MODULUS: Data-Driven Mechanistic Modeling of Hierarchical Tissues

该项目将开发新的统计和数学模型，描述细胞内的细胞和分子如何自组织以在生物体内执行生物功能。虽然通过收集许多尺度(例如，细胞和分子水平)的信息来研究整个生物系统越来越可行，但这种研究中的一个主要挑战是适当地整合来自个别组件的信息，以便获得系统的完整图景。使这项任务更令人望而生畏的是，生物系统通常是异质和动态的，这意味着系统的属性往往会随着个人、时间和空间的变化而变化。为了研究这种复杂的生物系统，这个项目汇集了一个由数据和生物科学家组成的跨学科团队，以开发和验证一个新的数学框架，该框架将统计和机械模型结合在一起，使科学家能够发现新兴的生物现象，并了解支配它们的规则。然后，这个框架将专门用于研究造血，这是一个负责创造和维持血细胞的非凡生物过程，涉及跨越时间和空间尺度的生化和物理事件之间的复杂相互作用，目前尚不清楚。此外，该项目将为本科生和研究生提供真正的跨学科体验，并得到数据和生物科学家的平等指导。该项目的总体目标是开发一个新的数据驱动的框架，用于研究具有异质性、动力学和跨多个时间和空间尺度的相互作用的复杂生物系统。研究人员将通过在分层贝叶斯框架中嵌入机械模型来实现这一目标。分层贝叶斯模型为整合不同规模的信息(以及先验知识)提供了一个自然的框架。另一方面，机械模型提供了一种灵活的框架，用于以能够进行预测和控制的方式对异类和动态系统进行建模。这一数学框架将用于开发最佳实验设计策略，以阐明造血动力学，执行新的体内实验以产生连续采样的条形码单细胞基因表达谱，并分析结果数据。对于这个建模框架来说，造血是一个理想的生物学过程，因为1)细胞群体(干细胞、祖细胞和成熟细胞)定义明确，2)实验模型系统允许容易操作，以及3)可以施加应激源以最小限度地扰乱系统，并观察回归稳态/平衡的过程。该项目的成功实施将使科学家能够深入了解生理性造血。本项目开发的方法论将可推广到发育生物学、生态学和流行病学中的其他异质和动态生物系统。该奖项是由分子和细胞生物科学部的系统和合成生物学以及数学科学部的数学生物学项目共同资助的。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 project will develop new statistical and mathematical models that describe how cells and molecules within cells self organize to perform biological functions within an organism. While it is increasingly feasible to study biological systems as a whole by collecting information across many scales (e.g., cellular and molecular levels), a major challenge in such studies is to properly integrate information from individual components in order to obtain a complete picture of the system. What makes this task even more daunting is the fact that biological systems are typically heterogeneous and dynamic, meaning that the system properties tend to change across individuals, time, and space. For investigating such complex biological systems, this project brings together an interdisciplinary team of data and biological scientists in order to develop and validate a new mathematical framework that combines statistical and mechanistic models together to enable scientists to discover emergent biological phenomena and to understand the rules that govern them. This framework will then specifically be used to investigate hematopoiesis, which is a remarkable biological process responsible for creation and maintenance of blood cells, and involves complex interactions among biochemical and physical events across temporal and spatial scales that are still not well-understood. Additionally, this project will provide undergraduate and graduate students with a true interdisciplinary experience with equal mentorship from data and biological scientists. The overarching objective of this project is to develop a new data-driven framework for investigating complex biological systems that are characterized by heterogeneity, dynamics, and interactions across multiple time and space scales. The investigators will achieve this goal by embedding mechanistic models in a hierarchical Bayesian framework. Hierarchical Bayesian models provide a natural framework for integrating information (as well as prior knowledge) available at different scales. Mechanistic models, on the other hand, provide a flexible framework for modeling heterogeneous and dynamic systems in ways that enable prediction and control. This mathematical framework will be used to develop optimal experimental design strategies in order to elucidate hematopoiesis dynamics, perform new in vivo experiments to produce serially sampled barcoded single-cell gene expression profiles, and analyze the resulting data. Hematopoiesis is an ideal biological process for this modeling framework because 1) cell populations (stem, progenitor, and mature cells) are well-defined, 2) experimental model systems allow for easy manipulation, and 3) it is possible to apply stressors to minimally perturb the system and observe the process of returning to homeostasis/equilibrium. Successful implementation of this project will allow scientists to gain insights into physiologic hematopoiesis. The methodology developed in this project will be transferable to other heterogeneous and dynamic biological systems in developmental biology, ecology, and epidemiology. This award was co-funded by Systems and Synthetic Biology in the Division of Molecular and Cellular Biosciences and the Mathematical Biology Program of the Division of Mathematical Sciences.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.