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Wise DL, Escobedo-Lozoya Y, Valakh V, Gao EY, Bhonsle A, Lei QL, Cheng X, Greene SB, Van Hooser SD, Nelson SB. Prolonged Activity Deprivation Causes Pre- and Postsynaptic Compensatory Plasticity at Neocortical Excitatory Synapses. eNeuro 2024; 11:ENEURO.0366-23.2024. [PMID: 38777611 DOI: 10.1523/eneuro.0366-23.2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 05/10/2024] [Accepted: 05/15/2024] [Indexed: 05/25/2024] Open
Abstract
Homeostatic plasticity stabilizes firing rates of neurons, but the pressure to restore low activity rates can significantly alter synaptic and cellular properties. Most previous studies of homeostatic readjustment to complete activity silencing in rodent forebrain have examined changes after 2 d of deprivation, but it is known that longer periods of deprivation can produce adverse effects. To better understand the mechanisms underlying these effects and to address how presynaptic as well as postsynaptic compartments change during homeostatic plasticity, we subjected mouse cortical slice cultures to a more severe 5 d deprivation paradigm. We developed and validated a computational framework to measure the number and morphology of presynaptic and postsynaptic compartments from super-resolution light microscopy images of dense cortical tissue. Using these tools, combined with electrophysiological miniature excitatory postsynaptic current measurements, and synaptic imaging at the electron microscopy level, we assessed the functional and morphological results of prolonged deprivation. Excitatory synapses were strengthened both presynaptically and postsynaptically. Surprisingly, we also observed a decrement in the density of excitatory synapses, both as measured from colocalized staining of pre- and postsynaptic proteins in tissue and from the number of dendritic spines. Overall, our results suggest that cortical networks deprived of activity progressively move toward a smaller population of stronger synapses.
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Affiliation(s)
- Derek L Wise
- Department of Biology, Brandeis University, Waltham, Massachusetts 02454 9110
| | | | - Vera Valakh
- Department of Biology, Brandeis University, Waltham, Massachusetts 02454 9110
| | - Emma Y Gao
- Department of Biology, Brandeis University, Waltham, Massachusetts 02454 9110
| | - Aishwarya Bhonsle
- Department of Biology, Brandeis University, Waltham, Massachusetts 02454 9110
| | - Qian L Lei
- Department of Biology, Brandeis University, Waltham, Massachusetts 02454 9110
| | - Xinyu Cheng
- Department of Biology, Brandeis University, Waltham, Massachusetts 02454 9110
| | - Samuel B Greene
- Department of Biology, Brandeis University, Waltham, Massachusetts 02454 9110
| | | | - Sacha B Nelson
- Department of Biology, Brandeis University, Waltham, Massachusetts 02454 9110
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2
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Hickey JW, Becker WR, Nevins SA, Horning A, Perez AE, Zhu C, Zhu B, Wei B, Chiu R, Chen DC, Cotter DL, Esplin ED, Weimer AK, Caraccio C, Venkataraaman V, Schürch CM, Black S, Brbić M, Cao K, Chen S, Zhang W, Monte E, Zhang NR, Ma Z, Leskovec J, Zhang Z, Lin S, Longacre T, Plevritis SK, Lin Y, Nolan GP, Greenleaf WJ, Snyder M. Organization of the human intestine at single-cell resolution. Nature 2023; 619:572-584. [PMID: 37468586 PMCID: PMC10356619 DOI: 10.1038/s41586-023-05915-x] [Citation(s) in RCA: 34] [Impact Index Per Article: 34.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Accepted: 03/02/2023] [Indexed: 07/21/2023]
Abstract
The intestine is a complex organ that promotes digestion, extracts nutrients, participates in immune surveillance, maintains critical symbiotic relationships with microbiota and affects overall health1. The intesting has a length of over nine metres, along which there are differences in structure and function2. The localization of individual cell types, cell type development trajectories and detailed cell transcriptional programs probably drive these differences in function. Here, to better understand these differences, we evaluated the organization of single cells using multiplexed imaging and single-nucleus RNA and open chromatin assays across eight different intestinal sites from nine donors. Through systematic analyses, we find cell compositions that differ substantially across regions of the intestine and demonstrate the complexity of epithelial subtypes, and find that the same cell types are organized into distinct neighbourhoods and communities, highlighting distinct immunological niches that are present in the intestine. We also map gene regulatory differences in these cells that are suggestive of a regulatory differentiation cascade, and associate intestinal disease heritability with specific cell types. These results describe the complexity of the cell composition, regulation and organization for this organ, and serve as an important reference map for understanding human biology and disease.
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Affiliation(s)
- John W Hickey
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA
| | - Winston R Becker
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | | | - Aaron Horning
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Almudena Espin Perez
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Chenchen Zhu
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Bokai Zhu
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA
| | - Bei Wei
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Roxanne Chiu
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Derek C Chen
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Daniel L Cotter
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Edward D Esplin
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Annika K Weimer
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Chiara Caraccio
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA
| | | | - Christian M Schürch
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA
- Department of Pathology and Neuropathology, University Hospital and Comprehensive Cancer Center Tübingen, Tübingen, Germany
| | - Sarah Black
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA
| | - Maria Brbić
- Department of Computer Science, Stanford University, Stanford, CA, USA
- School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Kaidi Cao
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Shuxiao Chen
- Department of Statistics and Data Science, University of Pennsylvania, Pennsylvania, PA, USA
| | - Weiruo Zhang
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Emma Monte
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA
| | - Nancy R Zhang
- Department of Statistics and Data Science, University of Pennsylvania, Pennsylvania, PA, USA
| | - Zongming Ma
- Department of Statistics and Data Science, University of Pennsylvania, Pennsylvania, PA, USA
| | - Jure Leskovec
- Department of Computer Science, Stanford University, Stanford, CA, USA
| | - Zhengyan Zhang
- Department of Surgery, Washington University, St Louis, MO, USA
| | - Shin Lin
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Teri Longacre
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA
| | - Sylvia K Plevritis
- Department of Biomedical Data Science, Stanford School of Medicine, Stanford, CA, USA
| | - Yiing Lin
- Department of Surgery, Washington University, St Louis, MO, USA
| | - Garry P Nolan
- Department of Pathology, Stanford School of Medicine, Stanford, CA, USA.
| | | | - Michael Snyder
- Department of Genetics, Stanford School of Medicine, Stanford, CA, USA.
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3
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Tjahjono N, Jin Y, Hsu A, Roukes M, Tian L. Letting the little light of mind shine: Advances and future directions in neurochemical detection. Neurosci Res 2022; 179:65-78. [PMID: 34861294 PMCID: PMC9508992 DOI: 10.1016/j.neures.2021.11.012] [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] [Subscribe] [Scholar Register] [Received: 11/28/2021] [Accepted: 11/29/2021] [Indexed: 12/12/2022]
Abstract
Synaptic transmission via neurochemical release is the fundamental process that integrates and relays encoded information in the brain to regulate physiological function, cognition, and emotion. To unravel the biochemical, biophysical, and computational mechanisms of signal processing, one needs to precisely measure the neurochemical release dynamics with molecular and cell-type specificity and high resolution. Here we reviewed the development of analytical, electrochemical, and fluorescence imaging approaches to detect neurotransmitter and neuromodulator release. We discussed the advantages and practicality in implementation of each technology for ease-of-use, flexibility for multimodal studies, and challenges for future optimization. We hope this review will provide a versatile guide for tool engineering and applications for recording neurochemical release.
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Affiliation(s)
- Nikki Tjahjono
- Biomedical Engineering Graduate Group, University of California, Davis, Davis, CA, 95616, USA
| | - Yihan Jin
- Neuroscience Graduate Group, University of California, Davis, Davis, CA, 95618, USA
| | - Alice Hsu
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Michael Roukes
- Department of Physics, California Institute of Technology, Pasadena, CA, 91125, USA
| | - Lin Tian
- Department of Biochemistry and Molecular Medicine, School of Medicine, University of California, Davis, Davis, CA, 95616, USA.
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4
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Han W, Cheung AM, Yaffe MJ, Martel AL. Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training. Sci Rep 2022; 12:4399. [PMID: 35292693 PMCID: PMC8924193 DOI: 10.1038/s41598-022-08355-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 03/07/2022] [Indexed: 12/02/2022] Open
Abstract
Cellular profiling with multiplexed immunofluorescence (MxIF) images can contribute to a more accurate patient stratification for immunotherapy. Accurate cell segmentation of the MxIF images is an essential step. We propose a deep learning pipeline to train a Mask R-CNN model (deep network) for cell segmentation using nuclear (DAPI) and membrane (Na+K+ATPase) stained images. We used two-stage domain adaptation by first using a weakly labeled dataset followed by fine-tuning with a manually annotated dataset. We validated our method against manual annotations on three different datasets. Our method yields comparable results to the multi-observer agreement on an ovarian cancer dataset and improves on state-of-the-art performance on a publicly available dataset of mouse pancreatic tissues. Our proposed method, using a weakly labeled dataset for pre-training, showed superior performance in all of our experiments. When using smaller training sample sizes for fine-tuning, the proposed method provided comparable performance to that obtained using much larger training sample sizes. Our results demonstrate that using two-stage domain adaptation with a weakly labeled dataset can effectively boost system performance, especially when using a small training sample size. We deployed the model as a plug-in to CellProfiler, a widely used software platform for cellular image analysis.
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Affiliation(s)
- Wenchao Han
- Biomarker Imaging Research Laboratory, Sunnybrook Research Institute, Toronto, ON, Canada. .,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.
| | - Alison M Cheung
- Biomarker Imaging Research Laboratory, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Martin J Yaffe
- Biomarker Imaging Research Laboratory, Sunnybrook Research Institute, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Anne L Martel
- Biomarker Imaging Research Laboratory, Sunnybrook Research Institute, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
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5
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Hickey JW, Neumann EK, Radtke AJ, Camarillo JM, Beuschel RT, Albanese A, McDonough E, Hatler J, Wiblin AE, Fisher J, Croteau J, Small EC, Sood A, Caprioli RM, Angelo RM, Nolan GP, Chung K, Hewitt SM, Germain RN, Spraggins JM, Lundberg E, Snyder MP, Kelleher NL, Saka SK. Spatial mapping of protein composition and tissue organization: a primer for multiplexed antibody-based imaging. Nat Methods 2022; 19:284-295. [PMID: 34811556 PMCID: PMC9264278 DOI: 10.1038/s41592-021-01316-y] [Citation(s) in RCA: 134] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 09/15/2021] [Indexed: 02/07/2023]
Abstract
Tissues and organs are composed of distinct cell types that must operate in concert to perform physiological functions. Efforts to create high-dimensional biomarker catalogs of these cells have been largely based on single-cell sequencing approaches, which lack the spatial context required to understand critical cellular communication and correlated structural organization. To probe in situ biology with sufficient depth, several multiplexed protein imaging methods have been recently developed. Though these technologies differ in strategy and mode of immunolabeling and detection tags, they commonly utilize antibodies directed against protein biomarkers to provide detailed spatial and functional maps of complex tissues. As these promising antibody-based multiplexing approaches become more widely adopted, new frameworks and considerations are critical for training future users, generating molecular tools, validating antibody panels, and harmonizing datasets. In this Perspective, we provide essential resources, key considerations for obtaining robust and reproducible imaging data, and specialized knowledge from domain experts and technology developers.
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Affiliation(s)
- John W Hickey
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Elizabeth K Neumann
- Department of Biochemistry, Vanderbilt University, Nashville, TN, USA
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, USA
| | - Andrea J Radtke
- Lymphocyte Biology Section and Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA.
| | - Jeannie M Camarillo
- Departments of Chemistry, Molecular Biosciences and the National Resource for Translational and Developmental Proteomics, Northwestern University, Evanston, IL, USA
| | - Rebecca T Beuschel
- Lymphocyte Biology Section and Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Alexandre Albanese
- Institute for Medical Engineering and Science, MIT, Cambridge, MA, USA
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Boston Children's Hospital, Division of Hematology/Oncology, Boston, MA, USA
| | | | - Julia Hatler
- Antibody Development Department, Bio-Techne, Minneapolis, MN, USA
| | - Anne E Wiblin
- Department of Research and Development, Abcam, Cambridge, UK
| | - Jeremy Fisher
- Department of Research and Development, Cell Signaling Technology, Danvers, MA, USA
| | - Josh Croteau
- Department of Applications Science, BioLegend, San Diego, CA, USA
| | | | | | - Richard M Caprioli
- Department of Biochemistry, Vanderbilt University, Nashville, TN, USA
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, USA
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
| | - R Michael Angelo
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Garry P Nolan
- Department of Pathology, Stanford University School of Medicine, Stanford, CA, USA
| | - Kwanghun Chung
- Institute for Medical Engineering and Science, MIT, Cambridge, MA, USA
- Picower Institute for Learning and Memory, MIT, Cambridge, MA, USA
- Department of Chemical Engineering, MIT, Cambridge, MA, USA
- Department of Brain and Cognitive Sciences, MIT, Cambridge, MA, USA
- Center for Nanomedicine, Institute for Basic Science (IBS), Seoul, Republic of Korea
- Yonsei-IBS Institute, Yonsei University, Seoul, Republic of Korea
| | - Stephen M Hewitt
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Ronald N Germain
- Lymphocyte Biology Section and Center for Advanced Tissue Imaging, Laboratory of Immune System Biology, NIAID, NIH, Bethesda, MD, USA
| | - Jeffrey M Spraggins
- Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, USA
- Department of Chemistry, Vanderbilt University, Nashville, TN, USA
- Department of Cell and Developmental Biology, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Emma Lundberg
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH-Royal Institute of Technology, Stockholm, Sweden
| | - Michael P Snyder
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
| | - Neil L Kelleher
- Departments of Chemistry, Molecular Biosciences and the National Resource for Translational and Developmental Proteomics, Northwestern University, Evanston, IL, USA
| | - Sinem K Saka
- Wyss Institute for Biologically Inspired Engineering at Harvard University, Boston, MA, USA.
- European Molecular Biology Laboratory (EMBL), Genome Biology Unit, Heidelberg, Germany.
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6
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Guhathakurta D, Akdaş EY, Fejtová A, Weiss EM. Development and Application of Automatized Routines for Optical Analysis of Synaptic Activity Evoked by Chemical and Electrical Stimulation. FRONTIERS IN BIOINFORMATICS 2022; 2:814081. [PMID: 36304276 PMCID: PMC9580924 DOI: 10.3389/fbinf.2022.814081] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 01/24/2022] [Indexed: 11/24/2022] Open
Abstract
The recent development of cellular imaging techniques and the application of genetically encoded sensors of neuronal activity led to significant methodological progress in neurobiological studies. These methods often result in complex and large data sets consisting of image stacks or sets of multichannel fluorescent images. The detection of synapses, visualized by fluorescence labeling, is one major challenge in the analysis of these datasets, due to variations in synapse shape, size, and fluorescence intensity across the images. For their detection, most labs use manual or semi-manual techniques that are time-consuming and error-prone. We developed SynEdgeWs, a MATLAB-based segmentation algorithm that combines the application of an edge filter, morphological operators, and marker-controlled watershed segmentation. SynEdgeWs does not need training data and works with low user intervention. It was superior to methods based on cutoff thresholds and local maximum guided approaches in a realistic set of data. We implemented SynEdgeWs in two automatized routines that allow accurate, direct, and unbiased identification of fluorescently labeled synaptic puncta and their consecutive analysis. SynEval routine enables the analysis of three-channel images, and ImgSegRout routine processes image stacks. We tested the feasibility of ImgSegRout on a realistic live-cell imaging data set from experiments designed to monitor neurotransmitter release using synaptic phluorins. Finally, we applied SynEval to compare synaptic vesicle recycling evoked by electrical field stimulation and chemical depolarization in dissociated cortical cultures. Our data indicate that while the proportion of active synapses does not differ between stimulation modes, significantly more vesicles are mobilized upon chemical depolarization.
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Affiliation(s)
| | | | - Anna Fejtová
- *Correspondence: Anna Fejtová, ; Eva-Maria Weiss,
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7
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Tomov ML, O'Neil A, Abbasi HS, Cimini BA, Carpenter AE, Rubin LL, Bathe M. Resolving cell state in iPSC-derived human neural samples with multiplexed fluorescence imaging. Commun Biol 2021; 4:786. [PMID: 34168275 PMCID: PMC8225800 DOI: 10.1038/s42003-021-02276-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Accepted: 05/28/2021] [Indexed: 12/30/2022] Open
Abstract
Human induced pluripotent stem cell-derived (iPSC) neural cultures offer clinically relevant models of human diseases, including Amyotrophic Lateral Sclerosis, Alzheimer’s, and Autism Spectrum Disorder. In situ characterization of the spatial-temporal evolution of cell state in 3D culture and subsequent 2D dissociated culture models based on protein expression levels and localizations is essential to understanding neural cell differentiation, disease state phenotypes, and sample-to-sample variability. Here, we apply PRobe-based Imaging for Sequential Multiplexing (PRISM) to facilitate multiplexed imaging with facile, rapid exchange of imaging probes to analyze iPSC-derived cortical and motor neuron cultures that are relevant to psychiatric and neurodegenerative disease models, using over ten protein targets. Our approach permits analysis of cell differentiation, cell composition, and functional marker expression in complex stem-cell derived neural cultures. Furthermore, our approach is amenable to automation, offering in principle the ability to scale-up to dozens of protein targets and samples. Tomov et al. utilize DNA-PRISM to allow for multiplexed imaging of cultured cells using antibodies modified with oligonucleotide probes. The differentiation of iPSCs to cortical and motor neurons is characterized in model cultures, relevant for use in disease research and drug screening.
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Affiliation(s)
- Martin L Tomov
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.,Department of Biological Engineering, MIT, Cambridge, MA, USA
| | - Alison O'Neil
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.,Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA
| | - Hamdah S Abbasi
- Imaging Platform at Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Beth A Cimini
- Imaging Platform at Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Anne E Carpenter
- Imaging Platform at Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lee L Rubin
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA. .,Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA.
| | - Mark Bathe
- Department of Biological Engineering, MIT, Cambridge, MA, USA.
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8
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Costamagna G, Comi GP, Corti S. Advancing Drug Discovery for Neurological Disorders Using iPSC-Derived Neural Organoids. Int J Mol Sci 2021; 22:ijms22052659. [PMID: 33800815 PMCID: PMC7961877 DOI: 10.3390/ijms22052659] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Revised: 03/01/2021] [Accepted: 03/03/2021] [Indexed: 12/15/2022] Open
Abstract
In the last decade, different research groups in the academic setting have developed induced pluripotent stem cell-based protocols to generate three-dimensional, multicellular, neural organoids. Their use to model brain biology, early neural development, and human diseases has provided new insights into the pathophysiology of neuropsychiatric and neurological disorders, including microcephaly, autism, Parkinson’s disease, and Alzheimer’s disease. However, the adoption of organoid technology for large-scale drug screening in the industry has been hampered by challenges with reproducibility, scalability, and translatability to human disease. Potential technical solutions to expand their use in drug discovery pipelines include Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) to create isogenic models, single-cell RNA sequencing to characterize the model at a cellular level, and machine learning to analyze complex data sets. In addition, high-content imaging, automated liquid handling, and standardized assays represent other valuable tools toward this goal. Though several open issues still hamper the full implementation of the organoid technology outside academia, rapid progress in this field will help to prompt its translation toward large-scale drug screening for neurological disorders.
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Affiliation(s)
- Gianluca Costamagna
- Dino Ferrari Centre, Department of Pathophysiology and Transplantation (DEPT), Neuroscience Section, University of Milan, 20122 Milan, Italy; (G.C.); (G.P.C.)
- IRCCS Foundation Ca’ Granda Ospedale Maggiore Policlinico, Neurology Unit, Via Francesco Sforza 35, 20122 Milan, Italy
| | - Giacomo Pietro Comi
- Dino Ferrari Centre, Department of Pathophysiology and Transplantation (DEPT), Neuroscience Section, University of Milan, 20122 Milan, Italy; (G.C.); (G.P.C.)
- IRCCS Foundation Ca’ Granda Ospedale Maggiore Policlinico, Neurology Unit, Via Francesco Sforza 35, 20122 Milan, Italy
| | - Stefania Corti
- Dino Ferrari Centre, Department of Pathophysiology and Transplantation (DEPT), Neuroscience Section, University of Milan, 20122 Milan, Italy; (G.C.); (G.P.C.)
- IRCCS Foundation Ca’ Granda Ospedale Maggiore Policlinico, Neurology Unit, Via Francesco Sforza 35, 20122 Milan, Italy
- Correspondence:
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9
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Minehart JA, Speer CM. A Picture Worth a Thousand Molecules-Integrative Technologies for Mapping Subcellular Molecular Organization and Plasticity in Developing Circuits. Front Synaptic Neurosci 2021; 12:615059. [PMID: 33469427 PMCID: PMC7813761 DOI: 10.3389/fnsyn.2020.615059] [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: 10/08/2020] [Accepted: 12/07/2020] [Indexed: 12/23/2022] Open
Abstract
A key challenge in developmental neuroscience is identifying the local regulatory mechanisms that control neurite and synaptic refinement over large brain volumes. Innovative molecular techniques and high-resolution imaging tools are beginning to reshape our view of how local protein translation in subcellular compartments drives axonal, dendritic, and synaptic development and plasticity. Here we review recent progress in three areas of neurite and synaptic study in situ-compartment-specific transcriptomics/translatomics, targeted proteomics, and super-resolution imaging analysis of synaptic organization and development. We discuss synergies between sequencing and imaging techniques for the discovery and validation of local molecular signaling mechanisms regulating synaptic development, plasticity, and maintenance in circuits.
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Affiliation(s)
| | - Colenso M. Speer
- Department of Biology, University of Maryland, College Park, MD, United States
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10
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Wang Y, Wang C, Ranefall P, Broussard GJ, Wang Y, Shi G, Lyu B, Wu CT, Wang Y, Tian L, Yu G. SynQuant: an automatic tool to quantify synapses from microscopy images. Bioinformatics 2020; 36:1599-1606. [PMID: 31596456 DOI: 10.1093/bioinformatics/btz760] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Revised: 09/25/2019] [Accepted: 10/03/2019] [Indexed: 11/14/2022] Open
Abstract
MOTIVATION Synapses are essential to neural signal transmission. Therefore, quantification of synapses and related neurites from images is vital to gain insights into the underlying pathways of brain functionality and diseases. Despite the wide availability of synaptic punctum imaging data, several issues are impeding satisfactory quantification of these structures by current tools. First, the antibodies used for labeling synapses are not perfectly specific to synapses. These antibodies may exist in neurites or other cell compartments. Second, the brightness of different neurites and synaptic puncta is heterogeneous due to the variation of antibody concentration and synapse-intrinsic differences. Third, images often have low signal to noise ratio due to constraints of experiment facilities and availability of sensitive antibodies. These issues make the detection of synapses challenging and necessitates developing a new tool to easily and accurately quantify synapses. RESULTS We present an automatic probability-principled synapse detection algorithm and integrate it into our synapse quantification tool SynQuant. Derived from the theory of order statistics, our method controls the false discovery rate and improves the power of detecting synapses. SynQuant is unsupervised, works for both 2D and 3D data, and can handle multiple staining channels. Through extensive experiments on one synthetic and three real datasets with ground truth annotation or manually labeling, SynQuant was demonstrated to outperform peer specialized unsupervised synapse detection tools as well as generic spot detection methods. AVAILABILITY AND IMPLEMENTATION Java source code, Fiji plug-in, and test data are available at https://github.com/yu-lab-vt/SynQuant. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Yizhi Wang
- Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 22203, USA
| | - Congchao Wang
- Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 22203, USA
| | - Petter Ranefall
- Centre for Image Analysis and SciLifeLab, Department of Information Technology, Uppsala University, Uppsala, Sweden
| | - Gerard Joey Broussard
- Department of Molecular Biology and Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08544, USA
| | - Yinxue Wang
- Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 22203, USA
| | - Guilai Shi
- Department of Biochemistry and Molecular Medicine, University of California Davis School of Medicine, Sacramento, CA 95817, USA
| | - Boyu Lyu
- Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 22203, USA
| | - Chiung-Ting Wu
- Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 22203, USA
| | - Yue Wang
- Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 22203, USA
| | - Lin Tian
- Department of Biochemistry and Molecular Medicine, University of California Davis School of Medicine, Sacramento, CA 95817, USA
| | - Guoqiang Yu
- Bradley Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 22203, USA
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Salick MR, Lubeck E, Riesselman A, Kaykas A. The future of cerebral organoids in drug discovery. Semin Cell Dev Biol 2020; 111:67-73. [PMID: 32654970 DOI: 10.1016/j.semcdb.2020.05.024] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Revised: 04/28/2020] [Accepted: 05/27/2020] [Indexed: 12/27/2022]
Abstract
Until the discovery of human embryonic stem cells and human induced pluripotent stem cells, biotechnology companies were severely limited in the number of human tissues that they could model in large-scale in vitro studies. Until this point, companies have been limited to immortalized cancer lines or a small number of primary cell types that could be extracted and expanded. Nowadays, protocols continue to be developed in the stem cell field, enabling researchers to model an ever-growing library of cell types in controlled, large-scale screens. One differentiation method in particular- cerebral organoids- shows substantial potential in the field of neuroscience and developmental neurobiology. Cerebral organoid technology is still in an early phase of development, and there are several challenges that are currently being addressed by academic and industrial researchers alike. Here we briefly describe some of the early adopters of cerebral organoids, several of the challenges that they are likely facing, and various technologies that are currently being implemented to overcome them.
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Affiliation(s)
- Max R Salick
- insitro 279 East Grand Avenue South, San Francisco CA, United States
| | - Eric Lubeck
- insitro 279 East Grand Avenue South, San Francisco CA, United States
| | - Adam Riesselman
- insitro 279 East Grand Avenue South, San Francisco CA, United States
| | - Ajamete Kaykas
- insitro 279 East Grand Avenue South, San Francisco CA, United States
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