Tian Tianhai, Smith-Miles Kate
BMC Syst Biol. 2014;8 Suppl 1(Suppl 1):S8. doi: 10.1186/1752-0509-8-S1-S8. Epub 2014 Jan 24.
Hematopoiesis is a highly orchestrated developmental process that comprises various developmental stages of the hematopoietic stem cells (HSCs). During development, the decision to leave the self-renewing state and selection of a differentiation pathway is regulated by a number of transcription factors. Among them, genes GATA-1 and PU.1 form a core negative feedback module to regulate the genetic switching between the cell fate choices of HSCs. Although extensive experimental studies have revealed the mechanisms to regulate the expression of these two genes, it is still unclear how this simple module regulates the genetic switching.
In this work we proposed a mathematical model to study the mechanisms of the GATA-PU.1 gene network in the determination of HSC differentiation pathways. We incorporated the mechanisms of GATA switch into the module, and developed a mathematical model that comprises three genes GATA-1, GATA-2 and PU.1. In addition, a novel multiple-objective optimization method was designed to infer unknown parameters in the proposed model by realizing different experimental observations. A stochastic model was also designed to describe the critical function of noise, due to the small copy numbers of molecular species, in determining the differentiation pathways.
The proposed deterministic model has successfully realized three stable steady states representing the priming and different progenitor cells as well as genetic switching between the genetic states under various experimental conditions. Using different values of GATA-1 synthesis rate for the GATA-1 protein availability in the chromatin sites during the time period of GATA switch, stochastic simulations for the first time have realized different proportions of cells leading to different developmental pathways under various experimental conditions.
Mathematical models provide testable predictions regarding the mechanisms and conditions for realizing different differentiation pathways of hematopoietic stem cells. This work represents the first attempt at using a discrete stochastic model to realize the decision of HSC differentiation pathways showing a multimodal distribution.
造血作用是一个高度协调的发育过程，包括造血干细胞（HSC）的各个发育阶段。在发育过程中，离开自我更新状态的决定以及分化途径的选择由多种转录因子调控。其中，基因GATA-1和PU.1形成一个核心负反馈模块，以调节HSC细胞命运选择之间的基因转换。尽管广泛的实验研究已经揭示了调节这两个基因表达的机制，但仍不清楚这个简单的模块如何调节基因转换。
在这项工作中，我们提出了一个数学模型来研究GATA-PU.1基因网络在确定HSC分化途径中的机制。我们将GATA转换机制纳入该模块，并开发了一个包含GATA-1、GATA-2和PU.1三个基因的数学模型。此外，设计了一种新颖的多目标优化方法，通过实现不同的实验观察来推断所提出模型中的未知参数。还设计了一个随机模型来描述由于分子物种拷贝数少而产生的噪声在确定分化途径中的关键作用。
所提出的确定性模型成功实现了三种稳定稳态，分别代表启动细胞和不同的祖细胞，以及在各种实验条件下基因状态之间的基因转换。在GATA转换期间，使用不同的GATA-1合成速率值来表示染色质位点中GATA-1蛋白的可用性，随机模拟首次实现了在各种实验条件下导致不同发育途径的细胞的不同比例。
数学模型提供了关于实现造血干细胞不同分化途径的机制和条件的可测试预测。这项工作代表了首次尝试使用离散随机模型来实现显示多峰分布的HSC分化途径的决定。
