Single-cell analysis of immune cell fate decision making

描述（由申请人提供）：哺乳动物干细胞和祖细胞激活特定调控基因的表达来建立和稳定不同的细胞命运，但控制这一过程的机制和一般原理尚不清楚。细胞在发育过程中利用命运调控基因来建立和维持不同的命运身份，但它们如何激活和维持这些基因的表达来建立命运身份尚不清楚。在这里，我建议在两个系统的背景下研究这个问题：t细胞命运承诺，这是由t细胞特异性转录因子的激活驱动的

DESCRIPTION (provided by applicant): Mammalian stem and progenitor cells activate the expression of specific regulatory genes to establish and stabilize different cell fates, but the mechanisms and general principles controlling this process are not well understood. Cells utilize fate-specifying regulatory genes to establish and maintain distinct fate identities during development, but it is not clear how they activate and maintain the expression of these genes to establish fate identity. Here, I propose to study this question in the context of two systems: T-cell fate commitment, which is driven by the activation of the T-cell specific transcription factor Bcl11b (Aims 1 and 2); and macrophage development, which we recently found is driven by the cell-cycle length dependent accumulation of the myeloid transcription factor PU.1 (Kueh et al., 2013)1 (Aim 3). Using these two systems, I will test a number of widely debated ideas in the field of developmental gene regulation. First, I will test the idea that developmental signals directly activate the expression of regulatory genes to instruct cell fate (Aim 1). Next, I will tet two proposed classes of mechanisms for stabilizing regulatory gene expression and fate identity: cis-acting mechanisms involving stable and heritable epigenetic modifications at regulatory gene loci (Aim 2); and trans- acting mechanisms involving self-reinforcing positive feedback loops on regulatory gene expression (Aim 3). My main approach will be to use timelapse live-cell imaging to track the expression dynamics of Bcl11b during T-cell development, and PU.1 during macrophage development. As cell differentiation is a dynamic and intrinsically heterogeneous process, single-cell tracking by timelapse imaging will reveal insights that are difficult to obtain with conventional discrete time-point population measurements. To gain mechanistic insights, I will perturb the mechanisms under investigation, and measure their resultant effects using timelapse imaging. These perturbations will involve over-expression or knockdown of genes; for studies of cis-epigenetic mechanisms, I will also develop a CRISPr-based system for perturbing chromatin marks at specific sites in the genome. To better understand this experimental data, and generate predictions for future experiments, I will then use mathematical modeling to analyze the behavior and dynamics of the different regulatory mechanisms studied. Finally, I will complement these approaches with genome-wide measurements of gene expression states in developing cells using high throughput sequencing, which will provide a more global picture of developmental changes, and potentially yield new directions for future work. Through these studies, I hope to uncover fundamental insights into how mammalian cells establish and maintain their distinct fate identities. These insights will potentially help us develop new therapies for leukemia and other cancers, and help us better manipulate stem cells for regenerative medicine.