By complementing transcriptomic data with spatially resolved proteomic insights, PL provides a unique opportunity to deepen the understanding of glial cell biology in health and disease.
Abstract
Glial cells, including radial glia, oligodendrocyte precursor cells (OPCs), oligodendrocytes, astrocytes, and microglia, are active and dynamic regulators of central nervous system (CNS) development, homeostasis, and disease. Through extensive interactions with neurons, other glial populations, and the vasculature, they form highly specialized communication networks that are essential for normal brain function. While transcriptomic approaches have revealed extensive glial heterogeneity and enabled the prediction of putative signaling networks, a critical challenge remains in validating and translating these findings at the level of distinct protein complexes existing both within and between the various glial cell types. This is largely due to the fact that traditional proteomic technologies lack spatial resolution and/or fail to capture protein interaction networks. Proximity labeling (PL) has emerged as a powerful strategy to overcome these limitations by enabling cell‐type‐specific mapping of protein networks and subcellular proteomes, with spatial and temporal precision. Emerging studies have applied PL enzymes, such as BioID, TurboID, and HRP, across diverse glial populations, starting to uncover protein networks supporting their interactions with neurons and vascular elements, allowing metabolic support, maintenance of microenvironment homeostasis and cell–cell communication (including synaptic modulation). In this review, we summarize the main PL enzymes, discuss key studies across different glial cell types, and examine the technical challenges and future perspectives of applying PL to investigate glial biology. By complementing transcriptomic data with spatially resolved proteomic insights, PL provides a unique opportunity to deepen our understanding of glial cell biology in health and disease.
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