The virome is comprised of endogenous retroviruses, eukaryotic viruses, and bacteriophages and is increasingly being recognized as an essential part of the human microbiome. The human virome is associated with Type-1 diabetes (T1D), Type-2 diabetes (T2D), Inflammatory Bowel Disease (IBD), Human Immunodeficiency Virus (HIV) infection, and cancer. Increasing evidence also supports trans-kingdom interactions of viruses with bacteria, small eukaryotes and host in disease progression. The present review focuses on virus ecology and biology and how this translates mostly to human gut virome research. Current challenges in the field and how the development of bioinformatic tools and controls are aiding to overcome some of these challenges are also discussed. Finally, the present review also focuses on how human gut virome research could result in translational and clinical studies that may facilitate the development of therapeutic approaches.

Viruses are part of the microbiome and have essential roles in immunology, evolution, biogeochemical cycles, health, and disease progression. Viruses influence a wide variety of systems and processes, and the continued discovery of novel viruses is anticipated to reveal new mechanisms influencing the biology of diverse environments. While the identity and roles of viruses continue to be discovered and understood through viral metagenomics, most of the sequences in virome datasets cannot be attributed to known viruses or may be only distantly related to species already described in public sequence databases, at best. Such viruses are known as the viral dark matter. Ongoing discoveries from the viral dark matter have provided insights into novel viruses from a variety of environments, as well as their potential in immunological processes, virus evolution, health, disease, therapeutics, and surveillance. Increased understanding of the viral dark matter will continue with a combination of cultivation, microscopy, sequencing, and bioinformatic efforts, which are discussed in the present review.

Skin acts as a barrier that promotes the colonization of bacteria, fungi, archaea, and viruses whose membership and function may differ depending on the various specialized niches or micro-environments of the skin. The group of microorganisms inhabiting the skin, also known as the skin microbiome, offers protection against pathogens while actively interacting with the host’s immune system. Some members of the skin microbiome can also act as opportunistic pathogens. The skin microbiome is influenced by factors such as skin site, birth mode, genetics, environment, skin products, and skin conditions. The association(s) of the skin microbiome with health and disease has (have) been identified and characterized via culture-dependent and culture-independent methods. Culture-independent methods (such as high-throughput sequencing), in particular, have expanded our understanding of the skin microbiome’s role in maintaining health or promoting disease. However, the intrinsic challenges associated with the low microbial biomass and high host content of skin microbiome samples have hindered advancements in the field. In addition, the limitations of current collection and extraction methods and biases derived from sample preparation and analysis have significantly influenced the results and conclusions of many skin microbiome studies. Therefore, the present review discusses the technical challenges associated with the collection and processing of skin microbiome samples, the advantages and disadvantages of current sequencing approaches, and potential future areas of focus for the field.

The One Health framework recognizes that human, animal, and environmental health are linked and highly interdependent. Fecal contamination of water, soil, foodstuff, and air may impact many aspects of One Health, and culture, PCR-based, and sequencing methods are utilized in the detection of fecal contamination to determine source, load, and risk to inform targeted mitigation strategies. Viruses, particularly, have been considered as fecal contamination indicators given the narrow host range many exhibit and their association with other biological contaminants. Culture- and molecular-based methods are considered the gold-standards for virus detection and for determining specific sources of fecal contamination via viral indicators. However, viral metagenomics is also being considered as a tool for tracking sources of fecal contamination. In the present review, studies tracking potential sources of fecal contamination in freshwaters, marine waters, foodstuff, soil, and air using viral metagenomics are discussed to highlight the potential of viral metagenomics for optimizing fecal source tracking. Limitations of the use of viral metagenomics to track fecal contamination sources, including sample processing, nucleic acid recovery, sequencing depth, and bioinformatics are also discussed. Finally, the present review discusses the potential of viral metagenomics as part of the toolbox of methods in a One Health approach.

Sequencing of the 16S rRNA gene (16S) has long been a go-to method for microbiome characterization due to its accessibility and lower cost compared to shotgun metagenomic sequencing (SMS). However, 16S sequencing rarely provides species-level resolution and cannot provide direct assessment of other taxa (e.g., viruses and fungi) or functional gene content. Shallow shotgun metagenomic sequencing (SSMS) has emerged as an approach to bridge the gap between 16S sequencing and deep metagenomic sequencing. SSMS is cost-competitive with 16S sequencing, while also providing species-level resolution and functional gene content insights. In the present study, we evaluated the effects of sequencing depth on marker gene-mapping- and alignment-based annotation of bacteria in healthy human stool samples. The number of identified taxa decreased with lower sequencing depths, particularly with the marker gene-mapping-based approach. Other annotations, including viruses and pathways, also showed a depth-dependent effect on feature recovery. These results refine the understanding of the suitability and shortcomings of SSMS, as well as annotation tools for metagenomic analyses in human stool samples. Results may also translate to other sample types and may open the opportunity to explore the effect of sequencing depth and annotation method.

Little is still known about the microbiome resulting from the process of mummification of the human gut. In the present study, the gut microbiota, genes associated with metabolism, and putative resistome of Inca and Italian nobility mummies were characterized by using high-throughput sequencing. The Italian nobility mummies exhibited a higher bacterial diversity as compared to the Inca mummies when using 16S ribosomal (rRNA) gene amplicon sequencing, but both groups showed bacterial and fungal taxa when using shotgun metagenomic sequencing that may resemble both the thanatomicrobiome and extant human gut microbiomes. Identification of sequences associated with plants, animals, and carbohydrate-active enzymes (CAZymes) may provide further insights into the dietary habits of Inca and Italian nobility mummies. Putative antibiotic-resistance genes in the Inca and Italian nobility mummies support a human gut resistome prior to the antibiotic therapy era. The higher proportion of putative antibiotic-resistance genes in the Inca compared to Italian nobility mummies may support the hypotheses that a greater exposure to the environment may result in a greater acquisition of antibiotic-resistance genes. The present study adds knowledge of the microbiome resulting from the process of mummification of the human gut, insights of ancient dietary habits, and the preserved putative human gut resistome prior the antibiotic therapy era.