Identification of astrocyte subtypes in the Drosophila melanogaster visual system
Year: 2022
Type: dissertation
Abstract: Astrocytes are the most abundant glia cell type and regulate synapse formation, maturation, and function. Though often studied as a single population, astrocytes are now recognized as encompassing a heterogeneous population. However, the genetic signatures and functional properties of distinct astrocyte populations remain poorly understood. Drosophila melanogaster is a good model for studying astrocytes on this level due to many available genetic tools and conserved astrocyte properties. Here, we establish a bioinformatics and quantitative immunohistochemistry pipeline to investigate heterogeneity within Drosophila astrocytes. We identify three genetic markers to classify astrocytes among unlabeled glia clusters in sc-RNAseq datasets from the Drosophila visual system. These markers alrm, Eaat1, and Gat separate astrocytes among various glial populations during pupal development but only Eaat1 and Gat reliably label astrocytes during adulthood. Using these markers, we identify two astrocyte clusters in both datasets and find these clusters have the highest correlations when comparing their genetic profiles. To validate these predictions, we first identify the transgenic line GMR86E01-Gal4 as a more effective line for labeling astrocytes of the adult fly than the commonly used alrm- Gal4. Antibody labeling of Eaat1 and Gat shows high colocalization to GMR86E01-Gal4, validating the use of these markers to identify astrocytes. We then sought to identify genetic differences between the predicted astrocyte clusters. A differential gene analysis identified 3 genes that are differentially expressed between predicted astrocyte pupal clusters and 30 genes differentially expressed between predicted adult astrocyte clusters. Overall, this work provides insights for identifying genetic signatures in astrocyte subtypes.
DOI: 10.17918/00001295
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4308077965