A dynamic and multimodal framework to define microglial states

Abstract

The widespread use of single-cell RNA sequencing has generated numerous purportedly distinct and novel subsets of microglia. Here, we challenge this fragmented paradigm by proposing that microglia exist along a continuum rather than as discrete entities. We identify a methodological over-reliance on computational clustering algorithms as the fundamental issue, with arbitrary cluster numbers being interpreted as biological reality. Evidence suggests that the observed transcriptional diversity stems from a combination of microglial plasticity and technical noise, resulting in terminology describing largely overlapping cellular states. We introduce a continuous model of microglial states, where cell positioning along the continuum is determined by biological aging and cell-specific molecular contexts. The model accommodates the dynamic nature of microglia. We advocate for a parsimonious approach toward classification and terminology that acknowledges the continuous spectrum of microglial states, toward a robust framework for understanding these essential immune cells of the CNS.