Multi-omic dissection of the transcriptional, epigenetic, and proteomic signatures of cells infected with latent HIV
对潜伏 HIV 感染细胞的转录、表观遗传和蛋白质组学特征进行多组学分析
基本信息
- 批准号:10447107
- 负责人:
- 金额:$ 75.03万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-07-01 至 2025-06-30
- 项目状态:未结题
- 来源:
- 关键词:ATAC-seqAddressAntibodiesBar CodesBiological MarkersBiologyBloodCD4 Positive T LymphocytesCD8-Positive T-LymphocytesCatalogsCell SeparationCellsChromatinCustomDNADataDefective VirusesDetectionDevelopmentDissectionEpigenetic ProcessGene ExpressionGene Expression ProfileGenesGenetic TranscriptionGenomeGenomic DNAGenomicsGoalsHIVHIV GenomeHIV InfectionsHIV SeropositivityIn VitroIndividualInfectionInvestigationLengthLife Cycle StagesLinkMembrane ProteinsMessenger RNAMethodsMicrofluidicsMonitorNatural Killer CellsPathway interactionsPersonsPhysiologicalPopulationProcessPropertyProteinsProteomeProteomicsProvirusesRegulationResearchRoleSamplingSignal TransductionSiteSurfaceSystemT-LymphocyteTestingTherapeuticTimeTranscriptional RegulationTransposaseViralViral MarkersViremiaVirusVirus Latencyantiretroviral therapybasedigitalgenome-wide analysishigh throughput analysisimmunoregulationintegration siteinterestlatent HIV reservoirmultiple omicsnovelnovel strategiesnovel therapeutic interventionnovel therapeuticsprogramsproteomic signaturesingle cell sequencingsingle-cell RNA sequencingtooltranscription factortranscriptometranscriptome sequencingviral rebound
项目摘要
PROJECT SUMMARY
A small population of long-lived CD4 T cells harbors replication competent virus (the latent HIV reservoir) during
effective antiretroviral therapy even when viremia is undetectable; this latent HIV reservoir is invariably
associated with virus rebound when treatment is stopped. The latent HIV reservoir is a major barrier to curing
HIV, but multiple technical challenges limit its investigation. We developed an ultra-high throughput droplet
microfluidic workflow called PCR activated cell sorting (PACS) that detects, sorts and sequences single cells
containing a single copy of intracellular HIV DNA. In preliminary studies we demonstrated the ability of PACS
to 1) process millions of cells at ultra-high throughput, 2) detect HIV infected cells 3) single cell sort and sequence
this rare population of latently infected CD4 T cells. Based on these findings, we believe that PACS provides a
unique opportunity to overcome existing technical challenges and define, for the first time, the genomic
mechanisms that control the HIV latent reservoir. We hypothesize that latently infected cells have unique
properties that allow them to harbor replication competent HIV genomes without producing virus. Thus,
we propose to combine PACS with methods for single cell RNA-seq, genome and integration site analysis,
ATAC-seq and proteomics to define the genomic mechanisms that control the HIV latent reservoir in single
infected cells from people with ART suppression of the virus. Our Specific Aims are as follows:
Specific Aim 1: Define the transcriptome of single cells harboring latent virus. We propose to sequence
the transcriptomes of single HIV positive CD4 T cells isolated from the blood of individuals on ART, while
determining in parallel the HIV provirus sequence and insertion site. These studies will define the transcriptional
program of latently infected cells harboring full-length replication competent virus.
Specific Aim 2: Establish the chromatin landscape of single cells harboring latent virus. We propose to
analyze the chromatin profile of single HIV positive CD4 T cells in order to define the relationship between host
DNA chromatin status and HIV latency. These studies will determine the role of chromatin status in the control
of HIV latency and identify regulators of the transcriptional program of latently infected CD4 T cells.
Specific Aim 3: Identify surface markers of latently infected CD4 T cells. We propose to isolate HIV latently
infected CD4 T cells using PACS and analyze their surface proteome using barcoded antibody sequencing to
identify surface marker combinations that best define the HIV latent reservoir. Upon completion, these studies
will define novel surface marker combinations to identify latently infected CD4 T cells.
IN SUMMARY, these studies use a multi-omics approach based on our combined expertise in the genomic
regulation of immune cells, HIV biology, and microfluidics to define the mechanisms that control HIV latency.
Hence, these studies will guide the development of novel therapeutic interventions, while providing novel tools
for the monitoring of the latent HIV reservoir in infected individuals undergoing ART.
项目摘要
一小部分长寿命的CD4 T细胞在期间具有复制病毒(潜伏的HIV储藏)
即使无法检测到的病毒血症,有效的抗逆转录病毒疗法也是如此;这个潜在的艾滋病毒水库总是
停止治疗时与病毒反弹相关。潜在的艾滋病毒水库是治愈的主要障碍
艾滋病毒,但多种技术挑战限制了其调查。我们开发了一个超高的吞吐量液滴
微流体工作流,称为PCR激活细胞分选(PACS),检测,分类和序列单细胞
包含单个细胞内HIV DNA的副本。在初步研究中,我们证明了PAC的能力
到1)在超高吞吐量下处理数百万个细胞,2)检测受HIV感染的细胞3)单细胞排序和序列
这种罕见的潜在感染的CD4 T细胞。根据这些发现,我们认为PACS提供了
克服现有技术挑战并首次定义基因组的独特机会
控制艾滋病毒潜在储层的机制。我们假设潜在感染的细胞具有独特的
允许它们携带复制能胜任的HIV基因组的特性,而无需产生病毒。因此,
我们建议将PAC与单细胞RNA-seq,基因组和整合位点分析的方法相结合,
ATAC-SEQ和蛋白质组学定义了控制艾滋病毒潜在储层的基因组机制
感染了抑制病毒的人的细胞。我们的具体目的如下:
特定目标1:定义具有潜在病毒的单细胞的转录组。我们提出序列
单个HIV阳性CD4 T细胞的转录组从ART上的个体血液中分离出来,而
并行确定HIV病毒序列和插入位点。这些研究将定义转录
具有全长复制能力病毒的潜在感染细胞的程序。
特定目标2:建立具有潜在病毒的单细胞的染色质景观。我们建议
分析单个HIV阳性CD4 T细胞的染色质谱,以定义宿主之间的关系
DNA染色质状态和HIV潜伏期。这些研究将确定染色质状态在对照中的作用
艾滋病毒潜伏期并识别潜在感染CD4 T细胞的转录程序的调节剂。
特定目标3:确定潜在感染的CD4 T细胞的表面标记。我们建议将艾滋病毒分离出来
使用PACS感染CD4 T细胞,并使用条形码抗体测序对其表面蛋白质组进行分析
确定最能定义艾滋病毒潜伏储层的表面标记组合。完成后,这些研究
将定义新型的表面标记组合,以鉴定潜在感染的CD4 T细胞。
总而言之,这些研究使用基于我们基因组的综合专业知识的多摩学方法
免疫细胞,HIV生物学和微流体的调节,以定义控制HIV潜伏期的机制。
因此,这些研究将指导新型治疗干预措施的发展,同时提供新颖的工具
为了监测接受艺术的受感染者中潜伏的艾滋病毒水库。
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)
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Adam R. Abate其他文献
Adam R. Abate的其他文献
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{{ truncateString('Adam R. Abate', 18)}}的其他基金
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Multi-omic dissection of the transcriptional, epigenetic, and proteomic signatures of cells infected with latent HIV
对潜伏 HIV 感染细胞的转录、表观遗传和蛋白质组学特征进行多组学分析
- 批准号:
10197751 - 财政年份:2020
- 资助金额:
$ 75.03万 - 项目类别:
Multi-omic dissection of the transcriptional, epigenetic, and proteomic signatures of cells infected with latent HIV
对潜伏 HIV 感染细胞的转录、表观遗传和蛋白质组学特征进行多组学分析
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$ 75.03万 - 项目类别:
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