菊花推论链:单细胞和单基因组前病毒测序在表征HIV-1储存库中的作用。

IF 4
Guinevere Q Lee
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摘要

综述的目的:了解和靶向HIV病毒库需要导航推理分析的层次结构。定量病毒生长测定、FLIP-seq和完整前病毒DNA测定(IPDA)——尽管方法不同——基本上都是单细胞技术。每种方法都依赖于限制稀释来分离和询问来自单个感染细胞的单个前病毒基因组,为最感兴趣的结果提供高分辨率代理:复制能力和病毒反弹风险。这些分析不是提供直接测量,而是在一个嵌套的框架中相互推断。这篇综述强调了在这条推理链中批判性地解释分析结果以指导治疗导向策略和储层定量的重要性。最近的发现:最近的研究强调了当前检测HIV-1储存库的方法的复杂性和局限性。关键主题包括依赖基因组完整性的生物信息学定义来推断复制能力,以及由于病毒多样性,PCR扩增长度偏差和定义不一致而产生的重大限制。改良的检测方法,如亚型特异性IPDA旨在解决这些问题。摘要:标准化的、亚型特异性的单细胞方法对于准确表征HIV病毒库至关重要。未来的研究应将大规模测序与复制能力验证相结合,并应完善生物信息学方法以提高预测准确性。提高检测精度对于制定有效的艾滋病治愈策略至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A daisy chain of inferences: the role of single-cell and single-genome proviral sequencing in characterizing HIV-1 reservoirs.

Purpose of review: Understanding and targeting the HIV reservoir requires navigating a hierarchy of inferential assays. Quantitative viral outgrowth assays, FLIP-seq, and intact proviral DNA assays (IPDA) - though methodologically distinct - are all fundamentally single-cell technologies. Each relies on limiting dilution to isolate and interrogate individual proviral genomes derived from single infected cells, offering high-resolution proxies for the outcome of greatest interest: replication competence and the risk of viral rebound. Rather than providing direct measurements, these assays infer one another in a nested framework. This review highlights the importance of critically interpreting assay outputs within this chain of inference to guide cure-directed strategies and reservoir quantification.

Recent findings: Recent studies emphasize the complexity and limitations of current assays measuring HIV-1 reservoirs. Key themes include reliance on bioinformatics definitions of genome-intactness to infer replication competence, alongside significant limitations due to viral diversity, PCR amplification length biases, and definitional inconsistencies. Modified assays like subtype-specific IPDA aim to address these issues.

Summary: Standardized, subtype-specific single-cell methodologies are crucial for accurate HIV reservoir characterization. Future research should integrate large-scale sequencing with replication competence validation, and should refine bioinformatics approaches to enhance predictive accuracy. Enhanced assay precision is essential to inform effective HIV cure strategies.

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