1
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Herasymenko K, Walisinghe D, Konno M, Barneschi L, de Waele I, Sliwa M, Inoue K, Olivucci M, Haacke S. Archaerhodopsin 3 is an ideal template for the engineering of highly fluorescent optogenetic reporters. Chem Sci 2025; 16:761-774. [PMID: 39634579 PMCID: PMC11612921 DOI: 10.1039/d4sc05120c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2024] [Accepted: 11/13/2024] [Indexed: 12/07/2024] Open
Abstract
Archaerhodopsin-3 (AR-3) variants stand out among other rhodopsins in that they display a weak, but voltage-sensitive, near-infrared fluorescence emission. This has led to their application in optogenetics both in cell cultures and small animals. However, in the context of improving the fluorescence characteristics of the next generation of AR-3 reporters, an understanding of their ultrafast light-response in light-adapted conditions, is mandatory. To this end, we present a combined experimental and computational investigation of the excited state dynamics and quantum yields of AR-3 and its DETC and Arch-5 variants. The latter always display a mixture of all-trans/15-anti and 13-cis/15-syn isomers, which leads to a bi-exponential excited state decay. The isomerisation quantum yield is reduced more than 20 times as compared to WT AR-3 and proves that the steady-state fluorescence is induced by a single absorption photon event. In wild-type AR-3, we show that a 300 fs, barrier-less and vibrationally coherent isomerization is driven by an unusual covalent electronic character of its all-trans retinal chromophore leading to a metastable twisted diradical (TIDIR), in clear contrast to the standard charge-transfer scenario established for other microbial rhodopsins. We discuss how the presence of TIDIR makes AR-3 an ideal candidate for the design of variants with a one-photon induced fluorescence possibly reaching the emission quantum yield of the top natural emitter neorhodopsin (NeoR).
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Affiliation(s)
| | - Danushka Walisinghe
- Department of Chemistry, Bowling Green State University Bowling Green OH 43403 USA
| | - Masae Konno
- The Institute for Solid State Physics, University of Tokyo 5-1-5 Kashiwano-ha Kashiwa Chiba 277-8581 Japan
| | - Leonardo Barneschi
- Dipartimento di Biotecnologie, Chimica e Farmacia, Università di Siena I-53100 Siena Italy
| | | | - Michel Sliwa
- LASIRE, Université de Lille, CNRS 59000 Lille France
- LOB, CNRS, INSERM, École Polytechnique, Inst. Polytechnique de Paris 91120 Palaiseau France
| | - Keiichi Inoue
- The Institute for Solid State Physics, University of Tokyo 5-1-5 Kashiwano-ha Kashiwa Chiba 277-8581 Japan
| | - Massimo Olivucci
- Department of Chemistry, Bowling Green State University Bowling Green OH 43403 USA
- Dipartimento di Biotecnologie, Chimica e Farmacia, Università di Siena I-53100 Siena Italy
| | - Stefan Haacke
- University of Strasbourg, CNRS, IPCMS 23 Rue du Loess 67034 Strasbourg France
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2
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Clarke JPWE, Messmer ML, Pilon J, Reding J, Thibault PA, Salapa HE, Levin MC. Dysfunctional RNA binding protein induced neurodegeneration is attenuated by inhibition of the integrated stress response. Biochim Biophys Acta Mol Basis Dis 2025; 1871:167562. [PMID: 39521193 DOI: 10.1016/j.bbadis.2024.167562] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Revised: 10/14/2024] [Accepted: 11/01/2024] [Indexed: 11/16/2024]
Abstract
Dysfunction of the RNA binding protein heterogeneous nuclear ribonucleoprotein A1 (hnRNP A1) contributes to neurodegeneration, the primary cause of permanent disability in multiple sclerosis (MS). To better understand the role of hnRNP A1 dysfunction in the pathogenesis of neurodegeneration, we utilized optogenetics-driven hnRNP A1 clustering to model its dysfunction in neuron-like differentiated Neuro-2A cells. hnRNP A1 clustering activates the integrated stress response (ISR) and results in a neurodegenerative phenotype marked by decreased neuronal protein translation and neurite loss. Small molecule inhibition of the ISR with either PERKi (GSK2606414) or ISRIB (integrated stress response inhibitor) attenuated both the decrease in neuronal translation and neurite loss, without affecting hnRNP A1 clustering. We then confirmed a strong association between hnRNP A1 clustering and ISR activation in neurons from MS brains. These data illustrate that hnRNP A1 dysfunction promotes neurodegeneration by activation of the ISR in vitro and in vivo, thus revealing a novel therapeutic target to reduce neurodegeneration and subsequent disability in MS.
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Affiliation(s)
- Joseph-Patrick W E Clarke
- Office of the Saskatchewan Multiple Sclerosis Clinical Research Chair, University of Saskatchewan, Saskatoon, SK S7K-0M7, Canada; Cameco MS Neuroscience Research Centre, College of Medicine, University of Saskatchewan, Saskatoon, SK S7K 0M7, Canada; Department of Medicine, Neurology Division, University of Saskatchewan, Saskatoon, SK S7N-5E5, Canada.
| | - Miranda L Messmer
- Office of the Saskatchewan Multiple Sclerosis Clinical Research Chair, University of Saskatchewan, Saskatoon, SK S7K-0M7, Canada; Cameco MS Neuroscience Research Centre, College of Medicine, University of Saskatchewan, Saskatoon, SK S7K 0M7, Canada; Department of Anatomy, Physiology and Pharmacology, University of Saskatchewan, Saskatoon, SK S7N-5E5, Canada
| | - Jacob Pilon
- Office of the Saskatchewan Multiple Sclerosis Clinical Research Chair, University of Saskatchewan, Saskatoon, SK S7K-0M7, Canada; Cameco MS Neuroscience Research Centre, College of Medicine, University of Saskatchewan, Saskatoon, SK S7K 0M7, Canada; Department of Health Sciences, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N-5E5, Canada
| | - Jenna Reding
- Office of the Saskatchewan Multiple Sclerosis Clinical Research Chair, University of Saskatchewan, Saskatoon, SK S7K-0M7, Canada; Cameco MS Neuroscience Research Centre, College of Medicine, University of Saskatchewan, Saskatoon, SK S7K 0M7, Canada; Department of Anatomy, Physiology and Pharmacology, University of Saskatchewan, Saskatoon, SK S7N-5E5, Canada
| | - Patricia A Thibault
- Office of the Saskatchewan Multiple Sclerosis Clinical Research Chair, University of Saskatchewan, Saskatoon, SK S7K-0M7, Canada; Cameco MS Neuroscience Research Centre, College of Medicine, University of Saskatchewan, Saskatoon, SK S7K 0M7, Canada; Department of Medicine, Neurology Division, University of Saskatchewan, Saskatoon, SK S7N-5E5, Canada
| | - Hannah E Salapa
- Office of the Saskatchewan Multiple Sclerosis Clinical Research Chair, University of Saskatchewan, Saskatoon, SK S7K-0M7, Canada; Cameco MS Neuroscience Research Centre, College of Medicine, University of Saskatchewan, Saskatoon, SK S7K 0M7, Canada; Department of Medicine, Neurology Division, University of Saskatchewan, Saskatoon, SK S7N-5E5, Canada
| | - Michael C Levin
- Office of the Saskatchewan Multiple Sclerosis Clinical Research Chair, University of Saskatchewan, Saskatoon, SK S7K-0M7, Canada; Cameco MS Neuroscience Research Centre, College of Medicine, University of Saskatchewan, Saskatoon, SK S7K 0M7, Canada; Department of Medicine, Neurology Division, University of Saskatchewan, Saskatoon, SK S7N-5E5, Canada; Department of Health Sciences, College of Medicine, University of Saskatchewan, Saskatoon, SK S7N-5E5, Canada; Department of Anatomy, Physiology and Pharmacology, University of Saskatchewan, Saskatoon, SK S7N-5E5, Canada.
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3
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Gest AM, Sahan AZ, Zhong Y, Lin W, Mehta S, Zhang J. Molecular Spies in Action: Genetically Encoded Fluorescent Biosensors Light up Cellular Signals. Chem Rev 2024; 124:12573-12660. [PMID: 39535501 PMCID: PMC11613326 DOI: 10.1021/acs.chemrev.4c00293] [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: 04/17/2024] [Revised: 09/07/2024] [Accepted: 09/20/2024] [Indexed: 11/16/2024]
Abstract
Cellular function is controlled through intricate networks of signals, which lead to the myriad pathways governing cell fate. Fluorescent biosensors have enabled the study of these signaling pathways in living systems across temporal and spatial scales. Over the years there has been an explosion in the number of fluorescent biosensors, as they have become available for numerous targets, utilized across spectral space, and suited for various imaging techniques. To guide users through this extensive biosensor landscape, we discuss critical aspects of fluorescent proteins for consideration in biosensor development, smart tagging strategies, and the historical and recent biosensors of various types, grouped by target, and with a focus on the design and recent applications of these sensors in living systems.
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Affiliation(s)
- Anneliese
M. M. Gest
- Department
of Pharmacology, University of California,
San Diego, La Jolla, California 92093, United States
| | - Ayse Z. Sahan
- Department
of Pharmacology, University of California,
San Diego, La Jolla, California 92093, United States
- Biomedical
Sciences Graduate Program, University of
California, San Diego, La Jolla, California 92093, United States
| | - Yanghao Zhong
- Department
of Pharmacology, University of California,
San Diego, La Jolla, California 92093, United States
| | - Wei Lin
- Department
of Pharmacology, University of California,
San Diego, La Jolla, California 92093, United States
| | - Sohum Mehta
- Department
of Pharmacology, University of California,
San Diego, La Jolla, California 92093, United States
| | - Jin Zhang
- Department
of Pharmacology, University of California,
San Diego, La Jolla, California 92093, United States
- Shu
Chien-Gene Lay Department of Bioengineering, University of California, San Diego, La Jolla, California 92093, United States
- Department
of Chemistry and Biochemistry, University
of California, San Diego, La Jolla, California 92093, United States
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4
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Milicevic KD, Ivanova VO, Lovic DD, Platisa J, Andjus PR, Antic SD. Plateau depolarizations in spontaneously active neurons detected by calcium or voltage imaging. Sci Rep 2024; 14:22787. [PMID: 39367010 PMCID: PMC11452489 DOI: 10.1038/s41598-024-70319-4] [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: 10/30/2023] [Accepted: 08/14/2024] [Indexed: 10/06/2024] Open
Abstract
In calcium imaging studies, Ca2+ transients are commonly interpreted as neuronal action potentials (APs). However, our findings demonstrate that robust optical Ca2+ transients primarily stem from complex "AP-Plateaus", while simple APs lacking underlying depolarization envelopes produce much weaker photonic signatures. Under challenging in vivo conditions, these "AP-Plateaus" are likely to surpass noise levels, thus dominating the Ca2+ recordings. In spontaneously active neuronal culture, optical Ca2+ transients (OGB1-AM, GCaMP6f) exhibited approximately tenfold greater amplitude and twofold longer half-width compared to optical voltage transients (ArcLightD). The amplitude of the ArcLightD signal exhibited a strong correlation with the duration of the underlying membrane depolarization, and a weaker correlation with the presence of a fast sodium AP. Specifically, ArcLightD exhibited robust responsiveness to the slow "foot" but not the fast "trunk" of the neuronal AP. Particularly potent stimulators of optical signals in both Ca2+ and voltage imaging modalities were APs combined with plateau potentials (AP-Plateaus), resembling dendritic Ca2+ spikes or "UP states" in pyramidal neurons. Interestingly, even the spikeless plateaus (amplitude > 10 mV, duration > 200 ms) could generate conspicuous Ca2+ optical signals in neurons. Therefore, in certain circumstances, Ca2+ transients should not be interpreted solely as indicators of neuronal AP firing.
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Affiliation(s)
- Katarina D Milicevic
- School of Medicine, Institute for Systems Genomics, UConn Health, University of Connecticut Health, 263 Farmington Avenue, Farmington, CT, 06030, USA
- Institute of Physiology and Biochemistry 'Jean Giaja', Center for Laser Microscopy, University of Belgrade, Faculty of Biology, 11000, Belgrade, Serbia
| | - Violetta O Ivanova
- School of Medicine, Institute for Systems Genomics, UConn Health, University of Connecticut Health, 263 Farmington Avenue, Farmington, CT, 06030, USA
| | - Darko D Lovic
- School of Medicine, Institute for Systems Genomics, UConn Health, University of Connecticut Health, 263 Farmington Avenue, Farmington, CT, 06030, USA
- Institute of Physiology and Biochemistry 'Jean Giaja', Center for Laser Microscopy, University of Belgrade, Faculty of Biology, 11000, Belgrade, Serbia
| | - Jelena Platisa
- The John B. Pierce Laboratory, New Haven, CT, 06519, USA
- Department of Cellular and Molecular Physiology, School of Medicine, Yale University, New Haven, CT, 06519, USA
| | - Pavle R Andjus
- Institute of Physiology and Biochemistry 'Jean Giaja', Center for Laser Microscopy, University of Belgrade, Faculty of Biology, 11000, Belgrade, Serbia
| | - Srdjan D Antic
- School of Medicine, Institute for Systems Genomics, UConn Health, University of Connecticut Health, 263 Farmington Avenue, Farmington, CT, 06030, USA.
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5
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Lewis CM, Hoffmann A, Helmchen F. Linking brain activity across scales with simultaneous opto- and electrophysiology. NEUROPHOTONICS 2024; 11:033403. [PMID: 37662552 PMCID: PMC10472193 DOI: 10.1117/1.nph.11.3.033403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2023] [Revised: 07/19/2023] [Accepted: 07/24/2023] [Indexed: 09/05/2023]
Abstract
The brain enables adaptive behavior via the dynamic coordination of diverse neuronal signals across spatial and temporal scales: from fast action potential patterns in microcircuits to slower patterns of distributed activity in brain-wide networks. Understanding principles of multiscale dynamics requires simultaneous monitoring of signals in multiple, distributed network nodes. Combining optical and electrical recordings of brain activity is promising for collecting data across multiple scales and can reveal aspects of coordinated dynamics invisible to standard, single-modality approaches. We review recent progress in combining opto- and electrophysiology, focusing on mouse studies that shed new light on the function of single neurons by embedding their activity in the context of brain-wide activity patterns. Optical and electrical readouts can be tailored to desired scales to tackle specific questions. For example, fast dynamics in single cells or local populations recorded with multi-electrode arrays can be related to simultaneously acquired optical signals that report activity in specified subpopulations of neurons, in non-neuronal cells, or in neuromodulatory pathways. Conversely, two-photon imaging can be used to densely monitor activity in local circuits while sampling electrical activity in distant brain areas at the same time. The refinement of combined approaches will continue to reveal previously inaccessible and under-appreciated aspects of coordinated brain activity.
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Affiliation(s)
| | - Adrian Hoffmann
- University of Zurich, Brain Research Institute, Zurich, Switzerland
- University of Zurich, Neuroscience Center Zurich, Zurich, Switzerland
| | - Fritjof Helmchen
- University of Zurich, Brain Research Institute, Zurich, Switzerland
- University of Zurich, Neuroscience Center Zurich, Zurich, Switzerland
- University of Zurich, University Research Priority Program, Adaptive Brain Circuits in Development and Learning, Zurich, Switzerland
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6
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Chen HC, Ma Y, Cheng J, Chen YC. Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes. CANCER HETEROGENEITY AND PLASTICITY 2024; 1:0004. [PMID: 39156821 PMCID: PMC11328949 DOI: 10.47248/chp2401010004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/20/2024]
Abstract
Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.
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Affiliation(s)
- Hsiao-Chun Chen
- UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA
- Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA
| | - Yushu Ma
- UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA
- Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA
| | - Jinxiong Cheng
- UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 3700 O'Hara Street, Pittsburgh, PA 15260, USA
| | - Yu-Chih Chen
- UPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA
- Department of Computational and Systems Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA
- Department of Bioengineering, Swanson School of Engineering, University of Pittsburgh, 3700 O'Hara Street, Pittsburgh, PA 15260, USA
- CMU-Pitt Ph.D. Program in Computational Biology, University of Pittsburgh, 3420 Forbes Avenue, Pittsburgh, PA 15260, USA
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7
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Nikolaev D, Mironov VN, Metelkina EM, Shtyrov AA, Mereshchenko AS, Demidov NA, Vyazmin SY, Tennikova TB, Moskalenko SE, Bondarev SA, Zhouravleva GA, Vasin AV, Panov MS, Ryazantsev MN. Rational Design of Far-Red Archaerhodopsin-3-Based Fluorescent Genetically Encoded Voltage Indicators: from Elucidation of the Fluorescence Mechanism in Archers to Novel Red-Shifted Variants. ACS PHYSICAL CHEMISTRY AU 2024; 4:347-362. [PMID: 39069984 PMCID: PMC11274289 DOI: 10.1021/acsphyschemau.3c00073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 04/07/2024] [Accepted: 04/08/2024] [Indexed: 07/30/2024]
Abstract
Genetically encoded voltage indicators (GEVIs) have found wide applications as molecular tools for visualization of changes in cell membrane potential. Among others, several classes of archaerhodopsin-3-based GEVIs have been developed and have proved themselves promising in various molecular imaging studies. To expand the application range for this type of GEVIs, new variants with absorption band maxima shifted toward the first biological window and enhanced fluorescence signal are required. Here, we integrate computational and experimental strategies to reveal structural factors that distinguish far-red bright archaerhodopsin-3-based GEVIs, Archers, obtained by directed evolution in a previous study (McIsaac et al., PNAS, 2014) and the wild-type archaerhodopsin-3 with an extremely dim fluorescence signal, aiming to use the obtained information in subsequent rational design. We found that the fluorescence can be enhanced by stabilization of a certain conformation of the protein, which, in turn, can be achieved by tuning the pK a value of two titratable residues. These findings were supported further by introducing mutations into wild-type archeorhodopsin-3 and detecting the enhancement of the fluorescence signal. Finally, we came up with a rational design and proposed previously unknown Archers variants with red-shifted absorption bands (λmax up to 640 nm) and potential-dependent bright fluorescence (quantum yield up to 0.97%).
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Affiliation(s)
- Dmitrii
M. Nikolaev
- Institute
of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, St. Petersburg 198504, Russia
- Institute
of Biomedical Systems and Biotechnologies, Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Str., St. Petersburg 195251, Russia
| | - Vladimir N. Mironov
- Saint
Petersburg Academic University, 8/3 Khlopina Street, St.
Petersburg 194021, Russia
| | - Ekaterina M. Metelkina
- Institute
of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, St. Petersburg 198504, Russia
| | - Andrey A. Shtyrov
- Institute
of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, St. Petersburg 198504, Russia
| | - Andrey S. Mereshchenko
- Institute
of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, St. Petersburg 198504, Russia
| | - Nikita A. Demidov
- Saint
Petersburg Academic University, 8/3 Khlopina Street, St.
Petersburg 194021, Russia
| | - Sergey Yu. Vyazmin
- Saint
Petersburg Academic University, 8/3 Khlopina Street, St.
Petersburg 194021, Russia
| | - Tatiana B. Tennikova
- Institute
of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, St. Petersburg 198504, Russia
| | - Svetlana E. Moskalenko
- Department
of Genetics and Biotechnology, Saint Petersburg
State University, 7/9
Universitetskaya emb, St. Petersburg 199034, Russia
- Vavilov
Institute of General Genetics, St. Petersburg
Branch, Russian Academy of Sciences, St. Petersburg 199034, Russia
| | - Stanislav A. Bondarev
- Department
of Genetics and Biotechnology, Saint Petersburg
State University, 7/9
Universitetskaya emb, St. Petersburg 199034, Russia
- Laboratory
of Amyloid Biology, Saint Petersburg State
University, St. Petersburg 199034, Russia
| | - Galina A. Zhouravleva
- Department
of Genetics and Biotechnology, Saint Petersburg
State University, 7/9
Universitetskaya emb, St. Petersburg 199034, Russia
- Laboratory
of Amyloid Biology, Saint Petersburg State
University, St. Petersburg 199034, Russia
| | - Andrey V. Vasin
- Institute
of Biomedical Systems and Biotechnologies, Peter the Great St. Petersburg Polytechnic University, 29 Polytechnicheskaya Str., St. Petersburg 195251, Russia
| | - Maxim S. Panov
- Institute
of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, St. Petersburg 198504, Russia
- St.
Petersburg State Chemical Pharmaceutical University, Professor Popov str., 14, lit. A, St. Petersburg 197022, Russia
| | - Mikhail N. Ryazantsev
- Institute
of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, St. Petersburg 198504, Russia
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8
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Frei MS, Mehta S, Zhang J. Next-Generation Genetically Encoded Fluorescent Biosensors Illuminate Cell Signaling and Metabolism. Annu Rev Biophys 2024; 53:275-297. [PMID: 38346245 DOI: 10.1146/annurev-biophys-030722-021359] [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: 02/28/2024]
Abstract
Genetically encoded fluorescent biosensors have revolutionized the study of cell signaling and metabolism, as they allow for live-cell measurements with high spatiotemporal resolution. This success has spurred the development of tailor-made biosensors that enable the study of dynamic phenomena on different timescales and length scales. In this review, we discuss different approaches to enhancing and developing new biosensors. We summarize the technologies used to gain structural insights into biosensor design and comment on useful screening technologies. Furthermore, we give an overview of different applications where biosensors have led to key advances over recent years. Finally, we give our perspective on where future work is bound to make a large impact.
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Affiliation(s)
- Michelle S Frei
- Department of Pharmacology, University of California San Diego, La Jolla, California, USA; , ,
| | - Sohum Mehta
- Department of Pharmacology, University of California San Diego, La Jolla, California, USA; , ,
| | - Jin Zhang
- Department of Pharmacology, University of California San Diego, La Jolla, California, USA; , ,
- Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, California, USA
- Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, California, USA
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9
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Xiao S, Cunningham WJ, Kondabolu K, Lowet E, Moya MV, Mount RA, Ravasio C, Bortz E, Shaw D, Economo MN, Han X, Mertz J. Large-scale deep tissue voltage imaging with targeted-illumination confocal microscopy. Nat Methods 2024; 21:1094-1102. [PMID: 38840033 PMCID: PMC11500676 DOI: 10.1038/s41592-024-02275-w] [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: 07/04/2023] [Accepted: 04/09/2024] [Indexed: 06/07/2024]
Abstract
Voltage imaging with cellular specificity has been made possible by advances in genetically encoded voltage indicators. However, the kilohertz rates required for voltage imaging lead to weak signals. Moreover, out-of-focus fluorescence and tissue scattering produce background that both undermines the signal-to-noise ratio and induces crosstalk between cells, making reliable in vivo imaging in densely labeled tissue highly challenging. We describe a microscope that combines the distinct advantages of targeted illumination and confocal gating while also maximizing signal detection efficiency. The resulting benefits in signal-to-noise ratio and crosstalk reduction are quantified experimentally and theoretically. Our microscope provides a versatile solution for enabling high-fidelity in vivo voltage imaging at large scales and penetration depths, which we demonstrate across a wide range of imaging conditions and different genetically encoded voltage indicator classes.
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Affiliation(s)
- Sheng Xiao
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
| | | | | | - Eric Lowet
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Department of Neuroscience, Erasmus MC, Rotterdam, the Netherlands
| | - Maria V Moya
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Rebecca A Mount
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Cara Ravasio
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Emma Bortz
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Dana Shaw
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Michael N Economo
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
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10
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Cuhadar U, Calzado-Reyes L, Pascual-Caro C, Aberra AS, Ritzau-Jost A, Aggarwal A, Ibata K, Podgorski K, Yuzaki M, Geis C, Hallerman S, Hoppa MB, de Juan-Sanz J. Activity-driven synaptic translocation of LGI1 controls excitatory neurotransmission. Cell Rep 2024; 43:114186. [PMID: 38700985 PMCID: PMC11156761 DOI: 10.1016/j.celrep.2024.114186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 12/14/2023] [Accepted: 04/17/2024] [Indexed: 05/05/2024] Open
Abstract
The fine control of synaptic function requires robust trans-synaptic molecular interactions. However, it remains poorly understood how trans-synaptic bridges change to reflect the functional states of the synapse. Here, we develop optical tools to visualize in firing synapses the molecular behavior of two trans-synaptic proteins, LGI1 and ADAM23, and find that neuronal activity acutely rearranges their abundance at the synaptic cleft. Surprisingly, synaptic LGI1 is primarily not secreted, as described elsewhere, but exo- and endocytosed through its interaction with ADAM23. Activity-driven translocation of LGI1 facilitates the formation of trans-synaptic connections proportionally to the history of activity of the synapse, adjusting excitatory transmission to synaptic firing rates. Accordingly, we find that patient-derived autoantibodies against LGI1 reduce its surface fraction and cause increased glutamate release. Our findings suggest that LGI1 abundance at the synaptic cleft can be acutely remodeled and serves as a critical control point for synaptic function.
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Affiliation(s)
- Ulku Cuhadar
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, 75013 Paris, France
| | - Lorenzo Calzado-Reyes
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, 75013 Paris, France
| | - Carlos Pascual-Caro
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, 75013 Paris, France
| | - Aman S Aberra
- Department of Biology, Dartmouth College, Hanover, NH 03755, USA
| | - Andreas Ritzau-Jost
- Carl-Ludwig-Institute of Physiology, Faculty of Medicine, Leipzig University, 04317 Leipzig, Germany
| | - Abhi Aggarwal
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Keiji Ibata
- Department of Neurophysiology, Keio University, Tokyo 160-8582, Japan
| | | | - Michisuke Yuzaki
- Department of Neurophysiology, Keio University, Tokyo 160-8582, Japan
| | - Christian Geis
- Department of Neurology, Section Translational Neuroimmunology, Jena University Hospital, 07747 Jena, Germany
| | - Stefan Hallerman
- Carl-Ludwig-Institute of Physiology, Faculty of Medicine, Leipzig University, 04317 Leipzig, Germany
| | - Michael B Hoppa
- Department of Biology, Dartmouth College, Hanover, NH 03755, USA
| | - Jaime de Juan-Sanz
- Sorbonne Université, Institut du Cerveau - Paris Brain Institute - ICM, Inserm, CNRS, APHP, Hôpital de la Pitié Salpêtrière, 75013 Paris, France.
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11
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Zhang J, Newman J, Wang Z, Qian Y, Feliciano-Ramos P, Guo W, Honda T, Chen ZS, Linghu C, Etienne-Cummings R, Fossum E, Boyden E, Wilson M. Pixel-wise programmability enables dynamic high-SNR cameras for high-speed microscopy. Nat Commun 2024; 15:4480. [PMID: 38802338 PMCID: PMC11530699 DOI: 10.1038/s41467-024-48765-5] [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: 06/17/2023] [Accepted: 04/30/2024] [Indexed: 05/29/2024] Open
Abstract
High-speed wide-field fluorescence microscopy has the potential to capture biological processes with exceptional spatiotemporal resolution. However, conventional cameras suffer from low signal-to-noise ratio at high frame rates, limiting their ability to detect faint fluorescent events. Here, we introduce an image sensor where each pixel has individually programmable sampling speed and phase, so that pixels can be arranged to simultaneously sample at high speed with a high signal-to-noise ratio. In high-speed voltage imaging experiments, our image sensor significantly increases the output signal-to-noise ratio compared to a low-noise scientific CMOS camera (~2-3 folds). This signal-to-noise ratio gain enables the detection of weak neuronal action potentials and subthreshold activities missed by the standard scientific CMOS cameras. Our camera with flexible pixel exposure configurations offers versatile sampling strategies to improve signal quality in various experimental conditions.
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Affiliation(s)
- Jie Zhang
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA.
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
| | - Jonathan Newman
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Zeguan Wang
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Yong Qian
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Pedro Feliciano-Ramos
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Wei Guo
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Takato Honda
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Zhe Sage Chen
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Changyang Linghu
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | - Ralph Etienne-Cummings
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Eric Fossum
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
| | - Edward Boyden
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Matthew Wilson
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
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12
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Zhang J, Newman J, Wang Z, Qian Y, Feliciano-Ramos P, Guo W, Honda T, Chen ZS, Linghu C, Etienne-Cummings R, Fossum E, Boyden E, Wilson M. Pixel-wise programmability enables dynamic high-SNR cameras for high-speed microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.06.27.546748. [PMID: 37425952 PMCID: PMC10327006 DOI: 10.1101/2023.06.27.546748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
High-speed wide-field fluorescence microscopy has the potential to capture biological processes with exceptional spatiotemporal resolution. However, conventional cameras suffer from low signal-to-noise ratio at high frame rates, limiting their ability to detect faint fluorescent events. Here, we introduce an image sensor where each pixel has individually programmable sampling speed and phase, so that pixels can be arranged to simultaneously sample at high speed with a high signal-to-noise ratio. In high-speed voltage imaging experiments, our image sensor significantly increases the output signal-to-noise ratio compared to a low-noise scientific CMOS camera (~2-3 folds). This signal-to-noise ratio gain enables the detection of weak neuronal action potentials and subthreshold activities missed by the standard scientific CMOS cameras. Our camera with flexible pixel exposure configurations offers versatile sampling strategies to improve signal quality in various experimental conditions.
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Affiliation(s)
- Jie Zhang
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Jonathan Newman
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Zeguan Wang
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Yong Qian
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Pedro Feliciano-Ramos
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Wei Guo
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Takato Honda
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
| | - Zhe Sage Chen
- Department of Psychiatry, NYU Grossman School of Medicine, New York, NY, USA
| | - Changyang Linghu
- Department of Cell and Developmental Biology, University of Michigan, Ann Arbor, MI, USA
| | - Ralph Etienne-Cummings
- Department of Electrical and Computer Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Eric Fossum
- Thayer School of Engineering, Dartmouth College, Hanover, NH, USA
| | - Edward Boyden
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- McGovern Institute for Brain Research, MIT, Cambridge, MA, USA
| | - Matthew Wilson
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
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13
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Chen F, Liu K, Shang L, Wang Y, Tang X, Liang P, Li B. Precision isolation and cultivation of single cells by vortex and flat-top laser ejection. Front Microbiol 2024; 15:1369506. [PMID: 38659989 PMCID: PMC11039905 DOI: 10.3389/fmicb.2024.1369506] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 03/19/2024] [Indexed: 04/26/2024] Open
Abstract
Single-cell isolation stands as a critical step in single-cell studies, and single-cell ejection technology based on laser induced forward transfer technology (LIFT) is considered one of the most promising methods in this regard for its ability of visible isolating single cell from complex samples. In this study, we improve the LIFT technology and introduce optical vortex laser-induced forward transfer (OV-LIFT) and flat-top laser-induced forward transfer (FT-LIFT) by utilizing spatial light modulator (SLM), aiming to enhance the precision of single-cell sorting and the cell's viability after ejection. Experimental results demonstrate that applying vortex and flat-top beams during the sorting and collection process enables precise retrieval of single cells within diameter ranges of 50 μm and 100 μm, respectively. The recovery rates of Saccharomyces cerevisiae and Escherichia coli DH5α single cell ejected by vortex beam are 89 and 78%, by flat-top beam are 85 and 57%. When employing Gaussian beam sorting, the receiving range extends to 400 μm, with cultivation success rates of S. cerevisiae and E. coli DH5α single cell are 48 and 19%, respectively. This marks the first application of different mode beams in the ejection and cultivation of single cells, providing a novel and effective approach for the precise isolation and improving the viability of single cells.
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Affiliation(s)
- Fuyuan Chen
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Kunxiang Liu
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Lindong Shang
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yuntong Wang
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xusheng Tang
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Peng Liang
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Bei Li
- Key Laboratory of Optical System Advanced Manufacturing Technology, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
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14
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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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15
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Song C, Matlashov ME, Shcherbakova DM, Antic SD, Verkhusha VV, Knöpfel T. Characterization of two near-infrared genetically encoded voltage indicators. NEUROPHOTONICS 2024; 11:024201. [PMID: 38090225 PMCID: PMC10712888 DOI: 10.1117/1.nph.11.2.024201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 10/20/2023] [Accepted: 11/08/2023] [Indexed: 01/06/2024]
Abstract
Significance Efforts starting more than 20 years ago led to increasingly well performing genetically encoded voltage indicators (GEVIs) for optical imaging at wavelengths < 600 nm . Although optical imaging in the > 600 nm wavelength range has many advantages over shorter wavelength approaches for mesoscopic in vivo monitoring of neuronal activity in the mammalian brain, the availability and evaluation of well performing near-infrared GEVIs are still limited. Aim Here, we characterized two recent near-infrared GEVIs, Archon1 and nirButterfly, to support interested tool users in selecting a suitable near-infrared GEVI for their specific research question requirements. Approach We characterized side-by-side the brightness, sensitivity, and kinetics of both near-infrared GEVIs in a setting focused on population imaging. Results We found that nirButterfly shows seven-fold higher brightness than Archon1 under the same conditions and faster kinetics than Archon1 for population imaging without cellular resolution. But Archon1 showed larger signals than nirButterfly. Conclusions Neither GEVI characterized here surpasses in all three key parameters (brightness, kinetics, and sensitivity), so there is no unequivocal preference for one of the two. Our side-by-side characterization presented here provides new information for future in vitro and ex vivo experimental designs.
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Affiliation(s)
- Chenchen Song
- Imperial College, Laboratory for Neuronal Circuit Dynamics, London, United Kingdom
- Nanyang Technological University, Singapore
| | - Mikhail E. Matlashov
- Albert Einstein College of Medicine, Gruss-Lipper Biophotonics Center, Department of Genetics, Bronx, New York, United States
| | - Daria M. Shcherbakova
- Albert Einstein College of Medicine, Gruss-Lipper Biophotonics Center, Department of Genetics, Bronx, New York, United States
| | - Srdjan D. Antic
- Institute for Systems Genomics, UConn Health, Department of Neuroscience, Farmington, Connecticut, United States
| | - Vladislav V. Verkhusha
- Albert Einstein College of Medicine, Gruss-Lipper Biophotonics Center, Department of Genetics, Bronx, New York, United States
- University of Helsinki, Medicum, Faculty of Medicine, Helsinki, Finland
| | - Thomas Knöpfel
- Imperial College, Laboratory for Neuronal Circuit Dynamics, London, United Kingdom
- Hong Kong Baptist University, Laboratory for Neuronal Circuit Dynamics, Hong Kong, China
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16
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Nicoletti M, Chiodo L, Loppini A, Liu Q, Folli V, Ruocco G, Filippi S. Biophysical modeling of the whole-cell dynamics of C. elegans motor and interneurons families. PLoS One 2024; 19:e0298105. [PMID: 38551921 PMCID: PMC10980225 DOI: 10.1371/journal.pone.0298105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Accepted: 01/13/2024] [Indexed: 04/01/2024] Open
Abstract
The nematode Caenorhabditis elegans is a widely used model organism for neuroscience. Although its nervous system has been fully reconstructed, the physiological bases of single-neuron functioning are still poorly explored. Recently, many efforts have been dedicated to measuring signals from C. elegans neurons, revealing a rich repertoire of dynamics, including bistable responses, graded responses, and action potentials. Still, biophysical models able to reproduce such a broad range of electrical responses lack. Realistic electrophysiological descriptions started to be developed only recently, merging gene expression data with electrophysiological recordings, but with a large variety of cells yet to be modeled. In this work, we contribute to filling this gap by providing biophysically accurate models of six classes of C. elegans neurons, the AIY, RIM, and AVA interneurons, and the VA, VB, and VD motor neurons. We test our models by comparing computational and experimental time series and simulate knockout neurons, to identify the biophysical mechanisms at the basis of inter and motor neuron functioning. Our models represent a step forward toward the modeling of C. elegans neuronal networks and virtual experiments on the nematode nervous system.
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Affiliation(s)
- Martina Nicoletti
- Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
- Center for Life Nano- & Neuro-Science (CLN2S@Sapienza), Istituto Italiano di Tecnologia, Rome, Italy
| | - Letizia Chiodo
- Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Alessandro Loppini
- Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Rome, Italy
| | - Qiang Liu
- Department of Neuroscience, City University of Hong Kong, Hong Kong, China
| | - Viola Folli
- Center for Life Nano- & Neuro-Science (CLN2S@Sapienza), Istituto Italiano di Tecnologia, Rome, Italy
- D-tails s.r.l., Rome, Italy
| | - Giancarlo Ruocco
- Center for Life Nano- & Neuro-Science (CLN2S@Sapienza), Istituto Italiano di Tecnologia, Rome, Italy
| | - Simonetta Filippi
- Department of Engineering, Università Campus Bio-Medico di Roma, Rome, Italy
- Istituto Nazionale di Ottica del Consiglio Nazionale delle Ricerche (CNR-INO), Florence, Italy
- ICRANet—International Center for Relativistic Astrophysics Network, Pescara, Italy
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17
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Doszyn O, Dulski T, Zmorzynska J. Diving into the zebrafish brain: exploring neuroscience frontiers with genetic tools, imaging techniques, and behavioral insights. Front Mol Neurosci 2024; 17:1358844. [PMID: 38533456 PMCID: PMC10963419 DOI: 10.3389/fnmol.2024.1358844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 02/27/2024] [Indexed: 03/28/2024] Open
Abstract
The zebrafish (Danio rerio) is increasingly used in neuroscience research. Zebrafish are relatively easy to maintain, and their high fecundity makes them suitable for high-throughput experiments. Their small, transparent embryos and larvae allow for easy microscopic imaging of the developing brain. Zebrafish also share a high degree of genetic similarity with humans, and are amenable to genetic manipulation techniques, such as gene knockdown, knockout, or knock-in, which allows researchers to study the role of specific genes relevant to human brain development, function, and disease. Zebrafish can also serve as a model for behavioral studies, including locomotion, learning, and social interactions. In this review, we present state-of-the-art methods to study the brain function in zebrafish, including genetic tools for labeling single neurons and neuronal circuits, live imaging of neural activity, synaptic dynamics and protein interactions in the zebrafish brain, optogenetic manipulation, and the use of virtual reality technology for behavioral testing. We highlight the potential of zebrafish for neuroscience research, especially regarding brain development, neuronal circuits, and genetic-based disorders and discuss its certain limitations as a model.
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Affiliation(s)
| | | | - J. Zmorzynska
- Laboratory of Molecular and Cellular Neurobiology, International Institute of Molecular and Cell Biology in Warsaw (IIMCB), Warsaw, Poland
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18
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Wang Z, Zhang J, Symvoulidis P, Guo W, Zhang L, Wilson MA, Boyden ES. Imaging the voltage of neurons distributed across entire brains of larval zebrafish. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.15.571964. [PMID: 38168290 PMCID: PMC10760087 DOI: 10.1101/2023.12.15.571964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Neurons interact in networks distributed throughout the brain. Although much effort has focused on whole-brain calcium imaging, recent advances in genetically encoded voltage indicators (GEVIs) raise the possibility of imaging voltage of neurons distributed across brains. To achieve this, a microscope must image at high volumetric rate and signal-to-noise ratio. We present a remote scanning light-sheet microscope capable of imaging GEVI-expressing neurons distributed throughout entire brains of larval zebrafish at a volumetric rate of 200.8 Hz. We measured voltage of ∼1/3 of the neurons of the brain, distributed throughout. We observed that neurons firing at different times during a sequence were located at different brain locations, for sequences elicited by a visual stimulus, which mapped onto locations throughout the optic tectum, as well as during stimulus-independent bursts, which mapped onto locations in the cerebellum and medulla. Whole-brain voltage imaging may open up frontiers in the fundamental operation of neural systems.
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19
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Reumann D, Krauditsch C, Novatchkova M, Sozzi E, Wong SN, Zabolocki M, Priouret M, Doleschall B, Ritzau-Reid KI, Piber M, Morassut I, Fieseler C, Fiorenzano A, Stevens MM, Zimmer M, Bardy C, Parmar M, Knoblich JA. In vitro modeling of the human dopaminergic system using spatially arranged ventral midbrain-striatum-cortex assembloids. Nat Methods 2023; 20:2034-2047. [PMID: 38052989 PMCID: PMC10703680 DOI: 10.1038/s41592-023-02080-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2022] [Accepted: 10/10/2023] [Indexed: 12/07/2023]
Abstract
Ventral midbrain dopaminergic neurons project to the striatum as well as the cortex and are involved in movement control and reward-related cognition. In Parkinson's disease, nigrostriatal midbrain dopaminergic neurons degenerate and cause typical Parkinson's disease motor-related impairments, while the dysfunction of mesocorticolimbic midbrain dopaminergic neurons is implicated in addiction and neuropsychiatric disorders. Study of the development and selective neurodegeneration of the human dopaminergic system, however, has been limited due to the lack of an appropriate model and access to human material. Here, we have developed a human in vitro model that recapitulates key aspects of dopaminergic innervation of the striatum and cortex. These spatially arranged ventral midbrain-striatum-cortical organoids (MISCOs) can be used to study dopaminergic neuron maturation, innervation and function with implications for cell therapy and addiction research. We detail protocols for growing ventral midbrain, striatal and cortical organoids and describe how they fuse in a linear manner when placed in custom embedding molds. We report the formation of functional long-range dopaminergic connections to striatal and cortical tissues in MISCOs, and show that injected, ventral midbrain-patterned progenitors can mature and innervate the tissue. Using these assembloids, we examine dopaminergic circuit perturbations and show that chronic cocaine treatment causes long-lasting morphological, functional and transcriptional changes that persist upon drug withdrawal. Thus, our method opens new avenues to investigate human dopaminergic cell transplantation and circuitry reconstruction as well as the effect of drugs on the human dopaminergic system.
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Affiliation(s)
- Daniel Reumann
- Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria
- Vienna BioCenter, Doctoral School of the University of Vienna and Medical University of Vienna, Vienna, Austria
| | - Christian Krauditsch
- Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria
| | - Maria Novatchkova
- Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria
| | - Edoardo Sozzi
- Department of Experimental Medical Science, Developmental and Regenerative Neurobiology, Wallenberg Neuroscience Center, Lund Stem Cell Center, Lund University, Lund, Sweden
| | - Sakurako Nagumo Wong
- Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria
- Vienna BioCenter, Doctoral School of the University of Vienna and Medical University of Vienna, Vienna, Austria
| | - Michael Zabolocki
- Laboratory for Human Neurophysiology and Genetics, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia, Australia
- Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, Australia
| | - Marthe Priouret
- Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria
| | - Balint Doleschall
- Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria
- Vienna BioCenter, Doctoral School of the University of Vienna and Medical University of Vienna, Vienna, Austria
| | - Kaja I Ritzau-Reid
- Department of Materials, Department of Bioengineering, Institute of Biomedical Engineering, Imperial College London, London, UK
| | - Marielle Piber
- Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria
- Zebrafish Neurogenetics Unit, Institut Pasteur, Paris, France
| | - Ilaria Morassut
- Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria
- Department of Basic Neurosciences, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Charles Fieseler
- Department of Neuroscience and Developmental Biology, University of Vienna, Vienna, Austria
| | - Alessandro Fiorenzano
- Department of Experimental Medical Science, Developmental and Regenerative Neurobiology, Wallenberg Neuroscience Center, Lund Stem Cell Center, Lund University, Lund, Sweden
- Stem Cell Fate Laboratory, Institute of Genetics and Biophysics 'Adriano Buzzati Traverso' (IGB), CNR, Naples, Italy
| | - Molly M Stevens
- Department of Materials, Department of Bioengineering, Institute of Biomedical Engineering, Imperial College London, London, UK
| | - Manuel Zimmer
- Department of Neuroscience and Developmental Biology, University of Vienna, Vienna, Austria
| | - Cedric Bardy
- Laboratory for Human Neurophysiology and Genetics, South Australian Health and Medical Research Institute (SAHMRI), Adelaide, South Australia, Australia
- Flinders Health and Medical Research Institute, Flinders University, Adelaide, South Australia, Australia
| | - Malin Parmar
- Department of Experimental Medical Science, Developmental and Regenerative Neurobiology, Wallenberg Neuroscience Center, Lund Stem Cell Center, Lund University, Lund, Sweden
| | - Jürgen A Knoblich
- Institute of Molecular Biotechnology (IMBA) of the Austrian Academy of Sciences, Vienna BioCenter, Vienna, Austria.
- Department of Neurology, Medical University of Vienna, Vienna, Austria.
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20
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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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21
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Rappleye M, Wait SJ, Lee JD, Siebart JC, Torp L, Smith N, Muster J, Matreyek KA, Fowler DM, Berndt A. Optogenetic Microwell Array Screening System: A High-Throughput Engineering Platform for Genetically Encoded Fluorescent Indicators. ACS Sens 2023; 8:4233-4244. [PMID: 37956352 PMCID: PMC10683761 DOI: 10.1021/acssensors.3c01573] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Revised: 10/03/2023] [Accepted: 10/24/2023] [Indexed: 11/15/2023]
Abstract
Genetically encoded fluorescent indicators (GEFIs) are protein-based optogenetic tools that change their fluorescence intensity when binding specific ligands in cells and tissues. GEFI encoding DNA can be expressed in cell subtypes while monitoring cellular physiological responses. However, engineering GEFIs with physiological sensitivity and pharmacological specificity often requires iterative optimization through trial-and-error mutagenesis while assessing their biophysical function in vitro one by one. Here, the vast mutational landscape of proteins constitutes a significant obstacle that slows GEFI development, particularly for sensors that rely on mammalian host systems for testing. To overcome these obstacles, we developed a multiplexed high-throughput engineering platform called the optogenetic microwell array screening system (Opto-MASS) that functionally tests thousands of GEFI variants in parallel in mammalian cells. Opto-MASS represents the next step for engineering optogenetic tools as it can screen large variant libraries orders of magnitude faster than current methods. We showcase this system by testing over 13,000 dopamine and 21,000 opioid sensor variants. We generated a new dopamine sensor, dMASS1, with a >6-fold signal increase to 100 nM dopamine exposure compared to its parent construct. Our new opioid sensor, μMASS1, has a ∼4.6-fold signal increase over its parent scaffold's response to 500 nM DAMGO. Thus, Opto-MASS can rapidly engineer new sensors while significantly shortening the optimization time for new sensors with distinct biophysical properties.
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Affiliation(s)
- Michael Rappleye
- Department
of Bioengineering, University of Washington, 850 Republican Street, Seattle, Washington 98105, United States
- Institute
of Stem Cell and Regenerative Medicine, University of Washington, 850 Republican Street, Seattle, Washington 98109, United States
| | - Sarah J. Wait
- Institute
of Stem Cell and Regenerative Medicine, University of Washington, 850 Republican Street, Seattle, Washington 98109, United States
- Molecular
Engineering and Sciences Institute, University
of Washington, 3946 W Stevens Way NE, Seattle, Washington 98195, United States
| | - Justin Daho Lee
- Institute
of Stem Cell and Regenerative Medicine, University of Washington, 850 Republican Street, Seattle, Washington 98109, United States
- Molecular
Engineering and Sciences Institute, University
of Washington, 3946 W Stevens Way NE, Seattle, Washington 98195, United States
| | - Jamison C. Siebart
- The Wallace
H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Dr NW, Atlanta, Georgia 30332, United States
| | - Lily Torp
- Department
of Bioengineering, University of Washington, 850 Republican Street, Seattle, Washington 98105, United States
- Institute
of Stem Cell and Regenerative Medicine, University of Washington, 850 Republican Street, Seattle, Washington 98109, United States
| | - Netta Smith
- Department
of Bioengineering, University of Washington, 850 Republican Street, Seattle, Washington 98105, United States
- Institute
of Stem Cell and Regenerative Medicine, University of Washington, 850 Republican Street, Seattle, Washington 98109, United States
| | - Jeanot Muster
- Department
of Bioengineering, University of Washington, 850 Republican Street, Seattle, Washington 98105, United States
- Institute
of Stem Cell and Regenerative Medicine, University of Washington, 850 Republican Street, Seattle, Washington 98109, United States
| | - Kenneth A. Matreyek
- Department
of Pathology, Case Western Reserve University
School of Medicine, 2103 Cornell Road, Wolstein Research Building, Cleveland, Ohio 44106, United States
| | - Douglas M. Fowler
- Department
of Genome Sciences, Foege
Building S-250, 3720 15th Ave NE, Seattle, Washington 98195-5065, United States
| | - Andre Berndt
- Department
of Bioengineering, University of Washington, 850 Republican Street, Seattle, Washington 98105, United States
- Institute
of Stem Cell and Regenerative Medicine, University of Washington, 850 Republican Street, Seattle, Washington 98109, United States
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22
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Piatkevich KD, Boyden ES. Optogenetic control of neural activity: The biophysics of microbial rhodopsins in neuroscience. Q Rev Biophys 2023; 57:e1. [PMID: 37831008 DOI: 10.1017/s0033583523000033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2023]
Abstract
Optogenetics, the use of microbial rhodopsins to make the electrical activity of targeted neurons controllable by light, has swept through neuroscience, enabling thousands of scientists to study how specific neuron types contribute to behaviors and pathologies, and how they might serve as novel therapeutic targets. By activating a set of neurons, one can probe what functions they can initiate or sustain, and by silencing a set of neurons, one can probe the functions they are necessary for. We here review the biophysics of these molecules, asking why they became so useful in neuroscience for the study of brain circuitry. We review the history of the field, including early thinking, early experiments, applications of optogenetics, pre-optogenetics targeted neural control tools, and the history of discovering and characterizing microbial rhodopsins. We then review the biophysical attributes of rhodopsins that make them so useful to neuroscience - their classes and structure, their photocycles, their photocurrent magnitudes and kinetics, their action spectra, and their ion selectivity. Our hope is to convey to the reader how specific biophysical properties of these molecules made them especially useful to neuroscientists for a difficult problem - the control of high-speed electrical activity, with great precision and ease, in the brain.
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Affiliation(s)
- Kiryl D Piatkevich
- School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Edward S Boyden
- McGovern Institute and Koch Institute, Departments of Brain and Cognitive Sciences, Media Arts and Sciences, and Biological Engineering, K. Lisa Yang Center for Bionics and Center for Neurobiological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
- Howard Hughes Medical Institute, Cambridge, MA, USA
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23
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Lu X, Wang Y, Liu Z, Gou Y, Jaeger D, St-Pierre F. Widefield imaging of rapid pan-cortical voltage dynamics with an indicator evolved for one-photon microscopy. Nat Commun 2023; 14:6423. [PMID: 37828037 PMCID: PMC10570354 DOI: 10.1038/s41467-023-41975-3] [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: 08/23/2022] [Accepted: 09/20/2023] [Indexed: 10/14/2023] Open
Abstract
Widefield imaging with genetically encoded voltage indicators (GEVIs) is a promising approach for understanding the role of large cortical networks in the neural coding of behavior. However, the limited performance of current GEVIs restricts their deployment for single-trial imaging of rapid neuronal voltage dynamics. Here, we developed a high-throughput platform to screen for GEVIs that combine fast kinetics with high brightness, sensitivity, and photostability under widefield one-photon illumination. Rounds of directed evolution produced JEDI-1P, a green-emitting fluorescent indicator with enhanced performance across all metrics. Next, we optimized a neonatal intracerebroventricular delivery method to achieve cost-effective and wide-spread JEDI-1P expression in mice. We also developed an approach to correct optical measurements from hemodynamic and motion artifacts effectively. Finally, we achieved stable brain-wide voltage imaging and successfully tracked gamma-frequency whisker and visual stimulations in awake mice in single trials, opening the door to investigating the role of high-frequency signals in brain computations.
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Affiliation(s)
- Xiaoyu Lu
- Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX, 77005, USA
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Yunmiao Wang
- Neuroscience Graduate Program, Emory University, Atlanta, GA, 30322, USA
- Biology Department, Emory University, Atlanta, GA, 30322, USA
| | - Zhuohe Liu
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, USA
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA
| | - Yueyang Gou
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Dieter Jaeger
- Biology Department, Emory University, Atlanta, GA, 30322, USA.
| | - François St-Pierre
- Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX, 77005, USA.
- Department of Electrical and Computer Engineering, Rice University, Houston, TX, 77005, USA.
- Department of Neuroscience, Baylor College of Medicine, Houston, TX, 77030, USA.
- Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, 77030, USA.
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24
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Eom M, Han S, Park P, Kim G, Cho ES, Sim J, Lee KH, Kim S, Tian H, Böhm UL, Lowet E, Tseng HA, Choi J, Lucia SE, Ryu SH, Rózsa M, Chang S, Kim P, Han X, Piatkevich KD, Choi M, Kim CH, Cohen AE, Chang JB, Yoon YG. Statistically unbiased prediction enables accurate denoising of voltage imaging data. Nat Methods 2023; 20:1581-1592. [PMID: 37723246 PMCID: PMC10555843 DOI: 10.1038/s41592-023-02005-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Accepted: 08/10/2023] [Indexed: 09/20/2023]
Abstract
Here we report SUPPORT (statistically unbiased prediction utilizing spatiotemporal information in imaging data), a self-supervised learning method for removing Poisson-Gaussian noise in voltage imaging data. SUPPORT is based on the insight that a pixel value in voltage imaging data is highly dependent on its spatiotemporal neighboring pixels, even when its temporally adjacent frames alone do not provide useful information for statistical prediction. Such dependency is captured and used by a convolutional neural network with a spatiotemporal blind spot to accurately denoise voltage imaging data in which the existence of the action potential in a time frame cannot be inferred by the information in other frames. Through simulations and experiments, we show that SUPPORT enables precise denoising of voltage imaging data and other types of microscopy image while preserving the underlying dynamics within the scene.
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Affiliation(s)
- Minho Eom
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea
| | - Seungjae Han
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea
| | - Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Gyuri Kim
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea
| | - Eun-Seo Cho
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea
| | - Jueun Sim
- Department of Materials Science and Engineering, KAIST, Daejeon, Republic of Korea
| | - Kang-Han Lee
- Department of Biology, Chungnam National University, Daejeon, Republic of Korea
| | - Seonghoon Kim
- School of Biological Sciences, Seoul National University, Seoul, Republic of Korea
- Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Republic of Korea
| | - He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Urs L Böhm
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Einstein Center for Neurosciences, NeuroCure Cluster of Excellence, Charité University of Medicine Berlin, Berlin, Germany
| | - Eric Lowet
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Hua-An Tseng
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Jieun Choi
- Graduate School of Medical Science and Engineering, KAIST, Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, Daejeon, Republic of Korea
| | - Stephani Edwina Lucia
- Graduate School of Medical Science and Engineering, KAIST, Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, Daejeon, Republic of Korea
| | - Seung Hyun Ryu
- Interdisciplinary Program in Neuroscience, Seoul National University, Seoul, Republic of Korea
| | - Márton Rózsa
- Allen Institute for Neural Dynamics, Seattle, WA, USA
| | - Sunghoe Chang
- Department of Physiology and Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Pilhan Kim
- Graduate School of Medical Science and Engineering, KAIST, Daejeon, Republic of Korea
- KAIST Institute for Health Science and Technology, Daejeon, Republic of Korea
- Graduate School of Nanoscience and Technology, KAIST, Daejeon, Republic of Korea
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Kiryl D Piatkevich
- Research Center for Industries of the Future and School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China
| | - Myunghwan Choi
- School of Biological Sciences, Seoul National University, Seoul, Republic of Korea
- Institute of Molecular Biology and Genetics, Seoul National University, Seoul, Republic of Korea
| | - Cheol-Hee Kim
- Department of Biology, Chungnam National University, Daejeon, Republic of Korea
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Department of Physics, Harvard University, Cambridge, MA, USA
| | - Jae-Byum Chang
- Department of Materials Science and Engineering, KAIST, Daejeon, Republic of Korea
| | - Young-Gyu Yoon
- School of Electrical Engineering, KAIST, Daejeon, Republic of Korea.
- KAIST Institute for Health Science and Technology, Daejeon, Republic of Korea.
- Department of Semiconductor System Engineering, KAIST, Daejeon, Republic of Korea.
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25
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Zhang H, Papadaki S, Sun X, Wang X, Drobizhev M, Yao L, Rehbock M, Köster RW, Wu L, Namikawa K, Piatkevich KD. Quantitative assessment of near-infrared fluorescent proteins. Nat Methods 2023; 20:1605-1616. [PMID: 37666982 DOI: 10.1038/s41592-023-01975-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Accepted: 06/29/2023] [Indexed: 09/06/2023]
Abstract
Recent progress in fluorescent protein development has generated a large diversity of near-infrared fluorescent proteins (NIR FPs), which are rapidly becoming popular probes for a variety of imaging applications. However, the diversity of NIR FPs poses a challenge for end-users in choosing the optimal one for a given application. Here we conducted a systematic and quantitative assessment of intracellular brightness, photostability, oligomeric state, chemical stability and cytotoxicity of 22 NIR FPs in cultured mammalian cells and primary mouse neurons and identified a set of top-performing FPs including emiRFP670, miRFP680, miRFP713 and miRFP720, which can cover a majority of imaging applications. The top-performing proteins were further validated for in vivo imaging of neurons in Caenorhabditis elegans, zebrafish, and mice as well as in mice liver. We also assessed the applicability of the selected NIR FPs for multicolor imaging of fusions, expansion microscopy and two-photon imaging.
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Affiliation(s)
- Hanbin Zhang
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Stavrini Papadaki
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Xiaoting Sun
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Xinyue Wang
- Division of Cellular and Molecular Neurobiology, Zoological Institute, Technische Universität Braunschweig, Braunschweig, Germany
| | - Mikhail Drobizhev
- Department of Microbiology and Cell Biology, Montana State University, Bozeman, MT, USA
| | - Luxia Yao
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Michel Rehbock
- Division of Cellular and Molecular Neurobiology, Zoological Institute, Technische Universität Braunschweig, Braunschweig, Germany
| | - Reinhard W Köster
- Division of Cellular and Molecular Neurobiology, Zoological Institute, Technische Universität Braunschweig, Braunschweig, Germany
| | - Lianfeng Wu
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China
| | - Kazuhiko Namikawa
- Division of Cellular and Molecular Neurobiology, Zoological Institute, Technische Universität Braunschweig, Braunschweig, Germany
| | - Kiryl D Piatkevich
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China.
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China.
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, China.
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26
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Weber TD, Moya MV, Kılıç K, Mertz J, Economo MN. High-speed multiplane confocal microscopy for voltage imaging in densely labeled neuronal populations. Nat Neurosci 2023; 26:1642-1650. [PMID: 37604887 PMCID: PMC11209746 DOI: 10.1038/s41593-023-01408-2] [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: 02/09/2022] [Accepted: 07/17/2023] [Indexed: 08/23/2023]
Abstract
Genetically encoded voltage indicators (GEVIs) hold immense potential for monitoring neuronal population activity. To date, best-in-class GEVIs rely on one-photon excitation. However, GEVI imaging of dense neuronal populations remains difficult because out-of-focus background fluorescence produces low contrast and excess noise when paired with conventional one-photon widefield imaging methods. To address this challenge, we developed an imaging system capable of efficient, high-contrast GEVI imaging at near-kHz rates and demonstrate it for in vivo and ex vivo imaging applications in the mouse neocortex. Our approach uses simultaneous multiplane imaging to monitor activity within contiguous tissue volumes with no penalty in speed or requirement for high excitation power. This approach, multi-Z imaging with confocal detection (MuZIC), permits high signal-to-noise ratio voltage imaging in densely labeled neuronal populations and is compatible with imaging through micro-optics. Moreover, it minimizes artifacts associated with concurrent imaging and optogenetic photostimulation for all-optical electrophysiology.
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Affiliation(s)
- Timothy D Weber
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - Maria V Moya
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
| | - Kıvılcım Kılıç
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
- Center for Systems Neuroscience, Boston University, Boston, MA, USA
- Neurophotonics Center, Boston University, Boston, MA, USA
- Photonics Center, Boston University, Boston, MA, USA
| | - Michael N Economo
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.
- Center for Systems Neuroscience, Boston University, Boston, MA, USA.
- Neurophotonics Center, Boston University, Boston, MA, USA.
- Photonics Center, Boston University, Boston, MA, USA.
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27
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Chai F, Cheng D, Nasu Y, Terai T, Campbell RE. Maximizing the performance of protein-based fluorescent biosensors. Biochem Soc Trans 2023; 51:1585-1595. [PMID: 37431791 PMCID: PMC10586770 DOI: 10.1042/bst20221413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Revised: 06/22/2023] [Accepted: 06/26/2023] [Indexed: 07/12/2023]
Abstract
Fluorescent protein (FP)-based biosensors are genetically encoded tools that enable the imaging of biological processes in the context of cells, tissues, or live animals. Though widely used in biological research, practically all existing biosensors are far from ideal in terms of their performance, properties, and applicability for multiplexed imaging. These limitations have inspired researchers to explore an increasing number of innovative and creative ways to improve and maximize biosensor performance. Such strategies include new molecular biology methods to develop promising biosensor prototypes, high throughput microfluidics-based directed evolution screening strategies, and improved ways to perform multiplexed imaging. Yet another approach is to effectively replace components of biosensors with self-labeling proteins, such as HaloTag, that enable the biocompatible incorporation of synthetic fluorophores or other ligands in cells or tissues. This mini-review will summarize and highlight recent innovations and strategies for enhancing the performance of FP-based biosensors for multiplexed imaging to advance the frontiers of research.
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Affiliation(s)
- Fu Chai
- Department of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
| | - Dazhou Cheng
- Department of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
| | - Yusuke Nasu
- Department of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
- PRESTO, Japan Science and Technology Agency, Chiyoda-ku, Tokyo 102-0075, Japan
| | - Takuya Terai
- Department of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
| | - Robert E. Campbell
- Department of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan
- Department of Chemistry, University of Alberta, Edmonton, Alberta T6G 2G2, Canada
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28
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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: 0.5] [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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29
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Xiao S, Cunningham WJ, Kondabolu K, Lowet E, Moya MV, Mount R, Ravasio C, Economo MN, Han X, Mertz J. Large-scale deep tissue voltage imaging with targeted illumination confocal microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.21.548930. [PMID: 37502929 PMCID: PMC10370169 DOI: 10.1101/2023.07.21.548930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
Voltage imaging with cellular specificity has been made possible by the tremendous advances in genetically encoded voltage indicators (GEVIs). However, the kilohertz rates required for voltage imaging lead to weak signals. Moreover, out-of-focus fluorescence and tissue scattering produce background that both undermines signal-to-noise ratio (SNR) and induces crosstalk between cells, making reliable in vivo imaging in densely labeled tissue highly challenging. We describe a microscope that combines the distinct advantages of targeted illumination and confocal gating, while also maximizing signal detection efficiency. The resulting benefits in SNR and crosstalk reduction are quantified experimentally and theoretically. Our microscope provides a versatile solution for enabling high-fidelity in vivo voltage imaging at large scales and penetration depths, which we demonstrate across a wide range of imaging conditions and different GEVI classes.
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Affiliation(s)
- Sheng Xiao
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | | | | | - Eric Lowet
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Maria V. Moya
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Rebecca Mount
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Cara Ravasio
- Department of Biomedical Engineering, Boston University, Boston MA 02215
| | - Michael N. Economo
- Department of Biomedical Engineering, Boston University, Boston MA 02215
- Neurophotonics Center, Boston University, Boston MA, 02215
| | - Xue Han
- Department of Biomedical Engineering, Boston University, Boston MA 02215
- Neurophotonics Center, Boston University, Boston MA, 02215
| | - Jerome Mertz
- Department of Biomedical Engineering, Boston University, Boston MA 02215
- Neurophotonics Center, Boston University, Boston MA, 02215
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30
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Zheng Y, Li Y. Past, present, and future of tools for dopamine detection. Neuroscience 2023:S0306-4522(23)00295-6. [PMID: 37419404 DOI: 10.1016/j.neuroscience.2023.06.025] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 06/26/2023] [Accepted: 06/29/2023] [Indexed: 07/09/2023]
Abstract
Dopamine (DA) is a critical neuromodulator involved in various brain functions. To understand how DA regulates neural circuits and behaviors in the physiological and pathological conditions, it is essential to have tools that enable the direct detection of DA dynamics in vivo. Recently, genetically encoded DA sensors based on G protein-coupled receptors revolutionized this field, as it allows us to track in vivo DA dynamic with unprecedented spatial-temporal resolution, high molecular specificity, and sub-second kinetics. In this review, we first summarize traditional DA detection methods. Then we focus on the development of genetically encoded DA sensors and feature its significance to understanding dopaminergic neuromodulation across diverse behaviors and species. Finally, we present our perspectives about the future direction of the next-generation DA sensors and extend their potential applications. Overall, this review offers a comprehensive perspective on the past, present, and future of DA detection tools, with important implications for the study of DA functions in health and disease.
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Affiliation(s)
- Yu Zheng
- Peking-Tsinghua Center for Life Sciences, 100871 Beijing, China
| | - Yulong Li
- Peking-Tsinghua Center for Life Sciences, 100871 Beijing, China; State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, 100871 Beijing, China; PKU-IDG/McGovern Institute for Brain Research, 100871 Beijing, China; National Biomedical Imaging Center, Peking University, 100871 Beijing, China.
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31
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Affiliation(s)
- Alessio Andreoni
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, CA, USA
| | - Lin Tian
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, CA, USA.
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32
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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: 5.5] [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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33
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Tian H, Davis HC, Wong-Campos JD, Park P, Fan LZ, Gmeiner B, Begum S, Werley CA, Borja GB, Upadhyay H, Shah H, Jacques J, Qi Y, Parot V, Deisseroth K, Cohen AE. Video-based pooled screening yields improved far-red genetically encoded voltage indicators. Nat Methods 2023; 20:1082-1094. [PMID: 36624211 PMCID: PMC10329731 DOI: 10.1038/s41592-022-01743-5] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 11/28/2022] [Indexed: 01/11/2023]
Abstract
Video-based screening of pooled libraries is a powerful approach for directed evolution of biosensors because it enables selection along multiple dimensions simultaneously from large libraries. Here we develop a screening platform, Photopick, which achieves precise phenotype-activated photoselection over a large field of view (2.3 × 2.3 mm, containing >103 cells, per shot). We used the Photopick platform to evolve archaerhodopsin-derived genetically encoded voltage indicators (GEVIs) with improved signal-to-noise ratio (QuasAr6a) and kinetics (QuasAr6b). These GEVIs gave improved signals in cultured neurons and in live mouse brains. By combining targeted in vivo optogenetic stimulation with high-precision voltage imaging, we characterized inhibitory synaptic coupling between individual cortical NDNF (neuron-derived neurotrophic factor) interneurons, and excitatory electrical synapses between individual hippocampal parvalbumin neurons. The QuasAr6 GEVIs are powerful tools for all-optical electrophysiology and the Photopick approach could be adapted to evolve a broad range of biosensors.
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Affiliation(s)
- He Tian
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Hunter C Davis
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - J David Wong-Campos
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Pojeong Park
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Linlin Z Fan
- Department of Bioengineering, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | - Benjamin Gmeiner
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Shahinoor Begum
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | | | | | | | | | | | - Yitong Qi
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
| | - Vicente Parot
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
- Institute for Biological and Medical Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Karl Deisseroth
- Department of Bioengineering, Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Howard Hughes Medical Institute, Chevy Chase, MA, USA
| | - Adam E Cohen
- Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA.
- Department of Physics, Harvard University, Cambridge, MA, USA.
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34
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Aseyev N, Ivanova V, Balaban P, Nikitin E. Current Practice in Using Voltage Imaging to Record Fast Neuronal Activity: Successful Examples from Invertebrate to Mammalian Studies. BIOSENSORS 2023; 13:648. [PMID: 37367013 DOI: 10.3390/bios13060648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 06/09/2023] [Accepted: 06/12/2023] [Indexed: 06/28/2023]
Abstract
The optical imaging of neuronal activity with potentiometric probes has been credited with being able to address key questions in neuroscience via the simultaneous recording of many neurons. This technique, which was pioneered 50 years ago, has allowed researchers to study the dynamics of neural activity, from tiny subthreshold synaptic events in the axon and dendrites at the subcellular level to the fluctuation of field potentials and how they spread across large areas of the brain. Initially, synthetic voltage-sensitive dyes (VSDs) were applied directly to brain tissue via staining, but recent advances in transgenic methods now allow the expression of genetically encoded voltage indicators (GEVIs), specifically in selected neuron types. However, voltage imaging is technically difficult and limited by several methodological constraints that determine its applicability in a given type of experiment. The prevalence of this method is far from being comparable to patch clamp voltage recording or similar routine methods in neuroscience research. There are more than twice as many studies on VSDs as there are on GEVIs. As can be seen from the majority of the papers, most of them are either methodological ones or reviews. However, potentiometric imaging is able to address key questions in neuroscience by recording most or many neurons simultaneously, thus providing unique information that cannot be obtained via other methods. Different types of optical voltage indicators have their advantages and limitations, which we focus on in detail. Here, we summarize the experience of the scientific community in the application of voltage imaging and try to evaluate the contribution of this method to neuroscience research.
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Affiliation(s)
- Nikolay Aseyev
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Butlerova 5A, Moscow 117485, Russia
| | - Violetta Ivanova
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Butlerova 5A, Moscow 117485, Russia
| | - Pavel Balaban
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Butlerova 5A, Moscow 117485, Russia
| | - Evgeny Nikitin
- Institute of Higher Nervous Activity and Neurophysiology, Russian Academy of Sciences, Butlerova 5A, Moscow 117485, Russia
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35
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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: 34] [Impact Index Per Article: 17.0] [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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36
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Linghu C, An B, Shpokayte M, Celiker OT, Shmoel N, Zhang R, Zhang C, Park D, Park WM, Ramirez S, Boyden ES. Recording of cellular physiological histories along optically readable self-assembling protein chains. Nat Biotechnol 2023; 41:640-651. [PMID: 36593405 PMCID: PMC10188365 DOI: 10.1038/s41587-022-01586-7] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 10/21/2022] [Indexed: 01/03/2023]
Abstract
Observing cellular physiological histories is key to understanding normal and disease-related processes. Here we describe expression recording islands-a fully genetically encoded approach that enables both continual digital recording of biological information within cells and subsequent high-throughput readout in fixed cells. The information is stored in growing intracellular protein chains made of self-assembling subunits, human-designed filament-forming proteins bearing different epitope tags that each correspond to a different cellular state or function (for example, gene expression downstream of neural activity or pharmacological exposure), allowing the physiological history to be read out along the ordered subunits of protein chains with conventional optical microscopy. We use expression recording islands to record gene expression timecourse downstream of specific pharmacological and physiological stimuli in cultured neurons and in living mouse brain, with a time resolution of a fraction of a day, over periods of days to weeks.
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Affiliation(s)
- Changyang Linghu
- Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Biological Engineering, MIT, Cambridge, MA, USA
- Media Arts and Sciences, MIT, Cambridge, MA, USA
- McGovern Institute, MIT, Cambridge, MA, USA
- Department of Cell and Developmental Biology, Program in Single Cell Spatial Analysis, and Michigan Neuroscience Institute, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Bobae An
- Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Biological Engineering, MIT, Cambridge, MA, USA
- Media Arts and Sciences, MIT, Cambridge, MA, USA
- McGovern Institute, MIT, Cambridge, MA, USA
| | - Monika Shpokayte
- Graduate Program for Neuroscience, Boston University, Boston, MA, USA
- Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Orhan T Celiker
- Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Biological Engineering, MIT, Cambridge, MA, USA
- Media Arts and Sciences, MIT, Cambridge, MA, USA
- McGovern Institute, MIT, Cambridge, MA, USA
| | - Nava Shmoel
- Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Biological Engineering, MIT, Cambridge, MA, USA
- Media Arts and Sciences, MIT, Cambridge, MA, USA
- McGovern Institute, MIT, Cambridge, MA, USA
| | - Ruihan Zhang
- Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Biological Engineering, MIT, Cambridge, MA, USA
- Media Arts and Sciences, MIT, Cambridge, MA, USA
- McGovern Institute, MIT, Cambridge, MA, USA
| | - Chi Zhang
- Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Biological Engineering, MIT, Cambridge, MA, USA
- Media Arts and Sciences, MIT, Cambridge, MA, USA
- McGovern Institute, MIT, Cambridge, MA, USA
| | - Demian Park
- Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Biological Engineering, MIT, Cambridge, MA, USA
- Media Arts and Sciences, MIT, Cambridge, MA, USA
- McGovern Institute, MIT, Cambridge, MA, USA
| | - Won Min Park
- Chemical Engineering, Kansas State University, Manhattan, KS, USA
| | - Steve Ramirez
- Psychological and Brain Sciences, Boston University, Boston, MA, USA
| | - Edward S Boyden
- Brain and Cognitive Sciences, MIT, Cambridge, MA, USA.
- Biological Engineering, MIT, Cambridge, MA, USA.
- Media Arts and Sciences, MIT, Cambridge, MA, USA.
- McGovern Institute, MIT, Cambridge, MA, USA.
- Howard Hughes Medical Institute, MIT, Cambridge, MA, USA.
- K Lisa Yang Center for Bionics, MIT, Cambridge, MA, USA.
- Center for Neurobiological Engineering, MIT, Cambridge, MA, USA.
- Koch Institute, MIT, Cambridge, MA, USA.
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37
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Ganapathy S, Meng X, Mossel D, Jagt M, Brinks D. Expanding the family of genetically encoded voltage indicators with a candidate Heliorhodopsin exhibiting near-infrared fluorescence. J Biol Chem 2023; 299:104771. [PMID: 37127067 DOI: 10.1016/j.jbc.2023.104771] [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: 11/17/2022] [Revised: 04/22/2023] [Accepted: 04/23/2023] [Indexed: 05/03/2023] Open
Abstract
Genetically encoded voltage indicators (GEVIs), particularly those based on microbial rhodopsins, are gaining traction in neuroscience as fluorescent sensors for imaging voltage dynamics with high-spatiotemporal precision. Here we establish a novel GEVI candidate based on the recently discovered subfamily of the microbial rhodopsin clade, termed heliorhodopsins. We discovered that upon excitation at 530-560nm, wild type heliorhodopsin exhibits near infra-red fluorescence which is sensitive to membrane voltage. We characterized the fluorescence brightness, photostability, voltage sensitivity and kinetics of wild type heliorhodopsin in HEK293T cells and further examined the impact of mutating key residues near the retinal chromophore. The S237A mutation significantly improved the fluorescence response of heliorhodopsin by 76% providing a highly promising starting point for further protein evolution.
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Affiliation(s)
- Srividya Ganapathy
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands; Department of Pediatrics & Cellular and Molecular Medicine, UCSD School of Medicine, San Diego, USA
| | - Xin Meng
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Delizzia Mossel
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Mels Jagt
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands
| | - Daan Brinks
- Department of Imaging Physics, Delft University of Technology, Delft, The Netherlands; Department of Molecular Genetics, Erasmus University Medical Center, Rotterdam, The Netherlands.
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38
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Moore JJ, Rashid SK, Johnson CD, Codrington N, Chklovskii DB, Basu J. Sub-cellular population imaging tools reveal stable apical dendrites in hippocampal area CA3. RESEARCH SQUARE 2023:rs.3.rs-2733660. [PMID: 37131789 PMCID: PMC10153397 DOI: 10.21203/rs.3.rs-2733660/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Anatomically segregated apical and basal dendrites of pyramidal neurons receive functionally distinct inputs, but it is unknown if this results in compartment-level functional diversity during behavior. Here we imaged calcium signals from apical dendrites, soma, and basal dendrites of pyramidal neurons in area CA3 of mouse hippocampus during head-fixed navigation. To examine dendritic population activity, we developed computational tools to identify dendritic regions of interest and extract accurate fluorescence traces. We identified robust spatial tuning in apical and basal dendrites, similar to soma, though basal dendrites had reduced activity rates and place field widths. Across days, apical dendrites were more stable than soma or basal dendrites, resulting in better decoding of the animal's position. These population-level dendritic differences may reflect functionally distinct input streams leading to different dendritic computations in CA3. These tools will facilitate future studies of signal transformations between cellular compartments and their relation to behavior.
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Affiliation(s)
- Jason J Moore
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Center for Computational Neuroscience, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
| | - Shannon K Rashid
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Cara D. Johnson
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Naomi Codrington
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
| | - Dmitri B Chklovskii
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Center for Computational Neuroscience, Flatiron Institute, Simons Foundation, New York, NY 10010, USA
| | - Jayeeta Basu
- Neuroscience Institute, New York University Langone Health, New York, NY 10016, USA
- Department of Neuroscience and Physiology, New York University Grossman School of Medicine, New York, NY 10016, USA
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY 10016, USA
- Center for Neural Science, New York University, New York, NY 10003, USA
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39
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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: 2.0] [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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40
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Bergs ACF, Liewald JF, Rodriguez-Rozada S, Liu Q, Wirt C, Bessel A, Zeitzschel N, Durmaz H, Nozownik A, Dill H, Jospin M, Vierock J, Bargmann CI, Hegemann P, Wiegert JS, Gottschalk A. All-optical closed-loop voltage clamp for precise control of muscles and neurons in live animals. Nat Commun 2023; 14:1939. [PMID: 37024493 PMCID: PMC10079764 DOI: 10.1038/s41467-023-37622-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Accepted: 03/24/2023] [Indexed: 04/08/2023] Open
Abstract
Excitable cells can be stimulated or inhibited by optogenetics. Since optogenetic actuation regimes are often static, neurons and circuits can quickly adapt, allowing perturbation, but not true control. Hence, we established an optogenetic voltage-clamp (OVC). The voltage-indicator QuasAr2 provides information for fast, closed-loop optical feedback to the bidirectional optogenetic actuator BiPOLES. Voltage-dependent fluorescence is held within tight margins, thus clamping the cell to distinct potentials. We established the OVC in muscles and neurons of Caenorhabditis elegans, and transferred it to rat hippocampal neurons in slice culture. Fluorescence signals were calibrated to electrically measured potentials, and wavelengths to currents, enabling to determine optical I/V-relationships. The OVC reports on homeostatically altered cellular physiology in mutants and on Ca2+-channel properties, and can dynamically clamp spiking in C. elegans. Combining non-invasive imaging with control capabilities of electrophysiology, the OVC facilitates high-throughput, contact-less electrophysiology in individual cells and paves the way for true optogenetic control in behaving animals.
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Affiliation(s)
- Amelie C F Bergs
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Jana F Liewald
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Silvia Rodriguez-Rozada
- Research Group Synaptic Wiring and Information Processing, Center for Molecular Neurobiology Hamburg, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
| | - Qiang Liu
- Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior, The Rockefeller University, New York, NY, 10065, USA
- Department of Neuroscience, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong, Hong Kong, China
| | - Christin Wirt
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Artur Bessel
- Independent Researcher, Melatener Strasse 93, 52074, Aachen, Germany
| | - Nadja Zeitzschel
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Hilal Durmaz
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Adrianna Nozownik
- Research Group Synaptic Wiring and Information Processing, Center for Molecular Neurobiology Hamburg, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
| | - Holger Dill
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany
| | - Maëlle Jospin
- Université Claude Bernard Lyon 1, Institut NeuroMyoGène, 8 Avenue Rockefeller, 69008, Lyon, France
| | - Johannes Vierock
- Institute for Biology, Experimental Biophysics, Humboldt University, 10115, Berlin, Germany
| | - Cornelia I Bargmann
- Lulu and Anthony Wang Laboratory of Neural Circuits and Behavior, The Rockefeller University, New York, NY, 10065, USA
- Chan Zuckerberg Initiative, Palo Alto, CA, USA
| | - Peter Hegemann
- Institute for Biology, Experimental Biophysics, Humboldt University, 10115, Berlin, Germany
| | - J Simon Wiegert
- Research Group Synaptic Wiring and Information Processing, Center for Molecular Neurobiology Hamburg, University Medical Center Hamburg-Eppendorf, 20251, Hamburg, Germany
- Medical Faculty Mannheim, University of Heidelberg, Ludolf-Krehl-Strasse 13-17, 68167, Mannheim, Germany
| | - Alexander Gottschalk
- Buchmann Institute for Molecular Life Sciences, Goethe University, Max-von-Laue-Strasse 15, 60438, Frankfurt, Germany.
- Institute of Biophysical Chemistry, Goethe University, Max-von-Laue-Strasse 9, 60438, Frankfurt, Germany.
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41
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Won SM, Cai L, Gutruf P, Rogers JA. Wireless and battery-free technologies for neuroengineering. Nat Biomed Eng 2023; 7:405-423. [PMID: 33686282 PMCID: PMC8423863 DOI: 10.1038/s41551-021-00683-3] [Citation(s) in RCA: 117] [Impact Index Per Article: 58.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2020] [Accepted: 12/28/2020] [Indexed: 12/16/2022]
Abstract
Tethered and battery-powered devices that interface with neural tissues can restrict natural motions and prevent social interactions in animal models, thereby limiting the utility of these devices in behavioural neuroscience research. In this Review Article, we discuss recent progress in the development of miniaturized and ultralightweight devices as neuroengineering platforms that are wireless, battery-free and fully implantable, with capabilities that match or exceed those of wired or battery-powered alternatives. Such classes of advanced neural interfaces with optical, electrical or fluidic functionality can also combine recording and stimulation modalities for closed-loop applications in basic studies or in the practical treatment of abnormal physiological processes.
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Affiliation(s)
- Sang Min Won
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, South Korea
| | - Le Cai
- Biomedical Engineering, College of Engineering, The University of Arizona, Tucson, AZ, USA
| | - Philipp Gutruf
- Biomedical Engineering, College of Engineering, The University of Arizona, Tucson, AZ, USA.
- Bio5 Institute and Neuroscience GIDP, University of Arizona, Tucson, AZ, USA.
- Department of Electrical and Computer Engineering, University of Arizona, Tucson, AZ, USA.
| | - John A Rogers
- Department of Materials Science and Engineering, Northwestern University, Evanston, IL, USA.
- Center for Bio-Integrated Electronics, Northwestern University, Evanston, IL, USA.
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
- Center for Advanced Molecular Imaging, Northwestern University, Evanston, IL, USA.
- Department of Mechanical Engineering, Northwestern University, Evanston, IL, USA.
- Department of Chemistry, Northwestern University, Evanston, IL, USA.
- Department of Neurological Surgery, Northwestern University, Evanston, IL, USA.
- Department of Electrical and Computer Engineering, Northwestern University, Evanston, IL, USA.
- Simpson Querrey Institute for BioNanotechnology, Northwestern University, Evanston, IL, USA.
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42
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Kawanishi S, Kojima K, Shibukawa A, Sakamoto M, Sudo Y. Detection of Membrane Potential-Dependent Rhodopsin Fluorescence Using Low-Intensity Light Emitting Diode for Long-Term Imaging. ACS OMEGA 2023; 8:4826-4834. [PMID: 36777568 PMCID: PMC9910066 DOI: 10.1021/acsomega.2c06980] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Accepted: 01/13/2023] [Indexed: 06/18/2023]
Abstract
Microbial rhodopsin is a family of photoreceptive membrane proteins that commonly consist of a seven-transmembrane domain and a derivative of vitamin-A, retinal, as a chromophore. In 2011, archaeorhodopsin-3 (AR3) was shown to exhibit voltage-dependent fluorescence changes in mammalian cells. Since then, AR3 and its variants have been used as genetically encoded voltage indicators, in which mostly intense laser stimulation (1-1000 W/cm2) is used for the detection of dim fluorescence of rhodopsin, leading to high spatiotemporal resolution. However, intense laser stimulation potentially causes serious cell damage, particularly during long-term imaging over minutes. In this study, we present the successful detection of voltage-sensitive fluorescence of AR3 and its high fluorescence mutant Archon1 in a variety of mammalian cell lines using low-intensity light emitting diode stimulation (0.15 W/cm2) with long exposure time (500 ms). The detection system enables real-time imaging of drug-induced slow changes in voltage within the cells for minutes harmlessly and without fluorescence bleaching. Therefore, we demonstrate a method to quantitatively understand the dynamics of slow changes in membrane voltage on long time scales.
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Affiliation(s)
- Shiho Kawanishi
- Graduate
School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8530, Japan
| | - Keiichi Kojima
- Graduate
School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8530, Japan
- Faculty
of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8530, Japan
| | - Atsushi Shibukawa
- Graduate
School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8530, Japan
| | - Masayuki Sakamoto
- Department
of Optical Neural and Molecular Physiology, Graduate School of Biostudies, Kyoto University, Kyoto 606-8507, Japan
| | - Yuki Sudo
- Graduate
School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8530, Japan
- Faculty
of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama 700-8530, Japan
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43
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Nikolaev DM, Mironov VN, Shtyrov AA, Kvashnin ID, Mereshchenko AS, Vasin AV, Panov MS, Ryazantsev MN. Fluorescence Imaging of Cell Membrane Potential: From Relative Changes to Absolute Values. Int J Mol Sci 2023; 24:2435. [PMID: 36768759 PMCID: PMC9916766 DOI: 10.3390/ijms24032435] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 01/20/2023] [Accepted: 01/23/2023] [Indexed: 01/28/2023] Open
Abstract
Membrane potential is a fundamental property of biological cells. Changes in membrane potential characterize a vast number of vital biological processes, such as the activity of neurons and cardiomyocytes, tumorogenesis, cell-cycle progression, etc. A common strategy to record membrane potential changes that occur in the process of interest is to utilize organic dyes or genetically-encoded voltage indicators with voltage-dependent fluorescence. Sensors are introduced into target cells, and alterations of fluorescence intensity are recorded with optical methods. Techniques that allow recording relative changes of membrane potential and do not take into account fluorescence alterations due to factors other than membrane voltage are already widely used in modern biological and biomedical studies. Such techniques have been reviewed previously in many works. However, in order to investigate a number of processes, especially long-term processes, the measured signal must be corrected to exclude the contribution from voltage-independent factors or even absolute values of cell membrane potential have to be evaluated. Techniques that enable such measurements are the subject of this review.
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Affiliation(s)
- Dmitrii M. Nikolaev
- Institute of Biomedical Systems and Biotechnologies, Peter the Great Saint Petersburg Polytechnic University, 29 Polytechnicheskaya str., 195251 Saint Petersburg, Russia
- Nanotechnology Research and Education Centre RAS, Saint Petersburg Academic University, 8/3 Khlopina str., 194021 Saint Petersburg, Russia
| | - Vladimir N. Mironov
- Nanotechnology Research and Education Centre RAS, Saint Petersburg Academic University, 8/3 Khlopina str., 194021 Saint Petersburg, Russia
| | - Andrey A. Shtyrov
- Institute of Biomedical Systems and Biotechnologies, Peter the Great Saint Petersburg Polytechnic University, 29 Polytechnicheskaya str., 195251 Saint Petersburg, Russia
- Nanotechnology Research and Education Centre RAS, Saint Petersburg Academic University, 8/3 Khlopina str., 194021 Saint Petersburg, Russia
| | - Iaroslav D. Kvashnin
- Nanotechnology Research and Education Centre RAS, Saint Petersburg Academic University, 8/3 Khlopina str., 194021 Saint Petersburg, Russia
| | - Andrey S. Mereshchenko
- Institute of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, 198504 Saint Petersburg, Russia
| | - Andrey V. Vasin
- Institute of Biomedical Systems and Biotechnologies, Peter the Great Saint Petersburg Polytechnic University, 29 Polytechnicheskaya str., 195251 Saint Petersburg, Russia
| | - Maxim S. Panov
- Institute of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, 198504 Saint Petersburg, Russia
- Center for Biophysical Studies, Saint Petersburg State Chemical Pharmaceutical University, 14 Professor Popov str., lit. A, 197022 Saint Petersburg, Russia
| | - Mikhail N. Ryazantsev
- Nanotechnology Research and Education Centre RAS, Saint Petersburg Academic University, 8/3 Khlopina str., 194021 Saint Petersburg, Russia
- Institute of Chemistry, Saint Petersburg State University, 26 Universitetskii pr, 198504 Saint Petersburg, Russia
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44
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Lee J, Campillo B, Hamidian S, Liu Z, Shorey M, St-Pierre F. Automating the High-Throughput Screening of Protein-Based Optical Indicators and Actuators. Biochemistry 2023; 62:169-177. [PMID: 36315460 PMCID: PMC9852035 DOI: 10.1021/acs.biochem.2c00357] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
Over the last 25 years, protein engineers have developed an impressive collection of optical tools to interface with biological systems: indicators to eavesdrop on cellular activity and actuators to poke and prod native processes. To reach the performance level required for their downstream applications, protein-based tools are usually sculpted by iterative rounds of mutagenesis. In each round, libraries of variants are made and evaluated, and the most promising hits are then retrieved, sequenced, and further characterized. Early efforts to engineer protein-based optical tools were largely manual, suffering from low throughput, human error, and tedium. Here, we describe approaches to automating the screening of libraries generated as colonies on agar, multiwell plates, and pooled populations of single-cell variants. We also briefly discuss emerging approaches for screening, including cell-free systems and machine learning.
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Affiliation(s)
- Jihwan Lee
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Beatriz Campillo
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Shaminta Hamidian
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - Zhuohe Liu
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
| | - Matthew Shorey
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
| | - François St-Pierre
- Department of Neuroscience, Baylor College of Medicine, Houston, TX 77030, USA
- Systems, Synthetic, and Physical Biology Program, Rice University, Houston, TX 77005, USA
- Department of Electrical and Computer Engineering, Rice University, Houston, TX 77005, USA
- Department of Biochemistry and Molecular Biology, Baylor College of Medicine, Houston, TX, USA
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45
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Pedraza-González L, Barneschi L, Marszałek M, Padula D, De Vico L, Olivucci M. Automated QM/MM Screening of Rhodopsin Variants with Enhanced Fluorescence. J Chem Theory Comput 2023; 19:293-310. [PMID: 36516450 DOI: 10.1021/acs.jctc.2c00928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
We present a computational protocol for the fast and automated screening of excited-state hybrid quantum mechanics/molecular mechanics (QM/MM) models of rhodopsins to be used as fluorescent probes based on the automatic rhodopsin modeling protocol (a-ARM). Such "a-ARM fluorescence screening protocol" is implemented through a general Python-based driver, PyARM, that is also proposed here. The implementation and performance of the protocol are benchmarked using different sets of rhodopsin variants whose absorption and, more relevantly, emission spectra have been experimentally measured. We show that, despite important limitations that make unsafe to use it as a black-box tool, the protocol reproduces the observed trends in fluorescence and it is capable of selecting novel potentially fluorescent rhodopsins. We also show that the protocol can be used in mechanistic investigations to discern fluorescence enhancement effects associated with a near degeneracy of the S1/S2 states or, alternatively, with a barrier generated via coupling of the S0/S1 wave functions.
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Affiliation(s)
- Laura Pedraza-González
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy
| | - Leonardo Barneschi
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy
| | - Michał Marszałek
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy.,Faculty of Chemistry, Wrocław University of Science and Technology, Wybrzeże Wyspiaǹskiego 27, 50-370 Wrocław, Poland
| | - Daniele Padula
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy
| | - Luca De Vico
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy
| | - Massimo Olivucci
- Department of Biotechnology, Chemistry and Pharmacy, Università degli Studi di Siena, Via A. Moro 2, I-53100 Siena, Italy.,Department of Chemistry, Bowling Green State University, Bowling Green, Ohio 43403, United States
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46
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Harmon J, Findinier J, Ishii NT, Herbig M, Isozaki A, Grossman A, Goda K. Intelligent image-activated sorting of Chlamydomonas reinhardtii by mitochondrial localization. Cytometry A 2022; 101:1027-1034. [PMID: 35643943 DOI: 10.1002/cyto.a.24661] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 05/22/2022] [Accepted: 05/24/2022] [Indexed: 01/27/2023]
Abstract
Organelle positioning in cells is associated with various metabolic functions and signaling in unicellular organisms. Specifically, the microalga Chlamydomonas reinhardtii repositions its mitochondria, depending on the levels of inorganic carbon. Mitochondria are typically randomly distributed in the Chlamydomonas cytoplasm, but relocate toward the cell periphery at low inorganic carbon levels. This mitochondrial relocation is linked with the carbon-concentrating mechanism, but its significance is not yet thoroughly understood. A genotypic understanding of this relocation would require a high-throughput method to isolate rare mutant cells not exhibiting this relocation. However, this task is technically challenging due to the complex intracellular morphological difference between mutant and wild-type cells, rendering conventional non-image-based high-event-rate methods unsuitable. Here, we report our demonstration of intelligent image-activated cell sorting by mitochondrial localization. Specifically, we applied an intelligent image-activated cell sorting system to sort for C. reinhardtii cells displaying no mitochondrial relocation. We trained a convolutional neural network (CNN) to distinguish the cell types based on the complex morphology of their mitochondria. The CNN was employed to perform image-activated sorting for the mutant cell type at 180 events per second, which is 1-2 orders of magnitude faster than automated microscopy with robotic pipetting, resulting in an enhancement of the concentration from 5% to 56.5% corresponding to an enrichment factor of 11.3. These results show the potential of image-activated cell sorting for connecting genotype-phenotype relations for rare-cell populations, which require a high throughput and could lead to a better understanding of metabolic functions in cells.
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Affiliation(s)
- Jeffrey Harmon
- Department of Chemistry, The University of Tokyo, Tokyo, Japan
| | - Justin Findinier
- Department of Plant Biology, Carnegie Institution for Science, Stanford, California, USA
| | | | - Maik Herbig
- Department of Chemistry, The University of Tokyo, Tokyo, Japan
| | - Akihiro Isozaki
- Department of Chemistry, The University of Tokyo, Tokyo, Japan
| | - Arthur Grossman
- Department of Plant Biology, Carnegie Institution for Science, Stanford, California, USA.,Department of Biology, Stanford University, Stanford, California, USA
| | - Keisuke Goda
- Department of Chemistry, The University of Tokyo, Tokyo, Japan.,Department of Bioengineering, University of California, California, Los Angeles, USA.,Institute of Technological Sciences, Wuhan University, Hubei, China
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47
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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: 6.7] [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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48
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Retinal chromophore charge delocalization and confinement explain the extreme photophysics of Neorhodopsin. Nat Commun 2022; 13:6652. [PMID: 36333283 PMCID: PMC9636224 DOI: 10.1038/s41467-022-33953-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 10/07/2022] [Indexed: 11/06/2022] Open
Abstract
The understanding of how the rhodopsin sequence can be modified to exactly modulate the spectroscopic properties of its retinal chromophore, is a prerequisite for the rational design of more effective optogenetic tools. One key problem is that of establishing the rules to be satisfied for achieving highly fluorescent rhodopsins with a near infrared absorption. In the present paper we use multi-configurational quantum chemistry to construct a computer model of a recently discovered natural rhodopsin, Neorhodopsin, displaying exactly such properties. We show that the model, that successfully replicates the relevant experimental observables, unveils a geometrical and electronic structure of the chromophore featuring a highly diffuse charge distribution along its conjugated chain. The same model reveals that a charge confinement process occurring along the chromophore excited state isomerization coordinate, is the primary cause of the observed fluorescence enhancement.
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49
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Walton RT, Singh A, Blainey PC. Pooled genetic screens with image-based profiling. Mol Syst Biol 2022; 18:e10768. [PMID: 36366905 PMCID: PMC9650298 DOI: 10.15252/msb.202110768] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Revised: 09/12/2022] [Accepted: 09/16/2022] [Indexed: 11/13/2022] Open
Abstract
Spatial structure in biology, spanning molecular, organellular, cellular, tissue, and organismal scales, is encoded through a combination of genetic and epigenetic factors in individual cells. Microscopy remains the most direct approach to exploring the intricate spatial complexity defining biological systems and the structured dynamic responses of these systems to perturbations. Genetic screens with deep single-cell profiling via image features or gene expression programs have the capacity to show how biological systems work in detail by cataloging many cellular phenotypes with one experimental assay. Microscopy-based cellular profiling provides information complementary to next-generation sequencing (NGS) profiling and has only recently become compatible with large-scale genetic screens. Optical screening now offers the scale needed for systematic characterization and is poised for further scale-up. We discuss how these methodologies, together with emerging technologies for genetic perturbation and microscopy-based multiplexed molecular phenotyping, are powering new approaches to reveal genotype-phenotype relationships.
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Affiliation(s)
- Russell T Walton
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Department of Biological EngineeringMITCambridgeMAUSA
| | - Avtar Singh
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Present address:
Department of Cellular and Tissue GenomicsGenentechSouth San FranciscoCAUSA
| | - Paul C Blainey
- Broad Institute of MIT and HarvardCambridgeMAUSA
- Department of Biological EngineeringMITCambridgeMAUSA
- Koch Institute for Integrative Cancer ResearchMITCambridgeMAUSA
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Machado TA, Kauvar IV, Deisseroth K. Multiregion neuronal activity: the forest and the trees. Nat Rev Neurosci 2022; 23:683-704. [PMID: 36192596 PMCID: PMC10327445 DOI: 10.1038/s41583-022-00634-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/25/2022] [Indexed: 12/12/2022]
Abstract
The past decade has witnessed remarkable advances in the simultaneous measurement of neuronal activity across many brain regions, enabling fundamentally new explorations of the brain-spanning cellular dynamics that underlie sensation, cognition and action. These recently developed multiregion recording techniques have provided many experimental opportunities, but thoughtful consideration of methodological trade-offs is necessary, especially regarding field of view, temporal acquisition rate and ability to guarantee cellular resolution. When applied in concert with modern optogenetic and computational tools, multiregion recording has already made possible fundamental biological discoveries - in part via the unprecedented ability to perform unbiased neural activity screens for principles of brain function, spanning dozens of brain areas and from local to global scales.
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Affiliation(s)
- Timothy A Machado
- Department of Bioengineering, Stanford University, Stanford, CA, USA
| | - Isaac V Kauvar
- Department of Bioengineering, Stanford University, Stanford, CA, USA
- Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Karl Deisseroth
- Department of Bioengineering, Stanford University, Stanford, CA, USA.
- Howard Hughes Medical Institute, Stanford University, Stanford, CA, USA.
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA.
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