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Li Y, Fang Y, Li K, Yang H, Duan S, Sun L. Morphological Tracing and Functional Identification of Monosynaptic Connections in the Brain: A Comprehensive Guide. Neurosci Bull 2024; 40:1364-1378. [PMID: 38700806 PMCID: PMC11365912 DOI: 10.1007/s12264-024-01196-0] [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: 11/15/2023] [Accepted: 01/19/2024] [Indexed: 09/01/2024] Open
Abstract
Behavioral studies play a crucial role in unraveling the mechanisms underlying brain function. Recent advances in optogenetics, neuronal typing and labeling, and circuit tracing have facilitated the dissection of the neural circuitry involved in various important behaviors. The identification of monosynaptic connections, both upstream and downstream of specific neurons, serves as the foundation for understanding complex neural circuits and studying behavioral mechanisms. However, the practical implementation and mechanistic understanding of monosynaptic connection tracing techniques and functional identification remain challenging, particularly for inexperienced researchers. Improper application of these methods and misinterpretation of results can impede experimental progress and lead to erroneous conclusions. In this paper, we present a comprehensive description of the principles, specific operational details, and key steps involved in tracing anterograde and retrograde monosynaptic connections. We outline the process of functionally identifying monosynaptic connections through the integration of optogenetics and electrophysiological techniques, providing practical guidance for researchers.
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Affiliation(s)
- Yuanyuan Li
- Affiliated Mental Health Center and Hangzhou Seventh People's Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Yuanyuan Fang
- Affiliated Mental Health Center and Hangzhou Seventh People's Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100005, China
| | - Kaiyuan Li
- Affiliated Mental Health Center and Hangzhou Seventh People's Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Hongbin Yang
- Affiliated Mental Health Center and Hangzhou Seventh People's Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
| | - Shumin Duan
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China
- Department of Neurobiology and Department of Neurology of the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
| | - Li Sun
- Affiliated Mental Health Center and Hangzhou Seventh People's Hospital and School of Brain Science and Brain Medicine, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, 311121, China.
- NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou, 310058, China.
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Giachello CNG, Hunter I, Pettini T, Coulson B, Knüfer A, Cachero S, Winding M, Arzan Zarin A, Kohsaka H, Fan YN, Nose A, Landgraf M, Baines RA. Electrophysiological Validation of Monosynaptic Connectivity between Premotor Interneurons and the aCC Motoneuron in the Drosophila Larval CNS. J Neurosci 2022; 42:6724-6738. [PMID: 35868863 PMCID: PMC9435966 DOI: 10.1523/jneurosci.2463-21.2022] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 04/28/2022] [Accepted: 05/31/2022] [Indexed: 11/21/2022] Open
Abstract
The Drosophila connectome project aims to map the synaptic connectivity of entire larval and adult fly neural networks, which is essential for understanding nervous system development and function. So far, the project has produced an impressive amount of electron microscopy data that has facilitated reconstructions of specific synapses, including many in the larval locomotor circuit. While this breakthrough represents a technical tour de force, the data remain underutilized, partly because of a lack of functional validation of reconstructions. Attempts to validate connectivity posited by the connectome project, have mostly relied on behavioral assays and/or GFP reconstitution across synaptic partners (GRASP) or GCaMP imaging. While these techniques are useful, they have limited spatial or temporal resolution. Electrophysiological assays of synaptic connectivity overcome these limitations. Here, we combine patch-clamp recordings with optogenetic stimulation in male and female larvae, to test synaptic connectivity proposed by connectome reconstructions. Specifically, we use multiple driver lines to confirm that several connections between premotor interneurons and the anterior corner cell motoneuron are, as the connectome project suggests, monosynaptic. In contrast, our results also show that conclusions based on GRASP imaging may provide false-positive results regarding connectivity between cells. We also present a novel imaging tool, based on the same technology as our electrophysiology, as a favorable alternative to GRASP imaging. Finally, of eight Gal4 lines tested, five are reliably expressed in the premotor interneurons they are targeted to. Thus, our work highlights the need to confirm functional synaptic connectivity, driver line specificity, and use of appropriate genetic tools to support connectome projects.SIGNIFICANCE STATEMENT The Drosophila connectome project aims to provide a complete description of connectivity between neurons in an organism that presents experimental advantages over other models. It has reconstructed hundreds of thousands of synaptic connections of the fly larva by manual identification of anatomic landmarks present in serial section transmission electron microscopy (ssTEM) volumes of the larval CNS. We use a highly reliable electrophysiological approach to verify these connections, providing useful insight into the accuracy of work based on ssTEM. We also present a novel imaging tool for validating excitatory monosynaptic connections between cells and show that several genetic driver lines designed to target neurons of the larval connectome exhibit nonspecific and/or unreliable expression.
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Affiliation(s)
- Carlo N G Giachello
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
| | - Iain Hunter
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
| | - Tom Pettini
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
| | - Bramwell Coulson
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
| | - Athene Knüfer
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
| | - Sebastian Cachero
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, United Kingdom
| | - Michael Winding
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
| | - Aref Arzan Zarin
- Department of Biology, Texas A&M University, College Station, Texas 77843-3258
| | - Hiroshi Kohsaka
- Graduate School of Informatics and Engineering, The University of Electro-Communications, Tokyo 182-8585, Japan
| | - Yuen Ngan Fan
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
| | - Akinao Nose
- Department of Complexity Science and Engineering, Graduate School of Frontier Sciences, University of Tokyo, Chiba 277-8561, Japan
| | - Matthias Landgraf
- Department of Zoology, University of Cambridge, Cambridge CB2 3EJ, United Kingdom
| | - Richard A Baines
- Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PT, United Kingdom
- Manchester Academic Health Science Centre, Manchester M13 9NQ, United Kingdom
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Hunter I, Coulson B, Zarin AA, Baines RA. The Drosophila Larval Locomotor Circuit Provides a Model to Understand Neural Circuit Development and Function. Front Neural Circuits 2021; 15:684969. [PMID: 34276315 PMCID: PMC8282269 DOI: 10.3389/fncir.2021.684969] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 06/09/2021] [Indexed: 11/13/2022] Open
Abstract
It is difficult to answer important questions in neuroscience, such as: "how do neural circuits generate behaviour?," because research is limited by the complexity and inaccessibility of the mammalian nervous system. Invertebrate model organisms offer simpler networks that are easier to manipulate. As a result, much of what we know about the development of neural circuits is derived from work in crustaceans, nematode worms and arguably most of all, the fruit fly, Drosophila melanogaster. This review aims to demonstrate the utility of the Drosophila larval locomotor network as a model circuit, to those who do not usually use the fly in their work. This utility is explored first by discussion of the relatively complete connectome associated with one identified interneuron of the locomotor circuit, A27h, and relating it to similar circuits in mammals. Next, it is developed by examining its application to study two important areas of neuroscience research: critical periods of development and interindividual variability in neural circuits. In summary, this article highlights the potential to use the larval locomotor network as a "generic" model circuit, to provide insight into mammalian circuit development and function.
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Affiliation(s)
- Iain Hunter
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, School of Biological Sciences, University of Manchester, Manchester, United Kingdom
| | - Bramwell Coulson
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, School of Biological Sciences, University of Manchester, Manchester, United Kingdom
| | - Aref Arzan Zarin
- Department of Biology, The Texas A&M Institute for Neuroscience, Texas A&M University, College Station, TX, United States
| | - Richard A Baines
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, School of Biological Sciences, University of Manchester, Manchester, United Kingdom
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Leinwand SG, Scott K. Juvenile hormone drives the maturation of spontaneous mushroom body neural activity and learned behavior. Neuron 2021; 109:1836-1847.e5. [PMID: 33915110 DOI: 10.1016/j.neuron.2021.04.006] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 03/26/2021] [Accepted: 04/07/2021] [Indexed: 12/21/2022]
Abstract
Mature behaviors emerge from neural circuits sculpted by genetic programs and spontaneous and evoked neural activity. However, how neural activity is refined to drive maturation of learned behavior remains poorly understood. Here, we explore how transient hormonal signaling coordinates a neural activity state transition and maturation of associative learning. We identify spontaneous, asynchronous activity in a Drosophila learning and memory brain region, the mushroom body. This activity declines significantly over the first week of adulthood. Moreover, this activity is generated cell-autonomously via Cacophony voltage-gated calcium channels in a single cell type, α'/β' Kenyon cells. Juvenile hormone, a crucial developmental regulator, acts transiently in α'/β' Kenyon cells during a young adult sensitive period to downregulate spontaneous activity and enable subsequent enhanced learning. Hormone signaling in young animals therefore controls a neural activity state transition and is required for improved associative learning, providing insight into the maturation of circuits and behavior.
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Affiliation(s)
- Sarah G Leinwand
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA.
| | - Kristin Scott
- Department of Molecular and Cell Biology and Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA 94720, USA.
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Suzuki Y, Schenk JE, Tan H, Gaudry Q. A Population of Interneurons Signals Changes in the Basal Concentration of Serotonin and Mediates Gain Control in the Drosophila Antennal Lobe. Curr Biol 2020; 30:1110-1118.e4. [PMID: 32142699 DOI: 10.1016/j.cub.2020.01.018] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2019] [Revised: 09/02/2019] [Accepted: 01/07/2020] [Indexed: 12/15/2022]
Abstract
Serotonin (5-HT) represents a quintessential neuromodulator, having been identified in nearly all animal species [1] where it functions in cognition [2], motor control [3], and sensory processing [4]. In the olfactory circuits of flies and mice, serotonin indirectly inhibits odor responses in olfactory receptor neurons (ORNs) via GABAergic local interneurons (LNs) [5, 6]. However, the effects of 5-HT in olfaction are likely complicated, because multiple receptor subtypes are distributed throughout the olfactory bulb (OB) and antennal lobe (AL), the first layers of olfactory neuropil in mammals and insects, respectively [7]. For example, serotonin has a non-monotonic effect on odor responses in Drosophila projection neurons (PNs), where low concentrations suppress odor-evoked activity and higher concentrations boost PN responses [8]. Serotonin reaches the AL via the diffusion of paracrine 5-HT through the fly hemolymph [8] and by activation of the contralaterally projecting serotonin-immunoreactive deuterocerebral interneurons (CSDns): the only serotonergic cells that innervate the AL [9, 10]. Concentration-dependent effects could arise by either the expression of multiple 5-HT receptors (5-HTRs) on the same cells or by populations of neurons dedicated to detecting serotonin at different concentrations. Here, we identify a population of LNs that express 5-HT7Rs exclusively to detect basal concentrations of 5-HT. These LNs inhibit PNs via GABAB receptors and mediate subtractive gain control. LNs expressing 5-HT7Rs are broadly tuned to odors and target every glomerulus in the antennal lobe. Our results demonstrate that serotonergic modulation at low concentrations targets a specific population of LNs to globally downregulate PN odor responses in the AL.
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Affiliation(s)
- Yoshinori Suzuki
- Department of Biology, University of Maryland, College Park, MD 20742, USA
| | - Jonathan E Schenk
- Department of Biology, University of Maryland, College Park, MD 20742, USA
| | - Hua Tan
- Department of Biology, University of Maryland, College Park, MD 20742, USA
| | - Quentin Gaudry
- Department of Biology, University of Maryland, College Park, MD 20742, USA.
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