MODULUS: Integrative multiscale modeling and multimodal experiments to decode systems-level molecular mecanisms of epithelial systems

该项目的目标是整合新的多尺度数学建模方法和专门设计的实验，以预测分子信号如何在发育过程中驱动细胞和组织形状的产生和维持。经过实验验证的生物系统的多尺度数学模型将被用来推断上皮形态发生的基本原理和规则。这项跨学科的研究计划将被用来发现形态原作为细胞力学调节器的新角色，以及细胞力学如何在果蝇翅膀想象盘的发育过程中提供间接的潜在反馈到形态原信号中，果蝇翅膀想象盘是研究动物和人类发育基本机制的主要生物学模型之一。对正常发育扰动的研究还将为从出生缺陷到与不受控制的组织生长有关的癌症的机制基础提供一般的生物学见解。该项目还将为开发用于合成多细胞系统的预测设计工具提供基础，包括工程有机物或软机器人。该项目将为来自代表性不足群体的学生提供数学和计算生物学、定量生物学和生物信号通路调控方面的培训。加州大学河滨分校生物学定量建模跨学科中心将举办为期一天的研讨会，传播科学知识，促进数学与计算生物学、应用数学、定量生物学和实验生物学领域的交叉培养。这项研究项目将结合数学建模和定量实验来回答一些关键问题，如骨形成蛋白和无翼/WNT信号通路如何调节控制器官发育过程中细胞和组织形状形成和维持的细胞骨架蛋白。这项研究将专注于在幼虫发育过程中建立果蝇翅想象盘上皮形态发生的多尺度模型，因为有丰富的遗传和成像工具可用于测试将形态原与肌动蛋白收缩能力和细胞外基质联系起来的特定假说。将利用实验数据开发和校准三维结合生化信号和细胞力学的模型。变形表面上反应扩散系统理论的突破，结合描述细胞膜和细胞骨架的粗粒化方法，将与来自实验图像的数据驱动的代理模型一起使用。将使用机器学习方法从生物数据中提取定量信息，以促进实验结果和模型预测之间的比较。基于深度学习的超分辨率成像方法将被开发来确定细胞的亚细胞属性。将纳入统计方法和灵敏度分析，以防止模型过度拟合。组合摄动模拟和实验将导致系统的模型比较。该项目还将产生一个用于预测形态发生结果的通用建模平台。该项目将推进STEM招生和培训代表性不足群体的学生的目标。该奖项由分子和细胞生物科学部(MCB)通过系统和合成生物学计划以及MPS数学科学部(DMS)通过数学生物学计划共同资助。该奖项反映了NSF的法定使命，并通过基金会的智力价值和更广泛的影响审查标准进行了评估，被认为值得支持。

The goal of this project is to integrate novel multi-scale mathematical modeling approaches and specifically designed experiments for predicting how molecular signaling drives cell and tissue shape generation and maintenance during development. Experimentally validated multi-scale mathematical models of biological systems will be used to infer the basic principles and rules of epithelial morphogenesis. The interdisciplinary research program will be used to discover new roles of morphogens as regulators of cell mechanics and how cell mechanics provide indirect potential feedback into morphogen signaling during development of the fruit fly Drosophila wing imaginal disc, one of the main biological models for studying basic mechanisms of animal and human development. The study of perturbations to normal development will also provide general biological insights into the mechanistic basis for diseases from birth defects to cancers related to uncontrolled tissue growth. The project will also provide a basis for developing predictive design tools for synthetic multicellular systems, including engineering organoids or soft robotics. The project will provide training for students from underrepresented groups in mathematical and computational biology, quantitative biology and biological signaling pathways regulation. One-day workshops will be held by the UC Riverside Interdisciplinary Center for Quantitative Modeling in Biology to disseminate scientific knowledge and facilitate cross-fertilization between fields of mathematical and computational biology, applied mathematics, quantitative and experimental biology. This research project will combine mathematical modeling and quantitative experiments to answer key questions regarding how morphogens such as the Bone Morphogenetic Protein and Wingless/WNT signaling pathways regulate the cytoskeletal proteins that control cell and tissue shape formation and maintenance during organ development. The research will focus on developing multi-scale models of epithelial morphogenesis in the fruit fly wing imaginal disc during larval development due to the wealth of genetic and imaging tools available to test specific hypotheses that connect morphogens to actomyosin contractility and the extracellular matrix. Models that incorporate biochemical signaling and cell mechanics in three dimensions will be developed and calibrated using experimental data. Breakthroughs in the theory of reaction-diffusion systems on deforming surfaces coupled with coarse graining approaches describing cell membrane and cytoskeleton will be utilized together with data driven surrogate models that derived from experimental images. Machine learning approaches will be used to extract quantitative information from biological data to facilitate a comparison between experimental outcomes and model predictions. Deep learning based super-resolution imaging approaches will be developed to determine subcellular properties of cells. Statistical methods and sensitivity analysis will be incorporated to prevent model overfitting. Combinatorial perturbation simulations and experiments will result in systematic model comparison. The project will also result in a general modeling platform for predicting morphogenesis outcomes. The project will advance goals for STEM recruitment and training students from underrepresented groups. Scientific workshops will be organized to facilitate cross-fertilization between fields of mathematical and computational biology and quantitative and experimental biology.This award is being co-funded by the Division of Molecular and Cellular Biosciences (MCB) through the Systems and Synthetic Biology Program, and the MPS Division of Mathematical Sciences (DMS) through the Mathematical Biology Program.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.