Viruses are evolving at an alarming rate, spreading and inconspicuously adapting to cutting-edge therapies. Therefore, the search for rapid, informative and reliable diagnostic methods is becoming urgent as ever. Conventional clinical tests (PCR, serology, etc.) are being continually optimized, yet provide very limited data. Could high throughput sequencing (HTS) become the future gold standard in molecular diagnostics of viral infections? Compared to conventional clinical tests, HTS is universal and more precise at profiling pathogens. Nevertheless, it has not yet been widely accepted as a diagnostic tool, owing primarily to its high cost and the complexity of sample preparation and data analysis. Those obstacles must be tackled to integrate HTS into daily clinical practice. For this, three objectives are to be achieved: (1) designing and assessing universal protocols for library preparation, (2) assembling purpose-specific pipelines, and (3) building computational infrastructure to suit the needs and financial abilities of modern healthcare centers. Data harvested with HTS could not only augment diagnostics and help to choose the correct therapy, but also facilitate research in epidemiology, genetics and virology. This information, in turn, could significantly aid clinicians in battling viral infections.

Whole-genome sequencing (WGS) of pathogens is becoming increasingly important not only for basic research but also for clinical science and practice. In virology, WGS is important for the development of novel treatments and vaccines, and for increasing the power of molecular epidemiology and evolutionary genomics. In this Opinion article, we suggest that WGS of viruses in a clinical setting will become increasingly important for patient care. We give an overview of different WGS methods that are used in virology and summarize their advantages and disadvantages. Although there are only partially addressed technical, financial and ethical issues in regard to the clinical application of viral WGS, this technique provides important insights into virus transmission, evolution and pathogenesis.

Computational chemical biology, applied to research on hepatitis B virus (HBV), has two major branches: bioinformatics (statistical models) and first-principle methods (molecular physics). While bioinformatics focuses on statistical tools and biological databases, molecular physics uses mathematics and chemical theory to study the interactions of biomolecules. Three computational techniques most commonly used in HBV research are homology modeling, molecular docking, and molecular dynamics. Homology modeling is a computational simulation to predict protein structure and has been used to construct conformers of the viral polymerase (reverse transcriptase domain and RNase H domain) and the HBV X protein. Molecular docking is used to predict the most likely orientation of a ligand when it is bound to a protein, as well as determining an energy score of the docked conformation. Molecular dynamics is a simulation that analyzes biomolecule motions and determines conformation and stability patterns. All of these modeling techniques have aided in the understanding of resistance mutations on HBV non-nucleos(t)ide reverse-transcriptase inhibitor binding. Finally, bioinformatics can be used to study the DNA and RNA protein sequences of viruses to both analyze drug resistance and to genotype the viral genomes. Overall, with these techniques, and others, computational chemical biology is becoming more and more necessary in hepatitis B research. This article forms part of a symposium in Antiviral Research on "An unfinished story: from the discovery of the Australia antigen to the development of new curative therapies for hepatitis B."

Lately, advances in high-throughput technologies in biomedical research have led to a dramatic increase in the accessibility of molecular insights at multiple biological levels in hepatology. Much of this information is available in publications, but an increasing number of large-scale analyses are currently being stored in databases. Scopes of these databases are very divergent and may range from large, general databases collecting information on almost every known disease, to very specialized databases covering only a specific liver disease or aspect of hepatology. Over recent years, these bioinformatics data repositories have rapidly evolved into an essential aid for molecular hepatology. However, although publicly available through the internet, many of these databases are only known to a few experts. To facilitate access to these resources, the publicly available databases supporting research on liver diseases are summarized in this review.

The beginning of the second century of research in the field of virology (the first virus was discovered in 1898) was marked by its amalgamation with bioinformatics, resulting in the birth of a new domain--viroinformatics. The availability of more than 100 Web servers and databases embracing all or specific viruses (for example, dengue virus, influenza virus, hepatitis virus, human immunodeficiency virus [HIV], hemorrhagic fever virus [HFV], human papillomavirus [HPV], West Nile virus, etc.) as well as distinct applications (comparative/diversity analysis, viral recombination, small interfering RNA [siRNA]/short hairpin RNA [shRNA]/microRNA [miRNA] studies, RNA folding, protein-protein interaction, structural analysis, and phylotyping and genotyping) will definitely aid the development of effective drugs and vaccines. However, information about their access and utility is not available at any single source or on any single platform. Therefore, a compendium of various computational tools and resources dedicated specifically to virology is presented in this article.

The clinical course of infections with the hepatitis B virus (HBV) substantially varies between individuals, as a consequence of a complex interplay between viral, host, environmental and other factors. Due to the high genetic variability of HBV, the virus can be categorized into different HBV genotypes and subgenotypes, which considerably differ with respect to geographical distribution, transmission routes, disease progression, responses to antiviral therapy or vaccination, and clinical outcome measures such as cirrhosis or hepatocellular carcinoma. However, HBV (sub)genotyping has caused some controversies in the past due to misclassifications and incorrect interpretations of different genotyping methods. Thus, an accurate, holistic and dynamic classification system is essential. In this review article, we aimed at highlighting potential pitfalls in genetic and phylogenetic analyses of HBV and suggest novel terms for HBV classification. Analyzing full-length genome sequences when classifying genotypes and subgenotypes is the foremost prerequisite of this classification system. Careful attention must be paid to all aspects of phylogenetic analysis, such as bootstrapping values and meeting the necessary thresholds for (sub)genotyping. Quasi-subgenotype refers to subgenotypes that were incorrectly suggested to be novel. As many of these strains were misclassified due to genetic differences resulting from recombination, we propose the term "recombino-subgenotype". Moreover, immigration is an important confounding facet of global HBV distribution and substantially changes the geographic pattern of HBV (sub)genotypes. We therefore suggest the term "immigro-subgenotype" to distinguish exotic (sub)genotypes from native ones. We are strongly convinced that applying these two proposed terms in HBV classification will help harmonize this rapidly progressing field and allow for improved prophylaxis, diagnosis and treatment.

Hepatitis B virus (HBV) remains as the viral infection with the highest risk of transmission by transfusion. This risk is associated with window period donations, occult HBV infection (OBI) and the emergence of escape mutants, which render blood donations false negative for hepatitis B surface antigen (HBsAg) serological testing. A retrospective study was conducted to gain insights into the molecular epidemiology of HBV escape mutants in Scottish blood donors. The criterion for selection was HBV positivity either by serology or nucleic acid testing (NAT). HBsAg detection was compared across several commercial immunoassays. The full length S gene from plasma samples was PCR amplified, cloned and expressed in HepG2 cells. Eight samples showed HBsAg discordant results, while 5 OBI samples were found. Four escape mutants, containing missense mutations in the S gene, are described here. These mutations impaired HBsAg detection both from HBV infected plasma samples and from recombinant proteins derived from its infected donors. Phylogenetic analysis showed that most of the mutants were clustered in the genotype D and were closely related to strains from Asia and the Middle East. We report here a proline substitution, outside the major hydrophilic region, that impaired HBsAg detection in vivo and in vitro, warning about the risk for the emergence of vaccine escape mutants with mutations outside the major neutralisation site.

Drug resistance resulting from reverse transcriptase (RT) mutations is one of the main obstacles to successful hepatitis B virus (HBV) therapy. Indeed, HBV treatment guidelines recommend HBV genotypic resistance testing for patients receiving nucleos(t)ide RT inhibitors (N(t)RTIs) who develop virological failure. N(t)RTI-resistance mutations at 10 RT positions have been well characterized in phenotypic studies, however, data are lacking on the relative frequency of these mutations in N(t)RTI-treated and untreated individuals. There are also few published data on the extent of amino acid variation at most of the 344 positions of HBV RT and the extent to which this variation is influenced by N(t)RTI treatment. We retrieved 23,871 HBV RT sequences from GenBank and reviewed the published reports of these sequences to ascertain the number of individuals from whom the sequences were obtained, the N(t)RTI treatments of these individuals, and the year and region of virus sampling. We then used these data to populate a relational database we named HBVrtDB. As of July 2010, HBVrtDB contained 6811 sequences from 3869 individuals reported in 281 references. Among these 3869 individuals, 73% were N(t)RTI-naïve and 27% received one or more N(t)RTIs. Among the 10 well-characterized N(t)RTI-resistance mutations, L80I/V, V173L, L180M, A181T, T184S, S202G and M204I/V were significantly associated with treatment with lamivudine, an l-nucleoside analog, and A181S/T/V and N236T were significantly associated with treatment with adefovir, an acyclic nucleoside phosphonate. A similar analysis of ten additional less well-characterized resistance mutations demonstrated a significant association with N(t)RTI treatment for four of the mutations: L82M, S85A, A200V, and Q215S. We also created an interactive program, HBVseq, to enable users to identify mutations in submitted sequences and retrieve the prevalence of these mutations in HBVrtDB according to genotype and N(t)RTI treatment. HBVrtDB and HBVseq are available at http://hivdb.stanford.edu/HBV/releaseNotes/.

The aim of this study is to evaluate hepatitis B vaccine protection in those adults who have taken one or two does of vaccine before. It was a retrospective cross sectional study was conducted on fifty-six military personnel in Tehran, Iran in the spring 2007. Demographic data such as age, marital status, education level, number of vaccine doses injected and, type of vaccine and date of last vaccination was collected. Their serum was tested for HBs Ab, HBc Ab and HBs Ag and finally the results were analyzed by SPSS software. All individuals were male with the mean age of 33.9+/-8.9 years. Twelve individuals who had only received one dose of injected vaccine had no antibody against HBsAg and no protection against hepatitis B virus. Of forty-four individuals that had received two doses of injected vaccine, 27 persons (61.4%) were protected and had serum HBsAb more than 10 MIU mL(-1). In conclusion one dose of HBV vaccine cannot produce immunity for five years but two doses of HBV vaccine can produce immunity for five years. However, HBsAb should be tested to make sure of immunity.

The many Hepadnaviridae sequences available have widely varied functional annotation. The genomes are very compact (approximately 3.2 kb) but contain multiple layers of functional regulatory elements in addition to coding regions. Key regions are subject to purifying selection, as mutations in these regions will produce non-functional viruses.

These genomic sequences have been organized into a structured database to facilitate research at the molecular level. HBVRegDB is a comparative genomic analysis tool with an integrated underlying sequence database. The database contains genomic sequence data from representative viruses. In addition to INSDC and RefSeq annotation, HBVRegDB also contains expert and systematically calculated annotations (e.g. promoters) and comparative genome analysis results (e.g. blastn, tblastx). It also contains analyses based on curated HBV alignments. Information about conserved regions - including primary conservation (e.g. CDS-Plotcon) and RNA secondary structure predictions (e.g. Alidot) - is integrated into the database. A large amount of data is graphically presented using the GBrowse (Generic Genome Browser) adapted for analysis of viral genomes. Flexible query access is provided based on any annotated genomic feature. Novel regulatory motifs can be found by analysing the annotated sequences.

HBVRegDB serves as a knowledge database and as a comparative genomic analysis tool for molecular biologists investigating HBV. It is publicly available and complementary to other viral and HBV focused datasets and tools http://hbvregdb.otago.ac.nz. The availability of multiple and highly annotated sequences of viral genomes in one database combined with comparative analysis tools facilitates detection of novel genomic elements.