In silico Analysis of SARS-CoV-2 ORF8-Binding Proteins Reveals the Involvement of ORF8 in Acquired-Immune and Innate-Immune Systems

被引:8
|
作者
Takatsuka, Hisashi [1 ]
Fahmi, Muhamad [2 ,3 ]
Hamanishi, Kotono [1 ]
Sakuratani, Takuya [1 ]
Kubota, Yukihiko [1 ]
Ito, Masahiro [1 ]
机构
[1] Ritsumeikan Univ, Coll Life Sci, Dept Bioinformat, Kusatsu, Japan
[2] Res Inst Humanity & Nat, Res Dept, Kyoto, Japan
[3] Ritsumeikan Univ, Res Org Sci & Technol, Kusatsu, Japan
关键词
SARS-CoV-2; phylogenetic profiling; immune evasion; COVID-19; pathogenesis; ORF8 accessory gene; PATHWAYS; KEGG;
D O I
10.3389/fmed.2022.824622
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
SARS-CoV-2 is the causative agent of a new type of coronavirus infection, COVID-19, which has rapidly spread worldwide. The overall genome sequence homology between SARS-CoV-2 and SARS-CoV is 79%. However, the homology of the ORF8 protein between these two coronaviruses is low, at ~26%. Previously, it has been suggested that infection by the ORF8-deleted variant of SARS-CoV-2 results in less severe symptoms than in the case of wild-type SARS-CoV-2. Although we found that ORF8 is involved in the proteasome autoimmunity system, the precise role of ORF8 in infection and pathology has not been fully clarified. In this study, we determined a new network of ORF8-interacting proteins by performing in silico analysis of the binding proteins against the previously described 47 ORF8-binding proteins. We used as a dataset 431 human protein candidates from Uniprot that physically interacted with 47 ORF8-binding proteins, as identified using STRING. Homology and phylogenetic profile analyses of the protein dataset were performed on 446 eukaryotic species whose genome sequences were available in KEGG OC. Based on the phylogenetic profile results, clustering analysis was performed using Ward's method. Our phylogenetic profiling showed that the interactors of the ORF8-interacting proteins were clustered into three classes that were conserved across chordates (Class 1: 152 proteins), metazoans (Class 2: 163 proteins), and eukaryotes (Class 3: 114 proteins). Following the KEGG pathway analysis, classification of cellular localization, tissue-specific expression analysis, and a literature study on each class of the phylogenetic profiling cluster tree, we predicted that the following: protein members in Class 1 could contribute to COVID-19 pathogenesis via complement and coagulation cascades and could promote sarcoidosis; the members of Class 1 and 2, together, may contribute to the downregulation of Interferon-beta; and Class 3 proteins are associated with endoplasmic reticulum stress and the degradation of human leukocyte antigen.
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页数:10
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