The genomic underpinnings of eukaryotic virus taxonomy: creating a sequence-based framework for family-level virus classification

How to introduce a new bacteriophage on the block: a short guide to phage classification

Bacteriophage (phage) studies established the field of molecular biology and continue to propel life science research forward due to their diversity, abundance, and potential applications. In this Gem article, we orient newcomers to four common ways phages are currently classified: infection cycle, morphology, taxonomy, and supergroup. By using these classifications, researchers can determine where any novel phage fits into the scheme of the known "phage-verse".

A simplified method of bacteriophage preparation for transmission electron microscope

Bacteriophages are viruses that infect bacteria. Researchers use different methods to study the characteristics of bacteriophages. Transmission electron microscope (TEM) is considered the best method to analyze these characteristics. However, the quality of TEM micrographs is significantly influenced by the preparation methods used to prepare the bacteriophages sample. In this study, researchers compared two different methods for preparing the bacteriophage samples. In one method was used SM buffer, while in the other used deionized water. The results were analyzed by TEM and compared with each other. Additionally, the viability of bacteriophage in deionized water and SM buffer at 4°C was determined through plaque assay within 72 hours. TEM micrographs showed that the quality of bacteriophage sample prepared with deionized water is superior to those prepared with SM buffer. Furthermore, the titer of the bacteriophages did not show a significant reduction during 72 hours in both SM and deionized water. In conclusion, the results suggested that preparation method can significantly impact the quality of TEM micrographs. Using sterile deionized water for the preparation of bacteriophages is a simple way to improve the quality of TEM micrographs and it is advisable to send the samples to the laboratory within 72 hours.

The virtue of training: extending phage host spectra against vancomycin-resistant Enterococcus faecium strains using the Appelmans method

Phage therapy has (re)emerged as a serious possibility for combating multidrug-resistant bacterial infections, including those caused by vancomycin-resistant Enterococcus faecium strains. These opportunistic pathogens belong to a specific clonal complex 17, against which relatively few phages have been screened. We isolated a collection of 21 virulent phages growing on these vancomycin-resistant isolates. Each of these phages harbored a typical narrow plaquing host range, lysing at most 5 strains and covering together 10 strains of our panel of 14 clinical isolates. To enlarge the host spectrum of our phages, the Appelmans protocol was used. We mixed four out of our most complementary phages in a cocktail that we iteratively grew on eight naive strains from our panel, of which six were initially refractory to at least three of the combined phages. Fifteen successive passages permitted to significantly improve the lytic activity of the cocktail, from which phages with extended host ranges within the E. faecium species could be isolated. A single evolved phage able to kill up to 10 of the 14 initial E. faecium strains was obtained, and it barely infected nearby species. All evolved phages had acquired point mutations or a recombination event in the tail fiber genetic region, suggesting these genes might have driven phage evolution by contributing to their extended host spectra.

Genetic diversity of RNA viruses infecting invertebrate pests of rice

Invertebrate species are a natural reservoir of viral genetic diversity, and invertebrate pests are widely distributed in crop fields. However, information on viruses infecting invertebrate pests of crops is limited. In this report, we describe the deep metatranscriptomic sequencing of 88 invertebrate samples covering all major invertebrate pests in rice fields. We identified 296 new RNA viruses and 13 known RNA viruses. These viruses clustered within 31 families, with many highly divergent viruses constituting potentially new families and genera. Of the identified viruses, 13 RNA viruses clustered within the Fiersviridae family of bacteriophages, and 48 RNA viruses clustered within families and genera of mycoviruses. We detected known rice viruses in novel invertebrate hosts at high abundances. Furthermore, some novel RNA viruses have genome structures closely matching to known plant viruses and clustered within genera of several plant virus species. Forty-five potential insect pathogenic RNA viruses were detected in invertebrate species. Our analysis revealed that host taxonomy plays a major role and geographical location plays an important role in structuring viral diversity. Cross-species transmission of RNA viruses was detected between invertebrate hosts. Newly identified viral genomes showed extensive variation for invertebrate viral families or genera. Together, the large-scale metatranscriptomic analysis greatly expands our understanding of RNA viruses in rice invertebrate species, the results provide valuable information for developing efficient strategies to manage insect pests and virus-mediated crop diseases.

MArVD2: a machine learning enhanced tool to discriminate between archaeal and bacterial viruses in viral datasets

Our knowledge of viral sequence space has exploded with advancing sequencing technologies and large-scale sampling and analytical efforts. Though archaea are important and abundant prokaryotes in many systems, our knowledge of archaeal viruses outside of extreme environments is limited. This largely stems from the lack of a robust, high-throughput, and systematic way to distinguish between bacterial and archaeal viruses in datasets of curated viruses. Here we upgrade our prior text-based tool (MArVD) via training and testing a random forest machine learning algorithm against a newly curated dataset of archaeal viruses. After optimization, MArVD2 presented a significant improvement over its predecessor in terms of scalability, usability, and flexibility, and will allow user-defined custom training datasets as archaeal virus discovery progresses. Benchmarking showed that a model trained with viral sequences from the hypersaline, marine, and hot spring environments correctly classified 85% of the archaeal viruses with a false detection rate below 2% using a random forest prediction threshold of 80% in a separate benchmarking dataset from the same habitats.

Developments in the classification and nomenclature of arthropod-infecting large DNA viruses that contain pif genes

Viruses of four families of arthropod-specific, large dsDNA viruses (the nuclear arthropod large DNA viruses, or NALDVs) possess homologs of genes encoding conserved components involved in the baculovirus primary infection mechanism. The presence of such homologs encoding per os infectivity factors (pif genes), along with their absence from other viruses and the occurrence of other shared characteristics, suggests a common origin for the viruses of these families. Therefore, the class Naldaviricetes was recently established, accommodating these four families. In addition, within this class, the ICTV approved the creation of the order Lefavirales for three of these families, whose members carry homologs of the baculovirus genes that code for components of the viral RNA polymerase, which is responsible for late gene expression. We further established a system for the binomial naming of all virus species in the order Lefavirales, in accordance with a decision by the ICTV in 2019 to move towards a standardized nomenclature for all virus species. The binomial species names for members of the order Lefavirales consist of the name of the genus to which the species belongs (e.g., Alphabaculovirus), followed by a single epithet that refers to the host species from which the virus was originally isolated. The common names of viruses and the abbreviations thereof will not change, as the format of virus names lies outside the remit of the ICTV.

Virus taxonomy and the role of the International Committee on Taxonomy of Viruses (ICTV)

The taxonomy of viruses is developed and overseen by the International Committee on Taxonomy of Viruses (ICTV), which scrutinizes, approves and ratifies taxonomic proposals, and maintains a list of virus taxa with approved names (https://ictv.global). The ICTV has approximately 180 members who vote by simple majority. Taxon-specific Study Groups established by the ICTV have a combined membership of over 600 scientists from the wider virology community; they provide comprehensive expertise across the range of known viruses and are major contributors to the creation and evaluation of taxonomic proposals. Proposals can be submitted by anyone and will be considered by the ICTV irrespective of Study Group support. Thus, virus taxonomy is developed from within the virology community and realized by a democratic decision-making process. The ICTV upholds the distinction between a virus or replicating genetic element as a physical entity and the taxon category to which it is assigned. This is reflected by the nomenclature of the virus species taxon, which is now mandated by the ICTV to be in a binomial format (genus + species epithet) and is typographically distinct from the names of viruses. Classification of viruses below the rank of species (such as, genotypes or strains) is not within the remit of the ICTV. This article, authored by the ICTV Executive Committee, explains the principles of virus taxonomy and the organization, function, processes and resources of the ICTV, with the aim of encouraging greater understanding and interaction among the wider virology community.

VirClust-A Tool for Hierarchical Clustering, Core Protein Detection and Annotation of (Prokaryotic) Viruses

Recent years have seen major changes in the classification criteria and taxonomy of viruses. The current classification scheme, also called "megataxonomy of viruses", recognizes six different viral realms, defined based on the presence of viral hallmark genes (VHGs). Within the realms, viruses are classified into hierarchical taxons, ideally defined by the phylogeny of their shared genes. To enable the detection of shared genes, viruses have first to be clustered, and there is currently a need for tools to assist with virus clustering and classification. Here, VirClust is presented. It is a novel, reference-free tool capable of performing: (i) protein clustering, based on BLASTp and Hidden Markov Models (HMMs) similarities; (ii) hierarchical clustering of viruses based on intergenomic distances calculated from their shared protein content; (iii) identification of core proteins and (iv) annotation of viral proteins. VirClust has flexible parameters both for protein clustering and for splitting the viral genome tree into smaller genome clusters, corresponding to different taxonomic levels. Benchmarking on a phage dataset showed that the genome trees produced by VirClust match the current ICTV classification at family, sub-family and genus levels. VirClust is freely available, as a web-service and stand-alone tool.

Ancient origin of Jingchuvirales derived glycoproteins integrated in arthropod genomes

Endogenous virus elements (EVEs) are viral-derived sequences integrated into their host genomes. EVEs of the Jingchuvirales order were detected in a wide range of insect genomes covering several distantly related families. Moreover, Jingchuvirales-derived glycoproteins were recently associated by our group with the origin of a putative new retrovirus based on a glycoprotein captured by a mosquito retrotransposon. But, except for mosquitoes, there is a lack of a more detailed understanding of the endogenization mechanism, timing, and frequency per Jingchuvirales viral lineages. Here we screened Jingchuvirales glycoprotein-derived EVEs (Jg-EVEs) in eukaryotic genomes. We found six distinct endogenization events of Jg-EVEs, that belong to two out of five known Jingchuvirales families (Chuviridae and Natareviridae). For seven arthropod families bearing Jg-EVEs there is no register of bona fide circulating chuvirus infection. Hence, our results show that Jingchuvirales viruses infected or still infect these host families. Although we found abundant evidence of LTR-Gypsy retrotransposons fragments associated with the glycoprotein in Hymenoptera and other insect orders, our results show that the widespread distribution of Jingchuvirales glycoproteins in extant Arhtropods is a result of multiple ancient endogenization events and that these virus fossils are being vertically inherited in Arthropods genomes for millions of years.

Identification of RNA Virus-Derived RdRp Sequences in Publicly Available Transcriptomic Data Sets

RNA viruses are abundant and highly diverse and infect all or most eukaryotic organisms. However, only a tiny fraction of the number and diversity of RNA virus species have been catalogued. To cost-effectively expand the diversity of known RNA virus sequences, we mined publicly available transcriptomic data sets. We developed 77 family-level Hidden Markov Model profiles for the viral RNA-dependent RNA polymerase (RdRp)-the only universal "hallmark" gene of RNA viruses. By using these to search the National Center for Biotechnology Information Transcriptome Shotgun Assembly database, we identified 5,867 contigs encoding RNA virus RdRps or fragments thereof and analyzed their diversity, taxonomic classification, phylogeny, and host associations. Our study expands the known diversity of RNA viruses, and the 77 curated RdRp Profile Hidden Markov Models provide a useful resource for the virus discovery community.

Four principles to establish a universal virus taxonomy

A universal taxonomy of viruses is essential for a comprehensive view of the virus world and for communicating the complicated evolutionary relationships among viruses. However, there are major differences in the conceptualisation and approaches to virus classification and nomenclature among virologists, clinicians, agronomists, and other interested parties. Here, we provide recommendations to guide the construction of a coherent and comprehensive virus taxonomy, based on expert scientific consensus. Firstly, assignments of viruses should be congruent with the best attainable reconstruction of their evolutionary histories, i.e., taxa should be monophyletic. This fundamental principle for classification of viruses is currently included in the International Committee on Taxonomy of Viruses (ICTV) code only for the rank of species. Secondly, phenotypic and ecological properties of viruses may inform, but not override, evolutionary relatedness in the placement of ranks. Thirdly, alternative classifications that consider phenotypic attributes, such as being vector-borne (e.g., "arboviruses"), infecting a certain type of host (e.g., "mycoviruses," "bacteriophages") or displaying specific pathogenicity (e.g., "human immunodeficiency viruses"), may serve important clinical and regulatory purposes but often create polyphyletic categories that do not reflect evolutionary relationships. Nevertheless, such classifications ought to be maintained if they serve the needs of specific communities or play a practical clinical or regulatory role. However, they should not be considered or called taxonomies. Finally, while an evolution-based framework enables viruses discovered by metagenomics to be incorporated into the ICTV taxonomy, there are essential requirements for quality control of the sequence data used for these assignments. Combined, these four principles will enable future development and expansion of virus taxonomy as the true evolutionary diversity of viruses becomes apparent.

Large-scale investigation of zoonotic viruses in the era of high-throughput sequencing

Zoonotic diseases considerably impact public health and socioeconomics. RNA viruses reportedly caused approximately 94% of zoonotic diseases documented from 1990 to 2010, emphasizing the importance of investigating RNA viruses in animals. Furthermore, it has been estimated that hundreds of thousands of animal viruses capable of infecting humans are yet to be discovered, warning against the inadequacy of our understanding of viral diversity. High-throughput sequencing (HTS) has enabled the identification of viral infections with relatively little bias. Viral searches using both symptomatic and asymptomatic animal samples by HTS have revealed hidden viral infections. This review introduces the history of viral searches using HTS, current analytical limitations, and future potentials. We primarily summarize recent research on large-scale investigations on viral infections reusing HTS data from public databases. Furthermore, considering the accumulation of uncultivated viruses, we discuss current studies and challenges for connecting viral sequences to their phenotypes using various approaches: performing data analysis, developing predictive modeling, or implementing high-throughput platforms of virological experiments. We believe that this article provides a future direction in large-scale investigations of potential zoonotic viruses using the HTS technology.

Phage family classification under Caudoviricetes: A review of current tools using the latest ICTV classification framework

Bacteriophages, which are viruses infecting bacteria, are the most ubiquitous and diverse entities in the biosphere. There is accumulating evidence revealing their important roles in shaping the structure of various microbiomes. Thanks to (viral) metagenomic sequencing, a large number of new bacteriophages have been discovered. However, lacking a standard and automatic virus classification pipeline, the taxonomic characterization of new viruses seriously lag behind the sequencing efforts. In particular, according to the latest version of ICTV, several large phage families in the previous classification system are removed. Therefore, a comprehensive review and comparison of taxonomic classification tools under the new standard are needed to establish the state-of-the-art. In this work, we retrained and tested four recently published tools on newly labeled databases. We demonstrated their utilities and tested them on multiple datasets, including the RefSeq, short contigs, simulated metagenomic datasets, and low-similarity datasets. This study provides a comprehensive review of phage family classification in different scenarios and a practical guidance for choosing appropriate taxonomic classification pipelines. To our best knowledge, this is the first review conducted under the new ICTV classification framework. The results show that the new family classification framework overall leads to better conserved groups and thus makes family-level classification more feasible.

Complete Genome Sequences of Five Phietaviruses Infecting Staphylococcus aureus

The annotated whole-genome sequences of five cultured phietaviruses infecting Staphylococcus aureus are presented. They are closely related to prophages that were previously sequenced as part of S. aureus genomes.

Ayka, a Novel Curtobacterium Bacteriophage, Provides Protection against Soybean Bacterial Wilt and Tan Spot

Diseases caused by the Gram-positive bacterium Curtobacteriumflaccumfaciens pv. flaccumfaciens (Cff) inflict substantial economic losses in soybean cultivation. Use of specific bacterial viruses (bacteriophages) for treatment of seeds and plants to prevent the development of bacterial infections is a promising approach for bioprotection in agriculture. Phage control has been successfully tested for a number of staple crops. However, this approach has never been applied to treat bacterial diseases of legumes caused by Cff, and no specific bacteriophages have been known to date. This paper presents detailed characteristics of the first lytic bacteriophage infecting this pathogen. Phage Ayka, related to φ29-like (Salasmaviridae) viruses, but representing a new subfamily, was shown to control the development of bacterial wilt and tan spot in vitro and in greenhouse plants.

Novel lineages of single-stranded DNA phages that coevolved with the symbiotic bacteria Rhizobium

This study describes novel single-stranded DNA phages isolated from common bean agriculture soils by infection of the nitrogen-fixing symbiotic bacteria Rhizobium etli and R. phaseoli. A total of 29 phages analyzed have 4.3-6 kb genomes in size and GC 59-60%. They belong to different clades unrelated to other Microviridae subfamilies. Three-dimensional models of the major capsid protein (MCP) showed a conserved β-barrel structural "jelly-roll" fold. A variable-length loop in the MCPs distinguished three Rhizobium microvirus groups. Microviridae subfamilies were consistent with viral clusters determined by the protein-sharing network. All viral clusters, except for Bullavirinae, included mostly microviruses identified in metagenomes from distinct ecosystems. Two Rhizobium microvirus clusters, chaparroviruses, and chicoviruses, were included within large viral unknown clusters with microvirus genomes identified in diverse metagenomes. A third Rhizobium microvirus cluster belonged to the subfamily Amoyvirinae. Phylogenetic analysis of the MCP confirms the divergence of the Rhizobium microviruses into separate clades. The phylogeny of the bacterial hosts matches the microvirus MCP phylogeny, suggesting a coevolutionary history between the phages and their bacterial host. This study provided essential biological information on cultivated microvirus for understanding the evolution and ecological diversification of the Microviridae family in diverse microbial ecosystems.

Analysis of public domain plant transcriptomes expands the phylogenetic diversity of the family Secoviridae

Secoviruses are mono-/bipartite plant-infecting, icosahedral RNA viruses that incite economically important diseases in plants. In the present study, nine secoviruses tentatively named as Ananas comosus secovirus (AcSV), Artocarpus altilis secovirus (AaSV), Boehmeria nivea secovirus (BnSV), Gynostemma pentaphyllum secovirus (GpSV), Orobanche cernua secovirus (OcSV), Paris polyphylla secovirus 1 (PpSV1), Paris polyphylla secovirus 2 (PpSV2), Rhododendron delavayi secovirus (RdSV), and Yucca gloriosa secovirus (YgSV) were identified by probing publicly available transcriptomes of eight plant species. Coding-complete genome/genome segments of all the identified viruses encoding a polyprotein were recovered. Two of the nine identified viruses-AcSV and GpSV were discovered in few of the small RNA libraries of respective plant species. Putative cleavage sites were predicted in polyproteins encoded by AcSV, GpSV, PpSV2 and YgSV genome segments. Phylogenetic and sequence identity analyses revealed that AcSV, GpSV and YgSV, PpSV1 and RdSV putatively belong to the genera- Sadwavirus (sub genus: Cholivirus), Fabavirus, Nepovirus and Waikavirus, respectively, while AaSV, BnSV, and PpSV2 may represent a distinct group of viruses within the family Secoviridae as they could not conclusively be assigned to a single genus.

Comprehensive Evaluation of RNA and DNA Viromic Methods Based on Species Richness and Abundance Analyses Using Marmot Rectal Samples

Viral metagenomics is the most powerful tool to profile viromic composition for a given sample. Different viromic methods, including amplification-free ones, have been developed, but choosing them for different purposes requires comprehensive benchmarks. Here, we assessed the performance of four routinely used methods, i.e., multiple displacement amplification (MDA), direct metagenomic sequencing (MTG), sequence-independent single-primer amplification (SIA), and metatranscriptomic sequencing (MTT), using marmot rectal samples as the templates spiked with five known viruses of different genome types. The obtained clean data were differently contaminated by host and bacterial genomes, resulting in MDA having the most, with ~72.1%, but MTT had only ~7.5% data, useful for follow-up viromic analysis. MDA showed a broader spectrum with higher efficiency to profile the DNA virome, and MTT captured almost all RNA viruses with extraordinary sensitivity; hence, they are advisable in richness-based viromic studies. MTG was weak in capturing single-stranded DNA viruses, and SIA could detect both RNA and DNA viruses but with high randomness. Due to biases to certain types of viruses, the four methods caused different alterations to species abundance compared to the initial virus composition. SIA and MDA introduced greater stochastic errors to relative abundances of species, genus, and family taxa, whereas the two amplification-free methods were more tolerant toward such errors and thus are recommendable in abundance-based analyses. In addition, genus taxon is a compromising analytic level that ensures technically supported and biologically and/or ecologically meaningful viromic conclusions. IMPORTANCE Viral metagenomics can be roughly divided into species richness-based studies and species abundance-based analyses. Viromic methods with different principles have been developed, but rational selection of these techniques according to different purposes requires comprehensive understanding of their properties. By assessing the four most widely used methods using template samples, we found that multiple displacement amplification (MDA) and metatranscriptomic sequencing (MTT) are advisable for species richness-based viromic studies, as they show excellent efficiency to detect DNA and RNA viruses. Meanwhile, metagenomic sequencing (MTG) and MTT are more compatible with stochastic errors of methods introduced into relative abundance of viromic taxa and hence are rational choices in species abundance-based analyses. This study also highlights that MTG needs to tackle host genome contamination and ameliorate the capacity to detect single-stranded DNA viruses in the future, and the MTT method requires an improvement in bacterial rRNA depletion prior to library preparation.

VirusTaxo: Taxonomic classification of viruses from the genome sequence using k-mer enrichment

Classification of viruses into their taxonomic ranks (e.g., order, family, and genus) provides a framework to organize an abundant population of viruses. Next-generation metagenomic sequencing technologies lead to a rapid increase in generating sequencing data of viruses which require bioinformatics tools to analyze the taxonomy. Many metagenomic taxonomy classifiers have been developed to study microbiomes, but it is particularly challenging to assign the taxonomy of diverse virus sequences and there is a growing need for dedicated methods to be developed that are optimized to classify virus sequences into their taxa. For taxonomic classification of viruses from metagenomic sequences, we developed VirusTaxo using diverse (e.g., 402 DNA and 280 RNA) genera of viruses. VirusTaxo has an average accuracy of 93% at genus level prediction in DNA and RNA viruses. VirusTaxo outperformed existing taxonomic classifiers of viruses where it assigned taxonomy of a larger fraction of metagenomic contigs compared to other methods. Benchmarking of VirusTaxo on a collection of SARS-CoV-2 sequencing libraries and metavirome datasets suggests that VirusTaxo can characterize virus taxonomy from highly diverse contigs and provide a reliable decision on the taxonomy of viruses.

Computational Tools for the Analysis of Uncultivated Phage Genomes

Over a century of bacteriophage research has uncovered a plethora of fundamental aspects of their biology, ecology, and evolution. Furthermore, the introduction of community-level studies through metagenomics has revealed unprecedented insights on the impact that phages have on a range of ecological and physiological processes. It was not until the introduction of viral metagenomics that we began to grasp the astonishing breadth of genetic diversity encompassed by phage genomes. Novel phage genomes have been reported from a diverse range of biomes at an increasing rate, which has prompted the development of computational tools that support the multilevel characterization of these novel phages based solely on their genome sequences. The impact of these technologies has been so large that, together with MAGs (Metagenomic Assembled Genomes), we now have UViGs (Uncultivated Viral Genomes), which are now officially recognized by the International Committee for the Taxonomy of Viruses (ICTV), and new taxonomic groups can now be created based exclusively on genomic sequence information. Even though the available tools have immensely contributed to our knowledge of phage diversity and ecology, the ongoing surge in software programs makes it challenging to keep up with them and the purpose each one is designed for. Therefore, in this review, we describe a comprehensive set of currently available computational tools designed for the characterization of phage genome sequences, focusing on five specific analyses: (i) assembly and identification of phage and prophage sequences, (ii) phage genome annotation, (iii) phage taxonomic classification, (iv) phage-host interaction analysis, and (v) phage microdiversity.

GRAN3SAT: Creating Flexible Higher-Order Logic Satisfiability in the Discrete Hopfield Neural Network

One of the main problems in representing information in the form of nonsystematic logic is the lack of flexibility, which leads to potential overfitting. Although nonsystematic logic improves the representation of the conventional k Satisfiability, the formulations of the first, second, and third-order logical structures are very predictable. This paper proposed a novel higher-order logical structure, named G-Type Random k Satisfiability, by capitalizing the new random feature of the first, second, and third-order clauses. The proposed logic was implemented into the Discrete Hopfield Neural Network as a symbolic logical rule. The proposed logic in Discrete Hopfield Neural Networks was evaluated using different parameter settings, such as different orders of clauses, different proportions between positive and negative literals, relaxation, and differing numbers of learning trials. Each evaluation utilized various performance metrics, such as learning error, testing error, weight error, energy analysis, and similarity analysis. In addition, the flexibility of the proposed logic was compared with current state-of-the-art logic rules. Based on the simulation, the proposed logic was reported to be more flexible, and produced higher solution diversity.

Quantifying and Cataloguing Unknown Sequences within Human Microbiomes

Advances in genome sequencing technologies and lower costs have enabled the exploration of a multitude of known and novel environments and microbiomes. This has led to an exponential growth in the raw sequence data that are deposited in online repositories. Metagenomic and metatranscriptomic data sets are typically analysed with regard to a specific biological question. However, it is widely acknowledged that these data sets are comprised of a proportion of sequences that bear no similarity to any currently known biological sequence, and this so-called "dark matter" is often excluded from downstream analyses. In this study, a systematic framework was developed to assemble, identify, and measure the proportion of unknown sequences present in distinct human microbiomes. This framework was applied to 40 distinct studies, comprising 963 samples, and covering 10 different human microbiomes including fecal, oral, lung, skin, and circulatory system microbiomes. We found that while the human microbiome is one of the most extensively studied, on average 2% of assembled sequences have not yet been taxonomically defined. However, this proportion varied extensively among different microbiomes and was as high as 25% for skin and oral microbiomes that have more interactions with the environment. A rate of taxonomic characterization of 1.64% of unknown sequences being characterized per month was calculated from these taxonomically unknown sequences discovered in this study. A cross-study comparison led to the identification of similar unknown sequences in different samples and/or microbiomes. Both our computational framework and the novel unknown sequences produced are publicly available for future cross-referencing. Our approach led to the discovery of several novel viral genomes that bear no similarity to sequences in the public databases. Some of these are widespread as they have been found in different microbiomes and studies. Hence, our study illustrates how the systematic characterization of unknown sequences can help the discovery of novel microbes, and we call on the research community to systematically collate and share the unknown sequences from metagenomic studies to increase the rate at which the unknown sequence space can be classified.

Mono- and combinational drug therapies for global viral pandemic preparedness

Broadly effective antiviral therapies must be developed to be ready for clinical trials, which should begin soon after the emergence of new life-threatening viruses. Here, we pave the way towards this goal by reviewing conserved druggable virus-host interactions, mechanisms of action, immunomodulatory properties of available broad-spectrum antivirals (BSAs), routes of BSA delivery, and interactions of BSAs with other antivirals. Based on the review, we concluded that the range of indications of BSAs can be expanded, and new pan- and cross-viral mono- and combinational therapies can be developed. We have also developed a new scoring algorithm that can help identify the most promising few of the thousands of potential BSAs and BSA-containing drug cocktails (BCCs) to prioritize their development during the critical period between the identification of a new virus and the development of virus-specific vaccines, drugs, and therapeutic antibodies.

Antiviral plant-derived natural products to combat RNA viruses: Targets throughout the viral life cycle

There is a need for new effective antivirals, particularly in response to the development of antiviral drug resistance and emerging RNA viruses such as SARS‐CoV‐2. Plants are a significant source of structurally diverse bioactive compounds for drug discovery suggesting that plant‐derived natural products could be developed as antiviral agents. This article reviews the antiviral activity of plant‐derived natural products against RNA viruses, with a focus on compounds targeting specific stages of the viral life cycle. A range of plant extracts and compounds have been identified with antiviral activity, often against multiple virus families suggesting they may be useful as broad‐spectrum antiviral agents. The antiviral mechanism of action of many of these phytochemicals is not fully understood and there are limited studies and clinical trials demonstrating their efficacy and toxicity in vivo. Further research is needed to evaluate the therapeutic potential of plant‐derived natural products as antiviral agents.

Bioinformatics of virus taxonomy: foundations and tools for developing sequence-based hierarchical classification

The genome sequence is the only characteristic readily obtainable for all known viruses, underlying the growing role of comparative genomics in organizing knowledge about viruses in a systematic evolution-aware way, known as virus taxonomy. Overseen by the International Committee on Taxonomy of Viruses (ICTV), development of virus taxonomy involves taxa demarcation at 15 ranks of a hierarchical classification, often in host-specific manner. Outside the ICTV remit, researchers assess fitting numerous unclassified viruses into the established taxa. They employ different metrics of virus clustering, basing on conserved domain(s), separation of viruses in rooted phylogenetic trees and pair-wise distance space. Computational approaches differ further in respect to methodology, number of ranks considered, sensitivity to uneven virus sampling, and visualization of results. Advancing and using computational tools will be critical for improving taxa demarcation across the virosphere and resolving rank origins in research that may also inform experimental virology.

Perspective on taxonomic classification of uncultivated viruses

Historically, virus taxonomy has been limited to describing viruses that were readily cultivated in the laboratory or emerging in natural biomes. Metagenomic analyses, single-particle sequencing, and database mining efforts have yielded new sequence data on an astounding number of previously unknown viruses. As metagenomes are relatively free of biases, these data provide an unprecedented insight into the vastness of the virosphere, but to properly value the extent of this diversity it is critical that the viruses are taxonomically classified. Inclusion of uncultivated viruses has already improved the process as well as the understanding of the taxa, viruses, and their evolutionary relationships. The continuous development and testing of computational tools will be required to maintain a dynamic virus taxonomy that can accommodate the new discoveries.

Diversity, taxonomy, and evolution of archaeal viruses of the class Caudoviricetes

The archaeal tailed viruses (arTV), evolutionarily related to tailed double-stranded DNA (dsDNA) bacteriophages of the class Caudoviricetes, represent the most common isolates infecting halophilic archaea. Only a handful of these viruses have been genomically characterized, limiting our appreciation of their ecological impacts and evolution. Here, we present 37 new genomes of haloarchaeal tailed virus isolates, more than doubling the current number of sequenced arTVs. Analysis of all 63 available complete genomes of arTVs, which we propose to classify into 14 new families and 3 orders, suggests ancient divergence of archaeal and bacterial tailed viruses and points to an extensive sharing of genes involved in DNA metabolism and counterdefense mechanisms, illuminating common strategies of virus-host interactions with tailed bacteriophages. Coupling of the comparative genomics with the host range analysis on a broad panel of haloarchaeal species uncovered 4 distinct groups of viral tail fiber adhesins controlling the host range expansion. The survey of metagenomes using viral hallmark genes suggests that the global architecture of the arTV community is shaped through recurrent transfers between different biomes, including hypersaline, marine, and anoxic environments.

Inherent virus characteristics and host range drive the zoonotic and emerging potential of viruses

Understanding the zoonotic and emerging potential of viruses is critical to prevent and control spread that can cause disease epidemics or pandemics. We developed a database using the most up-to-date information from the International Committee on Taxonomy of Viruses (4958 virus species) and identified 1479 vertebrate virus species and their host ranges. Viral traits and host ranges were then used as predictors in generalized linear mixed models for three host-associated outcomes - confirmed zoonotic, potential zoonotic and disease emergence. We identified significant interactions between host range and viral characteristics, not previously reported, that influence the zoonotic and emergence potential of viruses. Bat- and livestock-adapted viruses posed high risk, and the risk increased substantially if these viruses were also present in other vertebrates or were not reported from invertebrates. Our model predicted 39 viruses of interest that have never been reported to have zoonotic potential (27) or to potentially become emerging human viruses (12). We conclude that nucleic acid type is important in identifying the zoonotic and emerging potential of viruses. We recommend enhanced surveillance and monitoring of these virus species identified with a zoonotic and emerging potential to mitigate disease outbreaks and future epidemics.

A Previously Undescribed Highly Prevalent Phage Identified in a Danish Enteric Virome Catalog

Gut viruses are important, yet often neglected, players in the complex human gut microbial ecosystem. Recently, the number of human gut virome studies has been increasing; however, we are still only scratching the surface of the immense viral diversity. In this study, 254 virus-enriched fecal metagenomes from 204 Danish subjects were used to generate the Danish Enteric Virome Catalog (DEVoC) containing 12,986 nonredundant viral scaffolds, of which the majority was previously undescribed, encoding 190,029 viral genes. The DEVoC was used to compare 91 healthy DEVoC gut viromes from children, adolescents, and adults that were used to create the DEVoC. Gut viromes of healthy Danish subjects were dominated by phages. While most phage genomes (PGs) only occurred in a single subject, indicating large virome individuality, 39 PGs were present in more than 10 healthy subjects. Among these 39 PGs, the prevalences of three PGs were associated with age. To further study the prevalence of these 39 prevalent PGs, 1,880 gut virome data sets of 27 studies from across the world were screened, revealing several age-, geography-, and disease-related prevalence patterns. Two PGs also showed a remarkably high prevalence worldwide-a crAss-like phage (20.6% prevalence), belonging to the tentative AlphacrAssvirinae subfamily, and a previously undescribed circular temperate phage infecting Bacteroides dorei (14.4% prevalence), called LoVEphage because it encodes lots of viral elements. Due to the LoVEphage's high prevalence and novelty, public data sets in which the LoVEphage was detected were de novo assembled, resulting in an additional 18 circular LoVEphage-like genomes (67.9 to 72.4 kb). IMPORTANCE Through generation of the DEVoC, we added numerous previously uncharacterized viral genomes and genes to the ever-increasing worldwide pool of human gut viromes. The DEVoC, the largest human gut virome catalog generated from consistently processed fecal samples, facilitated the analysis of the 91 healthy Danish gut viromes. Characterizing the biggest cohort of healthy gut viromes from children, adolescents, and adults to date confirmed the previously established high interindividual variation in human gut viromes and demonstrated that the effect of age on the gut virome composition was limited to the prevalence of specific phage (groups). The identification of a previously undescribed prevalent phage illustrates the usefulness of developing virome catalogs, and we foresee that the DEVoC will benefit future analysis of the roles of gut viruses in human health and disease.

A High Rate Algal Pond Hosting a Dynamic Community of RNA Viruses

Despite a surge of RNA virome sequencing in recent years, there are still many RNA viruses to uncover-as indicated by the relevance of viral dark matter to RNA virome studies (i.e., putative viruses that do not match to taxonomically identified viruses). This study explores a unique site, a high-rate algal pond (HRAP), for culturing industrially microalgae, to elucidate new RNA viruses. The importance of viral-host interactions in aquatic systems are well documented, and the ever-expanding microalgae industry is no exception. As the industry becomes a more important source of sustainable plastic manufacturing, a producer of cosmetic pigments and alternative protein sources, and a means of CO2 remediation in the face of climate change, studying microalgal viruses becomes a vital practice for proactive management of microalgae cultures at the industrial level. This study provides evidence of RNA microalgal viruses persisting in a CO2 remediation pilot project HRAP and uncovers the diversity of the RNA virosphere contained within it. Evidence shows that family Marnaviridae is cultured in the basin, alongside other potential microalgal infecting viruses (e.g., family Narnaviridae, family Totitiviridae, and family Yueviridae). Finally, we demonstrate that the RNA viral diversity of the HRAP is temporally dynamic across two successive culturing seasons.

New viruses on the rise: a One Health and ecosystem-based perspective on emerging viruses

Empowered by interdisciplinary collaboration, we now have the tools to identify new viruses, contain future outbreaks and broadly understand natural processes toward a global health.

A proposed division of the family Picornaviridae into subfamilies based on phylogenetic relationships and functional genomic organization

The highly diverse virus family Picornaviridae presently comprises 68 approved genera with 158 species plus many unassigned viruses. In order to better match picornavirus taxonomy to the functional and genomic groupings between genera, the establishment of five subfamilies (Caphthovirinae, Kodimesavirinae, Ensavirinae, Paavivirinae and Heptrevirinae) is proposed. The subfamilies are defined by phylogenetic analyses of 3CD (precursor of virus-encoded proteinase and polymerase) and P1 (capsid protein precursor) coding sequences and comprise between 7 and 22 currently approved virus genera. Due to the high within-subfamily and between-subfamily divergences of the picornavirus genera, p-distance estimates are unsuited for the demarcation of subfamilies. Members of the proposed subfamilies typically show some commonalities in their genome organisations, including VP1/2A cleavage mechanisms and possession of leader proteins. Other features, such as internal ribosomal entry site types, are more variable within and between members of genera. Some subfamilies are characterised by homology of proteins 1A, 2A, 2B and 3A encoded by members, which do not belong to the canon of orthologous picornavirus proteins. The proposed addition of a subfamily layer to the taxonomy of picornaviruses provides a valuable additional organisational level to the family that acknowledges the existence of higher-level evolutionary groupings of its component genera.

A Roadmap for Genome-Based Phage Taxonomy

Bacteriophage (phage) taxonomy has been in flux since its inception over four decades ago. Genome sequencing has put pressure on the classification system and recent years have seen significant changes to phage taxonomy. Here, we reflect on the state of phage taxonomy and provide a roadmap for the future, including the abolition of the order Caudovirales and the families Myoviridae, Podoviridae, and Siphoviridae. Furthermore, we specify guidelines for the demarcation of species, genus, subfamily and family-level ranks of tailed phage taxonomy.

Translational adaptation of human viruses to the tissues they infect

Viruses need to hijack the translational machinery of the host cell for a productive infection to happen. However, given the dynamic landscape of tRNA pools among tissues, it is unclear whether different viruses infecting different tissues have adapted their codon usage toward their tropism. Here, we collect the coding sequences of 502 human-infecting viruses and determine that tropism explains changes in codon usage. Using the tRNA abundances across 23 human tissues from The Cancer Genome Atlas (TCGA), we build an in silico model of translational efficiency that validates the correspondence of the viral codon usage with the translational machinery of their tropism. For instance, we detect that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is specifically adapted to the upper respiratory tract and alveoli. Furthermore, this correspondence is specifically defined in early viral proteins. The observed tissue-specific translational efficiency could be useful for the development of antiviral therapies and vaccines.

Virus-mimetic systems for cancer diagnosis and therapy

Over past decades, various strategies have been developed to enhance the delivery efficiency of therapeutics and imaging agents to tumor tissues. However, the therapeutic outcome of tumors to date have not been significantly improved, which can be partly attributed to the weak targeting ability, fast elimination, and low stability of conventional delivery systems. Viruses are the most efficient agents for gene transfer, serving as a valuable source of inspiration for designing nanoparticle-based delivery systems. Based on the properties of viruses, including well-defined geometry, precise composition, easy modification, stable construction, and specific infection, researchers attempt to design biocompatible delivery vectors by mimicking virus assembly and using the vector system to selectively concentrate drugs or imaging probes in tumors with mitigated toxicity and improved efficacy. In this review, we introduce common viruses features and provide an overview of various virus-mimetic strategies for cancer therapy and diagnosis. The challenges faced by virus-mimetic systems are also discussed. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Pectobacterium Phage Jarilo Displays Broad Host Range and Represents a Novel Genus of Bacteriophages Within the Family Autographiviridae

Background: Soft rot Pectobacteriaceae includes the genera Pectobacterium and Dickeya, which are important plant pathogens being responsible for diseases in a wide range of plant species, with potatoes as the main group. Both genera cause pre- and postharvest losses of potatoes, resulting in huge economic losses linked with the soft rot diseases. Materials and Methods: Organic waste was used to isolate phages, with Pectobacterium carotovorum subsp. carotovorum DSM 30170 as host. Complete genome sequencing, comparative genomics, and electron microscopy were used to characterize the phage. An adsorption assay was used to estimate adsorption rate. Twenty-three strains from the genera Pectobacterium and Dickeya were used to examine the host range of the phage. Results: Pectobacterium phage Jarilo represents a novel genus of bacteriophages within the family Autographiviridae, order Caudovirales. Jarilo possesses a double-stranded DNA genome of 40557 bp with a G+C% content of 50.08% and 50 predicted open reading frames. Gene synteny and products seem to be partly conserved between Pectobacterium phage Jarilo and Enterobacteria phage T7, but limited nucleotide similarity is found between Jarilo and other phages within the family Autographiviridae. The adsorption rate of phage Jarilo increased continuously for 1 h upon infection. Phage Jarilo was not able to infect any strains of P. carotovorum and Dickeya tested with the exception of the P. carotovorum strain used for isolation. However, phage Jarilo infected 10 of 16 Pectobacterium atrosepticum strains tested. Conclusion: We propose Pectobacterium phage Jarilo as the first member of a new genus of bacteriophages within the family Autographiviridae, order Caudovirales, displaying a broad host range within the genera of Pectobacterium.

A Single-Tube HNB-Based Loop-Mediated Isothermal Amplification for the Robust Detection of the Ostreid herpesvirus 1

The Ostreid herpesvirus 1 species affects shellfish, contributing significantly to high economic losses during production. To counteract the threat related to mortality, there is a need for the development of novel point-of-care testing (POCT) that can be implemented in aquaculture production to prevent disease outbreaks. In this study, a simple, rapid and specific colorimetric loop-mediated isothermal amplification (LAMP) assay has been developed for the detection of Ostreid herpesvirus1 (OsHV-1) and its variants infecting Crassostrea gigas (C. gigas). The LAMP assay has been optimized to use hydroxynaphthol blue (HNB) for visual colorimetric distinction of positive and negative templates. The effect of an additional Tte UvrD helicase enzyme used in the reaction was also evaluated with an improved reaction time of 10 min. Additionally, this study provides a robust workflow for optimization of primers for uncultured viruses using designed target plasmid when DNA availability is limited.

Setting a baseline for global urban virome surveillance in sewage

The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective.

Domain-centric database to uncover structure of minimally characterized viral genomes

Protein domain-based approaches to analyzing sequence data are valuable tools for examining and exploring genomic architecture across genomes of different organisms. Here, we present a complete dataset of domains from the publicly available sequence data of 9,051 reference viral genomes. The data provided contain information such as sequence position and neighboring domains from 30,947 pHMM-identified domains from each reference viral genome. Domains were identified from viral whole-genome sequence using automated profile Hidden Markov Models (pHMM). This study also describes the framework for constructing "domain neighborhoods", as well as the dataset representing it. These data can be used to examine shared and differing domain architectures across viral genomes, to elucidate potential functional properties of genes, and potentially to classify viruses.

Predicting host taxonomic information from viral genomes: A comparison of feature representations

The rise in metagenomics has led to an exponential growth in virus discovery. However, the majority of these new virus sequences have no assigned host. Current machine learning approaches to predicting virus host interactions have a tendency to focus on nucleotide features, ignoring other representations of genomic information. Here we investigate the predictive potential of features generated from four different ‘levels’ of viral genome representation: nucleotide, amino acid, amino acid properties and protein domains. This more fully exploits the biological information present in the virus genomes. Over a hundred and eighty binary datasets for infecting versus non-infecting viruses at all taxonomic ranks of both eukaryote and prokaryote hosts were compiled. The viral genomes were converted into the four different levels of genome representation and twenty feature sets were generated by extracting k-mer compositions and predicted protein domains. We trained and tested Support Vector Machine, SVM, classifiers to compare the predictive capacity of each of these feature sets for each dataset. Our results show that all levels of genome representation are consistently predictive of host taxonomy and that prediction k-mer composition improves with increasing k-mer length for all k-mer based features. Using a phylogenetically aware holdout method, we demonstrate that the predictive feature sets contain signals reflecting both the evolutionary relationship between the viruses infecting related hosts, and host-mimicry. Our results demonstrate that incorporating a range of complementary features, generated purely from virus genome sequences, leads to improved accuracy for a range of virus host prediction tasks enabling computational assignment of host taxonomic information.

Elucidating the host of a newly identified virus species is an important challenge, with applications from knowing the source species of a newly emerged pathogen to understanding the bacteriophage-host relationships within the microbiome of any of earth’s ecosystems. Current high throughput methods used to identify viruses within biological or environmental samples have resulted in an unprecedented increase in virus discovery. However, for the majority of these virus genomes the host species/taxonomic classification remains unknown. To address this gap in our knowledge there is a need for fast, accurate computational methods for the assignment of putative host taxonomic information. Machine learning is an ideal approach but to maximise predictive accuracy the viral genomes need to be represented in a format (sets of features) that makes the discriminative information available to the machine learning algorithm. Here, we compare different types of features derived from the same viral genomes for their ability to predict host information. Our results demonstrate that all these feature sets are predictive of host taxonomy and when combined have the potential to improve accuracy over the use of individual feature sets across many virus host prediction applications.

Taxonomy of prokaryotic viruses: 2018-2019 update from the ICTV Bacterial and Archaeal Viruses Subcommittee

This article is a summary of the activities of the ICTV's Bacterial and Archaeal Viruses Subcommittee for the years 2018 and 2019. Highlights include the creation of a new order, 10 families, 22 subfamilies, 424 genera and 964 species. Some of our concerns about the ICTV's ability to adjust to and incorporate new DNA- and protein-based taxonomic tools are discussed.

Enteric Virome and Carcinogenesis in the Gut

Colorectal cancer (CRC) is a leading cause of cancer-related deaths in both the USA and the world. Recent research has demonstrated the involvement of the gut microbiota in CRC development and progression. Microbial biomarkers of disease have focused primarily on the bacterial component of the microbiome; however, the viral portion of the microbiome, consisting of both bacteriophages and eukaryotic viruses, together known as the virome, has been lesser studied. Here we review the recent advancements in high-throughput sequencing (HTS) technologies and bioinformatics, which have enabled scientists to better understand how viruses might influence the development of colorectal cancer. We discuss the contemporary findings revealing modulations in the virome and their correlation with CRC development and progression. While a variety of challenges still face viral HTS detection in clinical specimens, we consider herein numerous next steps for future basic and clinical research. Clinicians need to move away from a single infectious agent model for disease etiology by grasping new, more encompassing etiological paradigms, in which communities of various microbial components interact with each other and the host. The reporting and indexing of patient health information, socioeconomic data, and other relevant metadata will enable identification of predictive variables and covariates of viral presence and CRC development. Altogether, the virome has a more profound role in carcinogenesis and cancer progression than once thought, and viruses, specific for either human cells or bacteria, are clinically relevant in understanding CRC pathology, patient prognosis, and treatment development.

Analysis of Spounaviruses as a Case Study for the Overdue Reclassification of Tailed Phages

Tailed bacteriophages are the most abundant and diverse viruses in the world, with genome sizes ranging from 10 kbp to over 500 kbp. Yet, due to historical reasons, all this diversity is confined to a single virus order-Caudovirales, composed of just four families: Myoviridae, Siphoviridae, Podoviridae, and the newly created Ackermannviridae family. In recent years, this morphology-based classification scheme has started to crumble under the constant flood of phage sequences, revealing that tailed phages are even more genetically diverse than once thought. This prompted us, the Bacterial and Archaeal Viruses Subcommittee of the International Committee on Taxonomy of Viruses (ICTV), to consider overall reorganization of phage taxonomy. In this study, we used a wide range of complementary methods-including comparative genomics, core genome analysis, and marker gene phylogenetics-to show that the group of Bacillus phage SPO1-related viruses previously classified into the Spounavirinae subfamily, is clearly distinct from other members of the family Myoviridae and its diversity deserves the rank of an autonomous family. Thus, we removed this group from the Myoviridae family and created the family Herelleviridae-a new taxon of the same rank. In the process of the taxon evaluation, we explored the feasibility of different demarcation criteria and critically evaluated the usefulness of our methods for phage classification. The convergence of results, drawing a consistent and comprehensive picture of a new family with associated subfamilies, regardless of method, demonstrates that the tools applied here are particularly useful in phage taxonomy. We are convinced that creation of this novel family is a crucial milestone toward much-needed reclassification in the Caudovirales order.

Trans-Acting RNA-RNA Interactions in Segmented RNA Viruses

RNA viruses represent a large and important group of pathogens that infect a broad range of hosts. Segmented RNA viruses are a subclass of this group that encode their genomes in two or more molecules and package all of their RNA segments in a single virus particle. These divided genomes come in different forms, including double-stranded RNA, coding-sense single-stranded RNA, and noncoding single-stranded RNA. Genera that possess these genome types include, respectively, Orbivirus (e.g., Bluetongue virus), Dianthovirus (e.g., Red clover necrotic mosaic virus) and Alphainfluenzavirus (e.g., Influenza A virus). Despite their distinct genomic features and diverse host ranges (i.e., animals, plants, and humans, respectively) each of these viruses uses trans-acting RNA–RNA interactions (tRRIs) to facilitate co-packaging of their segmented genome. The tRRIs occur between different viral genome segments and direct the selective packaging of a complete genome complement. Here we explore the current state of understanding of tRRI-mediated co-packaging in the abovementioned viruses and examine other known and potential functions for this class of RNA–RNA interaction.

Viral taxonomy derived from evolutionary genome relationships

We describe a new genome alignment-based model for understanding the diversity of viruses based on evolutionary genetic relationships. This approach uses information theory and a physical model to determine the information shared by the genes in two genomes. Pairwise comparisons of genes from the viruses are created from alignments using NCBI BLAST, and their match scores are combined to produce a metric between genomes, which is in turn used to determine a global classification using the 5,817 viruses on RefSeq. In cases where there is no measurable alignment between any genes, the method falls back to a coarser measure of genome relationship: the mutual information of 4-mer frequency. This results in a principled model which depends only on the genome sequence, which captures many interesting relationships between viral families, and which creates clusters which correlate well with both the Baltimore and ICTV classifications. The incremental computational cost of classifying a novel virus is low and therefore newly discovered viruses can be quickly identified and classified. The model goes beyond alignment-free classifications by producing a full phylogeny similar to those constructed by virologists using qualitative features, while relying only on objective genes. These results bolster the case for mathematical models in microbiology which can characterize organisms using only their genetic material and provide an independent check for phylogenies constructed by humans, considerably faster and more cheaply than less modern approaches.

A review of bacteriophage therapy for pathogenic bacteria inactivation in the soil environment

The emerging contamination of pathogenic bacteria in the soil has caused a serious threat to public health and environmental security. Therefore, effective methods to inactivate pathogenic bacteria and decrease the environmental risks are urgently required. As a century-old technique, bacteriophage (phage) therapy has a high efficiency in targeting and inactivating pathogenic bacteria in different environmental systems. This review provides an update on the status of bacteriophage therapy for the inactivation of pathogenic bacteria in the soil environment. Specifically, the applications of phage therapy in soil-plant and soil-groundwater systems are summarized. In addition, the impact of phage therapy on soil functioning is described, including soil function gene transmission, soil microbial community stability, and soil nutrient cycling. Soil factors, such as soil temperature, pH, clay mineral, water content, and nutrient components, influence the survival and activity of phages in the soil. Finally, the future research prospects of phage therapy in soil environments are described.

Identification of the gene signature reflecting schizophrenia's etiology by constructing artificial intelligence-based method of enhanced reproducibility

Aims

As one of the most fundamental questions in modern science, “what causes schizophrenia (SZ)” remains a profound mystery due to the absence of objective gene markers. The reproducibility of the gene signatures identified by independent studies is found to be extremely low due to the incapability of available feature selection methods and the lack of measurement on validating signatures’ robustness. These irreproducible results have significantly limited our understanding of the etiology of SZ.

Methods

In this study, a new feature selection strategy was developed, and a comprehensive analysis was then conducted to ensure a reliable signature discovery. Particularly, the new strategy (a) combined multiple randomized sampling with consensus scoring and (b) assessed gene ranking consistency among different datasets, and a comprehensive analysis among nine independent studies was conducted.

Results

Based on a first‐ever evaluation of methods’ reproducibility that was cross‐validated by nine independent studies, the newly developed strategy was found to be superior to the traditional ones. As a result, 33 genes were consistently identified from multiple datasets by the new strategy as differentially expressed, which might facilitate our understanding of the mechanism underlying the etiology of SZ.

Conclusion

A new strategy capable of enhancing the reproducibility of feature selection in current SZ research was successfully constructed and validated. A group of candidate genes identified in this study should be considered as great potential for revealing the etiology of SZ.

Exploiting the Legacy of the Arbovirus Hunters

In recent years, it has become evident that a generational gap has developed in the community of arbovirus research. This apparent gap is due to the dis-investment of training for the next generation of arbovirologists, which threatens to derail the rich history of virus discovery, field epidemiology, and understanding of the richness of diversity that surrounds us. On the other hand, new technologies have resulted in an explosion of virus discovery that is constantly redefining the virosphere and the evolutionary relationships between viruses. This paradox presents new challenges that may have immediate and disastrous consequences for public health when yet to be discovered arboviruses emerge. In this review we endeavor to bridge this gap by providing a historical context for the work being conducted today and provide continuity between the generations. To this end, we will provide a narrative of the thrill of scientific discovery and excitement and the challenges lying ahead.