bioRxivImmunology
Predictive framework of macrophage activation
D. E. Sanin, Y. Ge, E. Marinkovic, A. M. Kabat, A. Castoldi, G. Caputa, K. M. Grzes, J. D. Curtis, S. Willenborg, S. Dichtl, S. Reinhardt, A. Dahl, E. L. Pearce, S. A. Eming, A. Gerbaulet, A. Roers, P. J. Murray, E. J. Pearce
Abstract
Macrophages populate every organ during homeostasis and disease, displaying features of tissue imprinting and heterogeneous activation. The disjointed picture of macrophage biology that emerged from these observations are a barrier for integration across models or with in vitro macrophage activation paradigms. We set out to contextualize macrophage heterogeneity across mouse tissues and inflammatory conditions, specifically aiming to define a common framework of macrophage activation. We built a predictive model with which we mapped the activation of macrophages across 12 tissues and 25 biological conditions, finding a striking commonality and finite number of transcriptional profiles, which we modelled as defined stages along four conserved activation paths. We verified this model with adoptive cell transfer experiments and identified transient RELM[a] expression as a feature of macrophage tissue engraftment. We propose that this integrative approach of macrophage classification allows the establishment of a common predictive framework of macrophage activation in inflammation and homeostasis. One Sentence SummaryWe propose an integrative approach of macrophage classification that allows the establishment of a common framework of macrophage activation in inflammation and homeostasis.
- organism: mouse
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: clustering
- approach: statistical model
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