Identification of candidate microRNAs from Ostreid herpesvirus-1 (OsHV-1) and their potential role in the infection of Pacific oysters (Crassostrea gigas).

Oyster production is an economic activity of great interest worldwide. Recently, oysters have been suffering significant mortalities from OsHV-1infection, which has resulted in substantial economic loses in several countries around the world. Understanding viral pathogenicity mechanisms is of central importance for the establishment of disease control measures. Thus, the present work aimed to identify and characterize miRNAs from OsHV-1 as well as to predict their target transcripts in the virus and the host. OsHV-1 genome was used for the in silico discovery of pre-miRNAs. Subsequently, viral and host target transcripts of the OsHV-1 miRNAs were predicted according to the base pairing interaction between mature miRNAs and mRNA 3' untranslated regions (UTRs). Six unique pre-miRNAs were found in different regions of the viral genome, ranging in length from 85 to 172 nucleotides. A complex network of self-regulation of viral gene expression mediated by the miRNAs was identified. These sequences also seem to have a broad ability to regulate the expression of host immune-related genes, especially those associated with pathogen recognition. Our results suggest that OsHV-1 encodes miRNAs with important functions in the infection process, inducing self-regulation of viral transcripts, as well as affecting the regulation of Pacific oyster transcripts related to immunity. Understanding the molecular basis of host-pathogen interactions can help mitigate the recurrent events of oyster mass mortalities by OsHV-1 observed worldwide.

Prediction of MicroRNAs in the Epstein-Barr Virus Reveals Potential Targets for the Viral Self-Regulation.

Studies involving miRNAs have opened discussions about their broad participation in viral infections. Regarding the Human gammaherpesvirus 4 or Epstein-Barr virus (EBV), miRNAs are important regulators of viral and cellular gene expression during the infectious process, promoting viral persistence and, in some cases, oncogenic processes. We identified 55 miRNAs of EBV type 2 and inferred the viral mRNA target to self-regulate. This data indicate that gene self-repression is an important strategy for maintenance of the viral latent phase. In addition, a protein network was constructed to establish essential proteins in the self-regulation process. We found ten proteins that work as hubs, highlighting BTRF1 and BSRF1 as the most important proteins in the network. These results open a new way to understand the infection by EBV type 2, where viral genes can be targeted for avoiding oncogenic processes, as well as new therapies to suppress and combat the persistent viral infection.

Genomic Signatures Among Acanthamoeba polyphaga Entoorganisms Unveil Evidence of Coevolution.

The definition of a genomic signature (GS) is "the total net response to selective pressure". Recent isolation and sequencing of naturally occurring organisms, hereby named entoorganisms, within Acanthamoeba polyphaga, raised the hypothesis of a common genomic signature despite their diverse and unrelated evolutionary origin. Widely accepted and implemented tests for GS detection are oligonucleotide relative frequencies (OnRF) and relative codon usage (RCU) surveys. A common pattern and strong correlations were unveiled from OnRFs among A. polyphaga's Mimivirus and virophage Sputnik. RCU showed a common A-T bias at third codon position. We expanded tests to the amoebal mitochondrial genome and amoeba-resistant bacteria, achieving strikingly coherent results to the aforementioned viral analyses. The GSs in these entoorganisms of diverse evolutionary origin are coevolutionarily conserved within an intracellular environment that provides sanctuary for species of ecological and biomedical relevance.

Genomic signatures in viral sequences by in-frame and out-frame mutual information.

In order to understand the unique biology of viruses, we use the Mutual Information Function (MIF) to characterize 792 viral sequences comprising 458 viral whole genomes. A 3-base periodicity (3-bp) was observed only in DNA-viruses whereas RNA-viruses showed irregular patterns. The correlation of MIF values at frequencies of 3-bp (in-frame) with frequencies of 4 and 5bps (out-frame), turned out to be useful to distinguish viruses according to their respective taxonomic order, and whether they pertain to any of the three different kingdoms, Eubacteria, Archaea and Eukarya. The clustering of viruses was carried out by the use of a new statistics, namely, the pair of in- and out-frame values of the MIF. The clustering thus obtained turned out to be entirely consistent with the current viral taxonomy. As a result we were able to compare in a single plot both viral and cellular genomes unlike any given phylogenetic reconstruction.