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Agerberg, J.

Publications and source records attributed to Agerberg, J..

2 recordsLinked to original sources

Chromatic topological mapping reveals organelle-specific spatial organization within microglia

In branched cells, including neurons and glia, intracellular organelles are distributed across complex cellular arbors where their spatial arrangement supports transport, signaling, and compartmentalized function. Although intracellular organelle organization is increasingly recognized as an important feature of cellular state and function, existing approaches assess organelle abundance or spatial position without accounting for the branching architecture that shapes cellular function. Here, we introduce the chromatic topological morphology descriptor (chromatic TMD), a framework that quantitatively resolves intracellular organization in relation to branching morphology. Applied to reconstructed microglia with annotated lysosomal and mitochondrial compartments across retinal layers and after optic nerve crush injury, chromatic TMD identifies distinct organelle-specific spatial programs: CD68+-endosomal-lysosomes undergo layer-dependent branch-specific redistribution, revealing selective intracellular reorganization after injury, whereas mitochondrial organization remains closely coupled to branching morphology. These findings establish intracellular organization as an additional layer of cellular architecture that can be systematically analyzed across branched neural cells.

neuroscience↗

Microglial MorphOMICs unravel region- and sex-dependent morphological phenotypes from postnatal development to degeneration

Microglia contribute to tissue homeostasis in physiological conditions with environmental cues influencing their ever-changing morphology. Strategies to identify these changes usually involve user-selected morphometric features, which, however, have proved ineffective in establishing a spectrum of context-dependent morphological phenotypes. Here, we have developed MorphOMICs, a topological data analysis approach to overcome feature-selection-based biases and biological variability. We extracted a spatially heterogeneous and sexually-dimorphic morphological phenotype for seven adult brain regions, with ovariectomized females forming their own distinct cluster. This sex-specific phenotype declines with maturation but increases over the disease trajectories in two neurodegeneration models, 5xFAD and CK-p25. Females show an earlier morphological shift in the immediately-affected brain regions. Finally, we demonstrate that both the primary- and the short terminal processes provide distinct insights to morphological phenotypes. MorphOMICs maps microglial morphology into a spectrum of cue-dependent phenotypes in a minimally-biased and semi-automatic way.

neuroscience↗