Biomathematical Analysis of Viral Dynamics and Evolution

描述（由申请人提供）：我们将建立在两个非常成功的前资助周期完成的研究。我们建议研究的艾滋病毒生物学的特定方面，是由设计HIV-1候选疫苗的研究人员的迫切需求所激发的。这些需求包括更好地表征传播和早期感染期间的病毒动力学，更深入地了解宿主免疫反应和病毒进化之间的相互作用，以及继续开发充分利用超深度测序（UDS）数据的计算方法。该项目将结合联合收割机我们在建模和计算分析丰富的序列，临床和分析数据集已完成和正在进行的研究项目的成熟的专业知识。首先，我们将设计，实施，验证和传播用于识别和预测单克隆中和抗体和多克隆血清靶向的序列和结构HIV-1包膜表位的计算方法。中和的计算分析所需的时间和成本是传统分子方法的一小部分，并且有可能达到或超过后者的准确性。预测的表位残基或基序随后可用于快速靶向体外验证、编目并使其在实验上可用，从而大大加快了合理的HIV-1疫苗设计的步伐。使用这些预测和验证的基序，可以筛选可用的序列，以估计由给定的nAb中和的循环病毒的比例。其次，我们将开发生物学上现实的进化模型，用于对HIV-1序列进行比较分析，这些序列解释了自然选择、氨基酸取代模式中的强烈偏好、重组、异序性和宿主效应。提出的比较序列分析方法将确定病毒逃避宿主免疫应答的分子机制、传播期间和之后的适应、隔室特异性动力学以及病毒gp 160和宿主IgG重链和轻链序列的共同进化。了解这些动态对于设计引发保护性免疫反应的免疫原至关重要。第三，我们将创建HIV-1特异性生物信息学工具和方法，利用UDS数据来促进我们对病毒进化和种群动态的理解。UDS技术允许在复杂样本中进行前所未有的测序粒度，例如从感染者中分离的HIV-1人群。对HIV-1常见和罕见遗传变异的突变谱和分布的可靠估计，结合统计模型，将更好地估计宿主内的种群动态，并揭示病毒所经历的遗传漂变和选择力之间的相互作用。该项目的一个关键交付成果将是开放源码软件工具，以满足本项目和与艾滋病毒和其他迅速演变的病原体有关的类似项目的独特统计分析、解释和数据访问需求。

DESCRIPTION (provided by applicant): We will build upon the research accomplished during two very successful previous funding cycles. The particular aspects of HIV biology, which we propose to study, have been motivated by pressing needs of researchers designing HIV-1 vaccine candidates. These needs include a better characterization of viral dynamics during transmission and early infection, a deeper understanding of the interplay between host immune response and viral evolution, and a continued development of computational methods that make full use of ultra-deep sequencing (UDS) data. This project will combine our proven expertise at modeling and computational analysis of rich sets of sequence, clinical, and assay data available from completed and ongoing research projects. First, we will design, implement, validate, and disseminate computational methods for identifying and predicting sequence and structural HIV-1 envelope epitopes targeted by monoclonal neutralizing antibodies and polyclonal sera. Computational analysis of neutralization takes a fraction of the time and cost of traditional molecular approaches and has the potential to match or exceed the accuracy of the latter. Predicted epitope residues or motifs can be subsequently used for rapid targeted in vitro validation, cataloged, and made publically available, thereby greatly accelerating the pace of rational HIV-1 vaccine design. Using these predicted and validated motifs, available sequences can be screened to estimate the proportion of circulating viruses neutralized by a given nAb. Second, we will develop biologically realistic evolutionary models for the comparative analysis of HIV-1 sequences that account for natural selection, strong biases in amino-acid substitution patterns, recombination, heterotachy and host effects. The proposed comparative sequence analysis methods will determine molecular mechanisms of viral escape from host immune response, adaptation during and following transmission, compartment-specific dynamics, and the co- evolution of viral gp160 and host IgG heavy and light chain sequences. Understanding these dynamics is crucial to the design of immunogens that elicit protective immune responses. Third, we will create HIV-1- specific bioinformatics tools and methodology that leverage UDS data for advancing our understanding of viral evolution and population dynamics. UDS technology allows for an unprecedented amount of sequencing granularity in complex samples, such as HIV-1 populations isolated from infected individuals. A reliable estimate of the mutational spectra and distribution of common and rare genetic variants of HIV-1, combined with statistical models, will yield better estimates of within-host population dynamics, and shed light on the interplay between genetic drift and selective forces experienced by the virus. A key deliverable of the project will be open-source software tools that address the unique statistical analysis, interpretation and data access needs of this and similar projects working with HIV and other rapidly evolving pathogens.