Measurement of Antibody Epitope Signatures by Peptide Microarrays to Determine Recency of HIV Infection

通过肽微阵列测量抗体表位特征来确定 HIV 感染的新近程度

基本信息

项目摘要

 DESCRIPTION (provided by applicant): There is a critical need in HIV research to develop a rapid, inexpensive, and accurate assay that can be used to estimate HIV incidence anywhere in the world and on any sample. In the absence of such a test, it is challenging to identify high risk populations, model transmission, and monitor the outcome of public health interventions. Our long term goal is to develop new methods to measure HIV incidence to improve HIV epidemiology in resource-poor settings. The overall objective of the proposed research is to use a cutting-edge immunologic assay, the global HIV-1 peptide microarray, to define the key epitope signatures of HIV-specific antibodies associated with different stages of HIV infection. Our central hypothesis is that the greater the duration of HIV infection, the greater the diversity of HIV-specific antibodies. The rationale for the proposed research is that, once it is known that antibody epitope signatures are associated with different stages of HIV infection, then the global HIV-1 peptide microarray can be further developed as a tool to measure HIV incidence. Guided by strong preliminary data, this hypothesis will be tested by pursuing two specific aims: 1) to identify the key epitope signatures of HIV-specific antibodies that are associated with three different stages of HIV infection (recent, chronic viremia, and ART suppression); and 2) to determine how HIV serologic diversity is associated with increasing HIV viral diversity in viremic subjects over time. Under the first aim, we will perform antibody epitope mapping with a global HIV-1 peptide microarray on individuals with known time since infection. We will complement the peptide microarray with established incidence assays to measure antibody magnitude and avidity. When the proposed studies have been completed, it is our expectation that the breadth of antibody epitope signatures will be significantly increased in non-recent HIV stages compared to in recent HIV infection. Under the second aim, we will determine the relationship between diversity of HIV epitope- specific antibody responses (as measured by peptide microarray) and HIV viral diversity (as measured by single genome amplification and Sanger sequencing) to provide a better pathogenic understanding of antibody evolution and how it relates to HIV incidence. When these studies have been completed, it is our expectation that the depth of antibody binding (# sequence variants recognized at any given binding site) will be positively associated with increasing HIV viral diversity measures over time. The research proposed in this application is innovative, in our opinion, because it introduces a novel high-throughput antibody-based assay that has the potential to be as sensitive and specific for recent HIV infection as a viral diversity assay. The proposed research is significant, because it is expected to be the demonstration that antibody epitope specificity - as measured by the diversity of antibody binding to HIV peptides - can serve as a biomarker of different stages of HIV infection. Ultimately, such knowledge will inform the design of novel HIV incidence assays that will have broad importance in the fields of HIV epidemiology and diagnostics.
 描述(由申请人提供):艾滋病毒研究迫切需要开发一种快速、廉价且准确的检测方法,可用于估计世界任何地方和任何样本的艾滋病毒发病率。在没有这样的测试的情况下,识别高风险是具有挑战性的 人群、传播模型并监测公共卫生干预措施的结果。我们的长期目标是开发测量艾滋病毒发病率的新方法,以改善资源匮乏地区的艾滋病毒流行病学。拟议研究的总体目标是使用尖端免疫学检测方法(全局 HIV-1 肽微阵列)来定义与 HIV 感染不同阶段相关的 HIV 特异性抗体的关键表位特征。我们的中心假设是,HIV 感染持续时间越长,多样性就越大 HIV特异性抗体。这项研究的基本原理是,一旦知道抗体表位特征与 HIV 感染的不同阶段相关,那么全局 HIV-1 肽微阵列就可以进一步开发为测量 HIV 发病率的工具。在强有力的初步数据的指导下,这一假设将通过追求两个具体目标进行检验:1)确定与 HIV 感染的三个不同阶段(近期、慢性病毒血症和 ART 抑制)相关的 HIV 特异性抗体的关键表位特征; 2) 确定随着时间的推移,HIV 血清学多样性与病毒血症受试者中 HIV 病毒多样性增加之间的关系。第一个目标是,我们将使用全局 HIV-1 肽微阵列对已知感染时间的个体进行抗体表位作图。我们将通过已建立的发病率测定来补充肽微阵列,以测量抗体的大小和亲合力。当拟议的研究完成后,我们期望与最近的 HIV 感染相比,非近期 HIV 阶段的抗体表位特征的广度将显着增加。在第二个目标下,我们将确定HIV表位特异性抗体反应的多样性(通过肽微阵列测量)和HIV病毒多样性(通过单基因组扩增和桑格测序测量)之间的关系,以更好地了解抗体进化的致病性及其与HIV发病率的关系。当这些研究完成后,我们预计抗体结合深度(在任何给定结合位点识别的#序列变体)将与随着时间的推移增加的 HIV 病毒多样性措施呈正相关。我们认为,该申请中提出的研究具有创新性,因为它引入了一种新型的基于高通量抗体的检测方法,该检测方法对于最近的 HIV 感染具有与病毒多样性检测一样敏感和特异的潜力。拟议的研究意义重大,因为它有望证明抗体表位特异性(通过抗体与 HIV 肽结合的多样性来衡量)可以作为 HIV 感染不同阶段的生物标志物。最终,这些知识将为新型艾滋病毒发病率测定的设计提供信息,这在艾滋病毒流行病学和诊断领域具有广泛的重要性。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Timothy Jensen Henrich其他文献

Timothy Jensen Henrich的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Timothy Jensen Henrich', 18)}}的其他基金

Mentoring Scientists for Careers in HIV Translational Clinical Research
指导科学家从事艾滋病毒转化临床研究
  • 批准号:
    10762827
  • 财政年份:
    2023
  • 资助金额:
    $ 22.51万
  • 项目类别:
HIV Reservoir and Gene Modified Cell Dynamics Following Autologous Stem Cell Transplantation
自体干细胞移植后的 HIV 储库和基因修饰细胞动力学
  • 批准号:
    10700521
  • 财政年份:
    2023
  • 资助金额:
    $ 22.51万
  • 项目类别:
In situ and digital spatial profiling of the active HIV reservoir in autopsy-derived tissues
尸检组织中活性 HIV 储存库的原位和数字空间分析
  • 批准号:
    10459933
  • 财政年份:
    2022
  • 资助金额:
    $ 22.51万
  • 项目类别:
In situ and digital spatial profiling of the active HIV reservoir in autopsy-derived tissues
尸检组织中活性 HIV 储存库的原位和数字空间分析
  • 批准号:
    10614019
  • 财政年份:
    2022
  • 资助金额:
    $ 22.51万
  • 项目类别:
In Vivo PET Imaging of HIV Infection
HIV 感染的体内 PET 成像
  • 批准号:
    10237379
  • 财政年份:
    2020
  • 资助金额:
    $ 22.51万
  • 项目类别:
In Vivo PET Imaging of HIV Infection
HIV 感染的体内 PET 成像
  • 批准号:
    10095057
  • 财政年份:
    2020
  • 资助金额:
    $ 22.51万
  • 项目类别:
In Vivo PET Imaging of HIV Infection
HIV 感染的体内 PET 成像
  • 批准号:
    10453617
  • 财政年份:
    2020
  • 资助金额:
    $ 22.51万
  • 项目类别:
Targeting Non Viral Markers of HIV Persistence
针对艾滋病毒持续存在的非病毒标志物
  • 批准号:
    10392921
  • 财政年份:
    2018
  • 资助金额:
    $ 22.51万
  • 项目类别:
Longitudinal Immunological Impact of SARS-CoV-2 Infection
SARS-CoV-2 感染的纵向免疫学影响
  • 批准号:
    10265644
  • 财政年份:
    2018
  • 资助金额:
    $ 22.51万
  • 项目类别:
Targeting Non Viral Markers of HIV Persistence
针对 HIV 持续存在的非病毒标志物
  • 批准号:
    9906848
  • 财政年份:
    2018
  • 资助金额:
    $ 22.51万
  • 项目类别:

相似海外基金

CAREER: Blessing of Nonconvexity in Machine Learning - Landscape Analysis and Efficient Algorithms
职业:机器学习中非凸性的祝福 - 景观分析和高效算法
  • 批准号:
    2337776
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Continuing Grant
CAREER: From Dynamic Algorithms to Fast Optimization and Back
职业:从动态算法到快速优化并返回
  • 批准号:
    2338816
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Continuing Grant
CAREER: Structured Minimax Optimization: Theory, Algorithms, and Applications in Robust Learning
职业:结构化极小极大优化:稳健学习中的理论、算法和应用
  • 批准号:
    2338846
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Continuing Grant
CRII: SaTC: Reliable Hardware Architectures Against Side-Channel Attacks for Post-Quantum Cryptographic Algorithms
CRII:SaTC:针对后量子密码算法的侧通道攻击的可靠硬件架构
  • 批准号:
    2348261
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Standard Grant
CRII: AF: The Impact of Knowledge on the Performance of Distributed Algorithms
CRII:AF:知识对分布式算法性能的影响
  • 批准号:
    2348346
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Standard Grant
CRII: CSR: From Bloom Filters to Noise Reduction Streaming Algorithms
CRII:CSR:从布隆过滤器到降噪流算法
  • 批准号:
    2348457
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Standard Grant
EAGER: Search-Accelerated Markov Chain Monte Carlo Algorithms for Bayesian Neural Networks and Trillion-Dimensional Problems
EAGER:贝叶斯神经网络和万亿维问题的搜索加速马尔可夫链蒙特卡罗算法
  • 批准号:
    2404989
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Standard Grant
CAREER: Efficient Algorithms for Modern Computer Architecture
职业:现代计算机架构的高效算法
  • 批准号:
    2339310
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Continuing Grant
CAREER: Improving Real-world Performance of AI Biosignal Algorithms
职业:提高人工智能生物信号算法的实际性能
  • 批准号:
    2339669
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Continuing Grant
DMS-EPSRC: Asymptotic Analysis of Online Training Algorithms in Machine Learning: Recurrent, Graphical, and Deep Neural Networks
DMS-EPSRC:机器学习中在线训练算法的渐近分析:循环、图形和深度神经网络
  • 批准号:
    EP/Y029089/1
  • 财政年份:
    2024
  • 资助金额:
    $ 22.51万
  • 项目类别:
    Research Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了