Preexisting cell state rather than stochastic noise confers high or low infection susceptibility of human lung epithelial cells to adenovirus.

IF 3.7 2区 生物学 Q2 MICROBIOLOGY mSphere Pub Date : 2024-10-29 Epub Date: 2024-09-24 DOI:10.1128/msphere.00454-24
Anthony Petkidis, Maarit Suomalainen, Vardan Andriasyan, Abhyudai Singh, Urs F Greber
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Abstract

Viruses display large variability across all stages of their life cycle, including entry, gene expression, replication, assembly, and egress. We previously reported that the immediate early adenovirus (AdV) E1A transcripts accumulate in human lung epithelial A549 cancer cells with high variability, mostly independent of the number of incoming viral genomes, but somewhat correlated to the cell cycle state at the time of inoculation. Here, we leveraged the classical Luria-Delbrück fluctuation analysis to address whether infection variability primarily arises from the cell state or stochastic noise. The E1A expression was measured by the expression of green fluorescent protein (GFP) from the endogenous E1A promoter in AdV-C5_E1A-FS2A-GFP and found to be highly correlated with the viral plaque formation, indicating reliability of the reporter virus. As an ensemble, randomly picked clonal A549 cell isolates displayed significantly higher coefficients of variation in the E1A expression than technical noise, indicating a phenotypic variability larger than noise. The underlying cell state determining infection variability was maintained for at least 9 weeks of cell cultivation. Our results indicate that preexisting cell states tune adenovirus infection in favor of the cell or the virus. These findings have implications for antiviral strategies and gene therapy applications.IMPORTANCEViral infections are known for their variability. Underlying mechanisms are still incompletely understood but have been associated with particular cell states, for example, the eukaryotic cell division cycle in DNA virus infections. A cell state is the collective of biochemical, morphological, and contextual features owing to particular conditions or at random. It affects how intrinsic or extrinsic cues trigger a response, such as cell division or anti-viral state. Here, we provide evidence that cell states with a built-in memory confer high or low susceptibility of clonal human epithelial cells to adenovirus infection. Results are reminiscent of the Luria-Delbrück fluctuation test with bacteriophage infections back in 1943, which demonstrated that mutations, in the absence of selective pressure prior to infection, cause infection resistance rather than being a consequence of infection. Our findings of dynamic cell states conferring adenovirus infection susceptibility uncover new challenges for the prediction and treatment of viral infections.

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人类肺上皮细胞对腺病毒感染易感性的高低取决于细胞原有状态而非随机噪音。
病毒在其生命周期的各个阶段(包括进入、基因表达、复制、组装和排出)都表现出很大的变异性。我们以前曾报道过,即刻早期腺病毒(AdV)E1A转录本在人肺上皮细胞A549癌细胞中的积累具有很高的变异性,大部分与进入的病毒基因组数量无关,但与接种时的细胞周期状态有一定的相关性。在这里,我们利用经典的 Luria-Delbrück 波动分析来解决感染变异性主要来自细胞状态还是随机噪声的问题。我们通过 AdV-C5_E1A-FS2A-GFP 中内源性 E1A 启动子的绿色荧光蛋白(GFP)的表达来测量 E1A 的表达,结果发现 E1A 的表达与病毒斑块的形成高度相关,这表明报告病毒是可靠的。作为一个整体,随机挑选的克隆 A549 细胞分离物的 E1A 表达变异系数明显高于技术噪音,表明表型变异性大于噪音。决定感染变异性的基本细胞状态至少维持了 9 周的细胞培养。我们的研究结果表明,预先存在的细胞状态会调整腺病毒感染,使之有利于细胞或病毒。这些发现对抗病毒策略和基因治疗应用具有重要意义。人们对病毒感染的基本机制尚不完全清楚,但已将其与特定的细胞状态联系起来,例如 DNA 病毒感染中的真核细胞分裂周期。细胞状态是特定条件下或随机产生的生化、形态和环境特征的集合。它影响内在或外在线索如何触发反应,如细胞分裂或抗病毒状态。在这里,我们提供的证据表明,具有内置记忆的细胞状态会使克隆人类上皮细胞对腺病毒感染具有高敏感性或低敏感性。这些结果让人想起 1943 年用噬菌体感染进行的 Luria-Delbrück 波动试验,该试验证明,在感染前没有选择压力的情况下,突变会导致抗感染性,而不是感染的结果。我们关于腺病毒感染易感性的动态细胞状态的发现,为病毒感染的预测和治疗带来了新的挑战。
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来源期刊
mSphere
mSphere Immunology and Microbiology-Microbiology
CiteScore
8.50
自引率
2.10%
发文量
192
审稿时长
11 weeks
期刊介绍: mSphere™ is a multi-disciplinary open-access journal that will focus on rapid publication of fundamental contributions to our understanding of microbiology. Its scope will reflect the immense range of fields within the microbial sciences, creating new opportunities for researchers to share findings that are transforming our understanding of human health and disease, ecosystems, neuroscience, agriculture, energy production, climate change, evolution, biogeochemical cycling, and food and drug production. Submissions will be encouraged of all high-quality work that makes fundamental contributions to our understanding of microbiology. mSphere™ will provide streamlined decisions, while carrying on ASM''s tradition for rigorous peer review.
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