Identifying glial cell‐surface proteins critical in normal brain aging

Abstract

AbstractBackgroundGlial cells play a variety of supportive functions to facilitate effective neural communication, including maintaining an effective immune response, myelination of axons, and maintaining extracellular homeostasis. Glia also display age‐related transcriptomic and morphological alterations, and glial cell metabolism is altered in Alzheimer’s Disease (AD). Fully characterizing age‐related alterations to the cell‐surface proteosome of glial cells in both healthy and pathogenic forms of brain aging could provide further insight into how neuron‐glia interactions facilitate brain aging and identify novel biomarkers and treatment targets of AD.MethodWe performed tissue‐specific in‐situ cell surface proteomics on young (5‐day old) and aged (50‐day old) D. melanogaster utilizing the protocol developed by Li et al. (2020) with the Repo driver to target glial cells. From this, we identified 19 genes of interest with the most significant age‐related increase in protein expression and performed a broad genetic screen to identify how knockdown of genes upregulated with age in glial cells impacted fly lifespan. For this, we utilized the Repo‐GS‐UAS system to screen several transgenic D. melanogaster RNAi lines for the genes of interest, with 2‐3 RNAi lines per gene.ResultBased on a Gene Ontology (GO) analysis of the most upregulated candidate genes, we observed that most were associated with cell localization and transport. Additionally, from our preliminary screen, we have identified five top candidate genes of interest that, when knocked down, appear to increase average fly lifespan relative to the controls. Currently, we are in the process of validating the initial lifespan results, repeating lifespan screens of the top candidate genes in a new glial GS line and a glial Gal4 line.ConclusionWe have identified genes that appear to extend lifespan when knocked down and could serve as targets for further study. These results can provide a basis of understanding healthy brain aging and could serve as a basis of comparison to AD models.