The Race between Viral Immune Evasion and the MHC Class I Antigen Processing Pathway

Clicks: 3
ID: 322869
2026
Article Quality & Performance Metrics
Overall Quality
0.0 /100
Combines engagement data with AI-assessed academic quality
AI Quality Assessment
Not analyzed
Abstract
Viral immune evasion of the major histocompatibility complex class I (MHC-I) antigen processing and presentation (APP) pathway is a centerpiece of the art of deception that enables persistence, reinfection, and severe disease. It does so by blunting peptide-MHC-I (pMHC-I) display, weakening CD8+ cytotoxic T lymphocyte (CTL) surveillance, and balancing the counterpressure imposed by natural killer (NK) cell missing-self responses. Rather than relying on a single trick, viruses deploy coordinated, multinode interference that functionally rewires the APP assembly line. These deceptive strategies include limiting antigen substrate availability, reshaping proteasomal peptide generation, sabotaging transporters associated with antigen processing (TAP)-dependent peptide import, disrupting peptide-loading complex-assisted editing, misdirecting MHC-I trafficking, and accelerating surface pMHC-I degradation. In parallel, many viruses fine-tune immune visibility through allele-selective modulation and nonclassical MHC circuits such as human leukocyte antigen E (HLA-E), thereby optimizing CTL evasion without inducing overwhelming NK activation. This review, therefore, describes the development of pathway-centered mechanistic synthesis across DNA and RNA virus families. We further integrate innate immune antagonism, endoplasmic reticulum stress, antigen-presentation competence, cross-presentation limits, and virus-shaped peptide landscapes into a unified framework for understanding viral control of MHC-I output and its translational implications.
Reference Key
openalex_W7171522922 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Yu Ye, Ying Zhang, 聂皓冰, Xiaoyi Liao, Shuigen Rao, Chunfu Zheng
Journal FEMS microbiology reviews
Year 2026
DOI
10.1093/femsre/fuag036
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.