Integrative multi‐omics for normal brain aging and Alzheimer’s Disease in Drosophila

Abstract

AbstractBackgroundNormal brain aging and Alzheimer’s Disease (AD) are both characterized by neurodegeneration and share many similarities. However, the mechanisms underlying both their similarities and differences remain largely unknown. Cell‐cell interactions mediate nearly all aspects of an organism’s physiology via cell‐surface proteins; as such, ∼70% of pharmaceutical drugs target cell‐surface proteins. Glial cells play many important roles in cell‐cell communication, plasticity, and immune function; thus, glial cell‐surface proteins present ideal novel biomarkers and drug targets. However, it remains difficult to profile glial cell‐surface proteins from intact brains, or to fully characterize gene expression changes during the progression of age‐related neurodegeneration. MethodTo investigate, we're fully characterizing how glial cells and their cell‐surface proteins differentially contribute to the progression of normal brain aging and AD, integrating state‐of‐the‐art in‐situ cell‐surface proteomics and high‐resolution single‐cell transcriptomics. Our study will be the first to apply in‐situ cell‐surface proteomics to glial cells in Drosophila, and the first to exhaustively profile and integrate the glial cell‐surface proteomes and single‐cell transcriptomes of both aging‐ and AD‐model flies. This will allow us to capture the “full picture” of how dysregulation of glial cell‐surface proteins differentially contributes to normal brain aging and AD, as changes in gene expression at the protein and mRNA levels often show considerable discrepancies.ResultIn total, our glial cell‐surface proteomics identified 872 proteins predicted to be involved in normal brain aging, and strong replicate correlations were observed. A Gene Ontology analysis revealed that most up‐regulated genes were associated with cell localization and transport, while most down‐regulated genes were associated with neural development, circuit organization, and neuroplasticity. We selected 48 candidate genes for further screening, based on which were the most up‐ and down‐regulated. Referencing our transcriptomic data, we found that 9/48 candidate genes identified by our cell‐surface proteomics also showed significant increases/decreases in expression levels, and selected 24 additional candidate genes for further screening.ConclusionCurrently, we are in the process of conducting several GOF/LOF genetic screens to investigate the effects of each candidate gene on lifespan. Based on preliminary data from our lifespan screens, we have identified 5 top candidate genes for further investigation.