Department of Haematology, Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom.
Department of Haematology, Wellcome Trust-Medical Research Council Cambridge Stem Cell Institute, University of Cambridge, Cambridge Institute for Medical Research, Cambridge CB2 0XY, United Kingdom
Proc Natl Acad Sci U S A. 2017 Jun 6;114(23):5822-5829. doi: 10.1073/pnas.1610609114.
Adult blood contains a mixture of mature cell types, each with specialized functions. Single hematopoietic stem cells (HSCs) have been functionally shown to generate all mature cell types for the lifetime of the organism. Differentiation of HSCs toward alternative lineages must be balanced at the population level by the fate decisions made by individual cells. Transcription factors play a key role in regulating these decisions and operate within organized regulatory programs that can be modeled as transcriptional regulatory networks. As dysregulation of single HSC fate decisions is linked to fatal malignancies such as leukemia, it is important to understand how these decisions are controlled on a cell-by-cell basis. Here we developed and applied a network inference method, exploiting the ability to infer dynamic information from single-cell snapshot expression data based on expression profiles of 48 genes in 2,167 blood stem and progenitor cells. This approach allowed us to infer transcriptional regulatory network models that recapitulated differentiation of HSCs into progenitor cell types, focusing on trajectories toward megakaryocyte-erythrocyte progenitors and lymphoid-primed multipotent progenitors. By comparing these two models, we identified and subsequently experimentally validated a difference in the regulation of nuclear factor, erythroid 2 () and core-binding factor, runt domain, alpha subunit 2, translocated to, 3 homolog () by the transcription factor Gata2. Our approach confirms known aspects of hematopoiesis, provides hypotheses about regulation of HSC differentiation, and is widely applicable to other hierarchical biological systems to uncover regulatory relationships.
成人血液中含有多种成熟细胞类型，每种细胞类型都具有特定的功能。功能上已证实，单个造血干细胞（HSCs）可在生物体的整个生命周期中生成所有成熟细胞类型。HSCs 向替代谱系的分化必须通过单个细胞做出的命运决定在群体水平上保持平衡。转录因子在调节这些决定中起着关键作用，并在可以建模为转录调控网络的组织化调控程序内发挥作用。由于单个 HSC 命运决定的失调与白血病等致命恶性肿瘤有关，因此了解这些决定如何在单细胞基础上得到控制非常重要。在这里，我们开发并应用了一种网络推断方法，利用了根据 2167 个血液干细胞和祖细胞中 48 个基因的表达谱从单细胞快照表达数据推断动态信息的能力。这种方法使我们能够推断转录调控网络模型，这些模型再现了 HSCs 向祖细胞类型的分化，重点关注向巨核细胞-红细胞祖细胞和淋巴样-多能祖细胞的轨迹。通过比较这两个模型，我们确定并随后通过实验验证了转录因子 Gata2 对核因子、红细胞 2（）和核心结合因子、 runt 结构域、α亚基 2、易位到、3 同源物（）的调节存在差异。我们的方法证实了造血的已知方面，提供了关于 HSC 分化调控的假设，并广泛适用于其他分层生物系统，以揭示调控关系。
