Overview of Virus Metagenomic Classification Methods and Their Biological Applications

Highly divergent and diverse viral community infecting sylvatic mosquitoes from Northeast Brazil

Mosquitoes can transmit several pathogenic viruses to humans, but their natural viral community is also composed of a myriad of other viruses such as insect-specific viruses (ISVs) and those that infect symbiotic microorganisms. Besides a growing number of studies investigating the mosquito virome, the majority are focused on few urban species, and relatively little is known about the virome of sylvatic mosquitoes, particularly in high biodiverse biomes such as the Brazilian biomes. Here, we characterized the RNA virome of 10 sylvatic mosquito species from Atlantic forest remains at a sylvatic-urban interface in Northeast Brazil employing a metatranscriptomic approach. A total of 16 viral families were detected. The phylogenetic reconstructions of 14 viral families revealed that the majority of the sequences are putative ISVs. The phylogenetic positioning and, in most cases, the association with a high RNA-dependent RNA polymerase amino acid divergence from other known viruses suggests that the viruses characterized here represent at least 34 new viral species. Therefore, the sylvatic mosquito viral community is predominantly composed of highly divergent viruses highlighting the limited knowledge we still have about the natural virome of mosquitoes in general. Moreover, we found that none of the viruses recovered were shared between the species investigated, and only one showed high identity to a virus detected in a mosquito sampled in Peru, South America. These findings add further in-depth understanding about the interactions and coevolution between mosquitoes and viruses in natural environments.

IMPORTANCE

Mosquitoes are medically important insects as they transmit pathogenic viruses to humans and animals during blood feeding. However, their natural microbiota is also composed of a diverse set of viruses that cause no harm to the insect and other hosts, such as insect-specific viruses. In this study, we characterized the RNA virome of sylvatic mosquitoes from Northeast Brazil using unbiased metatranscriptomic sequencing and in-depth bioinformatic approaches. Our analysis revealed that these mosquitoes species harbor a diverse set of highly divergent viruses, and the majority comprises new viral species. Our findings revealed many new virus lineages characterized for the first time broadening our understanding about the natural interaction between mosquitoes and viruses. Finally, it also provided several complete genomes that warrant further assessment for mosquito and vertebrate host pathogenicity and their potential interference with pathogenic arboviruses.

The effects of sequencing strategies on Metagenomic pathogen detection using bronchoalveolar lavage fluid samples

Objectives

Metagenomic next-generation sequencing (mNGS) is a powerful tool for pathogen detection. The accuracy depends on both wet lab and dry lab procedures. The objective of our study was to assess the influence of read length and dataset size on pathogen detection.

Methods

In this study, 43 clinical BALF samples, which tested positive via clinical mNGS and were consistent with the diagnosis, were subjected to re-sequencing on the Illumina NovaSeq 6000 platform. The raw re-sequencing data, consisting of 100 million (M) paired-end 150 bp (PE150) reads, were divided into simulated datasets with eight different data sizes (5 M, 10 M, 15 M, 20 M, 30 M, 50 M, 75 M, 100 M) and five different read lengths (single-end 50 bp (SE50), SE75, SE100, PE100, and PE150). Both Kraken2 and IDseq bioinformatics pipelines were employed to analyze the previously diagnosed pathogens in the simulated data. Detection of pathogens was based on read counts ranging from 1 to 10 and RPM values ranging from 0.2 to 2.

Results

Our results revealed that increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection. However, a larger data sizes for mNGS require higher economic costs and longer turnaround time for data analysis. Our findings indicate 20 M reads being sufficient for SE75 mode to achieve high recall rates. Additionally, high nucleic acid loads in samples can lead to increased stability in pathogen detection efficiency, reducing the impact of sequencing strategies. The choice of bioinformatics pipelines had a significant impact on recall rates achieved in pathogen detection.

Conclusions

Increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection but increase the economic and time costs of sequencing and data analysis. Currently, the 20 M reads in SE75 mode may be the best sequencing option.

Deepvirusclassifier: a deep learning tool for classifying SARS-CoV-2 based on viral subtypes within the coronaviridae family

PURPOSE

In this study, we present DeepVirusClassifier, a tool capable of accurately classifying Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) viral sequences among other subtypes of the coronaviridae family. This classification is achieved through a deep neural network model that relies on convolutional neural networks (CNNs). Since viruses within the same family share similar genetic and structural characteristics, the classification process becomes more challenging, necessitating more robust models. With the rapid evolution of viral genomes and the increasing need for timely classification, we aimed to provide a robust and efficient tool that could increase the accuracy of viral identification and classification processes. Contribute to advancing research in viral genomics and assist in surveilling emerging viral strains.

METHODS

Based on a one-dimensional deep CNN, the proposed tool is capable of training and testing on the Coronaviridae family, including SARS-CoV-2. Our model's performance was assessed using various metrics, including F1-score and AUROC. Additionally, artificial mutation tests were conducted to evaluate the model's generalization ability across sequence variations. We also used the BLAST algorithm and conducted comprehensive processing time analyses for comparison.

RESULTS

DeepVirusClassifier demonstrated exceptional performance across several evaluation metrics in the training and testing phases. Indicating its robust learning capacity. Notably, during testing on more than 10,000 viral sequences, the model exhibited a more than 99% sensitivity for sequences with fewer than 2000 mutations. The tool achieves superior accuracy and significantly reduced processing times compared to the Basic Local Alignment Search Tool algorithm. Furthermore, the results appear more reliable than the work discussed in the text, indicating that the tool has great potential to revolutionize viral genomic research.

CONCLUSION

DeepVirusClassifier is a powerful tool for accurately classifying viral sequences, specifically focusing on SARS-CoV-2 and other subtypes within the Coronaviridae family. The superiority of our model becomes evident through rigorous evaluation and comparison with existing methods. Introducing artificial mutations into the sequences demonstrates the tool's ability to identify variations and significantly contributes to viral classification and genomic research. As viral surveillance becomes increasingly critical, our model holds promise in aiding rapid and accurate identification of emerging viral strains.

Metabuli: sensitive and specific metagenomic classification via joint analysis of amino acid and DNA

Metagenomic taxonomic classifiers analyze either DNA or amino acid (AA) sequences. Metabuli ( https://metabuli.steineggerlab.com ), however, jointly analyzes both DNA and AA to leverage AA conservation for sensitive homology detection and DNA mutations for specific differentiation of closely related taxa. In the Critical Assessment of Metagenome Interpretation 2 plant-associated dataset, Metabuli covered 99% and 98% of classifications of state-of-the-art DNA- and AA-based classifiers, respectively.

Application and Comparison of Machine Learning and Database-Based Methods in Taxonomic Classification of High-Throughput Sequencing Data

The advent of high-throughput sequencing technologies has not only revolutionized the field of bioinformatics but has also heightened the demand for efficient taxonomic classification. Despite technological advancements, efficiently processing and analyzing the deluge of sequencing data for precise taxonomic classification remains a formidable challenge. Existing classification approaches primarily fall into two categories, database-based methods and machine learning methods, each presenting its own set of challenges and advantages. On this basis, the aim of our study was to conduct a comparative analysis between these two methods while also investigating the merits of integrating multiple database-based methods. Through an in-depth comparative study, we evaluated the performance of both methodological categories in taxonomic classification by utilizing simulated data sets. Our analysis revealed that database-based methods excel in classification accuracy when backed by a rich and comprehensive reference database. Conversely, while machine learning methods show superior performance in scenarios where reference sequences are sparse or lacking, they generally show inferior performance compared with database methods under most conditions. Moreover, our study confirms that integrating multiple database-based methods does, in fact, enhance classification accuracy. These findings shed new light on the taxonomic classification of high-throughput sequencing data and bear substantial implications for the future development of computational biology. For those interested in further exploring our methods, the source code of this study is publicly available on https://github.com/LoadStar822/Genome-Classifier-Performance-Evaluator. Additionally, a dedicated webpage showcasing our collected database, data sets, and various classification software can be found at http://lab.malab.cn/~tqz/project/taxonomic/.

Genome analysis of a novel avian atadenovirus reveals a possible horizontal gene transfer

We report the discovery and characterization of a novel adenovirus, Zoothera dauma adenovirus (ZdAdV), from a wild bird species, Zoothera dauma (Scaly thrush). This new atadenovirus was discovered by metagenomic sequencing without virus cultivation. Analyses of the full genome sequence revealed that this new virus is a distinct member of the genus Atadenovirus and represents a novel species. ZdAdV has a genome of 34,760 bp with 28 predicted genes and 39% GC content. ZdAdV is the first atadenovirus to contain ORF19, a gene previously found only in aviadenoviruses. Phylogenetic analysis of ORF19 suggests that it was acquired by ZdAdV through horizontal gene transfer from an aviadenovirus. By analyzing all orthologous genes of aviadenovirus, mastadenovirus, atadenovirus, and siadenovirus, we also found potential horizontal gene transfer for the E4 gene in Pigeon aviadenovirus B. Our study widens our knowledge concerning the genetic diversity and evolutionary history of atadenoviruses and their potential for cross-species transmission.

INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance

BACKGROUND

Implementation of clinical metagenomics and pathogen genomic surveillance can be particularly challenging due to the lack of bioinformatics tools and/or expertise. In order to face this challenge, we have previously developed INSaFLU, a free web-based bioinformatics platform for virus next-generation sequencing data analysis. Here, we considerably expanded its genomic surveillance component and developed a new module (TELEVIR) for metagenomic virus identification.

RESULTS

The routine genomic surveillance component was strengthened with new workflows and functionalities, including (i) a reference-based genome assembly pipeline for Oxford Nanopore technologies (ONT) data; (ii) automated SARS-CoV-2 lineage classification; (iii) Nextclade analysis; (iv) Nextstrain phylogeographic and temporal analysis (SARS-CoV-2, human and avian influenza, monkeypox, respiratory syncytial virus (RSV A/B), as well as a "generic" build for other viruses); and (v) algn2pheno for screening mutations of interest. Both INSaFLU pipelines for reference-based consensus generation (Illumina and ONT) were benchmarked against commonly used command line bioinformatics workflows for SARS-CoV-2, and an INSaFLU snakemake version was released. In parallel, a new module (TELEVIR) for virus detection was developed, after extensive benchmarking of state-of-the-art metagenomics software and following up-to-date recommendations and practices in the field. TELEVIR allows running complex workflows, covering several combinations of steps (e.g., with/without viral enrichment or host depletion), classification software (e.g., Kaiju, Kraken2, Centrifuge, FastViromeExplorer), and databases (RefSeq viral genome, Virosaurus, etc.), while culminating in user- and diagnosis-oriented reports. Finally, to potentiate real-time virus detection during ONT runs, we developed findONTime, a tool aimed at reducing costs and the time between sample reception and diagnosis.

CONCLUSIONS

The accessibility, versatility, and functionality of INSaFLU-TELEVIR are expected to supply public and animal health laboratories and researchers with a user-oriented and pan-viral bioinformatics framework that promotes a strengthened and timely viral metagenomic detection and routine genomics surveillance. INSaFLU-TELEVIR is compatible with Illumina, Ion Torrent, and ONT data and is freely available at https://insaflu.insa.pt/ (online tool) and https://github.com/INSaFLU (code).

Benchmarking bioinformatic virus identification tools using real-world metagenomic data across biomes

BACKGROUND

As most viruses remain uncultivated, metagenomics is currently the main method for virus discovery. Detecting viruses in metagenomic data is not trivial. In the past few years, many bioinformatic virus identification tools have been developed for this task, making it challenging to choose the right tools, parameters, and cutoffs. As all these tools measure different biological signals, and use different algorithms and training and reference databases, it is imperative to conduct an independent benchmarking to give users objective guidance.

RESULTS

We compare the performance of nine state-of-the-art virus identification tools in thirteen modes on eight paired viral and microbial datasets from three distinct biomes, including a new complex dataset from Antarctic coastal waters. The tools have highly variable true positive rates (0-97%) and false positive rates (0-30%). PPR-Meta best distinguishes viral from microbial contigs, followed by DeepVirFinder, VirSorter2, and VIBRANT. Different tools identify different subsets of the benchmarking data and all tools, except for Sourmash, find unique viral contigs. Performance of tools improved with adjusted parameter cutoffs, indicating that adjustment of parameter cutoffs before usage should be considered.

CONCLUSIONS

Together, our independent benchmarking facilitates selecting choices of bioinformatic virus identification tools and gives suggestions for parameter adjustments to viromics researchers.

High prevalence of Enterovirus E, Bovine Kobuvirus, and Astrovirus revealed by viral metagenomics in fecal samples from cattle in Central Colombia

Livestock plays a crucial role in ensuring food security and driving the global economy. However, viral infections can have far-reaching consequences beyond economic productivity, affecting the health of cattle, as well as posing risks to human health and other animals. Identifying viruses present in fecal samples, a primary route of pathogen transmission, is essential for developing effective prevention, control, and surveillance strategies. Viral metagenomic approaches offer a broader perspective and hold great potential for detecting previously unknown viruses or uncovering previously undescribed agents. Ubaté Province is Colombia's dairy capital and a key center for livestock production in the country. Therefore, the purpose of this study was to characterize viral communities in fecal samples from cattle in this region. A total of 42 samples were collected from three municipalities in Ubaté Province, located in central Colombia, using a convenient non-probabilistic sampling method. We utilized metagenomic sequencing with Oxford Nanopore Technologies (ONT), combined with diversity and phylogenetic analysis. The findings revealed a consistent and stable viral composition across the municipalities, primarily comprising members of the Picornaviridae family. At the species level, the most frequent viruses were Enterovirus E (EVE) and Bovine Astrovirus (BoAstV). Significantly, this study reported, for the first time in Colombia, the presence of viruses with veterinary importance occurring at notable frequencies: EVE (59%), Bovine Kobuvirus (BKV) (52%), and BoAstV (19%). Additionally, the study confirmed the existence of Circular replicase-encoding single-stranded (CRESS) Virus in animal feces. These sequences were phylogenetically grouped with samples obtained from Asia and Latin America, underscoring the importance of having adequate representation across the continent. The virome of bovine feces in Ubaté Province is characterized by the predominance of potentially pathogenic viruses such as BoAstV and EVE that have been reported with substantial frequency and quantities. Several of these viruses were identified in Colombia for the first time. This study showcases the utility of using metagenomic sequencing techniques in epidemiological surveillance. It also paves the way for further research on the influence of these agents on bovine health and their frecuency across the country.

Genomic Analysis and Taxonomic Characterization of Seven Bacteriophage Genomes Metagenomic-Assembled from the Dishui Lake

Viruses in aquatic ecosystems exhibit remarkable abundance and diversity. However, scattered studies have been conducted to mine uncultured viruses and identify them taxonomically in lake water. Here, whole genomes (29-173 kbp) of seven uncultured dsDNA bacteriophages were discovered in Dishui Lake, the largest artificial lake in Shanghai. We analyzed their genomic signatures and found a series of viral auxiliary metabolic genes closely associated with protein synthesis and host metabolism. Dishui Lake phages shared more genes with uncultivated environmental viruses than with reference viruses based on the gene-sharing network classification. Phylogeny of proteomes and comparative genomics delineated three new genera within two known viral families of Kyanoviridae and Autographiviridae, and four new families in Caudoviricetes for these seven novel phages. Their potential hosts appeared to be from the dominant bacterial phyla in Dishui Lake. Altogether, our study provides initial insights into the composition and diversity of bacteriophage communities in Dishui Lake, contributing valuable knowledge to the ongoing research on the roles played by viruses in freshwater ecosystems.

Viral Diversity and Epidemiology in Critically Endangered Yangtze Finless Porpoises (Neophocaena asiaeorientalis asiaeorientalis)

The Yangtze finless porpoise (YFP) (Neophocaena asiaeorientalis asiaeorientalis) is a critically endangered freshwater cetacean, with about 1,249 individuals thought to be left in the wild. However, viral entities and viral diseases of YFPs remain obscure. In this study, anal swabs for virome analysis were collected during the physical examination of YFPs in the Tian-E-Zhou Oxbow (TEO) ex situ reserve. A total of 19 eukaryotic viral species belonging to 9 families, including Papillomaviridae, Herpesviridae, Picornaviridae, Picobirnaviridae, Caliciviridae, Retroviridae, Parvoviridae, Virgaviridae, and Narnaviridae, and other unclassified viruses were identified based on metasequencing. Among these detected viruses, a novel herpesvirus (NaHV), two different kobuviruses (NaKV1-2), and six different papillomaviruses (NaPV1 to -6) were considered potential risks to YFPs and confirmed by PCR or reverse transcription-PCR (RT-PCR). Most YFPs sampled were found to harbor one or more kinds of detected viral genomes (52/58 [89.7%]). Surveillance results demonstrated that kobuvirus and herpesvirus displayed obvious age distribution and PVs showed significant gender difference in YFPs. According to species demarcation criteria in individual genera in Papillomaviridae, two novel species (referred to as Omikronpapillomavirus 2 and 3) and four novel isolates of PV were identified in YFPs. Further evolutionary analysis suggested that NaPVs would occupy the mucosal niche and that virus-host codivergence mixed with duplications and host-switching events drives the evolution of cetacean PVs. Divergence times of PVs in YFP and other cetacean reflect the incipient speciation of YFPs. In summary, our findings revealed the potential viral entities, their prevalence, and their evolutionary history in YFPs, which raises an important issue regarding effects of viral infection on the fitness of YFPs. IMPORTANCE The Yangtze finless porpoise (YFP) is the only cetacean species in freshwater following the functional extinction of the baiji (Lipotes vexillifer). Health management, disease treatment, and other special measures are important for maintaining the existing YFP populations, especially in in situ and ex situ reserves. The discovery of potential viral entities and their prevalence in YFPs raises an important issue regarding the effects of viral infection on the fitness of YFPs and may contribute to the conservation of YFPs. The evolutionary history of papillomaviruses in YFP and other cetaceans reflects the phylogeny of their hosts and supports the status of incipient species, opening a window to investigate the evolutionary adaptation of cetaceans to freshwater as well as their phylogeny to remedy the deficiency of fossil evidence.

Searching for a Reliable Viral Indicator of Faecal Pollution in Aquatic Environments

The disposal of sewage in significant quantities poses a health hazard to aquatic ecosystems. These effluents can contain a wide range of pathogens, making faecal contamination a leading source of waterborne diseases around the world. Yet monitoring bacteria or viruses in aquatic environments is time consuming and expensive. The standard indicators of faecal pollution all have limitations, including difficulty in determining the source due to lack of host specificity, poor connection with the presence of non-bacterial pathogens, or low environmental persistence. Innovative monitoring techniques are sorely needed to provide more accurate and targeted solutions. Viruses are a promising alternative to faecal indicator bacteria for monitoring, as they are more persistent in ambient water, more abundant in faeces, and are extremely host-specific. Given the range of viruses found in diverse contexts, it is not easy to find one "ideal" viral indicator of faecal pollution; however, several are of interest. In parallel, the ongoing development of molecular techniques coupled with metagenomics and bioinformatics should enable improved ways to detect faecal contamination using viruses. This review examines the evolution of faecal contamination monitoring with the following aims (i) to identify the characteristics of the main viral indicators of faecal contamination, including human enteric viruses, bacteriophages, CRESS and plant viruses, (ii) to assess how these have been used to monitor water pollution in recent years, (iii) to evaluate the reliability of recent detection methods of such viruses, and (iv) to tentatively determine which viruses may be most effective as markers of faecal pollution.

Bioinformatic Tools for NGS-Based Metagenomics to Improve the Clinical Diagnosis of Emerging, Re-Emerging and New Viruses

Epidemics and pandemics have occurred since the beginning of time, resulting in millions of deaths. Many such disease outbreaks are caused by viruses. Some viruses, particularly RNA viruses, are characterized by their high genetic variability, and this can affect certain phenotypic features: tropism, antigenicity, and susceptibility to antiviral drugs, vaccines, and the host immune response. The best strategy to face the emergence of new infectious genomes is prompt identification. However, currently available diagnostic tests are often limited for detecting new agents. High-throughput next-generation sequencing technologies based on metagenomics may be the solution to detect new infectious genomes and properly diagnose certain diseases. Metagenomic techniques enable the identification and characterization of disease-causing agents, but they require a large amount of genetic material and involve complex bioinformatic analyses. A wide variety of analytical tools can be used in the quality control and pre-processing of metagenomic data, filtering of untargeted sequences, assembly and quality control of reads, and taxonomic profiling of sequences to identify new viruses and ones that have been sequenced and uploaded to dedicated databases. Although there have been huge advances in the field of metagenomics, there is still a lack of consensus about which of the various approaches should be used for specific data analysis tasks. In this review, we provide some background on the study of viral infections, describe the contribution of metagenomics to this field, and place special emphasis on the bioinformatic tools (with their capabilities and limitations) available for use in metagenomic analyses of viral pathogens.

Evaluation of tools for taxonomic classification of viruses

Viruses are the most abundant infectious agents on earth, and they infect living organisms such as bacteria, plants and animals, among others. They play an important role in the balance of different ecosystems by modulating microbial populations. In humans, they are responsible for some common diseases and may cause severe illnesses. Viral metagenomic studies have become essential and offer the possibility to understand and extend the knowledge of virus diversity and functionality. For these approaches, an essential step is the classification of viral sequences. In this work, 11 taxonomic classification tools were compared by analysing their performances, in terms of sensitivity and precision, to classify reads at the species and family levels using the same (viral and nonviral) datasets and evaluation metrics, as well as their processing times and memory requirements. The results showed that factors such as richness (numbers of viral species in samples), taxonomic level in the classification and read length influence tool performance. High values of viral richness in samples decreased the performances of most tools. Additionally, the classifications were better at higher taxonomic levels, such as families, compared to lower taxonomic levels, such as species, and were more evident in short reads. The results also indicated that BLAST and Kraken2 were the best tools for classifying all types of reads, while FastViromeExplorer and VirusFinder were only good when used for long reads and Centrifuge, DIAMOND, and One Codex when used for short reads. Regarding nonviral datasets (human and bacterial), all tools correctly classified them as nonviral.

Novel Virus Identification through Metagenomics: A Systematic Review

Metagenomic Next Generation Sequencing (mNGS) allows the evaluation of complex microbial communities, avoiding isolation and cultivation of each microbial species, and does not require prior knowledge of the microbial sequences present in the sample. Applications of mNGS include virome characterization, new virus discovery and full-length viral genome reconstruction, either from virus preparations enriched in culture or directly from clinical and environmental specimens. Here, we systematically reviewed studies that describe novel virus identification through mNGS from samples of different origin (plant, animal and environment). Without imposing time limits to the search, 379 publications were identified that met the search parameters. Sample types, geographical origin, enrichment and nucleic acid extraction methods, sequencing platforms, bioinformatic analytical steps and identified viral families were described. The review highlights mNGS as a feasible method for novel virus discovery from samples of different origins, describes which kind of heterogeneous experimental and analytical protocols are currently used and provides useful information such as the different commercial kits used for the purification of nucleic acids and bioinformatics analytical pipelines.

Next Generation Sequencing Approaches to Characterize the Respiratory Tract Virome

The COVID-19 pandemic and heightened perception of the risk of emerging viral infections have boosted the efforts to better understand the virome or complete repertoire of viruses in health and disease, with a focus on infectious respiratory diseases. Next-generation sequencing (NGS) is widely used to study microorganisms, allowing the elucidation of bacteria and viruses inhabiting different body systems and identifying new pathogens. However, NGS studies suffer from a lack of standardization, in particular, due to various methodological approaches and no single format for processing the results. Here, we review the main methodological approaches and key stages for studies of the human virome, with an emphasis on virome changes during acute respiratory viral infection, with applications for clinical diagnostics and epidemiologic analyses.

Viral metagenomics combined with metabolomics reveals the role of gut viruses in mouse model of depression

Depression is a heterogeneous mental disorder that has been linked to disturbances in the gut microbiome. As an essential part of the gut microbiome, gut virome may play critical roles in disease progression and development. However, the relationship between the effect of gut virome on neurotransmitter metabolism and depression is unknown. We evaluated the alterations of gut virome and neurotransmitters in chronic restraint stress (CRS)-induced mouse model of depression based on viral metagenomics and LC-MS/MS metabolomics analyses. The results reveal that the gut virome profile of CRS group differed significantly from CON group. Microviridae was the most abundant differential viral family in both groups, followed by Podoviridae, while Siphoviridae was only enriched in CRS group of the top 100 differential viruses. The differential viruses that predicted to Enterobacteriaceae phage, Gammaproteobacteria phage and Campylobacteraceae phage were enriched in CRS group. Furthermore, 12 differential neurotransmitters primarily involved in the tryptophan metabolism pathway were altered in depressive-like mice. Besides, tryptamine and 5-methoxytryptamine hydrochloride were strongly associated with differential viruses belonging to Podoviridae and Microviridae. Our findings provide new insight into understanding the potential role of the gut virome and metabolites in depression.

Viral Metagenomics for Identification of Emerging Viruses in Transfusion Medicine

Viral metagenomics has revolutionized our understanding for identification of unknown or poorly characterized viruses. For that reason, metagenomic studies gave been largely applied for virus discovery in a wide variety of clinical samples, including blood specimens. The emerging blood-transmitted virus infections represent important problem for public health, and the emergence of HIV in the 1980s is an example for the vulnerability of Blood Donation systems to such infections. When viral metagenomics is applied to blood samples, it can give a complete overview of the viral nucleic acid abundance, also named "blood virome". Detailed characterization of the blood virome of healthy donors could identify unknown (emerging) viral genomes that might be assumed as hypothetic transfusion threats. However, it is impossible only by application of viral metagenomics to assign that one viral agent could impact blood transfusion. That said, this is a complex issue and will depend on the ability of the infectious agent to cause clinically important infection in blood recipients, the viral stability in blood derivatives and the presence of infectious viruses in blood, making possible its transmission by transfusion. This brief review summarizes information regarding the blood donor virome and some important challenges for use of viral metagenomics in hemotherapy for identification of transfusion-transmitted viruses.

MetaPhage: an Automated Pipeline for Analyzing, Annotating, and Classifying Bacteriophages in Metagenomics Sequencing Data

Phages are the most abundant biological entities on the planet, and they play an important role in controlling density, diversity, and network interactions among bacterial communities through predation and gene transfer. To date, a variety of bacteriophage identification tools have been developed that differ in the phage mining strategies used, input files requested, and results produced. However, new users attempting bacteriophage analysis can struggle to select the best methods and interpret the variety of results produced. Here, we present MetaPhage, a comprehensive reads-to-report pipeline that streamlines the use of multiple phage miners and generates an exhaustive report. The report both summarizes and visualizes the key findings and enables further exploration of key results via interactive filterable tables. The pipeline is implemented in Nextflow, a widely adopted workflow manager that enables an optimized parallelization of tasks in different locations, from local server to the cloud; this ensures reproducible results from containerized packages. MetaPhage is designed to enable scalability and reproducibility; also, it can be easily expanded to include new miners and methods as they are developed in this continuously growing field. MetaPhage is freely available under a GPL-3.0 license at https://github.com/MattiaPandolfoVR/MetaPhage. IMPORTANCE Bacteriophages (viruses that infect bacteria) are the most abundant biological entities on earth and are increasingly studied as members of the resident microbiota community in many environments, from oceans to soils and the human gut. Their identification is of great importance to better understand complex bacterial dynamics and microbial ecosystem function. A variety of metagenome bacteriophage identification tools have been developed that differ in the phage mining strategies used, input files requested, and results produced. To facilitate the management and the execution of such a complex workflow, we developed MetaPhage (MP), a comprehensive reads-to-report pipeline that streamlines the use of multiple phage miners and generates an exhaustive report. The pipeline is implemented in Nextflow, a widely adopted workflow manager that enables an optimized parallelization of tasks. MetaPhage is designed to enable scalability and reproducibility and offers an installation-free, dependency-free, and conflict-free workflow execution.

Metatranscriptomics Reveals the Diversity of the Tick Virome in Northwest China

Blood-sucking ticks are obligate parasites and vectors of a variety of human and animal viruses. Some tick-borne viruses have been identified as pathogens of infectious diseases in humans or animals, potentially imposing significant public health burdens and threats to the husbandry industry. Therefore, identifying the profiles of tick-borne viruses will provide valuable information about the evolution and pathogen ecology of tick-borne viruses. In this study, we investigated the viromes of parasitic ticks collected from the body surfaces of herbivores in Xinjiang Uyghur Autonomous Region and Inner Mongolia Autonomous Region of China, two regions in northwest China. By using a metatranscriptomic approach, 17 RNA viruses with high diversity in genomic organization and evolution were identified. Among them, nine are proposed to be novel species. The classified viruses belonged to six viral families, including Phenuiviridae, Rhabdoviridae, Peribunyaviridae, Lispiviridae, Chuviridae, and Reoviridae, and unclassified viruses were also identified. In addition, although some viruses from different sampling locations shared significant similarities, the abundance and diversity of viruses notably varied among the different collection locations. This study demonstrates the diversity of tick-borne viruses in Xinjiang and Inner Mongolia and provides informative data for further study of the evolution and pathogenicity of these RNA viruses. IMPORTANCE Ticks are widely distributed in pastoral areas in northwestern China and act as vectors that carry and transmit a variety of pathogens, especially viruses. Our study revealed the diversity of tick viruses in Xinjiang and Inner Mongolia and uncovered the phylogenetic relationships of some RNA viruses, especially the important zoonotic tick-borne severe fever with thrombocytopenia syndrome virus in Inner Mongolia. These data suggest a complex and diverse evolutionary history and potential ecological factors associated with pathogenic viruses. The pathogenicity of these tick-borne viruses currently remains unclear. Therefore, future research should focus on evaluating the transmissability and pathogenicity of these tick-borne viruses.

Development and Validation of a Bioinformatic Workflow for the Rapid Detection of Viruses in Biosecurity

The field of biosecurity has greatly benefited from the widespread adoption of high-throughput sequencing technologies, for its ability to deeply query plant and animal samples for pathogens for which no tests exist. However, the bioinformatics analysis tools designed for rapid analysis of these sequencing datasets are not developed with this application in mind, limiting the ability of diagnosticians to standardise their workflows using published tool kits. We sought to assess previously published bioinformatic tools for their ability to identify plant- and animal-infecting viruses while distinguishing from the host genetic material. We discovered that many of the current generation of virus-detection pipelines are not adequate for this task, being outperformed by more generic classification tools. We created synthetic MinION and HiSeq libraries simulating plant and animal infections of economically important viruses and assessed a series of tools for their suitability for rapid and accurate detection of infection, and further tested the top performing tools against the VIROMOCK Challenge dataset to ensure that our findings were reproducible when compared with international standards. Our work demonstrated that several methods provide sensitive and specific detection of agriculturally important viruses in a timely manner and provides a key piece of ground truthing for method development in this space.

A metagenomic insight into the Yangtze finless porpoise virome

The Yangtze finless porpoise (Neophocaena phocaenoides asiaeorientalis) inhabiting the Yantze River, China is critically endangered because of the influences of infectious disease, human activity, and water contamination. Viral diseases are one of the crucial factors that threatening the health of Yangtze finless porpoise. However, there are few studies which elaborate the viral diversity of Yangtze finless. Therefore, this study was performed to investigate the viral diversity of Yangtze finless by metagenomics. Results indicated that a total of 12,686,252 high-quality valid sequences were acquired and 2,172 virus reads were recognized. Additionally, we also obtained a total of 10,600 contigs. Phages was the most abundant virus in the samples and the ratio of DNA and RNA viruses were 69.75 and 30.25%, respectively. Arenaviridae, Ackermannviridae and Siphoviridae were the three most predominant families in all the samples. Moreover, the majority of viral genus were Mammarenavirus, Limestonevirus and Lambdavirus. The results of gene prediction indicated that these viruses play vital roles in biological process, cellular component, molecular function, and disease. To the best of our knowledge, this is the first report on the viral diversity of Yangtze finless porpoise, which filled the gaps in its viral information. Meanwhile, this study can also provide a theoretical basis for the establishment of the prevention and protection system for virus disease of Yangtze finless porpoise.

A comparative study of flow cytometry-sorted communities and shotgun viral metagenomics in a Singapore municipal wastewater treatment plant

Traditional or "bulk" viral enrichment and amplification methods used in viral metagenomics introduce unavoidable bias in viral diversity. This bias is due to shortcomings in existing viral enrichment methods and overshadowing by the more abundant viral populations. To reduce the complexity and improve the resolution of viral diversity, we developed a strategy coupling fluorescence-activated cell sorting (FACS) with random amplification and compared this to bulk metagenomics. This strategy was validated on both influent and effluent samples from a municipal wastewater treatment plant using the Modified Ludzack-Ettinger (MLE) process as the treatment method. We found that DNA and RNA communities generated using bulk samples were mostly different from those derived following FACS for both treatments before and after MLE. Before MLE treatment, FACS identified five viral families and 512 viral annotated contigs. Up to 43% of mapped reads were not detected in bulk samples. Nucleo-cytoplasmic large DNA viral families were enriched to a greater extent in the FACS-coupled subpopulations compared with bulk samples. FACS-coupled viromes captured a single-contig viral genome associated with Anabaena phage, which was not observed in bulk samples or in FACS-sorted samples after MLE. These short metagenomic reads, which were assembled into a high-quality draft genome of 46 kbp, were found to be highly dominant in one of the pre-MLE FACS annotated virome fractions (57.4%). Using bulk metagenomics, we identified that between Primary Settling Tank and Secondary Settling Tank viromes, Virgaviridae, Astroviridae, Parvoviridae, Picobirnaviridae, Nodaviridae, and Iridoviridae were susceptible to MLE treatment. In all, bulk and FACS-coupled metagenomics are complementary approaches that enable a more thorough understanding of the community structure of DNA and RNA viruses in complex environmental samples, of which the latter is critical for increasing the sensitivity of detection of viral signatures that would otherwise be lost through bulk viral metagenomics.

Ecosystem-specific microbiota and microbiome databases in the era of big data

The rapid development of sequencing methods over the past decades has accelerated both the potential scope and depth of microbiota and microbiome studies. Recent developments in the field have been marked by an expansion away from purely categorical studies towards a greater investigation of community functionality. As in-depth genomic and environmental coverage is often distributed unequally across major taxa and ecosystems, it can be difficult to identify or substantiate relationships within microbial communities. Generic databases containing datasets from diverse ecosystems have opened a new era of data accessibility despite costs in terms of data quality and heterogeneity. This challenge is readily embodied in the integration of meta-omics data alongside habitat-specific standards which help contextualise datasets both in terms of sample processing and background within the ecosystem. A special case of large genomic repositories, ecosystem-specific databases (ES-DB's), have emerged to consolidate and better standardise sample processing and analysis protocols around individual ecosystems under study, allowing independent studies to produce comparable datasets. Here, we provide a comprehensive review of this emerging tool for microbial community analysis in relation to current trends in the field. We focus on the factors leading to the formation of ES-DB's, their comparison to traditional microbial databases, the potential for ES-DB integration with meta-omics platforms, as well as inherent limitations in the applicability of ES-DB's.

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.

PIMGAVir and Vir-MinION: Two Viral Metagenomic Pipelines for Complete Baseline Analysis of 2nd and 3rd Generation Data

The taxonomic classification of viral sequences is frequently used for the rapid identification of pathogens, which is a key point for when a viral outbreak occurs. Both Oxford Nanopore Technologies (ONT) MinION and the Illumina (NGS) technology provide efficient methods to detect viral pathogens. Despite the availability of many strategies and software, matching them can be a very tedious and time-consuming task. As a result, we developed PIMGAVir and Vir-MinION, two metagenomics pipelines that automatically provide the user with a complete baseline analysis. The PIMGAVir and Vir-MinION pipelines work on 2nd and 3rd generation data, respectively, and provide the user with a taxonomic classification of the reads through three strategies: assembly-based, read-based, and clustering-based. The pipelines supply the scientist with comprehensive results in graphical and textual format for future analyses. Finally, the pipelines equip the user with a stand-alone platform with dedicated and various viral databases, which is a requirement for working in field conditions without internet connection.

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.

Novel Viral DNA Polymerases From Metagenomes Suggest Genomic Sources of Strand-Displacing Biochemical Phenotypes

Viruses are the most abundant and diverse biological entities on the planet and constitute a significant proportion of Earth's genetic diversity. Most of this diversity is not represented by isolated viral-host systems and has only been observed through sequencing of viral metagenomes (viromes) from environmental samples. Viromes provide snapshots of viral genetic potential, and a wealth of information on viral community ecology. These data also provide opportunities for exploring the biochemistry of novel viral enzymes. The in vitro biochemical characteristics of novel viral DNA polymerases were explored, testing hypothesized differences in polymerase biochemistry according to protein sequence phylogeny. Forty-eight viral DNA Polymerase I (PolA) proteins from estuarine viromes, hot spring metagenomes, and reference viruses, encompassing a broad representation of currently known diversity, were synthesized, expressed, and purified. Novel functionality was shown in multiple PolAs. Intriguingly, some of the estuarine viral polymerases demonstrated moderate to strong innate DNA strand displacement activity at high enzyme concentration. Strand-displacing polymerases have important technological applications where isothermal reactions are desirable. Bioinformatic investigation of genes neighboring these strand displacing polymerases found associations with SNF2 helicase-associated proteins. The specific function of SNF2 family enzymes is unknown for prokaryotes and viruses. In eukaryotes, SNF2 enzymes have chromatin remodeling functions but do not separate nucleic acid strands. This suggests the strand separation function may be fulfilled by the DNA polymerase for viruses carrying SNF2 helicase-associated proteins. Biochemical data elucidated from this study expands understanding of the biology and ecological behavior of unknown viruses. Moreover, given the numerous biotechnological applications of viral DNA polymerases, novel viral polymerases discovered within viromes may be a rich source of biological material for further in vitro DNA amplification advancements.

Molecular characterization of the gastrointestinal eukaryotic virome in elderly people in Belem, Para, Brazil

Acute gastroenteritis is one of the main causes of mortality and morbidity worldwide, affecting mainly children, the immunocompromised and elderly people. Enteric viruses, especially rotavirus A, are considered important etiological agents, while long-term care facilities are considered favorable environments for the occurrence of sporadic cases and outbreaks of acute gastroenteritis. Therefore, it is important to monitor the viral agents present in nursing homes, especially because studies involving the elderly population in Brazil are scarce, resulting in a lack of available virological data. As a result, the causative agent remains unidentified in a large number of reported acute gastroenteritis cases. However, the advent of next-generation sequencing provides new opportunities for viral detection and discovery. The aim of this study was to identify the viruses that circulate among elderly people with and without acute gastroenteritis, living in residential care homes in Belém, Pará, Brazil, between 2017 and 2019. Ninety-three samples were collected and screened by immunochromatography and qPCR. After, the samples were analyzed individually or in pools by next generation sequencing to identify the viruses circulating in this population. In 26 sequenced samples, members of 13 eukaryotic virus families were identified. The most abundantly present virus families were Parvoviridae, Genomoviridae and Smacoviridae. Contigs displaying similarity to pegiviruses were also detected. Furthermore, a near-complete rotavirus A genome was obtained and could be classified as G3P[8] genotype with the equine DS-1-like genetic background. Complete sequences of the VP4 and VP7 genes of a rotavirus C were also detected, belonging to G4P[2]. This study demonstrates the first characterization of the gastrointestinal virome in elderly in Northern Brazil. A diversity of viruses was found to be present in patients with and without diarrhea, reinforcing the need to monitor elderly people residing in long-term care facilities, especially in cases of acute gastroenteritis.

Performance of Five Metagenomic Classifiers for Virus Pathogen Detection Using Respiratory Samples from a Clinical Cohort

Viral metagenomics is increasingly applied in clinical diagnostic settings for detection of pathogenic viruses. While several benchmarking studies have been published on the use of metagenomic classifiers for abundance and diversity profiling of bacterial populations, studies on the comparative performance of the classifiers for virus pathogen detection are scarce. In this study, metagenomic data sets (n = 88) from a clinical cohort of patients with respiratory complaints were used for comparison of the performance of five taxonomic classifiers: Centrifuge, Clark, Kaiju, Kraken2, and Genome Detective. A total of 1144 positive and negative PCR results for a total of 13 respiratory viruses were used as gold standard. Sensitivity and specificity of these classifiers ranged from 83 to 100% and 90 to 99%, respectively, and was dependent on the classification level and data pre-processing. Exclusion of human reads generally resulted in increased specificity. Normalization of read counts for genome length resulted in a minor effect on overall performance, however it negatively affected the detection of targets with read counts around detection level. Correlation of sequence read counts with PCR Ct-values varied per classifier, data pre-processing (R² range 15.1–63.4%), and per virus, with outliers up to 3 log₁₀ reads magnitude beyond the predicted read count for viruses with high sequence diversity. In this benchmarking study, sensitivity and specificity were within the ranges of use for diagnostic practice when the cut-off for defining a positive result was considered per classifier.

Optimization of cerebrospinal fluid microbial DNA metagenomic sequencing diagnostics

Infection in the central nervous system is a severe condition associated with high morbidity and mortality. Despite ample testing, the majority of encephalitis and meningitis cases remain undiagnosed. Metagenomic sequencing of cerebrospinal fluid has emerged as an unbiased approach to identify rare microbes and novel pathogens. However, several major hurdles remain, including establishment of individual limits of detection, removal of false positives and implementation of universal controls. Twenty-one cerebrospinal fluid samples, in which a known pathogen had been positively identified by available clinical techniques, were subjected to metagenomic DNA sequencing. Fourteen samples contained minute levels of Epstein-Barr virus. The detection threshold for each sample was calculated by using the total leukocyte content in the sample and environmental contaminants found in the bioinformatic classifiers. Virus sequences were detected in all ten samples, in which more than one read was expected according to the calculations. Conversely, no viral reads were detected in seven out of eight samples, in which less than one read was expected according to the calculations. False positive pathogens of computational or environmental origin were readily identified, by using a commonly available cell control. For bacteria, additional filters including a comparison between classifiers removed the remaining false positives and alleviated pathogen identification. Here we show a generalizable method for identification of pathogen species using DNA metagenomic sequencing. The choice of bioinformatic method mainly affected the efficiency of pathogen identification, but not the sensitivity of detection. Identification of pathogens requires multiple filtering steps including read distribution, sequence diversity and complementary verification of pathogen reads.

Spaceflight Virology: What Do We Know about Viral Threats in the Spaceflight Environment?

Viruses constitute a significant part of the human microbiome, so wherever humans go, viruses are brought with them, even on space missions. In this mini review, we focus on the International Space Station (ISS) as the only current human habitat in space that has a diverse range of viral genera that infect microorganisms from bacteria to eukaryotes. Thus, we have reviewed the literature on the physical conditions of space habitats that have an impact on both virus transmissibility and interaction with their host, which include UV radiation, ionizing radiation, humidity, and microgravity. Also, we briefly comment on the practices used on space missions that reduce virus spread, that is, use of antimicrobial surfaces, spacecraft sterilization practices, and air filtration. Finally, we turn our attention to the health threats that viruses pose to space travel. Overall, even though efforts are taken to ensure safe conditions during human space travel, for example, preflight quarantines of astronauts, we reflect on the potential risks humans might be exposed to and how those risks might be aggravated in extraterrestrial habitats.

The Human Virome: Viral Metagenomics, Relations with Human Diseases, and Therapeutic Applications

The human body is colonized by a wide range of microorganisms. The field of viromics has expanded since the first reports on the detection of viruses via metagenomic sequencing in 2002. With the continued development of reference materials and databases, viral metagenomic approaches have been used to explore known components of the virome and discover new viruses from various types of samples. The virome has attracted substantial interest since the outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Increasing numbers of studies and review articles have documented the diverse virome in various sites in the human body, as well as interactions between the human host and the virome with regard to health and disease. However, there have been few studies of direct causal relationships. Viral metagenomic analyses often lack standard references and are potentially subject to bias. Moreover, most virome-related review articles have focused on the gut virome and did not investigate the roles of the virome in other sites of the body in human disease. This review presents an overview of viral metagenomics, with updates regarding the relations between alterations in the human virome and the pathogenesis of human diseases, recent findings related to COVID-19, and therapeutic applications related to the human virome.

LABRADOR-A Computational Workflow for Virus Detection in High-Throughput Sequencing Data

High-throughput sequencing (HTS) allows detection of known and unknown viruses in samples of broad origin. This makes HTS a perfect technology to determine whether or not the biological products, such as vaccines are free from the adventitious agents, which could support or replace extensive testing using various in vitro and in vivo assays. Due to bioinformatics complexities, there is a need for standardized and reliable methods to manage HTS generated data in this field. Thus, we developed LABRADOR—an analysis pipeline for adventitious virus detection. The pipeline consists of several third-party programs and is divided into two major parts: (i) direct reads classification based on the comparison of characteristic profiles between reads and sequences deposited in the database supported with alignment of to the best matching reference sequence and (ii) de novo assembly of contigs and their classification on nucleotide and amino acid levels. To meet the requirements published in guidelines for biologicals’ safety we generated a custom nucleotide database with viral sequences. We tested our pipeline on publicly available HTS datasets and showed that LABRADOR can reliably detect viruses in mixtures of model viruses, vaccines and clinical samples.

Human and Animal RNA Virus Diversity Detected by Metagenomics in Cameroonian Clams

Many recent pandemics have been recognized as zoonotic viral diseases. While their origins remain frequently unknown, environmental contamination may play an important role in emergence. Thus, being able to describe the viral diversity in environmental samples contributes to understand the key issues in zoonotic transmission. This work describes the use of a metagenomic approach to assess the diversity of eukaryotic RNA viruses in river clams and identify sequences from human or potentially zoonotic viruses. Clam samples collected over 2years were first screened for the presence of norovirus to verify human contamination. Selected samples were analyzed using metagenomics, including a capture of sequences from viral families infecting vertebrates (VirCapSeq-VERT) before Illumina NovaSeq sequencing. The bioinformatics analysis included pooling of data from triplicates, quality filtering, elimination of bacterial and host sequences, and a deduplication step before de novo assembly. After taxonomic assignment, the viral fraction represented 0.8–15% of reads with most sequences (68–87%) remaining un-assigned. Yet, several mammalian RNA viruses were identified. Contigs identified as belonging to the Astroviridae were the most abundant, with some nearly complete genomes of bastrovirus identified. Picobirnaviridae sequences were related to strains infecting bats, and few others to strains infecting humans or other hosts. Hepeviridae sequences were mostly related to strains detected in sponge samples but also strains from swine samples. For Caliciviridae and Picornaviridae, most of identified sequences were related to strains infecting bats, with few sequences close to human norovirus, picornavirus, and genogroup V hepatitis A virus. Despite a need to improve the sensitivity of our method, this study describes a large diversity of RNA virus sequences from clam samples. To describe all viral contaminants in this type of food, and being able to identify the host infected by viral sequences detected, may help to understand some zoonotic transmission events and alert health authorities of possible emergence.

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.

Contamination Issue in Viral Metagenomics: Problems, Solutions, and Clinical Perspectives

We describe the most common internal and external sources and types of contamination encountered in viral metagenomic studies and discuss their negative impact on sequencing results, particularly for low-biomass samples and clinical applications. We also propose some basic recommendations for reducing the background noise in viral shotgun metagenomic (SM) studies, which would limit the bias introduced by various classes of contaminants. Regardless of the specific viral SM protocol, contamination cannot be totally avoided; in particular, the issue of reagent contamination should always be addressed with high priority. There is an urgent need for the development and validation of standards for viral metagenomic studies especially if viral SM protocols will be more widely applied in diagnostics.

Metagenomic profiling of placental tissue suggests DNA virus infection of the placenta is rare

It is widely recognized that pathogens can be transmitted across the placenta from mother to foetus. Recent re-evaluation of metagenomic studies indicates that the placenta has no unique microbiome of commensal bacteria. However, viral transmission across the placenta, including transmission of DNA viruses such as the human herpesviruses, is possible. A fuller understanding of which DNA virus sequence can be found in the placenta is required. We employed a metagenomic analysis to identify viral DNA sequences in placental metagenomes from full-term births (20 births), pre-term births (13 births), births from pregnancies associated with antenatal infections (12 births) or pre-term births with antenatal infections (three births). Our analysis found only a small number of DNA sequences corresponding to the genomes of human herpesviruses in four of the 48 metagenomes analysed. Therefore, our data suggest that DNA virus infection of the placenta is rare and support the concept that the placenta is largely free of pathogen infection.

Viruses and Their Interactions With Bacteria and Archaea of Hypersaline Great Salt Lake

Viruses play vital biogeochemical and ecological roles by (a) expressing auxiliary metabolic genes during infection, (b) enhancing the lateral transfer of host genes, and (c) inducing host mortality. Even in harsh and extreme environments, viruses are major players in carbon and nutrient recycling from organic matter. However, there is much that we do not yet understand about viruses and the processes mediated by them in the extreme environments such as hypersaline habitats. The Great Salt Lake (GSL) in Utah, United States is a hypersaline ecosystem where the biogeochemical role of viruses is poorly understood. This study elucidates the diversity of viruses and describes virus–host interactions in GSL sediments along a salinity gradient. The GSL sediment virosphere consisted of Haloviruses (32.07 ± 19.33%) and members of families Siphoviridae (39.12 ± 19.8%), Myoviridae (13.7 ± 6.6%), and Podoviridae (5.43 ± 0.64%). Our results demonstrate that salinity alongside the concentration of organic carbon and inorganic nutrients (nitrogen and phosphorus) governs the viral, bacteria, and archaeal diversity in this habitat. Computational host predictions for the GSL viruses revealed a wide host range with a dominance of viruses that infect Proteobacteria, Actinobacteria, and Firmicutes. Identification of auxiliary metabolic genes for photosynthesis (psbA), carbon fixation (rbcL, cbbL), formaldehyde assimilation (SHMT), and nitric oxide reduction (NorQ) shed light on the roles played by GSL viruses in biogeochemical cycles of global relevance.

Fusion of intelligent learning for COVID-19: A state-of-the-art review and analysis on real medical data

The unprecedented surge of a novel coronavirus in the month of December 2019, named as COVID-19 by the World Health organization has caused a serious impact on the health and socioeconomic activities of the public all over the world. Since its origin, the number of infected and deceased cases has been growing exponentially in almost all the affected countries of the world. The rapid spread of the novel coronavirus across the world results in the scarcity of medical resources and overburdened hospitals. As a result, the researchers and technocrats are continuously working across the world for the inculcation of efficient strategies which may assist the government and healthcare system in controlling and managing the spread of the COVID-19 pandemic. Therefore, this study provides an extensive review of the ongoing strategies such as diagnosis, prediction, drug and vaccine development and preventive measures used in combating the COVID-19 along with technologies used and limitations. Moreover, this review also provides a comparative analysis of the distinct type of data, emerging technologies, approaches used in diagnosis and prediction of COVID-19, statistics of contact tracing apps, vaccine production platforms used in the COVID-19 pandemic. Finally, the study highlights some challenges and pitfalls observed in the systematic review which may assist the researchers to develop more efficient strategies used in controlling and managing the spread of COVID-19.

Utilizing the VirIdAl Pipeline to Search for Viruses in the Metagenomic Data of Bat Samples

According to various estimates, only a small percentage of existing viruses have been discovered, naturally much less being represented in the genomic databases. High-throughput sequencing technologies develop rapidly, empowering large-scale screening of various biological samples for the presence of pathogen-associated nucleotide sequences, but many organisms are yet to be attributed specific loci for identification. This problem particularly impedes viral screening, due to vast heterogeneity in viral genomes. In this paper, we present a new bioinformatic pipeline, VirIdAl, for detecting and identifying viral pathogens in sequencing data. We also demonstrate the utility of the new software by applying it to viral screening of the feces of bats collected in the Moscow region, which revealed a significant variety of viruses associated with bats, insects, plants, and protozoa. The presence of alpha and beta coronavirus reads, including the MERS-like bat virus, deserves a special mention, as it once again indicates that bats are indeed reservoirs for many viral pathogens. In addition, it was shown that alignment-based methods were unable to identify the taxon for a large proportion of reads, and we additionally applied other approaches, showing that they can further reveal the presence of viral agents in sequencing data. However, the incompleteness of viral databases remains a significant problem in the studies of viral diversity, and therefore necessitates the use of combined approaches, including those based on machine learning methods.

Molecular diagnostic assays for COVID-19: an overview

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the cardinal importance of rapid and accurate diagnostic assays. Since the early days of the outbreak, researchers with different scientific backgrounds across the globe have tried to fulfill the urgent need for such assays, with many assays having been approved and with others still undergoing clinical validation. Molecular diagnostic assays are a major group of tests used to diagnose COVID-19. Currently, the detection of SARS-CoV-2 RNA by reverse transcription polymerase chain reaction (RT-PCR) is the most widely used method. Other diagnostic molecular methods, including CRISPR-based assays, isothermal nucleic acid amplification methods, digital PCR, microarray assays, and next generation sequencing (NGS), are promising alternatives. In this review, we summarize the technical and clinical applications of the different COVID-19 molecular diagnostic assays and suggest directions for the implementation of such technologies in future infectious disease outbreaks.

Benchmark of thirteen bioinformatic pipelines for metagenomic virus diagnostics using datasets from clinical samples

INTRODUCTION

Metagenomic sequencing is increasingly being used in clinical settings for difficult to diagnose cases. The performance of viral metagenomic protocols relies to a large extent on the bioinformatic analysis. In this study, the European Society for Clinical Virology (ESCV) Network on NGS (ENNGS) initiated a benchmark of metagenomic pipelines currently used in clinical virological laboratories.

METHODS

Metagenomic datasets from 13 clinical samples from patients with encephalitis or viral respiratory infections characterized by PCR were selected. The datasets were analyzed with 13 different pipelines currently used in virological diagnostic laboratories of participating ENNGS members. The pipelines and classification tools were: Centrifuge, DAMIAN, DIAMOND, DNASTAR, FEVIR, Genome Detective, Jovian, MetaMIC, MetaMix, One Codex, RIEMS, VirMet, and Taxonomer. Performance, characteristics, clinical use, and user-friendliness of these pipelines were analyzed.

RESULTS

Overall, viral pathogens with high loads were detected by all the evaluated metagenomic pipelines. In contrast, lower abundance pathogens and mixed infections were only detected by 3/13 pipelines, namely DNASTAR, FEVIR, and MetaMix. Overall sensitivity ranged from 80% (10/13) to 100% (13/13 datasets). Overall positive predictive value ranged from 71-100%. The majority of the pipelines classified sequences based on nucleotide similarity (8/13), only a minority used amino acid similarity, and 6 of the 13 pipelines assembled sequences de novo. No clear differences in performance were detected that correlated with these classification approaches. Read counts of target viruses varied between the pipelines over a range of 2-3 log, indicating differences in limit of detection.

CONCLUSION

A wide variety of viral metagenomic pipelines is currently used in the participating clinical diagnostic laboratories. Detection of low abundant viral pathogens and mixed infections remains a challenge, implicating the need for standardization and validation of metagenomic analysis for clinical diagnostic use. Future studies should address the selective effects due to the choice of different reference viral databases.

Challenges and Solutions to Viral Diseases of Finfish in Marine Aquaculture

Aquaculture is the fastest food-producing sector in the world, accounting for one-third of global food production. As is the case with all intensive farming systems, increase in infectious diseases has adversely impacted the growth of marine fish farming worldwide. Viral diseases cause high economic losses in marine aquaculture. We provide an overview of the major challenges limiting the control and prevention of viral diseases in marine fish farming, as well as highlight potential solutions. The major challenges include increase in the number of emerging viral diseases, wild reservoirs, migratory species, anthropogenic activities, limitations in diagnostic tools and expertise, transportation of virus contaminated ballast water, and international trade. The proposed solutions to these problems include developing biosecurity policies at global and national levels, implementation of biosecurity measures, vaccine development, use of antiviral drugs and probiotics to combat viral infections, selective breeding of disease-resistant fish, use of improved diagnostic tools, disease surveillance, as well as promoting the use of good husbandry and management practices. A multifaceted approach combining several control strategies would provide more effective long-lasting solutions to reduction in viral infections in marine aquaculture than using a single disease control approach like vaccination alone.

k-mer-Based Metagenomics Tools Provide a Fast and Sensitive Approach for the Detection of Viral Contaminants in Biopharmaceutical and Vaccine Manufacturing Applications Using Next-Generation Sequencing

Adventitious agent detection during the production of vaccines and biotechnology-based medicines is of critical importance to ensure the final product is free from any possible viral contamination. Increasing the speed and accuracy of viral detection is beneficial as a means to accelerate development timelines and to ensure patient safety. Here, several rapid viral metagenomics approaches were tested on simulated next-generation sequencing (NGS) data sets and existing data sets from virus spike-in studies done in CHO-K1 and HeLa cell lines. It was observed that these rapid methods had comparable sensitivity to full-read alignment methods used for NGS viral detection for these data sets, but their specificity could be improved. A method that first filters host reads using KrakenUniq and then selects the virus classification tool based on the number of remaining reads is suggested as the preferred approach among those tested to detect nonlatent and nonendogenous viruses. Such an approach shows reasonable sensitivity and specificity for the data sets examined and requires less time and memory as full-read alignment methods.IMPORTANCE Next-generation sequencing (NGS) has been proposed as a complementary method to detect adventitious viruses in the production of biotherapeutics and vaccines to current in vivo and in vitro methods. Before NGS can be established in industry as a main viral detection technology, further investigation into the various aspects of bioinformatics analyses required to identify and classify viral NGS reads is needed. In this study, the ability of rapid metagenomics tools to detect viruses in biopharmaceutical relevant samples is tested and compared to recommend an efficient approach. The results showed that KrakenUniq can quickly and accurately filter host sequences and classify viral reads and had comparable sensitivity and specificity to slower full read alignment approaches, such as BLASTn, for the data sets examined.

Temporal landscape of human gut RNA and DNA virome in SARS-CoV-2 infection and severity

BACKGROUND

Coronavirus disease 2019 (COVID-19) caused by the enveloped RNA virus SARS-CoV-2 primarily affects the respiratory and gastrointestinal tracts. SARS-CoV-2 was isolated from fecal samples, and active viral replication was reported in human intestinal cells. The human gut also harbors an enormous amount of resident viruses (collectively known as the virome) that play a role in regulating host immunity and disease pathophysiology. Understanding gut virome perturbation that underlies SARS-CoV-2 infection and severity is an unmet need.

METHODS

We enrolled 98 COVID-19 patients with varying disease severity (3 asymptomatic, 53 mild, 34 moderate, 5 severe, 3 critical) and 78 non-COVID-19 controls matched for gender and co-morbidities. All subjects had fecal specimens sampled at inclusion. Blood specimens were collected for COVID-19 patients at admission to test for inflammatory markers and white cell counts. Among COVID-19 cases, 37 (38%) patients had serial fecal samples collected 2 to 3 times per week from time of hospitalization until after discharge. Using shotgun metagenomics sequencing, we sequenced and profiled the fecal RNA and DNA virome. We investigated alterations and longitudinal dynamics of the gut virome in association with disease severity and blood parameters.

RESULTS

Patients with COVID-19 showed underrepresentation of Pepper mild mottle virus (RNA virus) and multiple bacteriophage lineages (DNA viruses) and enrichment of environment-derived eukaryotic DNA viruses in fecal samples, compared to non-COVID-19 subjects. Such gut virome alterations persisted up to 30 days after disease resolution. Fecal virome in SARS-CoV-2 infection harbored more stress-, inflammation-, and virulence-associated gene encoding capacities including those pertaining to bacteriophage integration, DNA repair, and metabolism and virulence associated with their bacterial host. Baseline fecal abundance of 10 virus species (1 RNA virus, pepper chlorotic spot virus, and 9 DNA virus species) inversely correlated with disease COVID-19 severity. These viruses inversely correlated with blood levels of pro-inflammatory proteins, white cells, and neutrophils. Among the 10 COVID-19 severity-associated DNA virus species, 4 showed inverse correlation with age; 5 showed persistent lower abundance both during disease course and after disease resolution relative to non-COVID-19 subjects.

CONCLUSIONS

Both enteric RNA and DNA virome in COVID-19 patients were different from non-COVID-19 subjects, which persisted after disease resolution of COVID-19. Gut virome may calibrate host immunity and regulate severity to SARS-CoV-2 infection. Our observation that gut viruses inversely correlated with both severity of COVID-19 and host age may partly explain that older subjects are prone to severe and worse COVID-19 outcomes. Altogether, our data highlight the importance of human gut virome in severity and potentially therapeutics of COVID-19. Video Abstract.

Recommendations for the introduction of metagenomic next-generation sequencing in clinical virology, part II: bioinformatic analysis and reporting

Metagenomic next-generation sequencing (mNGS) is an untargeted technique for determination of microbial DNA/RNA sequences in a variety of sample types from patients with infectious syndromes. mNGS is still in its early stages of broader translation into clinical applications. To further support the development, implementation, optimization and standardization of mNGS procedures for virus diagnostics, the European Society for Clinical Virology (ESCV) Network on Next-Generation Sequencing (ENNGS) has been established. The aim of ENNGS is to bring together professionals involved in mNGS for viral diagnostics to share methodologies and experiences, and to develop application guidelines. Following the ENNGS publication Recommendations for the introduction of mNGS in clinical virology, part I: wet lab procedure in this journal, the current manuscript aims to provide practical recommendations for the bioinformatic analysis of mNGS data and reporting of results to clinicians.

viromeBrowser: A Shiny App for Browsing Virome Sequencing Analysis Results

Experiments in which complex virome sequencing data is generated remain difficult to explore and unpack for scientists without a background in data science. The processing of raw sequencing data by high throughput sequencing workflows usually results in contigs in FASTA format coupled to an annotation file linking the contigs to a reference sequence or taxonomic identifier. The next step is to compare the virome of different samples based on the metadata of the experimental setup and extract sequences of interest that can be used in subsequent analyses. The viromeBrowser is an application written in the opensource R shiny framework that was developed in collaboration with end-users and is focused on three common data analysis steps. First, the application allows interactive filtering of annotations by default or custom quality thresholds. Next, multiple samples can be visualized to facilitate comparison of contig annotations based on sample specific metadata values. Last, the application makes it easy for users to extract sequences of interest in FASTA format. With the interactive features in the viromeBrowser we aim to enable scientists without a data science background to compare and extract annotation data and sequences from virome sequencing analysis results.

Biases in Viral Metagenomics-Based Detection, Cataloguing and Quantification of Bacteriophage Genomes in Human Faeces, a Review

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.