SARS-CoV-2病毒感染潜在关键分子生物标志物及免疫浸润特征分析

应用生物信息学方法筛选新型冠状病毒肺炎（corona virus disease 2019,COVID-19）感染的潜在关键分子生物标志物并分析其免疫浸润特征。从GEO数据库下载GSE152418数据集,其中COVID-19患者17例,健康对照17例。用加权基因共表达网络分析（weighted gene co-expression network analysis,WGCNA）方法筛选出COVID-19最相关的模块基因。与差异基因取交集得到共同基因,进行功能及信号通路富集分析,构建蛋白互作网络筛选关键基因,构建关键基因的miRNATF-mRNA调控网络,用CIBERSORT算法预测样本免疫细胞浸润特征。差异分析得到2 049个差异基因。WGCNA分析7个模块中“土耳其蓝色”模块与COVID-19相关性最高（r=0.91,P<0.001）。模块中基因显著性和模块隶属度呈显著正相关（r=0.96,P<0.001）。得到共同基因766个,主要参与有丝分裂、微管结合、阳离子通道活性及卵母细胞减数分裂、细胞衰老等。蛋白互作网络筛选到前10位关键基因分别为CDK1、BUB1、CCNA2...     

化湿败毒方治疗新型冠状病毒肺炎的药理学机制探讨和网络药理学研究

本文旨在探讨化湿败毒方治疗COVID-19的现代药理学研究并运用网络药理学方法预测化湿败毒方治疗COVID-19的作用机制。通过查阅文献及临床报道,总结化湿败毒方治疗COVID-19现代药理学研究。通过TCMSP数据库获取化湿败毒方的主要活性化合物及对应靶点并利用GeneCards数据库获取COVID-19的疾病靶点。使用STRING数据库构建蛋白互作网络并对核心靶点进行GO富集和KEGG通路分析,利用Cytoscape3.7.0软件构建化合物-靶标网络。最后把主要核心化合物与SARS-CoV-2 3CL水解酶及ACE2受体进行分子对接。现代药理学研究表明,化湿败毒方有抗炎、抗病毒和调节免疫作用。结果筛选到261个中药靶点,251个疾病相关靶点,药物和疾病靶点取交集得到关键靶点49个。GO富集包括1 547条生物过程、29条细胞组分以及86项分子功能,KEGG通路富集得156条通路与COVID-19相关(P0.05),涉及卡波西氏肉瘤相关疱疹病毒感染、人巨细胞病毒感染、甲型流感、IL-17通路、TNF通路、AGE-RAGE通路等相关通路。预测出主要的核心化合物有槲皮素、木犀草素、山奈酚、汉黄芩素、柚皮素、β-谷甾醇、黄芩素等,在整个网络中发挥着关键作用。分子对接结果显示槲皮素、木犀草素、山奈酚与3CL水解酶和ACE2均有较好的结合。本研究较为全面揭示了化湿败毒方治疗COVID-19"多成分、多靶点、多通路"的特点,为深入探讨化湿败毒方治疗COVID-19的作用机制提供参考依据。     

2019冠状病毒病对肺外系统的影响及可能机制探讨

2019冠状病毒病(coronavirus disease 2019,COVID-19)是由严重急性呼吸综合征冠状病毒2 (severe acute respiratory syndrome coronavirus 2,SARS-CoV-2)导致的感染性疾病。SARS-CoV-2感染人体后除作用于肺部的SARS-CoV-2功能受体外,还可以作用于心脏、消化道、肝脏、肾脏、中枢系统的SARS-CoV-2功能受体,引起肺外脏器的损伤,诱发多器官功能衰竭,增加COVID-19的病死率。但目前对SARS-CoV-2引起肺外各脏器损伤的具体作用机制还不是很清楚,需要更多临床和实验室数据支持。通过检索COVID-19相关的文献,对SARS-CoV-2导致的肺外系统影响及其可能作用机制作一综述。     

基于蛋白质互作网络挖掘自闭症谱系障碍的功能模块与核心基因

自闭症谱系障碍(autism spectrum disorder, ASD)是一种具有高遗传性、临床异质性和生物复杂性的神经行为障碍类疾病。为挖掘ASD发生发展过程中的功能模块与核心基因,本文从自闭症谱系障碍疾病数据库获取ASD相关基因;利用STRING数据库构建ASD相关基因的蛋白质互作网络;通过MCODE算法对蛋白质互作网络进行模块分析并筛选核心基因;最后对各功能模块进行KEGG通路分析,根据富集到的通路类别评估功能模块之间的相互作用。结果显示, 3个疾病基因数据库筛选出182个共有基因,构建的蛋白质互作网络包含171个节点和1 041条边,其中NRXN1、GRIN2B、GRIN2A、DLG4、NLGN3、MECP2、CNTNAP2、BDNF、NLGN4X、FMR1等23个基因具有较高的连通度(degree)。从蛋白质互作网络中分析得到5个功能模块,包括68个核心基因。KEGG富集分析发现功能模块参与多个生物学通路,包括细胞黏附分子、钙离子通路、神经活性的配体-受体相互作用、多巴胺能神经突触等。分析结果提示,挖掘的ASD功能模块和核心基因大多集中在神经元活动、信号分子和信号传导等,且各模块相互作用共同影响ASD的发生发展。     

乳腺癌致病microRNA调控网络的识别与生物信息学分析

目的:构建并解析乳腺癌致病microRNA(miRNA)调控网络,探究其在乳腺癌发生发展中的调控机制。方法:整合TCGA、ENCODE、Fantom等公共数据库资源,得到miRNA、转录因子和基因候选调控关系数据,结合差异表达、变异系数与PCA,构建乳腺癌miRNA调控网络,解析调控网络的度中心性与聚类系数,使用DAVID进行功能富集分析,构建Cox回归模型作生存曲线。结果:共识别miRNA调控网络262个,其中包含5个显著差异表达miRNA,8个转录因子和130个基因。通过功能富集分析发现这些miRNA靶基因显著参与细胞周期、细胞分化、细胞生长、转移等转录后调控的肿瘤生物进程,并与FoxO信号通路、p53信号通路、基因监测通路等信号通路高度相关。通过分析生存曲线发现hsa-mir-144与hsa-mir-133a-2显著与乳腺癌患者生存相关。结论:识别的乳腺癌致病miRNA调控网络中miRNA之间有相互作用,且网络整体功能不仅受hub网络影响,也受元件自身特性影响,这些miRNA靶基因显著富集于肿瘤相关生物学进程与信号通路中。     

基于基因表达谱分析的乙肝阳性转移性肝细胞癌的分子机制分析

本研究旨在筛选与乙肝阳性转移性肝细胞癌相关的基因并揭示其潜在的分子机制。利用GEO数据库中GSE364数据集,筛选在肝内扩散转移组和门静脉癌栓转移组都差异表达的基因,DAVID对差异表达基因进行GO与信号通路富集分析,并用STRING和Cytoscape构建蛋白互作网络,随后用mi Rwalk 2.0筛选可能参与肝细胞癌转移的miRNAs,构建miRNA-枢纽基因调控网络。之后使用Smoami R DB 2.0和c Bio Portal分析枢纽基因突变与circRNA和肝细胞癌预后的关系。我们获得在肝内扩散转移组和门静脉癌栓转移组都差异表达的基因701个,富集分析发现这些基因主要涉及血管生成和血管内皮生长因子信号转导等信号通路。从构建的蛋白互作网络中获得参与蛋白互作模式1的15个枢纽基因,GO分析发现其主要参与RNA加工、代谢、剪接等生物过程。构建的miRNA-枢纽基因调控网络中有4个miRNA参与两个枢纽基因的调控,此外肝细胞癌中SRSF1基因有突变并可转录为hsa_circ_0044757,SNRNP200基因突变与患者预后相关。本研究发现的差异表达基因和枢纽基因,有助于我们认识乙肝相关性肝细胞癌转移的分子机制,并可作为新的用于诊断和预后判断的分子标志物。     

慢性鼻-鼻窦炎伴鼻息肉基因表达谱的生物信息学分析

本研究从美国国立生物信息中心(NCBI)的子数据库基因表达数据库(GEO)中选择基因表达谱GSE36830数据集,采用GEO2R筛选正常钩突和鼻息肉组织之间的差异表达基因(DEGs),对关键通路和差异表达基因进行数据库挖掘和分析,经筛选后的差异表达基因采用戴维在线工具对其进行基因本体富集分析(GO)、京都基因和基因组百科全书(KEGG)分析,然后将DEGs导入String数据库进行蛋白质互作网络分析,绘制差异表达基因互作网络图,将其数据导入Cytoscape软件中,筛选网络中心节点和关键基因,分析关键子网络。共筛选出699个DEGs,其中475个基因为上调表达基因,224个基因为下调表达基因。在GO分析中,针对生物过程,上调的DEGs包括:炎症反应、免疫反应、细胞趋化性、炎症反应的正向调节和细胞的粘附等;下调的DEGs主要参与:唾液分泌、生物矿物组织发展、细胞氨基酸生物合成过程、视网膜内稳态及离子跨膜转运等。在KEGG分析中,上调的DEGs主要在参与造血细胞系、细胞因子-细胞因子受体相互作用、破骨细胞分化、趋化因子信号通路、癌症中的转录失调、哮喘、金黄色葡萄球菌感染等信号通路中富集,而下调的DEGs在唾液腺分泌及胆汁分泌信号通路中富集。差异表达基因互作网络图筛选出前10个关键基因:ITGAM、IL10、CD86、TLR8、ITGAX、CCL2、CCR7、SRC、EGF及ITGB2。本研究得到了一组鼻息肉差异表达基因的生物信息学分析结果,但仍需进一步用基础试验来验证。本文分析的结论为慢性鼻-鼻窦炎、鼻息肉的研究提供了新的研究方向,也为鼻息肉发病机制研究的思路提供了一定的建设性作用。     

基于ceRNA网络识别登革热诊断标志物

通过比较登革热患者和健康人群转录组数据,识别差异基因,构建失调ceRNA网络,筛选关键基因富集分析,解析潜在生物学功能,助力登革热诊断标志物的研究。从GEO数据库下载登革热外周血芯片数据,识别差异基因并进行富集分析。结合miRNA-mRNA互作数据,利用超几何算法和皮尔森相关性计算方法识别登革热失调ceRNA互作对,使用Cytoscape软件可视化ceRNA网络与模块挖掘,对网络模块进行功能富集及外部数据验证表达模式。筛选出251个差异基因,发现其富集在细胞周期等生物学通路中。经外部数据验证,网络模块基因的表达趋势与训练集数据大致相同,表明模块基因在登革热疾病中的潜在诊断效能。本研究可为确定有效的疾病诊断分子标志物提供思路。     

Hsa-miR-210-5p靶基因预测及其相关信号通路的生物信息学分析

为深入研究miR-210-5p的调控机制及生物学功能提供理论机制,应用生物信息学方法分析miR-210-5p序列,预测其靶基因,用Veney2.1.0绘制韦恩图得到靶基因集合,并对其靶基因集合进行蛋白质互作分析,GO功能注释分析和KEGG Pathway分析。结果发现,已知的成熟miR-210-5p序列在各物种间高度保守。蛋白质互作分析显示,miR-210-5p预测靶基因所编码蛋白质间相互作用关系较复杂,尤其是靶基因CDK8、MED18、MED13等编码的蛋白质,在互作中起关键作用。GO分析发现其靶基因集合可能参与细胞组分、分子功能、生物调节等生物学过程;KEGG pathway分析发现其靶基因集合主要富集在MAPK、VEGF、癌症、甲状腺激素信号通路等信号通路。miR-210-5p调控靶基因参与多种重要的生物学过程,为后续研究提供了线索。     

猪流行性腹泻病毒通过病毒蛋白酶激活Caspase-3诱导细胞凋亡

冠状病毒是一大类能够引起呼吸系统疾病,从而威胁人类健康的病毒．目前,对冠状病毒诱导细胞凋亡及其机制研究甚少.本研究以动物冠状病毒 猪流行性腹泻病毒(PEDV) 为模型探讨冠状病毒诱导细胞凋亡效应及其可能作用机制. 通过流式细胞术检测发现感染PEDV病毒后细胞凋亡率明显升高,且PEDV诱导细胞凋亡呈时间和剂量依赖性(P<0.05或P<0.01);进一步研究发现,冠状病毒木瓜样蛋白酶（PLP）在病毒引起凋亡过程中起重要作用.实验发现,转染PEDV-PLP质粒后,caspase-3活化体表达水平明显升高. 提示冠状病毒PLP蛋白酶通过激活caspase-3在病毒诱导细胞凋亡过程中起着关键作用. 以上结果为研究人类冠状病毒PLP蛋白功能及其通过细胞凋亡调节宿主抗病毒天然免疫机制提供重要基础.     

应用 PPIN分析肝移植临床耐受患者PBMC基因表达特点

应用生物信息学方法分析肝移植临床耐受患者PBMC基因表达特征,筛选临床耐受关键基因。从GEO数据库获取19个肝移植临床耐受病例及22个非临床耐受病例基因表达谱数据。应用DAVID网络软件进行差异基因功能注释与聚类分析;通过Cytoscape软件的MiMI插件构建蛋白质相互作用网络(PPIN)筛选肝移植临床耐受关键基因。差异基因涉及蛋白质及RNA代谢、免疫应答、膜结构调节等复杂生物过程。PPIN网络分析获得10个临床耐受核心基因。我们的研究表明:肝移植临床耐受涉及外周血免疫细胞复杂的基因表达调控机制及蛋白质间相互作用;RNA的转录后加工及蛋白质降解在免疫耐受的形成中发挥了重要作用;RBM8A、DHX9、CBL、IKBKB、CSNK2A1、HSPA8等核心基因发挥重要的免疫调节功能。     

Single-cell RNA sequencing identify SDCBP in ACE2-positive bronchial epithelial cells negatively correlates with COVID-19 severity

The coronavirus disease 2019 (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in many deaths throughout the world. It is vital to identify the novel prognostic biomarkers and therapeutic targets to assist with the subsequent diagnosis and treatment plan to mitigate the expansion of COVID-19. Since angiotensin-converting enzyme 2 (ACE2)-positive cells are hosts for COVID-19, we focussed on this cell type to explore the underlying mechanisms of COVID-19. In this study, we identified that ACE2-positive cells from the bronchoalveolar lavage fluid (BALF) of patients with COVID-19 belong to bronchial epithelial cells. Comparing with patients of COVID-19 showing severe symptoms, the antigen processing and presentation pathway was increased and 12 typical genes, HLA-DRB5, HLA-DRB1, CD74, HLA-DRA, HLA-DPA1, HLA-DQA1, HSP90AA1, HSP90AB1, HLA-DPB1, HLA-DQB1, HLA-DQA2, and HLA-DMA, particularly HLA-DPB1, were obviously up-regulated in ACE2-positive bronchial epithelial cells of patients with mild disease. We further discovered SDCBP was positively correlated with above 12 genes particularly with HLA-DPB1 in ACE2-positive bronchial epithelial cells of COVID-19 patients. Moreover, SDCBP may increase the immune infiltration of B cells, CD8+ T cells, CD4+ T cells, macrophages, neutrophils and dendritic cells in different lung carcinoma. Moreover, we found the expression of SDCBP was positively correlated with the expression of antigen processing and presentation genes in post-mortem lung biopsies tissues, which is consistent with previous discoveries. These results suggest that SDCBP has good potential to be further developed as a novel diagnostic and therapeutic target in the treatment of COVID-19.     

氯雷他定的生物信息学分析及其对COVID-19的潜在治疗意义

为探讨氯雷他定对新型冠状病毒肺炎的潜在治疗作用.从基因表达谱数据库(Gene expression omnibus,GEO)获取氯雷他定数据,分别进行差异分析、基因本体学(GO)富集分析、京都基因与基因组百科全书(KEGG)富集分析、蛋白质相互作用(Protein-protein interaction,PPI)网络分...     

Identification of immune-associated signatures and potential therapeutic targets for pulmonary arterial hypertension

Pulmonary arterial hypertension (PAH) comprises a heterogeneous group of diseases with diverse aetiologies. It is characterized by increased pulmonary arterial pressure and right ventricular (RV) failure without specific drugs for treatment. Emerging evidence suggests that inflammation and autoimmune disorders are common features across all PAH phenotypes. This provides a novel idea to explore the characteristics of immunological disorders in PAH and identify immune-related genes or biomarkers for specific anti-remodelling regimens. In this study, we integrated three gene expression profiles and performed Gene Ontology (GO) and KEGG pathway analysis. CIBERSORT was utilized to estimate the abundance of tissue-infiltrating immune cells in PAH. The PPI network and machine learning were constructed to identify immune-related hub genes and then evaluate the relationship between hub genes and differential immune cells using ImmucellAI. Additionally, we implemented molecular docking to screen potential small-molecule compounds based on the obtained genes. Our findings demonstrated the density and distribution of infiltrating CD4 T cells in PAH and identified four immune-related genes (ROCK2, ATHL1, HSP90AA1 and ACTR2) as potential targets. We also listed 20 promising molecules, including TDI01953, pemetrexed acid and radotinib, for PAH treatment. These results provide a promising avenue for further research into immunological disorders in PAH and potential novel therapeutic targets.     

In-silico network-based analysis of drugs used against COVID-19: Human well-being study

IntroductionResearchers worldwide with great endeavor searching and repurpose drugs might be potentially useful in fighting newly emerged coronavirus. These drugs show inhibition but also show side effects and complications too. On December 27, 2020, 80,926,235 cases have been reported worldwide. Specifically, in Pakistan, 471,335 has been reported with inconsiderable deaths.Problem statementIdentification of COVID-19 drugs pathway through drug-gene and gene−gene interaction to find out the most important genes involved in the pathway to deal with the actual cause of side effects beyond the beneficent effects of the drugs.MethodologyThe medicines used to treat COVID-19 are retrieved from the Drug Bank. The drug-gene interaction was performed using the Drug Gene Interaction Database to check the relation between the genes and the drugs. The networks of genes are developed by Gene MANIA, while Cytoscape is used to check the active functional association of the targeted gene. The developed systems cross-validated using the EnrichNet tool and identify drug genes'' concerned pathways using Reactome and STRING.ResultsFive drugs Azithromycin, Bevacizumab, CQ, HCQ, and Lopinavir, are retrieved. The drug-gene interaction shows several genes that are targeted by the drug. Gene MANIA interaction network shows the functional association of the genes like co-expression, physical interaction, predicted, genetic interaction, co-localization, and shared protein domains.ConclusionOur study suggests the pathways for each drug in which targeted genes and medicines play a crucial role, which will help experts in-vitro overcome and deal with the side effects of these drugs, as we find out the in-silico gene analysis for the COVID-19 drugs.     

A Potential Role of the CD47/SIRPalpha Axis in COVID-19 Pathogenesis

The coronavirus SARS-CoV-2 is the cause of the ongoing COVID-19 pandemic. Most SARS-CoV-2 infections are mild or even asymptomatic. However, a small fraction of infected individuals develops severe, life-threatening disease, which is caused by an uncontrolled immune response resulting in hyperinflammation. However, the factors predisposing individuals to severe disease remain poorly understood. Here, we show that levels of CD47, which is known to mediate immune escape in cancer and virus-infected cells, are elevated in SARS-CoV-2-infected Caco-2 cells, Calu-3 cells, and air−liquid interface cultures of primary human bronchial epithelial cells. Moreover, SARS-CoV-2 infection increases SIRPalpha levels, the binding partner of CD47, on primary human monocytes. Systematic literature searches further indicated that known risk factors such as older age and diabetes are associated with increased CD47 levels. High CD47 levels contribute to vascular disease, vasoconstriction, and hypertension, conditions that may predispose SARS-CoV-2-infected individuals to COVID-19-related complications such as pulmonary hypertension, lung fibrosis, myocardial injury, stroke, and acute kidney injury. Hence, age-related and virus-induced CD47 expression is a candidate mechanism potentially contributing to severe COVID-19, as well as a therapeutic target, which may be addressed by antibodies and small molecules. Further research will be needed to investigate the potential involvement of CD47 and SIRPalpha in COVID-19 pathology. Our data should encourage other research groups to consider the potential relevance of the CD47/ SIRPalpha axis in their COVID-19 research.     

Revealing Potential Bioactive Compounds and Mechanisms of Lithospermum erythrorhizon against COVID-19 via Network Pharmacology Study

Lithospermum erythrorhizon (LE) is known in Korean traditional medicine for its potent therapeutic effect and antiviral activity. Currently, coronavirus (COVID-19) disease is a developing global pandemic that can cause pneumonia. A precise study of the infection and molecular pathway of COVID-19 is therefore obviously important. The compounds of LE were identified from the Natural Product Activity and Species Source (NPASS) database and screened by SwissADME. The targets interacted with the compounds and were selected using the Similarity Ensemble Approach (SEA) and Swiss Target Prediction (STP) methods. PubChem was used to classify targets linked to COVID-19. The protein–protein interaction (PPI) networks and signaling pathways–targets–bioactive compounds (STB) networks were constructed by RPackage. Lastly, we performed the molecular docking test (MDT) to verify the binding affinity between significant complexes through AutoDock 1.5.6. The Natural Product Activity and Species Source (NPASS) revealed a total of 82 compounds from LE, which interacted with 1262 targets (SEA and STP), and 249 overlapping targets were identified. The 19 final overlapping targets from the 249 targets and 356 COVID-19 targets were ultimately selected. A bubble chart exhibited that inhibition of the MAPK signaling pathway could be a key mechanism of LE on COVID-19. The three key targets (RELA, TNF, and VEGFA) directly related to the MAPK signaling pathway, and methyl 4-prenyloxycinnamate, tormentic acid, and eugenol were related to each target and had the most stable binding affinity. The three bioactive effects on the three key targets might be synergistic effects to alleviate symptoms of COVID-19 infection. Overall, this study shows that LE can play a role in alleviating COVID-19 symptoms, revealing that the three components (bioactive compounds, targets, and mechanism) are the most significant elements of LE against COVID-19. However, the promising mechanism of LE on COVID-19 is only predicted on the basis of mining data; the efficacy of the chemical compounds and the affinity between compounds and the targets in experiment was ignored, which should be further substantiated through clinical trials.     

The potential role of Th17 immune responses in coronavirus immunopathology and vaccine-induced immune enhancement

Increasing evidence points to host Th17 inflammatory responses as contributing to the severe lung pathology and mortality of lower respiratory tract infections from coronaviruses. This includes host inflammatory and cytokine responses to COVID-19 caused by the SARS-2 coronavirus (SARS CoV2). From studies conducted in laboratory animals, there are additional concerns about immune enhancement and the role of potential host immunopathology resulting from experimental human COVID-19 vaccines. Here we summarize evidence suggesting there may be partial overlap between the underlying immunopathologic processes linked to both coronavirus infection and vaccination, and a role for Th17 in immune enhancement and eosinophilic pulmonary immunopathology. Such findings help explain the link between viral-vectored coronavirus vaccines and immune enhancement and its reduction through alum adjuvants. Additional research may also clarify links between COVID-19 pulmonary immunopathology and heart disease.