Hepatitis B Virus and microRNAs: A Bioinformatics Approach.

In recent decades, microRNAs (miRNAs) have emerged as key regulators of gene expression, and the identification of viral miRNAs (v-miRNAs) within some viruses, including hepatitis B virus (HBV), has attracted significant attention. HBV infections often progress to chronic states (CHB) and may induce fibrosis/cirrhosis and hepatocellular carcinoma (HCC). The presence of HBV can dysregulate host miRNA expression, influencing several biological pathways, such as apoptosis, innate and immune response, viral replication, and pathogenesis. Consequently, miRNAs are considered a promising biomarker for diagnostic, prognostic, and treatment response. The dynamics of miRNAs during HBV infection are multifaceted, influenced by host variability and miRNA interactions. Given the ability of miRNAs to target multiple messenger RNA (mRNA), understanding the viral-host (human) interplay is complex but essential to develop novel clinical applications. Therefore, bioinformatics can help to analyze, identify, and interpret a vast amount of miRNA data. This review explores the bioinformatics tools available for viral and host miRNA research. Moreover, we introduce a brief overview focusing on the role of miRNAs during HBV infection. In this way, this review aims to help the selection of the most appropriate bioinformatics tools based on requirements and research goals.

Phylogenetic and Phylodynamic Analysis of Delta Strains Circulating in Italy.

The hepatitis delta virus (HDV) exhibits high genetic and evolutionary variability and is classified into eight genotypes (HDV-1 to -8). HDV-1 is the most widespread genotype worldwide and includes several subtypes. It predominates mainly in Europe, the Middle East, North America, and Northern Africa, and is associated with both severe and mild forms of liver disease. In this study, we performed phylogenetic and phylodynamic analyses of HDV strains circulating in Regione Lazio, Italy, to understand when these strains were introduced into the Lazio region and to define their genetic variability in Italy. Fifty HDV RNA positive patient samples were amplified using a nested RT-PCR approach targeting the HDV R0 region and sequenced. A phylogenetic tree of patient-derived sequences and reference sequences representing HDV-1 to -8 was constructed using the GTRGAMMA model in RAxML v8. The results indicated that HDV-1 was the predominant genotype with HDV-1d being the most frequently inferred subtype. HDV-1 sequences clustering with subtypes 1b and 1e were also identified. A phylodynamic analysis of HDV-1 sequences employing a Bayesian birth-death model inferred a clock rate of 3.04 × 10-4 substitutions per site per million years, with a 95% Highest Posterior Density (HPD) interval of 3.45 × 10-5 to 5.72 × 10-4. A Bayesian birth-death analysis with tree calibration based on a sample dating approach indicated multiple original sources of infection (from the late 1950s to late 1980s). Overall, these results suggest that HDV sequences from the native Italian and non-Italian patients analyzed in this study represent multiple lineages introduced across a wide period. A common ancestral origin should be excluded.