Transcriptional regulation of disease-relevant microglial activation programs
McQuade, A.; Mishra, R.; Hagan, V.; Liang, W.; Colias, P.; Castillo, V. C.; Lubin, J.; Haage, V.; Marshe, V.; Fujita, M.; Gomes, L.; Ta, T.; Teter, O.; Chasins, S. E.; De Jager, P. L.; Nunez, J. K.; Kampmann, M.
Show abstract
Microglia, the brains innate immune cells, can adopt a wide variety of activation states relevant to health and disease. Dysregulation of microglial activation occurs in numerous brain disorders, and driving or inhibiting specific states could be therapeutic. To discover regulators of microglial activation states, we conducted CRISPR interference screens in iPSC-derived microglia for inhibitors and activators of six microglial states. We identified transcriptional regulators for each of these states and characterized 31 regulators at the single-cell transcriptomic and cell-surface proteome level in two distinct iPSC-derived microglia models. Finally, we functionally characterized several regulators. STAT2 knockdown inhibits interferon response and lysosomal function. PRDM1 knockdown drives disease-associated and lipid-rich signatures and enhanced phagocytosis. DNMT1 knockdown results in widespread loss of methylation, activating negative regulators of interferon signaling. These findings provide a framework to direct microglial activation to selectively enrich microglial activation states, define their functional outputs, and inform future therapies. HighlightsO_LICRISPRi screening reveals novel regulators of six microglia activation states C_LIO_LIMulti-modal single-cell screens highlight differences between mRNA and protein level expression C_LIO_LIiPSC-microglia models show different baseline distributions of activation states C_LIO_LILoss of DNMT1 leads to widespread DNA demethylation, promoting some states but limiting the interferon-response state C_LIO_LILoss of PRDM1 drives microglial disease-associated state C_LI
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Natural genetic variation determines microglia heterogeneity in wild-derived mouse models of Alzheimer's disease 97%
- Triglyceride metabolism controls inflammation and APOE4-associated disease states in microglia 96%
- Applying high-resolution spatial transcriptomics to characterise the amyloid plaque cell niche in Alzheimer's Disease 96%
Similar papers in this journal
Similar papers in this journal
- The Alzheimers Disease Risk Genes MS4A4A And MS4A6A Cooperate to Negatively Regulate Trem2 and Microglia states 97%
- A systems biology-based identification and in vivo functional screening of Alzheimer's disease risk genes reveals modulators of memory function 96%
- CRISPRi-based screens in iAssembloids to elucidate neuron-glia interactions 96%
Similar papers in this journal
- Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis 97%
- Distinct transcriptomic and epigenomic responses of mature oligodendrocytes during disease progression in a mouse model of multiple sclerosis 96%
- Molecular characterization of selectively vulnerable neurons in Alzheimer's Disease 96%
Similar papers in this journal
- Multimodal single-cell profiling reveals neuronal vulnerability and pathological cell states in focal cortical dysplasia 96%
- Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles 95%
- A myeloid program associated with COVID-19 severity is decreased by therapeutic blockade of IL-6 signaling 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.