We report a massive expansion in RNA-encoded bacterial viral genomes, which have been overlooked within environments.

The number of novel bacteriophage sequences has expanded significantly as a result of many metagenomic studies of phage populations in diverse environments. Most of these novel sequences bear little or no homology to existing databases (referred to as the “viral dark matter”). Also, these sequences are primarily derived from DNA-encoded bacteriophages (phages) with few RNA phages included. Despite the rapid advancements in high-throughput sequencing, few studies enrich for RNA viruses, i.e., target viral rather than cellular fraction and/or RNA rather than DNA via a reverse transcriptase step, in an attempt to capture the RNA viruses present in a microbial communities. It is timely to compile existing and relevant information about RNA phages to provide an insight into many of their important biological features, which should aid in sequence-based discovery and in their subsequent annotation. Without comprehensive studies, the biological significance of RNA phages has been largely ignored. Future bacteriophage studies should be adapted to ensure they are properly represented in phageomic studies.

The human gut is colonised by a vast array of microbes that include bacteria, viruses, fungi, and archaea. While interest in these microbial entities has largely focused on the bacterial constituents, recently the viral component has attracted more attention. Metagenomic advances, compared to classical isolation procedures, have greatly enhanced our understanding of the composition, diversity, and function of viruses in the human microbiome (virome). We highlight that viral extraction methodologies are crucial in terms of identifying and characterising communities of viruses infecting eukaryotes and bacteria. Different viral extraction protocols, including those used in some of the most significant human virome publications to date, have introduced biases affecting their a overall conclusions. It is important that protocol variations should be clearly highlighted across studies, with the ultimate goal of identifying and acknowledging biases associated with different protocols and, perhaps, the generation of an unbiased and standardised method for examining this portion of the human microbiome.

The vast majority of described prokaryotic viruses have double-stranded or single-stranded DNA or double-stranded RNA genomes. Until 2020, a mere four prokaryotic single-stranded, positive-sense RNA viruses have been classified in two genera (Riboviria; Lenarviricota; Allassoviricetes; Leviviridae). Several recent metagenomic and metatranscriptomic studies revealed a vastly greater diversity of these viruses in prokaryotic soil communities than ever anticipated. Phylogenetic analysis of these newly discovered viruses prompted the reorganization of class Allassoviricetes, now renamed Leviviricetes, to include two orders, Norzivirales and Timlovirales, and a total of six families, 428 genera and 882 species. Here we outline the new taxonomy of Leviviricetes, approved and ratified in 2021 by the International Committee on Taxonomy of Viruses, and describe open-access hidden Markov models to accommodate the anticipated identification and future classification of hundreds, if not thousands, of additional class members into this new taxonomic framework.

The International Committee on Taxonomy of Viruses recently adopted, and is gradually implementing, a binomial naming format for virus species. Although full Latinization of these names remains optional, a standardized nomenclature based on Latinized binomials has the advantage of comparability with all other biological taxonomies. As a language without living native speakers, Latin is more culturally neutral than many contemporary languages, and words built from Latin roots are already widely used in the language of science across the world. Conversion of established species names to Latinized binomials or creation of Latinized binomials de novo may seem daunting, but the rules for name creation are straightforward and can be implemented in a formulaic manner. Here, we describe approaches, strategies and steps for creating Latinized binomials for virus species without prior knowledge of Latin. We also discuss a novel approach to the automated generation of large batches of novel genus and species names. Importantly, conversion to a binomial format does not affect virus names, many of which are created from local languages.