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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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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: 3] [Impact Index Per Article: 3.0] [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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6
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Debnath A, Williams PDE, Bamber BA. Reduced Ca2+ transient amplitudes may signify increased or decreased depolarization depending on the neuromodulatory signaling pathway. Front Neurosci 2022; 16:931328. [PMID: 35937887 PMCID: PMC9354622 DOI: 10.3389/fnins.2022.931328] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Neuromodulators regulate neuronal excitability and bias neural circuit outputs. Optical recording of neuronal Ca2+ transients is a powerful approach to study the impact of neuromodulators on neural circuit dynamics. We are investigating the polymodal nociceptor ASH in Caenorhabditis elegans to better understand the relationship between neuronal excitability and optically recorded Ca2+ transients. ASHs depolarize in response to the aversive olfactory stimulus 1-octanol (1-oct) with a concomitant rise in somal Ca2+, stimulating an aversive locomotory response. Serotonin (5-HT) potentiates 1-oct avoidance through Gαq signaling, which inhibits L-type voltage-gated Ca2+ channels in ASH. Although Ca2+ signals in the ASH soma decrease, depolarization amplitudes increase because Ca2+ mediates inhibitory feedback control of membrane potential in this context. Here, we investigate octopamine (OA) signaling in ASH to assess whether this negative correlation between somal Ca2+ and depolarization amplitudes is a general phenomenon, or characteristic of certain neuromodulatory pathways. Like 5-HT, OA reduces somal Ca2+ transient amplitudes in ASH neurons. However, OA antagonizes 5-HT modulation of 1-oct avoidance behavior, suggesting that OA may signal through a different pathway. We further show that the pathway for OA diminution of ASH somal Ca2+ consists of the OCTR-1 receptor, the Go heterotrimeric G-protein, and the G-protein activated inwardly rectifying channels IRK-2 and IRK-3, and this pathway reduces depolarization amplitudes in parallel with somal Ca2+ transient amplitudes. Therefore, even within a single neuron, somal Ca2+ signal reduction may indicate either increased or decreased depolarization amplitude, depending on which neuromodulatory signaling pathways are activated, underscoring the need for careful interpretation of Ca2+ imaging data in neuromodulatory studies.
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Affiliation(s)
- Arunima Debnath
- Department of Biological Sciences, The University of Toledo, Toledo, OH, United States
| | - Paul D. E. Williams
- Department of Biomedical Sciences, College of Veterinary Medicine, Iowa State University, Ames, IA, United States
| | - Bruce A. Bamber
- Department of Biological Sciences, The University of Toledo, Toledo, OH, United States
- *Correspondence: Bruce A. Bamber,
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Zhu MH, Jogdand AH, Jang J, Nagella SC, Das B, Milosevic MM, Yan R, Antic SD. Evoked Cortical Depolarizations Before and After the Amyloid Plaque Accumulation: Voltage Imaging Study. J Alzheimers Dis 2022; 88:1443-1458. [PMID: 35811528 PMCID: PMC10493004 DOI: 10.3233/jad-220249] [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] [Indexed: 11/15/2022]
Abstract
BACKGROUND In Alzheimer's disease (AD), synaptic dysfunction is thought to occur many years before the onset of cognitive decline. OBJECTIVE Detecting synaptic dysfunctions at the earliest stage of AD would be desirable in both clinic and research settings. METHODS Population voltage imaging allows monitoring of synaptic depolarizations, to which calcium imaging is relatively blind. We developed an AD mouse model (APPswe/PS1dE9 background) expressing a genetically-encoded voltage indicator (GEVI) in the neocortex. GEVI was restricted to the excitatory pyramidal neurons (unlike the voltage-sensitive dyes). RESULTS Expression of GEVI did not disrupt AD model formation of amyloid plaques. GEVI expression was stable in both AD model mice and Control (healthy) littermates (CTRL) over 247 days postnatal. Brain slices were stimulated in layer 2/3. From the evoked voltage waveforms, we extracted several parameters for comparison AD versus CTRL. Some parameters (e.g., temporal summation, refractoriness, and peak latency) were weak predictors, while other parameters (e.g., signal amplitude, attenuation with distance, and duration (half-width) of the evoked transients) were stronger predictors of the AD condition. Around postnatal age 150 days (P150) and especially at P200, synaptically-evoked voltage signals in brain slices were weaker in the AD groups versus the age- and sex-matched CTRL groups, suggesting an AD-mediated synaptic weakening that coincides with the accumulation of plaques. However, at the youngest ages examined, P40 and P80, the AD groups showed differentially stronger signals, suggesting "hyperexcitability" prior to the formation of plaques. CONCLUSION Our results indicate bidirectional alterations in cortical physiology in AD model mice; occurring both prior (P40-80), and after (P150-200) the amyloid deposition.
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Affiliation(s)
- Mei Hong Zhu
- Department of Neuroscience, UConn Health, School of Medicine, Farmington, CT, USA
| | - Aditi H Jogdand
- Department of Neuroscience, UConn Health, School of Medicine, Farmington, CT, USA
| | - Jinyoung Jang
- Department of Neuroscience, UConn Health, School of Medicine, Farmington, CT, USA
| | - Sai C Nagella
- Department of Neuroscience, UConn Health, School of Medicine, Farmington, CT, USA
| | - Brati Das
- Department of Neuroscience, UConn Health, School of Medicine, Farmington, CT, USA
| | - Milena M Milosevic
- Department of Neuroscience, UConn Health, School of Medicine, Farmington, CT, USA
| | - Riqiang Yan
- Department of Neuroscience, UConn Health, School of Medicine, Farmington, CT, USA
| | - Srdjan D Antic
- Department of Neuroscience, UConn Health, School of Medicine, Farmington, CT, USA
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