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.

项目总结/摘要 目前的HIV进化枝系统并不能很好地监测HIV传播集群中的病毒变化 随着时间的推移：进化枝系统是在近20年前建立的，预选的进化枝参考是 不经常更新。此外，快速的病毒进化可以容易地使该分支系统在跟踪中次优 流行病中的病毒变化。更糟糕的是，尽管我们长期以来理所当然地依赖于这个进化支系统， 在大多数艾滋病研究中，这个系统在多大程度上代表了一个实际的 HIV-1多样性。这项拟议的研究旨在解决目前的分支系统的关键限制， 提高其在识别和跟踪艾滋病毒簇的出现和演变中的病毒变化方面的准确性。 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演变 集群已经存在于当代艾滋病毒流行病;然而，由于缺乏适当的调查， 和检测工具，新病毒多样性的信号在流行病学中被忽视或错过， 直到集群扩大并变得具有威胁性。我们的假设是基于我们之前的 新的G和J谱系的发现落在经典的HIV分支之外，以及越来越多的 全球HIV序列，其基因分型在当前HIV进化枝系统下无法实现。的理由 这项拟议的研究是，新的病毒多样性信息，希望通过发展揭示 动态聚类中的新工具，将有效地提高我们的能力，以跟踪出现， 艾滋病病毒集群不断扩大。在目标1中，通过对基因分型信息进行严格的质量控制， 通过广泛的数据挖掘，我们将确定第一个具有新多样性的HIV-1序列的实际列表 传统的A-K进化枝之外的信息。在目标2中，我们计划开发一种新的聚类算法， 最大限度地减少因参考选择不正确或缺失而导致的错误分类。该算法将 首次用于确定超出当前进化枝系统的新病毒多样性是否 通过形成集群获得了流行病的重要性。最后，在目标3中，我们将整合目标1和 目标2建立一个可查找、可访问和可重复使用的Web界面，以便有效地跟踪 非传统的艾滋病病毒在不断扩大的艾滋病病毒集群的出现和演变中的作用。该接口将 成为第一个具有跟踪过去被忽视的非传统艾滋病病毒感染的功能的平台。 我们将受益于我们超过17年的经验，在艾滋病毒分子流行病学，计算生物学， 算法/软件开发，以执行此拟议项目。在本研究结束时，我们将帮助填补 关于超越当前HIV进化枝系统的新病毒多样性的知识差距，以及 检测非传统的病毒分支我们希望能揭示出更大程度的艾滋病毒多样性， 在目前的艾滋病毒研究和监测中被低估了。我们提出的方法可以让艾滋病毒 更好地对序列数据进行基因分型，从而有助于改善基于基因组的艾滋病保健和治疗。