Transitions: Rational design of viral vectors

转变：病毒载体的合理设计

• 批准号: 2123367
• 负责人: Jean Peccoud
• 金额: $ 75万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2123367&HistoricalAwards=false
• 关键词: Transitions; Rational; design; viral; vectors

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.

利用遗传数据准确预测生物体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。该项目的目标之一是利用简单的病毒系统（水泡性口炎病毒）开发基因型-表型预测方法。项目的其他目标是让PI（一位受人尊敬的计算生物学家）获得使用几种关键实验技术的实践经验，并建立一个在实验和建模方面都有经验的研究项目。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。该模型将被开发为一个基因型到表型的图谱，捕捉在9600个工程水泡性口炎病毒变体库中观察到的基因型和表型之间的关系。该模型将确定水疱性口炎病毒5个基因的转录和翻译的遗传控制如何在不引入改变病毒基因组编码蛋白功能的突变的情况下决定病毒在细胞培养中的繁殖。从实验数据中得出的模型将指导设计结合低毒力和高度可重复性的优化载体。该项目将通过设计-构建-测试-学习周期的迭代进行，到性能期结束时，将允许每月对96种病毒变体进行表征。病毒变异文库将被设计和组装，然后在细胞培养中转染。他们将被流式细胞术检测。实验数据将通过向之前的迭代中收集的数据添加新数据来完善病毒复制的数学模型。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。