Staheli Jeannette P, Neal Maxwell L, Navare Arti, Mast Fred D, Aitchison John D
Center for Global Infectious Disease Research, Seattle Children's Research Institute, Seattle, WA 98101, USA.
NAR Mol Med. 2024 Jan 23;1(1):ugad001. doi: 10.1093/narmme/ugad001. eCollection 2024 Jan.
Traditional antiviral therapies often have limited effectiveness due to toxicity and the emergence of drug resistance. Host-based antivirals are an alternative, but can cause nonspecific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR knockout (KO) screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting antiviral SL drug targets. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Our comparison of SARS-CoV-2 and influenza infection data revealed potential broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.
传统的抗病毒疗法往往因毒性和耐药性的出现而效果有限。基于宿主的抗病毒药物是一种替代方案，但可能会产生非特异性影响。最近的证据表明，通过靶向被病毒感染破坏的蛋白质的合成致死（SL）伙伴，可以选择性地消除病毒感染的细胞。因此，我们假设在病毒感染细胞的CRISPR基因敲除（KO）筛选中缺失的基因可能富集于因感染而改变的蛋白质的SL伙伴中。为了对此进行研究，我们建立了一个预测抗病毒SL药物靶点的计算流程。首先，我们通过大量的组学数据识别出SARS-CoV-2诱导的基因产物变化。其次，我们为每个改变的基因产物识别出SL伙伴。最后，我们在CRISPR KO数据中筛选感染细胞中细胞存活所需的SL伙伴。尽管各种组学数据检测到的病毒诱导变化存在差异，但它们共享许多预测的SL靶点，在CRISPR KO缺失的数据集中有显著富集。我们对SARS-CoV-2和流感感染数据的比较揭示了潜在的广谱、基于宿主的抗病毒SL靶点。这表明，由于CRISPR KO数据与病毒改变状态的SL关系，其中充满了常见的抗病毒靶点，并且可以通过对组学数据集和SL预测的分析来揭示这些靶点。
