han
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Junqi Yang
- Peking University–Tsinghua University–National Institute of Biological Sciences Joint Graduate Program, School of Life Sciences, Peking University, Beijing 100871, China
| | - Yuan Li
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Chinese Institute for Brain Research (CIBR), Beijing 102206, China
| | - Yu Chen
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Huixia Ren
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Center for Quantitative Biology, Peking University, Beijing 100871, China
| | - Ran Ding
- Institute for Translational Neuroscience of the Second Affiliated Hospital of Nantong University, Center for Neural Developmental and Degenerative Research of Nantong University, Nantong 226001, China
| | - Weiran Qian
- Institute of Molecular Medicine, College of Future Technology, Peking University, Beijing 100871, China
| | - Keyuan Ren
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
| | - Beichen Xie
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
| | - Mengying Deng
- Research Center for Biomedical Optics and Molecular Imaging, Shenzhen Key Laboratory for Molecular Imaging, Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yinghan Xiao
- Research Center for Biomedical Optics and Molecular Imaging, Shenzhen Key Laboratory for Molecular Imaging, Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Jun Chu
- Research Center for Biomedical Optics and Molecular Imaging, Shenzhen Key Laboratory for Molecular Imaging, Guangdong Provincial Key Laboratory of Biomedical Optical Imaging Technology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Peng Zou
- College of Chemistry and Molecular Engineering, Synthetic and Functional Biomolecules Center Beijing National Laboratory for Molecular Sciences, Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
- Peking University–Tsinghua University–National Institute of Biological Sciences Joint Graduate Program, School of Life Sciences, Peking University, Beijing 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing 100871, China
- Chinese Institute for Brain Research (CIBR), Beijing 102206, China
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5
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Meng X, Ganapathy S, van Roemburg L, Post M, Brinks D. Voltage Imaging with Engineered Proton-Pumping Rhodopsins: Insights from the Proton Transfer Pathway. ACS PHYSICAL CHEMISTRY AU 2023; 3:320-333. [PMID: 37520318 PMCID: PMC10375888 DOI: 10.1021/acsphyschemau.3c00003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 04/13/2023] [Accepted: 04/13/2023] [Indexed: 08/01/2023]
Abstract
Voltage imaging using genetically encoded voltage indicators (GEVIs) has taken the field of neuroscience by storm in the past decade. Its ability to create subcellular and network level readouts of electrical dynamics depends critically on the kinetics of the response to voltage of the indicator used. Engineered microbial rhodopsins form a GEVI subclass known for their high voltage sensitivity and fast response kinetics. Here we review the essential aspects of microbial rhodopsin photocycles that are critical to understanding the mechanisms of voltage sensitivity in these proteins and link them to insights from efforts to create faster, brighter and more sensitive microbial rhodopsin-based GEVIs.
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Affiliation(s)
- Xin Meng
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
| | - Srividya Ganapathy
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
- Department
of Pediatrics & Cellular and Molecular Medicine, UCSD School of Medicine, La Jolla, California 92093, United States
| | - Lars van Roemburg
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
| | - Marco Post
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
| | - Daan Brinks
- Department
of Imaging Physics, Delft University of
Technology, 2628 CJ Delft, The
Netherlands
- Department
of Molecular Genetics, Erasmus University
Medical Center, 3015 GD Rotterdam, The Netherlands
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6
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Evans SW, Shi DQ, Chavarha M, Plitt MH, Taxidis J, Madruga B, Fan JL, Hwang FJ, van Keulen SC, Suomivuori CM, Pang MM, Su S, Lee S, Hao YA, Zhang G, Jiang D, Pradhan L, Roth RH, Liu Y, Dorian CC, Reese AL, Negrean A, Losonczy A, Makinson CD, Wang S, Clandinin TR, Dror RO, Ding JB, Ji N, Golshani P, Giocomo LM, Bi GQ, Lin MZ. A positively tuned voltage indicator for extended electrical recordings in the brain. Nat Methods 2023; 20:1104-1113. [PMID: 37429962 PMCID: PMC10627146 DOI: 10.1038/s41592-023-01913-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 05/15/2023] [Indexed: 07/12/2023]
Abstract
Genetically encoded voltage indicators (GEVIs) enable optical recording of electrical signals in the brain, providing subthreshold sensitivity and temporal resolution not possible with calcium indicators. However, one- and two-photon voltage imaging over prolonged periods with the same GEVI has not yet been demonstrated. Here, we report engineering of ASAP family GEVIs to enhance photostability by inversion of the fluorescence-voltage relationship. Two of the resulting GEVIs, ASAP4b and ASAP4e, respond to 100-mV depolarizations with ≥180% fluorescence increases, compared with the 50% fluorescence decrease of the parental ASAP3. With standard microscopy equipment, ASAP4e enables single-trial detection of spikes in mice over the course of minutes. Unlike GEVIs previously used for one-photon voltage recordings, ASAP4b and ASAP4e also perform well under two-photon illumination. By imaging voltage and calcium simultaneously, we show that ASAP4b and ASAP4e can identify place cells and detect voltage spikes with better temporal resolution than commonly used calcium indicators. Thus, ASAP4b and ASAP4e extend the capabilities of voltage imaging to standard one- and two-photon microscopes while improving the duration of voltage recordings.
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Affiliation(s)
- S Wenceslao Evans
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Dong-Qing Shi
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Mariya Chavarha
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Mark H Plitt
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Jiannis Taxidis
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| | - Blake Madruga
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - Jiang Lan Fan
- UC Berkeley/UCSF Joint Program in Bioengineering, University of California Berkeley, Berkeley, CA, USA
| | - Fuu-Jiun Hwang
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, USA
| | - Siri C van Keulen
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | | | - Michelle M Pang
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Sharon Su
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Sungmoo Lee
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Yukun A Hao
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Guofeng Zhang
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Dongyun Jiang
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Lagnajeet Pradhan
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Richard H Roth
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, USA
| | - Yu Liu
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, USA
- Department of Ophthalmology, Stanford University Medical Center, Stanford, CA, USA
| | - Conor C Dorian
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - Austin L Reese
- Institute for Genomic Medicine, Columbia University, New York, NY, USA
| | - Adrian Negrean
- Department of Neuroscience, Columbia University, New York, NY, USA
| | - Attila Losonczy
- Department of Neuroscience, Columbia University, New York, NY, USA
- Mortimer B. Zuckerman Mind Brain Behavior Institute, New York, NY, USA
- Kavli Institute for Brain Science, New York, NY, USA
| | - Christopher D Makinson
- Institute for Genomic Medicine, Columbia University, New York, NY, USA
- Department of Neurology, Columbia University, New York, NY, USA
| | - Sui Wang
- Department of Ophthalmology, Stanford University Medical Center, Stanford, CA, USA
| | - Thomas R Clandinin
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Ron O Dror
- Department of Computer Science, Stanford University, Stanford, CA, USA
- Department of Structural Biology, Stanford University School of Medicine, Stanford, CA, USA
- Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA, USA
- Department of Molecular and Cellular Physiology, Stanford University, Stanford, USA
| | - Jun B Ding
- Department of Neurosurgery, Stanford University Medical Center, Stanford, CA, USA
- Department of Neurology and Neurological Sciences, Stanford University Medical Center, Stanford, CA, USA
| | - Na Ji
- Program in Neurosciences & Mental Health, Hospital for Sick Children, Toronto, Ontario, Canada
- Department of Molecular and Cell Biology, University of California Berkeley, Berkeley, CA, USA
- Department of Physics, University of California Berkeley, Berkeley, CA, USA
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA, USA
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Peyman Golshani
- Department of Neurology, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
- Semel Institute for Neuroscience and Human Behavior, UCLA David Geffen School of Medicine, Los Angeles, CA, USA
| | - Lisa M Giocomo
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA
| | - Guo-Qiang Bi
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Interdisciplinary Center for Brain Information, Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Michael Z Lin
- Department of Neurobiology, Stanford University Medical Center, Stanford, CA, USA.
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Department of Chemical and Systems Biology, Stanford University, Stanford, USA.
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7
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Platisa J, Ye X, Ahrens AM, Liu C, Chen IA, Davison IG, Tian L, Pieribone VA, Chen JL. High-speed low-light in vivo two-photon voltage imaging of large neuronal populations. Nat Methods 2023; 20:1095-1103. [PMID: 36973547 PMCID: PMC10894646 DOI: 10.1038/s41592-023-01820-3] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 02/16/2023] [Indexed: 03/29/2023]
Abstract
Monitoring spiking activity across large neuronal populations at behaviorally relevant timescales is critical for understanding neural circuit function. Unlike calcium imaging, voltage imaging requires kilohertz sampling rates that reduce fluorescence detection to near shot-noise levels. High-photon flux excitation can overcome photon-limited shot noise, but photobleaching and photodamage restrict the number and duration of simultaneously imaged neurons. We investigated an alternative approach aimed at low two-photon flux, which is voltage imaging below the shot-noise limit. This framework involved developing positive-going voltage indicators with improved spike detection (SpikeyGi and SpikeyGi2); a two-photon microscope ('SMURF') for kilohertz frame rate imaging across a 0.4 mm × 0.4 mm field of view; and a self-supervised denoising algorithm (DeepVID) for inferring fluorescence from shot-noise-limited signals. Through these combined advances, we achieved simultaneous high-speed deep-tissue imaging of more than 100 densely labeled neurons over 1 hour in awake behaving mice. This demonstrates a scalable approach for voltage imaging across increasing neuronal populations.
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Affiliation(s)
- Jelena Platisa
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT, USA
- The John B. Pierce Laboratory, New Haven, CT, USA
| | - Xin Ye
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | | | - Chang Liu
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | | | - Ian G Davison
- Neurophotonics Center, Boston University, Boston, MA, USA
- Department of Biology, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Lei Tian
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
- Department of Electrical and Computer Engineering, Boston University, Boston, MA, USA
| | - Vincent A Pieribone
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT, USA.
- The John B. Pierce Laboratory, New Haven, CT, USA.
- Department of Neuroscience, Yale University, New Haven, CT, USA.
| | - Jerry L Chen
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
- Neurophotonics Center, Boston University, Boston, MA, USA.
- Department of Biology, Boston University, Boston, MA, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, USA.
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8
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Lecoq JA, Podgorski K, Grewe BF. AI to the rescue of voltage imaging. CELL REPORTS METHODS 2023; 3:100505. [PMID: 37426751 PMCID: PMC10326374 DOI: 10.1016/j.crmeth.2023.100505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
In a recent issue of Nature Methods, Platisa et al. present an approach for long-term, in vivo population voltage imaging with single spike resolution across a local population of 100 neurons.1 Key to this step forward was the combination of a customized high-speed two-photon microscope with an optimized, positive-going, genetically encoded voltage indicator and a tailored machine learning denoising algorithm.
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Affiliation(s)
| | | | - Benjamin F. Grewe
- Institute of Neuroinformatics, University of Zurich and ETH Zurich, Zurich, Switzerland
- ETH AI Center, ETH Zurich, Zurich, Switzerland
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9
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Abdelfattah AS, Zheng J, Singh A, Huang YC, Reep D, Tsegaye G, Tsang A, Arthur BJ, Rehorova M, Olson CVL, Shuai Y, Zhang L, Fu TM, Milkie DE, Moya MV, Weber TD, Lemire AL, Baker CA, Falco N, Zheng Q, Grimm JB, Yip MC, Walpita D, Chase M, Campagnola L, Murphy GJ, Wong AM, Forest CR, Mertz J, Economo MN, Turner GC, Koyama M, Lin BJ, Betzig E, Novak O, Lavis LD, Svoboda K, Korff W, Chen TW, Schreiter ER, Hasseman JP, Kolb I. Sensitivity optimization of a rhodopsin-based fluorescent voltage indicator. Neuron 2023; 111:1547-1563.e9. [PMID: 37015225 PMCID: PMC10280807 DOI: 10.1016/j.neuron.2023.03.009] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 02/15/2023] [Accepted: 03/07/2023] [Indexed: 04/05/2023]
Abstract
The ability to optically image cellular transmembrane voltages at millisecond-timescale resolutions can offer unprecedented insight into the function of living brains in behaving animals. Here, we present a point mutation that increases the sensitivity of Ace2 opsin-based voltage indicators. We use the mutation to develop Voltron2, an improved chemigeneic voltage indicator that has a 65% higher sensitivity to single APs and 3-fold higher sensitivity to subthreshold potentials than Voltron. Voltron2 retained the sub-millisecond kinetics and photostability of its predecessor, although with lower baseline fluorescence. In multiple in vitro and in vivo comparisons with its predecessor across multiple species, we found Voltron2 to be more sensitive to APs and subthreshold fluctuations. Finally, we used Voltron2 to study and evaluate the possible mechanisms of interneuron synchronization in the mouse hippocampus. Overall, we have discovered a generalizable mutation that significantly increases the sensitivity of Ace2 rhodopsin-based sensors, improving their voltage reporting capability.
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Affiliation(s)
| | - Jihong Zheng
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Amrita Singh
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Yi-Chieh Huang
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Daniel Reep
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Getahun Tsegaye
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Arthur Tsang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Benjamin J Arthur
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Monika Rehorova
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Carl V L Olson
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Yichun Shuai
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Lixia Zhang
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Tian-Ming Fu
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Daniel E Milkie
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Maria V Moya
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Timothy D Weber
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Andrew L Lemire
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | - Natalie Falco
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Qinsi Zheng
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Jonathan B Grimm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Mighten C Yip
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Deepika Walpita
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | | | | | | | - Allan M Wong
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Craig R Forest
- George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Michael N Economo
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Glenn C Turner
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Minoru Koyama
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Bei-Jung Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Eric Betzig
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; Departments of Molecular and Cell Biology and Physics, Howard Hughes Medical Institute, Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA; Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Ondrej Novak
- Department of Physiology, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Luke D Lavis
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Karel Svoboda
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Wyatt Korff
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA
| | - Tsai-Wen Chen
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan.
| | - Eric R Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
| | - Jeremy P Hasseman
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
| | - Ilya Kolb
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA; GENIE Project Team, Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, USA.
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10
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Silic MR, Zhang G. Bioelectricity in Developmental Patterning and Size Control: Evidence and Genetically Encoded Tools in the Zebrafish Model. Cells 2023; 12:cells12081148. [PMID: 37190057 DOI: 10.3390/cells12081148] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2023] [Revised: 04/03/2023] [Accepted: 04/10/2023] [Indexed: 05/17/2023] Open
Abstract
Developmental patterning is essential for regulating cellular events such as axial patterning, segmentation, tissue formation, and organ size determination during embryogenesis. Understanding the patterning mechanisms remains a central challenge and fundamental interest in developmental biology. Ion-channel-regulated bioelectric signals have emerged as a player of the patterning mechanism, which may interact with morphogens. Evidence from multiple model organisms reveals the roles of bioelectricity in embryonic development, regeneration, and cancers. The Zebrafish model is the second most used vertebrate model, next to the mouse model. The zebrafish model has great potential for elucidating the functions of bioelectricity due to many advantages such as external development, transparent early embryogenesis, and tractable genetics. Here, we review genetic evidence from zebrafish mutants with fin-size and pigment changes related to ion channels and bioelectricity. In addition, we review the cell membrane voltage reporting and chemogenetic tools that have already been used or have great potential to be implemented in zebrafish models. Finally, new perspectives and opportunities for bioelectricity research with zebrafish are discussed.
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Affiliation(s)
- Martin R Silic
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA
| | - GuangJun Zhang
- Department of Comparative Pathobiology, Purdue University, West Lafayette, IN 47907, USA
- Center for Cancer Research, Purdue University, West Lafayette, IN 47907, USA
- Purdue Institute for Inflammation, Immunology and Infectious Diseases (PI4D), Purdue University, West Lafayette, IN 47907, USA
- Purdue Institute for Integrative Neuroscience, Purdue University, 625 Harrison Street, West Lafayette, IN 47907, USA
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11
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Kannan M, Vasan G, Haziza S, Huang C, Chrapkiewicz R, Luo J, Cardin JA, Schnitzer MJ, Pieribone VA. Dual-polarity voltage imaging of the concurrent dynamics of multiple neuron types. Science 2022; 378:eabm8797. [PMID: 36378956 PMCID: PMC9703638 DOI: 10.1126/science.abm8797] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Genetically encoded fluorescent voltage indicators are ideally suited to reveal the millisecond-scale interactions among and between targeted cell populations. However, current indicators lack the requisite sensitivity for in vivo multipopulation imaging. We describe next-generation green and red voltage sensors, Ace-mNeon2 and VARNAM2, and their reverse response-polarity variants pAce and pAceR. Our indicators enable 0.4- to 1-kilohertz voltage recordings from >50 spiking neurons per field of view in awake mice and ~30-minute continuous imaging in flies. Using dual-polarity multiplexed imaging, we uncovered brain state–dependent antagonism between neocortical somatostatin-expressing (SST
+
) and vasoactive intestinal peptide–expressing (VIP
+
) interneurons and contributions to hippocampal field potentials from cell ensembles with distinct axonal projections. By combining three mutually compatible indicators, we performed simultaneous triple-population imaging. These approaches will empower investigations of the dynamic interplay between neuronal subclasses at single-spike resolution.
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Affiliation(s)
- Madhuvanthi Kannan
- The John B. Pierce Laboratory, New Haven, CT 06519, USA
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT 06520, USA
| | - Ganesh Vasan
- The John B. Pierce Laboratory, New Haven, CT 06519, USA
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT 06520, USA
| | - Simon Haziza
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
| | - Cheng Huang
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
| | - Radosław Chrapkiewicz
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
| | - Junjie Luo
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Jessica A. Cardin
- Department of Neuroscience, Yale University, New Haven, CT 06520, USA
- Kavli Institute of Neuroscience, Yale University, New Haven, CT 06520, USA
- Wu Tsai Institute, Yale University, New Haven, CT 06520, USA
| | - Mark J. Schnitzer
- James H. Clark Center, Stanford University, Stanford, CA 94305, USA
- CNC Program, Stanford University, Stanford, CA 94305, USA
- Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA
| | - Vincent A. Pieribone
- The John B. Pierce Laboratory, New Haven, CT 06519, USA
- Department of Cellular and Molecular Physiology, Yale University, New Haven, CT 06520, USA
- Department of Neuroscience, Yale University, New Haven, CT 06520, USA
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12
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QuasAr Odyssey: the origin of fluorescence and its voltage sensitivity in microbial rhodopsins. Nat Commun 2022; 13:5501. [PMID: 36127376 PMCID: PMC9489792 DOI: 10.1038/s41467-022-33084-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Accepted: 08/26/2022] [Indexed: 11/29/2022] Open
Abstract
Rhodopsins had long been considered non-fluorescent until a peculiar voltage-sensitive fluorescence was reported for archaerhodopsin-3 (Arch3) derivatives. These proteins named QuasArs have been used for imaging membrane voltage changes in cell cultures and small animals. However due to the low fluorescence intensity, these constructs require use of much higher light intensity than other optogenetic tools. To develop the next generation of sensors, it is indispensable to first understand the molecular basis of the fluorescence and its modulation by the membrane voltage. Based on spectroscopic studies of fluorescent Arch3 derivatives, we propose a unique photo-reaction scheme with extended excited-state lifetimes and inefficient photoisomerization. Molecular dynamics simulations of Arch3, of the Arch3 fluorescent derivative Archon1, and of several its mutants have revealed different voltage-dependent changes of the hydrogen-bonding networks including the protonated retinal Schiff-base and adjacent residues. Experimental observations suggest that under negative voltage, these changes modulate retinal Schiff base deprotonation and promote a decrease in the populations of fluorescent species. Finally, we identified molecular constraints that further improve fluorescence quantum yield and voltage sensitivity. The authors present an in-depth investigation of excited state dynamics and molecular mechanism of the voltage sensing in microbial rhodopsins. Using a combination of spectroscopic investigations and molecular dynamics simulations, the study proposes the voltage-modulated deprotonation of the chromophore as the key event in the voltage sensing. Thus, molecular constraints that may further improve the fluorescence quantum yield and the voltage sensitivity are presented.
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13
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de Grip WJ, Ganapathy S. Rhodopsins: An Excitingly Versatile Protein Species for Research, Development and Creative Engineering. Front Chem 2022; 10:879609. [PMID: 35815212 PMCID: PMC9257189 DOI: 10.3389/fchem.2022.879609] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2022] [Accepted: 05/16/2022] [Indexed: 01/17/2023] Open
Abstract
The first member and eponym of the rhodopsin family was identified in the 1930s as the visual pigment of the rod photoreceptor cell in the animal retina. It was found to be a membrane protein, owing its photosensitivity to the presence of a covalently bound chromophoric group. This group, derived from vitamin A, was appropriately dubbed retinal. In the 1970s a microbial counterpart of this species was discovered in an archaeon, being a membrane protein also harbouring retinal as a chromophore, and named bacteriorhodopsin. Since their discovery a photogenic panorama unfolded, where up to date new members and subspecies with a variety of light-driven functionality have been added to this family. The animal branch, meanwhile categorized as type-2 rhodopsins, turned out to form a large subclass in the superfamily of G protein-coupled receptors and are essential to multiple elements of light-dependent animal sensory physiology. The microbial branch, the type-1 rhodopsins, largely function as light-driven ion pumps or channels, but also contain sensory-active and enzyme-sustaining subspecies. In this review we will follow the development of this exciting membrane protein panorama in a representative number of highlights and will present a prospect of their extraordinary future potential.
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Affiliation(s)
- Willem J. de Grip
- Leiden Institute of Chemistry, Department of Biophysical Organic Chemistry, Leiden University, Leiden, Netherlands
- Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, Netherlands
| | - Srividya Ganapathy
- Department of Imaging Physics, Delft University of Technology, Netherlands
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14
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Swanson JL, Chin PS, Romero JM, Srivastava S, Ortiz-Guzman J, Hunt PJ, Arenkiel BR. Advancements in the Quest to Map, Monitor, and Manipulate Neural Circuitry. Front Neural Circuits 2022; 16:886302. [PMID: 35719420 PMCID: PMC9204427 DOI: 10.3389/fncir.2022.886302] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/27/2022] [Indexed: 01/27/2023] Open
Abstract
Neural circuits and the cells that comprise them represent the functional units of the brain. Circuits relay and process sensory information, maintain homeostasis, drive behaviors, and facilitate cognitive functions such as learning and memory. Creating a functionally-precise map of the mammalian brain requires anatomically tracing neural circuits, monitoring their activity patterns, and manipulating their activity to infer function. Advancements in cell-type-specific genetic tools allow interrogation of neural circuits with increased precision. This review provides a broad overview of recombination-based and activity-driven genetic targeting approaches, contemporary viral tracing strategies, electrophysiological recording methods, newly developed calcium, and voltage indicators, and neurotransmitter/neuropeptide biosensors currently being used to investigate circuit architecture and function. Finally, it discusses methods for acute or chronic manipulation of neural activity, including genetically-targeted cellular ablation, optogenetics, chemogenetics, and over-expression of ion channels. With this ever-evolving genetic toolbox, scientists are continuing to probe neural circuits with increasing resolution, elucidating the structure and function of the incredibly complex mammalian brain.
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Affiliation(s)
- Jessica L. Swanson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
| | - Pey-Shyuan Chin
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
| | - Juan M. Romero
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, United States
| | - Snigdha Srivastava
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, United States
| | - Joshua Ortiz-Guzman
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
| | - Patrick J. Hunt
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, United States
| | - Benjamin R. Arenkiel
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, United States
- Jan and Dan Duncan Neurological Research Institute, Texas Children’s Hospital, Houston, TX, United States
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, United States
- Medical Scientist Training Program, Baylor College of Medicine, Houston, TX, United States
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15
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Beck C, Gong Y. Engineering rhodopsins' activation spectra using a FRET-based approach. Biophys J 2022; 121:1765-1776. [PMID: 35331688 PMCID: PMC9117881 DOI: 10.1016/j.bpj.2022.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 12/01/2021] [Accepted: 03/18/2022] [Indexed: 11/16/2022] Open
Abstract
In the past decade, optogenetics has become a nearly ubiquitous tool in neuroscience because it enables researchers to manipulate neural activity with high temporal resolution and genetic specificity. Rational engineering of optogenetic tools has produced channelrhodopsins with a wide range of kinetics and photocurrent magnitude. Genome mining for previously unidentified species of rhodopsin has uncovered optogenetic tools with diverse spectral sensitivities. However, rational engineering of a rhodopsin has thus far been unable to re-engineer spectral sensitivity while preserving full photocurrent. Here, we developed and characterized ChroME-mTFP, a rhodopsin-fluorescent protein fusion that drives photocurrent through Förster resonance energy transfer (FRET). This FRET-opsin mechanism artificially broadened the activation spectrum of the blue-green-light-activated rhodopsin ChroME by approximately 50 nm, driving higher photocurrent at blue-shifted excitation wavelengths without sacrificing kinetics. The excitation spectra's increase at short wavelengths enabled us to optogenetically excite neurons at lower excitation powers with shorter wavelengths of light. Increasing this rhodopsin's sensitivity to shorter, bluer wavelengths pushes it toward dual-channel, crosstalk-free optogenetic stimulation and imaging with green-light-activated sensors. However, this iteration of FRET-opsin suffers from some imaging-light-induced photocurrent crosstalk from green or yellow light due to maintained, low-efficiency excitation at longer wavelengths.
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Affiliation(s)
- Connor Beck
- Department of Biomedical Engineering, Duke University, Durham, North Carolina.
| | - Yiyang Gong
- Department of Biomedical Engineering, Duke University, Durham, North Carolina.
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16
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Farrants H, Tebo AG. Fluorescent chemigenetic actuators and indicators for use in living animals. Curr Opin Pharmacol 2022; 62:159-167. [DOI: 10.1016/j.coph.2021.12.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 12/03/2021] [Accepted: 12/12/2021] [Indexed: 11/28/2022]
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17
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Fluorescence imaging of large-scale neural ensemble dynamics. Cell 2022; 185:9-41. [PMID: 34995519 PMCID: PMC8849612 DOI: 10.1016/j.cell.2021.12.007] [Citation(s) in RCA: 68] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 12/06/2021] [Accepted: 12/07/2021] [Indexed: 12/14/2022]
Abstract
Recent progress in fluorescence imaging allows neuroscientists to observe the dynamics of thousands of individual neurons, identified genetically or by their connectivity, across multiple brain areas and for extended durations in awake behaving mammals. We discuss advances in fluorescent indicators of neural activity, viral and genetic methods to express these indicators, chronic animal preparations for long-term imaging studies, and microscopes to monitor and manipulate the activity of large neural ensembles. Ca2+ imaging studies of neural activity can track brain area interactions and distributed information processing at cellular resolution. Across smaller spatial scales, high-speed voltage imaging reveals the distinctive spiking patterns and coding properties of targeted neuron types. Collectively, these innovations will propel studies of brain function and dovetail with ongoing neuroscience initiatives to identify new neuron types and develop widely applicable, non-human primate models. The optical toolkit's growing sophistication also suggests that "brain observatory" facilities would be useful open resources for future brain-imaging studies.
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18
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Abdelfattah AS, Ahuja S, Akkin T, Allu SR, Brake J, Boas DA, Buckley EM, Campbell RE, Chen AI, Cheng X, Čižmár T, Costantini I, De Vittorio M, Devor A, Doran PR, El Khatib M, Emiliani V, Fomin-Thunemann N, Fainman Y, Fernandez-Alfonso T, Ferri CGL, Gilad A, Han X, Harris A, Hillman EMC, Hochgeschwender U, Holt MG, Ji N, Kılıç K, Lake EMR, Li L, Li T, Mächler P, Miller EW, Mesquita RC, Nadella KMNS, Nägerl UV, Nasu Y, Nimmerjahn A, Ondráčková P, Pavone FS, Perez Campos C, Peterka DS, Pisano F, Pisanello F, Puppo F, Sabatini BL, Sadegh S, Sakadzic S, Shoham S, Shroff SN, Silver RA, Sims RR, Smith SL, Srinivasan VJ, Thunemann M, Tian L, Tian L, Troxler T, Valera A, Vaziri A, Vinogradov SA, Vitale F, Wang LV, Uhlířová H, Xu C, Yang C, Yang MH, Yellen G, Yizhar O, Zhao Y. Neurophotonic tools for microscopic measurements and manipulation: status report. NEUROPHOTONICS 2022; 9:013001. [PMID: 35493335 PMCID: PMC9047450 DOI: 10.1117/1.nph.9.s1.013001] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics' agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, this status report reviews an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion report, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- Ahmed S. Abdelfattah
- Brown University, Department of Neuroscience, Providence, Rhode Island, United States
| | - Sapna Ahuja
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Taner Akkin
- University of Minnesota, Department of Biomedical Engineering, Minneapolis, Minnesota, United States
| | - Srinivasa Rao Allu
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - David A. Boas
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Erin M. Buckley
- Georgia Institute of Technology and Emory University, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University, Department of Pediatrics, Atlanta, Georgia, United States
| | - Robert E. Campbell
- University of Tokyo, Department of Chemistry, Tokyo, Japan
- University of Alberta, Department of Chemistry, Edmonton, Alberta, Canada
| | - Anderson I. Chen
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Xiaojun Cheng
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Tomáš Čižmár
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Irene Costantini
- University of Florence, European Laboratory for Non-Linear Spectroscopy, Department of Biology, Florence, Italy
- National Institute of Optics, National Research Council, Rome, Italy
| | - Massimo De Vittorio
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Anna Devor
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Patrick R. Doran
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Mirna El Khatib
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | | | - Natalie Fomin-Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Yeshaiahu Fainman
- University of California San Diego, Department of Electrical and Computer Engineering, La Jolla, California, United States
| | - Tomas Fernandez-Alfonso
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Christopher G. L. Ferri
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Ariel Gilad
- The Hebrew University of Jerusalem, Institute for Medical Research Israel–Canada, Department of Medical Neurobiology, Faculty of Medicine, Jerusalem, Israel
| | - Xue Han
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Andrew Harris
- Weizmann Institute of Science, Department of Brain Sciences, Rehovot, Israel
| | | | - Ute Hochgeschwender
- Central Michigan University, Department of Neuroscience, Mount Pleasant, Michigan, United States
| | - Matthew G. Holt
- University of Porto, Instituto de Investigação e Inovação em Saúde (i3S), Porto, Portugal
| | - Na Ji
- University of California Berkeley, Department of Physics, Berkeley, California, United States
| | - Kıvılcım Kılıç
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Evelyn M. R. Lake
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, Connecticut, United States
| | - Lei Li
- California Institute of Technology, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, Pasadena, California, United States
| | - Tianqi Li
- University of Minnesota, Department of Biomedical Engineering, Minneapolis, Minnesota, United States
| | - Philipp Mächler
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Evan W. Miller
- University of California Berkeley, Departments of Chemistry and Molecular & Cell Biology and Helen Wills Neuroscience Institute, Berkeley, California, United States
| | | | | | - U. Valentin Nägerl
- Interdisciplinary Institute for Neuroscience University of Bordeaux & CNRS, Bordeaux, France
| | - Yusuke Nasu
- University of Tokyo, Department of Chemistry, Tokyo, Japan
| | - Axel Nimmerjahn
- Salk Institute for Biological Studies, Waitt Advanced Biophotonics Center, La Jolla, California, United States
| | - Petra Ondráčková
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Francesco S. Pavone
- National Institute of Optics, National Research Council, Rome, Italy
- University of Florence, European Laboratory for Non-Linear Spectroscopy, Department of Physics, Florence, Italy
| | - Citlali Perez Campos
- Columbia University, Zuckerman Mind Brain Behavior Institute, New York, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behavior Institute, New York, United States
| | - Filippo Pisano
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Ferruccio Pisanello
- Istituto Italiano di Tecnologia, Center for Biomolecular Nanotechnologies, Arnesano, Italy
| | - Francesca Puppo
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Bernardo L. Sabatini
- Harvard Medical School, Howard Hughes Medical Institute, Department of Neurobiology, Boston, Massachusetts, United States
| | - Sanaz Sadegh
- University of California San Diego, Departments of Neurosciences, La Jolla, California, United States
| | - Sava Sakadzic
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Shy Shoham
- New York University Grossman School of Medicine, Tech4Health and Neuroscience Institutes, New York, New York, United States
| | - Sanaya N. Shroff
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - R. Angus Silver
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Ruth R. Sims
- Sorbonne University, INSERM, CNRS, Institut de la Vision, Paris, France
| | - Spencer L. Smith
- University of California Santa Barbara, Department of Electrical and Computer Engineering, Santa Barbara, California, United States
| | - Vivek J. Srinivasan
- New York University Langone Health, Departments of Ophthalmology and Radiology, New York, New York, United States
| | - Martin Thunemann
- Boston University, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Lei Tian
- Boston University, Departments of Electrical Engineering and Biomedical Engineering, Boston, Massachusetts, United States
| | - Lin Tian
- University of California Davis, Department of Biochemistry and Molecular Medicine, Davis, California, United States
| | - Thomas Troxler
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Antoine Valera
- University College London, Department of Neuroscience, Physiology and Pharmacology, London, United Kingdom
| | - Alipasha Vaziri
- Rockefeller University, Laboratory of Neurotechnology and Biophysics, New York, New York, United States
- The Rockefeller University, The Kavli Neural Systems Institute, New York, New York, United States
| | - Sergei A. Vinogradov
- University of Pennsylvania, Perelman School of Medicine, Department of Biochemistry and Biophysics, Philadelphia, Pennsylvania, United States
- University of Pennsylvania, School of Arts and Sciences, Department of Chemistry, Philadelphia, Pennsylvania, United States
| | - Flavia Vitale
- Center for Neuroengineering and Therapeutics, Departments of Neurology, Bioengineering, Physical Medicine and Rehabilitation, Philadelphia, Pennsylvania, United States
| | - Lihong V. Wang
- California Institute of Technology, Andrew and Peggy Cherng Department of Medical Engineering, Department of Electrical Engineering, Pasadena, California, United States
| | - Hana Uhlířová
- Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | - Chris Xu
- Cornell University, School of Applied and Engineering Physics, Ithaca, New York, United States
| | - Changhuei Yang
- California Institute of Technology, Departments of Electrical Engineering, Bioengineering and Medical Engineering, Pasadena, California, United States
| | - Mu-Han Yang
- University of California San Diego, Department of Electrical and Computer Engineering, La Jolla, California, United States
| | - Gary Yellen
- Harvard Medical School, Department of Neurobiology, Boston, Massachusetts, United States
| | - Ofer Yizhar
- Weizmann Institute of Science, Department of Brain Sciences, Rehovot, Israel
| | - Yongxin Zhao
- Carnegie Mellon University, Department of Biological Sciences, Pittsburgh, Pennsylvania, United States
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19
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Xiao S, Lowet E, Gritton HJ, Fabris P, Wang Y, Sherman J, Mount RA, Tseng HA, Man HY, Straub C, Piatkevich KD, Boyden ES, Mertz J, Han X. Large-scale voltage imaging in behaving mice using targeted illumination. iScience 2021; 24:103263. [PMID: 34761183 PMCID: PMC8567393 DOI: 10.1016/j.isci.2021.103263] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 08/30/2021] [Accepted: 10/11/2021] [Indexed: 11/26/2022] Open
Abstract
Recent improvements in genetically encoded voltage indicators enabled optical imaging of action potentials and subthreshold transmembrane voltage in vivo. To perform high-speed voltage imaging of many neurons simultaneously over a large anatomical area, widefield microscopy remains an essential tool. However, the lack of optical sectioning makes widefield microscopy prone to background cross-contamination. We implemented a digital-micromirror-device-based targeted illumination strategy to restrict illumination to the cells of interest and quantified the resulting improvement both theoretically and experimentally with SomArchon expressing neurons. We found that targeted illumination increased SomArchon signal contrast, decreased photobleaching, and reduced background cross-contamination. With the use of a high-speed, large-area sCMOS camera, we routinely imaged tens of spiking neurons simultaneously over minutes in behaving mice. Thus, the targeted illumination strategy described here offers a simple solution for widefield voltage imaging of many neurons over a large field of view in behaving animals.
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Affiliation(s)
- Sheng Xiao
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Eric Lowet
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Howard J. Gritton
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
- Department of Comparative Biosciences, University of Illinois, Urbana, IL 61802, USA
| | - Pierre Fabris
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Yangyang Wang
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Jack Sherman
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Rebecca A. Mount
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Hua-an Tseng
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Heng-Ye Man
- Department of Biology, Boston University, Boston, MA 02215, USA
| | - Christoph Straub
- Department of Biomedical Sciences, College of Osteopathic Medicine, University of New England, Biddeford, ME 04005, USA
| | - Kiryl D. Piatkevich
- School of Life Sciences, Westlake University, Westlake Laboratory of Life Sciences and Biomedicine, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Edward S. Boyden
- MIT McGovern Institute for Brain Research, MIT, Cambridge, MA 02139, USA
- Howard Hughes Medical Institute, MIT, Cambridge, MA 02139, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
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20
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Bringing together the best of chemistry and biology: hybrid indicators for imaging neuronal membrane potential. J Neurosci Methods 2021; 363:109348. [PMID: 34480955 DOI: 10.1016/j.jneumeth.2021.109348] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Revised: 08/27/2021] [Accepted: 08/30/2021] [Indexed: 12/15/2022]
Abstract
Membrane potential is an indispensable biophysical signal in neurobiology. Imaging neuronal electrical signals with fluorescent indicators allows for non-invasive recording at high spatial resolution. Over the past decades, both genetically encoded voltage indicators (GEVIs) and organic voltage sensing dyes (OVSDs) have been developed to achieve imaging membrane potential dynamics in cultured neurons and in vivo. More recently, hybrid voltage indicators have gained increasing attention due to their superior fluorescent quantum yield and photostability as compared to conventional GEVIs. In this mini-review, we summarize the design, characterization and biological applications of hybrid voltage indicators, and discuss future improvements.
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21
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Zhang XM, Yokoyama T, Sakamoto M. Imaging Voltage with Microbial Rhodopsins. Front Mol Biosci 2021; 8:738829. [PMID: 34513932 PMCID: PMC8423911 DOI: 10.3389/fmolb.2021.738829] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 08/11/2021] [Indexed: 12/15/2022] Open
Abstract
Membrane potential is the critical parameter that reflects the excitability of a neuron, and it is usually measured by electrophysiological recordings with electrodes. However, this is an invasive approach that is constrained by the problems of lacking spatial resolution and genetic specificity. Recently, the development of a variety of fluorescent probes has made it possible to measure the activity of individual cells with high spatiotemporal resolution. The adaptation of this technique to image electrical activity in neurons has become an informative method to study neural circuits. Genetically encoded voltage indicators (GEVIs) can be used with superior performance to accurately target specific genetic populations and reveal neuronal dynamics on a millisecond scale. Microbial rhodopsins are commonly used as optogenetic actuators to manipulate neuronal activities and to explore the circuit mechanisms of brain function, but they also can be used as fluorescent voltage indicators. In this review, we summarize recent advances in the design and the application of rhodopsin-based GEVIs.
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Affiliation(s)
- Xiao Min Zhang
- Department of Pathophysiology, Guangdong Provincial Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, China
| | - Tatsushi Yokoyama
- Department of Optical Neural and Molecular Physiology, Graduate School of Biostudies, Kyoto University, Kyoto, Japan
| | - Masayuki Sakamoto
- Department of Optical Neural and Molecular Physiology, Graduate School of Biostudies, Kyoto University, Kyoto, Japan.,Precursory Research for Embryonic Science and Technology (PRESTO), Japan Science and Technology Agency, Kyoto, Japan
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22
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Post MR, Sulzer D. The chemical tools for imaging dopamine release. Cell Chem Biol 2021; 28:748-764. [PMID: 33894160 PMCID: PMC8532025 DOI: 10.1016/j.chembiol.2021.04.005] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 02/23/2021] [Accepted: 04/06/2021] [Indexed: 02/07/2023]
Abstract
Dopamine is a modulatory neurotransmitter involved in learning, motor functions, and reward. Many neuropsychiatric disorders, including Parkinson's disease, autism, and schizophrenia, are associated with imbalances or dysfunction in the dopaminergic system. Yet, our understanding of these pervasive public health issues is limited by our ability to effectively image dopamine in humans, which has long been a goal for chemists and neuroscientists. The last two decades have witnessed the development of many molecules used to trace dopamine. We review the small molecules, nanoparticles, and protein sensors used with fluorescent microscopy/photometry, MRI, and PET that shape dopamine research today. None of these tools observe dopamine itself, but instead harness the biology of the dopamine system-its synthetic and metabolic pathways, synaptic vesicle cycle, and receptors-in elegant ways. Their advantages and weaknesses are covered here, along with recent examples and the chemistry and biology that allow them to function.
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Affiliation(s)
- Michael R Post
- Department of Psychiatry, Columbia University Medical Center, New York, NY, USA; Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, USA.
| | - David Sulzer
- Departments of Psychiatry, Neurology, and Pharmacology, Columbia University Medical Center, New York, NY, USA; Division of Molecular Therapeutics, New York State Psychiatric Institute, New York, NY, USA.
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23
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Adam Y. All-optical electrophysiology in behaving animals. J Neurosci Methods 2021; 353:109101. [PMID: 33600851 DOI: 10.1016/j.jneumeth.2021.109101] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 01/13/2021] [Accepted: 02/09/2021] [Indexed: 12/28/2022]
Abstract
Technology for simultaneous control and readout of the membrane potential of multiple neurons in behaving animals at high spatio-temporal resolution will have a high impact on neuroscience research. Significant progress in the development of Genetically Encoded Voltage Indicators (GEVIs) now enables to optically record subthreshold and spiking activity from ensembles of cells in behaving animals. In some cases, the GEVIs were also combined with optogenetic actuators to enable 'all-optical' control and readout of membrane potential at cellular resolution. Here I describe the recent progress in GEVI development and discuss the various aspects necessary to perform a successful 'all-optical' electrophysiology experiment in behaving, head-fixed animals. These aspects include the voltage indicators, the optogenetic actuators, strategies for protein expression, optical hardware, and image processing software. Furthermore, I discuss various applications of the technology, highlighting its advantages over classic electrode-based techniques. I argue that GEVIs now transformed from a 'promising' technology to a practical tool that can be used to tackle fundamental questions in neuroscience.
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Affiliation(s)
- Yoav Adam
- Edmond and Lily Safra Center for Brain Science, The Hebrew University of Jerusalem, Jerusalem, Israel.
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24
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A dark quencher genetically encodable voltage indicator (dqGEVI) exhibits high fidelity and speed. Proc Natl Acad Sci U S A 2021; 118:2020235118. [PMID: 33531364 PMCID: PMC8017929 DOI: 10.1073/pnas.2020235118] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
Voltage sensing with genetically expressed optical probes is highly desirable for large-scale recordings of neuronal activity and detection of localized voltage signals in single neurons. Here we describe a method for a two-component (hybrid) genetically encodable fluorescent voltage sensing in neurons. The approach uses a glycosylphosphatidylinositol-tagged fluorescent protein (enhanced green fluorescent protein) that ensures the fluorescence to be specifically confined to the outside of the plasma membrane and D3, a voltage-dependent quencher. Previous hybrid genetically encoded voltage sensing approaches relied on a single quenching molecule, dipycrilamine (DPA), which is toxic, increases membrane capacitance, interferes with neurotransmitters, and is explosive. Our method uses a nontoxic and nonexplosive compound that performs better than DPA in all aspects of fluorescent voltage sensing. Voltage sensing with genetically expressed optical probes is highly desirable for large-scale recordings of neuronal activity and detection of localized voltage signals in single neurons. Most genetically encodable voltage indicators (GEVI) have drawbacks including slow response, low fluorescence, or excessive bleaching. Here we present a dark quencher GEVI approach (dqGEVI) using a Förster resonance energy transfer pair between a fluorophore glycosylphosphatidylinositol–enhanced green fluorescent protein (GPI-eGFP) on the outer surface of the neuronal membrane and an azo-benzene dye quencher (D3) that rapidly moves in the membrane driven by voltage. In contrast to previous probes, the sensor has a single photon bleaching time constant of ∼40 min, has a high temporal resolution and fidelity for detecting action potential firing at 100 Hz, resolves membrane de- and hyperpolarizations of a few millivolts, and has negligible effects on passive membrane properties or synaptic events. The dqGEVI approach should be a valuable tool for optical recordings of subcellular or population membrane potential changes in nerve cells.
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25
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Liang Y, Walczak P. Long term intravital single cell tracking under multiphoton microscopy. J Neurosci Methods 2020; 349:109042. [PMID: 33340557 DOI: 10.1016/j.jneumeth.2020.109042] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 12/07/2020] [Accepted: 12/11/2020] [Indexed: 12/13/2022]
Abstract
Visualizing and tracking cells over time in a living organism has been a much-coveted dream before the invention of intravital microscopy. The opaque nature of tissue was a major hurdle that was remedied by the multiphoton microscopy. With the advancement of optical imaging and fluorescent labeling tools, intravital high resolution imaging has become increasingly accessible over the past few years. Long-term intravital tracking of single cells (LIST) under multiphoton microscopy provides a unique opportunity to gain insight into the longitudinal changes in the morphology, migration, or function of cells or subcellular structures. It is particularly suitable for studying slow-evolving cellular and molecular events during normal development or disease progression, without losing the opportunity of catching fast events such as calcium signals. Here, we review the application of LIST under 2-photon microscopy in various fields of neurobiology and discuss challenges and new directions in labeling and imaging methods for LIST. Overall, this review provides an overview of current applications of LIST in mammals, which is an emerging field that will contribute to a better understanding of essential molecular and cellular events in health and disease.
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Affiliation(s)
- Yajie Liang
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA.
| | - Piotr Walczak
- Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
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26
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Monakhov MV, Matlashov ME, Colavita M, Song C, Shcherbakova DM, Antic SD, Verkhusha VV, Knöpfel T. Screening and Cellular Characterization of Genetically Encoded Voltage Indicators Based on Near-Infrared Fluorescent Proteins. ACS Chem Neurosci 2020; 11:3523-3531. [PMID: 33063984 DOI: 10.1021/acschemneuro.0c00046] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
We developed genetically encoded voltage indicators using a transmembrane voltage-sensing domain and bright near-infrared fluorescent proteins derived from bacterial phytochromes. These new voltage indicators are excited by 640 nm light and emission is measured at 670 nm, allowing imaging in the near-infrared tissue transparency window. The spectral properties of our new indicators permit seamless voltage imaging with simultaneous blue-green light optogenetic actuator activation as well as simultaneous voltage-calcium imaging when paired with green calcium indicators. Iterative optimizations led to a fluorescent probe, here termed nirButterfly, which reliably reports neuronal activities including subthreshold membrane potential depolarization and hyperpolarization as well as spontaneous spiking or electrically- and optogenetically evoked action potentials. This enables largely improved all-optical causal interrogations of physiology.
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Affiliation(s)
- Mikhail V Monakhov
- Institute for Systems Genomics, Stem Cell Institute, Department of Neuroscience, UConn Health, Farmington, Connecticut 06030, United States
- Department of Anatomy and Structural Biology and Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, New York 10461, United States
| | - Mikhail E Matlashov
- Department of Anatomy and Structural Biology and Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, New York 10461, United States
| | - Michelangelo Colavita
- Laboratory for Neuronal Circuit Dynamics, Imperial College London, London W12 0NN, U.K
| | - Chenchen Song
- Laboratory for Neuronal Circuit Dynamics, Imperial College London, London W12 0NN, U.K
| | - Daria M Shcherbakova
- Department of Anatomy and Structural Biology and Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, New York 10461, United States
| | - Srdjan D Antic
- Institute for Systems Genomics, Stem Cell Institute, Department of Neuroscience, UConn Health, Farmington, Connecticut 06030, United States
| | - Vladislav V Verkhusha
- Department of Anatomy and Structural Biology and Gruss-Lipper Biophotonics Center, Albert Einstein College of Medicine, Bronx, New York 10461, United States
| | - Thomas Knöpfel
- Laboratory for Neuronal Circuit Dynamics, Imperial College London, London W12 0NN, U.K
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