1
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He J, Phan BN, Kerkhoff WG, Alikaya A, Hong T, Brull OR, Fredericks JM, Sedorovitz M, Srinivasan C, Leone MJ, Wirfel OM, Brown A, Dauby S, Tittle RK, Lin MK, Hooks BM, Bostan AC, Gharbawie OA, Byrne LC, Pfenning AR, Stauffer WR. Machine learning identification of enhancers in the rhesus macaque genome. Neuron 2025; 113:1548-1561.e8. [PMID: 40403706 DOI: 10.1016/j.neuron.2025.04.030] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2024] [Revised: 03/28/2025] [Accepted: 04/28/2025] [Indexed: 05/24/2025]
Abstract
Nonhuman primate (NHP) neuroanatomy and cognitive complexity make NHPs ideal models to study human neurobiology and disease. However, NHP circuit-function investigations are limited by the availability of molecular reagents that are effective in NHPs. This calls for reagent development approaches that prioritize NHPs. Therefore, we derived enhancers from the NHP genome. We defined cell-type-specific open chromatin regions (OCRs) in single-cell data from rhesus macaques. We trained machine-learning models to rank those OCRs according to their potential as cell-type-specific enhancers for cells in the dorsolateral prefrontal cortex (DLPFC). We packaged the top-ranked layer-3-pyramidal-neuron enhancer into AAV and injected it into the macaque DLPFC. Expression was mostly restricted to layers 2 and 3 and confirmed with light-driven activation of channelrhodopsin. These results provide a crucial tool for studying the causal functions of DLPFC and provide a roadmap for optimized gene delivery in primates.
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Affiliation(s)
- Jing He
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - BaDoi N Phan
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA; University of Pittsburgh-Carnegie Mellon University Medical Scientist Training Program, Pittsburgh, PA 15213, USA
| | - Willa G Kerkhoff
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Aydin Alikaya
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Tao Hong
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA; Program in Neural Computation, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Olivia R Brull
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - J Megan Fredericks
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Morgan Sedorovitz
- Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Chaitanya Srinivasan
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Michael J Leone
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA; University of Pittsburgh-Carnegie Mellon University Medical Scientist Training Program, Pittsburgh, PA 15213, USA
| | - Olivia M Wirfel
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Ashley Brown
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA
| | - Samuel Dauby
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Rachel K Tittle
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Meng K Lin
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Bryan M Hooks
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Andreea C Bostan
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Omar A Gharbawie
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Leah C Byrne
- Department of Ophthalmology, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Andreas R Pfenning
- Computational Biology Department, Carnegie Mellon University, Pittsburgh, PA 15213, USA; Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA 15213, USA.
| | - William R Stauffer
- Department of Neurobiology, University of Pittsburgh, Pittsburgh, PA 15213, USA.
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2
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Li C, Gong FX, Yang Z, Fu X, Shi H, Sun X, Zhang X, Xiao R. Alternative splicing categorizes organ development by stage and reveals unique human splicing variants linked to neuromuscular disorders. J Biol Chem 2025; 301:108542. [PMID: 40288647 DOI: 10.1016/j.jbc.2025.108542] [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: 09/18/2024] [Revised: 04/15/2025] [Accepted: 04/17/2025] [Indexed: 04/29/2025] Open
Abstract
Alternative splicing (AS) diversifies protein expression and contributes to species-specific differences in organ development. Here, we focused on stage-specific splicing variants and their correlation with disease in humans compared to mice during brain and heart development. Temporal transcriptomic analysis revealed that splicing factors (SFs) can accurately classify organ developmental stages, and 5 SFs were identified specifically upregulated in humans during organogenesis. Additionally, inter-stage splicing variations were identified across analogous human and mouse developmental stages. Developmentally dynamic alternative splicing genes (devASGs) were enriched in various neurodevelopmental disorders in both species, with the most significant changes observed in human newborn brain and 16 weeks post-conception heart. Intriguingly, diseases specifically enriched in humans were primarily associated with neuro-muscular dysfunction, and human-specific neuromuscular devASGs were linked to mannose glycosylation and ciliary motility. These findings highlight the significance of SFs and AS events in organogenesis and inform the selection of appropriate models for translational research.
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Affiliation(s)
- Chen Li
- Research Center of Plastic Surgery Hospital, CAMS Key Laboratory of Tissue and Organ Regeneration, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fu-Xing Gong
- Research Center of Plastic Surgery Hospital, CAMS Key Laboratory of Tissue and Organ Regeneration, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhigang Yang
- Research Center of Plastic Surgery Hospital, CAMS Key Laboratory of Tissue and Organ Regeneration, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xin Fu
- Research Center of Plastic Surgery Hospital, CAMS Key Laboratory of Tissue and Organ Regeneration, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hang Shi
- Research Center of Plastic Surgery Hospital, CAMS Key Laboratory of Tissue and Organ Regeneration, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xuejian Sun
- Research Center of Plastic Surgery Hospital, CAMS Key Laboratory of Tissue and Organ Regeneration, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaorong Zhang
- State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Haihe Laboratory of Cell Ecosystem, CAMS Key Laboratory for Prevention and Control of Hematological Disease Treatment Related Infection, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin, China.
| | - Ran Xiao
- Research Center of Plastic Surgery Hospital, CAMS Key Laboratory of Tissue and Organ Regeneration, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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Morito T, Watamura N, Sasaguri H, Tomita T, Higuchi M, Okano H, Sasaki E, Saido TC. Experimental basis for generating nonhuman primate models of frontotemporal dementia and Alzheimer's disease. J Alzheimers Dis 2025; 104:955-962. [PMID: 40025729 DOI: 10.1177/13872877251321116] [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] [Indexed: 03/04/2025]
Abstract
To our knowledge, no reports have described nonhuman primate (NHP) models of frontotemporal dementia with Parkinsonism linked to chromosome 17 (FTDP-17) that do not depend on an overexpression paradigm. Based on our recent success in generating single human MAPT knock-in mouse models of FTDP-17, we describe the experimental basis for generating knock-in marmoset models of FTDP-17. In addition, successful generation of mutant PSEN1 knock-in marmoset models lacking exon 9 (PSEN1-Δ9) of Alzheimer's disease (AD) indicates that we will be able to reconstitute two major pathological features of AD, i.e., amyloid plaques and neurofibrillary tangles, in an accelerated manner by combining these models.
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Affiliation(s)
| | - Naoto Watamura
- RIKEN Center for Brain Science, Wako, Japan
- UK Dementia Research Institute, University College London, London, UK
| | | | - Taisuke Tomita
- Graduate School of Pharmaceutical Sciences, The University of Tokyo, Tokyo, Japan
| | - Makoto Higuchi
- Institute for Quantum Medical Science, National Institutes for Quantum Science and Technology, Chiba, Japan
| | - Hideyuki Okano
- RIKEN Center for Brain Science, Wako, Japan
- Department of Physiology, School of Medicine, Keio University, Tokyo, Japan
| | - Erika Sasaki
- Central Institute for Experimental Medicine and Life Science, Kawasaki, Kanagawa, Japan
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Amly W, Chen CY, Onoe H, Isa T. Different properties of successful and error saccades in marmosets. Neurosci Res 2025; 213:60-71. [PMID: 39920999 DOI: 10.1016/j.neures.2025.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2024] [Revised: 01/11/2025] [Accepted: 02/02/2025] [Indexed: 02/10/2025]
Abstract
Various oculomotor tasks have been used to study eye movements, cognitive control, attention, and neurological disorders. Typically, analysis focuses on successful trials, where the saccade lands very close to the intended target, in both humans or non-human primates (NHPs). Error trials, in which the saccade fails to land on the intended target, are often excluded from these analyses. In this study, we hypothesized that saccades contain information that can predict whether they will result in success or not. We collected data from common marmosets performing the gap saccade task and the oculomotor delayed response task. Successful saccades in both tasks were characterized by higher peak velocities, shorter durations, and shorter latencies compared to errant saccades, regardless of whether the amplitudes were matched or not. These results were further validated using a generalized linear model, with saccade velocity, duration, and latency as predictors. The model demonstrated high accuracy in distinguishing between behavioural outcomes. Our findings suggest that the likelihood of a saccadic eye movement leading to a successful outcome may be predetermined, potentially reflecting the interaction between cognitive processes and saccade programming.
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Affiliation(s)
- Wajd Amly
- Division of Neurobiology and Physiology, Department of Neuroscience, Graduate School of Medicine, Kyoto University, Kyoto, Japan; Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Chih-Yang Chen
- Division of Neurobiology and Physiology, Department of Neuroscience, Graduate School of Medicine, Kyoto University, Kyoto, Japan; Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Hirotaka Onoe
- Kobe Gakuin University, Faculty of Pharmaceutical Science, Laboratory of Neuropsychopharmacology, Kobe, Japan
| | - Tadashi Isa
- Division of Neurobiology and Physiology, Department of Neuroscience, Graduate School of Medicine, Kyoto University, Kyoto, Japan; Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan; Human Brain Research Centre, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
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5
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Vanderlip CR, Jutras ML, Asch PA, Zhu SY, Lerma MN, Buffalo EA, Glavis-Bloom C. Parallel patterns of age-related working memory impairment in marmosets and macaques. Aging (Albany NY) 2025; 17:778-797. [PMID: 40131878 PMCID: PMC11984434 DOI: 10.18632/aging.206225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2024] [Accepted: 03/06/2025] [Indexed: 03/27/2025]
Abstract
As humans age, some experience cognitive impairment while others do not. When impairment does occur, it is not expressed uniformly across cognitive domains and varies in severity across individuals. Translationally relevant model systems are critical for understanding the neurobiological drivers of this variability, which is essential to uncovering the mechanisms underlying the brain's susceptibility to the effects of aging. As such, non-human primates (NHPs) are particularly important due to shared behavioral, neuroanatomical, and age-related neuropathological features with humans. For many decades, macaque monkeys have served as the primary NHP model for studying the neurobiology of cognitive aging. More recently, the common marmoset has emerged as an advantageous model for this work due to its short lifespan that facilitates longitudinal studies. Despite their growing popularity as a model, whether marmosets exhibit patterns of age-related cognitive impairment comparable to those observed in macaques and humans remains unexplored. To address this major limitation for the development and evaluation of the marmoset as a model of cognitive aging, we directly compared working memory ability as a function of age in macaques and marmosets on the identical task. We also implemented varying delays to further tax working memory capacity. Our findings demonstrate that marmosets and macaques exhibit remarkably similar age-related working memory deficits, with macaques performing better than marmosets on longer delays. These results highlight the similarities and differences between the two most commonly used NHP models and support the value of the marmoset as a model for cognitive aging research within the neuroscience community.
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Affiliation(s)
- Casey R. Vanderlip
- Systems Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Megan L. Jutras
- Department of Neurobiology and Biophysics, University of Washington School of Medicine, Seattle, WA 98195, USA
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Payton A. Asch
- Systems Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
| | - Stephanie Y. Zhu
- Department of Neurobiology and Biophysics, University of Washington School of Medicine, Seattle, WA 98195, USA
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Monica N. Lerma
- Department of Neurobiology and Biophysics, University of Washington School of Medicine, Seattle, WA 98195, USA
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Elizabeth A. Buffalo
- Department of Neurobiology and Biophysics, University of Washington School of Medicine, Seattle, WA 98195, USA
- Washington National Primate Research Center, University of Washington, Seattle, WA 98195, USA
| | - Courtney Glavis-Bloom
- Systems Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA 92037, USA
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6
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Dragoi T, Sugihara H, Le NM, Adam E, Sharma J, Feng G, Desimone R, Sur M. Global to local influences on temporal expectation in marmosets and humans. Curr Biol 2025; 35:1095-1106.e7. [PMID: 39970916 DOI: 10.1016/j.cub.2025.01.052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2024] [Revised: 09/04/2024] [Accepted: 01/24/2025] [Indexed: 02/21/2025]
Abstract
Marmosets are emerging rapidly as experimental models for studying the neural bases of cognition and, importantly, for modeling disorders of human cognition, but many aspects of their mental attributes remain to be characterized. When judging elapsed time, humans implicitly use prior information to predict upcoming events and reduce perceptual and decision-making uncertainty. An influential model of temporal expectation is the hazard rate model, which posits the likelihood of an event occurring in the future, provided it has not occurred already. Here, we report that marmosets trained on a reaction time task acquire the hazard rate model of expectation, consistent with the global task structure. The model emerges progressively with learning but unexpectedly continues to be modified by local contingencies, as demonstrated by a serial effect of trial duration on responses. The combined effects of global and local task structure are well described by a multiple regression model and computationally by Bayesian updating of the hazard function. Parallel experiments in human subjects similarly demonstrate global followed by local influences on reaction times and temporal expectation. Thus, in both marmosets and humans, task history and local structure continuously update task-specific responses, surprisingly at the expense of optimal responses after the competent acquisition of an internal model.
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Affiliation(s)
- Tudor Dragoi
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Graduate Program for Neuroscience, Boston University, Boston, MA 02215, USA
| | - Hiroki Sugihara
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Nhat Minh Le
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Elie Adam
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Anaesthesia, Harvard Medical School, Boston, MA 02115, USA
| | - Jitendra Sharma
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Guoping Feng
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Robert Desimone
- McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Mriganka Sur
- Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
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7
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Andrei AR, Dragoi V. Optogenetic modulation of long-range cortical circuits in awake nonhuman primates. Nat Protoc 2025:10.1038/s41596-024-01123-7. [PMID: 39905198 DOI: 10.1038/s41596-024-01123-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 12/02/2024] [Indexed: 02/06/2025]
Abstract
Causal control of short- and long-range projections between networks is necessary to study complex cognitive processes and cortical computations. Neural circuits can be studied via optogenetic approaches, which provide excellent genetic and temporal control and electrophysiological recordings. However, in nonhuman primates (NHPs), these approaches are commonly performed at a single location, missing out on the potential to test connections between separate networks. We have recently developed an approach for optogenetic manipulation in NHPs which targets intra- and interareal cortical projections. Here we describe the combination of optogenetic stimulation with standard chamber-based electrophysiological recordings in awake NHPs to monitor and manipulate both short- and long-range feedforward and feedback circuits. We describe the injection of viral constructs, the simultaneous electrophysiological recordings with the optical stimulation of neurons at various cortical distances and the evaluation of gene expression using a focal biopsy technique. We focus on details that are specific to NHP preparations, such as the precise targeting of injection sites, choosing appropriate viral constructs and considerations for behavioral measures. When combined with laminar electrode configurations (to functionally identify cortical layers) and complex cognitive behavioral tasks, our approach can be used to investigate an array of systems neuroscience questions, such as the role of feedback circuits in attention and the role of lateral connections in contrast normalization. The procedure requires 2-3 active days and 45 waiting days to transduce selected neural circuits and several weeks to complete experiments. The procedure is appropriate for users with expertise in in vivo, awake electrophysiology with NHPs.
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Affiliation(s)
- Ariana R Andrei
- Center for Neural Systems Restoration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX, USA
| | - Valentin Dragoi
- Center for Neural Systems Restoration, Department of Neurosurgery, Houston Methodist Research Institute, Houston, TX, USA.
- Neuroengineering Initiative, Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.
- Brain and Mind Research Institute, Department of Physiology and Biophysics, Weill Cornell Medical College, New York, NY, USA.
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8
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Campos LJ, Drzewiecki CM, Fox AS. Insights into the Neurobiology of Behavioral Inhibition from Nonhuman Primate Models. Curr Top Behav Neurosci 2024. [PMID: 39739174 DOI: 10.1007/7854_2024_561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2025]
Abstract
Children with extreme behavioral inhibition (BI) are at a significantly greater risk to develop anxiety disorders later in life. We and others have identified similar early-life temperamental BI in nonhuman primates (NHPs), including rhesus monkeys. NHP models of BI provide a unique opportunity to study the neurobiology of BI in a species that shares biological, developmental, and socioemotional similarities with humans. Rhesus monkey models have identified a distributed brain circuit that includes the central extended amygdala (EAc) as being critical for the genesis of BI. By leveraging multimodal neuroimaging, brain lesions, RNA-sequencing, and viral vector manipulations in rhesus monkeys, these studies have identified specific brain regions, genetic factors, and molecular mechanisms that causally contribute to BI. Here, we discuss these findings from NHPs and how they fit into a translational framework that can contribute to our understanding of the neural circuits that give rise to the risk to develop anxiety and depressive disorders.
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Affiliation(s)
- Lillian J Campos
- Department of Psychology, University of California, Davis, CA, USA
- California National Primate Research Center, University of California, Davis, CA, USA
| | - Carly M Drzewiecki
- California National Primate Research Center, University of California, Davis, CA, USA
| | - Andrew S Fox
- Department of Psychology, University of California, Davis, CA, USA.
- California National Primate Research Center, University of California, Davis, CA, USA.
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9
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Oh S, Jekal J, Won J, Lim KS, Jeon CY, Park J, Yeo HG, Kim YG, Lee YH, Ha LJ, Jung HH, Yea J, Lee H, Ha J, Kim J, Lee D, Song S, Son J, Yu TS, Lee J, Lee S, Lee J, Kim BH, Choi JW, Rah JC, Song YM, Jeong JW, Choi HJ, Xu S, Lee Y, Jang KI. A stealthy neural recorder for the study of behaviour in primates. Nat Biomed Eng 2024:10.1038/s41551-024-01280-w. [PMID: 39516303 DOI: 10.1038/s41551-024-01280-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Accepted: 10/08/2024] [Indexed: 11/16/2024]
Abstract
By monitoring brain neural signals, neural recorders allow for the study of neurological mechanisms underlying specific behavioural and cognitive states. However, the large brain volumes of non-human primates and their extensive range of uncontrolled movements and inherent wildness make it difficult to carry out covert and long-term recording and analysis of deep-brain neural signals. Here we report the development and performance of a stealthy neural recorder for the study of naturalistic behaviours in non-human primates. The neural recorder includes a fully implantable wireless and battery-free module for the recording of local field potentials and accelerometry data in real time, a flexible 32-electrode neural probe with a resorbable insertion shuttle, and a repeater coil-based wireless-power-transfer system operating at the body scale. We used the device to record neurobehavioural data for over 1 month in a freely moving monkey and leveraged the recorded data to train an artificial intelligence model for the classification of the animals' eating behaviours.
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Affiliation(s)
- Saehyuck Oh
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Janghwan Jekal
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Jinyoung Won
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Republic of Korea
| | - Kyung Seob Lim
- Futuristic Animal Resource and Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Republic of Korea
| | - Chang-Yeop Jeon
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Republic of Korea
| | - Junghyung Park
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Republic of Korea
| | - Hyeon-Gu Yeo
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Republic of Korea
- KRIBB School of Bioscience, Korea National University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Yu Gyeong Kim
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Republic of Korea
- KRIBB School of Bioscience, Korea National University of Science and Technology (UST), Daejeon, Republic of Korea
| | - Young Hee Lee
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
- Wide River Institute of Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Leslie Jaesun Ha
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
- Wide River Institute of Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Han Hee Jung
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Junwoo Yea
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Hyeokjun Lee
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Jeongdae Ha
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Jinmo Kim
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Doyoung Lee
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Soojeong Song
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Jieun Son
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Tae Sang Yu
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Jungmin Lee
- Hertie Institute for Clinical Brain Research, International Max Planck Research School and University of Tuebingen, Tuebingen, Germany
| | - Sanghoon Lee
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Jaehong Lee
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Bong Hoon Kim
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Ji-Woong Choi
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
| | - Jong-Cheol Rah
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea
- Korea Brain Research Institute (KBRI), Daegu, Republic of Korea
| | - Young Min Song
- School of Electrical Engineering and Computer Science, Gwangju Institute of Science and Technology (GIST), Gwangju, Republic of Korea
| | - Jae-Woong Jeong
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Hyung Jin Choi
- Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Republic of Korea
- Wide River Institute of Immunology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Sheng Xu
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Youngjeon Lee
- National Primate Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Cheongju, Republic of Korea.
- KRIBB School of Bioscience, Korea National University of Science and Technology (UST), Daejeon, Republic of Korea.
| | - Kyung-In Jang
- Department of Robotics and Mechatronics Engineering, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
- Brain Engineering Convergence Research Center, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
- Department of Electrical Engineering and Computer Science, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
- Department of Brain Sciences, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
- Korea Brain Research Institute (KBRI), Daegu, Republic of Korea.
- Artificial Intelligence Major in Department of Interdisciplinary Studies, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
- Institute of Next-generation Semiconductor Convergence Technology, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
- Sensorium Institute, Daegu Gyeongbuk Institute of Science and Technology (DGIST), Daegu, Republic of Korea.
- ENSIDE Corporation, Daegu, Republic of Korea.
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10
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Burette AC, Vihma H, Smith AL, Ozarkar SS, Bennett J, Amaral DG, Philpot BD. Transcription factor 4 expression in the developing non-human primate brain: a comparative analysis with the mouse brain. Front Neuroanat 2024; 18:1478689. [PMID: 39502395 PMCID: PMC11534587 DOI: 10.3389/fnana.2024.1478689] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2024] [Accepted: 10/04/2024] [Indexed: 11/08/2024] Open
Abstract
Transcription factor 4 (TCF4) has been implicated in a range of neuropsychiatric disorders, including major depressive disorder, bipolar disorder, and schizophrenia. Mutations or deletions in TCF4 cause Pitt-Hopkins syndrome (PTHS), a rare neurodevelopmental disorder. A detailed understanding of its spatial expression across the developing brain is necessary for comprehending TCF4 biology and, by extension, to develop effective treatments for TCF4-associated disorders. However, most current knowledge is derived from mouse models, which are invaluable for preclinical studies but may not fully capture the complexities of human neuropsychiatric phenotypes. This study compared TCF4 expression in the developing mouse brain to its regional and cellular expression patterns in normal prenatal, neonatal, and young adult rhesus macaque brains, a species more relevant to human neurodevelopment. While the general developmental expression of TCF4 is largely conserved between macaques and mice, we saw several interspecies differences. Most notably, a distinct layered pattern of TCF4 expression was clear in the developing macaque neocortex but largely absent in the mouse brain. High TCF4 expression was seen in the inner dentate gyrus of adult mice but not in macaques. Conversely, TCF4 expression was higher in the adult macaque striatum compared to the mouse striatum. Further research is needed to show the significance of these interspecies differences. Still, they underscore the importance of integrating rodent and primate studies to comprehensively understand TCF4 function and its implications for human disorders. Moreover, the primate-specific expression patterns of TCF4 will inform genetic and other therapeutic strategies to treat TCF4-associated disorders.
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Affiliation(s)
- Alain C. Burette
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Hanna Vihma
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Audrey L. Smith
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Siddhi S. Ozarkar
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jeff Bennett
- Department of Psychiatry and Behavioral Sciences, MIND Institute, University of California, Davis, Davis, CA, United States
- California National Primate Research Center, University of California, Davis, Davis, CA, United States
| | - David G. Amaral
- Department of Psychiatry and Behavioral Sciences, MIND Institute, University of California, Davis, Davis, CA, United States
- California National Primate Research Center, University of California, Davis, Davis, CA, United States
| | - Benjamin D. Philpot
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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11
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Zhong T, Wang Y, Xu X, Wu X, Liang S, Ning Z, Wang L, Niu Y, Li G, Zhang Y. A brain subcortical segmentation tool based on anatomy attentional fusion network for developing macaques. Comput Med Imaging Graph 2024; 116:102404. [PMID: 38870599 DOI: 10.1016/j.compmedimag.2024.102404] [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: 01/31/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 06/15/2024]
Abstract
Magnetic Resonance Imaging (MRI) plays a pivotal role in the accurate measurement of brain subcortical structures in macaques, which is crucial for unraveling the complexities of brain structure and function, thereby enhancing our understanding of neurodegenerative diseases and brain development. However, due to significant differences in brain size, structure, and imaging characteristics between humans and macaques, computational tools developed for human neuroimaging studies often encounter obstacles when applied to macaques. In this context, we propose an Anatomy Attentional Fusion Network (AAF-Net), which integrates multimodal MRI data with anatomical constraints in a multi-scale framework to address the challenges posed by the dynamic development, regional heterogeneity, and age-related size variations of the juvenile macaque brain, thus achieving precise subcortical segmentation. Specifically, we generate a Signed Distance Map (SDM) based on the initial rough segmentation of the subcortical region by a network as an anatomical constraint, providing comprehensive information on positions, structures, and morphology. Then we construct AAF-Net to fully fuse the SDM anatomical constraints and multimodal images for refined segmentation. To thoroughly evaluate the performance of our proposed tool, over 700 macaque MRIs from 19 datasets were used in this study. Specifically, we employed two manually labeled longitudinal macaque datasets to develop the tool and complete four-fold cross-validations. Furthermore, we incorporated various external datasets to demonstrate the proposed tool's generalization capabilities and promise in brain development research. We have made this tool available as an open-source resource at https://github.com/TaoZhong11/Macaque_subcortical_segmentation for direct application.
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Affiliation(s)
- Tao Zhong
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Ya Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, USA
| | - Xiaotong Xu
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Xueyang Wu
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Shujun Liang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Zhenyuan Ning
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, USA
| | - Yuyu Niu
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, China
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, USA.
| | - Yu Zhang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, China.
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12
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Ning C, Wu X, Zhao X, Lu Z, Yao X, Zhou T, Yi L, Sun Y, Wu S, Liu Z, Huang X, Gao L, Liu J. Epigenomic landscapes during prefrontal cortex development and aging in rhesus. Natl Sci Rev 2024; 11:nwae213. [PMID: 39183748 PMCID: PMC11342245 DOI: 10.1093/nsr/nwae213] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2023] [Revised: 06/07/2024] [Accepted: 06/09/2024] [Indexed: 08/27/2024] Open
Abstract
The prefrontal cortex (PFC) is essential for higher-level cognitive functions. How epigenetic dynamics participates in PFC development and aging is largely unknown. Here, we profiled epigenomic landscapes of rhesus monkey PFCs from prenatal to aging stages. The dynamics of chromatin states, including higher-order chromatin structure, chromatin interaction and histone modifications are coordinated to regulate stage-specific gene transcription, participating in distinct processes of neurodevelopment. Dramatic changes of epigenetic signals occur around the birth stage. Notably, genes involved in neuronal cell differentiation and layer specification are pre-configured by bivalent promoters. We identified a cis-regulatory module and the transcription factors (TFs) associated with basal radial glia development, which was associated with large brain size in primates. These TFs include GLI3, CREB5 and SOX9. Interestingly, the genes associated with the basal radial glia (bRG)-associated cis-element module, such as SRY and SOX9, are enriched in sex differentiation. Schizophrenia-associated single nucleotide polymorphisms are more enriched in super enhancers (SEs) than typical enhancers, suggesting that SEs play an important role in neural network wiring. A cis-regulatory element of DBN1 is identified, which is critical for neuronal cell proliferation and synaptic neuron differentiation. Notably, the loss of distal chromatin interaction and H3K27me3 signal are hallmarks of PFC aging, which are associated with abnormal expression of aging-related genes and transposon activation, respectively. Collectively, our findings shed light on epigenetic mechanisms underlying primate brain development and aging.
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Affiliation(s)
- Chao Ning
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xi Wu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- Division of HIV/AIDS and Sex-Transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC), State Key Laboratory of Drug Regulatory Science, Beijing 102629, China
| | - Xudong Zhao
- Key Laboratory of Animal Models and Human Disease Mechanisms of Chinese Academy of Sciences, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Zongyang Lu
- School of Life Science and Technology, Shanghai Tech University, Shanghai 201210, China
| | - Xuelong Yao
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- GuangzhouNvwa Life Technology Co., Ltd, Guangzhou 510535, China
| | - Tao Zhou
- Shenzhen Neher Neural Plasticity Laboratory, CAS Key Laboratory of Brain Connectome and Manipulation, The Brain Cognition and Brain Disease Institute, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Lizhi Yi
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yaoyu Sun
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shuaishuai Wu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhenbo Liu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Xingxu Huang
- School of Life Science and Technology, Shanghai Tech University, Shanghai 201210, China
- Zhejiang Provincial Key Laboratory of Pancreatic Disease, The First Affiliated Hospital, and Institute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Lei Gao
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
| | - Jiang Liu
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
- Key Laboratory of Epigenetic Regulation and Intervention, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
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13
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Vanderlip CR, Jutras ML, Asch PA, Zhu SY, Lerma MN, Buffalo EA, Glavis-Bloom C. Parallel patterns of cognitive aging in marmosets and macaques. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.22.604411. [PMID: 39091859 PMCID: PMC11291085 DOI: 10.1101/2024.07.22.604411] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 08/04/2024]
Abstract
As humans age, some experience cognitive impairment while others do not. When impairment does occur, it is not expressed uniformly across cognitive domains and varies in severity across individuals. Translationally relevant model systems are critical for understanding the neurobiological drivers of this variability, which is essential to uncovering the mechanisms underlying the brain's susceptibility to the effects of aging. As such, non-human primates are particularly important due to shared behavioral, neuroanatomical, and age-related neuropathological features with humans. For many decades, macaque monkeys have served as the primary non-human primate model for studying the neurobiology of cognitive aging. More recently, the common marmoset has emerged as an advantageous model for this work due to its short lifespan that facilitates longitudinal studies. Despite their growing popularity as a model, whether marmosets exhibit patterns of age-related cognitive impairment comparable to those observed in macaques and humans remains unexplored. To address this major limitation for the development and evaluation of the marmoset as a model of cognitive aging, we directly compared working memory ability as a function of age in macaques and marmosets on the identical working memory task. Our results demonstrate that marmosets and macaques exhibit remarkably similar age-related working memory deficits, highlighting the value of the marmoset as a model for cognitive aging research within the neuroscience community.
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Affiliation(s)
- Casey R. Vanderlip
- Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, USA
| | - Megan L. Jutras
- Department of Physiology and Biophysics, University of Washington School of Medicine, Seattle, WA, USA
- Washington National Primate Research Center, Seattle, WA, USA
| | - Payton A. Asch
- Systems Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
| | - Stephanie Y. Zhu
- Department of Biology, University of Washington, Seattle, WA, USA
| | - Monica N. Lerma
- Washington National Primate Research Center, Seattle, WA, USA
- Department of Brain Science, Allen Institute for Brain Science, Seattle, WA, USA
| | - Elizabeth A. Buffalo
- Department of Physiology and Biophysics, University of Washington School of Medicine, Seattle, WA, USA
- Washington National Primate Research Center, Seattle, WA, USA
| | - Courtney Glavis-Bloom
- Systems Neurobiology Laboratory, Salk Institute for Biological Studies, La Jolla, CA, USA
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14
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Zhong T, Wu X, Liang S, Ning Z, Wang L, Niu Y, Yang S, Kang Z, Feng Q, Li G, Zhang Y. nBEST: Deep-learning-based non-human primates Brain Extraction and Segmentation Toolbox across ages, sites and species. Neuroimage 2024; 295:120652. [PMID: 38797384 DOI: 10.1016/j.neuroimage.2024.120652] [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: 02/07/2024] [Revised: 05/21/2024] [Accepted: 05/22/2024] [Indexed: 05/29/2024] Open
Abstract
Accurate processing and analysis of non-human primate (NHP) brain magnetic resonance imaging (MRI) serves an indispensable role in understanding brain evolution, development, aging, and diseases. Despite the accumulation of diverse NHP brain MRI datasets at various developmental stages and from various imaging sites/scanners, existing computational tools designed for human MRI typically perform poor on NHP data, due to huge differences in brain sizes, morphologies, and imaging appearances across species, sites, and ages, highlighting the imperative for NHP-specialized MRI processing tools. To address this issue, in this paper, we present a robust, generic, and fully automated computational pipeline, called non-human primates Brain Extraction and Segmentation Toolbox (nBEST), whose main functionality includes brain extraction, non-cerebrum removal, and tissue segmentation. Building on cutting-edge deep learning techniques by employing lifelong learning to flexibly integrate data from diverse NHP populations and innovatively constructing 3D U-NeXt architecture, nBEST can well handle structural NHP brain MR images from multi-species, multi-site, and multi-developmental-stage (from neonates to the elderly). We extensively validated nBEST based on, to our knowledge, the largest assemblage dataset in NHP brain studies, encompassing 1,469 scans with 11 species (e.g., rhesus macaques, cynomolgus macaques, chimpanzees, marmosets, squirrel monkeys, etc.) from 23 independent datasets. Compared to alternative tools, nBEST outperforms in precision, applicability, robustness, comprehensiveness, and generalizability, greatly benefiting downstream longitudinal, cross-sectional, and cross-species quantitative analyses. We have made nBEST an open-source toolbox (https://github.com/TaoZhong11/nBEST) and we are committed to its continual refinement through lifelong learning with incoming data to greatly contribute to the research field.
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Affiliation(s)
- Tao Zhong
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Xueyang Wu
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Shujun Liang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Zhenyuan Ning
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Li Wang
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Yuyu Niu
- Yunnan Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, China
| | - Shihua Yang
- College of Veterinary Medicine, South China Agricultural University, Guangzhou, China
| | - Zhuang Kang
- Department of Radiology, The Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Qianjin Feng
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China
| | - Gang Li
- Department of Radiology and Biomedical Research Imaging Center, University of North Carolina at Chapel Hill, Chapel Hill, USA.
| | - Yu Zhang
- School of Biomedical Engineering, Guangdong Provincial Key Laboratory of Medical Image Processing and Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Southern Medical University, Guangzhou, China.
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15
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Gonzalez Ramirez C, Salvador SG, Patel RKR, Clark S, Miller NW, James LM, Ringelberg NW, Simon JM, Bennett J, Amaral DG, Burette AC, Philpot BD. Regional and cellular organization of the autism-associated protein UBE3A/E6AP and its antisense transcript in the brain of the developing rhesus monkey. Front Neuroanat 2024; 18:1410791. [PMID: 38873093 PMCID: PMC11169893 DOI: 10.3389/fnana.2024.1410791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Accepted: 05/17/2024] [Indexed: 06/15/2024] Open
Abstract
Angelman syndrome (AS) is a neurogenetic disorder caused by mutations or deletions in the maternally-inherited UBE3A allele, leading to a loss of UBE3A protein expression in neurons. The paternally-inherited UBE3A allele is epigenetically silenced in neurons during development by a noncoding transcript (UBE3A-ATS). The absence of neuronal UBE3A results in severe neurological symptoms, including speech and language impairments, intellectual disability, and seizures. While no cure exists, therapies aiming to restore UBE3A function-either by gene addition or by targeting UBE3A-ATS-are under development. Progress in developing these treatments relies heavily on inferences drawn from mouse studies about the function of UBE3A in the human brain. To aid translational efforts and to gain an understanding of UBE3A and UBE3A-ATS biology with greater relevance to human neurodevelopmental contexts, we investigated UBE3A and UBE3A-ATS expression in the developing brain of the rhesus macaque, a species that exhibits complex social behaviors, resembling aspects of human behavior to a greater degree than mice. Combining immunohistochemistry and in situ hybridization, we mapped UBE3A and UBE3A-ATS regional and cellular expression in normal prenatal, neonatal, and adolescent rhesus macaque brains. We show that key hallmarks of UBE3A biology, well-known in rodents, are also present in macaques, and suggest paternal UBE3A silencing in neurons-but not glial cells-in the macaque brain, with onset between gestational day 48 and 100. These findings support proposals that early-life, perhaps even prenatal, intervention is optimal for overcoming the maternal allele loss of UBE3A linked to AS.
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Affiliation(s)
- Chavely Gonzalez Ramirez
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Sarah G. Salvador
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Ridthi Kartik Rekha Patel
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Sarah Clark
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Noah W. Miller
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Lucas M. James
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Nicholas W. Ringelberg
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Jeremy M. Simon
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
- Department of Data Science, Dana-Farber Cancer Institute, Boston, MA, United States
| | - Jeffrey Bennett
- Department of Psychiatry and Behavioral Sciences, MIND Institute, Davis, CA, United States
- California National Primate Research Center, University of California, Davis, CA, United States
| | - David G. Amaral
- Department of Psychiatry and Behavioral Sciences, MIND Institute, Davis, CA, United States
- California National Primate Research Center, University of California, Davis, CA, United States
| | - Alain C. Burette
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Benjamin D. Philpot
- Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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16
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Sun Y, Zhong M, Xu N, Zhang X, Sun H, Wang Y, Lu Y, Nie Y, Li Q, Sun Q, Jiang J, Tang YC, Chang HC. High-frequency neural activity dysregulation is associated with sleep and psychiatric disorders in BMAL1-deficient animal models. iScience 2024; 27:109381. [PMID: 38500822 PMCID: PMC10946332 DOI: 10.1016/j.isci.2024.109381] [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: 09/25/2023] [Revised: 01/29/2024] [Accepted: 02/27/2024] [Indexed: 03/20/2024] Open
Abstract
Sleep disturbance led by BMAL1-deficiency has been recognized both in rodent and non-human primate models. Yet it remained unclear how their diurnal brain oscillations were affected upon BMAL1 ablation and what caused the discrepancy in the quantity of sleep between the two species. Here, we investigated diurnal electroencephalographs of BMAL1-deficient mice and cynomolgus monkeys at young adult age and uncovered a shared defect of dysregulated high-frequency oscillations by Kullback-Leibler divergence analysis. We found beta and gamma oscillations were significantly disturbed in a day versus night manner in BMAL1-deficient monkeys, while in mice the beta band difference was less evident. Notably, the dysregulation of beta oscillations was particularly associated with psychiatric behaviors in BMAL1-deficient monkeys, including the occurrence of self-injuring and delusion-like actions. As such psychiatric phenotypes were challenging to uncover in rodent models, our results offered a unique method to study the correlation between circadian clock dysregulation and psychiatric disorders.
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Affiliation(s)
- Yu Sun
- Lingang Laboratory, Shanghai 201203, China
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Mingzhu Zhong
- Lingang Laboratory, Shanghai 201203, China
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Niannian Xu
- Lingang Laboratory, Shanghai 201203, China
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | | | - Yan Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yong Lu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yanhong Nie
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Qing Li
- Lingang Laboratory, Shanghai 201203, China
| | - Qiang Sun
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jian Jiang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | | | - Hung-Chun Chang
- Lingang Laboratory, Shanghai 201203, China
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai 201210, China
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17
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Henriques C, Lopes MM, Silva AC, Lobo DD, Badin RA, Hantraye P, Pereira de Almeida L, Nobre RJ. Viral-based animal models in polyglutamine disorders. Brain 2024; 147:1166-1189. [PMID: 38284949 DOI: 10.1093/brain/awae012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 11/26/2023] [Accepted: 12/30/2023] [Indexed: 01/30/2024] Open
Abstract
Polyglutamine disorders are a complex group of incurable neurodegenerative disorders caused by an abnormal expansion in the trinucleotide cytosine-adenine-guanine tract of the affected gene. To better understand these disorders, our dependence on animal models persists, primarily relying on transgenic models. In an effort to complement and deepen our knowledge, researchers have also developed animal models of polyglutamine disorders employing viral vectors. Viral vectors have been extensively used to deliver genes to the brain, not only for therapeutic purposes but also for the development of animal models, given their remarkable flexibility. In a time- and cost-effective manner, it is possible to use different transgenes, at varying doses, in diverse targeted tissues, at different ages, and in different species, to recreate polyglutamine pathology. This paper aims to showcase the utility of viral vectors in disease modelling, share essential considerations for developing animal models with viral vectors, and provide a comprehensive review of existing viral-based animal models for polyglutamine disorders.
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Affiliation(s)
- Carina Henriques
- Center for Neuroscience and Cell Biology (CNC), Gene and Stem Cell Therapies for the Brain Group, University of Coimbra, 3004-504 Coimbra, Portugal
- Center for Innovative Biomedicine and Biotechnology (CIBB), Vectors, Gene and Cell Therapy Group, University of Coimbra, 3004-504 Coimbra, Portugal
- ViraVector-Viral Vector for Gene Transfer Core Facility, University of Coimbra, 3004-504 Coimbra, Portugal
- Faculty of Pharmacy, University of Coimbra, 3000-548 Coimbra, Portugal
| | - Miguel M Lopes
- Center for Neuroscience and Cell Biology (CNC), Gene and Stem Cell Therapies for the Brain Group, University of Coimbra, 3004-504 Coimbra, Portugal
- Center for Innovative Biomedicine and Biotechnology (CIBB), Vectors, Gene and Cell Therapy Group, University of Coimbra, 3004-504 Coimbra, Portugal
- ViraVector-Viral Vector for Gene Transfer Core Facility, University of Coimbra, 3004-504 Coimbra, Portugal
- Institute for Interdisciplinary Research (III), University of Coimbra, 3030-789 Coimbra, Portugal
| | - Ana C Silva
- Center for Neuroscience and Cell Biology (CNC), Gene and Stem Cell Therapies for the Brain Group, University of Coimbra, 3004-504 Coimbra, Portugal
- Center for Innovative Biomedicine and Biotechnology (CIBB), Vectors, Gene and Cell Therapy Group, University of Coimbra, 3004-504 Coimbra, Portugal
- ViraVector-Viral Vector for Gene Transfer Core Facility, University of Coimbra, 3004-504 Coimbra, Portugal
- Institute for Interdisciplinary Research (III), University of Coimbra, 3030-789 Coimbra, Portugal
| | - Diana D Lobo
- Center for Neuroscience and Cell Biology (CNC), Gene and Stem Cell Therapies for the Brain Group, University of Coimbra, 3004-504 Coimbra, Portugal
- Center for Innovative Biomedicine and Biotechnology (CIBB), Vectors, Gene and Cell Therapy Group, University of Coimbra, 3004-504 Coimbra, Portugal
- ViraVector-Viral Vector for Gene Transfer Core Facility, University of Coimbra, 3004-504 Coimbra, Portugal
- Institute for Interdisciplinary Research (III), University of Coimbra, 3030-789 Coimbra, Portugal
| | - Romina Aron Badin
- CEA, DRF, Institute of Biology François Jacob, Molecular Imaging Research Center (MIRCen), 92265 Fontenay-aux-Roses, France
- CNRS, CEA, Paris-Sud University, Université Paris-Saclay, Neurodegenerative Diseases Laboratory (UMR9199), 92265 Fontenay-aux-Roses, France
| | - Philippe Hantraye
- CEA, DRF, Institute of Biology François Jacob, Molecular Imaging Research Center (MIRCen), 92265 Fontenay-aux-Roses, France
- CNRS, CEA, Paris-Sud University, Université Paris-Saclay, Neurodegenerative Diseases Laboratory (UMR9199), 92265 Fontenay-aux-Roses, France
| | - Luís Pereira de Almeida
- Center for Neuroscience and Cell Biology (CNC), Gene and Stem Cell Therapies for the Brain Group, University of Coimbra, 3004-504 Coimbra, Portugal
- Center for Innovative Biomedicine and Biotechnology (CIBB), Vectors, Gene and Cell Therapy Group, University of Coimbra, 3004-504 Coimbra, Portugal
- ViraVector-Viral Vector for Gene Transfer Core Facility, University of Coimbra, 3004-504 Coimbra, Portugal
- Faculty of Pharmacy, University of Coimbra, 3000-548 Coimbra, Portugal
| | - Rui Jorge Nobre
- Center for Neuroscience and Cell Biology (CNC), Gene and Stem Cell Therapies for the Brain Group, University of Coimbra, 3004-504 Coimbra, Portugal
- Center for Innovative Biomedicine and Biotechnology (CIBB), Vectors, Gene and Cell Therapy Group, University of Coimbra, 3004-504 Coimbra, Portugal
- ViraVector-Viral Vector for Gene Transfer Core Facility, University of Coimbra, 3004-504 Coimbra, Portugal
- Institute for Interdisciplinary Research (III), University of Coimbra, 3030-789 Coimbra, Portugal
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18
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Lemon R. The Corticospinal System and Amyotrophic Lateral Sclerosis: IFCN handbook chapter. Clin Neurophysiol 2024; 160:56-67. [PMID: 38401191 DOI: 10.1016/j.clinph.2024.02.001] [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: 08/31/2023] [Revised: 12/23/2023] [Accepted: 02/03/2024] [Indexed: 02/26/2024]
Abstract
Corticospinal neurons located in motor areas of the cerebral neocortex project corticospinal axons which synapse with the spinal network; a parallel corticobulbar system projects to the cranial motor network and to brainstem motor pathways. The primate corticospinal system has a widespread cortical origin and an extensive range of different fibre diameters, including thick, fast-conducting axons. Direct cortico-motoneuronal (CM) projections from the motor cortex to arm and hand alpha motoneurons are a recent evolutionary feature, that is well developed in dexterous primates and particularly in humans. Many of these projections originate from the caudal subdivision of area 4 ('new' M1: primary motor cortex). They arise from corticospinal neurons of varied soma size, including those with fast- and relatively slow-conducting axons. This CM system has been shown to be involved in the control of skilled movements, carried out with fractionation of the distal extremities and at low force levels. During movement, corticospinal neurons are activated quite differently from 'lower' motoneurons, and there is no simple or fixed functional relationship between a so-called 'upper' motoneuron and its target lower motoneuron. There are key differences in the organisation and function of the corticospinal and CM system in primates versus non-primates, such as rodents. These differences need to be recognized when making the choice of animal model for understanding disorders such as amyotrophic lateral sclerosis (ALS). In this neurodegenerative brain disease there is a selective loss of fast-conducting corticospinal axons, and their synaptic connections, and this is reflected in responses to non-invasive cortical stimuli and measures of cortico-muscular coherence. The loss of CM connections influencing distal limb muscles results in a differential loss of muscle strength or 'split-hand' phenotype. Importantly, there is also a unique impairment in the coordination of skilled hand tasks that require fractionation of digit movement. Scores on validated tests of skilled hand function could be used to assess disease progression.
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Affiliation(s)
- Roger Lemon
- Department of Clinical and Movement Sciences, Queen Square Institute of Neurology, UCL, London WC1N 3BG, UK.
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19
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Coop SH, Yates JL, Mitchell JF. Pre-saccadic Neural Enhancements in Marmoset Area MT. J Neurosci 2024; 44:e2034222023. [PMID: 38050176 PMCID: PMC10860570 DOI: 10.1523/jneurosci.2034-22.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 09/15/2023] [Accepted: 11/20/2023] [Indexed: 12/06/2023] Open
Abstract
Each time we make an eye movement, attention moves before the eyes, resulting in a perceptual enhancement at the target. Recent psychophysical studies suggest that this pre-saccadic attention enhances the visual features at the saccade target, whereas covert attention causes only spatially selective enhancements. While previous nonhuman primate studies have found that pre-saccadic attention does enhance neural responses spatially, no studies have tested whether changes in neural tuning reflect an automatic feature enhancement. Here we examined pre-saccadic attention using a saccade foraging task developed for marmoset monkeys (one male and one female). We recorded from neurons in the middle temporal area with peripheral receptive fields that contained a motion stimulus, which would either be the target of a saccade or a distracter as a saccade was made to another location. We established that marmosets, like macaques, show enhanced pre-saccadic neural responses for saccades toward the receptive field, including increases in firing rate and motion information. We then examined if the specific changes in neural tuning might support feature enhancements for the target. Neurons exhibited diverse changes in tuning but predominantly showed additive and multiplicative increases that were uniformly applied across motion directions. These findings confirm that marmoset monkeys, like macaques, exhibit pre-saccadic neural enhancements during saccade foraging tasks with minimal training requirements. However, at the level of individual neurons, the lack of feature-tuned enhancements is similar to neural effects reported during covert spatial attention.
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Affiliation(s)
- Shanna H Coop
- Brain and Cognitive Sciences, University of Rochester, Rochester 14627-0268, New York
- Center for Visual Science, University of Rochester, Rochester 14627-0268, New York
| | - Jacob L Yates
- Brain and Cognitive Sciences, University of Rochester, Rochester 14627-0268, New York
- Center for Visual Science, University of Rochester, Rochester 14627-0268, New York
- Department of Biology, University of Maryland College Park, College Park, Maryland, 20742-5025
| | - Jude F Mitchell
- Brain and Cognitive Sciences, University of Rochester, Rochester 14627-0268, New York
- Center for Visual Science, University of Rochester, Rochester 14627-0268, New York
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20
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Chang YT, Lee YJ, Haque M, Chang HC, Javed S, Lin YC, Cho Y, Abramovitz J, Chin G, Khamis A, Raja R, Murai KK, Huang WH. Comparative analyses of the Smith-Magenis syndrome protein RAI1 in mice and common marmoset monkeys. J Comp Neurol 2024; 532:e25589. [PMID: 38289192 DOI: 10.1002/cne.25589] [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: 04/13/2023] [Revised: 11/11/2023] [Accepted: 12/17/2023] [Indexed: 02/01/2024]
Abstract
Retinoic acid-induced 1 (RAI1) encodes a transcriptional regulator critical for brain development and function. RAI1 haploinsufficiency in humans causes a syndromic autism spectrum disorder known as Smith-Magenis syndrome (SMS). The neuroanatomical distribution of RAI1 has not been quantitatively analyzed during the development of the prefrontal cortex, a brain region critical for cognitive function and social behaviors and commonly implicated in autism spectrum disorders, including SMS. Here, we performed comparative analyses to uncover the evolutionarily convergent and divergent expression profiles of RAI1 in major cell types during prefrontal cortex maturation in common marmoset monkeys (Callithrix jacchus) and mice (Mus musculus). We found that while RAI1 in both species is enriched in neurons, the percentage of excitatory neurons that express RAI1 is higher in newborn mice than in newborn marmosets. By contrast, RAI1 shows similar neural distribution in adult marmosets and adult mice. In marmosets, RAI1 is expressed in several primate-specific cell types, including intralaminar astrocytes and MEIS2-expressing prefrontal GABAergic neurons. At the molecular level, we discovered that RAI1 forms a protein complex with transcription factor 20 (TCF20), PHD finger protein 14 (PHF14), and high mobility group 20A (HMG20A) in the marmoset brain. In vitro assays in human cells revealed that TCF20 regulates RAI1 protein abundance. This work demonstrates that RAI1 expression and protein interactions are largely conserved but with some unique expression in primate-specific cells. The results also suggest that altered RAI1 abundance could contribute to disease features in disorders caused by TCF20 dosage imbalance.
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Affiliation(s)
- Ya-Ting Chang
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Yu-Ju Lee
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Minza Haque
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Hao-Cheng Chang
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Sehrish Javed
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Yu Cheng Lin
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Yoobin Cho
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Joseph Abramovitz
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Gabriella Chin
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Asma Khamis
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Reesha Raja
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Keith K Murai
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
| | - Wei-Hsiang Huang
- Department of Neurology and Neurosurgery, Centre for Research in Neuroscience, McGill University, Montréal, Québec, Canada
- Brain Repair and Integrative Neuroscience Program, The Research Institute of the McGill University Health Centre, Montréal, Québec, Canada
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21
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Cao J, Li W, Li J, Mazid MA, Li C, Jiang Y, Jia W, Wu L, Liao Z, Sun S, Song W, Fu J, Wang Y, Lu Y, Xu Y, Nie Y, Bian X, Gao C, Zhang X, Zhang L, Shang S, Li Y, Fu L, Liu H, Lai J, Wang Y, Yuan Y, Jin X, Li Y, Liu C, Lai Y, Shi X, Maxwell PH, Xu X, Liu L, Poo M, Wang X, Sun Q, Esteban MA, Liu Z. Live birth of chimeric monkey with high contribution from embryonic stem cells. Cell 2023; 186:4996-5014.e24. [PMID: 37949056 DOI: 10.1016/j.cell.2023.10.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 07/18/2023] [Accepted: 10/03/2023] [Indexed: 11/12/2023]
Abstract
A formal demonstration that mammalian pluripotent stem cells possess preimplantation embryonic cell-like (naive) pluripotency is the generation of chimeric animals through early embryo complementation with homologous cells. Whereas such naive pluripotency has been well demonstrated in rodents, poor chimerism has been achieved in other species including non-human primates due to the inability of the donor cells to match the developmental state of the host embryos. Here, we have systematically tested various culture conditions for establishing monkey naive embryonic stem cells and optimized the procedures for chimeric embryo culture. This approach generated an aborted fetus and a live chimeric monkey with high donor cell contribution. A stringent characterization pipeline demonstrated that donor cells efficiently (up to 90%) incorporated into various tissues (including the gonads and placenta) of the chimeric monkeys. Our results have major implications for the study of primate naive pluripotency and genetic engineering of non-human primates.
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Affiliation(s)
- Jing Cao
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China; Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Wenjuan Li
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Jie Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Md Abdul Mazid
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Chunyang Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yu Jiang
- State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, and College of Veterinary Medicine, Jilin University, Changchun 130062, China
| | - Wenqi Jia
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Liang Wu
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Zhaodi Liao
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Shiyu Sun
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Weixiang Song
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Jiqiang Fu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yan Wang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yong Lu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yuting Xu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yanhong Nie
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xinyan Bian
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Changshan Gao
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Xiaotong Zhang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Liansheng Zhang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Shenshen Shang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yunpan Li
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Lixin Fu
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Hao Liu
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Junjian Lai
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China
| | - Yang Wang
- BGI-Research, Hangzhou 310030, China
| | - Yue Yuan
- BGI-Research, Hangzhou 310030, China
| | - Xin Jin
- BGI-Research, Shenzhen 518083, China; School of Medicine, South China University of Technology, Guangzhou, China
| | - Yan Li
- BGI-Research, Shenzhen 518083, China
| | | | - Yiwei Lai
- BGI-Research, Hangzhou 310030, China
| | | | - Patrick H Maxwell
- School of Clinical Medicine, University of Cambridge, Cambridge CB2 0ST, United Kingdom
| | - Xun Xu
- BGI-Research, Hangzhou 310030, China; BGI-Research, Shenzhen 518083, China; Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen 518120, China
| | | | - Muming Poo
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China; University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaolong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Qiang Sun
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Miguel A Esteban
- BGI-Research, Hangzhou 310030, China; Guangdong Provincial Key Laboratory of Stem Cells and Regenerative Medicine, CAS Key Laboratory of Regenerative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China; State Key Laboratory for Diagnosis and Treatment of Severe Zoonotic Infectious Diseases, Key Laboratory for Zoonosis Research of the Ministry of Education, Institute of Zoonosis, and College of Veterinary Medicine, Jilin University, Changchun 130062, China.
| | - Zhen Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai 200031, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China; University of Chinese Academy of Sciences, Beijing 100049, China.
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22
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Zhai R, Tong G, Li Z, Song W, Hu Y, Xu S, Wei Q, Zhang X, Li Y, Liao B, Yuan C, Fan Y, Song G, Ouyang Y, Zhang W, Tang Y, Jin M, Zhang Y, Li H, Yang Z, Lin GN, Stein DJ, Xiong ZQ, Wang Z. Rhesus monkeys exhibiting spontaneous ritualistic behaviors resembling obsessive-compulsive disorder. Natl Sci Rev 2023; 10:nwad312. [PMID: 38152386 PMCID: PMC10751879 DOI: 10.1093/nsr/nwad312] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 12/05/2023] [Accepted: 12/06/2023] [Indexed: 12/29/2023] Open
Abstract
Obsessive-compulsive disorder (OCD) is a chronic and debilitating psychiatric disorder that affects ∼2%-3% of the population globally. Studying spontaneous OCD-like behaviors in non-human primates may improve our understanding of the disorder. In large rhesus monkey colonies, we found 10 monkeys spontaneously exhibiting persistent sequential motor behaviors (SMBs) in individual-specific sequences that were repetitive, time-consuming and stable over prolonged periods. Genetic analysis revealed severely damaging mutations in genes associated with OCD risk in humans. Brain imaging showed that monkeys with SMBs had larger gray matter (GM) volumes in the left caudate nucleus and lower fractional anisotropy of the corpus callosum. The GM volume of the left caudate nucleus correlated positively with the daily duration of SMBs. Notably, exposure to a stressor (human presence) significantly increased SMBs. In addition, fluoxetine, a serotonergic medication commonly used for OCD, decreased SMBs in these monkeys. These findings provide a novel foundation for developing better understanding and treatment of OCD.
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Affiliation(s)
- Rongwei Zhai
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Lingang Laboratory, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Geya Tong
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Zheqin Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Weichen Song
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yang Hu
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Sha Xu
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Lingang Laboratory, Shanghai 200031, China
| | - Qiqi Wei
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Lingang Laboratory, Shanghai 200031, China
| | - Xiaocheng Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Lingang Laboratory, Shanghai 200031, China
| | - Yi Li
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Bingbing Liao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Chenyu Yuan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yinqing Fan
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Ge Song
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yinyin Ouyang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Wenxuan Zhang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yaqiu Tang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Minghui Jin
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Yuxian Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - He Li
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhi Yang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Guan Ning Lin
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Dan J Stein
- Translational Neuropsychiatry Unit (TNU), Department of Clinical Medicine, Aarhus University, Aarhus 8200, Denmark
| | - Zhi-Qi Xiong
- Institute of Neuroscience, State Key Laboratory of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
- Shanghai Center for Brain Science and Brain-Inspired Technology, Shanghai 201602, China
| | - Zhen Wang
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
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23
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Zhu L, Zheng D, Li R, Shen CJ, Cai R, Lyu C, Tang B, Sun H, Wang X, Ding Y, Xu B, Jia G, Li X, Gao L, Li XM. Induction of Anxiety-Like Phenotypes by Knockdown of Cannabinoid Type-1 Receptors in the Amygdala of Marmosets. Neurosci Bull 2023; 39:1669-1682. [PMID: 37368194 PMCID: PMC10603018 DOI: 10.1007/s12264-023-01081-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 03/08/2023] [Indexed: 06/28/2023] Open
Abstract
The amygdala is an important hub for regulating emotions and is involved in the pathophysiology of many mental diseases, such as depression and anxiety. Meanwhile, the endocannabinoid system plays a crucial role in regulating emotions and mainly functions through the cannabinoid type-1 receptor (CB1R), which is strongly expressed in the amygdala of non-human primates (NHPs). However, it remains largely unknown how the CB1Rs in the amygdala of NHPs regulate mental diseases. Here, we investigated the role of CB1R by knocking down the cannabinoid receptor 1 (CNR1) gene encoding CB1R in the amygdala of adult marmosets through regional delivery of AAV-SaCas9-gRNA. We found that CB1R knockdown in the amygdala induced anxiety-like behaviors, including disrupted night sleep, agitated psychomotor activity in new environments, and reduced social desire. Moreover, marmosets with CB1R-knockdown had up-regulated plasma cortisol levels. These results indicate that the knockdown of CB1Rs in the amygdala induces anxiety-like behaviors in marmosets, and this may be the mechanism underlying the regulation of anxiety by CB1Rs in the amygdala of NHPs.
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Affiliation(s)
- Lin Zhu
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Di Zheng
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Rui Li
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Chen-Jie Shen
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Ruolan Cai
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Chenfei Lyu
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Binliang Tang
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
- Rehabilitation Medicine Center, Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Department of Rehabilitation Medicine, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, 311399, China
| | - Hao Sun
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Xiaohui Wang
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Yu Ding
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
| | - Bin Xu
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Guoqiang Jia
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Xinjian Li
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China
| | - Lixia Gao
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China.
- Interdisciplinary Institute of Neuroscience and Technology, Zhejiang University School of Medicine, Hangzhou, 310029, China.
| | - Xiao-Ming Li
- Department of Neurobiology and Department of Neurology of Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310058, China.
- NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brian Medicine, Zhejiang University, Hangzhou, 310058, China.
- Center for Brain Science and Brain-Inspired Intelligence, Research Units for Emotion and Emotion Disorders, Chinese Academy of Medical Sciences, China/Guangdong-Hong Kong-Macao Greater Bay Area, Joint Institute for Genetics and Genome Medicine Between Zhejiang University and University of Toronto, Hangzhou, 310058, China.
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24
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Li L, Liu Z. Genetic Approaches for Neural Circuits Dissection in Non-human Primates. Neurosci Bull 2023; 39:1561-1576. [PMID: 37258795 PMCID: PMC10533465 DOI: 10.1007/s12264-023-01067-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 03/27/2023] [Indexed: 06/02/2023] Open
Abstract
Genetic tools, which can be used for the morphology study of specific neurons, pathway-selective connectome mapping, neuronal activity monitoring, and manipulation with a spatiotemporal resolution, have been widely applied to the understanding of complex neural circuit formation, interactions, and functions in rodents. Recently, similar genetic approaches have been tried in non-human primates (NHPs) in neuroscience studies for dissecting the neural circuits involved in sophisticated behaviors and clinical brain disorders, although they are still very preliminary. In this review, we introduce the progress made in the development and application of genetic tools for brain studies on NHPs. We also discuss the advantages and limitations of each approach and provide a perspective for using genetic tools to study the neural circuits of NHPs.
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Affiliation(s)
- Ling Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Zhen Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, 200031, China.
- Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, 200031, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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25
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Liu S, Kosugi Y. Human Brain Penetration Prediction Using Scaling Approach from Animal Machine Learning Models. AAPS J 2023; 25:86. [PMID: 37667061 DOI: 10.1208/s12248-023-00850-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 08/14/2023] [Indexed: 09/06/2023] Open
Abstract
Machine learning (ML) approaches have been applied to predicting drug pharmacokinetic properties. Previously, we predicted rat unbound brain-to-plasma ratio (Kpuu,brain) by ML models. In this study, we aimed to predict human Kpuu,brain through animal ML models. First, we re-evaluated ML models for rat Kpuu,brain prediction by using trendy open-source packages. We then developed ML models for monkey Kpuu,brain prediction. Leave-one-out cross validation was utilized to rationally build models using a relatively small dataset. After establishing the monkey and rat ML models, human Kpuu,brain prediction was achieved by implementing the animal models considering appropriate scaling methods. Mechanistic NeuroPK models for the identical monkey and human dataset were treated as the criteria for comparison. Results showed that rat Kpuu,brain predictivity was successfully replicated. The optimal ML model for monkey Kpuu,brain prediction was superior to the NeuroPK model, where accuracy within 2-fold error was 78% (R2 = 0.76). For human Kpuu,brain prediction, rat model using relative expression factor (REF), scaled transporter efflux ratios (ERs), and monkey model using in vitro ERs can provide comparable predictivity to the NeuroPK model, where accuracy within 2-fold error was 71% and 64% (R2 = 0.30 and 0.52), respectively. We demonstrated that ML models can deliver promising Kpuu,brain prediction with several advantages: (1) predict reasonable animal Kpuu,brain; (2) prospectively predict human Kpuu,brain from animal models; and (3) can skip expensive monkey studies for human prediction by using the rat model. As a result, ML models can be a powerful tool for drug Kpuu,brain prediction in the discovery stage.
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Affiliation(s)
- Siyu Liu
- Drug Metabolism & Pharmacokinetics Research Laboratories, Preclinical & Translational Sciences, Research, Takeda Pharmaceutical Company Limited, Shonan Health Innovation Park, 26-1, Muraoka-Higashi 2-Chome, Fujisawa, Kanagawa, 251-8555, Japan.
| | - Yohei Kosugi
- Drug Metabolism & Pharmacokinetics Research Laboratories, Preclinical & Translational Sciences, Research, Takeda Pharmaceutical Company Limited, Shonan Health Innovation Park, 26-1, Muraoka-Higashi 2-Chome, Fujisawa, Kanagawa, 251-8555, Japan
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26
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Lorents A, Colin ME, Bjerke IE, Nougaret S, Montelisciani L, Diaz M, Verschure P, Vezoli J. Human Brain Project Partnering Projects Meeting: Status Quo and Outlook. eNeuro 2023; 10:ENEURO.0091-23.2023. [PMID: 37669867 PMCID: PMC10481639 DOI: 10.1523/eneuro.0091-23.2023] [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: 03/19/2023] [Revised: 08/03/2023] [Accepted: 08/04/2023] [Indexed: 09/07/2023] Open
Abstract
As the European Flagship Human Brain Project (HBP) ends in September 2023, a meeting dedicated to the Partnering Projects (PPs), a collective of independent research groups that partnered with the HBP, was held on September 4-7, 2022. The purpose of this meeting was to allow these groups to present their results, reflect on their collaboration with the HBP and discuss future interactions with the European Research Infrastructure (RI) EBRAINS that has emerged from the HBP. In this report, we share the tour-de-force that the Partnering Projects that were present in the meeting have made in furthering knowledge concerning various aspects of Brain Research with the HBP. We describe briefly major achievements of the HBP Partnering Projects in terms of a systems-level understanding of the functional architecture of the brain and its possible emulation in artificial systems. We then recapitulate open discussions with EBRAINS representatives about the evolution of EBRAINS as a sustainable Research Infrastructure for the Partnering Projects after the HBP, and also for the wider scientific community.
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Affiliation(s)
| | | | - Ingvild Elise Bjerke
- Neural Systems Laboratory, Institute of Basic Medical Sciences, University of Oslo, Oslo 0372, Norway
| | - Simon Nougaret
- Institut de Neurosciences de la Timone, Unité Mixte de Recherche 7289, Aix Marseille Université, Centre National de la Recherche Scientifique, Marseille 13005, France
| | - Luca Montelisciani
- Cognitive and Systems Neuroscience Group, Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam 1098XH, The Netherlands
| | - Marissa Diaz
- Institute for Advanced Simulation (IAS), Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH, Jülich 52428, Germany
| | - Paul Verschure
- Donders Center for Neuroscience (DCN-FNWI), Radboud University, Nijmegen 6500HD, The Netherlands
| | - Julien Vezoli
- Ernst Strügmann Institute (ESI) for Neuroscience in Cooperation with Max Planck Society, Frankfurt am Main 60528, Germany
- Institut National de la Santé et de la Recherche Médicale Unité 1208, Stem Cell and Brain Research Institute, Université Claude Bernard Lyon 1, Bron 69500, France
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27
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Xu L, Wang D, Zhao L, Yang Z, Liu X, Li X, Yuan T, Wang Y, Huang T, Bian N, He Y, Chen X, Tian B, Liu Z, Luo F, Si W, Gao G, Ji W, Niu Y, Wei J. C9orf72 poly(PR) aggregation in nucleus induces ALS/FTD-related neurodegeneration in cynomolgus monkeys. Neurobiol Dis 2023; 184:106197. [PMID: 37328037 DOI: 10.1016/j.nbd.2023.106197] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/27/2023] [Accepted: 06/08/2023] [Indexed: 06/18/2023] Open
Abstract
Poly(PR) is a dipeptide repeat protein comprising proline and arginine residues. It is one of the translational product of expanded G4C2 repeats in the C9orf72 gene, and its accumulation is contributing to the neuropathogenesis of C9orf72-associated amyotrophic lateral sclerosis and/or frontotemporal dementia (C9-ALS/FTD). In this study, we demonstrate that poly(PR) protein alone is sufficient to induce neurodegeneration related to ALS/FTD in cynomolgus monkeys. By delivering poly(PR) via AAV, we observed that the PR proteins were located within the nucleus of infected cells. The expression of (PR)50 protein, consisting of 50 PR repeats, led to increased loss of cortical neurons, cytoplasmic lipofuscin, and gliosis in the brain, as well as demyelination and loss of ChAT positive neurons in the spinal cord of monkeys. While, these pathologies were not observed in monkeys expressing (PR)5, a protein comprising only 5 PR repeats. Furthermore, the (PR)50-expressing monkeys exhibited progressive motor deficits, cognitive impairment, muscle atrophy, and abnormal electromyography (EMG) potentials, which closely resemble clinical symptoms seen in C9-ALS/FTD patients. By longitudinally tracking these monkeys, we found that changes in cystatin C and chitinase-1 (CHIT1) levels in the cerebrospinal fluid (CSF) corresponded to the phenotypic progression of (PR)50-induced disease. Proteomic analysis revealed that the major clusters of dysregulated proteins were nuclear-localized, and downregulation of the MECP2 protein was implicated in the toxic process of poly(PR). This research indicates that poly(PR) expression alone induces neurodegeneration and core phenotypes associated with C9-ALS/FTD in monkeys, which may provide insights into the mechanisms of disease pathogenesis.
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Affiliation(s)
- Lizhu Xu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Dan Wang
- Horae Gene Therapy Center, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA
| | - Lu Zhao
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Zhengsheng Yang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Xu Liu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Xinyue Li
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Tingli Yuan
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Ye Wang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Tianzhuang Huang
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Ning Bian
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China
| | - Yuqun He
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Xinglong Chen
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Baohong Tian
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Zexian Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Fucheng Luo
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Wei Si
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China
| | - Guangping Gao
- Horae Gene Therapy Center, University of Massachusetts Chan Medical School, Worcester, MA 01605, USA.
| | - Weizhi Ji
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China.
| | - Yuyu Niu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China; Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, Yunnan 650500, China.
| | - Jingkuan Wei
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan 650500, China; Yunnan Key Laboratory of Primate Biomedical Research, Kunming, Yunnan 650500, China.
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28
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Wei J, Dai S, Yan Y, Li S, Yang P, Zhu R, Huang T, Li X, Duan Y, Wang Z, Ji W, Si W. Spatiotemporal proteomic atlas of multiple brain regions across early fetal to neonatal stages in cynomolgus monkey. Nat Commun 2023; 14:3917. [PMID: 37400444 PMCID: PMC10317979 DOI: 10.1038/s41467-023-39411-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 06/12/2023] [Indexed: 07/05/2023] Open
Abstract
Fetal stages are critical periods for brain development. However, the protein molecular signature and dynamics of the human brain remain unclear due to sampling difficulty and ethical limitations. Non-human primates present similar developmental and neuropathological features to humans. This study constructed a spatiotemporal proteomic atlas of cynomolgus macaque brain development from early fetal to neonatal stages. Here we showed that (1) the variability across stages was greater than that among brain regions, and comparisons of cerebellum vs. cerebrum and cortical vs. subcortical regions revealed region-specific dynamics across early fetal to neonatal stages; (2) fluctuations in abundance of proteins associated with neural disease suggest the risk of nervous disorder at early fetal stages; (3) cross-species analysis (human, monkey, and mouse) and comparison between proteomic and transcriptomic data reveal the proteomic specificity and genes with mRNA/protein discrepancy. This study provides insight into fetal brain development in primates.
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Affiliation(s)
- Jingkuan Wei
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Shaoxing Dai
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Yaping Yan
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Shulin Li
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
| | - Pengpeng Yang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
| | - Ran Zhu
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
| | - Tianzhuang Huang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Xi Li
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Yanchao Duan
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China
| | - Zhengbo Wang
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China.
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China.
| | - Weizhi Ji
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China.
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China.
- Chinese Primate Biomedical Research Alliance (CPBRA), 650500, Kunming, Yunnan, China.
| | - Wei Si
- State Key Laboratory of Primate Biomedical Research; Institute of Primate Translational Medicine, Kunming University of Science and Technology, 650500, Kunming, Yunnan, China.
- Yunnan Key Laboratory of Primate Biomedical Research, 650500, Kunming, Yunnan, China.
- Chinese Primate Biomedical Research Alliance (CPBRA), 650500, Kunming, Yunnan, China.
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29
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Skibbe H, Rachmadi MF, Nakae K, Gutierrez CE, Hata J, Tsukada H, Poon C, Schlachter M, Doya K, Majka P, Rosa MGP, Okano H, Yamamori T, Ishii S, Reisert M, Watakabe A. The Brain/MINDS Marmoset Connectivity Resource: An open-access platform for cellular-level tracing and tractography in the primate brain. PLoS Biol 2023; 21:e3002158. [PMID: 37384809 DOI: 10.1371/journal.pbio.3002158] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 05/11/2023] [Indexed: 07/01/2023] Open
Abstract
The primate brain has unique anatomical characteristics, which translate into advanced cognitive, sensory, and motor abilities. Thus, it is important that we gain insight on its structure to provide a solid basis for models that will clarify function. Here, we report on the implementation and features of the Brain/MINDS Marmoset Connectivity Resource (BMCR), a new open-access platform that provides access to high-resolution anterograde neuronal tracer data in the marmoset brain, integrated to retrograde tracer and tractography data. Unlike other existing image explorers, the BMCR allows visualization of data from different individuals and modalities in a common reference space. This feature, allied to an unprecedented high resolution, enables analyses of features such as reciprocity, directionality, and spatial segregation of connections. The present release of the BMCR focuses on the prefrontal cortex (PFC), a uniquely developed region of the primate brain that is linked to advanced cognition, including the results of 52 anterograde and 164 retrograde tracer injections in the cortex of the marmoset. Moreover, the inclusion of tractography data from diffusion MRI allows systematic analyses of this noninvasive modality against gold-standard cellular connectivity data, enabling detection of false positives and negatives, which provide a basis for future development of tractography. This paper introduces the BMCR image preprocessing pipeline and resources, which include new tools for exploring and reviewing the data.
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Affiliation(s)
- Henrik Skibbe
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | | | - Ken Nakae
- Exploratory Research Center on Life and Living Systems (ExCELLS), National Institutes of Natural Sciences, Aichi, Japan
| | - Carlos Enrique Gutierrez
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Onna Village, Japan
| | - Junichi Hata
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Hiromichi Tsukada
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Onna Village, Japan
- Center for Mathematical Science and Artificial Intelligence, Chubu University, Kasugai, Aichi, Japan
| | - Charissa Poon
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | - Matthias Schlachter
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
| | - Kenji Doya
- Neural Computation Unit, Okinawa Institute of Science and Technology Graduate University, Onna Village, Japan
| | - Piotr Majka
- Laboratory of Neuroinformatics, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, Australia
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, Australia
| | - Marcello G P Rosa
- Australian Research Council, Centre of Excellence for Integrative Brain Function, Monash University Node, Clayton, Australia
- Neuroscience Program, Biomedicine Discovery Institute and Department of Physiology, Monash University, Clayton, Australia
| | - Hideyuki Okano
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Tetsuo Yamamori
- Laboratory of Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Japan
| | - Shin Ishii
- Department of Systems Science, Kyoto University, Kyoto, Japan
| | - Marco Reisert
- Brain Image Analysis Unit, RIKEN Center for Brain Science, Wako, Saitama, Japan
- Department of Stereotactic and Functional Neurosurgery, Medical Center of the University of Freiburg, Freiburg Im Breisgau, Germany
- Medical Faculty of the University of Freiburg, Freiburg Im Breisgau, Germany
- Department of Diagnostic and Interventional Radiology, Medical Physics, Medical Center-University of Freiburg, Freiburg Im Breisgau, Germany
| | - Akiya Watakabe
- Laboratory of Haptic Perception and Cognitive Physiology, RIKEN Center for Brain Science, Wako, Saitama, Japan
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30
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Kilpatrick S, Irwin C, Singh KK. Human pluripotent stem cell (hPSC) and organoid models of autism: opportunities and limitations. Transl Psychiatry 2023; 13:217. [PMID: 37344450 PMCID: PMC10284884 DOI: 10.1038/s41398-023-02510-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 05/09/2023] [Accepted: 06/05/2023] [Indexed: 06/23/2023] Open
Abstract
Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder caused by genetic or environmental perturbations during early development. Diagnoses are dependent on the identification of behavioral abnormalities that likely emerge well after the disorder is established, leaving critical developmental windows uncharacterized. This is further complicated by the incredible clinical and genetic heterogeneity of the disorder that is not captured in most mammalian models. In recent years, advancements in stem cell technology have created the opportunity to model ASD in a human context through the use of pluripotent stem cells (hPSCs), which can be used to generate 2D cellular models as well as 3D unguided- and region-specific neural organoids. These models produce profoundly intricate systems, capable of modeling the developing brain spatiotemporally to reproduce key developmental milestones throughout early development. When complemented with multi-omics, genome editing, and electrophysiology analysis, they can be used as a powerful tool to profile the neurobiological mechanisms underlying this complex disorder. In this review, we will explore the recent advancements in hPSC-based modeling, discuss present and future applications of the model to ASD research, and finally consider the limitations and future directions within the field to make this system more robust and broadly applicable.
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Affiliation(s)
- Savannah Kilpatrick
- Donald K. Johnson Eye Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada
- Department of Biochemistry and Biomedical Science, McMaster University, Hamilton, ON, Canada
| | - Courtney Irwin
- Donald K. Johnson Eye Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Karun K Singh
- Donald K. Johnson Eye Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
- Department of Laboratory Medicine and Pathobiology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
- Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON, Canada.
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31
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Yates JL, Coop SH, Sarch GH, Wu RJ, Butts DA, Rucci M, Mitchell JF. Detailed characterization of neural selectivity in free viewing primates. Nat Commun 2023; 14:3656. [PMID: 37339973 PMCID: PMC10282080 DOI: 10.1038/s41467-023-38564-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Accepted: 05/08/2023] [Indexed: 06/22/2023] Open
Abstract
Fixation constraints in visual tasks are ubiquitous in visual and cognitive neuroscience. Despite its widespread use, fixation requires trained subjects, is limited by the accuracy of fixational eye movements, and ignores the role of eye movements in shaping visual input. To overcome these limitations, we developed a suite of hardware and software tools to study vision during natural behavior in untrained subjects. We measured visual receptive fields and tuning properties from multiple cortical areas of marmoset monkeys who freely viewed full-field noise stimuli. The resulting receptive fields and tuning curves from primary visual cortex (V1) and area MT match reported selectivity from the literature which was measured using conventional approaches. We then combined free viewing with high-resolution eye tracking to make the first detailed 2D spatiotemporal measurements of foveal receptive fields in V1. These findings demonstrate the power of free viewing to characterize neural responses in untrained animals while simultaneously studying the dynamics of natural behavior.
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Affiliation(s)
- Jacob L Yates
- Brain and Cognitive Sciences, University of Rochester, Rochester, NY, USA.
- Center for Visual Science, University of Rochester, Rochester, NY, USA.
- Department of Biology and Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA.
- Herbert Wertheim School of Optometry and Vision Science, UC Berkeley, Berkeley, CA, USA.
| | - Shanna H Coop
- Brain and Cognitive Sciences, University of Rochester, Rochester, NY, USA
- Center for Visual Science, University of Rochester, Rochester, NY, USA
- Neurobiology, Stanford University, Stanford, CA, USA
| | - Gabriel H Sarch
- Brain and Cognitive Sciences, University of Rochester, Rochester, NY, USA
- Neuroscience Institute, Carnegie Mellon University, Pittsburgh, PA, USA
| | - Ruei-Jr Wu
- Center for Visual Science, University of Rochester, Rochester, NY, USA
- Institute of Optics, University of Rochester, Rochester, NY, USA
| | - Daniel A Butts
- Department of Biology and Program in Neuroscience and Cognitive Science, University of Maryland, College Park, MD, USA
| | - Michele Rucci
- Brain and Cognitive Sciences, University of Rochester, Rochester, NY, USA
- Center for Visual Science, University of Rochester, Rochester, NY, USA
| | - Jude F Mitchell
- Brain and Cognitive Sciences, University of Rochester, Rochester, NY, USA
- Center for Visual Science, University of Rochester, Rochester, NY, USA
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32
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Liu Y, Shan L, Liu T, Li J, Chen Y, Sun C, Yang C, Bian X, Niu Y, Zhang C, Xi J, Rao Y. Molecular and cellular mechanisms of the first social relationship: A conserved role of 5-HT from mice to monkeys, upstream of oxytocin. Neuron 2023; 111:1468-1485.e7. [PMID: 36868221 DOI: 10.1016/j.neuron.2023.02.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Revised: 10/21/2021] [Accepted: 02/07/2023] [Indexed: 03/05/2023]
Abstract
Maternal affiliation by infants is the first social behavior of mammalian animals. We report here that elimination of the Tph2 gene essential for serotonin synthesis in the brain reduced affiliation in mice, rats, and monkeys. Calcium imaging and c-fos immunostaining showed maternal odors activation of serotonergic neurons in the raphe nuclei (RNs) and oxytocinergic neurons in the paraventricular nucleus (PVN). Genetic elimination of oxytocin (OXT) or its receptor reduced maternal preference. OXT rescued maternal preference in mouse and monkey infants lacking serotonin. Tph2 elimination from RN serotonergic neurons innervating PVN reduced maternal preference. Reduced maternal preference after inhibiting serotonergic neurons was rescued by oxytocinergic neuronal activation. Our genetic studies reveal a role for serotonin in affiliation conserved from mice and rats to monkeys, while electrophysiological, pharmacological, chemogenetic, and optogenetic studies uncover OXT downstream of serotonin. We suggest serotonin as the master regulator upstream of neuropeptides in mammalian social behaviors.
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Affiliation(s)
- Yan Liu
- Chinese Institutes for Medical Research (CIMR) and Department of Neurobiology, School of Basic Medical Sciences, Beijing Key Laboratory of Neural Regeneration and Repair, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 10069, China.
| | - Liang Shan
- PKU-IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, School of Life Sciences, School of Pharmaceutical Sciences, School of Chemistry and Chemical Engineering, Peking University, Beijing 100871, China; Chinese Institute for Brain Research, Beijing, Zhongguangcun Life Science Park, Beijing, China
| | - Tiane Liu
- PKU-IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, School of Life Sciences, School of Pharmaceutical Sciences, School of Chemistry and Chemical Engineering, Peking University, Beijing 100871, China; Chinese Institute for Brain Research, Beijing, Zhongguangcun Life Science Park, Beijing, China
| | - Juan Li
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China
| | - Yongchang Chen
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Changhong Sun
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China
| | - Chaojuan Yang
- Chinese Institutes for Medical Research (CIMR) and Department of Neurobiology, School of Basic Medical Sciences, Beijing Key Laboratory of Neural Regeneration and Repair, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 10069, China
| | - Xiling Bian
- PKU-IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, School of Life Sciences, School of Pharmaceutical Sciences, School of Chemistry and Chemical Engineering, Peking University, Beijing 100871, China; Chinese Institute for Brain Research, Beijing, Zhongguangcun Life Science Park, Beijing, China
| | - Yuyu Niu
- State Key Laboratory of Primate Biomedical Research, Institute of Primate Translational Medicine, Kunming University of Science and Technology, Kunming, Yunnan, China
| | - Chen Zhang
- Chinese Institutes for Medical Research (CIMR) and Department of Neurobiology, School of Basic Medical Sciences, Beijing Key Laboratory of Neural Regeneration and Repair, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 10069, China
| | - Jianzhong Xi
- State Key Laboratory of Natural and Biomimetic Drugs, Department of Biomedical Engineering, College of Engineering, Peking University, Beijing 100871, China
| | - Yi Rao
- Chinese Institutes for Medical Research (CIMR) and Department of Neurobiology, School of Basic Medical Sciences, Beijing Key Laboratory of Neural Regeneration and Repair, Advanced Innovation Center for Human Brain Protection, Capital Medical University, Beijing 10069, China; PKU-IDG/McGovern Institute for Brain Research, Peking-Tsinghua Center for Life Sciences, School of Life Sciences, School of Pharmaceutical Sciences, School of Chemistry and Chemical Engineering, Peking University, Beijing 100871, China; Changping Laboratory, Yard 28, Science Park Road, Changping District, Beijing, China; Chinese Institute for Brain Research, Beijing, Zhongguangcun Life Science Park, Beijing, China; Research Unit of Medical Neurobiology, Chinese Academy of Medical Sciences, Beijing, China.
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33
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Li J, Zhu Q, Cao J, Liu Y, Lu Y, Sun Y, Li Q, Huang Y, Shang S, Bian X, Li C, Zhang L, Wang Y, Nie Y, Fu J, Li W, Mazid MA, Jiang Y, Jia W, Wang X, Sun Y, Esteban MA, Sun Q, Zhou F, Liu Z. Cynomolgus monkey embryo model captures gastrulation and early pregnancy. Cell Stem Cell 2023; 30:362-377.e7. [PMID: 37028403 DOI: 10.1016/j.stem.2023.03.009] [Citation(s) in RCA: 33] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 02/18/2023] [Accepted: 03/16/2023] [Indexed: 04/09/2023]
Abstract
Human stem cell-derived blastoids display similar morphology and cell lineages to normal blastocysts. However, the ability to investigate their developmental potential is limited. Here, we construct cynomolgus monkey blastoids resembling blastocysts in morphology and transcriptomics using naive ESCs. These blastoids develop to embryonic disk with the structures of yolk sac, chorionic cavity, amnion cavity, primitive streak, and connecting stalk along the rostral-caudal axis through prolonged in vitro culture (IVC). Primordial germ cells, gastrulating cells, visceral endoderm/yolk sac endoderm, three germ layers, and hemato-endothelial progenitors in IVC cynomolgus monkey blastoids were observed by single-cell transcriptomics or immunostaining. Moreover, transferring cynomolgus monkey blastoids to surrogates achieves pregnancies, as indicated by progesterone levels and presence of early gestation sacs. Our results reveal the capacity of in vitro gastrulation and in vivo early pregnancy of cynomolgus monkey blastoids, providing a useful system to dissect primate embryonic development without the same ethical concerns and access challenges in human embryo study.
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Affiliation(s)
- Jie Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Qingyuan Zhu
- Haihe Laboratory of Cell Ecosystem, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, China
| | - Jing Cao
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China; Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shanxi, China
| | - Ying Liu
- Haihe Laboratory of Cell Ecosystem, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, China
| | - Yong Lu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Yining Sun
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Qian Li
- Haihe Laboratory of Cell Ecosystem, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, China
| | - Yiming Huang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Shenshen Shang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China; College of Agriculture, Henan University of Science and Technology, Luoyang 471023, Henan, China
| | - Xinyan Bian
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Chunyang Li
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Liansheng Zhang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Yan Wang
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Yanhong Nie
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Jiqiang Fu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Wenjuan Li
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Md Abdul Mazid
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Yu Jiang
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Wenqi Jia
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Xiaolong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shanxi, China
| | - Yidi Sun
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China
| | - Miguel A Esteban
- Laboratory of Integrative Biology, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou, China
| | - Qiang Sun
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China; University of Chinese Academy of Sciences, 100049 Beijing, China.
| | - Fan Zhou
- Haihe Laboratory of Cell Ecosystem, Tsinghua-Peking Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, China.
| | - Zhen Liu
- Institute of Neuroscience, CAS Center for Excellence in Brain Science and Intelligence Technology, CAS Key Laboratory of Primate Neurobiology, State Key Laboratory of Neuroscience, Chinese Academy of Sciences, Shanghai, China; Shanghai Center for Brain Science and Brain-Inspired Intelligence Technology, Shanghai, China; University of Chinese Academy of Sciences, 100049 Beijing, China.
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34
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Latham LE, Dobrovolsky VN, Liu S, Talpos JC, Hanig JP, Slikker W, Wang C, Liu F. Establishment of neural stem cells from fetal monkey brain for neurotoxicity testing. Exp Biol Med (Maywood) 2023; 248:633-640. [PMID: 37208932 PMCID: PMC10350806 DOI: 10.1177/15353702231168145] [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: 02/13/2023] [Accepted: 03/06/2023] [Indexed: 05/21/2023] Open
Abstract
Neurotoxicity assessments are generally performed using laboratory animals. However, as in vitro neurotoxicity models are continuously refined to reach adequate predicative concordance with in vivo responses, they are increasingly used for some endpoints of neurotoxicity. In this study, gestational day 80 fetal rhesus monkey brain tissue was obtained for neural stem cells (NSCs) isolation. Cells from the entire hippocampus were harvested, mechanically dissociated, and cultured for proliferation and differentiation. Immunocytochemical staining and biological assays demonstrated that the harvested hippocampal cells exhibited typical NSC phenotypes in vitro: (1) cells proliferated vigorously and expressed NSC markers nestin and sex-determining region Y-box 2 (SOX2) and (2) cells differentiated into neurons, astrocytes, and oligodendrocytes, as confirmed by positive staining with class III β-tubulin, glial fibrillary acidic protein, and galactocerebroside, respectively. The NSC produced detectable responses following neurotoxicant exposures (e.g. trimethyltin and 3-nitropropionic acid). Our results indicated that non-human primate NSCs may be a practical tool to study the biology of neural cells and to evaluate the neurotoxicity of chemicals in vitro, thereby providing data that are translatable to humans and may also reduce the number of animals needed for developmental neurotoxicological studies.
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Affiliation(s)
- Leah E Latham
- Division of Neurotoxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR 72079, USA
| | - Vasily N Dobrovolsky
- Division of Genetic and Molecular Toxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR 72079, USA
| | - Shuliang Liu
- Division of Neurotoxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR 72079, USA
| | - John C Talpos
- Division of Neurotoxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR 72079, USA
| | - Joseph P Hanig
- Office of Pharmaceutical Quality, Center for Drug Evaluation and Research, U.S. FDA, Silver Spring, MD 20903, USA
| | - William Slikker
- Office of Director, National Center for Toxicological Research, U.S. FDA, Jefferson, AR 72079, USA
| | - Cheng Wang
- Division of Neurotoxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR 72079, USA
| | - Fang Liu
- Division of Neurotoxicology, National Center for Toxicological Research, U.S. FDA, Jefferson, AR 72079, USA
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35
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Wong RK, Selvanayagam J, Johnston KD, Everling S. Delay-related activity in marmoset prefrontal cortex. Cereb Cortex 2023; 33:3523-3537. [PMID: 35945687 PMCID: PMC10068290 DOI: 10.1093/cercor/bhac289] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 06/28/2022] [Accepted: 06/28/2022] [Indexed: 11/13/2022] Open
Abstract
Persistent delay-period activity in prefrontal cortex (PFC) has long been regarded as a neural signature of working memory (WM). Electrophysiological investigations in macaque PFC have provided much insight into WM mechanisms; however, a barrier to understanding is the fact that a portion of PFC lies buried within the principal sulcus in this species and is inaccessible for laminar electrophysiology or optical imaging. The relatively lissencephalic cortex of the New World common marmoset (Callithrix jacchus) circumvents such limitations. It remains unknown, however, whether marmoset PFC neurons exhibit persistent activity. Here, we addressed this gap by conducting wireless electrophysiological recordings in PFC of marmosets performing a delayed-match-to-location task on a home cage-based touchscreen system. As in macaques, marmoset PFC neurons exhibited sample-, delay-, and response-related activity that was directionally tuned and linked to correct task performance. Models constructed from population activity consistently and accurately predicted stimulus location throughout the delay period, supporting a framework of delay activity in which mnemonic representations are relatively stable in time. Taken together, our findings support the existence of common neural mechanisms underlying WM performance in PFC of macaques and marmosets and thus validate the marmoset as a suitable model animal for investigating the microcircuitry underlying WM.
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Affiliation(s)
- Raymond K Wong
- Graduate Program in Neuroscience, Western University, London, ON N6A 3K7, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON N6A 5B7, Canada
| | - Janahan Selvanayagam
- Graduate Program in Neuroscience, Western University, London, ON N6A 3K7, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON N6A 5B7, Canada
| | - Kevin D Johnston
- Graduate Program in Neuroscience, Western University, London, ON N6A 3K7, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON N6A 5B7, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON N6A 3K7, Canada
| | - Stefan Everling
- Graduate Program in Neuroscience, Western University, London, ON N6A 3K7, Canada
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON N6A 5B7, Canada
- Department of Physiology and Pharmacology, University of Western Ontario, London, ON N6A 3K7, Canada
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36
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Kodera T, Takeuchi RF, Takahashi S, Suzuki K, Kassai H, Aiba A, Shiozawa S, Okano H, Osakada F. Modeling the marmoset brain using embryonic stem cell-derived cerebral assembloids. Biochem Biophys Res Commun 2023; 657:119-127. [PMID: 37002985 DOI: 10.1016/j.bbrc.2023.03.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 03/08/2023] [Indexed: 03/13/2023]
Abstract
Studying the non-human primate (NHP) brain is required for the translation of rodent research to humans, but remains a challenge for molecular, cellular, and circuit-level analyses in the NHP brain due to the lack of in vitro NHP brain system. Here, we report an in vitro NHP cerebral model using marmoset (Callithrix jacchus) embryonic stem cell-derived cerebral assembloids (CAs) that recapitulate inhibitory neuron migration and cortical network activity. Cortical organoids (COs) and ganglionic eminence organoids (GEOs) were induced from cjESCs and fused to generate CAs. GEO cells expressing the inhibitory neuron marker LHX6 migrated toward the cortical side of CAs. COs developed their spontaneous neural activity from a synchronized pattern to an unsynchronized pattern as COs matured. CAs containing excitatory and inhibitory neurons showed mature neural activity with an unsynchronized pattern. The CAs represent a powerful in vitro model for studying excitatory and inhibitory neuron interactions, cortical dynamics, and their dysfunction. The marmoset assembloid system will provide an in vitro platform for the NHP neurobiology and facilitate translation into humans in neuroscience research, regenerative medicine, and drug discovery.
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37
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Yoshimatsu S, Nakajima M, Sonn I, Natsume R, Sakimura K, Nakatsukasa E, Sasaoka T, Nakamura M, Serizawa T, Sato T, Sasaki E, Deng H, Okano H. Attempts for deriving extended pluripotent stem cells from common marmoset embryonic stem cells. Genes Cells 2023; 28:156-169. [PMID: 36530170 DOI: 10.1111/gtc.13000] [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: 12/04/2021] [Revised: 12/13/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022]
Abstract
Extended pluripotent stem cells (EPSCs) derived from mice and humans showed an enhanced potential for chimeric formation. By exploiting transcriptomic approaches, we assessed the differences in gene expression profile between extended EPSCs derived from mice and humans, and those newly derived from the common marmoset (marmoset; Callithrix jacchus). Although the marmoset EPSC-like cells displayed a unique colony morphology distinct from murine and human EPSCs, they displayed a pluripotent state akin to embryonic stem cells (ESCs), as confirmed by gene expression and immunocytochemical analyses of pluripotency markers and three-germ-layer differentiation assay. Importantly, the marmoset EPSC-like cells showed interspecies chimeric contribution to mouse embryos, such as E6.5 blastocysts in vitro and E6.5 epiblasts in vivo in mouse development. Also, we discovered that the perturbation of gene expression of the marmoset EPSC-like cells from the original ESCs resembled that of human EPSCs. Taken together, our multiple analyses evaluated the efficacy of the method for the derivation of marmoset EPSCs.
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Affiliation(s)
- Sho Yoshimatsu
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan.,Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan
| | - Mayutaka Nakajima
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Iki Sonn
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Rie Natsume
- Department of Animal Model Development, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kenji Sakimura
- Department of Animal Model Development, Brain Research Institute, Niigata University, Niigata, Japan
| | - Ena Nakatsukasa
- Department of Animal Model Development, Brain Research Institute, Niigata University, Niigata, Japan
| | - Toshikuni Sasaoka
- Department of Animal Model Development, Brain Research Institute, Niigata University, Niigata, Japan
| | - Mari Nakamura
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Takashi Serizawa
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Tsukika Sato
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan
| | - Erika Sasaki
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan.,Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kanagawa, Japan
| | - Hongkui Deng
- Stem Cell Research Center, Peking University, Beijing, China
| | - Hideyuki Okano
- Department of Physiology, Keio University School of Medicine, Tokyo, Japan.,Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Saitama, Japan
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Emborg ME. Reframing the perception of outliers and negative data in translational research. Brain Res Bull 2023; 192:203-207. [PMID: 36464129 PMCID: PMC9891652 DOI: 10.1016/j.brainresbull.2022.11.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 11/29/2022] [Indexed: 12/05/2022]
Abstract
Negative results can be a source of disappointment for scientists, yet their publication is needed for scientific progress, in particular for cutting-edge translational research of novel therapeutics. This manuscript is directed to scientists, junior and senior, that produce and review data for publication. It discusses the difference between 'negative' or 'unexpected' data and 'useless' data, re-evaluates the importance of the experimental design to generate valuable data and proposes strategies to work with and report negative results. Overall, it aims to reframe the perception of working with, reporting and reviewing unexpected data as an opportunity to provide rationale for innovative ideas, prevent the misuse of limited resources and, ultimately, strengthen the reputation of a scientist.
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Affiliation(s)
- Marina E Emborg
- Preclinical Parkinson's Research Program, Wisconsin National Primate Research Center, Department of Medical Physics, University of Wisconsin-Madison, 1220 Capitol Court, Madison, WI 53715, USA.
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39
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Glavis-Bloom C, Vanderlip CR, Reynolds JH. Age-Related Learning and Working Memory Impairment in the Common Marmoset. J Neurosci 2022; 42:8870-8880. [PMID: 36257687 PMCID: PMC9698676 DOI: 10.1523/jneurosci.0985-22.2022] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 09/06/2022] [Accepted: 09/09/2022] [Indexed: 12/29/2022] Open
Abstract
Aging is the greatest risk factor for the development of neurodegenerative diseases, yet we still do not understand how the aging process leads to pathologic vulnerability. The research community has relied heavily on mouse models, but the considerable anatomic, physiological, and cognitive differences between mice and humans limit their translational relevance. Ultimately, these barriers necessitate the development of novel aging models. As a nonhuman primate (NHP), the common marmoset (Callithrix jacchus) shares many features in common with humans and yet has a significantly shorter lifespan (10 years) than other primates, making it ideally suited to longitudinal studies of aging. Our objective was to evaluate the marmoset as a model of age-related cognitive impairment. To do this, we used the Delayed Recognition Span Task (DRST) to characterize age-related changes in working memory capacity in a cohort of sixteen marmosets, of both sexes, varying in age from young adult to geriatric. These monkeys performed thousands of trials over periods of time ranging up to 50% of their adult lifespan. To our knowledge, this represents the most thorough cognitive profiling of any marmoset aging study conducted to date. By analyzing individual learning curves, we found that aged animals exhibited delayed onset of learning, slowed learning rate after onset, and decreased asymptotic working memory performance. These findings are not accounted for by age-related impairments in motor speed and motivation. This work firmly establishes the marmoset as a model of age-related cognitive impairment.SIGNIFICANCE STATEMENT Understanding the normal aging process is fundamental to identifying therapeutics for neurodegenerative diseases for which aging is the biggest risk factor. Historically, the aging field has relied on animal models that differ markedly from humans, constraining translatability. Here, we firmly establish a short-lived nonhuman primate (NHP), the common marmoset, as a key model of age-related cognitive impairment. We demonstrate, through continuous testing over a substantial portion of the adult marmoset lifespan, that aging is associated with both impaired learning and working memory capacity, unaccounted for by age-related changes in motor speed and motivation. Characterizing individual cognitive aging trajectories reveals inherent heterogeneity, which could lead to earlier identification of the onset of impairment, and extended timelines during which therapeutics are effective.
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Affiliation(s)
- Courtney Glavis-Bloom
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037
| | - Casey R Vanderlip
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037
| | - John H Reynolds
- Systems Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, California 92037
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40
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Ma S, Skarica M, Li Q, Xu C, Risgaard RD, Tebbenkamp AT, Mato-Blanco X, Kovner R, Krsnik Ž, de Martin X, Luria V, Martí-Pérez X, Liang D, Karger A, Schmidt DK, Gomez-Sanchez Z, Qi C, Gobeske KT, Pochareddy S, Debnath A, Hottman CJ, Spurrier J, Teo L, Boghdadi AG, Homman-Ludiye J, Ely JJ, Daadi EW, Mi D, Daadi M, Marín O, Hof PR, Rasin MR, Bourne J, Sherwood CC, Santpere G, Girgenti MJ, Strittmatter SM, Sousa AM, Sestan N. Molecular and cellular evolution of the primate dorsolateral prefrontal cortex. Science 2022; 377:eabo7257. [PMID: 36007006 PMCID: PMC9614553 DOI: 10.1126/science.abo7257] [Citation(s) in RCA: 125] [Impact Index Per Article: 41.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
The granular dorsolateral prefrontal cortex (dlPFC) is an evolutionary specialization of primates that is centrally involved in cognition. We assessed more than 600,000 single-nucleus transcriptomes from adult human, chimpanzee, macaque, and marmoset dlPFC. Although most cell subtypes defined transcriptomically are conserved, we detected several that exist only in a subset of species as well as substantial species-specific molecular differences across homologous neuronal, glial, and non-neural subtypes. The latter are exemplified by human-specific switching between expression of the neuropeptide somatostatin and tyrosine hydroxylase, the rate-limiting enzyme in dopamine production in certain interneurons. The above molecular differences are also illustrated by expression of the neuropsychiatric risk gene FOXP2, which is human-specific in microglia and primate-specific in layer 4 granular neurons. We generated a comprehensive survey of the dlPFC cellular repertoire and its shared and divergent features in anthropoid primates.
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Affiliation(s)
- Shaojie Ma
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Mario Skarica
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Qian Li
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Chuan Xu
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Ryan D. Risgaard
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
- Medical Scientist Training Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | | | - Xoel Mato-Blanco
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Rothem Kovner
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Željka Krsnik
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Croatian Institute for Brain Research, School of Medicine, University of Zagreb, 10000 Zagreb, Croatia
| | - Xabier de Martin
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Victor Luria
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Xavier Martí-Pérez
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Dan Liang
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Amir Karger
- IT-Research Computing, Harvard Medical School, Boston, MA, USA
| | - Danielle K. Schmidt
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Zachary Gomez-Sanchez
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Cai Qi
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Kevin T. Gobeske
- Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, New Haven, CT 06510, USA
| | - Sirisha Pochareddy
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - Ashwin Debnath
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Cade J. Hottman
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Joshua Spurrier
- Program in Cellular Neuroscience, Neurodegeneration and Repair, Department of Neurology, Yale School of Medicine, New Haven, CT 06536, USA
| | - Leon Teo
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - Anthony G. Boghdadi
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - Jihane Homman-Ludiye
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - John J. Ely
- MAEBIOS, Alamogordo, NM 88310, USA
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
| | - Etienne W. Daadi
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Da Mi
- Tsinghua-Peking Center for Life Sciences, IDG/McGovern Institute for Brain Research, School of Life Sciences, Tsinghua University, Beijing 100084, China
| | - Marcel Daadi
- Southwest National Primate Research Center, Texas Biomedical Research Institute, San Antonio, TX, USA
- Department of Cell Systems & Anatomy, Radiology, Long School of Medicine, UT Health San Antonio
- NeoNeuron LLC, Palo Alto, CA 94306, USA
| | - Oscar Marín
- Centre for Developmental Neurobiology, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE1 1UL, UK
- MRC Centre for Neurodevelopmental Disorders, King’s College London, London SE1 1UL, UK
| | - Patrick R. Hof
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mladen-Roko Rasin
- Department of Neuroscience and Cell Biology, Robert Wood Johnson Medical School, Rutgers University, Piscataway, NJ 08854, USA
| | - James Bourne
- Australian Regenerative Medicine Institute, 15 Innovation Walk, Monash University, Clayton VIC, 3800, Australia
| | - Chet C. Sherwood
- Department of Anthropology and Center for the Advanced Study of Human Paleobiology, The George Washington University, Washington, DC, USA
| | - Gabriel Santpere
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Neurogenomics Group, Research Programme on Biomedical Informatics (GRIB), Hospital del Mar Medical Research Institute (IMIM), MELIS, Universitat Pompeu Fabra, 08003 Barcelona, Catalonia, Spain
| | - Matthew J. Girgenti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT 06510, USA
- National Center for PTSD, US Department of Veterans Affairs, White River Junction, VT, USA
| | - Stephen M. Strittmatter
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Program in Cellular Neuroscience, Neurodegeneration and Repair, Department of Neurology, Yale School of Medicine, New Haven, CT 06536, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
| | - André M.M. Sousa
- Waisman Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
- Department of Neuroscience, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Nenad Sestan
- Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT 06510, USA
- Kavli Institute for Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
- Departments of Genetics and Comparative Medicine, Program in Cellular Neuroscience, Neurodegeneration and Repair, and Yale Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA
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41
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Yoshimatsu S, Seki F, Okahara J, Watanabe H, Sasaguri H, Haga Y, Hata JI, Sanosaka T, Inoue T, Mineshige T, Lee CY, Shinohara H, Kurotaki Y, Komaki Y, Kishi N, Murayama AY, Nagai Y, Minamimoto T, Yamamoto M, Nakajima M, Zhou Z, Nemoto A, Sato T, Ikeuchi T, Sahara N, Morimoto S, Shiozawa S, Saido TC, Sasaki E, Okano H. Multimodal analyses of a non-human primate model harboring mutant amyloid precursor protein transgenes driven by the human EF1α promoter. Neurosci Res 2022; 185:49-61. [PMID: 36075457 DOI: 10.1016/j.neures.2022.08.008] [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: 03/29/2022] [Revised: 08/18/2022] [Accepted: 08/21/2022] [Indexed: 11/30/2022]
Abstract
Alzheimer's disease (AD) is the leading cause of dementia which afflicts tens of millions of people worldwide. Despite many scientific progresses to dissect the AD's molecular basis from studies on various mouse models, it has been suffered from evolutionary species differences. Here, we report generation of a non-human primate (NHP), common marmoset model ubiquitously expressing Amyloid-beta precursor protein (APP) transgenes with the Swedish (KM670/671NL) and Indiana (V717F) mutations. The transgene integration of generated two transgenic marmosets (TG1&TG2) was thoroughly investigated by genomic PCR, whole-genome sequencing, and fluorescence in situ hybridization. By reprogramming, we confirmed the validity of transgene expression in induced neurons in vitro. Moreover, we discovered structural changes in specific brain regions of transgenic marmosets by magnetic resonance imaging analysis, including in the entorhinal cortex and hippocampus. In immunohistochemistry, we detected increased Aβ plaque-like structures in TG1 brain at 7 years old, although evident neuronal loss or glial inflammation was not observed. Thus, this study summarizes our attempt to establish an NHP AD model. Although the transgenesis approach alone seemed not sufficient to fully recapitulate AD in NHPs, it may be beneficial for drug development and further disease modeling by combination with other genetically engineered models and disease-inducing approaches.
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Affiliation(s)
- Sho Yoshimatsu
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan; Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan
| | - Fumiko Seki
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Junko Okahara
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan
| | - Hirotaka Watanabe
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Hiroki Sasaguri
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan
| | - Yawara Haga
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan; Graduate School of Human Health Sciences, Tokyo Metropolitan University, Arakawa-ku, Tokyo 116-8551, Japan
| | - Jun-Ichi Hata
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan; Graduate School of Human Health Sciences, Tokyo Metropolitan University, Arakawa-ku, Tokyo 116-8551, Japan
| | - Tsukasa Sanosaka
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Takashi Inoue
- Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Takayuki Mineshige
- Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Chia-Ying Lee
- Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Haruka Shinohara
- Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Yoko Kurotaki
- Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Yuji Komaki
- Live Imaging Center, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan
| | - Noriyuki Kishi
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan
| | - Ayaka Y Murayama
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan
| | - Yuji Nagai
- Department of Functional Brain Imaging Research, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba City, Chiba 263-8555, Japan
| | - Takafumi Minamimoto
- Department of Functional Brain Imaging Research, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba City, Chiba 263-8555, Japan
| | - Masafumi Yamamoto
- ICLAS Monitoring Center, Central Institute for Experimental Animals, Kanagawa 210-0821, Japan
| | - Mayutaka Nakajima
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Zhi Zhou
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Akisa Nemoto
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Tsukika Sato
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Chuo-ku, Niigata 951-8122, Japan
| | - Naruhiko Sahara
- Department of Functional Brain Imaging Research, National Institute of Radiological Sciences, National Institutes for Quantum and Radiological Science and Technology, Chiba City, Chiba 263-8555, Japan
| | - Satoru Morimoto
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Seiji Shiozawa
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan
| | - Takaomi C Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan
| | - Erika Sasaki
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan; Department of Marmoset Biology and Medicine, Central Institute for Experimental Animals, Kawasaki, Kanagawa 210-0821, Japan.
| | - Hideyuki Okano
- Department of Physiology, School of Medicine, Keio University, Shinjuku-ku, Tokyo 160-8582, Japan; Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako City, Saitama 351-0198, Japan.
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Kaczanowska J, Ganglberger F, Chernomor O, Kargl D, Galik B, Hess A, Moodley Y, von Haeseler A, Bühler K, Haubensak W. Molecular archaeology of human cognitive traits. Cell Rep 2022; 40:111287. [PMID: 36044840 DOI: 10.1016/j.celrep.2022.111287] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Revised: 05/20/2022] [Accepted: 08/05/2022] [Indexed: 01/06/2023] Open
Abstract
The brains and minds of our human ancestors remain inaccessible for experimental exploration. Therefore, we reconstructed human cognitive evolution by projecting nonsynonymous/synonymous rate ratios (ω values) in mammalian phylogeny onto the anatomically modern human (AMH) brain. This atlas retraces human neurogenetic selection and allows imputation of ancestral evolution in task-related functional networks (FNs). Adaptive evolution (high ω values) is associated with excitatory neurons and synaptic function. It shifted from FNs for motor control in anthropoid ancestry (60-41 mya) to attention in ancient hominoids (26-19 mya) and hominids (19-7.4 mya). Selection in FNs for language emerged with an early hominin ancestor (7.4-1.7 mya) and was later accompanied by adaptive evolution in FNs for strategic thinking during recent (0.8 mya-present) speciation of AMHs. This pattern mirrors increasingly complex cognitive demands and suggests that co-selection for language alongside strategic thinking may have separated AMHs from their archaic Denisovan and Neanderthal relatives.
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Affiliation(s)
- Joanna Kaczanowska
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria
| | | | - Olga Chernomor
- Center for Integrative Bioinformatics Vienna (CIBIV), Max Perutz Labs, University of Vienna, Medical University of Vienna, Dr. Bohr Gasse 9, 1030 Vienna, Austria
| | - Dominic Kargl
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria; Department of Neuronal Cell Biology, Center for Brain Research, Medical University of Vienna, Vienna, Austria
| | - Bence Galik
- Bioinformatics and Scientific Computing, Vienna Biocenter Core Facilities (VBCF), Dr. Bohr Gasse 3, 1030 Vienna, Austria
| | - Andreas Hess
- Institute of Experimental and Clinical Pharmacology and Toxicology, Friedrich-Alexander University Erlangen-Nuremberg, Fahrstrasse 17, 91054 Erlangen, Germany
| | - Yoshan Moodley
- Department of Zoology, University of Venda, Private Bag X5050, Thohoyandou, Republic of South Africa
| | - Arndt von Haeseler
- Center for Integrative Bioinformatics Vienna (CIBIV), Max Perutz Labs, University of Vienna, Medical University of Vienna, Dr. Bohr Gasse 9, 1030 Vienna, Austria; Faculty of Computer Science, University of Vienna, Währinger Str. 29, 1090 Vienna, Austria
| | - Katja Bühler
- VRVis Research Center, Donau-City Strasse 11, 1220 Vienna, Austria
| | - Wulf Haubensak
- Research Institute of Molecular Pathology (IMP), Vienna Biocenter (VBC), Campus-Vienna-Biocenter 1, 1030 Vienna, Austria; Department of Neuronal Cell Biology, Center for Brain Research, Medical University of Vienna, Vienna, Austria.
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43
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Yoshimatsu S, Kisu I, Qian E, Noce T. A New Horizon in Reproductive Research with Pluripotent Stem Cells: Successful In Vitro Gametogenesis in Rodents, Its Application to Large Animals, and Future In Vitro Reconstitution of Reproductive Organs Such as “Uteroid” and “Oviductoid”. BIOLOGY 2022; 11:biology11070987. [PMID: 36101367 PMCID: PMC9312112 DOI: 10.3390/biology11070987] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2022] [Revised: 06/24/2022] [Accepted: 06/28/2022] [Indexed: 11/16/2022]
Abstract
Simple Summary Functional gametes, such as oocytes and spermatozoa, have been derived from rodent pluripotent stem cells, which can be applied to large animals and ultimately, to humans. In addition to summarizing these topics, we also review additional approaches for in vitro reconstitution of reproductive organs. This review illustrates intensive past efforts and future challenges on stem cell research for in vitro biogenesis in various mammalian models. Abstract Recent success in derivation of functional gametes (oocytes and spermatozoa) from pluripotent stem cells (PSCs) of rodents has made it feasible for future application to large animals including endangered species and to ultimately humans. Here, we summarize backgrounds and recent studies on in vitro gametogenesis from rodent PSCs, and similar approaches using PSCs from large animals, including livestock, nonhuman primates (NHPs), and humans. We also describe additional developing approaches for in vitro reconstitution of reproductive organs, such as the ovary (ovarioid), testis (testisoid), and future challenges in the uterus (uteroid) and oviduct (oviductoid), all of which may be derived from PSCs. Once established, these in vitro systems may serve as a robust platform for elucidating the pathology of infertility-related disorders and ectopic pregnancy, principle of reproduction, and artificial biogenesis. Therefore, these possibilities, especially when using human cells, require consideration of ethical issues, and international agreements and guidelines need to be raised before opening “Pandora’s Box”.
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Affiliation(s)
- Sho Yoshimatsu
- Department of Stem Cell Biology and Medicine, Graduate School of Medical Sciences, Kyushu University, Higashi-ku, Fukuoka 812-8582, Japan
- Research Fellow of Japan Society for the Promotion of Science (JSPS), Chiyoda-ku, Tokyo 102-0083, Japan
- Department of Physiology, Keio University School of Medicine, Shinjuku-ku, Tokyo 160-8582, Japan;
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako-City 351-0198, Japan;
- Correspondence:
| | - Iori Kisu
- Department of Obstetrics and Gynecology, Keio University School of Medicine, Shinjuku-ku, Tokyo 160-8582, Japan;
| | - Emi Qian
- Department of Physiology, Keio University School of Medicine, Shinjuku-ku, Tokyo 160-8582, Japan;
| | - Toshiaki Noce
- Laboratory for Marmoset Neural Architecture, RIKEN Center for Brain Science, Wako-City 351-0198, Japan;
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Chung C, Shin W, Kim E. Early and Late Corrections in Mouse Models of Autism Spectrum Disorder. Biol Psychiatry 2022; 91:934-944. [PMID: 34556257 DOI: 10.1016/j.biopsych.2021.07.021] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 06/18/2021] [Accepted: 07/21/2021] [Indexed: 12/18/2022]
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by social and repetitive symptoms. A key feature of ASD is early-life manifestations of symptoms, indicative of early pathophysiological mechanisms. In mouse models of ASD, increasing evidence indicates that there are early pathophysiological mechanisms that can be corrected early to prevent phenotypic defects in adults, overcoming the disadvantage of the short-lasting effects that characterize adult-initiated treatments. In addition, the results from gene restorations indicate that ASD-related phenotypes can be rescued in some cases even after the brain has fully matured. These results suggest that we need to consider both temporal and mechanistic aspects in studies of ASD models and carefully compare genetic and nongenetic corrections. Here, we summarize the early and late corrections in mouse models of ASD by genetic and pharmacological interventions and discuss how to better integrate these results to ensure efficient and long-lasting corrections for eventual clinical translation.
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Affiliation(s)
- Changuk Chung
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, South Korea; Department of Neurosciences, University of California San Diego, La Jolla, California
| | - Wangyong Shin
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, South Korea
| | - Eunjoon Kim
- Center for Synaptic Brain Dysfunctions, Institute for Basic Science, Daejeon, South Korea; Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, South Korea.
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45
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Wakeman DR, Weed MR, Perez SE, Cline EN, Viola KL, Wilcox KC, Moddrelle DS, Nisbett EZ, Kurian AM, Bell AF, Pike R, Jacobson PB, Klein WL, Mufson EJ, Lawrence MS, Elsworth JD. Intrathecal amyloid-beta oligomer administration increases tau phosphorylation in the medial temporal lobe in the African green monkey: A nonhuman primate model of Alzheimer's disease. Neuropathol Appl Neurobiol 2022; 48:e12800. [PMID: 35156715 PMCID: PMC10902791 DOI: 10.1111/nan.12800] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 01/31/2022] [Accepted: 02/05/2022] [Indexed: 11/26/2022]
Abstract
AIMS An obstacle to developing new treatment strategies for Alzheimer's disease (AD) has been the inadequate translation of findings in current AD transgenic rodent models to the prediction of clinical outcomes. By contrast, nonhuman primates (NHPs) share a close neurobiology with humans in virtually all aspects relevant to developing a translational AD model. The present investigation used African green monkeys (AGMs) to refine an inducible NHP model of AD based on the administration of amyloid-beta oligomers (AβOs), a key upstream initiator of AD pathology. METHODS AβOs or vehicle were repeatedly delivered over 4 weeks to age-matched young adult AGMs by intracerebroventricular (ICV) or intrathecal (IT) injections. Induction of AD-like pathology was assessed in subregions of the medial temporal lobe (MTL) by quantitative immunohistochemistry (IHC) using the AT8 antibody to detect hyperphosphorylated tau. Hippocampal volume was measured by magnetic resonance imaging (MRI) scans prior to, and after, intrathecal injections. RESULTS IT administration of AβOs in young adult AGMs revealed an elevation of tau phosphorylation in the MTL cortical memory circuit compared with controls. The largest increases were detected in the entorhinal cortex that persisted for at least 12 weeks after dosing. MRI scans showed a reduction in hippocampal volume following AβO injections. CONCLUSIONS Repeated IT delivery of AβOs in young adult AGMs led to an accelerated AD-like neuropathology in MTL, similar to human AD, supporting the value of this translational model to de-risk the clinical trial of diagnostic and therapeutic strategies.
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Affiliation(s)
| | | | - Sylvia E Perez
- Neurobiology, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Erika N Cline
- Neurobiology, Northwestern University, Evanston, Illinois, USA
| | - Kirsten L Viola
- Neurobiology, Northwestern University, Evanston, Illinois, USA
| | - Kyle C Wilcox
- Neurobiology, Northwestern University, Evanston, Illinois, USA
| | - David S Moddrelle
- Virscio Inc., St. Kitts Biomedical Research Foundation, St. Kitts, West Indies
| | - Ernell Z Nisbett
- Virscio Inc., St. Kitts Biomedical Research Foundation, St. Kitts, West Indies
| | | | - Amanda F Bell
- Virscio Inc., St. Kitts Biomedical Research Foundation, St. Kitts, West Indies
| | - Ricaldo Pike
- Virscio Inc., St. Kitts Biomedical Research Foundation, St. Kitts, West Indies
| | | | - William L Klein
- Neurobiology, Northwestern University, Evanston, Illinois, USA
| | - Elliott J Mufson
- Neurobiology, Barrow Neurological Institute, Phoenix, Arizona, USA
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46
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Guo S, Xue J, Liu J, Ye X, Guo Y, Liu D, Zhao X, Xiong F, Han X, Peng H. Smart imaging to empower brain-wide neuroscience at single-cell levels. Brain Inform 2022; 9:10. [PMID: 35543774 PMCID: PMC9095808 DOI: 10.1186/s40708-022-00158-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 04/12/2022] [Indexed: 11/10/2022] Open
Abstract
A deep understanding of the neuronal connectivity and networks with detailed cell typing across brain regions is necessary to unravel the mechanisms behind the emotional and memorial functions as well as to find the treatment of brain impairment. Brain-wide imaging with single-cell resolution provides unique advantages to access morphological features of a neuron and to investigate the connectivity of neuron networks, which has led to exciting discoveries over the past years based on animal models, such as rodents. Nonetheless, high-throughput systems are in urgent demand to support studies of neural morphologies at larger scale and more detailed level, as well as to enable research on non-human primates (NHP) and human brains. The advances in artificial intelligence (AI) and computational resources bring great opportunity to 'smart' imaging systems, i.e., to automate, speed up, optimize and upgrade the imaging systems with AI and computational strategies. In this light, we review the important computational techniques that can support smart systems in brain-wide imaging at single-cell resolution.
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Affiliation(s)
- Shuxia Guo
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China.
| | - Jie Xue
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Jian Liu
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Xiangqiao Ye
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Yichen Guo
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Di Liu
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Xuan Zhao
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Feng Xiong
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
| | - Xiaofeng Han
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China.
| | - Hanchuan Peng
- Institute for Brain and Intelligence, Southeast University, Nanjing, 210096, Jiangsu, China
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Song X, Guo Y, Li H, Chen C, Lee JH, Zhang Y, Schmidt Z, Wang X. Mesoscopic landscape of cortical functions revealed by through-skull wide-field optical imaging in marmoset monkeys. Nat Commun 2022; 13:2238. [PMID: 35474064 PMCID: PMC9042927 DOI: 10.1038/s41467-022-29864-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 04/04/2022] [Indexed: 12/15/2022] Open
Abstract
The primate cerebral cortex is organized into specialized areas representing different modalities and functions along a continuous surface. The functional maps across the cortex, however, are often investigated a single modality at a time (e.g., audition or vision). To advance our understanding of the complex landscape of primate cortical functions, here we develop a polarization-gated wide-field optical imaging method for measuring cortical functions through the un-thinned intact skull in awake marmoset monkeys (Callithrix jacchus), a primate species featuring a smooth cortex. Using this method, adjacent auditory, visual, and somatosensory cortices are noninvasively parcellated in individual subjects with detailed tonotopy, retinotopy, and somatotopy. An additional pure-tone-responsive tonotopic gradient is discovered in auditory cortex and a face-patch sensitive to motion in the lower-center visual field is localized near an auditory region representing frequencies of conspecific vocalizations. This through-skull landscape-mapping approach provides new opportunities for understanding how the primate cortex is organized and coordinated to enable real-world behaviors.
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Affiliation(s)
- Xindong Song
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Yueqi Guo
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Hongbo Li
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Chenggang Chen
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Jong Hoon Lee
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Yang Zhang
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Zachary Schmidt
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
| | - Xiaoqin Wang
- grid.21107.350000 0001 2171 9311Laboratory of Auditory Neurophysiology, Department of Biomedical Engineering, Johns Hopkins University School of Medicine, Baltimore, MD 21205 USA
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48
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Li G, Li X, Zhuang S, Wang L, Zhu Y, Chen Y, Sun W, Wu Z, Zhou Z, Chen J, Huang X, Wang J, Li D, Li W, Wang H, Wei W. Gene editing and its applications in biomedicine. SCIENCE CHINA. LIFE SCIENCES 2022; 65:660-700. [PMID: 35235150 PMCID: PMC8889061 DOI: 10.1007/s11427-021-2057-0] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Accepted: 12/06/2021] [Indexed: 02/06/2023]
Abstract
The steady progress in genome editing, especially genome editing based on the use of clustered regularly interspaced short palindromic repeats (CRISPR) and programmable nucleases to make precise modifications to genetic material, has provided enormous opportunities to advance biomedical research and promote human health. The application of these technologies in basic biomedical research has yielded significant advances in identifying and studying key molecular targets relevant to human diseases and their treatment. The clinical translation of genome editing techniques offers unprecedented biomedical engineering capabilities in the diagnosis, prevention, and treatment of disease or disability. Here, we provide a general summary of emerging biomedical applications of genome editing, including open challenges. We also summarize the tools of genome editing and the insights derived from their applications, hoping to accelerate new discoveries and therapies in biomedicine.
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Affiliation(s)
- Guanglei Li
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Xiangyang Li
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Songkuan Zhuang
- Department of Clinical Laboratory, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, 518035, China
| | - Liren Wang
- Shanghai Frontiers Science Research Base of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yifan Zhu
- Shanghai Frontiers Science Research Base of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, School of Life Sciences, East China Normal University, Shanghai, 200241, China
| | - Yangcan Chen
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China
| | - Wen Sun
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China
| | - Zeguang Wu
- Biomedical Pioneering Innovation Center, Beijing Advanced Innovation Center for Genomics, Peking-Tsinghua Center for Life Sciences, Peking University Genome Editing Research Center, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, 100871, China
| | - Zhuo Zhou
- Biomedical Pioneering Innovation Center, Beijing Advanced Innovation Center for Genomics, Peking-Tsinghua Center for Life Sciences, Peking University Genome Editing Research Center, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, 100871, China
| | - Jia Chen
- Gene Editing Center, School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
| | - Xingxu Huang
- School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China.
| | - Jin Wang
- Department of Clinical Laboratory, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People's Hospital, Shenzhen, 518035, China.
| | - Dali Li
- Shanghai Frontiers Science Research Base of Genome Editing and Cell Therapy, Shanghai Key Laboratory of Regulatory Biology, School of Life Sciences, East China Normal University, Shanghai, 200241, China.
| | - Wei Li
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China.
- Bejing Institute for Stem Cell and Regenerative Medicine, Beijing, 100101, China.
- HIT Center for Life Sciences, Harbin Institute of Technology, Harbin, 150001, China.
| | - Haoyi Wang
- State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
- Institute for Stem Cell and Regenerative Medicine, Chinese Academy of Sciences, Beijing, 100101, China.
| | - Wensheng Wei
- Biomedical Pioneering Innovation Center, Beijing Advanced Innovation Center for Genomics, Peking-Tsinghua Center for Life Sciences, Peking University Genome Editing Research Center, State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Peking University, Beijing, 100871, China.
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49
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New pathogenic insights from large animal models of neurodegenerative diseases. Protein Cell 2022; 13:707-720. [PMID: 35334073 PMCID: PMC9233730 DOI: 10.1007/s13238-022-00912-8] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 02/23/2022] [Indexed: 12/12/2022] Open
Abstract
Animal models are essential for investigating the pathogenesis and developing the treatment of human diseases. Identification of genetic mutations responsible for neurodegenerative diseases has enabled the creation of a large number of small animal models that mimic genetic defects found in the affected individuals. Of the current animal models, rodents with genetic modifications are the most commonly used animal models and provided important insights into pathogenesis. However, most of genetically modified rodent models lack overt neurodegeneration, imposing challenges and obstacles in utilizing them to rigorously test the therapeutic effects on neurodegeneration. Recent studies that used CRISPR/Cas9-targeted large animal (pigs and monkeys) have uncovered important pathological events that resemble neurodegeneration in the patient’s brain but could not be produced in small animal models. Here we highlight the unique nature of large animals to model neurodegenerative diseases as well as the limitations and challenges in establishing large animal models of neurodegenerative diseases, with focus on Huntington disease, Amyotrophic lateral sclerosis, and Parkinson diseases. We also discuss how to use the important pathogenic insights from large animal models to make rodent models more capable of recapitulating important pathological features of neurodegenerative diseases.
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50
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He J, Kleyman M, Chen J, Alikaya A, Rothenhoefer KM, Ozturk BE, Wirthlin M, Bostan AC, Fish K, Byrne LC, Pfenning AR, Stauffer WR. Transcriptional and anatomical diversity of medium spiny neurons in the primate striatum. Curr Biol 2021; 31:5473-5486.e6. [PMID: 34727523 PMCID: PMC9359438 DOI: 10.1016/j.cub.2021.10.015] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 09/17/2021] [Accepted: 10/06/2021] [Indexed: 10/20/2022]
Abstract
Medium spiny neurons (MSNs) constitute the vast majority of striatal neurons and the principal interface between dopamine reward signals and functionally diverse cortico-basal ganglia circuits. Information processing in these circuits is dependent on distinct MSN types: cell types that are traditionally defined according to their projection targets or dopamine receptor expression. Single-cell transcriptional studies have revealed greater MSN heterogeneity than predicted by traditional circuit models, but the transcriptional landscape in the primate striatum remains unknown. Here, we set out to establish molecular definitions for MSN subtypes in Rhesus monkeys and to explore the relationships between transcriptionally defined subtypes and anatomical subdivisions of the striatum. Our results suggest at least nine MSN subtypes, including dorsal striatum subtypes associated with striosome and matrix compartments, ventral striatum subtypes associated with the nucleus accumbens shell and olfactory tubercle, and an MSN-like cell type restricted to μ-opioid receptor rich islands in the ventral striatum. Although each subtype was demarcated by discontinuities in gene expression, continuous variation within subtypes defined gradients corresponding to anatomical locations and, potentially, functional specializations. These results lay the foundation for achieving cell-type-specific transgenesis in the primate striatum and provide a blueprint for investigating circuit-specific information processing.
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Affiliation(s)
- Jing He
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Michael Kleyman
- Department of Computational Biology, School of Computer Science, Neuroscience Institute, Center for the Neural Basis of Cognition, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
| | - Jianjiao Chen
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Aydin Alikaya
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Kathryn M Rothenhoefer
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Bilge Esin Ozturk
- Department of Ophthalmology, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Morgan Wirthlin
- Department of Computational Biology, School of Computer Science, Neuroscience Institute, Center for the Neural Basis of Cognition, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA
| | - Andreea C Bostan
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA
| | - Kenneth Fish
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Leah C Byrne
- Department of Ophthalmology, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, Pittsburgh, PA 15213, USA
| | - Andreas R Pfenning
- Department of Computational Biology, School of Computer Science, Neuroscience Institute, Center for the Neural Basis of Cognition, Carnegie Mellon University, 5000 Forbes Avenue, Pittsburgh, PA 15213, USA.
| | - William R Stauffer
- Department of Neurobiology, Systems Neuroscience Center, Brain Institute, Center for Neuroscience, Center for the Neural Basis of Cognition, University of Pittsburgh, 3501 Fifth Avenue, Pittsburgh, PA 15213, USA.
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