CAREER: Inference of Gene Regulatory Networks and Cell Dynamics That Control Stem Cell Fate

干细胞负责在我们的一生中产生和维持器官。干细胞通过干细胞命运决策过程分化为成熟细胞：在大多数情况下，我们还不能解释或预测这一过程。该项目将开发数学模型，以了解干细胞如何做出命运决定。这些模型将描述干细胞的动力学以及细胞内发生的基因动力学和组织中许多细胞之间发生的更高层次的协调。PI将采用新的方法，使用公开的基因组学数据为两个器官的模型提供信息：血液（造血）和肾脏上皮系统。研究成果将是预测和解释干细胞命运决定的能力：这些知识将使我们更接近能够构建新器官。该项目的教育目标是培养新一代科学家，使他们在生物学和定量思维方面同样熟练。这将通过开发新的课程为本科生，中/高，小学水平的学生，紧密结合该项目的研究目标来实现。该项目将开发模型，以解释如何协调和维持干细胞分化在复杂的信号环境。干细胞分化受细胞内部基因调控网络以及来自微环境和细胞及组织尺度效应的信号控制。干细胞分化的预测模型必须考虑到所有这些生物尺度上发生的动态。将研究两个系统中的干细胞状态（稳态和扰动）：造血和肾上皮。对于每个系统，将利用公开的单细胞基因组学数据来推断转录到细胞尺度的调控网络。这将通过三个科学目标来实现：1）开发贝叶斯推理方法来学习单细胞调控网络; 2）通过动态系统建模和参数推理研究干细胞谱系动力学; 3）通过多尺度建模预测组织对刺激的反应。由此产生的模型将为干细胞的功能提供新的见解，并可能揭示不同器官之间信号通路基序的共同调控逻辑。该项目的教育目标是培养新一代的科学家，使他们同时具备数学和生命科学方面的知识。这将通过与南加州大学联合教育项目合作，通过两个教育目标实现：1）为当地小学制定课程，以使数学和生物学的参与多样化，并激发人们的热情; 2）开发一个定量生物学本科课程与服务学习组件中/该奖项反映了NSF的法定使命，并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

Stem cells are responsible for producing and maintaining organs throughout our lifetime. Stem cells differentiate into mature cells through the process of stem cell fate decision-making: in most cases, we cannot yet explain or predict this process. This project will develop mathematical models to understand how stem cells make fate decisions. The models will describe the dynamics of stem cells as well as the gene dynamics occurring inside cells and the higher-level coordination that occurs between the many cells of a tissue. The PI will take the novel approach of using publicly available genomics data to inform models of two organs: the blood (hematopoietic) and kidney epithelial systems. The research outcome will be an ability to predict and explain stem cell fate decisions: knowledge that will bring us one step closer to being able to build new organs. The educational objective of this project is to train a new generation of scientists to be equally skilled in biological and quantitative thinking. This will be achieved by developing new curricula for undergraduate, middle/high, and elementary level students, closely coupled to the research goals of the project.This project will develop models to explain how stem cell differentiation is coordinated and maintained in complex signaling environments. Stem cell differentiation is controlled by cell-internal gene regulatory networks as well as signals from the microenvironment and cell- and tissue-scale effects. Predictive models of stem cell differentiation must take into account the dynamics occurring on all of these biological scales. Stem cell states (both homeostatic and perturbed) in two systems will be studied: hematopoiesis and kidney epithelia. For each system, publicly available single-cell genomics data will be leveraged to infer regulatory networks across transcriptional-to-cellular scales. This will be achieved via three scientific objectives: 1) Develop Bayesian inference methods to learn single-cell regulatory networks; 2) Investigate stem cell lineage dynamics via dynamical systems modeling and parameter inference; 3) Predict tissue-scale responses to stimuli through multiscale modeling. The resulting models will give fundamental new insight into how stem cells function, and may reveal shared regulatory logic of signaling pathway motifs across different organs. The educational goal of this project is to train a new generation of scientists to be simultaneously literate in mathematical and life sciences. This will be achieved in collaboration with the USC Joint Educational Project via two educational objectives: 1) Develop a curriculum for local elementary schools to diversify participation in and spark enthusiasm for mathematics and biology; 2) Develop a quantitative biology undergraduate course with a service-learning component in middle/high schools.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.