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Rui Y, Zhang M, Lee DM, Snyder VC, Raghuraman R, Gofas-Salas E, Mecê P, Yadav S, Tiruveedhula P, Grieve K, Sahel JA, Errera MH, Rossi EA. Label-Free Imaging of Inflammation at the Level of Single Cells in the Living Human Eye. OPHTHALMOLOGY SCIENCE 2024; 4:100475. [PMID: 38881602 PMCID: PMC11179426 DOI: 10.1016/j.xops.2024.100475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 12/22/2023] [Accepted: 01/16/2024] [Indexed: 06/18/2024]
Abstract
Purpose Putative microglia were recently detected using adaptive optics ophthalmoscopy in healthy eyes. Here we evaluate the use of nonconfocal adaptive optics scanning light ophthalmoscopy (AOSLO) for quantifying the morphology and motility of presumed microglia and other immune cells in eyes with retinal inflammation from uveitis and healthy eyes. Design Observational exploratory study. Participants Twelve participants were imaged, including 8 healthy participants and 4 posterior uveitis patients recruited from the clinic of 1 of the authors (M.H.E.). Methods The Pittsburgh AOSLO imaging system was used with a custom-designed 7-fiber optical fiber bundle for simultaneous confocal and nonconfocal multioffset detection. The inner retina was imaged at several locations at multiple timepoints in healthy participants and uveitis patients to generate time-lapse images. Main Outcome Measures Microglia and macrophages were manually segmented from nonconfocal AOSLO images, and their morphological characteristics quantified (including soma size, diameter, and circularity). Cell soma motion was quantified across time for periods of up to 30 minutes and their speeds were calculated by measuring their displacement over time. Results A spectrum of cell morphologies was detected in healthy eyes from circular amoeboid cells to elongated cells with visible processes, resembling activated and ramified microglia, respectively. Average soma diameter was 16.1 ± 0.9 μm. Cell movement was slow in healthy eyes (0.02 μm/sec on average), but macrophage-like cells moved rapidly in some uveitis patients (up to 3 μm/sec). In an eye with infectious uveitis, many macrophage-like cells were detected; during treatment their quantity and motility decreased as vision improved. Conclusions In vivo adaptive optics ophthalmoscopy offers promise as a potentially powerful tool for detecting and monitoring inflammation and response to treatment at a cellular level in the living eye. Financial Disclosures Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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Affiliation(s)
- Yuhua Rui
- Department of Ophthalmology, University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania
- Eye Center of Xiangya Hospital, Central South University Hunan Key Laboratory of Ophthalmology Changsha, Hunan, China
| | - Min Zhang
- Department of Ophthalmology, University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania
| | - Daniel M.W. Lee
- Department of Bioengineering, University of Pittsburgh Swanson School of Engineering Pittsburgh, Pennsylvania
| | - Valerie C. Snyder
- Department of Ophthalmology, University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania
| | - Rashmi Raghuraman
- Department of Ophthalmology, University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania
| | - Elena Gofas-Salas
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
- CHNO des Quinze-Vingts, INSERM-DGOS CIC 1423, Paris, France
| | - Pedro Mecê
- Institut Langevin, ESPCI Paris, Université PSL, CNRS, Paris, France
| | - Sanya Yadav
- Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania
| | | | - Kate Grieve
- Sorbonne Université, INSERM, CNRS, Institut de la Vision, Paris, France
- CHNO des Quinze-Vingts, INSERM-DGOS CIC 1423, Paris, France
| | - José-Alain Sahel
- Department of Ophthalmology, University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania
| | - Marie-Hélène Errera
- Department of Ophthalmology, University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania
| | - Ethan A. Rossi
- Department of Ophthalmology, University of Pittsburgh School of Medicine Pittsburgh, Pennsylvania
- Department of Bioengineering, University of Pittsburgh Swanson School of Engineering Pittsburgh, Pennsylvania
- McGowan Institute for Regenerative Medicine Pittsburgh, Pennsylvania
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2
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Petillo E, Veneruso V, Gragnaniello G, Brochier L, Frigerio E, Perale G, Rossi F, Cardia A, Orro A, Veglianese P. Targeted therapy and deep learning insights into microglia modulation for spinal cord injury. Mater Today Bio 2024; 27:101117. [PMID: 38975239 PMCID: PMC11225820 DOI: 10.1016/j.mtbio.2024.101117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 05/31/2024] [Accepted: 06/08/2024] [Indexed: 07/09/2024] Open
Abstract
Spinal cord injury (SCI) is a devastating condition that can cause significant motor and sensory impairment. Microglia, the central nervous system's immune sentinels, are known to be promising therapeutic targets in both SCI and neurodegenerative diseases. The most effective way to deliver medications and control microglial inflammation is through nanovectors; however, because of the variability in microglial morphology and the lack of standardized techniques, it is still difficult to precisely measure their activation in preclinical models. This problem is especially important in SCI, where the intricacy of the glia response following traumatic events necessitates the use of a sophisticated method to automatically discern between various microglial cell activation states that vary over time and space as the secondary injury progresses. We address this issue by proposing a deep learning-based technique for quantifying microglial activation following drug-loaded nanovector treatment in a preclinical SCI model. Our method uses a convolutional neural network to segment and classify microglia based on morphological characteristics. Our approach's accuracy and efficiency are demonstrated through evaluation on a collection of histology pictures from injured and intact spinal cords. This robust computational technique has potential for analyzing microglial activation across various neuropathologies and demonstrating the usefulness of nanovectors in modifying microglia in SCI and other neurological disorders. It has the ability to speed development in this crucial sector by providing a standardized and objective way to compare therapeutic options.
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Affiliation(s)
- Emilia Petillo
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, via Mario Negri 2, Milano 20156, Italy
- Department of Chemistry, Materials and Chemical Engineering “Giulio Natta”, Politecnico di Milano, via Mancinelli 7, Milano 20131, Italy
| | - Valeria Veneruso
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, via Mario Negri 2, Milano 20156, Italy
- Faculty of Biomedical Sciences, Università della Svizzera Italiana, via Buffi 13, Lugano 6900, Switzerland
| | - Gianluca Gragnaniello
- Department of Biomedical Sciences, Italian National Research Council, Institute of Biomedical Technologies, Segrate 20054, Italy
| | - Lorenzo Brochier
- Department of Biomedical Sciences, Italian National Research Council, Institute of Biomedical Technologies, Segrate 20054, Italy
| | - Enrico Frigerio
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, via Mario Negri 2, Milano 20156, Italy
| | - Giuseppe Perale
- Faculty of Biomedical Sciences, Università della Svizzera Italiana, via Buffi 13, Lugano 6900, Switzerland
- Ludwig Boltzmann Institute for Experimental and Clinical Traumatology, Donaueschingenstrasse 13, 1200 Vienna, Austria
- Regenera GmbH, Modecenterstrasse 22/D01, 1030 Vienna, Austria
| | - Filippo Rossi
- Department of Chemistry, Materials and Chemical Engineering “Giulio Natta”, Politecnico di Milano, via Mancinelli 7, Milano 20131, Italy
| | - Andrea Cardia
- Department of Neurosurgery, Neurocenter of the Southern Switzerland, Regional Hospital of Lugano, Ente Ospedaliero Cantonale (EOC), Lugano, Switzerland
| | - Alessandro Orro
- Department of Biomedical Sciences, Italian National Research Council, Institute of Biomedical Technologies, Segrate 20054, Italy
| | - Pietro Veglianese
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, via Mario Negri 2, Milano 20156, Italy
- Faculty of Biomedical Sciences, Università della Svizzera Italiana, via Buffi 13, Lugano 6900, Switzerland
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3
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Hoyer-Kimura C, Hay M, Konhilas JP, Morrison HW, Methajit M, Strom J, Polt R, Salcedo V, Fricks JP, Kalya A, Pires PW. PNA5, A Novel Mas Receptor Agonist, Improves Neurovascular and Blood-Brain-Barrier Function in a Mouse Model of Vascular Cognitive Impairment and Dementia. Aging Dis 2024; 15:1927-1951. [PMID: 37815905 PMCID: PMC11272189 DOI: 10.14336/ad.2023.0928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 09/28/2023] [Indexed: 10/12/2023] Open
Abstract
It is well established that decreased brain blood flow, increased reactive oxygen species production (ROS), and pro-inflammatory mechanisms accelerate neurodegenerative disease progressions, including vascular cognitive impairment and dementia (VCID). Previous studies in our laboratory have shown that our novel glycosylated Angiotensin-(1-7) Mas receptor agonist PNA5 reverses cognitive deficits, decreases ROS production, and inhibits inflammatory cytokine production in our preclinical mouse model of VCID that is induced by chronic heart failure (VCID-HF). In the present study, the effects of VCID-HF and treatment with PNA5 on microglia activation, blood-brain-barrier (BBB) integrity, and neurovascular coupling were assessed in our mouse model of VCID-HF. Three-month-old male C57BL/6J mice were subjected to myocardial infarction (MI) to induce heart failure for four weeks and then treated with subcutaneous injections of extended-release PNA5. Microglia activation, BBB permeability, cerebral perfusion, and neurovascular coupling were assessed. Results show that in our VCID-HF model, there was an increase in microglial activation and recruitment within the CA1 and CA3 regions of the hippocampus, a disruption in BBB integrity, and a decrease in neurovascular coupling. Treatment with PNA5 reversed these neuropathological effects of VCID-HF, suggesting that PNA5 may be an effective disease-modifying therapy to treat and prevent VCID. This study identifies potential mechanisms by which heart failure may induce VCID and highlights the possible mechanisms by which treatment with our novel glycosylated Angiotensin-(1-7) Mas receptor agonist, PNA5, may protect cognitive function in our model of VCID.
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Affiliation(s)
| | - Meredith Hay
- Department of Physiology, The University of Arizona, Tucson, AZ 85724, USA.
- Evelyn F. McKnight Brain Institute, The University of Arizona, Tucson, AZ 85724, USA.
- ProNeurogen, Inc, Tucson, AZ, USA
| | - John P Konhilas
- Department of Physiology, The University of Arizona, Tucson, AZ 85724, USA.
| | - Helena W Morrison
- College of Nursing, The University of Arizona, Tucson, AZ 85724, USA.
| | - Methawasin Methajit
- Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85724, USA.
| | - Joshua Strom
- Department of Cellular and Molecular Medicine, The University of Arizona, Tucson, AZ 85724, USA.
| | - Robin Polt
- Department of Chemistry and Biochemistry, The University of Arizona, Tucson, AZ 85724, USA.
| | - Victoria Salcedo
- Department of Physiology, The University of Arizona, Tucson, AZ 85724, USA.
| | | | - Anjna Kalya
- Department of Physiology, The University of Arizona, Tucson, AZ 85724, USA.
| | - Paulo W Pires
- Department of Physiology, The University of Arizona, Tucson, AZ 85724, USA.
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Strohm AO, Majewska AK. Physical exercise regulates microglia in health and disease. Front Neurosci 2024; 18:1420322. [PMID: 38911597 PMCID: PMC11192042 DOI: 10.3389/fnins.2024.1420322] [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: 04/19/2024] [Accepted: 05/20/2024] [Indexed: 06/25/2024] Open
Abstract
There is a well-established link between physical activity and brain health. As such, the effectiveness of physical exercise as a therapeutic strategy has been explored in a variety of neurological contexts. To determine the extent to which physical exercise could be most beneficial under different circumstances, studies are needed to uncover the underlying mechanisms behind the benefits of physical activity. Interest has grown in understanding how physical activity can regulate microglia, the resident immune cells of the central nervous system. Microglia are key mediators of neuroinflammatory processes and play a role in maintaining brain homeostasis in healthy and pathological settings. Here, we explore the evidence suggesting that physical activity has the potential to regulate microglia activity in various animal models. We emphasize key areas where future research could contribute to uncovering the therapeutic benefits of engaging in physical exercise.
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Affiliation(s)
- Alexandra O. Strohm
- Department of Environmental Medicine, University of Rochester Medical Center, Rochester, NY, United States
| | - Ania K. Majewska
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, United States
- Del Monte Institute for Neuroscience, University of Rochester Medical Center, Rochester, NY, United States
- Center for Visual Science, University of Rochester Medical Center, Rochester, NY, United States
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5
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Sancho L, Boisvert MM, Dawoodtabar T, Burgado J, Wang E, Allen NJ. Astrocyte CCN1 stabilizes neural circuits in the adult brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.14.585077. [PMID: 38559139 PMCID: PMC10979986 DOI: 10.1101/2024.03.14.585077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Neural circuits in many brain regions are refined by experience. Sensory circuits support higher plasticity at younger ages during critical periods - times of circuit refinement and maturation - and limit plasticity in adulthood for circuit stability. The mechanisms underlying these differing plasticity levels and how they serve to maintain and stabilize the properties of sensory circuits remain largely unclear. By combining a transcriptomic approach with ex vivo electrophysiology and in vivo imaging techniques, we identify that astrocytes release cellular communication network factor 1 (CCN1) to maintain synapse and circuit stability in the visual cortex. By overexpressing CCN1 in critical period astrocytes, we find that it promotes the maturation of inhibitory circuits and limits ocular dominance plasticity. Conversely, by knocking out astrocyte CCN1 in adults, binocular circuits are destabilized. These studies establish CCN1 as a novel astrocyte-secreted factor that stabilizes neuronal circuits. Moreover, they demonstrate that the composition and properties of sensory circuits require ongoing maintenance in adulthood, and that these maintenance cues are provided by astrocytes.
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6
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Fernandez ME, Martinez-Romero J, Aon MA, Bernier M, Price NL, de Cabo R. How is Big Data reshaping preclinical aging research? Lab Anim (NY) 2023; 52:289-314. [PMID: 38017182 DOI: 10.1038/s41684-023-01286-y] [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: 05/24/2023] [Accepted: 10/10/2023] [Indexed: 11/30/2023]
Abstract
The exponential scientific and technological progress during the past 30 years has favored the comprehensive characterization of aging processes with their multivariate nature, leading to the advent of Big Data in preclinical aging research. Spanning from molecular omics to organism-level deep phenotyping, Big Data demands large computational resources for storage and analysis, as well as new analytical tools and conceptual frameworks to gain novel insights leading to discovery. Systems biology has emerged as a paradigm that utilizes Big Data to gain insightful information enabling a better understanding of living organisms, visualized as multilayered networks of interacting molecules, cells, tissues and organs at different spatiotemporal scales. In this framework, where aging, health and disease represent emergent states from an evolving dynamic complex system, context given by, for example, strain, sex and feeding times, becomes paramount for defining the biological trajectory of an organism. Using bioinformatics and artificial intelligence, the systems biology approach is leading to remarkable advances in our understanding of the underlying mechanism of aging biology and assisting in creative experimental study designs in animal models. Future in-depth knowledge acquisition will depend on the ability to fully integrate information from different spatiotemporal scales in organisms, which will probably require the adoption of theories and methods from the field of complex systems. Here we review state-of-the-art approaches in preclinical research, with a focus on rodent models, that are leading to conceptual and/or technical advances in leveraging Big Data to understand basic aging biology and its full translational potential.
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Affiliation(s)
- Maria Emilia Fernandez
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Jorge Martinez-Romero
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Miguel A Aon
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- Laboratory of Cardiovascular Science, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Michel Bernier
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Nathan L Price
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Rafael de Cabo
- Experimental Gerontology Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA.
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Reddaway J, Richardson PE, Bevan RJ, Stoneman J, Palombo M. Microglial morphometric analysis: so many options, so little consistency. Front Neuroinform 2023; 17:1211188. [PMID: 37637472 PMCID: PMC10448193 DOI: 10.3389/fninf.2023.1211188] [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: 04/25/2023] [Accepted: 07/05/2023] [Indexed: 08/29/2023] Open
Abstract
Quantification of microglial activation through morphometric analysis has long been a staple of the neuroimmunologist's toolkit. Microglial morphological phenomics can be conducted through either manual classification or constructing a digital skeleton and extracting morphometric data from it. Multiple open-access and paid software packages are available to generate these skeletons via semi-automated and/or fully automated methods with varying degrees of accuracy. Despite advancements in methods to generate morphometrics (quantitative measures of cellular morphology), there has been limited development of tools to analyze the datasets they generate, in particular those containing parameters from tens of thousands of cells analyzed by fully automated pipelines. In this review, we compare and critique the approaches using cluster analysis and machine learning driven predictive algorithms that have been developed to tackle these large datasets, and propose improvements for these methods. In particular, we highlight the need for a commitment to open science from groups developing these classifiers. Furthermore, we call attention to a need for communication between those with a strong software engineering/computer science background and neuroimmunologists to produce effective analytical tools with simplified operability if we are to see their wide-spread adoption by the glia biology community.
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Affiliation(s)
- Jack Reddaway
- Division of Neuroscience, School of Biosciences, Cardiff University, Cardiff, United Kingdom
- Hodge Centre for Neuropsychiatric Immunology, Neuroscience and Mental Health Innovation Institute (NMHII), Cardiff University, Cardiff, United Kingdom
| | | | - Ryan J. Bevan
- UK Dementia Research Institute, Cardiff University, Cardiff, United Kingdom
| | - Jessica Stoneman
- Division of Neuroscience, School of Biosciences, Cardiff University, Cardiff, United Kingdom
| | - Marco Palombo
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, United Kingdom
- School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom
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8
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Anwer DM, Gubinelli F, Kurt YA, Sarauskyte L, Jacobs F, Venuti C, Sandoval IM, Yang Y, Stancati J, Mazzocchi M, Brandi E, O’Keeffe G, Steece-Collier K, Li JY, Deierborg T, Manfredsson FP, Davidsson M, Heuer A. A comparison of machine learning approaches for the quantification of microglial cells in the brain of mice, rats and non-human primates. PLoS One 2023; 18:e0284480. [PMID: 37126506 PMCID: PMC10150977 DOI: 10.1371/journal.pone.0284480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Accepted: 03/31/2023] [Indexed: 05/02/2023] Open
Abstract
Microglial cells are brain-specific macrophages that swiftly react to disruptive events in the brain. Microglial activation leads to specific modifications, including proliferation, morphological changes, migration to the site of insult, and changes in gene expression profiles. A change in inflammatory status has been linked to many neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease. For this reason, the investigation and quantification of microglial cells is essential for better understanding their role in disease progression as well as for evaluating the cytocompatibility of novel therapeutic approaches for such conditions. In the following study we implemented a machine learning-based approach for the fast and automatized quantification of microglial cells; this tool was compared with manual quantification (ground truth), and with alternative free-ware such as the threshold-based ImageJ and the machine learning-based Ilastik. We first trained the algorithms on brain tissue obtained from rats and non-human primate immunohistochemically labelled for microglia. Subsequently we validated the accuracy of the trained algorithms in a preclinical rodent model of Parkinson's disease and demonstrated the robustness of the algorithms on tissue obtained from mice, as well as from images provided by three collaborating laboratories. Our results indicate that machine learning algorithms can detect and quantify microglial cells in all the three mammalian species in a precise manner, equipotent to the one observed following manual counting. Using this tool, we were able to detect and quantify small changes between the hemispheres, suggesting the power and reliability of the algorithm. Such a tool will be very useful for investigation of microglial response in disease development, as well as in the investigation of compatible novel therapeutics targeting the brain. As all network weights and labelled training data are made available, together with our step-by-step user guide, we anticipate that many laboratories will implement machine learning-based quantification of microglial cells in their research.
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Affiliation(s)
- Danish M. Anwer
- Behavioural Neuroscience Laboratory, Department of Experimental Medical Sciences, Lund University Lund, Sweden
| | - Francesco Gubinelli
- Behavioural Neuroscience Laboratory, Department of Experimental Medical Sciences, Lund University Lund, Sweden
| | - Yunus A. Kurt
- Behavioural Neuroscience Laboratory, Department of Experimental Medical Sciences, Lund University Lund, Sweden
| | - Livija Sarauskyte
- Behavioural Neuroscience Laboratory, Department of Experimental Medical Sciences, Lund University Lund, Sweden
| | - Febe Jacobs
- Behavioural Neuroscience Laboratory, Department of Experimental Medical Sciences, Lund University Lund, Sweden
| | - Chiara Venuti
- Behavioural Neuroscience Laboratory, Department of Experimental Medical Sciences, Lund University Lund, Sweden
| | - Ivette M. Sandoval
- Barrow Neurological Institute, Parkinson’s Disease Research Unit, Department of Translational Neuroscience, Phoenix, Arizona, United States of America
| | - Yiyi Yang
- Experimental Neuroinflammation Laboratory, Department of Experimental Medical Sciences, Lund University, Lund, Sweden
| | - Jennifer Stancati
- Translational Neuroscience, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States of America
| | - Martina Mazzocchi
- Brain Development and Repair Group, Department of Anatomy and Neuroscience University College Cork, Cork, Ireland
| | - Edoardo Brandi
- Neural Plasticity and Repair, Department of Experimental Medical Sciences, Lund University, Lund, Sweden
| | - Gerard O’Keeffe
- Brain Development and Repair Group, Department of Anatomy and Neuroscience University College Cork, Cork, Ireland
| | - Kathy Steece-Collier
- Translational Neuroscience, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States of America
| | - Jia-Yi Li
- Neural Plasticity and Repair, Department of Experimental Medical Sciences, Lund University, Lund, Sweden
| | - Tomas Deierborg
- Experimental Neuroinflammation Laboratory, Department of Experimental Medical Sciences, Lund University, Lund, Sweden
| | - Fredric P. Manfredsson
- Barrow Neurological Institute, Parkinson’s Disease Research Unit, Department of Translational Neuroscience, Phoenix, Arizona, United States of America
| | - Marcus Davidsson
- Behavioural Neuroscience Laboratory, Department of Experimental Medical Sciences, Lund University Lund, Sweden
- Barrow Neurological Institute, Parkinson’s Disease Research Unit, Department of Translational Neuroscience, Phoenix, Arizona, United States of America
| | - Andreas Heuer
- Behavioural Neuroscience Laboratory, Department of Experimental Medical Sciences, Lund University Lund, Sweden
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Costello A, Linning-Duffy K, Vandenbrook C, Lonstein JS, Yan L. Daytime Light Deficiency Leads to Sex- and Brain Region-Specific Neuroinflammatory Responses in a Diurnal Rodent. Cell Mol Neurobiol 2023; 43:1369-1384. [PMID: 35864429 PMCID: PMC10635710 DOI: 10.1007/s10571-022-01256-x] [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: 03/15/2022] [Accepted: 07/07/2022] [Indexed: 11/30/2022]
Abstract
Seasonal changes in peripheral inflammation are well documented in both humans and animal models, but seasonal changes in neuroinflammation, especially the impact of seasonal lighting environment on neuroinflammation remain unclear. To address this question, the present study examined the effects of environmental lighting conditions on neuroinflammation in a diurnal rodent model, Nile grass rats (Arvicanthis niloticus). Male and female grass rats were housed in either bright (brLD) or dim (dimLD) light during the day to simulate a summer or winter light condition, respectively. After 4 weeks, microglia markers Iba-1 and CD11b, as well as pro-inflammatory cytokines TNF-α and IL-6, were examined in the anterior cingulate cortex (ACC), basolateral amygdala (BLA), and dorsal hippocampus (dHipp). The results revealed that winter-like dim light during the day leads to indicators of increased neuroinflammation in a brain site- and sex-specific manner. Specifically, relatively few changes in the neuroinflammatory markers were observed in the ACC, while numerous changes were found in the BLA and dHipp. In the BLA, winter-like dimLD resulted in hyper-ramified microglia morphology and increased expression of the pro-inflammatory cytokine IL-6, but only in males. In the dHipp, dimLD led to a higher number and hyper-ramified morphology of microglia as well as increased expression of CD11b and TNF-α, but only in females. Neuroinflammatory state is thus influenced by environmental light, differently in males and females, and could play a role in sex differences in the prevalence and symptoms of psychiatric or neurological disorders that are influenced by season or other environmental light conditions. Diurnal Nile grass rats were housed under bright or dim light during the day for 4 weeks, simulating seasonal fluctuations in daytime lighting environment. Dim light housing resulted in hyper-ramified morphology of microglia (scale bar, 15 μm) and altered expression of pro-inflammatory cytokines (TNF-α) in a sex- and brain region-specific manner.
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Affiliation(s)
- Allison Costello
- Behavioral Neuroscience Program, Department of Psychology, Michigan State University, 766, Service Road, East Lansing, MI, 48824, USA
| | - Katrina Linning-Duffy
- Behavioral Neuroscience Program, Department of Psychology, Michigan State University, 766, Service Road, East Lansing, MI, 48824, USA
| | - Carleigh Vandenbrook
- Behavioral Neuroscience Program, Department of Psychology, Michigan State University, 766, Service Road, East Lansing, MI, 48824, USA
| | - Joseph S Lonstein
- Behavioral Neuroscience Program, Department of Psychology, Michigan State University, 766, Service Road, East Lansing, MI, 48824, USA
- Neuroscience Program, Michigan State University, East Lansing, MI, 48824, USA
| | - Lily Yan
- Behavioral Neuroscience Program, Department of Psychology, Michigan State University, 766, Service Road, East Lansing, MI, 48824, USA.
- Neuroscience Program, Michigan State University, East Lansing, MI, 48824, USA.
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10
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Melo P, S Silveira M, Mendes-Pinto I, Relvas JB. MorphoMacro for in vivo and ex vivo quantitative morphometric analysis of microglia. Methods Cell Biol 2023; 174:75-92. [PMID: 36710053 DOI: 10.1016/bs.mcb.2022.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Microglia cells dynamically survey the central nervous system microenvironment and, in response to tissue damage inflicted by radiation therapy, disease or infection, undergo morphological and functional changes that culminate in microglia activation. Cell shape transformation can be assessed descriptively or, alternatively, it can be quantified as a continuous variable for parameters including total cell size as well as protrusion length, ramification and complexity. The purpose of the MorphoMacro method is to quantitatively profile multiple and single microglia cells using the available ImageJ platform. This method outlines the required steps and ImageJ plugins to convert fluorescence and bright-field photomicrographs into representative binary and skeletonized images and to analyze them using the MorphoMacro software plugin for multiparametric and multilevel description of microglia cell morphology in vivo and ex vivo. Overall, the protocol provides a quantitative and comprehensive tool that can be used to identify, stratify, and monitor diverse microglia morphologies in homeostatic, different disease conditions and subsequent therapeutic monitoring.
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Affiliation(s)
- Pedro Melo
- Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto, Porto, Portugal
| | - Mariana S Silveira
- Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto, Porto, Portugal; Instituto de Biofísica Carlos Chagas Filho, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil
| | - Inês Mendes-Pinto
- Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto, Porto, Portugal.
| | - João B Relvas
- Instituto de Investigação e Inovação em Saúde (i3S), Universidade do Porto, Porto, Portugal; Departmento de Biomedicina, Faculdade de Medicina, Universidade do Porto, Porto, Portugal.
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Hsueh SC, Scerba MT, Tweedie D, Lecca D, Kim DS, Baig AM, Kim YK, Hwang I, Kim S, Selman WR, Hoffer BJ, Greig NH. Activity of a Novel Anti-Inflammatory Agent F-3,6'-dithiopomalidomide as a Treatment for Traumatic Brain Injury. Biomedicines 2022; 10:2449. [PMID: 36289711 PMCID: PMC9598880 DOI: 10.3390/biomedicines10102449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2022] [Revised: 09/01/2022] [Accepted: 09/17/2022] [Indexed: 11/16/2022] Open
Abstract
Traumatic brain injury (TBI) is a major risk factor for several neurodegenerative disorders, including Parkinson's disease (PD) and Alzheimer's disease (AD). Neuroinflammation is a cause of later secondary cell death following TBI, has the potential to aggravate the initial impact, and provides a therapeutic target, albeit that has failed to translate into clinical trial success. Thalidomide-like compounds have neuroinflammation reduction properties across cellular and animal models of TBI and neurodegenerative disorders. They lower the generation of proinflammatory cytokines, particularly TNF-α which is pivotal in microglial cell activation. Unfortunately, thalidomide-like drugs possess adverse effects in humans before achieving anti-inflammatory drug levels. We developed F-3,6'-dithiopomalidomide (F-3,6'-DP) as a novel thalidomide-like compound to ameliorate inflammation. F-3,6'-DP binds to cereblon but does not efficiently trigger the degradation of the transcription factors (SALL4, Ikaros, and Aiolos) associated with the teratogenic and anti-proliferative responses of thalidomide-like drugs. We utilized a phenotypic drug discovery approach that employed cellular and animal models in the selection and development of F-3,6'-DP. F-3,6'-DP significantly mitigated LPS-induced inflammatory markers in RAW 264.7 cells, and lowered proinflammatory cytokine/chemokine levels in the plasma and brain of rats challenged with systemic LPS. We subsequently examined immunohistochemical, biochemical, and behavioral measures following controlled cortical impact (CCI) in mice, a model of moderate TBI known to induce inflammation. F-3,6'-DP decreased CCI-induced neuroinflammation, neuronal loss, and behavioral deficits when administered after TBI. F-3,6'-DP represents a novel class of thalidomide-like drugs that do not lower classical cereblon-associated transcription factors but retain anti-inflammatory actions and possess efficacy in the treatment of TBI and potentially longer-term neurodegenerative disorders.
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Affiliation(s)
- Shih Chang Hsueh
- Drug Design & Development Section, Translational Gerontology Branch, Intramural Research Program National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Michael T. Scerba
- Drug Design & Development Section, Translational Gerontology Branch, Intramural Research Program National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - David Tweedie
- Drug Design & Development Section, Translational Gerontology Branch, Intramural Research Program National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Daniela Lecca
- Drug Design & Development Section, Translational Gerontology Branch, Intramural Research Program National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Dong Seok Kim
- AevisBio, Inc., Gaithersburg, MD 20878, USA
- Aevis Bio, Inc., Daejeon 34141, Korea
| | - Abdul Mannan Baig
- Department of Biological and Biomedical Sciences, Aga Khan University, Karachi 74800, Pakistan
| | | | | | - Sun Kim
- Aevis Bio, Inc., Daejeon 34141, Korea
| | - Warren R. Selman
- Department of Neurological Surgery, Case Western Reserve University and University Hospitals, Cleveland, OH 44106, USA
| | - Barry J. Hoffer
- Department of Neurological Surgery, Case Western Reserve University and University Hospitals, Cleveland, OH 44106, USA
| | - Nigel H. Greig
- Drug Design & Development Section, Translational Gerontology Branch, Intramural Research Program National Institute on Aging, NIH, Baltimore, MD 21224, USA
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