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Updated: Feb 7, 2026

Isolation of Fidelity Variants of RNA Viruses and Characterization of Virus Mutation Frequency
Published on: June 16, 2011
Characterization of hepatitis B virus surface gene mutations from Huzhou, eastern China
Zihan Han1,2, Fang Jin3,4, Peng Luo5
1School of Basic Medical Sciences, Zhejiang Chinese Medical University, Hangzhou, Zhejiang, China.
Background:
Amino acid (AA) substitutions in the hepatitis B virus (HBV) S gene are key drivers of diagnostic evasion, vaccine breakthrough infections and immune escape. Understanding regional mutation profiles is essential for public health intervention. This study aimed to characterize the prevalence and mutation patterns of the HBV S gene in eastern China.
Methods:
In this cross-sectional study, serum samples from 244 patients with chronic HBV infection were collected. The S gene was amplified by nested polymerase chain reaction, followed by genotyping and AA substitution analysis using Geno2pheno HBV and the MEGA 11.0 platform. Concurrent laboratory assessments included serological (HBsAg, anti-HBs, HBeAg, anti-HBe), biochemical (ALT, AST) and virological (HBV DNA load).
Results:
Mutation frequencies were 38.9% (95/244) in the major hydrophilic region and 22.1% (54/244) in the α determinant. Hotspot mutations included Q101R/K, I/T126S/T/V/A/I, Q129H/R, M133L/T, G145R/T/A and F/Y161Y/F. Notably, AA substitutions including L104F/W, T113S, T123P, I126V and G145T differed from previously reported variants. Additional novel mutation sites P105L, S117R/T and W156L were identified. The I92T, Y100C/S and I126S/T/V mutations showed specific associations with genotype C, whereas Y161F was exclusively detected in genotype B.
Conclusions:
This study documents a high frequency of S gene mutations within critical immune regions among chronic HBV-infected patients in eastern China, alongside novel mutation sites and distinct genotype-dependent patterns. HBV genotype and age were independently associated with S gene mutation. These findings provide a molecular basis for optimizing regional diagnostic strategies and future vaccine design.
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