Viral Disease Mapping Initiative

病毒性传染病是造成人类疾病负担的主要原因之一。最近的大流行，如2003年的SARS、2009年的甲型流感、2016年的寨卡病毒和2020年的SARS-CoV-2，突显了迅速开发与疫苗垂直的抗病毒治疗的必要性。正如在SARS-CoV-2大流行中观察到的那样，即使是发达国家，在研制出合适的疫苗之前，也可能在健康、政治和社会经济层面上遭受巨大损失。小分子治疗方案将在一定程度上防止这种情况，并有助于在全球范围内控制大流行。为了确定对新出现的威胁具有抗病毒功效的化合物，在病毒和病毒家族开始在人类人口中传播之前，获得对它们的生物学和分子方面的了解是至关重要的。对受这些病毒干扰的生物网络进行多水平分析，包括上下文相关的基因表达调控和随后识别促进或抑制致病的因素，可以帮助识别属于病毒或宿主的可行治疗靶点。提供足够的分子知识，对临床上用于非传染性疾病(如肿瘤学、代谢性疾病等…)的药物进行再利用是可以实现的。在这里，我们建议全面分析高致病性流行病毒和大流行病毒感染后宿主基因表达网络的调节和重连。我们的初步数据提供了证据，证明RNA质量的调节(选择性剪接和选择性多聚腺苷化)是许多临床相关病毒的共同主题，并且RNA质量的改变可能是病毒致病性的一个被严重低估的决定因素。我们与多个实验室合作，这些实验室将提供感染高致病性病毒的原代细胞，我们将利用这些细胞进行深入的序列分析。基于最先进的统计和机器学习算法的计算分析将被应用于理解特定的病毒或病毒家族如何在定量和定性的基础上影响细胞转录组。转录组数据将得到蛋白质组学和磷酸蛋白质组学数据的补充(由ERC-Consoldator Grant PRODAP资助)，这将允许识别单个病毒感染之间的功能模块和联系。我们期望在病毒影响的信使核糖核酸质量控制的改变中获得机械性的见解。此外，通过药物相互作用网络的整合，我们有望帮助合理鉴定具有抗病毒特性的宿主导向药物。这一倡议将促进利用对新出现病毒的高级系统分子研究来启动对未来大流行的反应，明确的目的是在与公共卫生高度相关的临床环境中使用所获得的知识。

Viral infectious diseases are one of the leading causes of disease burden in human population. Recent pandemics, such as 2003 SARS, 2009 influenza A, 2016 Zika and the 2020 SARS-CoV-2, highlighted the requirement for rapid development of antiviral treatments orthogonal to vaccines. As observed in the SARS-CoV-2 pandemic, even developed nations can suffer massively on health, political and socioeconomic levels until the development of a suitable vaccine. Small molecule treatment options would in part prevent this and facilitate the control of a pandemic on the global scale. In order to identify compounds with antiviral efficacy against emerging threats, it is vital to gain biological and molecular understanding of viruses and viral families before they begin to spread in the human population. Multi-level analysis of biological networks perturbed by these viruses, including context-dependent gene expression regulation and subsequent identification of factors promoting or inhibiting pathogeneses, can facilitate the identification of viable treatment targets belonging to either the virus or the host. Providing sufficient molecular knowledge becomes available, repurposing of pharmacologically tested drugs that are in clinical use for non-infectious diseases (e.g. oncology, metabolic diseases etc…) can be achieved. Here we propose to comprehensively analyse the regulation and rewiring of the host’s gene expression networks after infection with highly pathogenic epidemic and pandemic viruses. Our preliminary data offers evidence that modulation of the RNA quality (alternative splicing and alternative polyadenylation) is a common theme seen for many clinically relevant viruses and that modifications of RNA quality may be a dramatically underestimated determinant of viral pathogenicity. We teamed up with multiple laboratories who will provide primary cells that are infected with highly pathogenic viruses, which we will use for in depth sequence analysis. Computational analyses based on state of the art statistical and machine learning algorithms will be applied to understand how specific viruses or viral families are influencing the cellular transcriptome on a quantitative and qualitative basis. The transcriptomics data will be complemented by proteomics and phosphoproteomics data (funded from ERC-consolidator grant PRODAP) which will allow to identify functional modules and links between individual viral infections. We expect to gain mechanistic insights in alterations of virus-affected mRNA quality control. Moreover, through integration of drug interaction networks we expect to aid rational identification of host-directed drugs with antiviral properties. This initiative will promote the use of advanced systematic molecular research on emerging viruses to prime responses against future pandemics with an explicit purpose of using the obtained knowledge in a clinical setting with high public health relevance.