Persistent viral attenuation by transcriptional and translational de-optimization

通过转录和翻译去优化实现持续的病毒减毒

基本信息

批准号：
8963812
负责人：
JAMES J BULL
金额：
$ 31万
依托单位：
UNIVERSITY OF TEXAS AT AUSTIN
依托单位国家：
美国
项目类别：
财政年份：
2009
资助国家：
美国
起止时间：
2009-08-01 至 2019-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/8963812
关键词：
Address Affect Attenuated Attenuated Vaccines Back Bacteriophage T7 Bacteriophages Biochemical Biological Biological Assay Biological Models Biology Cells Codon Nucleotides Communicable Diseases Computer Simulation Data Disease Engineering Evolution Foundations Gene Expression Regulation Gene Rearrangement Generations Generic Drugs Genetic Genetic Transcription Genome Genome engineering Goals Human poliovirus Immunity Inactivated Vaccines Incidence Infection Life Life Cycle Stages Measures Medicine Messenger RNA Methods Modeling Modification Molecular Molecular Biology Molecular Evolution Nucleotides Oral Patients Pattern Poliomyelitis Polioviruses Positioning Attribute Proteins Proteomics Public Health RNA RNA Viruses Recovery Research Personnel Resistance Ribosomes Sequence Analysis Staging Structure System Testing Texas Transcript Translations Universities Vaccinated Vaccines Variant Viral Viral Genome Virulence Virulent Virus Work attenuation austin base density design ds-DNA engineering design expectation experience fitness genome sequencing immunogenicity insight novel vaccines predictive modeling promoter public health relevance stem success synthetic biology transcriptomics virtual

项目摘要

DESCRIPTION (provided by applicant): Live virus vaccines offer some of the biggest successes of medicine. They offer superior immunogenicity over inactivated virus vaccines, but they have two drawbacks. First, methods for creating attenuated vaccines are hit-and-miss. Second, successful live-virus vaccines can often evolve back to high virulence. Indeed, polio eradication has remained elusive because of vaccine evolution. The first of these hurdles is potentially surmountable with genome engineering, if we can predict the viral fitness effect of the engineering. The second hurdle may also be overcome by engineering if we understand the molecular evolution of engineered viruses. This proposal develops a combined empirical and computational viral system to study attenuation of evolutionary reversal of that attenuation. The virus is a dsDNA bacteriophage (T7) that is safe, easily manipulated and engineered. With its extensive background of genetic, biochemical and evolutionary studies, it offers the best empirical and theoretical foundation of all viruses for addressing this problem. Our approach consists of three Aims that collectively combine genome engineering with molecular studies of the viral life cycle, fitness measures, evolution of attenuated genomes, sequence analysis, and computational modeling. In Aim 1, we build several genomes to test new methods of viral attenuation: silent codon modification, genome rearrangement, and promoter deletion. Two questions motivating this work are (i) whether the level of attenuation is predictable, and (ii) whether the attenuation is evolutionarily stable against reversion to high fit- ness. Beyond genome construction, we will thus measure fitness of all constructs and evolve all constructs for hundreds to thousands of generations, observing fitness recovery and sequence evolution. This Aim stems from a variety of preliminary work demonstrating feasibility of all technical aspects and is the foundation of Aims 2 and 3. Aim 2 is the application of key molecular assays to the viruses from Aim 1, proteomics, transcriptomics, and RNA densities on ribosomes (ribosomal profiling). The intracellular viral life cycle will be described at the level of transcription, translation, and protein abundance to understand the molecular bases of different attenuation methods and the paths of evolutionary recovery. Initially, we will compare patterns transcript and protein abundances with ribosome densities on mRNAs to determine whether they agree with each other and match expectations from the basic biology of the virus. Unexpected patterns will be confirmed experimentally. These methods will provide insight to how the different engineering methods attenuate and how they retard evolutionary recovery. Further, these methods will be used to parameterize and further develop an existing virtual model that gives an overall predictive framework for attenuation and evolution (Aim 3). Aim 3 consists of modeling and analysis. Initially, an existing, second-generation computational model of the viral life cycle will be calibrated to the data we obtain for wt and attenuated viruses. As the model incorporates transcription and translation, the molecular data obtained will be compared at a mechanistic level to model predictions. We expect that translation is modeled with insufficient detail in the current model, and we will develop a third-generation model that addresses the shortcomings of the current model. Ultimately, the model we are developing will be useful for prediction of both attenuation and evolution of T7.

描述（由申请人提供）：活病毒疫苗在医学上取得了一些最大的成功，它们比灭活病毒疫苗具有更好的免疫原性，但它们有两个缺点，第一，制造减毒疫苗的方法是偶然的。事实上，如果我们能够预测的话，由于疫苗的进化，第一个障碍可能可以通过基因组工程来克服。病毒式健身效应如果我们了解工程病毒的分子进化，第二个障碍也可以通过工程来克服。该提案开发了一种结合了经验和计算的病毒系统来研究这种减弱的进化逆转。该病毒是一种双链DNA噬菌体（T7）。凭借其广泛的遗传、生化和进化研究背景，它是安全的、易于操作和设计的，为解决这一问题提供了所有病毒的最佳经验和理论基础。基因组工程，包括病毒生命周期的分子研究、适应度测量、减毒基因组的进化、序列分析和计算建模。在目标 1 中，我们构建了多个基因组来测试病毒减毒的新方法：沉默密码子修饰、基因组重排和。推动这项工作的两个问题是（i）衰减水平是否可预测，以及（ii）衰减是否在进化上稳定，不会恢复到高适应性，因此，除了基因组构建之外，我们还将测量适应性。观察适应性恢复和序列进化，并将所有构建体进化成数百到数千代。该目标源于证明所有技术方面可行性的各种前期工作，并且是目标 2 和 3 的基础。目标 2 是目标 2。对目标 1、蛋白质组学、转录组学和核糖体 RNA 密度（核糖体分析）中的病毒进行关键分子测定的应用将在细胞内病毒生命周期的水平上进行描述。转录、翻译和蛋白质丰度，以了解不同减毒方法的分子基础和进化恢复的路径。首先，我们将比较转录本和蛋白质丰度模式与 mRNA 上的核糖体密度，以确定它们是否彼此一致并符合预期。病毒的基本生物学特征将通过实验得到证实，这些方法将深入了解不同的工程方法如何减弱以及它们如何阻碍进化恢复。此外，这些方法将用于参数化和进一步开发现有的虚拟病毒。模型给出了减毒和进化的总体预测框架（目标 3），最初，现有的第二代病毒生命周期计算模型将根据我们获得的 wt 和数据进行校准。由于该模型结合了转录和翻译，因此获得的分子数据将在机制水平上与模型预测进行比较，我们预计当前模型中的翻译建模细节不足，我们将开发第三代模型。地址最终，我们正在开发的模型将有助于预测 T7 的衰减和演化。