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，突出表明需要快速开发与疫苗正交的抗病毒治疗方法。正如在SARS-CoV-2大流行中所观察到的那样，即使是发达国家，在开发出合适的疫苗之前，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预防这种情况，并促进在全球范围内控制流行病。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群中传播之前，获得对病毒和病毒家族的生物学和分子理解至关重要。对受这些病毒干扰的生物网络进行多层次分析，包括环境依赖的基因表达调控和随后对促进或抑制发病的因素的鉴定，可以促进鉴定属于病毒或宿主的可行治疗靶点。提供足够的分子知识，可以实现临床使用的药理学测试药物的重新用途，用于治疗非传染性疾病（例如肿瘤学、代谢性疾病等）。在这里，我们建议全面分析宿主基因表达网络在感染高致病性流行病和大流行性病毒后的调控和重新布线。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聚腺苷化）是许多临床相关病毒的共同主题，RNA质量的修饰可能被严重低估了病毒致病性的决定因素。我们与多个实验室合作，他们将提供感染高致病性病毒的原代细胞，我们将使用这些原代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应用于了解特定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。转录组学数据将由蛋白质组学和磷酸化蛋白质组学数据（由erc -整合者资助PRODAP资助）补充，这将允许识别功能模块和个体病毒感染之间的联系。我们期望在病毒影响的mRNA质量控制的改变中获得机制的见解。此外，通过整合药物相互作用网络，我们期望有助于合理识别具有抗病毒特性的宿主定向药物。这一举措将促进对新出现病毒进行先进的系统分子研究，以初步应对未来的大流行病，其明确目的是在具有高度公共卫生相关性的临床环境中利用所获得的知识。

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.