A CRISPRi/a platform in human iPSC-derived microglia uncovers regulators of disease states.
Nina M DrägerSydney M SattlerCindy Tzu-Ling HuangOlivia M TeterKun LengSayed Hadi HashemiJason HongGiovanni AvilesClaire Dudley ClellandLihong ZhanJoe C UdeochuLay KodamaAndrew B SingletonMike A NallsJustin IchidaMichael Emmerson WardFaraz FaghriLi GanMartin Edward KampmannPublished in: Nature neuroscience (2022)
Microglia are emerging as key drivers of neurological diseases. However, we lack a systematic understanding of the underlying mechanisms. Here, we present a screening platform to systematically elucidate functional consequences of genetic perturbations in human induced pluripotent stem cell-derived microglia. We developed an efficient 8-day protocol for the generation of microglia-like cells based on the inducible expression of six transcription factors. We established inducible CRISPR interference and activation in this system and conducted three screens targeting the 'druggable genome'. These screens uncovered genes controlling microglia survival, activation and phagocytosis, including neurodegeneration-associated genes. A screen with single-cell RNA sequencing as the readout revealed that these microglia adopt a spectrum of states mirroring those observed in human brains and identified regulators of these states. A disease-associated state characterized by osteopontin (SPP1) expression was selectively depleted by colony-stimulating factor-1 (CSF1R) inhibition. Thus, our platform can systematically uncover regulators of microglial states, enabling their functional characterization and therapeutic targeting.
Keyphrases
- genome wide
- inflammatory response
- high throughput
- single cell
- neuropathic pain
- endothelial cells
- transcription factor
- induced pluripotent stem cells
- poor prognosis
- lipopolysaccharide induced
- dna methylation
- high glucose
- randomized controlled trial
- rna seq
- spinal cord
- oxidative stress
- spinal cord injury
- gene expression
- genome wide identification
- blood brain barrier
- genome wide analysis