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Lu M, Rao J, Ming J, He J, Huang B, Zheng G, Cao Y. Toxicity study of mineral medicine haematitum. JOURNAL OF ETHNOPHARMACOLOGY 2024; 333:118406. [PMID: 38838923 DOI: 10.1016/j.jep.2024.118406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 05/25/2024] [Accepted: 05/28/2024] [Indexed: 06/07/2024]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Haematitum, a time-honored mineral-based Chinese medicine, has been used medicinally in China for over 2000 years. It is now included in the Chinese Pharmacopoeia and used clinically for treating digestive and respiratory diseases. The Chinese Materia Medica records that it is toxic and should not be taken for a long period, but there are few research reports on the toxicity of Haematitum and its potential toxicity mechanisms. AIM OF THE STUDY This study aimed to evaluate the toxicity of Haematitum and calcined Haematitum, including organ toxicity, neurotoxicity, and reproductive toxicity. Further, it is also necessary to explore the mechanism of Haematitum toxicity and to provide a reference for the safe clinical use of the drug. MATERIALS AND METHODS The samples of Haematitum and calcined Haematitum decoctions were prepared. KM mice were treated with samples by gavage for 10 days, and lung damage and apoptosis were assessed by HE staining and TUNEL staining of lung tissues respectively. Metabolomics analysis was performed by HPLC-MS. Metallomics analysis was performed by ICP-MS. In addition, C. elegans was used as a model for 48 h exposure to examine the neurotoxicity and reproductive toxicity-related indices of Haematitum, including locomotor behaviors, growth and development, reproductive behaviors, AChE activities, sensory behaviors, apoptosis, and ROS levels. RESULTS The use of large doses of Haematitum decoction caused lung damage in mice. Neither calcined Haematitum decoction nor Haematitum decoction at clinically used doses showed organ damage. Metabolomics results showed that disorders in lipid metabolic pathways such as sphingolipid metabolism and glycerophospholipid metabolism may be important factors in Haematitum-induced pulmonary toxicity. High doses of Haematitum decoction caused neurological damage to C. elegans, while low doses of Haematitum decoction and calcined Haematitum decoction showed no significant neurotoxicity. Decoction of Haematitum and calcined Haematitum did not show reproductive toxicity to C. elegans. Toxicity was also not observed in the control group of iron (Ⅱ) and iron (Ⅲ) ions in equal amounts with high doses of Haematitum. CONCLUSIONS Haematitum is relatively safe for routine doses and short-term use. Calcination can significantly reduce Haematitum toxicity, and this study provides a reference for safe clinical use.
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Affiliation(s)
- Min Lu
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, China; Hubei Shizhen Laboratory, Wuhan, 430061, China
| | - Jiali Rao
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, China; Hubei Shizhen Laboratory, Wuhan, 430061, China
| | - Jing Ming
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, China; Hubei Shizhen Laboratory, Wuhan, 430061, China
| | - Jianhua He
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, China; Hubei Shizhen Laboratory, Wuhan, 430061, China
| | - Bisheng Huang
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, China; Hubei Shizhen Laboratory, Wuhan, 430061, China
| | - Guohua Zheng
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, China; Hubei Shizhen Laboratory, Wuhan, 430061, China
| | - Yan Cao
- College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, 430065, China; Hubei Shizhen Laboratory, Wuhan, 430061, China.
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2
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Guo M, Wu Y, Hobson CM, Su Y, Qian S, Krueger E, Christensen R, Kroeschell G, Bui J, Chaw M, Zhang L, Liu J, Hou X, Han X, Lu Z, Ma X, Zhovmer A, Combs C, Moyle M, Yemini E, Liu H, Liu Z, Benedetto A, La Riviere P, Colón-Ramos D, Shroff H. Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.15.562439. [PMID: 37986950 PMCID: PMC10659418 DOI: 10.1101/2023.10.15.562439] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more optics into the imaging path. Our method (i) introduces synthetic aberrations to images acquired on the shallow side of image stacks, making them resemble those acquired deeper into the volume and (ii) trains neural networks to reverse the effect of these aberrations. We use simulations and experiments to show that applying the trained 'de-aberration' networks outperforms alternative methods, providing restoration on par with adaptive optics techniques; and subsequently apply the networks to diverse datasets captured with confocal, light-sheet, multi-photon, and super-resolution microscopy. In all cases, the improved quality of the restored data facilitates qualitative image inspection and improves downstream image quantitation, including orientational analysis of blood vessels in mouse tissue and improved membrane and nuclear segmentation in C. elegans embryos.
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3
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Kramer TS, Flavell SW. Building and integrating brain-wide maps of nervous system function in invertebrates. Curr Opin Neurobiol 2024; 86:102868. [PMID: 38569231 DOI: 10.1016/j.conb.2024.102868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 02/13/2024] [Accepted: 03/07/2024] [Indexed: 04/05/2024]
Abstract
The selection and execution of context-appropriate behaviors is controlled by the integrated action of neural circuits throughout the brain. However, how activity is coordinated across brain regions, and how nervous system structure enables these functional interactions, remain open questions. Recent technical advances have made it feasible to build brain-wide maps of nervous system structure and function, such as brain activity maps, connectomes, and cell atlases. Here, we review recent progress in this area, focusing on C. elegans and D. melanogaster, as recent work has produced global maps of these nervous systems. We also describe neural circuit motifs elucidated in studies of specific networks, which highlight the complexities that must be captured to build accurate models of whole-brain function.
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Affiliation(s)
- Talya S Kramer
- Picower Institute for Learning and Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; MIT Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven W Flavell
- Picower Institute for Learning and Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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Ouzounidis VR, Green M, van Capelle CDC, Gebhardt C, Crellin H, Finlayson C, Prevo B, Cheerambathur DK. The outer kinetochore components KNL-1 and Ndc80 complex regulate axon and neuronal cell body positioning in the C. elegans nervous system. Mol Biol Cell 2024; 35:ar83. [PMID: 38656792 PMCID: PMC11238089 DOI: 10.1091/mbc.e23-08-0325] [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: 08/23/2023] [Revised: 04/12/2024] [Accepted: 04/15/2024] [Indexed: 04/26/2024] Open
Abstract
The KMN (Knl1/Mis12/Ndc80) network at the kinetochore, primarily known for its role in chromosome segregation, has been shown to be repurposed during neurodevelopment. Here, we investigate the underlying neuronal mechanism and show that the KMN network promotes the proper axonal organization within the C. elegans head nervous system. Postmitotic degradation of KNL-1, which acts as a scaffold for signaling and has microtubule-binding activities at the kinetochore, led to disorganized ganglia and aberrant placement and organization of axons in the nerve ring - an interconnected axonal network. Through gene-replacement approaches, we demonstrate that the signaling motifs within KNL-1, responsible for recruiting protein phosphatase 1, and activating the spindle assembly checkpoint are required for neurodevelopment. Interestingly, while the microtubule-binding activity is crucial to KMN's neuronal function, microtubule dynamics and organization were unaffected in the absence of KNL-1. Instead, the NDC-80 microtubule-binding mutant displayed notable defects in axon bundling during nerve ring formation, indicating its role in facilitating axon-axon contacts. Overall, these findings provide evidence for a noncanonical role for the KMN network in shaping the structure and connectivity of the nervous system in C. elegans during brain development.
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Affiliation(s)
- Vasileios R. Ouzounidis
- Wellcome Centre for Cell Biology & Institute of Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, EH9 3BF, UK
| | - Mattie Green
- Wellcome Centre for Cell Biology & Institute of Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, EH9 3BF, UK
| | - Charlotte de Ceuninck van Capelle
- Wellcome Centre for Cell Biology & Institute of Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, EH9 3BF, UK
| | - Clara Gebhardt
- Wellcome Centre for Cell Biology & Institute of Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, EH9 3BF, UK
| | - Helena Crellin
- Wellcome Centre for Cell Biology & Institute of Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, EH9 3BF, UK
| | - Cameron Finlayson
- Wellcome Centre for Cell Biology & Institute of Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, EH9 3BF, UK
| | - Bram Prevo
- Wellcome Centre for Cell Biology & Institute of Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, EH9 3BF, UK
| | - Dhanya K. Cheerambathur
- Wellcome Centre for Cell Biology & Institute of Cell Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, EH9 3BF, UK
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5
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Bustillo ME, Douthit J, Astigarraga S, Treisman JE. Two distinct mechanisms of Plexin A function in Drosophila optic lobe lamination and morphogenesis. Development 2024; 151:dev202237. [PMID: 38738602 PMCID: PMC11190435 DOI: 10.1242/dev.202237] [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: 08/06/2023] [Accepted: 04/28/2024] [Indexed: 05/14/2024]
Abstract
Visual circuit development is characterized by subdivision of neuropils into layers that house distinct sets of synaptic connections. We find that, in the Drosophila medulla, this layered organization depends on the axon guidance regulator Plexin A. In Plexin A null mutants, synaptic layers of the medulla neuropil and arborizations of individual neurons are wider and less distinct than in controls. Analysis of semaphorin function indicates that Semaphorin 1a, acting in a subset of medulla neurons, is the primary partner for Plexin A in medulla lamination. Removal of the cytoplasmic domain of endogenous Plexin A has little effect on the formation of medulla layers; however, both null and cytoplasmic domain deletion mutations of Plexin A result in an altered overall shape of the medulla neuropil. These data suggest that Plexin A acts as a receptor to mediate morphogenesis of the medulla neuropil, and as a ligand for Semaphorin 1a to subdivide it into layers. Its two independent functions illustrate how a few guidance molecules can organize complex brain structures by each playing multiple roles.
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Affiliation(s)
- Maria E. Bustillo
- Department of Cell Biology, New York University Grossman School of Medicine, 435 E. 30th Street, New York, NY 10016, USA
| | - Jessica Douthit
- Department of Cell Biology, New York University Grossman School of Medicine, 435 E. 30th Street, New York, NY 10016, USA
| | - Sergio Astigarraga
- Department of Cell Biology, New York University Grossman School of Medicine, 435 E. 30th Street, New York, NY 10016, USA
| | - Jessica E. Treisman
- Department of Cell Biology, New York University Grossman School of Medicine, 435 E. 30th Street, New York, NY 10016, USA
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6
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Agi E, Reifenstein ET, Wit C, Schneider T, Kauer M, Kehribar M, Kulkarni A, von Kleist M, Hiesinger PR. Axonal self-sorting without target guidance in Drosophila visual map formation. Science 2024; 383:1084-1092. [PMID: 38452066 DOI: 10.1126/science.adk3043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 02/01/2024] [Indexed: 03/09/2024]
Abstract
The idea of guidance toward a target is central to axon pathfinding and brain wiring in general. In this work, we show how several thousand axonal growth cones self-pattern without target-dependent guidance during neural superposition wiring in Drosophila. Ablation of all target lamina neurons or loss of target adhesion prevents the stabilization but not the development of the pattern. Intravital imaging at the spatiotemporal resolution of growth cone dynamics in intact pupae and data-driven dynamics simulations reveal a mechanism by which >30,000 filopodia do not explore potential targets, but instead simultaneously generate and navigate a dynamic filopodial meshwork that steers growth directions. Hence, a guidance mechanism can emerge from the interactions of the axons being guided, suggesting self-organization as a more general feature of brain wiring.
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Affiliation(s)
- Egemen Agi
- Division of Neurobiology, Free University of Berlin, 14195 Berlin, Germany
| | - Eric T Reifenstein
- Department of Mathematics, Free University of Berlin, 14195 Berlin, Germany
| | - Charlotte Wit
- Division of Neurobiology, Free University of Berlin, 14195 Berlin, Germany
| | - Teresa Schneider
- Division of Neurobiology, Free University of Berlin, 14195 Berlin, Germany
| | - Monika Kauer
- Division of Neurobiology, Free University of Berlin, 14195 Berlin, Germany
| | - Melinda Kehribar
- Division of Neurobiology, Free University of Berlin, 14195 Berlin, Germany
| | - Abhishek Kulkarni
- Division of Neurobiology, Free University of Berlin, 14195 Berlin, Germany
| | - Max von Kleist
- Department of Mathematics, Free University of Berlin, 14195 Berlin, Germany
| | - P Robin Hiesinger
- Division of Neurobiology, Free University of Berlin, 14195 Berlin, Germany
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7
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Wolterhoff N, Hiesinger PR. Synaptic promiscuity in brain development. Curr Biol 2024; 34:R102-R116. [PMID: 38320473 PMCID: PMC10849093 DOI: 10.1016/j.cub.2023.12.037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2024]
Abstract
Precise synaptic connectivity is a prerequisite for the function of neural circuits, yet individual neurons, taken out of their developmental context, readily form unspecific synapses. How does the genome encode brain wiring in light of this apparent contradiction? Synaptic specificity is the outcome of a long series of developmental processes and mechanisms before, during and after synapse formation. How much promiscuity is permissible or necessary at the moment of synaptic partner choice depends on the extent to which prior development restricts available partners or subsequent development corrects initially made synapses. Synaptic promiscuity at the moment of choice can thereby play important roles in the development of precise connectivity, but also facilitate developmental flexibility and robustness. In this review, we assess the experimental evidence for the prevalence and roles of promiscuous synapse formation during brain development. Many well-established experimental approaches are based on developmental genetic perturbation and an assessment of synaptic connectivity only in the adult; this can make it difficult to pinpoint when a given defect or mechanism occurred. In many cases, such studies reveal mechanisms that restrict partner availability already prior to synapse formation. Subsequently, at the moment of choice, factors including synaptic competency, interaction dynamics and molecular recognition further restrict synaptic partners. The discussion of the development of synaptic specificity through the lens of synaptic promiscuity suggests an algorithmic process based on neurons capable of promiscuous synapse formation that are continuously prevented from making the wrong choices, with no single mechanism or developmental time point sufficient to explain the outcome.
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Affiliation(s)
- Neele Wolterhoff
- Division of Neurobiology, Free University Berlin, 14195 Berlin, Germany
| | - P Robin Hiesinger
- Division of Neurobiology, Free University Berlin, 14195 Berlin, Germany.
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8
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Rabinowitch I, Colón-Ramos DA, Krieg M. Understanding neural circuit function through synaptic engineering. Nat Rev Neurosci 2024; 25:131-139. [PMID: 38172626 DOI: 10.1038/s41583-023-00777-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/29/2023] [Indexed: 01/05/2024]
Abstract
Synapses are a key component of neural circuits, facilitating rapid and specific signalling between neurons. Synaptic engineering - the synthetic insertion of new synaptic connections into in vivo neural circuits - is an emerging approach for neural circuit interrogation. This approach is especially powerful for establishing causality in neural circuit structure-function relationships, for emulating synaptic plasticity and for exploring novel patterns of circuit connectivity. Contrary to other approaches for neural circuit manipulation, synaptic engineering targets specific connections between neurons and functions autonomously with no user-controlled external activation. Synaptic engineering has been successfully implemented in several systems and in different forms, including electrical synapses constructed from ectopically expressed connexin gap junction proteins, synthetic optical synapses composed of presynaptic photon-emitting luciferase coupled with postsynaptic light-gated channels, and artificial neuropeptide signalling pathways. This Perspective describes these different methods and how they have been applied, and examines how the field may advance.
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Affiliation(s)
- Ithai Rabinowitch
- Department of Medical Neurobiology, Institute for Medical Research Israel-Canada, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
| | - Daniel A Colón-Ramos
- Wu Tsai Institute, Department of Neuroscience and Department of Cell Biology, Yale University School of Medicine, New Haven, CT, USA
| | - Michael Krieg
- ICFO - Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, Castelldefels, Spain
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9
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Majeed M, Han H, Zhang K, Cao WX, Liao CP, Hobert O, Lu H. Toolkits for detailed and high-throughput interrogation of synapses in C. elegans. eLife 2024; 12:RP91775. [PMID: 38224479 PMCID: PMC10945580 DOI: 10.7554/elife.91775] [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: 01/16/2024] Open
Abstract
Visualizing synaptic connectivity has traditionally relied on time-consuming electron microscopy-based imaging approaches. To scale the analysis of synaptic connectivity, fluorescent protein-based techniques have been established, ranging from the labeling of specific pre- or post-synaptic components of chemical or electrical synapses to transsynaptic proximity labeling technology such as GRASP and iBLINC. In this paper, we describe WormPsyQi, a generalizable image analysis pipeline that automatically quantifies synaptically localized fluorescent signals in a high-throughput and robust manner, with reduced human bias. We also present a resource of 30 transgenic strains that label chemical or electrical synapses throughout the nervous system of the nematode Caenorhabditis elegans, using CLA-1, RAB-3, GRASP (chemical synapses), or innexin (electrical synapse) reporters. We show that WormPsyQi captures synaptic structures in spite of substantial heterogeneity in neurite morphology, fluorescence signal, and imaging parameters. We use these toolkits to quantify multiple obvious and subtle features of synapses - such as number, size, intensity, and spatial distribution of synapses - in datasets spanning various regions of the nervous system, developmental stages, and sexes. Although the pipeline is described in the context of synapses, it may be utilized for other 'punctate' signals, such as fluorescently tagged neurotransmitter receptors and cell adhesion molecules, as well as proteins in other subcellular contexts. By overcoming constraints on time, sample size, cell morphology, and phenotypic space, this work represents a powerful resource for further analysis of synapse biology in C. elegans.
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Affiliation(s)
- Maryam Majeed
- Department of Biological Sciences, Howard Hughes Medical Institute, Columbia UniversityNew YorkUnited States
| | - Haejun Han
- School of Electrical and Computer Engineering, Georgia Institute of TechnologyAtlantaUnited States
- The Parker H Petit Institute of Bioengineering and Bioscience, Georgia Institute of TechnologyAtlantaUnited States
| | - Keren Zhang
- School of Chemical and Biomolecular Engineering, Georgia Institute of TechnologyAtlantaUnited States
| | - Wen Xi Cao
- Department of Biological Sciences, Howard Hughes Medical Institute, Columbia UniversityNew YorkUnited States
| | - Chien-Po Liao
- Department of Biological Sciences, Howard Hughes Medical Institute, Columbia UniversityNew YorkUnited States
| | - Oliver Hobert
- Department of Biological Sciences, Howard Hughes Medical Institute, Columbia UniversityNew YorkUnited States
| | - Hang Lu
- The Parker H Petit Institute of Bioengineering and Bioscience, Georgia Institute of TechnologyAtlantaUnited States
- School of Chemical and Biomolecular Engineering, Georgia Institute of TechnologyAtlantaUnited States
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10
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Onuchin AA, Chernizova AV, Lebedev MA, Polovnikov KE. Communities in C. elegans connectome through the prism of non-backtracking walks. Sci Rep 2023; 13:22923. [PMID: 38129512 PMCID: PMC10739864 DOI: 10.1038/s41598-023-49503-5] [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: 09/06/2022] [Accepted: 12/08/2023] [Indexed: 12/23/2023] Open
Abstract
The fundamental relationship between the mesoscopic structure of neuronal circuits and organismic functions they subserve is one of the major challenges in contemporary neuroscience. Formation of structurally connected modules of neurons enacts the conversion from single-cell firing to large-scale behaviour of an organism, highlighting the importance of their accurate profiling in the data. While connectomes are typically characterized by significant sparsity of neuronal connections, recent advances in network theory and machine learning have revealed fundamental limitations of traditionally used community detection approaches in cases where the network is sparse. Here we studied the optimal community structure in the structural connectome of Caenorhabditis elegans, for which we exploited a non-conventional approach that is based on non-backtracking random walks, virtually eliminating the sparsity issue. In full agreement with the previous asymptotic results, we demonstrated that non-backtracking walks resolve the ground truth annotation into clusters on stochastic block models (SBM) with the size and density of the connectome better than the spectral methods related to simple random walks. Based on the cluster detectability threshold, we determined that the optimal number of modules in a recently mapped connectome of C. elegans is 10, which precisely corresponds to the number of isolated eigenvalues in the spectrum of the non-backtracking flow matrix. The discovered communities have a clear interpretation in terms of their functional role, which allows one to discern three structural compartments in the worm: the Worm Brain (WB), the Worm Movement Controller (WMC), and the Worm Information Flow Connector (WIFC). Broadly, our work provides a robust network-based framework to reveal mesoscopic structures in sparse connectomic datasets, paving way to further investigation of connectome mechanisms for different functions.
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Affiliation(s)
- Arsenii A Onuchin
- Skolkovo Institute of Science and Technology, Moscow, Russia, 121205
- Laboratory of Complex Networks, Center for Neurophysics and Neuromorphic Technologies, Moscow, Russia
| | - Alina V Chernizova
- Institute of Higher Nervous Activity and Neurophysiology of the Russian Academy of Sciences, Moscow, Russia, 117485
| | - Mikhail A Lebedev
- Faculty of Mechanics and Mathematics, Lomonosov Moscow State University, Moscow, Russia, 119991
- Sechenov Institute of Evolutionary Physiology and Biochemistry of the Russian Academy of Sciences, Saint Petersburg, Russia, 194223
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Ripoll-Sánchez L, Watteyne J, Sun H, Fernandez R, Taylor SR, Weinreb A, Bentley BL, Hammarlund M, Miller DM, Hobert O, Beets I, Vértes PE, Schafer WR. The neuropeptidergic connectome of C. elegans. Neuron 2023; 111:3570-3589.e5. [PMID: 37935195 PMCID: PMC7615469 DOI: 10.1016/j.neuron.2023.09.043] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 08/02/2023] [Accepted: 09/29/2023] [Indexed: 11/09/2023]
Abstract
Efforts are ongoing to map synaptic wiring diagrams, or connectomes, to understand the neural basis of brain function. However, chemical synapses represent only one type of functionally important neuronal connection; in particular, extrasynaptic, "wireless" signaling by neuropeptides is widespread and plays essential roles in all nervous systems. By integrating single-cell anatomical and gene-expression datasets with biochemical analysis of receptor-ligand interactions, we have generated a draft connectome of neuropeptide signaling in the C. elegans nervous system. This network is characterized by high connection density, extended signaling cascades, autocrine foci, and a decentralized topology, with a large, highly interconnected core containing three constituent communities sharing similar patterns of input connectivity. Intriguingly, several key network hubs are little-studied neurons that appear specialized for peptidergic neuromodulation. We anticipate that the C. elegans neuropeptidergic connectome will serve as a prototype to understand how networks of neuromodulatory signaling are organized.
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Affiliation(s)
- Lidia Ripoll-Sánchez
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Department of Psychiatry, Cambridge University, Cambridge, UK
| | - Jan Watteyne
- Department of Biology, KU Leuven, Leuven, Belgium
| | - HaoSheng Sun
- Department of Biological Sciences/HHMI, Columbia University, New York, NY, USA; Department of Cell, Developmental, and Integrative Biology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Robert Fernandez
- Department of Biological Sciences/HHMI, Columbia University, New York, NY, USA
| | - Seth R Taylor
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Alexis Weinreb
- Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Barry L Bentley
- Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, UK
| | - Marc Hammarlund
- Departments of Genetics and Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - David M Miller
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Oliver Hobert
- Department of Biological Sciences/HHMI, Columbia University, New York, NY, USA
| | - Isabel Beets
- Department of Biology, KU Leuven, Leuven, Belgium
| | - Petra E Vértes
- Department of Psychiatry, Cambridge University, Cambridge, UK
| | - William R Schafer
- Neurobiology Division, MRC Laboratory of Molecular Biology, Cambridge, UK; Department of Biology, KU Leuven, Leuven, Belgium.
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12
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Atanas AA, Kim J, Wang Z, Bueno E, Becker M, Kang D, Park J, Kramer TS, Wan FK, Baskoylu S, Dag U, Kalogeropoulou E, Gomes MA, Estrem C, Cohen N, Mansinghka VK, Flavell SW. Brain-wide representations of behavior spanning multiple timescales and states in C. elegans. Cell 2023; 186:4134-4151.e31. [PMID: 37607537 PMCID: PMC10836760 DOI: 10.1016/j.cell.2023.07.035] [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: 11/03/2022] [Revised: 07/05/2023] [Accepted: 07/28/2023] [Indexed: 08/24/2023]
Abstract
Changes in an animal's behavior and internal state are accompanied by widespread changes in activity across its brain. However, how neurons across the brain encode behavior and how this is impacted by state is poorly understood. We recorded brain-wide activity and the diverse motor programs of freely moving C. elegans and built probabilistic models that explain how each neuron encodes quantitative behavioral features. By determining the identities of the recorded neurons, we created an atlas of how the defined neuron classes in the C. elegans connectome encode behavior. Many neuron classes have conjunctive representations of multiple behaviors. Moreover, although many neurons encode current motor actions, others integrate recent actions. Changes in behavioral state are accompanied by widespread changes in how neurons encode behavior, and we identify these flexible nodes in the connectome. Our results provide a global map of how the cell types across an animal's brain encode its behavior.
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Affiliation(s)
- Adam A Atanas
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungsoo Kim
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ziyu Wang
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Bueno
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - McCoy Becker
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Di Kang
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungyeon Park
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Talya S Kramer
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; MIT Biology Graduate Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Flossie K Wan
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Saba Baskoylu
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ugur Dag
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Elpiniki Kalogeropoulou
- School of Computing, University of Leeds, Leeds, UK; School of Biology, University of Leeds, Leeds, UK
| | - Matthew A Gomes
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cassi Estrem
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Netta Cohen
- School of Computing, University of Leeds, Leeds, UK
| | - Vikash K Mansinghka
- Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Steven W Flavell
- Picower Institute for Learning & Memory, Massachusetts Institute of Technology, Cambridge, MA, USA; Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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13
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Venkat A, Bhaskar D, Krishnaswamy S. Multiscale geometric and topological analyses for characterizing and predicting immune responses from single cell data. Trends Immunol 2023; 44:551-563. [PMID: 37301677 DOI: 10.1016/j.it.2023.05.003] [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: 04/02/2023] [Revised: 05/03/2023] [Accepted: 05/04/2023] [Indexed: 06/12/2023]
Abstract
Single cell genomics has revolutionized our ability to map immune heterogeneity and responses. With the influx of large-scale data sets from diverse modalities, the resolution achieved has supported the long-held notion that immune cells are naturally organized into hierarchical relationships, characterized at multiple levels. Such a multigranular structure corresponds to key geometric and topological features. Given that differences between an effective and ineffective immunological response may not be found at one level, there is vested interest in characterizing and predicting outcomes from such features. In this review, we highlight single cell methods and principles for learning geometric and topological properties of data at multiple scales, discussing their contributions to immunology. Ultimately, multiscale approaches go beyond classical clustering, revealing a more comprehensive picture of cellular heterogeneity.
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Affiliation(s)
- Aarthi Venkat
- Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA
| | | | - Smita Krishnaswamy
- Computational Biology and Bioinformatics Program, Yale University, New Haven, CT, USA; Department of Genetics, Yale University, New Haven, CT, USA; Department of Computer Science, Yale University, New Haven, CT, USA.
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14
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Dag U, Nwabudike I, Kang D, Gomes MA, Kim J, Atanas AA, Bueno E, Estrem C, Pugliese S, Wang Z, Towlson E, Flavell SW. Dissecting the functional organization of the C. elegans serotonergic system at whole-brain scale. Cell 2023; 186:2574-2592.e20. [PMID: 37192620 PMCID: PMC10484565 DOI: 10.1016/j.cell.2023.04.023] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Revised: 03/07/2023] [Accepted: 04/17/2023] [Indexed: 05/18/2023]
Abstract
Serotonin influences many aspects of animal behavior. But how serotonin acts on its diverse receptors across the brain to modulate global activity and behavior is unknown. Here, we examine how serotonin release in C. elegans alters brain-wide activity to induce foraging behaviors, like slow locomotion and increased feeding. Comprehensive genetic analyses identify three core serotonin receptors (MOD-1, SER-4, and LGC-50) that induce slow locomotion upon serotonin release and others (SER-1, SER-5, and SER-7) that interact with them to modulate this behavior. SER-4 induces behavioral responses to sudden increases in serotonin release, whereas MOD-1 induces responses to persistent release. Whole-brain imaging reveals widespread serotonin-associated brain dynamics, spanning many behavioral networks. We map all sites of serotonin receptor expression in the connectome, which, together with synaptic connectivity, helps predict which neurons show serotonin-associated activity. These results reveal how serotonin acts at defined sites across a connectome to modulate brain-wide activity and behavior.
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Affiliation(s)
- Ugur Dag
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ijeoma Nwabudike
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Di Kang
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Matthew A Gomes
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungsoo Kim
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Adam A Atanas
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA; Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Bueno
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cassi Estrem
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sarah Pugliese
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ziyu Wang
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Emma Towlson
- Department of Computer Science, Department of Physics and Astronomy, Hotchkiss Brain Institute, Alberta Children's Research Hospital, University of Calgary, Calgary, AB, Canada
| | - Steven W Flavell
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
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15
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Temporal control of neuronal wiring. Semin Cell Dev Biol 2023; 142:81-90. [PMID: 35644877 DOI: 10.1016/j.semcdb.2022.05.012] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 05/13/2022] [Accepted: 05/16/2022] [Indexed: 12/22/2022]
Abstract
Wiring an animal brain is a complex process involving a staggering number of cell-types born at different times and locations in the developing brain. Incorporation of these cells into precise circuits with high fidelity is critical for animal survival and behavior. Assembly of neuronal circuits is heavily dependent upon proper timing of wiring programs, requiring neurons to express specific sets of genes (sometimes transiently) at the right time in development. While cell-type specificity of genetic programs regulating wiring has been studied in detail, mechanisms regulating proper timing and coordination of these programs across cell-types are only just beginning to emerge. In this review, we discuss some temporal regulators of wiring programs and how their activity is controlled over time and space. A common feature emerges from these temporal regulators - they are induced by cell-extrinsic cues and control transcription factors capable of regulating a highly cell-type specific set of target genes. Target specificity in these contexts comes from cell-type specific transcription factors. We propose that the spatiotemporal specificity of wiring programs is controlled by the combinatorial activity of temporal programs and cell-type specific transcription factors. Going forward, a better understanding of temporal regulators will be key to understanding the mechanisms underlying brain wiring, and will be critical for the development of in vitro models like brain organoids.
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16
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Cook SJ, Kalinski CA, Hobert O. Neuronal contact predicts connectivity in the C. elegans brain. Curr Biol 2023:S0960-9822(23)00553-5. [PMID: 37236179 DOI: 10.1016/j.cub.2023.04.071] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 01/26/2023] [Accepted: 04/27/2023] [Indexed: 05/28/2023]
Abstract
Axons must project to particular brain regions, contact adjacent neurons, and choose appropriate synaptic targets to form a nervous system. Multiple mechanisms have been proposed to explain synaptic partnership choice. In a "lock-and-key" mechanism, first proposed by Sperry's chemoaffinity model,1 a neuron selectively chooses a synaptic partner among several different, adjacent target cells, based on a specific molecular recognition code.2 Alternatively, Peters' rule posits that neurons indiscriminately form connections with other neuron types in their proximity; hence, neighborhood choice, determined by initial neuronal process outgrowth and position, is the main predictor of connectivity.3,4 However, whether Peters' rule plays an important role in synaptic wiring remains unresolved.5 To assess the nanoscale relationship between neuronal adjacency and connectivity, we evaluate the expansive set of C. elegans connectomes. We find that synaptic specificity can be accurately modeled as a process mediated by a neurite adjacency threshold and brain strata, offering strong support for Peters' rule as an organizational principle of C. elegans brain wiring.
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Affiliation(s)
- Steven J Cook
- Department of Biological Sciences, Howard Hughes Medical Institute, Columbia University, New York, NY, USA.
| | - Cristine A Kalinski
- Department of Biological Sciences, Howard Hughes Medical Institute, Columbia University, New York, NY, USA
| | - Oliver Hobert
- Department of Biological Sciences, Howard Hughes Medical Institute, Columbia University, New York, NY, USA.
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17
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Schuster HC, Hirth F. Phylogenetic tracing of midbrain-specific regulatory sequences suggests single origin of eubilaterian brains. SCIENCE ADVANCES 2023; 9:eade8259. [PMID: 37224241 PMCID: PMC10208574 DOI: 10.1126/sciadv.ade8259] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/10/2022] [Accepted: 04/18/2023] [Indexed: 05/26/2023]
Abstract
Conserved cis-regulatory elements (CREs) control Engrailed-, Pax2-, and dachshund-related gene expression networks directing the formation and function of corresponding midbrain circuits in arthropods and vertebrates. Polarized outgroup analyses of 31 sequenced metazoan genomes representing all animal clades reveal the emergence of Pax2- and dachshund-related CRE-like sequences in anthozoan Cnidaria. The full complement, including Engrailed-related CRE-like sequences, is only detectable in spiralians, ecdysozoans, and chordates that have a brain; they exhibit comparable genomic locations and extensive nucleotide identities that reveal the presence of a conserved core domain, all of which are absent in non-neural genes and, together, distinguish them from randomly assembled sequences. Their presence concurs with a genetic boundary separating the rostral from caudal nervous systems, demonstrated for the metameric brains of annelids, arthropods, and chordates and the asegmental cycloneuralian and urochordate brain. These findings suggest that gene regulatory networks for midbrain circuit formation evolved within the lineage that led to the common ancestor of protostomes and deuterostomes.
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Affiliation(s)
- Helen C. Schuster
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, and Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
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18
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Breau MA, Trembleau A. Chemical and mechanical control of axon fasciculation and defasciculation. Semin Cell Dev Biol 2023; 140:72-81. [PMID: 35810068 DOI: 10.1016/j.semcdb.2022.06.014] [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: 04/07/2022] [Revised: 06/14/2022] [Accepted: 06/21/2022] [Indexed: 01/28/2023]
Abstract
Neural networks are constructed through the development of robust axonal projections from individual neurons, which ultimately establish connections with their targets. In most animals, developing axons assemble in bundles to navigate collectively across various areas within the central nervous system or the periphery, before they separate from these bundles in order to find their specific targets. These processes, called fasciculation and defasciculation respectively, were thought for many years to be controlled chemically: while guidance cues may attract or repulse axonal growth cones, adhesion molecules expressed at the surface of axons mediate their fasciculation. Recently, an additional non-chemical parameter, the mechanical longitudinal tension of axons, turned out to play a role in axon fasciculation and defasciculation, through zippering and unzippering of axon shafts. In this review, we present an integrated view of the currently known chemical and mechanical control of axon:axon dynamic interactions. We highlight the facts that the decision to cross or not to cross another axon depends on a combination of chemical, mechanical and geometrical parameters, and that the decision to fasciculate/defasciculate through zippering/unzippering relies on the balance between axon:axon adhesion and their mechanical tension. Finally, we speculate about possible functional implications of zippering-dependent axon shaft fasciculation, in the collective migration of axons, and in the sorting of subpopulations of axons.
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Affiliation(s)
- Marie Anne Breau
- Sorbonne Université, Centre National de la Recherche Scientifique (CNRS UMR 7622), Institut de Biologie Paris Seine (IBPS), Developmental Biology Laboratory, Paris, France
| | - Alain Trembleau
- Sorbonne Université, Centre National de la Recherche Scientifique (CNRS UMR8246), Inserm U1130, Institut de Biologie Paris Seine (IBPS), Neuroscience Paris Seine (NPS), Paris, France.
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19
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Kuchroo M, DiStasio M, Song E, Calapkulu E, Zhang L, Ige M, Sheth AH, Majdoubi A, Menon M, Tong A, Godavarthi A, Xing Y, Gigante S, Steach H, Huang J, Huguet G, Narain J, You K, Mourgkos G, Dhodapkar RM, Hirn MJ, Rieck B, Wolf G, Krishnaswamy S, Hafler BP. Single-cell analysis reveals inflammatory interactions driving macular degeneration. Nat Commun 2023; 14:2589. [PMID: 37147305 PMCID: PMC10162998 DOI: 10.1038/s41467-023-37025-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Accepted: 02/27/2023] [Indexed: 05/07/2023] Open
Abstract
Due to commonalities in pathophysiology, age-related macular degeneration (AMD) represents a uniquely accessible model to investigate therapies for neurodegenerative diseases, leading us to examine whether pathways of disease progression are shared across neurodegenerative conditions. Here we use single-nucleus RNA sequencing to profile lesions from 11 postmortem human retinas with age-related macular degeneration and 6 control retinas with no history of retinal disease. We create a machine-learning pipeline based on recent advances in data geometry and topology and identify activated glial populations enriched in the early phase of disease. Examining single-cell data from Alzheimer's disease and progressive multiple sclerosis with our pipeline, we find a similar glial activation profile enriched in the early phase of these neurodegenerative diseases. In late-stage age-related macular degeneration, we identify a microglia-to-astrocyte signaling axis mediated by interleukin-1β which drives angiogenesis characteristic of disease pathogenesis. We validated this mechanism using in vitro and in vivo assays in mouse, identifying a possible new therapeutic target for AMD and possibly other neurodegenerative conditions. Thus, due to shared glial states, the retina provides a potential system for investigating therapeutic approaches in neurodegenerative diseases.
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Affiliation(s)
- Manik Kuchroo
- Department of Neuroscience, Yale University, New Haven, CT, USA
| | | | - Eric Song
- Department of Ophthalmology and Visual Science, Yale University, New Haven, CT, USA
| | - Eda Calapkulu
- Department of Ophthalmology and Visual Science, Yale University, New Haven, CT, USA
| | - Le Zhang
- Department of Neuroscience, Yale University, New Haven, CT, USA
- Department of Neurology, Yale University, New Haven, CT, USA
| | - Maryam Ige
- Yale School of Medicine, New Haven, CT, USA
| | | | - Abdelilah Majdoubi
- Department of Ophthalmology and Visual Science, Yale University, New Haven, CT, USA
| | - Madhvi Menon
- Division of Infection, Immunity and Respiratory Medicine, University of Manchester, Manchester, UK
| | - Alexander Tong
- Department of Computer Science, Yale University, New Haven, CT, USA
| | | | - Yu Xing
- Department of Ophthalmology and Visual Science, Yale University, New Haven, CT, USA
| | - Scott Gigante
- Computational Biology, Bioinformatics Program, Yale University, New Haven, CT, USA
| | - Holly Steach
- Department of Immunobiology, Yale University School of Medicine, New Haven, CT, USA
| | - Jessie Huang
- Department of Computer Science, Yale University, New Haven, CT, USA
| | - Guillaume Huguet
- Mila-Quebec AI institute, Montréal, QC, Canada
- Department of Mathematics and Statistics, Université de Montréal, Montréal, QC, Canada
| | - Janhavi Narain
- Department of Computer Science, Rutgers University, New Brunswick, NJ, USA
| | - Kisung You
- Department of Genetics, Yale University, New Haven, CT, USA
| | - George Mourgkos
- Department of Ophthalmology and Visual Science, Yale University, New Haven, CT, USA
| | | | - Matthew J Hirn
- Department of Computational Mathematics, Science and Engineering, Michigan State University, East Lansing, MI, USA
- Department of Mathematics, Michigan State University, East Lansing, MI, USA
| | - Bastian Rieck
- Department of Biosystems Science and Engineering, ETH Zurich, Zurich, Switzerland
| | - Guy Wolf
- Mila-Quebec AI institute, Montréal, QC, Canada
- Department of Mathematics and Statistics, Université de Montréal, Montréal, QC, Canada
| | - Smita Krishnaswamy
- Department of Computer Science, Yale University, New Haven, CT, USA.
- Department of Genetics, Yale University, New Haven, CT, USA.
| | - Brian P Hafler
- Department of Pathology, Yale University, New Haven, CT, USA.
- Department of Ophthalmology and Visual Science, Yale University, New Haven, CT, USA.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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20
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Porta-de-la-Riva M, Gonzalez AC, Sanfeliu-Cerdán N, Karimi S, Malaiwong N, Pidde A, Morales-Curiel LF, Fernandez P, González-Bolívar S, Hurth C, Krieg M. Neural engineering with photons as synaptic transmitters. Nat Methods 2023; 20:761-769. [PMID: 37024651 DOI: 10.1038/s41592-023-01836-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2021] [Accepted: 03/03/2023] [Indexed: 04/08/2023]
Abstract
Neuronal computation is achieved through connections of individual neurons into a larger network. To expand the repertoire of endogenous cellular communication, we developed a synthetic, photon-assisted synaptic transmission (PhAST) system. PhAST is based on luciferases and channelrhodopsins that enable the transmission of a neuronal state across space, using photons as neurotransmitters. PhAST overcomes synaptic barriers and rescues the behavioral deficit of a glutamate mutant with conditional, calcium-triggered photon emission between two neurons of the Caenorhabditis elegans nociceptive avoidance circuit. To demonstrate versatility and flexibility, we generated de novo synaptic transmission between two unconnected cells in a sexually dimorphic neuronal circuit, suppressed endogenous nocifensive response through activation of an anion channelrhodopsin and switched attractive to aversive behavior in an olfactory circuit. Finally, we applied PhAST to dissect the calcium dynamics of the temporal pattern generator in a motor circuit for ovipositioning. In summary, we established photon-based synaptic transmission that facilitates the modification of animal behavior.
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Affiliation(s)
| | | | | | - Shadi Karimi
- Institut de Ciències Fotòniques, Castelldefels, Spain
| | | | | | | | | | | | - Cedric Hurth
- Institut de Ciències Fotòniques, Castelldefels, Spain
| | - Michael Krieg
- Institut de Ciències Fotòniques, Castelldefels, Spain.
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21
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Dag U, Nwabudike I, Kang D, Gomes MA, Kim J, Atanas AA, Bueno E, Estrem C, Pugliese S, Wang Z, Towlson E, Flavell SW. Dissecting the Functional Organization of the C. elegans Serotonergic System at Whole-Brain Scale. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.15.524132. [PMID: 36711891 PMCID: PMC9882198 DOI: 10.1101/2023.01.15.524132] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Serotonin controls many aspects of animal behavior and cognition. But how serotonin acts on its diverse receptor types in neurons across the brain to modulate global activity and behavior is unknown. Here, we examine how serotonin release from a feeding-responsive neuron in C. elegans alters brain-wide activity to induce foraging behaviors, like slow locomotion and increased feeding. A comprehensive genetic analysis identifies three core serotonin receptors that collectively induce slow locomotion upon serotonin release and three others that interact with them to further modulate this behavior. The core receptors have different functional roles: some induce behavioral responses to sudden increases in serotonin release, whereas others induce responses to persistent release. Whole-brain calcium imaging reveals widespread serotonin-associated brain dynamics, impacting different behavioral networks in different ways. We map out all sites of serotonin receptor expression in the connectome, which, together with synaptic connectivity, helps predict serotonin-associated brain-wide activity changes. These results provide a global view of how serotonin acts at defined sites across a connectome to modulate brain-wide activity and behavior.
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Affiliation(s)
- Ugur Dag
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,These authors contributed equally to this work
| | - Ijeoma Nwabudike
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,These authors contributed equally to this work
| | - Di Kang
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,These authors contributed equally to this work
| | - Matthew A. Gomes
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jungsoo Kim
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Adam A. Atanas
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,Computational and Systems Biology Program, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Eric Bueno
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Cassi Estrem
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sarah Pugliese
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ziyu Wang
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Emma Towlson
- Department of Computer Science, Department of Physics and Astronomy, Hotchkiss Brain Institute, Alberta Children’s Research Hospital, University of Calgary, Calgary, Alberta, Canada
| | - Steven W. Flavell
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA,Corresponding Author:
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22
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Ruach R, Ratner N, Emmons SW, Zaslaver A. The synaptic organization in the Caenorhabditis elegans neural network suggests significant local compartmentalized computations. Proc Natl Acad Sci U S A 2023; 120:e2201699120. [PMID: 36630454 PMCID: PMC9934027 DOI: 10.1073/pnas.2201699120] [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: 01/12/2023] Open
Abstract
Neurons are characterized by elaborate tree-like dendritic structures that support local computations by integrating multiple inputs from upstream presynaptic neurons. It is less clear whether simple neurons, consisting of a few or even a single neurite, may perform local computations as well. To address this question, we focused on the compact neural network of Caenorhabditis elegans animals for which the full wiring diagram is available, including the coordinates of individual synapses. We find that the positions of the chemical synapses along the neurites are not randomly distributed nor can they be explained by anatomical constraints. Instead, synapses tend to form clusters, an organization that supports local compartmentalized computations. In mutually synapsing neurons, connections of opposite polarity cluster separately, suggesting that positive and negative feedback dynamics may be implemented in discrete compartmentalized regions along neurites. In triple-neuron circuits, the nonrandom synaptic organization may facilitate local functional roles, such as signal integration and coordinated activation of functionally related downstream neurons. These clustered synaptic topologies emerge as a guiding principle in the network, presumably to facilitate distinct parallel functions along a single neurite, which effectively increase the computational capacity of the neural network.
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Affiliation(s)
- Rotem Ruach
- aDepartment of Genetics, Silberman Institute of Life Science, The Hebrew University, Jerusalem9190401, Israel
| | - Nir Ratner
- aDepartment of Genetics, Silberman Institute of Life Science, The Hebrew University, Jerusalem9190401, Israel
| | - Scott W. Emmons
- bDominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, New York10461, NY
- cDepartment of Genetics, Albert Einstein College of Medicine, New York10461, NY
| | - Alon Zaslaver
- aDepartment of Genetics, Silberman Institute of Life Science, The Hebrew University, Jerusalem9190401, Israel
- 1To whom correspondence may be addressed.
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23
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Choi K, Kim WK, Hyeon C. Polymer Physics-Based Classification of Neurons. Neuroinformatics 2023; 21:177-193. [PMID: 36190621 DOI: 10.1007/s12021-022-09605-3] [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] [Accepted: 09/12/2022] [Indexed: 11/26/2022]
Abstract
Recognizing that diverse morphologies of neurons are reminiscent of structures of branched polymers, we put forward a principled and systematic way of classifying neurons that employs the ideas of polymer physics. In particular, we use 3D coordinates of individual neurons, which are accessible in recent neuron reconstruction datasets from electron microscope images. We numerically calculate the form factor, F(q), a Fourier transform of the distance distribution of particles comprising an object of interest, which is routinely measured in scattering experiments to quantitatively characterize the structure of materials. For a polymer-like object consisting of n monomers spanning over a length scale of r, F(q) scales with the wavenumber [Formula: see text] as [Formula: see text] at an intermediate range of q, where [Formula: see text] is the fractal dimension or the inverse scaling exponent ([Formula: see text]) characterizing the geometrical feature ([Formula: see text]) of the object. F(q) can be used to describe a neuron morphology in terms of its size ([Formula: see text]) and the extent of branching quantified by [Formula: see text]. By defining the distance between F(q)s as a measure of similarity between two neuronal morphologies, we tackle the neuron classification problem. In comparison with other existing classification methods for neuronal morphologies, our F(q)-based classification rests solely on 3D coordinates of neurons with no prior knowledge of morphological features. When applied to publicly available neuron datasets from three different organisms, our method not only complements other methods but also offers a physical picture of how the dendritic and axonal branches of an individual neuron fill the space of dense neural networks inside the brain.
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Affiliation(s)
- Kiri Choi
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, 02455, Korea
| | - Won Kyu Kim
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, 02455, Korea
| | - Changbong Hyeon
- School of Computational Sciences, Korea Institute for Advanced Study, Seoul, 02455, Korea.
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24
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Fukumasu K, Nose A, Kohsaka H. Extraction of bouton-like structures from neuropil calcium imaging data. Neural Netw 2022; 156:218-238. [DOI: 10.1016/j.neunet.2022.09.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 09/09/2022] [Accepted: 09/28/2022] [Indexed: 11/11/2022]
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25
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Yu YV, Xue W, Chen Y. Multisensory Integration in Caenorhabditis elegans in Comparison to Mammals. Brain Sci 2022; 12:brainsci12101368. [PMID: 36291302 PMCID: PMC9599712 DOI: 10.3390/brainsci12101368] [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: 08/31/2022] [Revised: 09/28/2022] [Accepted: 10/03/2022] [Indexed: 11/30/2022] Open
Abstract
Multisensory integration refers to sensory inputs from different sensory modalities being processed simultaneously to produce a unitary output. Surrounded by stimuli from multiple modalities, animals utilize multisensory integration to form a coherent and robust representation of the complex environment. Even though multisensory integration is fundamentally essential for animal life, our understanding of the underlying mechanisms, especially at the molecular, synaptic and circuit levels, remains poorly understood. The study of sensory perception in Caenorhabditis elegans has begun to fill this gap. We have gained a considerable amount of insight into the general principles of sensory neurobiology owing to C. elegans’ highly sensitive perceptions, relatively simple nervous system, ample genetic tools and completely mapped neural connectome. Many interesting paradigms of multisensory integration have been characterized in C. elegans, for which input convergence occurs at the sensory neuron or the interneuron level. In this narrative review, we describe some representative cases of multisensory integration in C. elegans, summarize the underlying mechanisms and compare them with those in mammalian systems. Despite the differences, we believe C. elegans is able to provide unique insights into how processing and integrating multisensory inputs can generate flexible and adaptive behaviors. With the emergence of whole brain imaging, the ability of C. elegans to monitor nearly the entire nervous system may be crucial for understanding the function of the brain as a whole.
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Affiliation(s)
- Yanxun V. Yu
- Department of Neurology, Medical Research Institute, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan 430070, China
- Frontier Science Center for Immunology and Metabolism, Wuhan University, Wuhan 430070, China
- Correspondence: or
| | - Weikang Xue
- Department of Neurology, Medical Research Institute, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan 430070, China
| | - Yuanhua Chen
- Department of Neurology, Medical Research Institute, Zhongnan Hospital of Wuhan University, Wuhan University, Wuhan 430070, China
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26
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Smith JJ, Kenny IW, Wolff C, Cray R, Kumar A, Sherwood DR, Matus DQ. A light sheet fluorescence microscopy protocol for Caenorhabditis elegans larvae and adults. Front Cell Dev Biol 2022; 10:1012820. [PMID: 36274853 PMCID: PMC9586288 DOI: 10.3389/fcell.2022.1012820] [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: 08/05/2022] [Accepted: 09/20/2022] [Indexed: 01/07/2023] Open
Abstract
Light sheet fluorescence microscopy (LSFM) has become a method of choice for live imaging because of its fast acquisition and reduced photobleaching and phototoxicity. Despite the strengths and growing availability of LSFM systems, no generalized LSFM mounting protocol has been adapted for live imaging of post-embryonic stages of C. elegans. A major challenge has been to develop methods to limit animal movement using a mounting media that matches the refractive index of the optical system. Here, we describe a simple mounting and immobilization protocol using a refractive-index matched UV-curable hydrogel within fluorinated ethylene propylene (FEP) tubes for efficient and reliable imaging of larval and adult C. elegans stages.
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Affiliation(s)
- Jayson J. Smith
- Department of Neurobiology, University of Chicago, Chicago, IL, United States,University of Chicago Neuroscience Institute, Chicago, IL, United States,Embryology: Modern Concepts and Techniques, Marine Biological Laboratory, Woods Hole, MA, United States
| | - Isabel W. Kenny
- Embryology: Modern Concepts and Techniques, Marine Biological Laboratory, Woods Hole, MA, United States,Department of Biology, Duke University, Durham, NC, United States
| | - Carsten Wolff
- Embryology: Modern Concepts and Techniques, Marine Biological Laboratory, Woods Hole, MA, United States,Marine Biological Laboratory, Woods Hole, MA, United States
| | - Rachel Cray
- Marine Biological Laboratory, Woods Hole, MA, United States
| | - Abhishek Kumar
- Embryology: Modern Concepts and Techniques, Marine Biological Laboratory, Woods Hole, MA, United States,Marine Biological Laboratory, Woods Hole, MA, United States
| | - David R. Sherwood
- Embryology: Modern Concepts and Techniques, Marine Biological Laboratory, Woods Hole, MA, United States,Department of Biology, Duke University, Durham, NC, United States,*Correspondence: David R. Sherwood, ; David Q. Matus,
| | - David Q. Matus
- Embryology: Modern Concepts and Techniques, Marine Biological Laboratory, Woods Hole, MA, United States,Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, NY, United States,*Correspondence: David R. Sherwood, ; David Q. Matus,
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27
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Abstract
Fluorescence microscopy is a highly effective tool for interrogating biological structure and function, particularly when imaging across multiple spatiotemporal scales. Here we survey recent innovations and applications in the relatively understudied area of multiscale fluorescence imaging of living samples. We discuss fundamental challenges in live multiscale imaging and describe successful examples that highlight the power of this approach. We attempt to synthesize general strategies from these test cases, aiming to help accelerate progress in this exciting area.
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Affiliation(s)
- Yicong Wu
- Laboratory of High-Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20892, USA.
| | - Hari Shroff
- Laboratory of High-Resolution Optical Imaging, National Institute of Biomedical Imaging and Bioengineering, National Institutes of Health, Bethesda, MD, 20892, USA
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 20147, USA
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28
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Ardiel EL, Lauziere A, Xu S, Harvey BJ, Christensen RP, Nurrish S, Kaplan JM, Shroff H. Stereotyped behavioral maturation and rhythmic quiescence in C.elegans embryos. eLife 2022; 11:76836. [PMID: 35929725 PMCID: PMC9448323 DOI: 10.7554/elife.76836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2022] [Accepted: 08/01/2022] [Indexed: 11/18/2022] Open
Abstract
Systematic analysis of rich behavioral recordings is being used to uncover how circuits encode complex behaviors. Here, we apply this approach to embryos. What are the first embryonic behaviors and how do they evolve as early neurodevelopment ensues? To address these questions, we present a systematic description of behavioral maturation for Caenorhabditis elegans embryos. Posture libraries were built using a genetically encoded motion capture suit imaged with light-sheet microscopy and annotated using custom tracking software. Analysis of cell trajectories, postures, and behavioral motifs revealed a stereotyped developmental progression. Early movement is dominated by flipping between dorsal and ventral coiling, which gradually slows into a period of reduced motility. Late-stage embryos exhibit sinusoidal waves of dorsoventral bends, prolonged bouts of directed motion, and a rhythmic pattern of pausing, which we designate slow wave twitch (SWT). Synaptic transmission is required for late-stage motion but not for early flipping nor the intervening inactive phase. A high-throughput behavioral assay and calcium imaging revealed that SWT is elicited by the rhythmic activity of a quiescence-promoting neuron (RIS). Similar periodic quiescent states are seen prenatally in diverse animals and may play an important role in promoting normal developmental outcomes.
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Affiliation(s)
- Evan L Ardiel
- Department of Molecular Biology, Massachusetts General Hospital, Boston, United States
| | - Andrew Lauziere
- National Institute of Biomedical Imaging and Bioengineering, Bethesda, United States
| | - Stephen Xu
- National Institute of Biomedical Imaging and Bioengineering, Bethesda, United States
| | - Brandon J Harvey
- National Institute of Biomedical Imaging and Bioengineering, Bethesda, United States
| | | | - Stephen Nurrish
- Department of Molecular Biology, Massachusetts General Hospital, Boston, United States
| | - Joshua M Kaplan
- Department of Molecular Biology, Massachusetts General Hospital, Boston, United States
| | - Hari Shroff
- National Institute of Biomedical Imaging and Bioengineering, Bethesda, United States
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29
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Effect of a maternal high fat diet with vegetable substitution on fetal brain transcriptome. J Nutr Biochem 2022; 108:109088. [PMID: 35691591 DOI: 10.1016/j.jnutbio.2022.109088] [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: 09/30/2021] [Revised: 04/02/2022] [Accepted: 05/12/2022] [Indexed: 11/20/2022]
Abstract
Maternal dietary conditions play a major role in fetal growth and brain development. The primary aim of this study was to determine the effects of 5% of energy substitution by vegetables in a maternal dietary fat on placental and fetal weight and on fetal brain gene expression. Two-month-old female C57BL/6 mice were fed 16% (normal-fat, NF), 45% fat (HF), or HF substituted with vegetables (5% energy, HF+VS) diets for 12 weeks. Dams were then bred with NF diet-fed male mice. Placenta and fetal weights were measured at gestational age 19 (D19). RNA was isolated from fetal whole brains and sequenced using Illumina HiSeq. HF+VS diet prevented maternal HF diet-induced decreases in placental weight at D19. Feeding of a maternal HF diet was associated with 79 differentially expressed genes (DEGs), while maternal vegetable substitution was associated with 131 DEGs. The vegetable substitution diet decreased Apold1 (P=0.0319), Spata2l (P=0.0404) and Celsr1 (P<0.03) expression compared to HF diet. Enrichment analysis of HF vs HF +VS DEGs identified that synapse organization, and regulation of embryonic development were significantly represented. KEGG enrichment analysis identified a significant representation of DEGs in the ubiquitin mediated proteolysis pathway in HF vs HF +VS, and chemokine signaling pathway in NF vs HF. These findings suggest that at D19, in a rodent model, a maternal HF diet alters placental and fetal growth, and that vegetable supplementation renders a protective effect against these changes.
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30
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Santella A, Kolotuev I, Kizilyaprak C, Bao Z. Cross-modality synthesis of EM time series and live fluorescence imaging. eLife 2022; 11:77918. [PMID: 35666127 PMCID: PMC9213002 DOI: 10.7554/elife.77918] [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: 02/15/2022] [Accepted: 06/05/2022] [Indexed: 11/13/2022] Open
Abstract
Analyses across imaging modalities allow the integration of complementary spatiotemporal information about brain development, structure, and function. However, systematic atlasing across modalities is limited by challenges to effective image alignment. We combine highly spatially resolved electron microscopy (EM) and highly temporally resolved time-lapse fluorescence microscopy (FM) to examine the emergence of a complex nervous system in Caenorhabditis elegans embryogenesis. We generate an EM time series at four classic developmental stages and create a landmark-based co-optimization algorithm for cross-modality image alignment, which handles developmental heterochrony among datasets to achieve accurate single-cell level alignment. Synthesis based on the EM series and time-lapse FM series carrying different cell-specific markers reveals critical dynamic behaviors across scales of identifiable individual cells in the emergence of the primary neuropil, the nerve ring, as well as a major sensory organ, the amphid. Our study paves the way for systematic cross-modality data synthesis in C. elegans and demonstrates a powerful approach that may be applied broadly.
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Affiliation(s)
- Anthony Santella
- Molecular Cytology Core, Memorial Sloan Kettering Cancer Center, New York, United States
| | - Irina Kolotuev
- Electron Microscopy Facility, University of Lausanne, Lausanne, Switzerland
| | | | - Zhirong Bao
- Developmental Biology Program, Memorial Sloan Kettering Cancer Center, New York, United States
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31
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Flavell SW, Gordus A. Dynamic functional connectivity in the static connectome of Caenorhabditis elegans. Curr Opin Neurobiol 2022; 73:102515. [PMID: 35183877 PMCID: PMC9621599 DOI: 10.1016/j.conb.2021.12.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 12/16/2021] [Accepted: 12/22/2021] [Indexed: 01/01/2023]
Abstract
A hallmark of adaptive behavior is the ability to flexibly respond to sensory cues. To understand how neural circuits implement this flexibility, it is critical to resolve how a static anatomical connectome can be modulated such that functional connectivity in the network can be dynamically regulated. Here, we review recent work in the roundworm Caenorhabditis elegans on this topic. EM studies have mapped anatomical connectomes of many C. elegans animals, highlighting the level of stereotypy in the anatomical network. Brain-wide calcium imaging and studies of specified neural circuits have uncovered striking flexibility in the functional coupling of neurons. The coupling between neurons is controlled by neuromodulators that act over long timescales. This gives rise to persistent behavioral states that animals switch between, allowing them to generate adaptive behavioral responses across environmental conditions. Thus, the dynamic coupling of neurons enables multiple behavioral states to be encoded in a physically stereotyped connectome.
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Affiliation(s)
- Steven W Flavell
- Picower Institute for Learning and Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA.
| | - Andrew Gordus
- Department of Biology, Solomon H. Snyder Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA.
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32
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Ohno H, Bao Z. Small RNAs couple embryonic developmental programs to gut microbes. SCIENCE ADVANCES 2022; 8:eabl7663. [PMID: 35319987 PMCID: PMC8942359 DOI: 10.1126/sciadv.abl7663] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 01/28/2022] [Indexed: 06/14/2023]
Abstract
Embryogenesis has long been known for its robustness to environmental factors. Although developmental tuning of embryogenesis to the environment experienced by the parent may be beneficial, little is understood on whether and how developmental patterns proactively change. Here, we show that Caenorhabditis elegans undergoes alternative embryogenesis in response to maternal gut microbes. Harmful microbes result in altered endodermal cell divisions; morphological changes, including left-right asymmetric development; double association between intestinal and primordial germ cells; and partial rescue of fecundity. The miR-35 microRNA family, which is controlled by systemic endogenous RNA interference and targets the β-transducin repeat-containing protein/cell division cycle 25 (CDC25) pathway, transmits intergenerational information to regulate cell divisions and reproduction. Our findings challenge the widespread assumption that C. elegans has an invariant cell lineage that consists of a fixed cell number and provide insights into how organisms optimize embryogenesis to adapt to environmental changes through epigenetic control.
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33
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Rapti G. Open Frontiers in Neural Cell Type Investigations; Lessons From Caenorhabditis elegans and Beyond, Toward a Multimodal Integration. Front Neurosci 2022; 15:787753. [PMID: 35321480 PMCID: PMC8934944 DOI: 10.3389/fnins.2021.787753] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 12/30/2021] [Indexed: 11/13/2022] Open
Abstract
Nervous system cells, the building blocks of circuits, have been studied with ever-progressing resolution, yet neural circuits appear still resistant to schemes of reductionist classification. Due to their sheer numbers, complexity and diversity, their systematic study requires concrete classifications that can serve reduced dimensionality, reproducibility, and information integration. Conventional hierarchical schemes transformed through the history of neuroscience by prioritizing criteria of morphology, (electro)physiological activity, molecular content, and circuit function, influenced by prevailing methodologies of the time. Since the molecular biology revolution and the recent advents in transcriptomics, molecular profiling gains ground toward the classification of neurons and glial cell types. Yet, transcriptomics entails technical challenges and more importantly uncovers unforeseen spatiotemporal heterogeneity, in complex and simpler nervous systems. Cells change states dynamically in space and time, in response to stimuli or throughout their developmental trajectory. Mapping cell type and state heterogeneity uncovers uncharted terrains in neurons and especially in glial cell biology, that remains understudied in many aspects. Examining neurons and glial cells from the perspectives of molecular neuroscience, physiology, development and evolution highlights the advantage of multifaceted classification schemes. Among the amalgam of models contributing to neuroscience research, Caenorhabditis elegans combines nervous system anatomy, lineage, connectivity and molecular content, all mapped at single-cell resolution, and can provide valuable insights for the workflow and challenges of the multimodal integration of cell type features. This review reflects on concepts and practices of neuron and glial cells classification and how research, in C. elegans and beyond, guides nervous system experimentation through integrated multidimensional schemes. It highlights underlying principles, emerging themes, and open frontiers in the study of nervous system development, regulatory logic and evolution. It proposes unified platforms to allow integrated annotation of large-scale datasets, gene-function studies, published or unpublished findings and community feedback. Neuroscience is moving fast toward interdisciplinary, high-throughput approaches for combined mapping of the morphology, physiology, connectivity, molecular function, and the integration of information in multifaceted schemes. A closer look in mapped neural circuits and understudied terrains offers insights for the best implementation of these approaches.
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34
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Juanez K, Ghose P. Repurposing the Killing Machine: Non-canonical Roles of the Cell Death Apparatus in Caenorhabditis elegans Neurons. Front Cell Dev Biol 2022; 10:825124. [PMID: 35237604 PMCID: PMC8882910 DOI: 10.3389/fcell.2022.825124] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/31/2022] [Indexed: 12/29/2022] Open
Abstract
Here we highlight the increasingly divergent functions of the Caenorhabditis elegans cell elimination genes in the nervous system, beyond their well-documented roles in cell dismantling and removal. We describe relevant background on the C. elegans nervous system together with the apoptotic cell death and engulfment pathways, highlighting pioneering work in C. elegans. We discuss in detail the unexpected, atypical roles of cell elimination genes in various aspects of neuronal development, response and function. This includes the regulation of cell division, pruning, axon regeneration, and behavioral outputs. We share our outlook on expanding our thinking as to what cell elimination genes can do and noting their versatility. We speculate on the existence of novel genes downstream and upstream of the canonical cell death pathways relevant to neuronal biology. We also propose future directions emphasizing the exploration of the roles of cell death genes in pruning and guidance during embryonic development.
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35
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Sengupta T, Koonce NL, Vázquez-Martínez N, Moyle MW, Duncan LH, Emerson SE, Han X, Shao L, Wu Y, Santella A, Fan L, Bao Z, Mohler W, Shroff H, Colón-Ramos DA. Differential adhesion regulates neurite placement via a retrograde zippering mechanism. eLife 2021; 10:71171. [PMID: 34783657 PMCID: PMC8843091 DOI: 10.7554/elife.71171] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Accepted: 11/15/2021] [Indexed: 11/13/2022] Open
Abstract
During development, neurites and synapses segregate into specific neighborhoods or layers within nerve bundles. The developmental programs guiding placement of neurites in specific layers, and hence their incorporation into specific circuits, are not well understood. We implement novel imaging methods and quantitative models to document the embryonic development of the C. elegans brain neuropil, and discover that differential adhesion mechanisms control precise placement of single neurites onto specific layers. Differential adhesion is orchestrated via developmentally-regulated expression of the IgCAM SYG-1, and its partner ligand SYG-2. Changes in SYG-1 expression across neuropil layers result in changes in adhesive forces, which sort SYG-2-expressing neurons. Sorting to layers occurs, not via outgrowth from the neurite tip, but via an alternate mechanism of retrograde zippering, involving interactions between neurite shafts. Our study indicates that biophysical principles from differential adhesion govern neurite placement and synaptic specificity in vivo in developing neuropil bundles.
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Affiliation(s)
- Titas Sengupta
- Yale University School of Medicine, New Haven, United States
| | - Noelle L Koonce
- Yale University School of Medicine, New Haven, United States
| | | | - Mark W Moyle
- Yale University School of Medicine, New Haven, United States
| | | | - Sarah E Emerson
- Yale University School of Medicine, New Haven, United States
| | - Xiaofei Han
- National Institutes of Health, Bethesda, United States
| | - Lin Shao
- Yale University School of Medicine, New Haven, United States
| | - Yicong Wu
- National Institutes of Health, Bethesda, United States
| | - Anthony Santella
- Developmental Biology Program, Molecular Cytology Core, Sloan-Kettering Institute, New York, United States
| | - Li Fan
- Helen and Robert Appel Alzheimer's Disease Institute, Weill Cornell Medicine, New York, United States
| | - Zhirong Bao
- Developmental Biology Program, Sloan-Kettering Institute, New York, United States
| | - William Mohler
- Department of Genetics and Developmental Biology, University of Connecticut Health Center, Farmington, United States
| | - Hari Shroff
- National Institutes of Health, Bethesda, United States
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36
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A genetically encoded tool for reconstituting synthetic modulatory neurotransmission and reconnect neural circuits in vivo. Nat Commun 2021; 12:4795. [PMID: 34373460 PMCID: PMC8352926 DOI: 10.1038/s41467-021-24690-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Accepted: 06/18/2021] [Indexed: 11/19/2022] Open
Abstract
Chemogenetic and optogenetic tools have transformed the field of neuroscience by facilitating the examination and manipulation of existing circuits. Yet, the field lacks tools that enable rational rewiring of circuits via the creation or modification of synaptic relationships. Here we report the development of HySyn, a system designed to reconnect neural circuits in vivo by reconstituting synthetic modulatory neurotransmission. We demonstrate that genetically targeted expression of the two HySyn components, a Hydra-derived neuropeptide and its receptor, creates de novo neuromodulatory transmission in a mammalian neuronal tissue culture model and functionally rewires a behavioral circuit in vivo in the nematode Caenorhabditis elegans. HySyn can interface with existing optogenetic, chemogenetic and pharmacological approaches to functionally probe synaptic transmission, dissect neuropeptide signaling, or achieve targeted modulation of specific neural circuits and behaviors. Engineering de novo synapse-like connections between neurons could enhance our understanding of neuronal circuits and how they generate behaviour. The authors present a two-component system that creates synthetic neuromodulatory connections to manipulate intracellular Ca2+ levels in in vivo neural circuits.
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37
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Byrd DT, Jin Y. Wired for insight-recent advances in Caenorhabditis elegans neural circuits. Curr Opin Neurobiol 2021; 69:159-169. [PMID: 33957432 PMCID: PMC8387325 DOI: 10.1016/j.conb.2021.02.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2021] [Revised: 02/16/2021] [Accepted: 02/22/2021] [Indexed: 11/15/2022]
Abstract
The completion of Caenorhabditis elegans connectomics four decades ago has long guided mechanistic investigation of neuronal circuits. Recent technological advances in microscopy and computation programs have aided re-examination of this connectomics, expanding our knowledge by both uncovering previously unreported synaptic connections and also generating models for neural networks underlying behaviors. Combining molecular information from single cell transcriptomes with elegant tools for cell-specific manipulation has further enhanced the ability to precisely investigate individual neurons in behaving animals. This mini-review aims to provide an overview of new information on connectomics and progress toward a molecular atlas of C. elegans nervous system, and discuss emerging findings on neuronal circuits.
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Affiliation(s)
- Dana T Byrd
- Neurobiology Section, University of California San Diego, La Jolla, CA, 92093, USA.
| | - Yishi Jin
- Neurobiology Section, University of California San Diego, La Jolla, CA, 92093, USA; Kavli Institute of Brain and Mind, University of California San Diego, La Jolla, CA, 92093, USA.
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38
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Weaver CJ, Poulain FE. From whole organism to ultrastructure: progress in axonal imaging for decoding circuit development. Development 2021; 148:271122. [PMID: 34328171 DOI: 10.1242/dev.199717] [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] [Indexed: 01/21/2023]
Abstract
Since the pioneering work of Ramón y Cajal, scientists have sought to unravel the complexities of axon development underlying neural circuit formation. Micrometer-scale axonal growth cones navigate to targets that are often centimeters away. To reach their targets, growth cones react to dynamic environmental cues that change in the order of seconds to days. Proper axon growth and guidance are essential to circuit formation, and progress in imaging has been integral to studying these processes. In particular, advances in high- and super-resolution microscopy provide the spatial and temporal resolution required for studying developing axons. In this Review, we describe how improved microscopy has revolutionized our understanding of axonal development. We discuss how novel technologies, specifically light-sheet and super-resolution microscopy, led to new discoveries at the cellular scale by imaging axon outgrowth and circuit wiring with extreme precision. We next examine how advanced microscopy broadened our understanding of the subcellular dynamics driving axon growth and guidance. We finally assess the current challenges that the field of axonal biology still faces for imaging axons, and examine how future technology could meet these needs.
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Affiliation(s)
- Cory J Weaver
- Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA
| | - Fabienne E Poulain
- Department of Biological Sciences, University of South Carolina, Columbia, SC 29208, USA
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39
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Taylor SR, Santpere G, Weinreb A, Barrett A, Reilly MB, Xu C, Varol E, Oikonomou P, Glenwinkel L, McWhirter R, Poff A, Basavaraju M, Rafi I, Yemini E, Cook SJ, Abrams A, Vidal B, Cros C, Tavazoie S, Sestan N, Hammarlund M, Hobert O, Miller DM. Molecular topography of an entire nervous system. Cell 2021; 184:4329-4347.e23. [PMID: 34237253 DOI: 10.1016/j.cell.2021.06.023] [Citation(s) in RCA: 280] [Impact Index Per Article: 93.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 04/09/2021] [Accepted: 06/14/2021] [Indexed: 02/08/2023]
Abstract
We have produced gene expression profiles of all 302 neurons of the C. elegans nervous system that match the single-cell resolution of its anatomy and wiring diagram. Our results suggest that individual neuron classes can be solely identified by combinatorial expression of specific gene families. For example, each neuron class expresses distinct codes of ∼23 neuropeptide genes and ∼36 neuropeptide receptors, delineating a complex and expansive "wireless" signaling network. To demonstrate the utility of this comprehensive gene expression catalog, we used computational approaches to (1) identify cis-regulatory elements for neuron-specific gene expression and (2) reveal adhesion proteins with potential roles in process placement and synaptic specificity. Our expression data are available at https://cengen.org and can be interrogated at the web application CengenApp. We expect that this neuron-specific directory of gene expression will spur investigations of underlying mechanisms that define anatomy, connectivity, and function throughout the C. elegans nervous system.
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Affiliation(s)
- Seth R Taylor
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Gabriel Santpere
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA; Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), DCEXS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Alexis Weinreb
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
| | - Alec Barrett
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
| | - Molly B Reilly
- Department of Biological Sciences, Columbia University, New York, NY, USA; Howard Hughes Medical Institute, Columbia University, New York, NY, USA
| | - Chuan Xu
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Erdem Varol
- Department of Statistics, Columbia University, New York, NY, USA
| | - Panos Oikonomou
- Department of Biological Sciences, Columbia University, New York, NY, USA; Department of Systems Biology, Columbia University Medical Center, New York, NY, USA
| | - Lori Glenwinkel
- Department of Biological Sciences, Columbia University, New York, NY, USA; Howard Hughes Medical Institute, Columbia University, New York, NY, USA
| | - Rebecca McWhirter
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Abigail Poff
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Manasa Basavaraju
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
| | - Ibnul Rafi
- Department of Biological Sciences, Columbia University, New York, NY, USA; Howard Hughes Medical Institute, Columbia University, New York, NY, USA
| | - Eviatar Yemini
- Department of Biological Sciences, Columbia University, New York, NY, USA; Howard Hughes Medical Institute, Columbia University, New York, NY, USA
| | - Steven J Cook
- Department of Biological Sciences, Columbia University, New York, NY, USA; Howard Hughes Medical Institute, Columbia University, New York, NY, USA
| | - Alexander Abrams
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA
| | - Berta Vidal
- Department of Biological Sciences, Columbia University, New York, NY, USA; Howard Hughes Medical Institute, Columbia University, New York, NY, USA
| | - Cyril Cros
- Department of Biological Sciences, Columbia University, New York, NY, USA; Howard Hughes Medical Institute, Columbia University, New York, NY, USA
| | - Saeed Tavazoie
- Department of Biological Sciences, Columbia University, New York, NY, USA; Department of Systems Biology, Columbia University Medical Center, New York, NY, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA
| | - Marc Hammarlund
- Department of Neuroscience, Yale University School of Medicine, New Haven, CT, USA; Department of Genetics, Yale University School of Medicine, New Haven, CT, USA.
| | - Oliver Hobert
- Department of Biological Sciences, Columbia University, New York, NY, USA; Howard Hughes Medical Institute, Columbia University, New York, NY, USA.
| | - David M Miller
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA; Program in Neuroscience, Vanderbilt University School of Medicine, Nashville, TN, USA.
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40
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Betzel R, Vértes P. Organizing principles of the C. elegans contactome. Cell Syst 2021; 12:689-691. [PMID: 34293322 DOI: 10.1016/j.cels.2021.06.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Two recent studies published in Nature generate and analyze, for the first time, the network of ∼100,000 membrane contacts between neurons in the C. elegans nerve ring. These novel data, extracted from legacy electron microscographs, represent a shift in our understanding of C. elegans neural networks and their similarity to mammalian brains.
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Affiliation(s)
- Richard Betzel
- Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN 47405, USA; Cognitive Science Program, Indiana University, Bloomington, IN 47405, USA; Program in Neuroscience, Indiana University, Bloomington, IN 47405, USA; Network Science Institute, Indiana University, Bloomington, IN 47405, USA.
| | - Petra Vértes
- Department of Psychiatry, University of Cambridge, Cambridge CB2 0SZ, UK; The Alan Turing Institute, London SE5 8AF, UK.
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41
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Berghoff EG, Glenwinkel L, Bhattacharya A, Sun H, Varol E, Mohammadi N, Antone A, Feng Y, Nguyen K, Cook SJ, Wood JF, Masoudi N, Cros CC, Ramadan YH, Ferkey DM, Hall DH, Hobert O. The Prop1-like homeobox gene unc-42 specifies the identity of synaptically connected neurons. eLife 2021; 10:e64903. [PMID: 34165428 PMCID: PMC8225392 DOI: 10.7554/elife.64903] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 05/17/2021] [Indexed: 12/13/2022] Open
Abstract
Many neuronal identity regulators are expressed in distinct populations of cells in the nervous system, but their function is often analyzed only in specific isolated cellular contexts, thereby potentially leaving overarching themes in gene function undiscovered. We show here that the Caenorhabditis elegans Prop1-like homeobox gene unc-42 is expressed in 15 distinct sensory, inter- and motor neuron classes throughout the entire C. elegans nervous system. Strikingly, all 15 neuron classes expressing unc-42 are synaptically interconnected, prompting us to investigate whether unc-42 controls the functional properties of this circuit and perhaps also the assembly of these neurons into functional circuitry. We found that unc-42 defines the routes of communication between these interconnected neurons by controlling the expression of neurotransmitter pathway genes, neurotransmitter receptors, neuropeptides, and neuropeptide receptors. Anatomical analysis of unc-42 mutant animals reveals defects in axon pathfinding and synaptic connectivity, paralleled by expression defects of molecules involved in axon pathfinding, cell-cell recognition, and synaptic connectivity. We conclude that unc-42 establishes functional circuitry by acting as a terminal selector of functionally connected neuron types. We identify a number of additional transcription factors that are also expressed in synaptically connected neurons and propose that terminal selectors may also function as 'circuit organizer transcription factors' to control the assembly of functional circuitry throughout the nervous system. We hypothesize that such organizational properties of transcription factors may be reflective of not only ontogenetic, but perhaps also phylogenetic trajectories of neuronal circuit establishment.
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Affiliation(s)
- Emily G Berghoff
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Lori Glenwinkel
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Abhishek Bhattacharya
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - HaoSheng Sun
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Erdem Varol
- Department of Statistics, Zuckerman Institute, Columbia UniversityNew YorkUnited States
| | - Nicki Mohammadi
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Amelia Antone
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Yi Feng
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Ken Nguyen
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of MedicineBronxUnited States
| | - Steven J Cook
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Jordan F Wood
- Department of Biological Sciences, University at Buffalo, The State University of New YorkBuffaloUnited States
| | - Neda Masoudi
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Cyril C Cros
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Yasmin H Ramadan
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
| | - Denise M Ferkey
- Department of Biological Sciences, University at Buffalo, The State University of New YorkBuffaloUnited States
| | - David H Hall
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of MedicineBronxUnited States
| | - Oliver Hobert
- Department of Biological Sciences, Columbia University, Howard Hughes Medical InstituteNew YorkUnited States
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42
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Emmons SW, Yemini E, Zimmer M. Methods for analyzing neuronal structure and activity in Caenorhabditis elegans. Genetics 2021; 218:6303616. [PMID: 34151952 DOI: 10.1093/genetics/iyab072] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Accepted: 04/20/2021] [Indexed: 11/12/2022] Open
Abstract
The model research animal Caenorhabditis elegans has unique properties making it particularly advantageous for studies of the nervous system. The nervous system is composed of a stereotyped complement of neurons connected in a consistent manner. Here, we describe methods for studying nervous system structure and function. The transparency of the animal makes it possible to visualize and identify neurons in living animals with fluorescent probes. These methods have been recently enhanced for the efficient use of neuron-specific reporter genes. Because of its simple structure, for a number of years, C. elegans has been at the forefront of connectomic studies defining synaptic connectivity by electron microscopy. This field is burgeoning with new, more powerful techniques, and recommended up-to-date methods are here described that encourage the possibility of new work in C. elegans. Fluorescent probes for single synapses and synaptic connections have allowed verification of the EM reconstructions and for experimental approaches to synapse formation. Advances in microscopy and in fluorescent reporters sensitive to Ca2+ levels have opened the way to observing activity within single neurons across the entire nervous system.
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Affiliation(s)
- Scott W Emmons
- Department of Genetics and Dominick Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 1041, USA
| | - Eviatar Yemini
- Department of Biological Sciences, Howard Hughes Medical Institute, Columbia University, New York, NY 10027, USA
| | - Manuel Zimmer
- Department of Neuroscience and Developmental Biology, University of Vienna, Vienna 1090, Austria and.,Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Vienna 1030, Austria
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43
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Mark B, Lai SL, Zarin AA, Manning L, Pollington HQ, Litwin-Kumar A, Cardona A, Truman JW, Doe CQ. A developmental framework linking neurogenesis and circuit formation in the Drosophila CNS. eLife 2021; 10:67510. [PMID: 33973523 PMCID: PMC8139831 DOI: 10.7554/elife.67510] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 05/10/2021] [Indexed: 01/02/2023] Open
Abstract
The mechanisms specifying neuronal diversity are well characterized, yet it remains unclear how or if these mechanisms regulate neural circuit assembly. To address this, we mapped the developmental origin of 160 interneurons from seven bilateral neural progenitors (neuroblasts) and identify them in a synapse-scale TEM reconstruction of the Drosophila larval central nervous system. We find that lineages concurrently build the sensory and motor neuropils by generating sensory and motor hemilineages in a Notch-dependent manner. Neurons in a hemilineage share common synaptic targeting within the neuropil, which is further refined based on neuronal temporal identity. Connectome analysis shows that hemilineage-temporal cohorts share common connectivity. Finally, we show that proximity alone cannot explain the observed connectivity structure, suggesting hemilineage/temporal identity confers an added layer of specificity. Thus, we demonstrate that the mechanisms specifying neuronal diversity also govern circuit formation and function, and that these principles are broadly applicable throughout the nervous system.
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Affiliation(s)
- Brandon Mark
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
| | - Sen-Lin Lai
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
| | - Aref Arzan Zarin
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
| | - Laurina Manning
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
| | - Heather Q Pollington
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
| | - Ashok Litwin-Kumar
- Mortimer B Zuckerman Mind Brain Behavior Institute, Department of Neuroscience, Columbia University, New York, United States
| | - Albert Cardona
- Janelia Research Campus, Howard Hughes Medical Institute, MRC Laboratory of Molecular Biology, Department of Physiology, Development & Neuroscience, University of Cambridge, Cambridge, United Kingdom
| | - James W Truman
- Janelia Research Campus, Howard Hughes Medical Institute, Friday Harbor Laboratories, University of Washington, Friday Harbor, United States
| | - Chris Q Doe
- Institute of Neuroscience, Howard Hughes Medical Institute, University of Oregon, Eugene, United States
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44
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Brittin CA, Cook SJ, Hall DH, Emmons SW, Cohen N. A multi-scale brain map derived from whole-brain volumetric reconstructions. Nature 2021; 591:105-110. [DOI: 10.1038/s41586-021-03284-x] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2020] [Accepted: 01/25/2021] [Indexed: 12/16/2022]
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