Features Of Hippocampal Astrocytic Domains And Their Spatial Relation To Excitatory And Inhibitory Neurons

Refaeli, Ron; Doron, A.; Benmelech-Chovav, Aviya; Groysman, Maya; Kreisel, Tirzah; Loewenstein, Yonatan; Goshen, Inbal

doi:10.1101/2020.05.25.114348

Cited by 9 publications

(10 citation statements)

References 39 publications

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“…To validate the spatial relationship between neurons and astrocytes, for each astrocyte the distance to the closest neuronal soma was calculated 13 ± 5 μm, ranging from 0.7 μm to 30 μm. The distribution falls within the range of literature observations, that is from 5 μm to 30 μm for three types of inhibitory neurons (Refaeli et al, 2020).…”

Section: Data Validation: Population-levelsupporting

confidence: 88%

Architecture of the Neuro-Glia-Vascular System

Zisis

Keller

Kanari

et al. 2021

Preprint

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Astrocytes connect the vasculature to neurons and mediate the supply of nutrients and biochemicals. They also remove metabolites from the neurons and extracellular environment. They are involved in a growing number of physiological and pathophysiological processes. Understanding the biophysical, physiological, and molecular interactions in this neuro-glia-vascular ensemble (NGV) and how they support brain function is severely restricted by the lack of detailed cytoarchitecture. To address this problem, we used data from multiple sources to create a data-driven digital reconstruction of the NGV at micrometer anatomical resolution. We reconstructed 0.2 mm3 of rat somatosensory cortical tissue with approximately 16000 morphologically detailed neurons, its microvasculature, and approximately 2500 morphologically detailed protoplasmic astrocytes. The consistency of the reconstruction with a wide array of experimental measurements allows novel predictions of the numbers and locations of astrocytes and astrocytic processes that support different types of neurons. This allows anatomical reconstruction of the spatial microdomains of astrocytes and their overlapping regions. The number and locations of end-feet connecting each astrocyte to the vasculature can be determined as well as the extent to which they cover the microvasculature. The structural analysis of the NGV circuit showed that astrocytic shape and numbers are constrained by vasculature’s spatial occupancy and their functional role to form NGV connections. The digital reconstruction of the NGV is a resource that will enable a better understanding of the anatomical principles and geometric constraints which govern how astrocytes support brain function.Table of contentsMain pointsThe Blue Brain Project digitally reconstructs a part of neocortical Neuro-Glia-Vascular organizationInterdependencies and topological methods allow dense in silico reconstruction from sparse experimental dataThe polarized role of protoplasmic astrocytes constrains their shapes and numbersTable of contents image

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Section: Data Validation: Population-levelsupporting

confidence: 88%

Architecture of the Neuro-Glia-Vascular System

Zisis

Keller

Kanari

et al. 2021

Preprint

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“…CellDART could precisely localize the cells, especially for CA1, CA2, CA3, dentate principal cells, and entorhinal cortex, which are known to be restricted in specific anatomical locations (Supplementary Figure S13) (37). Also, astrocytes are found to have high density in stratum oriens and stratum radiatum and oligodendrocytes in corpus callosum as previously reported (38)(39)(40). In short, CellDART can be applied to spatial transcriptome with different spatial resolution.…”

Section: Application Of Celldart In Slide-seq Datasupporting

confidence: 72%

“…The performance of CellDART was tested by modulating the number of markers in each cell cluster from 5 to 80 (5,10,20,40,80) which corresponds to the total number of markers from 109 to 1157 (109, 203, 364, 642, 1157). It showed that setting total number of markers between 300 and 400 leads to overall high AUC value (Supplementary Figure S2A).…”

Section: Optimal Parameter Selectionmentioning

confidence: 99%

CellDART: Cell type inference by domain adaptation of single-cell and spatial transcriptomic data

Bae

Koh

et al. 2021

Preprint

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Deciphering the cellular composition in genome-wide spatially resolved transcriptomic data is a critical task to clarify the spatial context of cells in a tissue. In this study, we developed a method, CellDART, which estimates the spatial distribution of cells defined by single-cell level data using domain adaptation of neural networks and applied it to the spatial mapping of human lung tissue. The neural network that predicts the cell proportion in a pseudospot, a virtual mixture of cells from single-cell data, is translated to decompose the cell types in each spatial barcoded region. First, CellDART was applied to mouse brain and human dorsolateral prefrontal cortex tissue to identify cell types with a layer-specific spatial distribution. Overall, the suggested approach was superior to the other computational methods in predicting the spatial localization of excitatory neurons. Furthermore, CellDART elucidated the cell type predominance defined by the human lung cell atlas across the lung tissue compartments and it corresponded to the known prevalent cell types. CellDART is expected to help to elucidate the spatial heterogeneity of cells and their close interactions in various tissues.

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“…Complementary to the analysis of astrocytes' complex spatiotemporal activity will be the accurate quantification of their three‐dimensional structure (e.g., territory, arborization, microdomain structure) and intracellular organelle distribution (e.g., mitochondria, ER) with respect to their surrounding environment (e.g., excitatory and inhibitory synapses, neuromodulatory fibers, neuronal cell types). For example, astrocytes are in close contact with various types of neurons or neuronal structures and exhibit diverse morphologies across layers and tissue regions (Eilam et al, 2016; Lanjakornsiripan et al, 2018; Refaeli et al, 2021). The complex morphology and cellular environment place fundamental constraints on what kinds of signals astrocytes can sense, how they can be integrated locally and globally, and which types of commands they can transmit to neurons.…”

Section: Relating Astrocyte Functions To Neural Circuit Operation And...mentioning

confidence: 99%

A perspective on astrocyte regulation of neural circuit function and animal behavior

Hirrlinger

Nimmerjahn

2022

Glia

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Studies over the past two decades have demonstrated that astrocytes are tightly associated with neurons and play pivotal roles in neural circuit development, operation, and adaptation in health and disease. Nevertheless, precisely how astrocytes integrate diverse neuronal signals, modulate neural circuit structure and function at multiple temporal and spatial scales, and influence animal behavior or disease through aberrant excitation and molecular output remains unclear. This Perspective discusses how new and state‐of‐the‐art approaches, including fluorescence indicators, opto‐ and chemogenetic actuators, genetic targeting tools, quantitative behavioral assays, and computational methods, might help resolve these longstanding questions. It also addresses complicating factors in interpreting astrocytes' role in neural circuit regulation and animal behavior, such as their heterogeneity, metabolism, and inter‐glial communication. Research on these questions should provide a deeper mechanistic understanding of astrocyte‐neuron assemblies' role in neural circuit function, complex behaviors, and disease.

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Features Of Hippocampal Astrocytic Domains And Their Spatial Relation To Excitatory And Inhibitory Neurons

Cited by 9 publications

References 39 publications

Architecture of the Neuro-Glia-Vascular System

Architecture of the Neuro-Glia-Vascular System

CellDART: Cell type inference by domain adaptation of single-cell and spatial transcriptomic data

A perspective on astrocyte regulation of neural circuit function and animal behavior

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