Liu Songlei, Li Li, Zhang Fan, Garcia-Corral Mariana, Meyer Katharina, Fortuna Patrick R J, van Sambeek Björn, Appleton Evan, Ng Alex H M, Khoshakhlagh Parastoo, Lu Yuancheng Ryan, Cameron James, Ramirez Ricardo N, Chen Yuting, Wu Chun-Ting, Huang Jeremy Y, Tan Yuqi, Chao George, Aach John, Lim Elaine T, Tam Jenny M, Raychaudhuri Soumya, Church George M
Department of Genetics, Blavatnik Institute, Harvard Medical School, Boston, MA, USA.
Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA.
Nat Commun. 2025 Jun 10;16(1):5136. doi: 10.1038/s41467-025-59596-3.
Differentiation of induced pluripotent stem cells (iPSCs) into specialized cell types is essential for uncovering cell-type specific molecular mechanisms and interrogating cellular function. Transcription factor screens have enabled efficient production of a few cell types; however, engineering cell types that require complex transcription factor combinations remains challenging. Here, we report an iterative, high-throughput single-cell transcription factor screening method that enables the identification of transcription factor combinations for specialized cell differentiation, which we validated by differentiating human microglia-like cells. We found that the expression of six transcription factors, SPI1, CEBPA, FLI1, MEF2C, CEBPB, and IRF8, is sufficient to differentiate human iPSC into cells with transcriptional and functional similarity to primary human microglia within 4 days. Through this screening method, we also describe a novel computational method allowing the exploration of single-cell RNA sequencing data derived from transcription factor perturbation assays to construct causal gene regulatory networks for future cell fate engineering.
将诱导多能干细胞（iPSC）分化为特定细胞类型对于揭示细胞类型特异性分子机制和探究细胞功能至关重要。转录因子筛选已能够高效产生少数几种细胞类型；然而，工程化需要复杂转录因子组合的细胞类型仍然具有挑战性。在此，我们报告了一种迭代的高通量单细胞转录因子筛选方法，该方法能够鉴定用于特定细胞分化的转录因子组合，我们通过分化人小胶质细胞样细胞对其进行了验证。我们发现，六种转录因子SPI1、CEBPA、FLI1、MEF2C、CEBPB和IRF8的表达足以在4天内将人iPSC分化为与原代人小胶质细胞具有转录和功能相似性的细胞。通过这种筛选方法，我们还描述了一种新颖的计算方法，该方法允许探索源自转录因子扰动试验的单细胞RNA测序数据，以构建用于未来细胞命运工程的因果基因调控网络。
