A de novo approach to detect and interrogate neglected HIV diversity

检测和询问被忽视的艾滋病毒多样性的从头方法

• 批准号: 10402978
• 负责人: Ming Zhang
• 金额: $ 18.88万
• 依托单位: UNIVERSITY OF GEORGIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-11-01 至 2023-10-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10402978
• 关键词: Address; Algorithmic Software; Algorithms; Basic Science; Clinical; Computational Biology; Data; Detection; Development; Disease Progression; Epidemic; Epidemiologic Monitoring; Epidemiology; Evolution; Foundations; Genomics; Genotype; Goals; HIV; HIV-1; Healthcare; Investigation; Knowledge; Methodology; Molecular Epidemiology; Monitor; Population Surveillance; Public Health; Quality Control; RNA Viruses; Research; Signal Transduction; Specific qualifier value; System; Techniques; Time; Ursidae Family; Viral; Virus; base; data mining; experience; falls; improved; neglect; novel; pathogen; software development; tool; transmission process; web interface

Project Summary/Abstract The current HIV clade system is not well tailored to monitor viral changes in HIV transmission clusters over time: The clade system was established nearly 20 years ago, and the pre-selected clade references are not updated often. Furthermore, rapid viral evolution can easily render this clade system suboptimal in tracking viral changes in epidemics. Even worse, although we have long taken for granted to rely on this clade system in most HIV research, it remains elusive as to the degree that this system represents an actual spectrum of HIV-1 diversity. This proposed study aims to address the critical limitation of the current clade system and improve its accuracy in identifying and tracking viral changes in the emergence and evolution of HIV clusters. Our central hypothesis is that some new viral diversity involved in the emergence and evolution of transmission clusters already exists in contemporary HIV epidemics; however, due to the lack of appropriate investigation and detection tools, signals for the new viral diversity have been overlooked or missed in epidemiological surveillance until the clusters expand and become threatening. Our hypothesis is based on our previous findings of new G and J lineages that fall outside of the classic HIV clades, as well as a growing number of global HIV sequences whose genotyping is unattainable under the current HIV clade system. The rationale for this proposed study is that the new viral diversity information, hopefully revealed through the development of new tools in phylodynamic clustering, will efficiently improve our capability to track the emergence and evolution of expanding HIV clusters. In Aim 1, through rigorous quality control of genotyping information and extensive data mining, we will determine the first actual list of HIV-1 sequences that bear new diversity information beyond the traditional A-K clades. In Aim 2, we plan to develop a novel clustering algorithm to minimize misclassifications derived from incorrect or absent reference selection. This algorithm will be employed to determine for the first time whether the new viral diversity beyond the current clade system has gained epidemic importance by forming clusters. Finally, in Aim 3, we will integrate the results from Aim 1 and Aim 2 to construct a findable, accessible and reusable web interface to facilitate efficient tracking of nontraditional HIV diversities in the emergence and evolution of expanding HIV clusters. This interface would be the first platform with features to track nontraditional HIV diversities that have been neglected in the past. We will benefit from our over 17 years’ experience in HIV molecular epidemiology, computational biology, and algorithm/software development to perform this proposed project. At the end of this study, we will help fill the knowledge gap about the new viral diversity beyond the current HIV clade system and a technique gap to detect nontraditional viral clades. We expect to reveal a greater degree of HIV diversity that may have been underestimated in the current HIV research and surveillance. Our proposed approach would allow HIV sequence data to be better genotyped, thus help improve genomic-based HIV healthcare and treatment.

项目概要/摘要 目前的艾滋病毒分支系统并不能很好地监测艾滋病毒传播集群中的病毒变化 随着时间的推移：进化枝系统已近20年前建立，预选的进化枝参考文献为 此外，快速的病毒进化很容易使该进化枝系统在追踪方面处于次优状态。 更糟糕的是，尽管我们长期以来理所当然地依赖这个进化枝系统。 在大多数艾滋病毒研究中，这个系统在多大程度上代表了实际的艾滋病毒谱系，这一点仍然难以捉摸。 HIV-1 多样性。这项拟议的研究旨在解决当前进化枝系统的关键限制和 提高其识别和跟踪艾滋病毒簇出现和演变过程中病毒变化的准确性。 我们的中心假设是，一些新的病毒多样性参与了传播的出现和进化 然而，由于缺乏适当的调查，当代艾滋病毒流行中已经存在聚集性现象； 和检测工具，新病毒多样性的信号在流行病学中被忽视或遗漏 我们的假设是基于我们之前的假设。 不属于经典 HIV 分支的新 G 和 J 谱系的发现，以及越来越多的 全球艾滋病毒序列，其基因分型在当前的艾滋病毒进化枝系统下是无法实现的。 这项拟议的研究是希望通过开发揭示新的病毒多样性信息 系统动力学聚类中的新工具将有效提高我们跟踪出现和发生的能力 在目标 1 中，通过对基因分型信息进行严格的质量控制和 广泛的数据挖掘，我们将确定第一个具有新多样性的实际 HIV-1 序列列表 在目标 2 中，我们计划开发一种新颖的聚类算法来获取超出传统 A-K 分支的信息。 该算法将最大限度地减少因参考选择不正确或缺失而产生的错误分类。 首次用于确定当前进化枝系统之外的新病毒多样性是否具有 最后，在目标 3 中，我们将整合目标 1 和目标 1 的结果。 目标 2 构建一个可查找、可访问和可重用的 Web 界面，以促进高效跟踪 不断扩大的艾滋病毒集群的出现和演变中的非传统艾滋病毒多样性。 成为第一个具有跟踪过去被忽视的非传统艾滋病毒多样性功能的平台。 我们将受益于超过 17 年的 HIV 分子流行病学、计算生物学和 算法/软件开发来执行这个提议的项目在本研究结束时，我们将帮助填写 关于当前 HIV 进化枝系统之外的新病毒多样性的知识差距和技术差距 检测非传统病毒分支，我们期望揭示出可能已经存在的更大程度的艾滋病毒多样性。 在当前的艾滋病毒研究和监测中被低估了，我们提出的方法将允许艾滋病毒。 序列数据可以更好地进行基因分型，从而有助于改善基于基因组的艾滋病毒医疗保健和治疗。