Transitions: Rational design of viral vectors

利用遗传数据准确预测生物属性的能力将对生物学的许多领域产生深远的影响，包括遗传学、分子生物学、合成生物学和生物医学工程。该项目的一个目标是开发使用简单的病毒系统(水泡性口炎病毒)进行基因表型预测的方法。其他项目目标是允许PI，这位备受尊敬的计算生物学家，使用几种关键的实验技术获得实践经验，并建立一个在实验和建模方面都有经验的研究计划。该项目还将为许多本科生和研究生提供研究机会，包括来自代表性不足群体的学生。该项目的总体目标是建立一个多尺度模型，显示分子水平上离散事件的波动如何决定病毒种群的定量毒力。这个模型将被开发为一个基因到表型的图谱，它捕捉了在9600个工程水泡性口炎病毒变体库中观察到的基因和表型之间的关系。这个模型将确定水泡性口炎病毒五个基因的转录和翻译的基因控制如何在不引入改变病毒基因组编码蛋白质功能的突变的情况下决定病毒在细胞培养中的传播。根据实验数据建立的模型将指导优化载体的设计，将低毒力和高重复性结合在一起。该项目将通过设计-建造-测试-学习周期的反复进行，以便在实施期结束前每月确定96种病毒变种的特征。病毒变异体的文库将在被转入细胞培养之前进行设计和组装。它们将通过流式细胞仪进行检测。实验数据将被用来改进病毒复制的数学模型，在之前的迭代中添加新的数据。这一奖项反映了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。

The ability to use genetic data to accurately predict the attributes of living organisms would have a profound impact on many fields of biology, including genetics, molecular biology, synthetic biology and biomedical engineering. One goal of this project is to develop approaches for genotype-phenotype predictions using a simple viral system (Vesicular Stomatitis Virus). Additional project goals are to allow the PI, who is a well-respected computational biologist, to gain hands-on experience using several crucial experimental techniques and to establish a research program that has experience in both experimentation and modeling. This project will also provide research opportunities for many undergraduate and graduate students, including students from underrepresented groups. The overall goal of the project is to build a multiscale model showing how fluctuations of discrete events at the molecular level determine the quantitative virulence of a virus population. This model will be developed as a genotype to phenotype map that captures the relationships between genotype and phenotype observed in a library of 9,600 engineered vesicular stomatitis virus variants. This model will establish how the genetic control of the transcription and translation of the vesicular stomatitis virus five genes can determine viral propagation in cell culture without introducing mutations that alter the function of the proteins coded by the viral genome. The model derived from experimental data will guide the design of optimized vectors that combine a low-virulence and a high-degree of reproducibility. The project will proceed through iterations of the Design-Build-Test-Learn cycle that will allow the characterization of 96 virus variants per month by the end of the performance period. Libraries of virus variants will be designed and assembled before being transfected in cell cultures. They will be tested by flow cytometry. Experimental data will be used to refine the mathematical model of viral replication by adding new data to that collected in previous iterations.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.