Prophages: an integral but understudied component of the human microbiome.

Phages integrated into a bacterial genome - called prophages - continuously monitor the vigour of the host bacteria to determine when to escape the genome and to protect their host from other phage infections, and they may provide genes that promote bacterial growth. Prophages are essential to almost all microbiomes, including the human microbiome. However, most human microbiome studies have focused on bacteria, ignoring free and integrated phages, so we know little about how these prophages affect the human microbiome. To address this gap in our knowledge, we compared the prophages identified in 14 987 bacterial genomes isolated from human body sites to characterize prophage DNA in the human microbiome. Here, we show that prophage DNA is ubiquitous, comprising on average 1-5 % of each bacterial genome. The prophage content per genome varies with the isolation site on the human body, the health of the human and whether the disease was symptomatic. The presence of prophages promotes bacterial growth and sculpts the microbiome. However, the disparities caused by prophages vary throughout the body.

Phables: from fragmented assemblies to high-quality bacteriophage genomes.

MOTIVATION: Microbial communities have a profound impact on both human health and various environments. Viruses infecting bacteria, known as bacteriophages or phages, play a key role in modulating bacterial communities within environments. High-quality phage genome sequences are essential for advancing our understanding of phage biology, enabling comparative genomics studies and developing phage-based diagnostic tools. Most available viral identification tools consider individual sequences to determine whether they are of viral origin. As a result of challenges in viral assembly, fragmentation of genomes can occur, and existing tools may recover incomplete genome fragments. Therefore, the identification and characterization of novel phage genomes remain a challenge, leading to the need of improved approaches for phage genome recovery. RESULTS: We introduce Phables, a new computational method to resolve phage genomes from fragmented viral metagenome assemblies. Phables identifies phage-like components in the assembly graph, models each component as a flow network, and uses graph algorithms and flow decomposition techniques to identify genomic paths. Experimental results of viral metagenomic samples obtained from different environments show that Phables recovers on average over 49% more high-quality phage genomes compared to existing viral identification tools. Furthermore, Phables can resolve variant phage genomes with over 99% average nucleotide identity, a distinction that existing tools are unable to make. AVAILABILITY AND IMPLEMENTATION: Phables is available on GitHub at https://github.com/Vini2/phables.

The human gut virome: composition, colonization, interactions, and impacts on human health.

The gut virome is an incredibly complex part of the gut ecosystem. Gut viruses play a role in many disease states, but it is unknown to what extent the gut virome impacts everyday human health. New experimental and bioinformatic approaches are required to address this knowledge gap. Gut virome colonization begins at birth and is considered unique and stable in adulthood. The stable virome is highly specific to each individual and is modulated by varying factors such as age, diet, disease state, and use of antibiotics. The gut virome primarily comprises bacteriophages, predominantly order Crassvirales, also referred to as crAss-like phages, in industrialized populations and other Caudoviricetes (formerly Caudovirales). The stability of the virome's regular constituents is disrupted by disease. Transferring the fecal microbiome, including its viruses, from a healthy individual can restore the functionality of the gut. It can alleviate symptoms of chronic illnesses such as colitis caused by Clostridiodes difficile. Investigation of the virome is a relatively novel field, with new genetic sequences being published at an increasing rate. A large percentage of unknown sequences, termed 'viral dark matter', is one of the significant challenges facing virologists and bioinformaticians. To address this challenge, strategies include mining publicly available viral datasets, untargeted metagenomic approaches, and utilizing cutting-edge bioinformatic tools to quantify and classify viral species. Here, we review the literature surrounding the gut virome, its establishment, its impact on human health, the methods used to investigate it, and the viral dark matter veiling our understanding of the gut virome.

Prophage rates in the human microbiome vary by body site and host health.

Phages integrated into a bacterial genome-called prophages-continuously monitor the health of the host bacteria to determine when to escape the genome, protect their host from other phage infections, and may provide genes that promote bacterial growth. Prophages are essential to almost all microbiomes, including the human microbiome. However, most human microbiome studies focus on bacteria, ignoring free and integrated phages, so we know little about how these prophages affect the human microbiome. We compared the prophages identified in 11,513 bacterial genomes isolated from human body sites to characterise prophage DNA in the human microbiome. Here, we show that prophage DNA comprised an average of 1-5% of each bacterial genome. The prophage content per genome varies with the isolation site on the human body, the health of the human, and whether the disease was symptomatic. The presence of prophages promotes bacterial growth and sculpts the microbiome. However, the disparities caused by prophages vary throughout the body.

The Promise and Pitfalls of Prophages.

Phages dominate every ecosystem on the planet. While virulent phages sculpt the microbiome by killing their bacterial hosts, temperate phages provide unique growth advantages to their hosts through lysogenic conversion. Many prophages benefit their host, and prophages are responsible for genotypic and phenotypic differences that separate individual microbial strains. However, the microbes also endure a cost to maintain those phages: additional DNA to replicate and proteins to transcribe and translate. We have never quantified those benefits and costs. Here, we analysed over two and a half million prophages from over half a million bacterial genome assemblies. Analysis of the whole dataset and a representative subset of taxonomically diverse bacterial genomes demonstrated that the normalised prophage density was uniform across all bacterial genomes above 2 Mbp. We identified a constant carrying capacity of phage DNA per bacterial DNA. We estimated that each prophage provides cellular services equivalent to approximately 2.4 % of the cell's energy or 0.9 ATP per bp per hour. We demonstrate analytical, taxonomic, geographic, and temporal disparities in identifying prophages in bacterial genomes that provide novel targets for identifying new phages. We anticipate that the benefits bacteria accrue from the presence of prophages balance the energetics involved in supporting prophages. Furthermore, our data will provide a new framework for identifying phages in environmental datasets, diverse bacterial phyla, and from different locations.

Phables: from fragmented assemblies to high-quality bacteriophage genomes.

Microbial communities influence both human health and different environments. Viruses infecting bacteria, known as bacteriophages or phages, play a key role in modulating bacterial communities within environments. High-quality phage genome sequences are essential for advancing our understanding of phage biology, enabling comparative genomics studies, and developing phage-based diagnostic tools. Most available viral identification tools consider individual sequences to determine whether they are of viral origin. As a result of the challenges in viral assembly, fragmentation of genomes can occur, leading to the need for new approaches in viral identification. Therefore, the identification and characterisation of novel phages remain a challenge. We introduce Phables, a new computational method to resolve phage genomes from fragmented viral metagenome assemblies. Phables identifies phage-like components in the assembly graph, models each component as a flow network, and uses graph algorithms and flow decomposition techniques to identify genomic paths. Experimental results of viral metagenomic samples obtained from different environments show that Phables recovers on average over 49% more high-quality phage genomes compared to existing viral identification tools. Furthermore, Phables can resolve variant phage genomes with over 99% average nucleotide identity, a distinction that existing tools are unable to make. Phables is available on GitHub at https://github.com/Vini2/phables.

How Metagenomics Has Transformed Our Understanding of Bacteriophages in Microbiome Research.

The microbiome is an essential part of most ecosystems. It was originally studied mostly through culturing but relatively few microbes can be cultured, so much of the microbiome was left unexplored. The emergence of metagenomic sequencing techniques changed that and allowed the study of microbiomes from all sorts of habitats. Metagenomic sequencing also allowed for a more thorough exploration of prophages, viruses that integrate into bacterial genomes, and how they benefit their hosts. One issue with using open-access metagenomic data is that sequences added to databases often have little to no metadata to work with, so finding enough sequences can be difficult. Many metagenomes have been manually curated but this is a time-consuming process and relies heavily on the uploader to be accurate and thorough when filling in metadata fields and the curators to be working with the same ontologies. Using algorithms to automatically sort metagenomes based on either the taxonomic profile or the functional profile may be a viable solution to the issues with manually curated metagenomes, but it requires that the algorithm is trained on carefully curated datasets and using the most informative profile possible in order to minimize errors.