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Detection of Low Copy Number Integrated Viral DNA Formed by In Vitro Hepatitis B Infection
Published on: November 7, 2018
Clinical application of estimating hepatitis B virus quasispecies complexity by massive sequencing: correlation
Maria Homs1, Andrea Caballero2, Josep Gregori3
1Centro de investigación biomédica en red: enfermedades hepáticas y digestivas (CIBERehd), Instituto de Salud Carlos III, Barcelona, Spain; Liver Pathology Unit, Departments of Biochemistry and Microbiology, Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain; Virology Unit, Department of Microbiology, Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Barcelona, Spain.
Aim:
To evaluate HBV quasispecies (QA) complexity in the preCore/Core regions in relation to HBeAg status, and explore QA changes under natural evolution and nucleoside analogue (NUC) treatment.
Methods:
Ultra-deep pyrosequencing of HBV preCore/Core regions in 30 sequential samples (baseline [diagnosis], treatment-free, and treatment-nonresponse) from 10 retrospectively selected patients grouped according to HBeAg status over time: HBeAg+ (N = 4), HBeAg- (N = 2), and fluctuating HBeAg (transient seroreversion/seroconversion pattern) (N = 4). QA complexity was defined by Shannon entropy, mutation frequency, nucleotide diversity, and mutation frequency of amino acids (MfAA) in preCore and Core.
Results:
The QA was less complex in HBeAg+ than in HBeAg- or fluctuating HBeAg. High complexity in preCore was associated with decreased viral replication (preCore MfAA negatively correlated with HBV-DNA, p = 0.005). QA complexity in the treatment-free period negatively correlated with values seen during treatment. Specific variants were mainly selected in the Core region in HBeAg- and fluctuating HBeAg patients, suggesting higher immune pressure than in HBeAg+.
Conclusions:
The negative correlation between QA natural evolution and on-treatment evolution indicates the importance of pre-treatment QA study to predict QA changes in NUC nonresponders. Study of QA complexity could be useful for managing HBV infection.
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