1
|
Huo J, Xu T, Liu Q, Polat M, Kumar S, Zhang X, Leifer AM, Wen Q. Hierarchical behavior control by a single class of interneurons. Proc Natl Acad Sci U S A 2024; 121:e2410789121. [PMID: 39531495 PMCID: PMC11588054 DOI: 10.1073/pnas.2410789121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 09/20/2024] [Indexed: 11/16/2024] Open
Abstract
Animal behavior is organized into nested temporal patterns that span multiple timescales. This behavior hierarchy is believed to arise from a hierarchical neural architecture: Neurons near the top of the hierarchy are involved in planning, selecting, initiating, and maintaining motor programs, whereas those near the bottom of the hierarchy act in concert to produce fine spatiotemporal motor activity. In Caenorhabditis elegans, behavior on a long timescale emerges from ordered and flexible transitions between different behavioral states, such as forward, reversal, and turn. On a short timescale, different parts of the animal body coordinate fast rhythmic bending sequences to produce directional movements. Here, we show that Sublateral Anterior A (SAA), a class of interneurons that enable cross-communication between dorsal and ventral head motor neurons, play a dual role in shaping behavioral dynamics on different timescales. On a short timescale, SAA regulate and stabilize rhythmic bending activity during forward movements. On a long timescale, the same neurons suppress spontaneous reversals and facilitate reversal termination by inhibiting Ring Interneuron M (RIM), an integrating neuron that helps maintain a behavioral state. These results suggest that feedback from a lower-level cell assembly to a higher-level command center is essential for bridging behavioral dynamics at different levels.
Collapse
Affiliation(s)
- Jing Huo
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei230027, China
- Department of Histology and Embryology, School of Basic Medical Sciences, Shandong Second Medical University, Weifang261053, China
| | - Tianqi Xu
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei230027, China
- Deep Space Exploration Laboratory, Hefei230088, China
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei230026, China
| | - Qi Liu
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei230027, China
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei230026, China
| | - Mahiber Polat
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei230027, China
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei230026, China
| | - Sandeep Kumar
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ08540
| | - Xiaoqian Zhang
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei230027, China
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei230026, China
| | - Andrew M. Leifer
- Princeton Neuroscience Institute, Princeton University, Princeton, NJ08540
- Department of Physics, Princeton University, Princeton, NJ08540
| | - Quan Wen
- Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei230027, China
- Deep Space Exploration Laboratory, Hefei230088, China
- Center for Integrative Imaging, Hefei National Laboratory for Physical Sciences at the Microscale, University of Science and Technology of China, Hefei230026, China
| |
Collapse
|
2
|
Poole RJ, Flames N, Cochella L. Neurogenesis in Caenorhabditis elegans. Genetics 2024; 228:iyae116. [PMID: 39167071 PMCID: PMC11457946 DOI: 10.1093/genetics/iyae116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2024] [Accepted: 06/24/2024] [Indexed: 08/23/2024] Open
Abstract
Animals rely on their nervous systems to process sensory inputs, integrate these with internal signals, and produce behavioral outputs. This is enabled by the highly specialized morphologies and functions of neurons. Neuronal cells share multiple structural and physiological features, but they also come in a large diversity of types or classes that give the nervous system its broad range of functions and plasticity. This diversity, first recognized over a century ago, spurred classification efforts based on morphology, function, and molecular criteria. Caenorhabditis elegans, with its precisely mapped nervous system at the anatomical level, an extensive molecular description of most of its neurons, and its genetic amenability, has been a prime model for understanding how neurons develop and diversify at a mechanistic level. Here, we review the gene regulatory mechanisms driving neurogenesis and the diversification of neuron classes and subclasses in C. elegans. We discuss our current understanding of the specification of neuronal progenitors and their differentiation in terms of the transcription factors involved and ensuing changes in gene expression and chromatin landscape. The central theme that has emerged is that the identity of a neuron is defined by modules of gene batteries that are under control of parallel yet interconnected regulatory mechanisms. We focus on how, to achieve these terminal identities, cells integrate information along their developmental lineages. Moreover, we discuss how neurons are diversified postembryonically in a time-, genetic sex-, and activity-dependent manner. Finally, we discuss how the understanding of neuronal development can provide insights into the evolution of neuronal diversity.
Collapse
Affiliation(s)
- Richard J Poole
- Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK
| | - Nuria Flames
- Developmental Neurobiology Unit, Instituto de Biomedicina de Valencia IBV-CSIC, Valencia 46012, Spain
| | - Luisa Cochella
- Department of Molecular Biology and Genetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| |
Collapse
|
3
|
Harel Y, Nasser RA, Stern S. Mapping the developmental structure of stereotyped and individual-unique behavioral spaces in C. elegans. Cell Rep 2024; 43:114683. [PMID: 39196778 PMCID: PMC11422485 DOI: 10.1016/j.celrep.2024.114683] [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: 01/28/2024] [Revised: 05/31/2024] [Accepted: 08/09/2024] [Indexed: 08/30/2024] Open
Abstract
Developmental patterns of behavior are variably organized in time and among different individuals. However, long-term behavioral diversity was previously studied using pre-defined behavioral parameters, representing a limited fraction of the full individuality structure. Here, we continuously extract ∼1.2 billion body postures of ∼2,200 single C. elegans individuals throughout their full development time to create a complete developmental atlas of stereotyped and individual-unique behavioral spaces. Unsupervised inference of low-dimensional movement modes of each single individual identifies a dynamic developmental trajectory of stereotyped behavioral spaces and exposes unique behavioral trajectories of individuals that deviate from the stereotyped patterns. Moreover, classification of behavioral spaces within tens of neuromodulatory and environmentally perturbed populations shows plasticity in the temporal structures of stereotyped behavior and individuality. These results present a comprehensive atlas of continuous behavioral dynamics across development time and a general framework for unsupervised dissection of shared and unique developmental signatures of behavior.
Collapse
Affiliation(s)
- Yuval Harel
- Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel
| | - Reemy Ali Nasser
- Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel
| | - Shay Stern
- Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel.
| |
Collapse
|
4
|
Kramer TS, Wan FK, Pugliese SM, Atanas AA, Hiser AW, Luo J, Bueno E, Flavell SW. Neural Sequences Underlying Directed Turning in C. elegans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.11.607076. [PMID: 39149398 PMCID: PMC11326294 DOI: 10.1101/2024.08.11.607076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/17/2024]
Abstract
Complex behaviors like navigation rely on sequenced motor outputs that combine to generate effective movement. The brain-wide organization of the circuits that integrate sensory signals to select and execute appropriate motor sequences is not well understood. Here, we characterize the architecture of neural circuits that control C. elegans olfactory navigation. We identify error-correcting turns during navigation and use whole-brain calcium imaging and cell-specific perturbations to determine their neural underpinnings. These turns occur as motor sequences accompanied by neural sequences, in which defined neurons activate in a stereotyped order during each turn. Distinct neurons in this sequence respond to sensory cues, anticipate upcoming turn directions, and drive movement, linking key features of this sensorimotor behavior across time. The neuromodulator tyramine coordinates these sequential brain dynamics. Our results illustrate how neuromodulation can act on a defined neural architecture to generate sequential patterns of activity that link sensory cues to motor actions.
Collapse
Affiliation(s)
- Talya S. Kramer
- Picower Institute for Learning & Memory, 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, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Sarah M. Pugliese
- 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
| | - Alex W. Hiser
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Jinyue Luo
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, 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
| | - Steven W. Flavell
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA
| |
Collapse
|
5
|
Fahoum SRH, Blitz DM. Neuropeptide modulation of bidirectional internetwork synapses. J Neurophysiol 2024; 132:184-205. [PMID: 38776457 DOI: 10.1152/jn.00149.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2024] [Revised: 05/20/2024] [Accepted: 05/21/2024] [Indexed: 05/25/2024] Open
Abstract
Oscillatory networks underlying rhythmic motor behaviors, and sensory and complex neural processing, are flexible, even in their neuronal composition. Neuromodulatory inputs enable neurons to switch participation between networks or participate in multiple networks simultaneously. Neuromodulation of internetwork synapses can both recruit and coordinate a switching neuron in a second network. We previously identified an example in which a neuron is recruited into dual-network activity via peptidergic modulation of intrinsic properties. We now ask whether the same neuropeptide also modulates internetwork synapses for internetwork coordination. The crab (Cancer borealis) stomatogastric nervous system contains two well-defined feeding-related networks (pyloric, food filtering, ∼1 Hz; gastric mill, food chewing, ∼0.1 Hz). The projection neuron MCN5 uses the neuropeptide Gly1-SIFamide to recruit the pyloric-only lateral posterior gastric (LPG) neuron into dual pyloric- plus gastric mill-timed bursting via modulation of LPG's intrinsic properties. Descending input is not required for a coordinated rhythm, thus intranetwork synapses between LPG and its second network must underlie coordination among these neurons. However, synapses between LPG and gastric mill neurons have not been documented. Using two-electrode voltage-clamp recordings, we found that graded synaptic currents between LPG and gastric mill neurons (lateral gastric, inferior cardiac, and dorsal gastric) were primarily negligible in saline, but were enhanced by Gly1-SIFamide. Furthermore, LPG and gastric mill neurons entrain each other during Gly1-SIFamide application, indicating bidirectional, functional connectivity. Thus, a neuropeptide mediates neuronal switching through parallel actions, modulating intrinsic properties for recruitment into a second network and as shown here, also modulating bidirectional internetwork synapses for coordination.NEW & NOTEWORTHY Neuromodulation can enable neurons to simultaneously coordinate with separate networks. Both recruitment into, and coordination with, a second network can occur via modulation of internetwork synapses. Alternatively, recruitment can occur via modulation of intrinsic ionic currents. We find that the same neuropeptide previously determined to modulate intrinsic currents also modulates bidirectional internetwork synapses that are typically ineffective. Thus, complementary modulatory peptide actions enable recruitment and coordination of a neuron into a second network.
Collapse
Affiliation(s)
- Savanna-Rae H Fahoum
- Department of Biology and Center for Neuroscience and Behavior, Miami University, Oxford, Ohio, United States
| | - Dawn M Blitz
- Department of Biology and Center for Neuroscience and Behavior, Miami University, Oxford, Ohio, United States
| |
Collapse
|
6
|
Sprague DY, Rusch K, Dunn RL, Borchardt JM, Ban S, Bubnis G, Chiu GC, Wen C, Suzuki R, Chaudhary S, Lee HJ, Yu Z, Dichter B, Ly R, Onami S, Lu H, Kimura KD, Yemini E, Kato S. Unifying community-wide whole-brain imaging datasets enables robust automated neuron identification and reveals determinants of neuron positioning in C. elegans. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.28.591397. [PMID: 38746302 PMCID: PMC11092512 DOI: 10.1101/2024.04.28.591397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
We develop a data harmonization approach for C. elegans volumetric microscopy data, still or video, consisting of a standardized format, data pre-processing techniques, and a set of human-in-the-loop machine learning based analysis software tools. We unify a diverse collection of 118 whole-brain neural activity imaging datasets from 5 labs, storing these and accompanying tools in an online repository called WormID (wormid.org). We use this repository to train three existing automated cell identification algorithms to, for the first time, enable accuracy in neural identification that generalizes across labs, approaching human performance in some cases. We mine this repository to identify factors that influence the developmental positioning of neurons. To facilitate communal use of this repository, we created open-source software, code, web-based tools, and tutorials to explore and curate datasets for contribution to the scientific community. This repository provides a growing resource for experimentalists, theorists, and toolmakers to (a) study neuroanatomical organization and neural activity across diverse experimental paradigms, (b) develop and benchmark algorithms for automated neuron detection, segmentation, cell identification, tracking, and activity extraction, and (c) inform models of neurobiological development and function.
Collapse
Affiliation(s)
| | - Kevin Rusch
- Department of Neurobiology, UMass Chan Medical School
| | - Raymond L. Dunn
- Department of Neurology, University of California San Francisco
| | | | - Steven Ban
- Department of Neurology, University of California San Francisco
| | - Greg Bubnis
- Department of Neurology, University of California San Francisco
| | - Grace C. Chiu
- Department of Neurology, University of California San Francisco
| | - Chentao Wen
- RIKEN Center for Biosystems Dynamics Research
| | - Ryoga Suzuki
- Graduate School of Science, Nagoya City University
| | - Shivesh Chaudhary
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology
| | - Hyun Jee Lee
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology
| | - Zikai Yu
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology
| | | | - Ryan Ly
- Scientific Data Division, Lawrence Berkeley National Laboratory
| | | | - Hang Lu
- School of Chemical and Biomolecular Engineering, Georgia Institute of Technology
| | | | | | - Saul Kato
- Department of Neurology, University of California San Francisco
| |
Collapse
|
7
|
Wang F, Liu Z, Ford SD, Deng M, Zhang W, Yang J, Palaniyappan L. Aberrant Brain Dynamics in Schizophrenia During Working Memory Task: Evidence From a Replication Functional MRI Study. Schizophr Bull 2024; 50:96-106. [PMID: 37018464 PMCID: PMC10754176 DOI: 10.1093/schbul/sbad032] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
Abstract
BACKGROUND AND HYPOTHESIS The integration of information that typifies working memory (WM) operation requires a flexible, dynamic functional relationship among brain regions. In schizophrenia, though WM capacity is prominently impaired at higher loads, the mechanistic underpinnings are unclear. As a result, we lack convincing cognitive remediation of load-dependent deficits. We hypothesize that reduced WM capacity arises from a disruption in dynamic functional connectivity when patients face cognitive demands. STUDY DESIGN We calculate the dynamic voxel-wise degree centrality (dDC) across the functional connectome in 142 patients with schizophrenia and 88 healthy controls (HCs) facing different WM loads during an n-back task. We tested associations of the altered variability in dDC and clinical symptoms and identified intermediate connectivity configurations (clustered states) across time during WM operation. These analyses were repeated in another independent dataset of 169 subjects (102 with schizophrenia). STUDY RESULTS Compared with HCs, patients showed an increased dDC variability of supplementary motor area (SMA) for the "2back vs. 0back" contrast. This instability at the SMA seen in patients correlated with increased positive symptoms and followed a limited "U-shape" pattern at rest-condition and 2 loads. In the clustering analysis, patients showed reduced centrality in the SMA, superior temporal gyrus, and putamen. These results were replicated in a constrained search in the second independent dataset. CONCLUSIONS Schizophrenia is characterized by a load-dependent reduction of stable centrality in SMA; this relates to the severity of positive symptoms, especially disorganized behaviour. Restoring SMA stability in the presence of cognitive demands may have a therapeutic effect in schizophrenia.
Collapse
Affiliation(s)
- Feiwen Wang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Zhening Liu
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Sabrina D Ford
- Robarts Research Institute, Western University, London, ON, Canada
| | - Mengjie Deng
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Wen Zhang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Jie Yang
- Department of Psychiatry, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- National Clinical Research Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Lena Palaniyappan
- Robarts Research Institute, Western University, London, ON, Canada
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, QC, Canada
- Department of Medical Biophysics, Western University, London, ON, Canada
| |
Collapse
|
8
|
Huang YC, Luo J, Huang W, Baker CM, Gomes MA, Meng B, Byrne AB, Flavell SW. A single neuron in C. elegans orchestrates multiple motor outputs through parallel modes of transmission. Curr Biol 2023; 33:4430-4445.e6. [PMID: 37769660 PMCID: PMC10860333 DOI: 10.1016/j.cub.2023.08.088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 07/24/2023] [Accepted: 08/30/2023] [Indexed: 10/03/2023]
Abstract
Animals generate a wide range of highly coordinated motor outputs, which allows them to execute purposeful behaviors. Individual neurons in the circuits that generate behaviors have a remarkable capacity for flexibility as they exhibit multiple axonal projections, transmitter systems, and modes of neural activity. How these multi-functional properties of neurons enable the generation of adaptive behaviors remains unknown. Here, we show that the HSN neuron in C. elegans evokes multiple motor programs over different timescales to enable a suite of behavioral changes during egg laying. Using HSN activity perturbations and in vivo calcium imaging, we show that HSN acutely increases egg laying and locomotion while also biasing the animals toward low-speed dwelling behavior over minutes. The acute effects of HSN on egg laying and high-speed locomotion are mediated by separate sets of HSN transmitters and different HSN axonal compartments. The long-lasting effects on dwelling are mediated in part by HSN release of serotonin, which is taken up and re-released by NSM, another serotonergic neuron class that directly evokes dwelling. Our results show how the multi-functional properties of a single neuron allow it to induce a coordinated suite of behaviors and also reveal that neurons can borrow serotonin from one another to control behavior.
Collapse
Affiliation(s)
- Yung-Chi Huang
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Jinyue Luo
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Wenjia Huang
- Department of Neurobiology, UMass Chan Medical School, Worcester, MA 01655, USA
| | - Casey M Baker
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Matthew A Gomes
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Bohan Meng
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Alexandra B Byrne
- Department of Neurobiology, UMass Chan Medical School, Worcester, MA 01655, USA
| | - Steven W Flavell
- Picower Institute for Learning & Memory, Department of Brain & Cognitive Sciences, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
| |
Collapse
|
9
|
Tang LTH, Lee GA, Cook SJ, Ho J, Potter CC, Bülow HE. Anatomical restructuring of a lateralized neural circuit during associative learning by asymmetric insulin signaling. Curr Biol 2023; 33:3835-3850.e6. [PMID: 37591249 PMCID: PMC10639090 DOI: 10.1016/j.cub.2023.07.041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 07/18/2023] [Accepted: 07/20/2023] [Indexed: 08/19/2023]
Abstract
Studies of neuronal connectivity in model organisms, i.e., of their connectomes, have been instrumental in dissecting the structure-function relationship of nervous systems. However, the limited sample size of these studies has impeded analyses into how variation of connectivity across populations may influence circuit architecture and behavior. Moreover, little is known about how experiences induce changes in circuit architecture. Here, we show that an asymmetric salt-sensing circuit in the nematode Caenorhabditis elegans exhibits variation that predicts the animals' salt preferences and undergoes restructuring during salt associative learning. Naive worms memorize and prefer the salt concentration they experience in the presence of food through a left-biased neural network architecture. However, animals conditioned at elevated salt concentrations change this left-biased network to a right-biased network. This change in circuit architecture occurs through the addition of new synapses in response to asymmetric, paracrine insulin signaling. Therefore, experience-dependent changes in an animal's neural connectome are induced by insulin signaling and are fundamental to learning and behavior.
Collapse
Affiliation(s)
- Leo T H Tang
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA.
| | - Garrett A Lee
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Steven J Cook
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Jacquelin Ho
- Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Cassandra C Potter
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Hannes E Bülow
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Dominick P. Purpura Department of Neuroscience, Albert Einstein College of Medicine, Bronx, NY 10461, USA.
| |
Collapse
|
10
|
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.
Collapse
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.
| |
Collapse
|
11
|
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: 15] [Impact Index Per Article: 15.0] [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.
Collapse
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.
| |
Collapse
|
12
|
Migliori ML, Goya ME, Lamberti ML, Silva F, Rota R, Bénard C, Golombek DA. Caenorhabditis elegans as a Promising Model Organism in Chronobiology. J Biol Rhythms 2023; 38:131-147. [PMID: 36680418 DOI: 10.1177/07487304221143483] [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] [Indexed: 01/22/2023]
Abstract
Circadian rhythms represent an adaptive feature, ubiquitously found in nature, which grants living beings the ability to anticipate daily variations in their environment. They have been found in a multitude of organisms, ranging from bacteria to fungi, plants, and animals. Circadian rhythms are generated by endogenous clocks that can be entrained daily by environmental cycles such as light and temperature. The molecular machinery of circadian clocks includes a transcriptional-translational feedback loop that takes approximately 24 h to complete. Drosophila melanogaster has been a model organism of choice to understand the molecular basis of circadian clocks. However, alternative animal models are also being adopted, each offering their respective experimental advantages. The nematode Caenorhabditis elegans provides an excellent model for genetics and neuro-behavioral studies, which thanks to its ease of use and manipulation, as well as availability of genetic data and mutant strains, is currently used as a novel model for circadian research. Here, we aim to evaluate C. elegans as a model for chronobiological studies, focusing on its strengths and weaknesses while reviewing the available literature. Possible zeitgebers (including light and temperature) are also discussed. Determining the molecular bases and the neural circuitry involved in the central pacemaker of the C. elegans' clock will contribute to the understanding of its circadian system, becoming a novel model organism for the study of diseases due to alterations of the circadian cycle.
Collapse
Affiliation(s)
- María Laura Migliori
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Bernal, Argentina
| | - María Eugenia Goya
- European Institute for the Biology of Aging, University Medical Center Groningen, Groningen, the Netherlands
| | | | - Francisco Silva
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Bernal, Argentina
| | - Rosana Rota
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Bernal, Argentina
| | - Claire Bénard
- Department of Biological Sciences, CERMO-FC Research Center, Universite du Québec à Montréal, Montreál, QC, Canada
| | - Diego Andrés Golombek
- Departamento de Ciencia y Tecnología, Universidad Nacional de Quilmes, Bernal, Argentina
- Universidad de San Andrés, Victoria, Argentina
| |
Collapse
|
13
|
Davis K, Mitchell C, Weissenfels O, Bai J, Raizen DM, Ailion M, Topalidou I. G protein-coupled receptor kinase-2 (GRK-2) controls exploration through neuropeptide signaling in Caenorhabditis elegans. PLoS Genet 2023; 19:e1010613. [PMID: 36652499 PMCID: PMC9886303 DOI: 10.1371/journal.pgen.1010613] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Revised: 01/30/2023] [Accepted: 01/12/2023] [Indexed: 01/19/2023] Open
Abstract
Animals alter their behavior in manners that depend on environmental conditions as well as their developmental and metabolic states. For example, C. elegans is quiescent during larval molts or during conditions of satiety. By contrast, worms enter an exploration state when removed from food. Sensory perception influences movement quiescence (defined as a lack of body movement), as well as the expression of additional locomotor states in C. elegans that are associated with increased or reduced locomotion activity, such as roaming (exploration behavior) and dwelling (local search). Here we find that movement quiescence is enhanced, and exploration behavior is reduced in G protein-coupled receptor kinase grk-2 mutant animals. grk-2 was previously shown to act in chemosensation, locomotion, and egg-laying behaviors. Using neuron-specific rescuing experiments, we show that GRK-2 acts in multiple ciliated chemosensory neurons to control exploration behavior. grk-2 acts in opposite ways from the cGMP-dependent protein kinase gene egl-4 to control movement quiescence and exploration behavior. Analysis of mutants with defects in ciliated sensory neurons indicates that grk-2 and the cilium-structure mutants act in the same pathway to control exploration behavior. We find that GRK-2 controls exploration behavior in an opposite manner from the neuropeptide receptor NPR-1 and the neuropeptides FLP-1 and FLP-18. Finally, we show that secretion of the FLP-1 neuropeptide is negatively regulated by GRK-2 and that overexpression of FLP-1 reduces exploration behavior. These results define neurons and molecular pathways that modulate movement quiescence and exploration behavior.
Collapse
Affiliation(s)
- Kristen Davis
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Center for Excellence in Environmental Toxicology (CEET), Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Department of Neuroscience, Vickie and Jack Farber Institute of Neuroscience, Thomas Jefferson University, Philadelphia, Pennsylvania, United States of America
| | - Christo Mitchell
- Department of Biochemistry, University of Washington, Seattle, Washington, United States of America
| | - Olivia Weissenfels
- Department of Biochemistry, University of Washington, Seattle, Washington, United States of America
| | - Jihong Bai
- Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - David M. Raizen
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
- Chronobiology and Sleep Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, United States of America
| | - Michael Ailion
- Department of Biochemistry, University of Washington, Seattle, Washington, United States of America
| | - Irini Topalidou
- Department of Biochemistry, University of Washington, Seattle, Washington, United States of America
- Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| |
Collapse
|
14
|
Preusser F, Neuschulz A, Junker JP, Rajewsky N, Preibisch S. Long-term imaging reveals behavioral plasticity during C. elegans dauer exit. BMC Biol 2022; 20:277. [PMID: 36514066 DOI: 10.1186/s12915-022-01471-4] [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: 06/16/2022] [Accepted: 11/18/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND During their lifetime, animals must adapt their behavior to survive in changing environments. This ability requires the nervous system to undergo adjustments at distinct temporal scales, from short-term dynamic changes in expression of neurotransmitters and receptors to longer-term growth, spatial and connectivity reorganization, while integrating external stimuli. The nematode Caenorhabditis elegans provides a model of nervous system plasticity, in particular its dauer exit decision. Under unfavorable conditions, larvae will enter the non-feeding and non-reproductive stress-resistant dauer stage and adapt their behavior to cope with the harsh new environment, with active reversal under improved conditions leading to resumption of reproductive development. However, how different environmental stimuli regulate the exit decision mechanism and thereby drive the larva's behavioral change is unknown. To fill this gap and provide insights on behavioral changes over extended periods of time, we developed a new open hardware method for long-term imaging (12h) of C. elegans larvae. RESULTS Our WormObserver platform comprises open hardware and software components for video acquisition, automated processing of large image data (> 80k images/experiment) and data analysis. We identified dauer-specific behavioral motifs and characterized the behavioral trajectory of dauer exit in different environments and genetic backgrounds to identify key decision points and stimuli promoting dauer exit. Combining long-term behavioral imaging with transcriptomics data, we find that bacterial ingestion triggers a change in neuropeptide gene expression to establish post-dauer behavior. CONCLUSIONS Taken together, we show how a developing nervous system can robustly integrate environmental changes activate a developmental switch and adapt the organism's behavior to a new environment. WormObserver is generally applicable to other research questions within and beyond the C. elegans field, having a modular and customizable character and allowing assessment of behavioral plasticity over longer periods.
Collapse
Affiliation(s)
- Friedrich Preusser
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 10115, Berlin, Germany. .,Institute for Biology, Humboldt University of Berlin, 10099, Berlin, Germany.
| | - Anika Neuschulz
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 10115, Berlin, Germany.,Institute for Biology, Humboldt University of Berlin, 10099, Berlin, Germany
| | - Jan Philipp Junker
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 10115, Berlin, Germany
| | - Nikolaus Rajewsky
- Berlin Institute for Medical Systems Biology (BIMSB), Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), 10115, Berlin, Germany
| | - Stephan Preibisch
- Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA, 20147, USA.
| |
Collapse
|
15
|
McLachlan IG, Kramer TS, Dua M, DiLoreto EM, Gomes MA, Dag U, Srinivasan J, Flavell SW. Diverse states and stimuli tune olfactory receptor expression levels to modulate food-seeking behavior. eLife 2022; 11:e79557. [PMID: 36044259 PMCID: PMC9433090 DOI: 10.7554/elife.79557] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Accepted: 08/19/2022] [Indexed: 12/24/2022] Open
Abstract
Animals must weigh competing needs and states to generate adaptive behavioral responses to the environment. Sensorimotor circuits are thus tasked with integrating diverse external and internal cues relevant to these needs to generate context-appropriate behaviors. However, the mechanisms that underlie this integration are largely unknown. Here, we show that a wide range of states and stimuli converge upon a single Caenorhabditis elegans olfactory neuron to modulate food-seeking behavior. Using an unbiased ribotagging approach, we find that the expression of olfactory receptor genes in the AWA olfactory neuron is influenced by a wide array of states and stimuli, including feeding state, physiological stress, and recent sensory cues. We identify odorants that activate these state-dependent olfactory receptors and show that altered expression of these receptors influences food-seeking and foraging. Further, we dissect the molecular and neural circuit pathways through which external sensory information and internal nutritional state are integrated by AWA. This reveals a modular organization in which sensory and state-related signals arising from different cell types in the body converge on AWA and independently control chemoreceptor expression. The synthesis of these signals by AWA allows animals to generate sensorimotor responses that reflect the animal's overall state. Our findings suggest a general model in which sensory- and state-dependent transcriptional changes at the sensory periphery modulate animals' sensorimotor responses to meet their ongoing needs and states.
Collapse
Affiliation(s)
- Ian G McLachlan
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Talya S Kramer
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
- MIT Biology Graduate Program, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Malvika Dua
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Elizabeth M DiLoreto
- Department of Biology and Biotechnology, Worcester Polytechnic InstituteWorcesterUnited States
| | - Matthew A Gomes
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Ugur Dag
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| | - Jagan Srinivasan
- Department of Biology and Biotechnology, Worcester Polytechnic InstituteWorcesterUnited States
| | - Steven W Flavell
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of TechnologyCambridgeUnited States
| |
Collapse
|
16
|
Gao J, Qian J, Ma N, Han J, Cui F, chen N, Tu Y. Protective Effects of Polydatin on Reproductive Injury Induced by Ionizing Radiation. Dose Response 2022; 20:15593258221107511. [PMID: 35783236 PMCID: PMC9244944 DOI: 10.1177/15593258221107511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The reproductive system is vulnerable to ionizing radiation, which is a hot research topic at present. We tested the effect of polydatin on spermatocytes(GC-1 cells) after X-ray irradiation. The reproductive damage model of C.elegans was established by 60Coγ-ray, and the protective effect of polydatin on reproductive damage caused by ionizing radiation was evaluated. We quantified the ROS levels of GC-1 cells and C.elegans after irradiation with polydatin and evaluated the anti-apoptosis effect of polydatin at proper concentration. Differential genes of C.elegans reproductive damage were screened out from transcriptome sequencing results and comparable GEO datasets. It was proved that 100μM polydatin significantly reduced the apoptosis of GC-1 cells induced by 2 Gy X-ray. In addition, the longevity, reproductive capacity, germ cell apoptosis and spawning and hatching capacity of polydatin were tested. The results showed that 100 μM polydatin content significantly increased the influence of 50 Gy 60Coγ-ray on reproductive capacity of C.elegans. Quantitative analysis of mRNA and protein levels of apoptosis-related genes and reproductive-related genes by qRT-PCR and Western blotcon firmed that polydatin with appropriate dosage had good protective effects on reproductive damage caused by radiation, which laid a foundation for the application research of polydatin in radiation protection.
Collapse
Affiliation(s)
- Jin Gao
- State Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, China
- Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Suzhou, China
| | - Jincheng Qian
- Department of Nuclear Medicine, First Affiliated Hospital of Soochow University, Suzhou, China
| | - Nan Ma
- The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jianfang Han
- State Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, China
- Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Suzhou, China
| | - Fengmei Cui
- State Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, China
- Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Suzhou, China
| | - Na chen
- State Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, China
- Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Suzhou, China
| | - Yu Tu
- State Key Laboratory of Radiation Medicine and Protection, School of Radiation Medicine and Protection, Soochow University, Suzhou, China
- Collaborative Innovation Center of Radiation Medicine of Jiangsu Higher Education Institutions, Suzhou, China
| |
Collapse
|