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Zhong X, Gu H, Lim J, Zhang P, Wang G, Zhang K, Li X. Genetically encoded sensors illuminate in vivo detection for neurotransmission: Development, application, and optimization strategies. IBRO Neurosci Rep 2025; 18:476-490. [PMID: 40177704 PMCID: PMC11964776 DOI: 10.1016/j.ibneur.2025.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2024] [Revised: 02/23/2025] [Accepted: 03/10/2025] [Indexed: 04/05/2025] Open
Abstract
Limitations in existing tools have hindered neuroscientists from achieving a deeper understanding of complex behaviors and diseases. The recent development and optimization of genetically encoded sensors offer a powerful solution for investigating intricate dynamics such as calcium influx, membrane potential, and the release of neurotransmitters and neuromodulators. In contrast, traditional methods are constrained by insufficient spatial and/or temporal resolution, low sensitivity, and stringent application conditions. Genetically encoded sensors have gained widespread popularity due to their advantageous features, which stem from their genetic encoding and optical imaging capabilities. These include broad applicability, tissue specificity, and non-invasive operation. When combined with advanced microscopic techniques, optogenetics, and machine learning approaches, these sensors have become versatile tools for studying neuronal circuits in intact living systems, providing millisecond-scale temporal resolution and spatial resolution ranging from nanometers to micrometers. In this review, we highlight the advantages of genetically encoded sensors over traditional methods in the study of neurotransmission. We also discuss their recent advancements, diverse applications, and optimization strategies.
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Affiliation(s)
- Xiaoyu Zhong
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hengyu Gu
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Juyao Lim
- Malaysian Medics International-Hospital Raja Permaisuri Bainun, Ipoh, Malaysia
| | - Peng Zhang
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Emotions and Affective Disorders (LEAD), Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Frontiers Science Center of Cellular Homeostasis and Human Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guangfu Wang
- HIT Center for Life Sciences, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
| | - Kun Zhang
- Department of Pharmacology and Chemical Biology, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Emotions and Affective Disorders (LEAD), Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Tumor Microenvironment and Inflammation, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Frontiers Science Center of Cellular Homeostasis and Human Diseases, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Key Laboratory of Cell Differentiation and Apoptosis of Chinese Ministry of Education, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaowan Li
- HIT Center for Life Sciences, School of Life Science and Technology, Harbin Institute of Technology, Harbin 150001, China
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2
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Luskin AT, Li L, Fu X, Martin MM, Barcomb K, Girven KS, Blackburn T, Wells BA, Thai ST, Li EM, Rana AN, Simon RC, Sun L, Gao L, Murry AD, Golden SA, Stuber GD, Ford CP, Gu L, Bruchas MR. Heterogeneous pericoerulear neurons tune arousal and exploratory behaviours. Nature 2025:10.1038/s41586-025-08952-w. [PMID: 40335695 DOI: 10.1038/s41586-025-08952-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2022] [Accepted: 03/27/2025] [Indexed: 05/09/2025]
Abstract
As the primary source of noradrenaline in the brain, the locus coeruleus (LC) regulates arousal, avoidance and stress responses1,2. However, how local neuromodulatory inputs control LC function remains unresolved. Here we identify a population of transcriptionally, spatially and functionally diverse GABAergic (γ-aminobutyric acid-producing) neurons in the LC dendritic field that receive distant inputs and modulate modes of LC firing to control global arousal levels and arousal-related processing and behaviours. We define peri-LC anatomy using viral tracing and combine single-cell RNA sequencing with spatial transcriptomics to molecularly define both LC noradrenaline-producing and peri-LC cell types. We identify several neuronal cell types that underlie peri-LC functional diversity using a series of complementary neural circuit approaches in behaving mice. Our findings indicate that LC and peri-LC neurons are transcriptionally, functionally and anatomically heterogenous neuronal populations that modulate arousal and avoidance states. Defining the molecular, cellular and functional diversity of the LC and peri-LC provides a roadmap for understanding the neurobiological basis of arousal, motivation and neuropsychiatric disorders.
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Affiliation(s)
- Andrew T Luskin
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, USA
- Laboratory of Neural Dynamics and Cognition, The Rockefeller University, New York, NY, USA
| | - Li Li
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Seattle Children's Research Institute, Seattle, WA, USA
| | - Xiaonan Fu
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Madison M Martin
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, USA
| | - Kelsey Barcomb
- Department of Pharmacology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, USA
| | - Kasey S Girven
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
| | - Taylor Blackburn
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
| | - Bailey A Wells
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
| | - Sarah T Thai
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
| | - Esther M Li
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Psychology, University of Washington, Seattle, WA, USA
| | - Akshay N Rana
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
| | - Rhiana C Simon
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Graduate Program in Neuroscience, University of Washington, Seattle, WA, USA
| | - Li Sun
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Biochemistry, University of Washington, Seattle, WA, USA
- TopoGene Inc., Seattle, WA, USA
| | - Lei Gao
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Alexandria D Murry
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Sam A Golden
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Biological Structure, University of Washington, Seattle, WA, USA
| | - Garret D Stuber
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Pharmacology, University of Washington, Seattle, WA, USA
| | - Christopher P Ford
- Department of Pharmacology, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, USA
| | - Liangcai Gu
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA
- Department of Biochemistry, University of Washington, Seattle, WA, USA
| | - Michael R Bruchas
- Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, WA, USA.
- Center for Neurobiology of Addiction, Pain, and Emotion, University of Washington, Seattle, WA, USA.
- Department of Pharmacology, University of Washington, Seattle, WA, USA.
- Department of Bioengineering, University of Washington, Seattle, WA, USA.
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3
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Wu CH, Camelot L, Lecca S, Mameli M. Neuromodulatory signaling contributing to the encoding of aversion. Trends Neurosci 2025:S0166-2236(25)00078-5. [PMID: 40318995 DOI: 10.1016/j.tins.2025.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2025] [Revised: 03/28/2025] [Accepted: 04/08/2025] [Indexed: 05/07/2025]
Abstract
The appropriate and rapid encoding of stimuli bearing a negative valence enables behaviors that are essential for survival. Recent advances in neuroscience using rodents as a model system highlight the relevance of cell type-specific neuronal activities in diverse brain networks for the encoding of aversion, as well as their importance for subsequent behavioral strategies. Within these networks, neuromodulators influence cell excitability, adjust fast synaptic neurotransmission, and affect plasticity, ultimately modulating behaviors. In this review we first discuss contemporary findings leveraging the use of cutting-edge neurotechnologies to define aversion-related neural circuits. The spatial and temporal dynamics of the release of neuromodulators and neuropeptides upon exposure to aversive stimuli are described within defined brain circuits. Together, these mechanistic insights update the present neural framework through which aversion drives motivated behaviors.
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Affiliation(s)
- Cheng-Hsi Wu
- Department of Fundamental Neuroscience, University of Lausanne, 1005 Lausanne, Switzerland
| | - Léa Camelot
- Department of Fundamental Neuroscience, University of Lausanne, 1005 Lausanne, Switzerland
| | - Salvatore Lecca
- Department of Fundamental Neuroscience, University of Lausanne, 1005 Lausanne, Switzerland
| | - Manuel Mameli
- Department of Fundamental Neuroscience, University of Lausanne, 1005 Lausanne, Switzerland; Institut National de la Santé et de la Recherche Médicale (INSERM), Unité Mixte de Recherche en Santé (UMRS) 839, 75005 Paris, France.
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4
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Inácio AR, Lam KC, Zhao Y, Pereira F, Gerfen CR, Lee S. Brain-wide presynaptic networks of functionally distinct cortical neurons. Nature 2025; 641:162-172. [PMID: 40011781 PMCID: PMC12043506 DOI: 10.1038/s41586-025-08631-w] [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: 05/02/2023] [Accepted: 01/10/2025] [Indexed: 02/28/2025]
Abstract
Revealing the connectivity of functionally identified individual neurons is necessary to understand how activity patterns emerge and support behaviour. Yet the brain-wide presynaptic wiring rules that lay the foundation for the functional selectivity of individual neurons remain largely unexplored. Cortical neurons, even in primary sensory cortex, are heterogeneous in their selectivity, not only to sensory stimuli but also to multiple aspects of behaviour. Here, to investigate presynaptic connectivity rules underlying the selectivity of pyramidal neurons to behavioural state1-10 in primary somatosensory cortex (S1), we used two-photon calcium imaging, neuropharmacology, single-cell-based monosynaptic input tracing and optogenetics. We show that behavioural state-dependent activity patterns are stable over time. These are minimally affected by direct neuromodulatory inputs and are driven primarily by glutamatergic inputs. Analysis of brain-wide presynaptic networks of individual neurons with distinct behavioural state-dependent activity profiles revealed that although behavioural state-related and behavioural state-unrelated neurons shared a similar pattern of local inputs within S1, their long-range glutamatergic inputs differed. Individual cortical neurons, irrespective of their functional properties, received converging inputs from the main S1-projecting areas. Yet neurons that tracked behavioural state received a smaller proportion of motor cortical inputs and a larger proportion of thalamic inputs. Optogenetic suppression of thalamic inputs reduced behavioural state-dependent activity in S1, but this activity was not externally driven. Our results reveal distinct long-range glutamatergic inputs as a substrate for preconfigured network dynamics associated with behavioural state.
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Affiliation(s)
- Ana R Inácio
- Unit on Functional Neural Circuits, Systems Neurodevelopment Laboratory, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
| | - Ka Chun Lam
- Machine Learning Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Yuan Zhao
- Machine Learning Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Francisco Pereira
- Machine Learning Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Charles R Gerfen
- Section on Neuroanatomy, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA
| | - Soohyun Lee
- Unit on Functional Neural Circuits, Systems Neurodevelopment Laboratory, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA.
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5
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Li Y, Li H, Wang H, Wang X. Utilizing Caenorhabditis Elegans as a Rapid and Precise Model for Assessing Amphetamine-Type Stimulants: A Novel Approach to Evaluating New Psychoactive Substances Activity and Mechanisms. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2025; 12:e2500808. [PMID: 40068108 PMCID: PMC12061310 DOI: 10.1002/advs.202500808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2025] [Revised: 02/27/2025] [Indexed: 05/10/2025]
Abstract
The surge of new psychoactive substances (NPS) poses significant public health challenges due to their unregulated status and diverse effects. However, existing in vivo models for evaluating their activities are limited. To address this gap, this study utilizes the model organism Caenorhabditis elegans (C. elegans) to evaluate the activity of amphetamine-type stimulants (ATS) and their analogs. The swimming-induced paralysis (SWIP) assay is employed to measure the acute responses of C. elegans to various ATS, including amphetamine (AMPH), methamphetamine (METH), 3,4-methylenedioxymethamphetamine (MDMA) and their enantiomers. The findings reveal distinct responses in wild-type and mutant C. elegans, highlighting the roles of dopaminergic and serotonergic pathways, particularly DOP-3 and SER-4 receptors. The assay also revealed that C. elegans can distinguish between the chiral forms of ATS. Additionally, structural activity relationships (SAR) are observed, with meta-R amphetamines showing more pronounced effects than ortho-R and para-R analogs. This study demonstrates the utility of C. elegans in rapidly assessing ATS activity and toxicity, providing a cost-effective and precise method for high-throughput testing of NPS. These results contribute to a better understanding of ATS pharmacology and offer a valuable framework for future research and potential regulatory applications.
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Affiliation(s)
- Yuanpeng Li
- Laboratory of Chemical BiologyChangchun Institute of Applied ChemistryChinese Academy of SciencesChangchunJilin130022China
- School of Applied Chemistry and EngineeringUniversity of Science and Technology of ChinaHefeiAnhui230026China
| | - Hongyuan Li
- Laboratory of Chemical BiologyChangchun Institute of Applied ChemistryChinese Academy of SciencesChangchunJilin130022China
| | - Hongshuang Wang
- Laboratory of Chemical BiologyChangchun Institute of Applied ChemistryChinese Academy of SciencesChangchunJilin130022China
| | - Xiaohui Wang
- Laboratory of Chemical BiologyChangchun Institute of Applied ChemistryChinese Academy of SciencesChangchunJilin130022China
- School of Applied Chemistry and EngineeringUniversity of Science and Technology of ChinaHefeiAnhui230026China
- State Key Laboratory of Brain Machine IntelligenceZhejiang UniversityHangzhou310027China
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6
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Xin Q, Wang J, Zheng J, Tan Y, Jia X, Ni Z, Xu Z, Feng J, Wu Z, Li Y, Li XM, Ma H, Hu H. Neuron-astrocyte coupling in lateral habenula mediates depressive-like behaviors. Cell 2025:S0092-8674(25)00411-8. [PMID: 40280131 DOI: 10.1016/j.cell.2025.04.010] [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: 09/08/2024] [Revised: 01/08/2025] [Accepted: 04/03/2025] [Indexed: 04/29/2025]
Abstract
The lateral habenula (LHb) neurons and astrocytes have been strongly implicated in depression etiology, but it was not clear how the two dynamically interact during depression onset. Here, using multi-brain-region calcium photometry recording in freely moving mice, we discover that stress induces a most rapid astrocytic calcium rise and a bimodal neuronal response in the LHb. LHb astrocytic calcium requires the α1A-adrenergic receptor and depends on a recurrent neural network between the LHb and locus coeruleus (LC). Through the gliotransmitter glutamate and ATP/adenosine, LHb astrocytes mediate the second-wave LHb neuronal activation and norepinephrine (NE) release. Activation or inhibition of LHb astrocytic calcium signaling facilitates or prevents stress-induced depressive-like behaviors, respectively. These results identify a stress-induced positive feedback loop in the LHb-LC axis, with astrocytes being a critical signaling relay. The identification of this prominent neuron-glia interaction may shed light on stress management and depression prevention.
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Affiliation(s)
- Qianqian Xin
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China; Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China
| | - Junying Wang
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China; Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China
| | - Jinkun Zheng
- Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China
| | - Yi Tan
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China; Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China; Department of Psychiatry and International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu 322000, China
| | - Xiaoning Jia
- Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China
| | - Zheyi Ni
- Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China
| | - Zijie Xu
- Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China
| | - Jiesi Feng
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Zhaofa Wu
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Xiao-Ming Li
- Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China
| | - Huan Ma
- Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China
| | - Hailan Hu
- Department of Neurobiology, Affiliated Mental Health Center & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, Hangzhou 310058, China; Nanhu Brain-Computer Interface Institute, Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-Machine Intelligence, New Cornerstone Science Laboratory, Zhejiang University, Hangzhou 311121, China; Department of Psychiatry and International Institutes of Medicine, The Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu 322000, China.
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7
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Brink AK, Lui SKC, Corbit LH. Alpha-2 agonism in the locus coeruleus impairs learning driven by negative prediction error. Neuropsychopharmacology 2025:10.1038/s41386-025-02092-5. [PMID: 40223132 DOI: 10.1038/s41386-025-02092-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2024] [Revised: 03/11/2025] [Accepted: 03/14/2025] [Indexed: 04/15/2025]
Abstract
Refining previous learning when environmental contingencies change is a critical adaptive function. Studies have shown that systemic noradrenaline (NA) manipulations, as well as optogenetic manipulations of the locus coeruleus (LC), the primary source of forebrain NA, can improve long-term retention of appetitive extinction. To determine whether the contribution of NA is specific to extinction or extends to other forms of learning where reward is less than expected, we suppressed LC activity with clonidine, an α2A-adrenergic receptor agonist, in two tasks: compound extinction, where two previously rewarded cues are presented together and no longer rewarded, and overexpectation, where animals are presented with two previously rewarded cues but receive a single reward rather than the expected two. In compound extinction, we found no differences between groups in training, extinction, or a spontaneous recovery test. However, animals that received clonidine reacquired responding to the previously extinguished cue significantly faster than saline-treated animals, suggesting weakened extinction learning. In overexpectation testing, the saline group responded significantly less to a stimulus that had undergone overexpectation relative to a control stimulus, indicating that they had recalibrated their estimation of reward magnitude following training where reward was less than expected. In contrast, clonidine-treated animals did not differ in responding to the overexpectation versus control stimuli, suggesting that clonidine impaired learning resulting from overexpectation. These results demonstrate that activity of the LC is important for learning to reduce responding in both extinction and overexpectation paradigms.
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Affiliation(s)
- Ashleigh K Brink
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada
| | - Simon K C Lui
- Department of Psychology, University of Toronto, Toronto, ON, Canada
| | - Laura H Corbit
- Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada.
- Department of Psychology, University of Toronto, Toronto, ON, Canada.
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8
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Wang H, Ortega HK, Kelly EB, Indajang J, Savalia NK, Glaeser-Khan S, Feng J, Li Y, Kaye AP, Kwan AC. Frontal noradrenergic and cholinergic transients exhibit distinct spatiotemporal dynamics during competitive decision-making. SCIENCE ADVANCES 2025; 11:eadr9916. [PMID: 40138407 PMCID: PMC11939063 DOI: 10.1126/sciadv.adr9916] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2024] [Accepted: 02/20/2025] [Indexed: 03/29/2025]
Abstract
Norepinephrine (NE) and acetylcholine (ACh) are crucial for learning and decision-making. In the cortex, NE and ACh are released transiently at specific sites along neuromodulatory axons, but how the spatiotemporal patterns of NE and ACh signaling link to behavioral events is unknown. Here, we use two-photon microscopy to visualize neuromodulatory signals in the premotor cortex (medial M2) as mice engage in a competitive matching pennies game. Spatially, NE signals are more segregated with choice and outcome encoded at distinct locations, whereas ACh signals can multiplex and reflect different behavioral correlates at the same site. Temporally, task-driven NE transients were more synchronized and peaked earlier than ACh transients. To test functional relevance, we stimulated neuromodulatory signals using optogenetics to find that NE, but not ACh, increases the animals' propensity to explore alternate options. Together, the results reveal distinct subcellular spatiotemporal patterns of ACh and NE transients during decision-making in mice.
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Affiliation(s)
- Hongli Wang
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Heather K. Ortega
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Emma B. Kelly
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Jonathan Indajang
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14853, USA
| | - Neil K. Savalia
- Interdepartmental Neuroscience Program, Yale University School of Medicine, New Haven, CT 06511, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14853, USA
- Medical Scientist Training Program, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Samira Glaeser-Khan
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
| | - Jiesi Feng
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
- Chinese Institute for Brain Research, Beijing, China
| | - Alfred P. Kaye
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- VA National Center for PTSD Clinical Neuroscience Division, West Haven, CT 06477, USA
- Wu Tsai Institute, New Haven, CT 06511, USA
| | - Alex C. Kwan
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT 06511, USA
- Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY 14853, USA
- Department of Psychiatry, Weill Cornell Medicine, New York, NY 10065, USA
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9
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Kalugin PN, Soden PA, Massengill CI, Amsalem O, Porniece M, Guarino DC, Tingley D, Zhang SX, Benson JC, Hammell MF, Tong DM, Ausfahl CD, Lacey TE, Courtney Y, Hochstetler A, Lutas A, Wang H, Geng L, Li G, Li B, Li Y, Lehtinen MK, Andermann ML. Simultaneous, real-time tracking of many neuromodulatory signals with Multiplexed Optical Recording of Sensors on a micro-Endoscope. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.01.26.634931. [PMID: 39896634 PMCID: PMC11785251 DOI: 10.1101/2025.01.26.634931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2025]
Abstract
Dozens of extracellular molecules jointly impact a given neuron, yet we lack methods to simultaneously record many such signals in real time. We developed a probe to track ten or more neuropeptides and neuromodulators using spatial multiplexing of genetically encoded fluorescent sensors. Cultured cells expressing one sensor at a time are immobilized at the front of a gradient refractive index (GRIN) lens for 3D two-photon imaging in vitro and in vivo . The sensor identity and detection sensitivity of each cell are determined via robotic dipping of the probe into wells containing various ligands and concentrations. Using this probe, we detected stimulation-evoked release of multiple neuromodulators in acute brain slices. We also tracked endogenous and drug-evoked changes in cerebrospinal fluid composition in the awake mouse lateral ventricle, which triggered downstream activation of the choroid plexus epithelium. Our approach offers a first step towards quantitative, real-time, high-dimensional tracking of brain fluid composition.
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10
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Zheng Y, Cai R, Wang K, Zhang J, Zhuo Y, Dong H, Zhang Y, Wang Y, Deng F, Ji E, Cui Y, Fang S, Zhang X, Zhang K, Wang J, Li G, Miao X, Wang Z, Yang Y, Li S, Grimm J, Johnsson K, Schreiter E, Lavis L, Chen Z, Mu Y, Li Y. In vivo multiplex imaging of dynamic neurochemical networks with designed far-red dopamine sensors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.12.22.629999. [PMID: 39763912 PMCID: PMC11703222 DOI: 10.1101/2024.12.22.629999] [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] [Indexed: 01/15/2025]
Abstract
Neurochemical signals like dopamine (DA) play a crucial role in a variety of brain functions through intricate interactions with other neuromodulators and intracellular signaling pathways. However, studying these complex networks has been hindered by the challenge of detecting multiple neurochemicals in vivo simultaneously. To overcome this limitation, we developed a single-protein chemigenetic DA sensor, HaloDA1.0, which combines a cpHaloTag-chemical dye approach with the G protein-coupled receptor activation-based (GRAB) strategy, providing high sensitivity for DA, sub-second response kinetics, and an extensive spectral range from far-red to near-infrared. When used together with existing green and red fluorescent neuromodulator sensors, Ca2+ indicators, cAMP sensors, and optogenetic tools, HaloDA1.0 provides high versatility for multiplex imaging in cultured neurons, brain slices, and behaving animals, facilitating in-depth studies of dynamic neurochemical networks.
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Affiliation(s)
- Yu Zheng
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Beijing 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
| | - Ruyi Cai
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Kui Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Junwei Zhang
- Institute of Molecular Medicine, Peking University College of Future Technology, Beijing 100871, China
| | - Yizhou Zhuo
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Hui Dong
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Yuqi Zhang
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
- Department of Chemical Biology, Max Planck Institute for Medical Research, Heidelberg 69120, Germany
| | - Yifan Wang
- Neuroscience Institute, New York University Langone Medical Center, New York 10016, USA
| | - Fei Deng
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - En Ji
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Yiwen Cui
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Beijing 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
| | - Shilin Fang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xinxin Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Kecheng Zhang
- Institute of Molecular Medicine, Peking University College of Future Technology, Beijing 100871, China
| | - Jinxu Wang
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
- Department of Anesthesiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Guochuan Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Xiaolei Miao
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
- Department of Anesthesiology, Beijing Chaoyang Hospital, Capital Medical University, Beijing 100020, China
| | - Zhenghua Wang
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Beijing 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
| | - Yuqing Yang
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Shaochuang Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
| | - Jonathan Grimm
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia 20147, USA
| | - Kai Johnsson
- Department of Chemical Biology, Max Planck Institute for Medical Research, Heidelberg 69120, Germany
| | - Eric Schreiter
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia 20147, USA
| | - Luke Lavis
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, Virginia 20147, USA
| | - Zhixing Chen
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Beijing 100871, China
- Institute of Molecular Medicine, Peking University College of Future Technology, Beijing 100871, China
- National Biomedical Imaging Center, Peking University, Beijing 100871, China
| | - Yu Mu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yulong Li
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Beijing 100871, China
- PKU-IDG/McGovern Institute for Brain Research, Beijing 100871, China
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing 100871, China
- Institute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen, Guangdong 518055, China
- National Biomedical Imaging Center, Peking University, Beijing 100871, China
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11
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López RC, Noble N, Özçete ÖD, Cai X, Handy GE, Andersen JW, Patriarchi T, Li Y, Kaeser PS. Innervation density governs crosstalk of GPCR-based norepinephrine and dopamine sensors. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.11.23.624963. [PMID: 39605389 PMCID: PMC11601633 DOI: 10.1101/2024.11.23.624963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2024]
Abstract
GPCR-based fluorescent sensors are widely used to correlate neuromodulatory signaling with brain function. While experiments in transfected cells often reveal selectivity for individual neurotransmitters, sensor specificity in the brain frequently remains uncertain. Pursuing experiments in brain slices and in vivo, we find that norepinephrine and dopamine cross-activate the respective sensors. Non-specific activation occurred when innervation of the cross-reacting transmitter was high, and silencing of specific innervation was indispensable for interpreting sensor fluorescence.
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Affiliation(s)
- Ricardo C. López
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Natalie Noble
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Özge D. Özçete
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Xintong Cai
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | - Gillian E. Handy
- Department of Neurobiology, Harvard Medical School, Boston, United States
| | | | - Tommaso Patriarchi
- Institute of Pharmacology and Toxicology, University of Zürich, Zürich, Switzerland
- Neuroscience Center Zürich, ETH and University of Zürich, Zürich, Switzerland
| | - Yulong Li
- State Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China
| | - Pascal S. Kaeser
- Department of Neurobiology, Harvard Medical School, Boston, United States
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12
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Zhao Z, Chen JL, Zhan H, Fang CR, Hua LB, Deng HY, Xiang Z, Yang Y, Huang L, Liu YU. Noradrenergic Projections from the Locus Coeruleus to the Medial Prefrontal Cortex Enhances Stress Coping Behavior in Mice Following Long-Term Intermittent Fasting. Neuromolecular Med 2024; 26:47. [PMID: 39580532 DOI: 10.1007/s12017-024-08818-w] [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: 10/25/2024] [Accepted: 11/12/2024] [Indexed: 11/25/2024]
Abstract
Intermittent fasting has been shown to alleviate stress, anxiety, and depressive symptoms. Although noradrenaline, also known as norepinephrine (NE), is implicated in stress regulation, the dynamics of NE release and the associated neural pathways during stress coping behaviors in fasting mice remain poorly understood. In this study, we employed the forced swimming test (FST) to evaluate the effects of intermittent fasting on stress coping behavior in mice. Our results demonstrate that mice subjected to long-term intermittent fasting exhibited significantly more active coping behaviors in the FST compared to control mice. In contrast, acute fasting did not produce similar effects. Using the fluorescent GRAB-NE sensor to measure NE release with sub-second temporal resolution during the FST, we found that intermittent fasting modulates the locus coeruleus-medial prefrontal cortex (LC-mPFC) pathway, which underlies these behavioral adaptations. Moreover, chemogenetic activation of LC-mPFC projections strongly promoted active coping in the FST. These findings suggest that enhanced LC-mPFC activity mediates the increased active coping behavior observed in fasting mice. This study provides new insights into the neural mechanisms through which intermittent fasting may ameliorate depressive-like behaviors, offering potential therapeutic targets for stress-related disorders.
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Affiliation(s)
- Zheng Zhao
- Guangzhou Overseas Chinese Hospital, The First Affiliated Hospital of Jinan University, Guangzhou, China
- Laboratory for Neuroimmunology in Health and Diseases, Center for medical research on innovation and translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Jun-Liang Chen
- Laboratory for Neuroimmunology in Health and Diseases, Center for medical research on innovation and translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Han Zhan
- Laboratory for Neuroimmunology in Health and Diseases, Center for medical research on innovation and translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Chang-Rong Fang
- Laboratory for Neuroimmunology in Health and Diseases, Center for medical research on innovation and translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Li-Bo Hua
- Laboratory for Neuroimmunology in Health and Diseases, Center for medical research on innovation and translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Hao-Yuan Deng
- Laboratory for Neuroimmunology in Health and Diseases, Center for medical research on innovation and translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Zongqin Xiang
- Laboratory for Neuroimmunology in Health and Diseases, Center for medical research on innovation and translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Ying Yang
- Guangzhou Overseas Chinese Hospital, The First Affiliated Hospital of Jinan University, Guangzhou, China
| | - Lang Huang
- Laboratory for Neuroimmunology in Health and Diseases, Center for medical research on innovation and translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
- Department of Neurology, Guangzhou First People's Hospital, Guangzhou, China.
| | - Yong U Liu
- Laboratory for Neuroimmunology in Health and Diseases, Center for medical research on innovation and translation, Institute of Clinical Medicine, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China.
- Department of Neurology, Guangzhou First People's Hospital, Guangzhou, China.
- Department of Neurology, Multi-Omics Research Center for Brain Disorders, The First Affiliated Hospital, University of South China, Hengyang, China.
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13
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Özçete ÖD, Banerjee A, Kaeser PS. Mechanisms of neuromodulatory volume transmission. Mol Psychiatry 2024; 29:3680-3693. [PMID: 38789677 PMCID: PMC11540752 DOI: 10.1038/s41380-024-02608-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 05/07/2024] [Accepted: 05/10/2024] [Indexed: 05/26/2024]
Abstract
A wealth of neuromodulatory transmitters regulate synaptic circuits in the brain. Their mode of signaling, often called volume transmission, differs from classical synaptic transmission in important ways. In synaptic transmission, vesicles rapidly fuse in response to action potentials and release their transmitter content. The transmitters are then sensed by nearby receptors on select target cells with minimal delay. Signal transmission is restricted to synaptic contacts and typically occurs within ~1 ms. Volume transmission doesn't rely on synaptic contact sites and is the main mode of monoamines and neuropeptides, important neuromodulators in the brain. It is less precise than synaptic transmission, and the underlying molecular mechanisms and spatiotemporal scales are often not well understood. Here, we review literature on mechanisms of volume transmission and raise scientific questions that should be addressed in the years ahead. We define five domains by which volume transmission systems can differ from synaptic transmission and from one another. These domains are (1) innervation patterns and firing properties, (2) transmitter synthesis and loading into different types of vesicles, (3) architecture and distribution of release sites, (4) transmitter diffusion, degradation, and reuptake, and (5) receptor types and their positioning on target cells. We discuss these five domains for dopamine, a well-studied monoamine, and then compare the literature on dopamine with that on norepinephrine and serotonin. We include assessments of neuropeptide signaling and of central acetylcholine transmission. Through this review, we provide a molecular and cellular framework for volume transmission. This mechanistic knowledge is essential to define how neuromodulatory systems control behavior in health and disease and to understand how they are modulated by medical treatments and by drugs of abuse.
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Affiliation(s)
- Özge D Özçete
- Department of Neurobiology, Harvard Medical School, Boston, MA, 02115, USA
| | - Aditi Banerjee
- Department of Neurobiology, Harvard Medical School, Boston, MA, 02115, USA
| | - Pascal S Kaeser
- Department of Neurobiology, Harvard Medical School, Boston, MA, 02115, USA.
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14
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Sulaman BA, Zhang Y, Matosevich N, Kjærby C, Foustoukos G, Andersen M, Eban-Rothschild A. Emerging Functions of Neuromodulation during Sleep. J Neurosci 2024; 44:e1277242024. [PMID: 39358018 PMCID: PMC11450531 DOI: 10.1523/jneurosci.1277-24.2024] [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: 07/04/2024] [Revised: 07/24/2024] [Accepted: 07/27/2024] [Indexed: 10/04/2024] Open
Abstract
Neuromodulators act on multiple timescales to affect neuronal activity and behavior. They function as synaptic fine-tuners and master coordinators of neuronal activity across distant brain regions and body organs. While much research on neuromodulation has focused on roles in promoting features of wakefulness and transitions between sleep and wake states, the precise dynamics and functions of neuromodulatory signaling during sleep have received less attention. This review discusses research presented at our minisymposium at the 2024 Society for Neuroscience meeting, highlighting how norepinephrine, dopamine, and acetylcholine orchestrate brain oscillatory activity, control sleep architecture and microarchitecture, regulate responsiveness to sensory stimuli, and facilitate memory consolidation. The potential of each neuromodulator to influence neuronal activity is shaped by the state of the synaptic milieu, which in turn is influenced by the organismal or systemic state. Investigating the effects of neuromodulator release across different sleep substates and synaptic environments offers unique opportunities to deepen our understanding of neuromodulation and explore the distinct computational opportunities that arise during sleep. Moreover, since alterations in neuromodulatory signaling and sleep are implicated in various neuropsychiatric disorders and because existing pharmacological treatments affect neuromodulatory signaling, gaining a deeper understanding of the less-studied aspects of neuromodulators during sleep is of high importance.
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Affiliation(s)
- Bibi Alika Sulaman
- Department of Psychology, University of Michigan, Ann Arbor, Michigan 48109
| | - Yiyao Zhang
- Neuroscience Institute, New York University, New York, New York 10016
| | - Noa Matosevich
- Sagol School of Neuroscience, Tel Aviv University, Tel Aviv-Yafo 69978, Israel
| | - Celia Kjærby
- Center for Translational Neuromedicine, University of Copenhagen, Copenhagen 2200, Denmark
| | - Georgios Foustoukos
- Department of Fundamental Neurosciences, University of Lausanne, Lausanne 1005, Switzerland
| | - Mie Andersen
- Center for Translational Neuromedicine, University of Copenhagen, Copenhagen 2200, Denmark
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15
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Huang J, Crochet S, Sandi C, Petersen CC. Dopamine dynamics in nucleus accumbens across reward-based learning of goal-directed whisker-to-lick sensorimotor transformations in mice. Heliyon 2024; 10:e37831. [PMID: 39323852 PMCID: PMC11422591 DOI: 10.1016/j.heliyon.2024.e37831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Revised: 08/12/2024] [Accepted: 09/11/2024] [Indexed: 09/27/2024] Open
Abstract
The synaptic and neuronal circuit mechanisms underlying reward-based learning remain to be fully determined. In the mammalian brain, dopamine release in nucleus accumbens is thought to contribute importantly to reward signals for learning and promoting synaptic plasticity. Here, through longitudinal fiber photometry of a genetically-encoded fluorescent sensor, we investigated dopamine signals in the nucleus accumbens of thirsty head-restrained mice as they learned to lick a liquid reward spout in response to single deflections of the C2 whisker across varying reward contingencies. Reward delivery triggered by well-timed licking drove fast transient dopamine increases in nucleus accumbens. On the other hand, unrewarded licking was overall associated with reduced dopamine sensor fluorescence, especially in trials where reward was unexpectedly omitted. The dopamine reward signal upon liquid delivery decreased within individual sessions as mice became sated. As mice learned to lick the reward spout in response to whisker deflection, a fast transient sensory-evoked dopamine signal developed, correlating with the learning of the whisker detection task across consecutive training days, as well as within single learning sessions. The well-defined behavioral paradigm involving a unitary stimulus of a single whisker as a reward-predicting cue along with precisely quantified licking allows untangling of sensory, motor and reward-related dopamine signals and how they evolve across the learning of whisker-dependent goal-directed sensorimotor transformations. Our longitudinal measurements of dopamine dynamics across reward-based learning are overall consistent with the hypothesis that dopamine could play an important role as a reward signal for reinforcement learning.
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Affiliation(s)
- Jun Huang
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Laboratory of Behavioral Genetics, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Sylvain Crochet
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Carmen Sandi
- Laboratory of Behavioral Genetics, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Carl C.H. Petersen
- Laboratory of Sensory Processing, Brain Mind Institute, Faculty of Life Sciences, Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
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16
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Muir J, Anguiano M, Kim CK. Neuromodulator and neuropeptide sensors and probes for precise circuit interrogation in vivo. Science 2024; 385:eadn6671. [PMID: 39325905 PMCID: PMC11488521 DOI: 10.1126/science.adn6671] [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: 03/27/2024] [Accepted: 07/01/2024] [Indexed: 09/28/2024]
Abstract
To determine how neuronal circuits encode and drive behavior, it is often necessary to measure and manipulate different aspects of neurochemical signaling in awake animals. Optogenetics and calcium sensors have paved the way for these types of studies, allowing for the perturbation and readout of spiking activity within genetically defined cell types. However, these methods lack the ability to further disentangle the roles of individual neuromodulator and neuropeptides on circuits and behavior. We review recent advances in chemical biology tools that enable precise spatiotemporal monitoring and control over individual neuroeffectors and their receptors in vivo. We also highlight discoveries enabled by such tools, revealing how these molecules signal across different timescales to drive learning, orchestrate behavioral changes, and modulate circuit activity.
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Affiliation(s)
- J. Muir
- Center for Neuroscience, University of California, Davis, Davis, CA 95618, USA
- Department of Neurology, School of Medicine, University of California, Davis, Sacramento, CA 95817, USA
| | - M. Anguiano
- Neuroscience Graduate Group, University of California, Davis, Davis, CA 95616, USA
| | - C. K. Kim
- Center for Neuroscience, University of California, Davis, Davis, CA 95618, USA
- Department of Neurology, School of Medicine, University of California, Davis, Sacramento, CA 95817, USA
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17
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McKenzie S, Sommer AL, Donaldson TN, Pimentel I, Kakani M, Choi IJ, Newman EL, English DF. Event boundaries drive norepinephrine release and distinctive neural representations of space in the rodent hippocampus. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.30.605900. [PMID: 39131365 PMCID: PMC11312532 DOI: 10.1101/2024.07.30.605900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Episodic memories are temporally segmented around event boundaries that tend to coincide with moments of environmental change. During these times, the state of the brain should change rapidly, or reset, to ensure that the information encountered before and after an event boundary is encoded in different neuronal populations. Norepinephrine (NE) is thought to facilitate this network reorganization. However, it is unknown whether event boundaries drive NE release in the hippocampus and, if so, how NE release relates to changes in hippocampal firing patterns. The advent of the new GRABNE sensor now allows for the measurement of NE binding with sub-second resolution. Using this tool in mice, we tested whether NE is released into the dorsal hippocampus during event boundaries defined by unexpected transitions between spatial contexts and presentations of novel objections. We found that NE binding dynamics were well explained by the time elapsed after each of these environmental changes, and were not related to conditioned behaviors, exploratory bouts of movement, or reward. Familiarity with a spatial context accelerated the rate in which phasic NE binding decayed to baseline. Knowing when NE is elevated, we tested how hippocampal coding of space differs during these moments. Immediately after context transitions we observed relatively unique patterns of neural spiking which settled into a modal state at a similar rate in which NE returned to baseline. These results are consistent with a model wherein NE release drives hippocampal representations away from a steady-state attractor. We hypothesize that the distinctive neural codes observed after each event boundary may facilitate long-term memory and contribute to the neural basis for the primacy effect.
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Affiliation(s)
- Sam McKenzie
- Department of Neurosciences, University of New Mexico Health Science Center, Albuquerque, NM 87106
| | - Alexandra L. Sommer
- Department of Neurosciences, University of New Mexico Health Science Center, Albuquerque, NM 87106
| | - Tia N. Donaldson
- Department of Neurosciences, University of New Mexico Health Science Center, Albuquerque, NM 87106
| | - Infania Pimentel
- Department of Neurosciences, University of New Mexico Health Science Center, Albuquerque, NM 87106
- Department of Mechanical Engineering, Tufts School of Engineering, Medford MA 02155
| | - Meenakshi Kakani
- Department of Neurosciences, University of New Mexico Health Science Center, Albuquerque, NM 87106
- Department of Biology, Virginia Commonwealth University, Richmond, VA 23284
| | - Irene Jungyeon Choi
- Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405
| | - Ehren L. Newman
- Psychological and Brain Sciences, Indiana University, Bloomington, IN, 47405
- Program in Neuroscience, Indiana University, Bloomington, IN, 47405
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