Systems-level measurements of biophysical parameters in the Dorsal/NF-kappaB pathway

Dorsal/NF-kappaB 通路中生物物理参数的系统级测量

• 批准号: 2105619
• 负责人: Gregory Reeves
• 金额: $ 63.25万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2023-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2105619&HistoricalAwards=false
• 关键词: Systems; level; measurements; biophysical; parameters

The complexity of an embryo is staggering: it begins as a single cell, but over time becomes populated with tens of thousands of cells or more. To begin to decipher the complexity of development and the role of molecules that help to determine cell fate during embryonic development, scientists and engineers have constructed mathematical models that describe developmental processes. However, as these mathematical systems biology models become more detailed, in order to describe the mechanistic complexity of development, they also become more uncertain. To overcome this uncertainty associated with mechanistic systems biology models, using the fruit fly Drosophila melanogaster as a model organism, the investigator will conduct carefully-designed experiments to measure molecular and tissue scale properties in live embryos. The project will result in a detailed understanding of how cells in the Drosophila embryo acquire their fate, increasing our insight into developmental processes in non-mamalian and ultimately mammalian systems. In addition to training graduate students, the broader impacts of the project include the expansion and online dissemination of a graduate course on systems biology and engineering, and further cultivation of academic programs at the K-12 level that synergistically combine biological and engineering principles as part of a multi-day summer camp for high school students, which is held in partnership with NC State University's Science House. In the past decade and a half, our understanding of developmental biology has been revolutionized by live, real-time, image-based experimental platforms, which enable the acquisition of vast quantitative datasets and provide novel views of tissue patterning during embryogenesis. Integrating experimental and computational advances, the overall objective of this project is to perform detailed measurements of individual biophysical parameters and tissue-level behavior to constrain a predictive, computational model of the Dorsal/NF-κB signaling module in the early Drosophila embryo. The Dorsal signaling module consists of spatially graded concentration of a transcription factor, Dorsal, throughout the dorsal-ventral axis of the embryo. The cells in the embryo respond to Dorsal in a concentration-dependent fashion, so that the spatial gradient of Dorsal patterns the dorsal-ventral axis into distinct sub-domains. The project will conduct measurements of individual biophysical parameters and global gradients that control embryonic protein concentrations, including nuclear import/export rates, embryo-level movement of Dorsal, and binding and dissociation rates of Dorsal with its cytoplasmic inhibitor Cactus. The experimental data will be used as model constraints for parameter optimization, and integrated to generate a predictive systems biology model for accurate prediction of the Dorsal activity gradient in wildtype and mutant Drosophila embryos. The project will advance our understanding of the dynamics of Dorsal gradient formation during embryogenesis, and provide a valuable prototype that demonstrates the use of experimental design to constrain systems biology models through the concurrent integration of locally (measurements of individual parameters) and globally (full-model constraint) generated measures.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.

胚胎的复杂性是惊人的：它开始时只有一个细胞，但随着时间的推移，它会被成千上万甚至更多的细胞所填充。为了开始破译发育的复杂性以及在胚胎发育过程中帮助决定细胞命运的分子的作用，科学家和工程师们建立了描述发育过程的数学模型。然而，随着这些数学系统生物学模型变得更加详细，以描述发展的机械复杂性，它们也变得更加不确定。为了克服与机械系统生物学模型相关的这种不确定性，研究者将使用果蝇黑腹果蝇作为模型生物，进行精心设计的实验来测量活胚胎的分子和组织尺度特性。该项目将详细了解果蝇胚胎中的细胞如何获得它们的命运，增加我们对非哺乳动物和最终哺乳动物系统发育过程的了解。除了培训研究生，该项目更广泛的影响包括扩展和在线传播系统生物学和工程研究生课程，以及进一步培养K-12级别的学术课程，这些课程将生物和工程原理协同结合起来，作为高中生多日夏令营的一部分，这是与北卡罗来纳州立大学科学之家合作举办的。在过去的15年里，我们对发育生物学的理解已经被实时、实时、基于图像的实验平台彻底改变，这些实验平台能够获得大量的定量数据集，并提供胚胎发生过程中组织模式的新观点。结合实验和计算的进步，这个项目的总体目标是对个体生物物理参数和组织水平行为进行详细测量，以约束背侧/NF的预测计算模型。早期果蝇胚胎中的B信号模块。Dorsal信号模块由转录因子Dorsal的空间梯度浓度组成，该转录因子遍布胚胎的背腹轴。胚胎中的细胞以浓度依赖性的方式对Dorsal作出反应，因此Dorsal的空间梯度将背-腹轴划分为不同的子域。该项目将对控制胚胎蛋白浓度的个体生物物理参数和全局梯度进行测量，包括核进出口率、Dorsal的胚胎水平运动、Dorsal与其细胞质抑制剂Cactus的结合和解离率。实验数据将作为参数优化的模型约束，并整合生成预测系统生物学模型，以准确预测野生型和突变型果蝇胚胎的背侧活动梯度。该项目将促进我们对胚胎发生过程中背侧梯度形成动力学的理解，并提供一个有价值的原型，通过同时集成局部（单个参数的测量）和全局（全模型约束）生成的测量，展示实验设计的使用来约束系统生物学模型。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。