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The World Health Organization plans to eliminate hepatitis B and C Infections by 2030. Therefore, there is a need to study and understand hepatitis B virus (HBV) epidemiology and viral evolution further, including evaluating occult (HBsAg-negative) HBV infection (OBI), given that such infections are frequently undiagnosed and rarely treated. We aimed to molecularly characterize HBV genomes from 108 individuals co-infected with human immunodeficiency virus (HIV) and chronic hepatitis B (CHB) or OBI identified from previous HIV studies conducted in Botswana from 2009 to 2012. Full-length (3.2 kb) and nearly full-length (~3 kb) genomes were amplified by nested polymerase chain reaction (PCR). Sequences from OBI participants were compared to sequences from CHB participants and GenBank references to identify OBI-unique mutations. HBV genomes from 50 (25 CHB and 25 OBI) individuals were successfully genotyped. Among OBI participants, subgenotype A1 was identified in 12 (48%), D3 in 12 (48%), and E in 1 (4%). A similar genotype distribution was observed in CHB participants. Whole HBV genome sequences from Botswana, representing OBI and CHB, were compared for the first time. There were 43 OBI-unique mutations, of which 26 were novel. Future studies using larger sample sizes and functional analysis of OBI-unique mutations are warranted. [ABSTRACT FROM AUTHOR]

Occult hepatitis B infections (OBI) represent a reservoir of undiagnosed and untreated hepatitis B virus (HBV), hence the need to identify mutations that lead to this phenotype. Functionally characterizing these mutations by in vitro studies is time-consuming and expensive. To bridge this gap, in silico approaches, which predict the effect of amino acid (aa) variants on HBV protein function, are necessary. We developed an algorithm for determining the relevance of OBI-associated mutations using in silico approaches. A 3 kb fragment of subgenotypes A1 and D3 from 24 chronic HBV-infected (CHB) and 24 OBI participants was analyzed. To develop and validate the algorithm, the effects of 68 previously characterized occult-associated mutations were determined using three computational tools: PolyPhen2, SNAP2, and PROVEAN. The percentage of deleterious mutations (with impact on protein function) predicted were 52 (76.5%) by PolyPhen2, 55 (80.9%) by SNAP2, and 65 (95.6%) by PROVEAN. At least two tools correctly predicted 59 (86.8%) mutations as deleterious. To identify OBI-associated mutations exclusive to Botswana, study sequences were compared to CHB sequences from GenBank. Of the 43 OBI-associated mutations identified, 26 (60.5%) were predicted by at least two tools to have an impact on protein function. To our knowledge, this is the first study to use in silico approaches to determine the impact of OBI-associated mutations, thereby identifying potential candidates for functional analysis to facilitate mechanistic studies of the OBI phenotype. [ABSTRACT FROM AUTHOR]