宿主-病毒相互作用组日益被认为是发现治疗流感的新治疗靶点的重要研究领域。已经报道了多个汇集的全基因组CRISPR-Cas筛选来鉴定甲型流感病毒的新的前体和抗病毒宿主因子。然而,目前,缺乏对结果的全面总结。我们对该领域所有已报道的CRISPR研究进行了系统评价,并结合使用信息内容荟萃分析(MAIC)算法进行了荟萃分析。基于15种前病毒和4种抗病毒筛选中的证据产生两个排序的基因列表。将前病毒MAIC结果中的富集途径与先前基于阵列的RNA干扰(RNAi)荟萃分析的那些进行比较。前50名前病毒MAIC列表包含其作用需要进一步阐明的基因,例如内体离子通道TPCN1和激酶WEE1。此外,MAIC指出,ALYREF,转录导出复合体的一个组成部分,具有抗病毒特性,而以前的击倒实验将前病毒作用归因于该宿主因子。CRISPR-Cas汇集的屏幕显示了对早期复制事件的偏见,而之前的RNAi荟萃分析涵盖了早期和晚期事件。RNAi筛选导致比CRISPR筛选更大部分必需基因的鉴定。总之,MAIC算法指出,在宿主-流感病毒相互作用中,几个不太为人所知的通路的重要性值得进一步研究.来自甲型流感病毒感染中CRISPR筛选的荟萃分析的结果可能有助于指导未来研究工作以开发针对宿主的抗流感药物。
目的:病毒的复制依赖于宿主因子,而宿主细胞进化出病毒限制因子。这些因素代表了面向宿主的抗病毒治疗的潜在目标。已经报道了多个汇集的全基因组CRISPR-Cas筛选在流感病毒感染的背景下鉴定亲和抗病毒宿主因子。我们根据公开的基因列表对这些筛选的结果进行了全面分析,使用最近开发的算法,按信息内容进行荟萃分析(MAIC)。MAIC允许将分级和未分级的基因列表系统地整合到最终分级的基因列表中。这种方法突出了特征不佳的宿主因子和途径,并有来自多个屏幕的证据,如囊泡对接和脂质代谢途径,值得进一步探索。
The host-virus interactome is increasingly recognized as an important research field to discover new therapeutic targets to treat influenza. Multiple pooled genome-wide CRISPR-Cas screens have been reported to identify new pro- and antiviral host factors of the influenza A virus. However, at present, a comprehensive summary of the results is lacking. We performed a systematic
review of all reported CRISPR studies in this field in combination with a meta-analysis using the algorithm of meta-analysis by information content (MAIC). Two ranked gene lists were generated based on evidence in 15 proviral and 4 antiviral screens. Enriched pathways in the proviral MAIC results were compared to those of a prior array-based RNA interference (RNAi) meta-analysis. The top 50 proviral MAIC list contained genes whose role requires further elucidation, such as the endosomal ion channel TPCN1 and the kinase WEE1. Moreover, MAIC indicated that ALYREF, a component of the transcription export complex, has antiviral properties, whereas former knockdown experiments attributed a proviral role to this host factor. CRISPR-Cas-pooled screens displayed a bias toward early-replication events, whereas the prior RNAi meta-analysis covered early and late-stage events. RNAi screens led to the identification of a larger fraction of essential genes than CRISPR screens. In summary, the MAIC algorithm points toward the importance of several less well-known pathways in host-influenza virus interactions that merit further investigation. The results from this meta-analysis of CRISPR screens in influenza A virus infection may help guide future research efforts to develop host-directed anti-influenza drugs.
OBJECTIVE: Viruses rely on host factors for their replication, whereas the host cell has evolved virus restriction factors. These factors represent potential targets for host-oriented antiviral therapies. Multiple pooled genome-wide CRISPR-Cas screens have been reported to identify pro- and antiviral host factors in the context of influenza virus infection. We performed a comprehensive analysis of the outcome of these screens based on the publicly available gene lists, using the recently developed algorithm meta-analysis by information content (MAIC). MAIC allows the systematic integration of ranked and unranked gene lists into a final ranked gene list. This approach highlighted poorly characterized host factors and pathways with evidence from multiple screens, such as the vesicle docking and lipid metabolism pathways, which merit further exploration.