ORF7a Palsies Macrophage to Worsen Diabetes by SMB/BPI/ABC Domains and PARP/Cap/Cyclin Enzyme System

IF 0.5 4区 生物学 Q4 BIOCHEMICAL RESEARCH METHODS
Wenzhong Liu, Hualan Li
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引用次数: 0

Abstract

Such factors as diabetes and obesity can dramatically worsen COVID-19 symptoms. In addition, macrophage accumulation in adipose tissue is related to obesity. Therefore, macrophages play a significant role in raising COVID-19 susceptibility and severity in diabetes and obese patients. Lipopolysaccharide activates the natural immune system response in obese and diabetic patients’ adipose tissue and increases the risk of susceptibility and severity of COVID-19. In this study, the functional impact of SARS-CoV-2 ORF7a on macrophages was analyzed using a domain-searching bioinformatics technique. Ca2+ binding domain, kinase and phosphatase, SMB/SRCR, LBP/BPI/CETP, ABC, TIR,PARP, Flavivirus Cap enzyme, Cyclin, and other domains have been identified in SARS-CoV-2 ORF7a. ORF7a binds to oxidized low-density lipoprotein cholesterol particles by the macrophage receptor-like domains such as SMB/SRCR and enters macrophages via macropinocytosis. Then, ORF7a prevents 18 S rRNA maturation and adds flavivirus cap 0/1/2 to mRNA to interfere with transcription and translation via PARP, Flavivirus Cap enzyme, and other associated domains. Meanwhile, ORF7a activates and promotes G2/M phase transition via cyclin-related enzymatic activity domains. The destructive activity of ORF7a hijacks the nitric oxide release pathway of macrophages and promotes macrophage death, enabling the virus to elude the innate immune system and aggravate diabetes-related problems in patients. We speculated that cells infected by the SARS-COV-2 virus often used its surface lipopolysaccharides to build expanded barriers to resist T cells, NK cells, and drugs.
ORF7a通过SMB/BPI/ABC结构域和PARP/Cap/Cyclin酶系统使巨噬细胞瘫痪使糖尿病恶化
糖尿病和肥胖等因素会严重加重新冠肺炎的症状。此外,脂肪组织中巨噬细胞的积累与肥胖有关。因此,巨噬细胞在提高糖尿病和肥胖患者COVID-19易感性和严重程度中起着重要作用。脂多糖激活肥胖和糖尿病患者脂肪组织的自然免疫系统反应,增加新冠肺炎的易感性和严重程度。本研究采用结构域搜索生物信息学技术分析了SARS-CoV-2 ORF7a对巨噬细胞的功能影响。在SARS-CoV-2 ORF7a中发现了Ca2+结合域、激酶和磷酸酶、SMB/SRCR、LBP/BPI/CETP、ABC、TIR、PARP、黄病毒Cap酶、Cyclin等结构域。ORF7a通过巨噬细胞受体样结构域(如SMB/SRCR)与氧化低密度脂蛋白胆固醇颗粒结合,并通过巨噬细胞吞噬作用进入巨噬细胞。然后,ORF7a阻止18s rRNA成熟,并通过PARP、黄病毒cap酶和其他相关结构域在mRNA上添加黄病毒cap 0/1/2来干扰转录和翻译。同时,ORF7a通过周期蛋白相关酶活性域激活并促进G2/M相变。ORF7a的破坏活性劫持巨噬细胞的一氧化氮释放途径,促进巨噬细胞死亡,使病毒能够逃避先天免疫系统,加重患者的糖尿病相关问题。我们推测,被SARS-COV-2病毒感染的细胞经常利用其表面脂多糖来建立扩大的屏障,以抵抗T细胞、NK细胞和药物。
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来源期刊
Current Proteomics
Current Proteomics BIOCHEMICAL RESEARCH METHODS-BIOCHEMISTRY & MOLECULAR BIOLOGY
CiteScore
1.60
自引率
0.00%
发文量
25
审稿时长
>0 weeks
期刊介绍: Research in the emerging field of proteomics is growing at an extremely rapid rate. The principal aim of Current Proteomics is to publish well-timed in-depth/mini review articles in this fast-expanding area on topics relevant and significant to the development of proteomics. Current Proteomics is an essential journal for everyone involved in proteomics and related fields in both academia and industry. Current Proteomics publishes in-depth/mini review articles in all aspects of the fast-expanding field of proteomics. All areas of proteomics are covered together with the methodology, software, databases, technological advances and applications of proteomics, including functional proteomics. Diverse technologies covered include but are not limited to: Protein separation and characterization techniques 2-D gel electrophoresis and image analysis Techniques for protein expression profiling including mass spectrometry-based methods and algorithms for correlative database searching Determination of co-translational and post- translational modification of proteins Protein/peptide microarrays Biomolecular interaction analysis Analysis of protein complexes Yeast two-hybrid projects Protein-protein interaction (protein interactome) pathways and cell signaling networks Systems biology Proteome informatics (bioinformatics) Knowledge integration and management tools High-throughput protein structural studies (using mass spectrometry, nuclear magnetic resonance and X-ray crystallography) High-throughput computational methods for protein 3-D structure as well as function determination Robotics, nanotechnology, and microfluidics.
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