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

胚胎的复杂性是惊人的：它开始时是一个单细胞，但随着时间的推移，它变成了成千上万个细胞或更多。为了开始破译发育的复杂性以及有助于决定胚胎发育过程中细胞命运的分子的作用，科学家和工程师们构建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，为了描述发育的机械复杂性，它们也变得更加不确定。为了克服这种与机械系统生物学模型相关的不确定性，研究人员将使用果蝇作为模型生物，进行精心设计的实验，以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。除了培养研究生，该项目的更广泛的影响包括系统生物学和工程研究生课程的扩展和在线传播，以及在K-12水平的学术课程的进一步培养，协同联合收割机生物和工程原理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的科学之家合作举办的。在过去的十五年中，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所彻底改变，这些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视图。整合实验和计算的进步，这个项目的总体目标是进行详细的测量个人的生物物理参数和组织水平的行为，以约束的预测，计算模型的Dorsal/NF-#954;B信号模块在早期果蝇胚胎。Dorsal信号模块由转录因子Dorsal在整个胚胎背腹轴上的空间分级浓度组成。胚胎中的细胞以浓度依赖性方式对Dorsal作出反应，因此Dorsal的空间梯度将背腹轴模式化为不同的子域。该项目将对控制胚胎蛋白质浓度的个体生物物理参数和全局梯度进行测量，包括核输入/输出速率、Dorsal的胚胎水平运动以及Dorsal与其细胞质抑制剂Cactus的结合和解离速率。 实验数据将被用作参数优化的模型约束，并整合以生成预测性系统生物学模型，用于准确预测野生型和突变果蝇胚胎中的Dorsal活性梯度。 该项目将促进我们对胚胎发生过程中背侧梯度形成动态的理解，并提供了一个有价值的原型，演示了使用实验设计，通过并发集成的本地约束系统生物学模型（单个参数的测量）和全球（全模型约束）该奖项反映了NSF的法定使命，并被认为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。

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.