Collaborative Research: Integrative Modeling, Prediction, and Validation of Multi-Scale Dynamics for Three-Dimensional Chromatin Structures in Cell Differentiation

这一跨学科奖项开发了数学模型和计算算法，以剖析不同类型的细胞如何从干细胞形成的机制。特定细胞类型的形成在生命的各个方面都起着举足轻重的作用，不同的组织由数百种类型的细胞组成。作为一种潜在的机制，DNA的三维结构经历了动态的重塑，并指导着这一复杂的过程。然而，由于系统的复杂性和大量的噪声数据，目前对其研究还不够深入，缺乏定量的模型。该项目将建立一个新的数学框架，以了解DNA结构的动态及其对新细胞类型形成的影响。还将设计有效的计算和统计算法来发现分子驱动因素，这将通过尖端实验进行询问。这一综合战略将在系统层面上对不同细胞类型形成的分子机制产生新的见解，对人类健康、合成生物学和疾病分析(包括神经退行性疾病和癌症)产生广泛影响。为了扩大社会影响，该项目将把科学发现与一系列公众参与的外联活动结合起来，包括新的互动教育单元和平台。将为本科生和研究生开展跨学科实践培训，重点是增加STEM教育中代表性不足的学生群体的多样性和参与度。总体目标是从理论和定量上描述动态3D基因组结构在多系细胞分化过程中的功能作用。由于染色质的多尺度3D组织的复杂性、转录和表观遗传因子的耦合动力学以及全基因组实验中的高缺失率，通过特定的细胞分化轨迹来系统地建模3D染色质的时间动力学一直是具有挑战性的。该项目采用综合策略，结合数学、计算、统计和实验方法来解决这一基本问题。具体地说，该项目将：1)通过整合不同的实验观察，建立一个新的多尺度数学模型，通过细胞分化来研究3D染色质结构的动力学；2)设计新的计算算法，从大规模的噪声数据中重建细胞分化的轨迹；以及3)开发有效的统计推理工具，以发现决定细胞命运的潜在分子事件。理论和计算预测都将通过实验技术进行彻底分析，包括3C-HTGTS和3D FISH。该项目产生的新方法，以及对不同细胞类型面板的全基因组预测，将对数学和生物学的多个科学领域产生广泛影响，并将显著提高细胞分化的机制理解、预测能力和实验工程。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This interdisciplinary award develops mathematical models and computational algorithms to dissect the mechanisms of how different types of cells are formed from stem cells. The formation of specific cell types plays pivotal roles in all aspects of life, and different tissues are composed of hundreds of types of cells. As one of the underlying mechanisms, the 3D structure of DNA undergoes dynamic reshaping and instructs this complex process. However, it is under-studied and quantitative models are lacking due to the complexity of the system and large amounts of noisy data. The project will establish a novel mathematical framework to understand the dynamics of DNA structures and its effects on new cell type formation. Efficient computational and statistical algorithms will also be designed to discover the molecular drivers, which will be interrogated by cutting-edge experiments. The integrative strategy will lead to new systems-level insights into the molecular mechanisms of the formation of diverse cell types, with broad impacts on human health, synthetic biology and disease analyses, including neurodegenerative diseases and cancer. To expand the societal impacts, the project will integrate the scientific discoveries with a series of outreach activities for public engagement, including new interactive educational modules and platforms. Interdisciplinary hands-on training will be developed for both undergraduate and graduate students, with an emphasis on increasing the diversity and participation of under-represented groups of students for STEM education.The overall goal is to theoretically and quantitatively delineate the functional roles of dynamic 3D genome structures in the process of multi-lineage cell differentiation. Due to the complexity of multi-scale 3D organizations of chromatin, the coupled dynamics of transcription and epigenetic factors, and the high rates of missing data in genome-wide experiments, systems-level modeling of the temporal dynamics of 3D chromatin through specific cell differentiation trajectory has been challenging. The project tackles this fundamental problem using an integrative strategy by combining mathematical, computational, statistical and experimental approaches. Specifically, the project will: 1) establish a new multi-scale mathematical model for the dynamics of 3D chromatin architecture through cell differentiation, by integrating different experimental observations; 2) design novel computational algorithms to reconstruct the trajectories across cell differentiation from large-scale noisy data; and 3) develop efficient statistical inference tools to discover the underlying molecular events of cell fate determination. Both theoretical and computational predictions will be thoroughly analyzed by experimental techniques, including 3C-HTGTS and 3D FISH. The new methodology generated by the project, along with the genome-wide predictions across diverse panels of cell types, will have broad impacts on multiple scientific fields in both mathematics and biology, and will significantly improve the mechanistic understandings, predictive capacities and experimental engineering of cell differentiation.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.