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使用单细胞技术来理解HIV潜伏模型。

Using single cell technologies to understand HIV latency models.

作者信息

Huff Julia S, Browne Edward P

机构信息

Department of Microbiology and Immunology.

UNC HIV Cure Center.

出版信息

Curr Opin HIV AIDS. 2025 Sep 1;20(5):488-492. doi: 10.1097/COH.0000000000000959. Epub 2025 Jul 11.

Abstract

PURPOSE OF REVIEW

This review outlines current model systems of HIV latency and their analysis with single-cell omics technologies. Previous studies have used bulk analyses of infected cell cultures to determine mechanisms of HIV transcription and to identify targets associated with HIV latency in vitro . However, heterogeneity in cell populations creates a barrier to the effectiveness of latency reversing agents. Single cell approaches promise to accelerate our understanding of how the host cell environment regulates complex behaviors of the HIV provirus.

RECENT FINDINGS

Several recent papers have applied cutting edge single cell omics methods to model systems of HIV latency, including scRNAseq and scATACseq, as well as multiomic methods such as DOGMAseq and ECCITEseq. These papers have revealed complex heterogeneity in latently infected cells but have also led to the identification of several new host cell genes that regulate HIV latency.

SUMMARY

Single-cell technologies provide sensitive detection of cellular subpopulations that contribute to proviral reactivation and latency, making them advantageous to apply to widely used cell line and primary cell models of HIV latency. These studies have increased our understanding of HIV latency model systems and generated novel hypotheses which can be tested in clinical samples from people with HIV.

摘要

综述目的

本综述概述了当前HIV潜伏的模型系统及其通过单细胞组学技术进行的分析。以往的研究使用对感染细胞培养物的整体分析来确定HIV转录机制,并在体外鉴定与HIV潜伏相关的靶点。然而,细胞群体的异质性给潜伏逆转剂的有效性带来了障碍。单细胞方法有望加快我们对宿主细胞环境如何调节HIV前病毒复杂行为的理解。

最新发现

最近的几篇论文将前沿的单细胞组学方法应用于HIV潜伏模型系统,包括scRNAseq和scATACseq,以及DOGMAseq和ECCITEseq等多组学方法。这些论文揭示了潜伏感染细胞中复杂的异质性,但也导致了几个调节HIV潜伏的新宿主细胞基因的鉴定。

总结

单细胞技术能够灵敏地检测有助于前病毒激活和潜伏的细胞亚群,使其有利于应用于广泛使用的HIV潜伏细胞系和原代细胞模型。这些研究增进了我们对HIV潜伏模型系统的理解,并产生了可以在HIV感染者的临床样本中进行检验的新假设。

相似文献

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Using single cell technologies to understand HIV latency models.使用单细胞技术来理解HIV潜伏模型。
Curr Opin HIV AIDS. 2025 Sep 1;20(5):488-492. doi: 10.1097/COH.0000000000000959. Epub 2025 Jul 11.

本文引用的文献

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A targeted CRISPR screen identifies ETS1 as a regulator of HIV-1 latency.一项靶向CRISPR筛选确定ETS1为HIV-1潜伏的调节因子。
PLoS Pathog. 2025 Apr 8;21(4):e1012467. doi: 10.1371/journal.ppat.1012467. eCollection 2025 Apr.
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Microwell array chip-based single-cell analysis.基于微井阵列芯片的单细胞分析。
Lab Chip. 2023 Mar 1;23(5):1066-1079. doi: 10.1039/d2lc00667g.

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