COVID-19: viral-host interactome analyzed by network based-approach model to study pathogenesis of SARS-CoV-2 infection.
新型冠状病毒肺炎: 基于网络模型的病毒-宿主相互作用组研究SARS-CoV-2 感染的发病机制。
- 作者列表："Messina F","Giombini E","Agrati C","Vairo F","Ascoli Bartoli T","Al Moghazi S","Piacentini M","Locatelli F","Kobinger G","Maeurer M","Zumla A","Capobianchi MR","Lauria FN","Ippolito G","COVID 19 INMI Network Medicine for IDs Study Group.
BACKGROUND:Epidemiological, virological and pathogenetic characteristics of SARS-CoV-2 infection are under evaluation. A better understanding of the pathophysiology associated with COVID-19 is crucial to improve treatment modalities and to develop effective prevention strategies. Transcriptomic and proteomic data on the host response against SARS-CoV-2 still have anecdotic character; currently available data from other coronavirus infections are therefore a key source of information. METHODS:We investigated selected molecular aspects of three human coronavirus (HCoV) infections, namely SARS-CoV, MERS-CoV and HCoV-229E, through a network based-approach. A functional analysis of HCoV-host interactome was carried out in order to provide a theoretic host-pathogen interaction model for HCoV infections and in order to translate the results in prediction for SARS-CoV-2 pathogenesis. The 3D model of S-glycoprotein of SARS-CoV-2 was compared to the structure of the corresponding SARS-CoV, HCoV-229E and MERS-CoV S-glycoprotein. SARS-CoV, MERS-CoV, HCoV-229E and the host interactome were inferred through published protein-protein interactions (PPI) as well as gene co-expression, triggered by HCoV S-glycoprotein in host cells. RESULTS:Although the amino acid sequences of the S-glycoprotein were found to be different between the various HCoV, the structures showed high similarity, but the best 3D structural overlap shared by SARS-CoV and SARS-CoV-2, consistent with the shared ACE2 predicted receptor. The host interactome, linked to the S-glycoprotein of SARS-CoV and MERS-CoV, mainly highlighted innate immunity pathway components, such as Toll Like receptors, cytokines and chemokines. CONCLUSIONS:In this paper, we developed a network-based model with the aim to define molecular aspects of pathogenic phenotypes in HCoV infections. The resulting pattern may facilitate the process of structure-guided pharmaceutical and diagnostic research with the prospect to identify potential new biological targets.
背景: SARS-CoV-2 感染的流行病学、病毒学和病原学特点正在评估中。更好地了解与新型冠状病毒肺炎相关的病理生理学对于改善治疗方式和制定有效的预防策略至关重要。关于宿主对SARS-CoV-2 应答的转录组学和蛋白质组学数据仍然具有轶事特征; 因此，来自其他冠状病毒感染的现有数据是一个关键的信息来源。 方法调查选定分子方面的三个人类冠状病毒 (HCoV) 感染，即传染性非典型肺炎-CoV，中东呼吸综合征冠状病毒和HCoV-229E，通过基于网络的方法.对HCoV-宿主相互作用组进行了功能分析，为HCoV感染提供了一个理论的宿主-病原体相互作用模型，并将结果应用于SARS-CoV-2 发病机制的预测。S AR S-CoV-2 wa S的s-糖蛋白的 3D模型与corre s ponding s AR S-CoV的S结构比较，HCoV-229E和MER S-CoV S-糖蛋白。S AR S-CoV、MER S-CoV、HCoV-229E和ho s t相互作用组通过publi s hed蛋白-蛋白相互作用s (PPI) 推断a s孔a s基因co-expre s s离子，由ho S t细胞s中的HCoV s-糖蛋白触发。 RE S ULT S: 虽然s-糖蛋白的氨基酸s等式S被发现在variou s HCoV之间是不同的，但s tructure s s how ed high s imilarity，但也s t 3D s tructural重叠s hared由S AR S CoV S AR S-CoV-2，con s i s帐篷s hared ACE2 预测受体.Ho s t相互作用组，与S AR S-CoV和MER S-CoV的S-糖蛋白连接，主要突出先天免疫途径成分s，s uch a s Toll样受体s、细胞因子s和趋化因子s。 结论: 在本文中，我们开发了一个基于网络的模型，目的是定义HCoV感染中致病表型的分子方面。由此产生的模式可能有助于结构引导的药物和诊断研究的过程，并有望确定潜在的新的生物靶点。
METHODS::Since mid-December of 2019, coronavirus disease 2019 (COVID-19) infection has been spreading from Wuhan, China. The confirmed COVID-19 patients in South Korea are those who came from or visited China. As secondary transmissions have occurred and the speed of transmission is accelerating, there are rising concerns about community infections. The 54-year old male is the third patient diagnosed with COVID-19 infection in Korea. He is a worker for a clothing business and had mild respiratory symptoms and intermittent fever in the beginning of hospitalization, and pneumonia symptoms on chest computerized tomography scan on day 6 of admission. This patient caused one case of secondary transmission and three cases of tertiary transmission. Hereby, we report the clinical findings of the index patient who was the first to cause tertiary transmission outside China. Interestingly, after lopinavir/ritonavir (Kaletra, AbbVie) was administered, β-coronavirus viral loads significantly decreased and no or little coronavirus titers were observed.
METHODS::In December 2019, a novel coronavirus (2019-nCoV) caused an outbreak in Wuhan, China, and soon spread to other parts of the world. It was believed that 2019-nCoV was transmitted through respiratory tract and then induced pneumonia, thus molecular diagnosis based on oral swabs was used for confirmation of this disease. Likewise, patient will be released upon two times of negative detection from oral swabs. However, many coronaviruses can also be transmitted through oral-fecal route by infecting intestines. Whether 2019-nCoV infected patients also carry virus in other organs like intestine need to be tested. We conducted investigation on patients in a local hospital who were infected with this virus. We found the presence of 2019-nCoV in anal swabs and blood as well, and more anal swab positives than oral swab positives in a later stage of infection, suggesting shedding and thereby transmitted through oral-fecal route. We also showed serology test can improve detection positive rate thus should be used in future epidemiology. Our report provides a cautionary warning that 2019-nCoV may be shed through multiple routes.
METHODS::There is a current worldwide outbreak of a new type of coronavirus (2019-nCoV), which originated from Wuhan in China and has now spread to 17 other countries. Governments are under increased pressure to stop the outbreak spiraling into a global health emergency. At this stage, preparedness, transparency, and sharing of information are crucial to risk assessments and beginning outbreak control activities. This information should include reports from outbreak sites and from laboratories supporting the investigation. This paper aggregates and consolidates the virology, epidemiology, clinical management strategies from both English and Chinese literature, official news channels, and other official government documents. In addition, by fitting the number of infections with a single-term exponential model, we report that the infection is spreading at an exponential rate, with a doubling period of 1.8 days.