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Integrative Single-Cell Analysis of Transcriptome, Epigenome, and Lineage in HIV Latency and Activation

HIV 潜伏期和激活过程中转录组、表观基因组和谱系的综合单细胞分析

基本信息

批准号：
10543067
负责人：
Kathleen L. Collins
金额：
$ 69.36万
依托单位：
UNIVERSITY OF MICHIGAN AT ANN ARBOR
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-12-19 至 2024-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10543067
关键词：
ATAC-seq Acute Address Affect Atlases Basic Science Biochemical Bioinformatics Biological Markers Cell Lineage Cell Separation Cell model Cells Chromatin Chromium Clinical Treatment Clonal Expansion Complement Computer Models Computing Methodologies DNA Data Development Disease Foundations Gene Expression Genes Genetic Transcription Genome Goals Granulocyte-Macrophage Colony-Stimulating Factor HIV Histone Deacetylase Inhibitor Human In Vitro Infection Link Macrophage Maps Marker Discovery Methods Modeling Patients Pattern Population Proviruses RNA Reporter Residual state Sampling Shock Site Surveys System TNF gene Time Viral Viral Genome Viral reservoir Virion Virus Activation Virus Integration Virus Latency Work XCL1 gene antiretroviral therapy biomarker identification cell type computer framework env Gene Products epigenome epigenomics hematopoietic differentiation insight integration site latent infection multiple omics novel single cell analysis single-cell RNA sequencing transcriptome transcriptomics

项目摘要

Abstract With the development of triple combination antiretroviral therapy, routine HIV treatment eliminates nearly all actively infected cells. Nevertheless, the small reservoir of latently infected cells, which can remain dormant for long periods of time before becoming active and producing new virus particles, represents a crucial barrier to completely curing the disease. Identifying markers that identify latently infected cells or the biochemical factors that control latency activation could enable the effective use of a “shock and kill” strategy, where specific targeting or activation of latently infected cells eliminates the viral reservoir. Our recent work suggests that the global transcriptomic and epigenomic changes during hematopoietic differentiation affect viral latency and activation. Additionally, we recently found that global inhibition of histone deacetylase activity increases viral activation in these cells, further implicating epigenomic changes in activation. These results raise fundamental questions: What are the markers of latently infected cells? How do the transcriptomic and epigenomic state of a cell affect latency and activation? How does differentiation state relate to viral latency? Here, we leverage our experimental platform for identifying latently and actively infected cells, single cell transcriptome and epigenome sequencing, and our recently developed computational integration methods to investigate these questions. Our interdisciplinary team combines expertise in HIV basic science, HIV clinical treatment, and bioinformatics to develop an experimental and computational framework for integrated gene expression, chromatin accessibility, and lineage into a single picture of viral latency and activation. Specifically, this project will (1) use single-cell RNA-seq and single-cell ATAC-seq to map diversity of infected cells, (2) investigate the relationship between hematopoietic differentiation state and viral activation, (3) determine viral integration sites through single-cell RNA-seq, (4) computationally integrate single cell transcriptome and epigenome profiles, and (5) computationally infer cell lineage relationships among viral genomes and infected cells. To accomplish these goals, we will carry out the following aims: (1) Characterize lineage, transcriptomic and epigenomic diversity of single latently and actively infected primary cells. (2) Investigate latency and activation during in vitro differentiation. (3) Survey single cell diversity of re-activated and in vitro infected cells from cART-suppressed patients. Together, these aims will produce a comprehensive, integrated transcriptomic and epigenomic atlas of the HIV reservoir, identify DNA and RNA biomarkers of latency, and characterize clonal expansion patterns. Our work also develops a broadly applicable experimental and computational framework, laying a foundation for the discovery of novel insights into HIV latency and activation.

摘要