Discovering viral genomes in human metagenomic data by predicting unknown protein families

Post-genomic platform for development of oligonucleotide vaccines against RNA viruses: diamond cuts diamond

The coronavirus pandemic has starkly demonstrated the need to create highly effective vaccines against various viral diseases. The emerging new platforms for vaccine creation (adenovirus vectors and mRNA vaccines) have shown their worth in the fight against the prevention of coronavirus infection. However, adenovirus vectors and mRNA vaccines have a serious disadvantage: as a rule, only the S protein of the coronavirus is presented as an antigen. This tactic for preventing infection allows the ever-mutating virus to escape quickly from the immunity protection provided by such vaccines. Today, viral genomic databases are well-developed, which makes it possible to create new vaccines on a fundamentally new post-genomic platform. In addition, the technology for the synthesis of nucleic acids is currently experiencing an upsurge in demand in various fields of molecular biology. The accumulated experience suggests that the unique genomic sequences of viruses can act as antigens that trigger powerful humoral and cellular immunity. To achieve this effect, the following conditions must be created: the structure of the nucleic acid must be single-stranded, have a permanent 3D nanostructure, and have a unique sequence absent in the vaccinated organism. Oligonucleotide vaccines are able to resist the rapidly changing genomic sequences of RNA viruses by using conserved regions of their genomes to generate a long-term immune response, acting according to the adage that a diamond cuts a diamond. In addition, oligonucleotide vaccines will not contribute to antibody-dependent enhanced infection, since the nucleic acid of the coronavirus is inside the viral particle. It is obvious that new epidemics and pandemics caused by RNA viruses will continue to arise periodically in the human population. The creation of new, safe, and effective platforms for the production of vaccines that can flexibly change and adapt to new subtypes of viruses is very urgent and at this moment should be considered as a strategically necessary task.

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.

Short k-mer abundance profiles yield robust machine learning features and accurate classifiers for RNA viruses

High-throughput sequencing technologies have greatly enabled the study of genomics, transcriptomics and metagenomics. Automated annotation and classification of the vast amounts of generated sequence data has become paramount for facilitating biological sciences. Genomes of viruses can be radically different from all life, both in terms of molecular structure and primary sequence. Alignment-based and profile-based searches are commonly employed for characterization of assembled viral contigs from high-throughput sequencing data. Recent attempts have highlighted the use of machine learning models for the task, but these models rely entirely on DNA genomes and owing to the intrinsic genomic complexity of viruses, RNA viruses have gone completely overlooked. Here, we present a novel short k-mer based sequence scoring method that generates robust sequence information for training machine learning classifiers. We trained 18 classifiers for the task of distinguishing viral RNA from human transcripts. We challenged our models with very stringent testing protocols across different species and evaluated performance against BLASTn, BLASTx and HMMER3 searches. For clean sequence data retrieved from curated databases, our models display near perfect accuracy, outperforming all similar attempts previously reported. On de novo assemblies of raw RNA-Seq data from cells subjected to Ebola virus, the area under the ROC curve varied from 0.6 to 0.86 depending on the software used for assembly. Our classifier was able to properly classify the majority of the false hits generated by BLAST and HMMER3 searches on the same data. The outstanding performance metrics of our model lays the groundwork for robust machine learning methods for the automated annotation of sequence data.

Beyond Just Bacteria: Functional Biomes in the Gut Ecosystem Including Virome, Mycobiome, Archaeome and Helminths

Gut microbiota refers to a complex network of microbes, which exerts a marked influence on the host’s health. It is composed of bacteria, fungi, viruses, and helminths. Bacteria, or collectively, the bacteriome, comprises a significant proportion of the well-characterized microbiome. However, the other communities referred to as ‘dark matter’ of microbiomes such as viruses (virome), fungi (mycobiome), archaea (archaeome), and helminths have not been completely elucidated. Development of new and improved metagenomics methods has allowed the identification of complete genomes from the genetic material in the human gut, opening new perspectives on the understanding of the gut microbiome composition, their importance, and potential clinical applications. Here, we review the recent evidence on the viruses, fungi, archaea, and helminths found in the mammalian gut, detailing their interactions with the resident bacterial microbiota and the host, to explore the potential impact of the microbiome on host’s health. The role of fecal virome transplantations, pre-, pro-, and syn-biotic interventions in modulating the microbiome and their related concerns are also discussed.

The Cancer Microbiome: Distinguishing Direct and Indirect Effects Requires a Systemic View

The collection of microbes that live in and on the human body - the human microbiome - can impact on cancer initiation, progression, and response to therapy, including cancer immunotherapy. The mechanisms by which microbiomes impact on cancers can yield new diagnostics and treatments, but much remains unknown. The interactions between microbes, diet, host factors, drugs, and cell-cell interactions within the cancer itself likely involve intricate feedbacks, and no single component can explain all the behavior of the system. Understanding the role of host-associated microbial communities in cancer systems will require a multidisciplinary approach combining microbial ecology, immunology, cancer cell biology, and computational biology - a systems biology approach.

Gut virome of mammals and birds reveals high genetic diversity of the family Microviridae

Nineteen families of phages infecting bacteria or archaea are currently recognized by the International Committee on Taxonomy of Viruses (ICTV). Of these, only two have single-stranded DNA genomes, namely Inoviridae and Microviridae. The distribution, genetic characteristics, and ecological roles of Microviridae remain largely under explored. Here, using viral metagenomics, we investigate the intestinal virome from human and twenty-four species of animals, as well as freshwater samples, containing abundant sequence reads showing similarity to the Microviridae. Eight hundred and sixty complete or near complete Microviridae-related genomes were generated, showing high levels of co-infections and sequence divergence. Sequence comparison and phylogenetic analysis showed that the Microviridae subfamily Gokushovirinae was highly prevalent and that some strains may qualify as new subfamilies. This study significantly augments our knowledge of the genetic diversity, genome evolution, and distribution in animal species of members of the family Microviridae.

Genetic and functional diversity of double-stranded DNA viruses in a tropical monsoonal estuary, India

The present study illustrates the genetic diversity of four uncultured viral communities from the surface waters of Cochin Estuary (CE), India. Viral diversity inferred using Illumina HiSeq paired-end sequencing using a linker-amplified shotgun library (LASL) revealed different double-stranded DNA (dsDNA) viral communities. The water samples were collected from four stations PR1, PR2, PR3, and PR4, during the pre-monsoon (PRM) season. Analysis of virus families indicated that the Myoviridae was the most common viral community in the CE followed by Siphoviridae and Podoviridae. There were significant (p < 0.05) spatial variations in the relative abundance of dominant families in response to the salinity regimes. The relative abundance of Myoviridae and Podoviridae were high in the euryhaline region and Siphoviridae in the mesohaline region of the estuary. The predominant phage type in CE was phages that infected Synechococcus. The viral proteins were found to be involved in major functional activities such as ATP binding, DNA binding, and DNA replication. The study highlights the genetic diversity of dsDNA viral communities and their functional protein predictions from a highly productive estuarine system. Further, the metavirome data generated in this study will enhance the repertoire of publicly available dataset and advance our understanding of estuarine viral ecology.