Glial Patchwork: Oligodendrocyte Progenitor Cells and Astrocytes Blanket the Central Nervous System

Barber, Heather M.; Ali, Maria F.; Kucenas, Sarah

doi:10.3389/fncel.2021.803057

Cited by 11 publications

(11 citation statements)

References 114 publications

(231 reference statements)

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“…Besides the practical utility, it is tempting to speculate about the possible scientific interpretation of our main finding. The systematically small ABEL values of glia suggest a tendency to optimize spatial occupancy, consistent with extensively reported tiling properties for these cells (Barber et al, 2021; Pogodalla et al, 2022). In contrast, the larger ABEL values of neurons are indicative of pressure to maximize spatial exploration, in line with the role of dendrites to integrate converging synaptic signals from multiple neural pathways (Anton-Sanchez et al, 2018; Stepanyants & Chklovskii, 2005).…”

Section: Discussionsupporting

confidence: 88%

Machine Learning Classification Reveals Robust Morphometric Biomarker of Glial and Neuronal Arbors

Akram

Wei

Ascoli

2022

Preprint

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Neurons and glia are the two main cell classes in the nervous systems of most animals. Although functionally distinct, neurons and glia are both characterized by multiple branching arbors stemming from the cell bodies. Glial processes are generally known to form smaller trees than neuronal dendrites. However, the full extent of morphological differences between neurons and glia in multiple species and brain regions has not yet been characterized, nor is it known whether these cells can be reliably distinguished based on geometric features alone. Here, we show that multiple supervised learning algorithms (K-nearest neighbor, random forest, and support vector machine) deployed on a large database of morphological reconstructions can systematically classify neuronal and glial arbors with nearly perfect accuracy and precision. Moreover, we report multiple morphometric properties, both size-related and size-independent, that differ substantially between these cell types. In particular, we newly identify an individual morphometric measurement, Average Branch Euclidean Length (ABEL) that can robustly separate neurons from glia across multiple animal models, a broad diversity of experimental conditions, and anatomical areas, with the notable exception of the cerebellum. We discuss the practical utility and physiological interpretation of this discovery.

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Section: Discussionsupporting

confidence: 88%

Machine Learning Classification Reveals Robust Morphometric Biomarker of Glial and Neuronal Arbors

Akram

Wei

Ascoli

2022

Preprint

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show abstract

“…Besides the practical utility, it is tempting to speculate about the possible scientific interpretation of our main finding. The systematically small ABEL values of glia suggest a tendency to optimize spatial occupancy, consistent with extensively reported tiling properties for these cells (Barber et al, 2021; Pogodalla et al, 2022). In contrast, the larger ABEL values of neurons are indicative of pressure to maximize spatial exploration, in line with the role of dendrites to integrate converging synaptic signals from multiple neural pathways (Anton‐Sanchez et al, 2018; Stepanyants & Chklovskii, 2005).…”

Section: Discussionsupporting

confidence: 87%

“…Besides the practical utility, it is tempting to speculate about the possible scientific interpretation of our main finding. The systematically small ABEL values of glia suggest a tendency to optimize spatial occupancy, consistent with extensively reported tiling properties for these cells (Barber et al, 2021;Pogodalla et al, 2022). In con- especially intriguing to consider the rare exceptions that emerged from our analysis.…”

Section: Spraguesupporting

confidence: 87%

Machine learning classification reveals robust morphometric biomarker of glial and neuronal arbors

Akram

Wei

Ascoli

2022

J of Neuroscience Research

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Neurons and glia are the two main cell classes in the nervous systems of most animals. Although functionally distinct, neurons and glia are both characterized by multiple branching arbors stemming from the cell bodies. Glial processes are generally known to form smaller trees than neuronal dendrites. However, the full extent of morphological differences between neurons and glia in multiple species and brain regions has not yet been characterized, nor is it known whether these cells can be reliably distinguished based on geometric features alone. Here, we show that multiple supervised learning algorithms deployed on a large database of morphological reconstructions can systematically classify neuronal and glial arbors with nearly perfect accuracy and precision. Moreover, we report multiple morphometric properties, both size related and size independent, that differ substantially between these cell types. In particular, we newly identify an individual morphometric measurement, Average Branch Euclidean Length that can robustly separate neurons from glia across multiple animal models, a broad diversity of experimental conditions, and anatomical areas, with the notable exception of the cerebellum. We discuss the practical utility and physiological interpretation of this discovery.

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“…An intriguing feature of OPCs is that despite being a proliferative precursor population with an intrinsic capacity for differentiation, they typically persist in quite large numbers even in the adult CNS tissue, where they are uniformly distributed in their own territories within both white and gray matter regions and homeostatically control their density (Barber et al, 2022). Nevertheless, the capacity of OPCs to divide and/or to generate new MOs declines with age and is altered in certain diseases and pathological conditions (Castro & Casaccia, 2018; Clayton & Tesar, 2021; Samudyata, Castelo‐Branco, & Liu, 2020).…”

Section: Introductionmentioning

confidence: 99%

Novel method of isolating nuclei of human oligodendrocyte precursor cells reveals substantial developmental changes in gene expression and H3K27ac histone modification

Kozlenkov,

Vadukapuram,

Zhou

et al. 2023

Glia

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Oligodendrocyte precursor cells (OPCs) generate differentiated mature oligodendrocytes (MOs) during development. In adult brain, OPCs replenish MOs in adaptive plasticity, neurodegenerative disorders, and after trauma. The ability of OPCs to differentiate to MOs decreases with age and is compromised in disease. Here we explored the cell specific and age‐dependent differences in gene expression and H3K27ac histone mark in these two cell types. H3K27ac is indicative of active promoters and enhancers. We developed a novel flow‐cytometry‐based approach to isolate OPC and MO nuclei from human postmortem brain and profiled gene expression and H3K27ac in adult and infant OPCs and MOs genome‐wide. In adult brain, we detected extensive H3K27ac differences between the two cell types with high concordance between gene expression and epigenetic changes. Notably, the expression of genes that distinguish MOs from OPCs appears to be under a strong regulatory control by the H3K27ac modification in MOs but not in OPCs. Comparison of gene expression and H3K27ac between infants and adults uncovered numerous developmental changes in each cell type, which were linked to several biological processes, including cell proliferation and glutamate signaling. A striking example was a subset of histone genes that were highly active in infant samples but fully lost activity in adult brain. Our findings demonstrate a considerable rearrangement of the H3K27ac landscape that occurs during the differentiation of OPCs to MOs and during postnatal development of these cell types, which aligned with changes in gene expression. The uncovered regulatory changes justify further in‐depth epigenetic studies of OPCs and MOs in development and disease.

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Glial Patchwork: Oligodendrocyte Progenitor Cells and Astrocytes Blanket the Central Nervous System

Cited by 11 publications

References 114 publications

Machine Learning Classification Reveals Robust Morphometric Biomarker of Glial and Neuronal Arbors

Machine Learning Classification Reveals Robust Morphometric Biomarker of Glial and Neuronal Arbors

Machine learning classification reveals robust morphometric biomarker of glial and neuronal arbors

Novel method of isolating nuclei of human oligodendrocyte precursor cells reveals substantial developmental changes in gene expression and H3K27ac histone modification

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