Single-cell deletion analyses show control of pro–T cell developmental speed and pathways by Tcf7, Spi1, Gata3, Bcl11a, Erg, and Bcl11b
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As early T cell precursors transition from multipotentiality to T lineage commitment, they change expression of multiple transcription factors. It is unclear whether individual transcription factors directly control choices between T cell identity and some alternative fate or whether these factors mostly affect proliferation or survival during the normal commitment process. Here, we unraveled the impacts of deleting individual transcription factors at two stages in early T cell development, using synchronized in vitro differentiation systems, single-cell RNA-seq with batch indexing, and controlled gene-disruption strategies. First, using a customized method for single-cell CRISPR disruption, we defined how the early-acting transcription factors Bcl11a, Erg, Spi1 (PU.1), Gata3, and Tcf7 (TCF1) function before commitment. The results revealed a kinetic tug of war within individual cells between T cell factors Tcf7 and Gata3 and progenitor factors Spi1 and Bcl11a, with an unexpected guidance role for Erg. Second, we tested how activation of transcription factor Bcl11b during commitment altered ongoing cellular programs. In knockout cells where Bcl11b expression was prevented, the cells did not undergo developmental arrest, instead following an alternative path as T lineage commitment was blocked. A stepwise, time-dependent regulatory cascade began with immediate-early transcription factor activation and E protein inhibition, finally leading Bcl11b knockout cells toward exit from the T cell pathway. Last, gene regulatory networks of transcription factor cross-regulation were extracted from the single-cell transcriptome results, characterizing the specification network operating before T lineage commitment and revealing its links to both the Bcl11b knockout alternative network and the network consolidating T cell identity during commitment.
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基因水平:PCR Array、RT-PCR、PCR、单细胞测序
蛋白水平:MSD、Luminex、CBA、Elispot、Antibody Array、ELISA、Sengenics
细胞水平:细胞染色、细胞分选、细胞培养、细胞功能
组织水平:空间多组学、多重荧光免疫组化、免疫组化、免疫荧光
数据分析:流式数据分析、组化数据分析、多因子数据分析
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