4.6 Article

Quantifying Glial-Glial Tiling Using Automated Image Analysis in Drosophila

期刊

FRONTIERS IN CELLULAR NEUROSCIENCE
卷 16, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fncel.2022.826483

关键词

glia; tiling; Drosophila; morphology; astrocytes; automated image analysis; cortex glia; glial-glial interaction

资金

  1. National Institute of Neurological Disorders and Stroke [R01NS121101]
  2. Summer Neuroscience Undergraduate Research Award
  3. NSF [DBI 1560180]
  4. UVM FOUR Summer Research Award
  5. UVM OVPR EXPRESS Grant

向作者/读者索取更多资源

This study explores the interaction between astrocytes and cortex glial cells in Drosophila, using an automated analysis pipeline. The results demonstrate a significant correlation between dysfunction in cortex glial cells and aberrant infiltration of astrocytes, as well as variations in their relationship across different regions of the central nervous system.
Not only do glia form close associations with neurons throughout the central nervous system (CNS), but glial cells also interact closely with other glial cells. As these cells mature, they undergo a phenomenon known as glial tiling, where they grow to abut one another, often without invading each other's boundaries. Glial tiling occurs throughout the animal kingdom, from fruit flies to humans; however, not much is known about the glial-glial interactions that lead to and maintain this tiling. Drosophila provide a strong model to investigate glial-glial tiling, where tiling occurs both among individual glial cells of the same subtype, as well as between those of different subtypes. Furthermore, the spatial segregation of the CNS allows for the unique ability to visualize and manipulate inter-subtype interactions. Previous work in Drosophila has suggested an interaction between cortex glia and astrocytes, where astrocytes cross the normal neuropil-cortex boundary in response to dysfunctional cortex glia. Here, we further explore this interaction by implementing an automated pipeline to more fully characterize this astrocyte-cortex glial relationship. By quantifying and correlating the extent of cortex glial dysfunction and aberrant astrocyte infiltration using automated analysis, we maximize the size of the quantified dataset to reveal subtle patterns in astrocyte-cortex glial interactions. We provide a guide for creating and validating a fully-automated image analysis pipeline for exploring these interactions, and implement this pipeline to describe a significant correlation between cortex glial dysfunction and aberrant astrocyte infiltration, as well as demonstrate variations in their relationship across different regions of the CNS.

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