Comprehensive analysis reveals transcriptomic diversity and immune evasion mechanisms in HBV-infected hepatocellular carcinoma models.
Background/Objectives: Despite extensive research on hepatitis B virus (HBV), its post-transcriptional regulatory mechanisms remain incompletely characterized, particularly regarding epitranscriptomic modifications. This study aims to systematically profile the transcriptomic complexity and RNA modification landscape of HBV in hepatocellular carcinoma models. Methods: We transfected PLC/PRF/5 and Huh7 cells with the HBV 1.3-mer WT replicon plasmid, followed by qPCR measurement of viral load. Total nucleic acids extracted from transfected cells underwent nanopore direct RNA sequencing. The complete HBV transcriptome was then analyzed in two established hepatocellular carcinoma cell lines (PLC/PRF/5 and Huh7), with alternative splicing, polyadenylation, and RNA modifications identified through comprehensive bioinformatics analysis. Results: Our analysis revealed substantial transcriptomic diversity, identifying 34 distinct splice variants—including 14 previously unreported isoforms—with cell-type-specific expression patterns. Additionally, we detected 30 high-confidence RNA modification sites across HBV transcripts, with 93% (28 sites) conserved between both cellular environments. Notably, we observed significant intercellular heterogeneity in poly(A) tail length distributions. Conclusions: A comparison of the post-transcriptional processing modifications of HBV in PLC/PRF/5 and Huh7 cells reveals that the former may be better able to mimic the immune evasion mechanisms of chronic HBV infection. In contrast, the longer poly(A) tails present in Huh7 cells facilitate efficient replication, rendering these cells more amenable to the study of HBV transcription and replication mechanisms. These findings comprehensively elucidate the post-transcriptional regulatory mechanisms of hepatitis B virus in different hepatocellular carcinoma cell lines, establishing a critical benchmark for selecting appropriate experimental models in virology research. The identified transcriptomic features may provide new insights for developing antiviral strategies targeting the viral epigenome.
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Zhang et al. (2025) studied this question.
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