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HIV正义和反义转录本对HIV随机转录和重新激活的影响。

The influence of HIV sense and antisense transcripts on stochastic HIV transcription and reactivation.

作者信息

Więcek Kamil, Wiśniewski Janusz, Chen Heng-Chang

机构信息

Quantitative Virology Research Group, Population Diagnostics Center, Łukasiewicz Research Network - PORT Polish Center for Technology Development, Stablowicka 147, Wrocław 54-066, Poland.

出版信息

Comput Struct Biotechnol J. 2025 Aug 6;27:3528-3546. doi: 10.1016/j.csbj.2025.08.003. eCollection 2025.

Abstract

In this study, we established dozens of single provirus-infected cellular clones offering various transcriptional phenotypes of HIV. We proposed that stochastic fluctuations in HIV transcription can appear at, at least, two levels: (1) the chromosomal landscape and (2) the in situ HIV integration site. In the former case, proviruses integrating at different genomic locations demonstrated a variety of transcriptional bursting and can be classified in noise space constructed based on the parameters associated with the coefficient of variation and using a mathematical model fitting a curve of exponential decay. In the latter case, stochastic HIV transcription can be unveiled through its phenotypic bifurcation and tended to be a pure epigenetic phenomenon: the identical provirus demonstrated fluctuations in its transcription with an elevated frequency. We observed similar expression patterns between sense and antisense RNA transcripts. Notably, both HIV long terminal repeats reacted to drug stimulation and may reveal distinct behaviors. Overall, our data suggest that HIV antisense transcripts could be involved in the stochastic nature of HIV transcription.

摘要

在本研究中,我们建立了数十个由单个前病毒感染的细胞克隆,这些克隆呈现出HIV的各种转录表型。我们提出,HIV转录中的随机波动至少可出现在两个层面:(1)染色体格局;(2)HIV原位整合位点。在前一种情况下,整合于不同基因组位置的前病毒表现出各种转录爆发,并且可以在基于与变异系数相关的参数构建的噪声空间中进行分类,并使用拟合指数衰减曲线的数学模型。在后一种情况下,HIV转录的随机性可通过其表型分歧得以揭示,并且倾向于成为一种纯粹的表观遗传现象:相同的前病毒表现出转录波动的频率增加。我们在正义和反义RNA转录本之间观察到了相似的表达模式。值得注意的是,HIV的两个长末端重复序列均对药物刺激产生反应,并且可能表现出不同的行为。总体而言,我们的数据表明,HIV反义转录本可能参与了HIV转录的随机性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8aa8/12356406/0f25b2ed70e1/ga1.jpg

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