Cross-source proteogenomic profiling of human microglia reveals a conserved core membrane protein and HERV signature
Hoi Tong Wong, Charles GleasoniD, Andrew Boylan, Michelle J. AdleriD, Roman KosoyiD, John F. FullardiD, Elizabeth LevendoskyiD, Gabriel E. HoffmaniD, Henrik MolinaiD, Panos RoussosiD, Dusan BogunoviciD, Viviana R. SimoniD, Lubbertus C. F. MulderiD
Abstract
Microglia are essential immune cells of the brain parenchyma which are responsible for maintaining homeostasis and responding to brain injury. When activated, they induce immune signaling and become phagocytic. In the context of neurodegenerative diseases, they exhibit both pro- and anti-inflammatory properties. Human endogenous retroviruses (HERVs) are the remnants of ancient retroviral germline infections that integrated into the human genome, and their expression has been directly linked to microglial-mediated neurodegenerative diseases. Despite this, HERV expression is not consistently included in analyses characterizing microglia. Investigating the function of microglia across different diseases is critical for elucidating mechanisms of disease progression and for the development of effective therapeutic interventions. Approaches to studying microglia include isolation from post-mortem brain tissues, differentiation from peripheral blood monocytes or differentiation of induced pluripotent stem cells (iPSC). Ex vivo brain derived microglia (BdMG) are considered most physiologically relevant, but constraints including the unpredictable timing of availability, labor-intensive protocols, and low yields reduce their practicality. Existing alternatives are iPSC-derived microglia (iMG) and monocyte-derived microglia (MDMi) models that circumvent sample accessibility and scalability issues. Here, we explored the transcriptome and proteome of these three microglia sources and identified a common microglia surface marker expression profile, establishing that MDMi and iMG exhibit similar phenotypes relative to BdMG. We also identified a common HERV expression profile across BdMG, iMG and MDMi, indicating deeper similarities across different sources. Altogether, our findings indicate that given the phenotypic similarities of the 2 models, MDMi represent a practical and reliable model for investigating microglial function with iMG models serving for more molecular based approaches, such as CRISPRa/i.
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