Predicting novel mosquito-associated viruses from metatranscriptomic dark matter.

The exponential growth of metatranscriptomic studies dedicated to arboviral surveillance in mosquitoes has yielded an unprecedented volume of unclassified sequences referred to as the virome dark matter. Mosquito-associated viruses are classified based on their host range into Mosquito-specific viruses (MSV) or Arboviruses. While MSV replication is restricted to mosquito cells, Arboviruses infect both mosquito vectors and vertebrate hosts. We developed the MosViR pipeline designed to identify complex genomic discriminatory patterns for predicting novel MSV or Arboviruses from viral contigs as short as 500 bp. The pipeline combines the predicted probability score from multiple predictive models, ensuring a robust classification with Area Under ROC (AUC) values exceeding 0.99 for test datasets. To assess the practical utility of MosViR in actual cases, we conducted a comprehensive analysis of 24 published mosquito metatranscriptomic datasets. By mining this metatranscriptomic dark matter, we identified 605 novel mosquito-associated viruses, with eight putative novel Arboviruses exhibiting high probability scores. Our findings highlight the limitations of current homology-based identification methods and emphasize the potentially transformative impact of the MosViR pipeline in advancing the classification of mosquito-associated viruses. MosViR offers a powerful and highly accurate tool for arboviral surveillance and for elucidating the complexities of the mosquito RNA virome.

(m, n)-mer-a simple statistical feature for sequence classification.

Summary: The (m, n)-mer is a simple alternative classification feature based on conditional probability distributions. In this application note, we compared k-mer and (m, n)-mer frequency features in 11 distinct datasets used for binary, multiclass and clustering classifications. Our findings show that the (m, n)-mer frequency features are related to the highest performance metrics and often statistically outperformed the k-mers. Here, the (m, n)-mer frequencies improved performance for classifying smaller sequence lengths (as short as 300 bp) and yielded higher metrics when using short values of k (ranging from 2 to 4). Therefore, we present the (m, n)-mers frequencies to the scientific community as a feature that seems to be quite effective in identifying complex discriminatory patterns and classifying polyphyletic sequence groups. Availability and implementation: The (m, n)-mer algorithm is released as an R package within the CRAN project (https://cran.r-project.org/web/packages/mnmer) and is also available at https://github.com/labinfo-lncc/mnmer. Supplementary information: Supplementary data are available at Bioinformatics Advances online.

Differential expression analysis and profiling of hepatic miRNA and isomiRNA in dengue hemorrhagic fever.

Dengue virus causes dengue hemorrhagic fever (DHF) and has been associated to fatal cases worldwide. The liver is one of the most important target tissues in severe cases, due to its intense viral replication and metabolic role. microRNAs role during infection is crucial to understand the regulatory mechanisms of DENV infection and can help in diagnostic and anti-viral therapies development. We sequenced the miRNome of six fatal cases and compared to five controls, to characterize the human microRNAs expression profile in the liver tissue during DHF. Eight microRNAs were differentially expressed, including miR-126-5p, a regulatory molecule of endothelial cells, miR-122-5p, a liver specific homeostasis regulator, and miR-146a-5p, an interferon-regulator. Enrichment analysis with predicted target genes of microRNAs revealed regulatory pathways of apoptosis, involving MAPK, RAS, CDK and FAS. Immune response pathways were related to NF- kB, CC and CX families, IL and TLR. This is the first description of the human microRNA and isomicroRNA profile in liver tissues from DHF cases. The results demonstrated the association of miR-126-5p, miR-122-5p and miR-146a-5p with DHF liver pathogenesis, involving endothelial repair and vascular permeability regulation, control of homeostasis and expression of inflammatory cytokines.

Complete genome sequence of Piry vesiculovirus.

Piry virus (PIRYV) is a rhabdovirus (genus Vesiculovirus) and is described as a possible human pathogen, originally isolated from a Philander opossum trapped in Para State, Northern Brazil. This study describes the complete full coding sequence and the genetic characterization of PIRYV. The genome sequence reveals that PIRYV has a typical vesiculovirus-like organization, encoding the five genes typical of the genus. Phylogenetic analysis confirmed that PIRYV is most closely related to Perinet virus and clustered in the same clade as Chandipura and Isfahan vesiculoviruses.