Biology subjects

Anantharaman, K.

Publications and source records attributed to Anantharaman, K..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Diversity and distribution of sulfur metabolism in the human gut microbiome and its association with colorectal cancer

Microbial sulfidogenesis produces genotoxic hydrogen sulfide (H2S) in the human gut using inorganic (sulfate) and organic (taurine/cysteine/methionine) substrates, however the majority of studies have focused on sulfate reduction using dissimilatory sulfite reductases (Dsr). Recent evidence implicates microbial sulfidogenesis as a potential trigger of colorectal cancer (CRC), highlighting the need for comprehensive knowledge of sulfur metabolism within the human gut. Here we show that microbial sulfur metabolism is more abundant and diverse than previously studied and is statistically associated with CRC. Using ~17,000 bacterial genomes from publicly available stool metagenomes, we studied the diversity of sulfur metabolic genes in 667 participants across different health statuses: healthy, adenoma, and carcinoma. Sulfidogenic genes were harbored by 142 bacterial genera and both organic and inorganic sulfidogenic genes were associated with carcinoma. Significantly, anaerobic sulfite reductases were twice as abundant as dsr. We identified twelve potential pathways for reductive taurine metabolism including novel pathways, and prevalence of organic sulfur metabolic genes indicate these substrates may be the most abundant source of microbially derived H2S. Our findings significantly expand knowledge of microbial sulfur metabolism in the human gut, and highlight key gaps that limit understanding of its potential contributions to the pathogenesis of CRC.

microbiology↗

bioRxiv2021

Polysaccharide utilization loci in Bacteroides determine population fitness and community-level interactions

Polysaccharide utilization loci (PULs) in the human gut microbiome have critical roles in shaping human health and ecological dynamics. We develop a CRISPR-FnCpf1-RecT genome-editing tool to study 23 PULs in the highly abundant species B. uniformis (BU). We identify the glycan-degrading functions of multiple PULs and elucidate transcriptional coordination between PULs that enables the population to adapt to the loss of PULs. Exploiting a pooled BU mutant barcoding strategy, we demonstrate that the in vitro fitness and the colonization ability of BU in the murine gut is enhanced by deletion of specific PULs and modulated by glycan availability. We show that BU PULs can mediate complex glycan-dependent interactions with butyrate producers that depend on the mechanism of degradation and the butyrate producer glycan utilizing ability. In sum, PULs are major determinants of community dynamics and butyrate production and can provide a selective advantage or disadvantage depending on the nutritional landscape.

synthetic biology↗

bioRxiv2021

Individuals at risk for developing rheumatoid arthritis harbor differential intestinal bacteriophage communities with distinct metabolic potential

Rheumatoid arthritis (RA) is an autoimmune disease characterized in seropositive individuals by the presence of anti-cyclic citrullinated protein (CCP) antibodies. RA is linked to the intestinal microbiota, yet the association of microbes with CCP serology and their contribution to RA is unclear. We describe intestinal phage communities of individuals at risk for developing RA, with or without anti-CCP antibodies, whose first degree relatives have been diagnosed with RA. We show that at-risk individuals harbor intestinal phage compositions that diverge based on CCP serology, are dominated by Lachnospiraceae phages, and originate from disparate ecosystems. These phages encode unique repertoires of auxiliary metabolic genes (AMGs) which associate with anti-CCP status, suggesting that these phages directly influence the metabolic and immunomodulatory capability of the microbiota. This work sets the stage for the use of phages as preclinical biomarkers and provides insight into a possible microbial-based causation of RA disease development.

microbiology↗

bioRxiv2021

Deciphering active prophages from metagenomes

Temperate phages (prophages) are ubiquitous in nature and persist as dormant components of host cells (lysogenic stage) before activating and lysing the host (lytic stage). Actively replicating prophages contribute to central community processes, such as enabling bacterial virulence, manipulating biogeochemical cycling, and driving microbial community diversification. Recent advances in sequencing technology have allowed for the identification and characterization of diverse phages, yet no approaches currently exist for identifying if a prophage has activated. Here, we present PropagAtE (Prophage Activity Estimator), an automated software tool for estimating if a prophage is in the lytic or lysogenic stage of infection. PropagAtE uses statistical analyses of prophage-to-host read coverage ratios to decipher actively replicating prophages, irrespective of whether prophages were induced or spontaneously activated. We demonstrate that PropagAtE is fast, accurate and sensitive, regardless of sequencing depth. Application of PropagAtE to prophages from 348 complex metagenomes from human gut, murine gut and soil environments identified distinct spatial and temporal prophage activation signatures, with the highest proportion of active prophages in murine gut samples. Among the soil habitats evaluated (bog, fen and palsa), we identified unique populations of Myxococcales, Acetobacteraceae and Acidimicrobiaceae prophages to be active in fen, palsa and bog habitats, respectively. Within the human gut, 11 prophage populations, some encoding the sulfur metabolism gene cysH or a rhuM-like virulence factor, were consistently present over time but not active. Overall, PropagAtE will facilitate accurate representations of viruses in microbiomes by associating prophages with their active roles in shaping microbial communities in nature.

bioinformatics↗

bioRxiv2021

Virus-associated organosulfur metabolism in human and environmental systems

Viruses influence the fate of nutrients and human health by killing microorganisms and altering metabolic processes. Organosulfur metabolism and biologically-derived hydrogen sulfide play dynamic roles in manifestation of diseases, infrastructure degradation, and essential biological processes. While microbial organosulfur metabolism is well-studied, the role of viruses in organosulfur metabolism is unknown. Here we report the discovery of 39 gene families involved in organosulfur metabolism encoded by 3,749 viruses from diverse ecosystems, including human microbiomes. The viruses infect organisms from all three domains of life. Six gene families encode for enzymes that degrade organosulfur compounds into sulfide, while others manipulate organosulfur compounds and may influence sulfide production. We show that viral metabolic genes encode key enzymatic domains, are translated into protein, are maintained after recombination, and that sulfide provides a fitness advantage to viruses. Our results reveal viruses as drivers of organosulfur metabolism with important implications for human and environmental health.

microbiology↗

bioRxiv2020

Ecology of inorganic sulfur auxiliary metabolism in widespread bacteriophages

Microbial sulfur metabolism contributes to biogeochemical cycling on global scales. Sulfur metabolizing microbes are infected by phages that can encode auxiliary metabolic genes (AMGs) to alter sulfur metabolism within host cells but remain poorly characterized. Here we identified 191 phages derived from twelve environments that encoded 227 AMGs for oxidation of sulfur and thiosulfate (dsrA, dsrC/tusE, soxC, soxD and soxYZ). Evidence for retention of AMGs during niche-differentiation of diverse phage populations provided evidence that auxiliary metabolism imparts measurable fitness benefits to phages with ramifications for ecosystem biogeochemistry. Gene abundance and expression profiles of AMGs suggested significant contributions by phages to sulfur and thiosulfate oxidation in freshwater lakes and oceans, and a sensitive response to changing sulfur concentrations in hydrothermal environments. Overall, our study provides novel insights on the distribution, diversity and ecology of phage auxiliary metabolism associated with sulfur and reinforces the necessity of incorporating viral contributions into biogeochemical configurations.

microbiology↗

bioRxiv2020

Microbial dark matter driven degradation of carbon fiber polymer composites

Polymer composites have become attractive for structural applications in the built environment due to their lightweight and high strength properties but can suffer from degradation due to environmental factors. While impacts of abiotic factors like temperature and moisture are well studied, little is known about the influence of naturally occurring microbial communities on their structural integrity. Here we apply complementary time-series multi-omics of biofilms growing on polymer composites and materials characterization to elucidate, for the first time, the processes driving their degradation. We measured a reduction in mechanical properties due to molecular chain breakage and reconstructed 121 microbial genomes to describe microbial diversity and pathways associated with their degradation. The composite microbiome is dominated by four bacterial groups including the Candidate Phyla Radiation that possess pathways for breakdown of acrylate, esters, and bisphenol, abundant in composites. Overall, we provide a foundation for understanding interactions of next-generation structural materials with their natural environment that can predict their durability and drive future designs.

microbiology↗

bioRxiv2020

Expanded Phylogenetic Diversity and Metabolic Flexibility of Microbial Mercury Methylation

Methylmercury is a potent, bioaccumulating neurotoxin that is produced by specific microorganisms by methylation of inorganic mercury released from anthropogenic sources. The hgcAB genes were recently discovered to be required for microbial methylmercury production in diverse anaerobic bacteria and archaea. However, the full phylogenetic and metabolic diversity of mercury methylating microorganisms has not been fully explored due to the limited number of cultured, experimentally verified methylators and the limitations of primer-based molecular methods. Here, we describe the phylogenetic diversity and metabolic flexibility of putative mercury methylating microorganisms identified by hgcA sequence identity from publicly available isolate genomes and metagenome-assembled genomes (MAGs), as well as novel freshwater MAGs. We demonstrate that putative mercury methylators are much more phylogenetically diverse than previously known, and the distribution of hgcA is most likely due to several independent horizontal gene transfer events. Identified methylating microorganisms possess diverse metabolic capabilities spanning carbon fixation, sulfate reduction, nitrogen fixation, and metal resistance pathways. Using a metatranscriptomic survey of a thawing permafrost gradient from which we identified 111 putative mercury methylators, we demonstrate that specific methylating populations may contribute to hgcA expression at different depths. Overall, we provide a framework for illuminating the microbial basis of mercury methylation using genome-resolved metagenomics and metatranscriptomics to identify methylators based upon hgcA presence and describe their putative functions in the environment. IMPORTANCESpecific anaerobic microorganisms among the Deltaproteobacteria, Firmicutes, and Euryarchaeota have been shown to produce the bioaccumulating neurotoxin methylmercury. Accurately assessing the sources of microbial methylmercury production in the context of phylogenetic identification, metabolic guilds, and activity in the environment is crucial for understanding the constraints and effects of mercury impacted sites. Advances in next-generation sequencing technologies have enabled large-scale, cultivation-independent surveys of diverse and poorly characterized microorganisms of numerous ecosystems. We used genome-resolved metagenomics and metatranscriptomics to highlight the vast phylogenetic and metabolic diversity of putative mercury methylators, and their depth-discrete activities in the environment. This work underscores the importance of using genome-resolved metagenomics to survey specific putative methylating populations of a given mercury-impacted ecosystem.

microbiology↗

bioRxiv2019

metabolisHMM: Phylogenomic analysis for exploration of microbial phylogenies and metabolic pathways

SummaryAdvances in high-throughput sequencing technologies and bioinformatic pipelines have exponentially increased the amount of data that can be obtained from uncultivated microbial lineages inhabiting diverse ecosystems. Various annotation tools and databases currently exist for predicting the functional potential of sequenced genomes or microbial communities based upon sequence identity. However, intuitive, reproducible, and user-friendly tools for further exploring and visualizing functional guilds of microbial community metagenomic sequencing datasets remains lacking. Here, we present metabolisHMM, a series of workflows for visualizing the distribution of curated and user-provided Hidden Markov Models (HMMs) to understand metabolic characteristics and evolutionary histories of microbial lineages. metabolisHMM performs functional annotations with a set of curated or user-defined HMMs to 1) construct ribosomal protein and single marker gene phylogenies, 2) summarize the presence/absence of metabolic pathway markers, and 3) create heatmap visualizations of presence/absence summaries. Availability and ImplementationmetabolisHMM is freely available on Github at https://github.com/elizabethmcd/metabolisHMM and on PyPi at https://pypi.org/project/metabolisHMM/ under the GNU General Public License v3.0.

bioinformatics↗

bioRxiv2019

VIBRANT: Automated recovery, annotation and curation of microbial viruses, and evaluation of virome function from genomic sequences

BackgroundViruses are central to microbial community structure in all environments. The ability to generate large metagenomic assemblies of mixed microbial and viral sequences provides the opportunity to tease apart complex microbiome dynamics, but these analyses are currently limited by the tools available for analyses of viral genomes and assessing their metabolic impacts on microbiomes. DesignHere we present VIBRANT, the first method to utilize a hybrid machine learning and protein similarity approach that is not reliant on sequence features for automated recovery and annotation of viruses, determination of genome quality and completeness, and characterization of virome function from metagenomic assemblies. VIBRANT uses neural networks of protein signatures and a novel v-score metric that circumvents traditional boundaries to maximize identification of lytic viral genomes and integrated proviruses, including highly diverse viruses. VIBRANT highlights viral auxiliary metabolic genes and metabolic pathways, thereby serving as a user-friendly platform for evaluating virome function. VIBRANT was trained and validated on reference virus datasets as well as microbiome and virome data. ResultsVIBRANT showed superior performance in recovering higher quality viruses and concurrently reduced the false identification of non-viral genome fragments in comparison to other virus identification programs, specifically VirSorter and VirFinder. When applied to 120,834 metagenomically derived viral sequences representing several human and natural environments, VIBRANT recovered an average of 94.5% of the viruses, whereas VirFinder and VirSorter achieved less powerful performance, averaging 48.1% and 56.0%, respectively. Similarly, VIBRANT identified more total viral sequence and proteins when applied to real metagenomes. When compared to PHASTER and Prophage Hunter for the ability to extract integrated provirus regions from host scaffolds, VIBRANT performed comparably and even identified proviruses that the other programs did not. To demonstrate applications of VIBRANT, we studied viromes associated with Crohns Disease to show that specific viral groups, namely Enterobacteriales-like viruses, as well as putative dysbiosis associated viral proteins are more abundant compared to healthy individuals, providing a possible viral link to maintenance of diseased states. ConclusionsThe ability to accurately recover viruses and explore viral impacts on microbial community metabolism will greatly advance our understanding of microbiomes, host-microbe interactions and ecosystem dynamics.

bioinformatics↗

bioRxiv2019

Depth-discrete eco-genomics of Lake Tanganyika reveals roles of diverse microbes, including candidate phyla, in tropical freshwater nutrient cycling

Lake Tanganyika (LT) is the largest tropical freshwater lake, and the largest body of anoxic freshwater on Earths surface. LTs mixed oxygenated surface waters float atop a permanently anoxic layer and host rich animal biodiversity. However, little is known about microorganisms inhabiting LTs 1470 m deep water column and their contributions to nutrient cycling, which affect ecosystem-level function and productivity. Here, we applied genome-resolved metagenomics and environmental analyses to link specific taxa to key biogeochemical processes across a vertical depth gradient in LT. We reconstructed 523 unique metagenome-assembled genomes (MAGs) from 21 bacterial and archaeal phyla, including many rarely observed in freshwater lakes. We identified sharp contrasts in community composition and metabolic potential with an abundance of typical freshwater taxa in oxygenated mixed upper layers, and Archaea and uncultured Candidate Phyla in deep anoxic waters. Genomic capacity for nitrogen and sulfur cycling was abundant in MAGs recovered from anoxic waters, highlighting microbial contributions to the productive surface layers via recycling of upwelled nutrients, and greenhouse gases such as nitrous oxide. Overall, our study provides a blueprint for incorporation of aquatic microbial genomics in the representation of tropical freshwater lakes, especially in the context of ongoing climate change which is predicted to bring increased stratification and anoxia to freshwater lakes.

microbiology↗

bioRxiv2019

Genome diversification in globally distributed novel marine Proteobacteria is linked to environmental adaptation

Proteobacteria constitute the most diverse and abundant group of microbes on Earth. In productive marine environments like deep-sea hydrothermal systems, Proteobacteria have been implicated in autotrophy coupled to sulfur, methane, and hydrogen oxidation, sulfate reduction, and denitrification. Beyond chemoautotrophy, little is known about the ecological significance of novel Proteobacteria that are globally distributed and active in hydrothermal systems. Here we apply multi-omics to characterize 51 metagenome-assembled genomes from three hydrothermal vent plumes in the Pacific and Atlantic Oceans that are affiliated with nine novel Proteobacteria lineages. Metabolic analyses revealed these organisms to contain a diverse functional repertoire including chemolithotrophic ability to utilize sulfur and C1 compounds, and chemoorganotrophic ability to utilize environment-derived fatty acids, aromatics, carbohydrates, and peptides. Comparative genomics with marine and terrestrial microbiomes suggests that lineage-associated functional traits could explain niche specificity. Our results shed light on the ecological functions and metabolic strategies of novel Proteobacteria in hydrothermal systems and beyond, and highlight the relationship between genome diversification and environmental adaptation.

microbiology↗

bioRxiv2019

Accurate and Complete Genomes from Metagenomes

Genomes are an integral component of the biological information about an organism and, logically, the more complete the genome, the more informative it is. Historically, bacterial and archaeal genomes were reconstructed from pure (monoclonal) cultures and the first reported sequences were manually curated to completion. However, the bottleneck imposed by the requirement for isolates precluded genomic insights for the vast majority of microbial life. Shotgun sequencing of microbial communities, referred to initially as community genomics and subsequently as genome-resolved metagenomics, can circumvent this limitation by obtaining metagenome-assembled genomes (MAGs), but gaps, local assembly errors, chimeras and contamination by fragments from other genomes limit the value of these genomes. Here, we discuss genome curation to improve and in some cases achieve complete (circularized, no gaps) MAGs (CMAGs). To date, few CMAGs have been generated, although notably some are from very complex systems such as soil and sediment. Through analysis of ~7000 published complete bacterial isolate genomes, we verify the value of cumulative GC skew in combination with other metrics to establish bacterial genome sequence accuracy. Interestingly, analysis of cumulative GC skew identified potential mis-assemblies in some reference genomes of isolated bacteria and the repeat sequences that likely gave rise to them. We discuss methods that could be implemented in bioinformatic approaches for curation to ensure that metabolic and evolutionary analyses can be based on very high-quality genomes.

microbiology↗

bioRxiv2019

METABOLIC: A scalable high-throughput metabolic and biogeochemical functional trait profiler based on microbial genomes

BackgroundAdvances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent, however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and contributions to biogeochemical cycling. ResultsWe present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, identification of metabolism markers, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the community, potential microbial metabolic handoffs and metabolite exchange, and calculation of microbial community contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or from single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, and community-scale metabolic networks using a newly defined metric MN-score (metabolic network score). METABOLIC takes [~]3 hours with 40 CPU threads to process [~]100 genomes and metagenomic reads within which the most compute-demanding part of hmmsearch takes [~]45 mins, while it takes [~]5 hours to complete hmmsearch for [~]3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut. ConclusionMETABOLIC enables consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available at https://github.com/AnantharamanLab/METABOLIC under GPLv3.

bioinformatics↗

bioRxiv2019

Clades of huge phage from across Earth’s ecosystems

Phage typically have small genomes and depend on their bacterial hosts for replication. DNA sequenced from many diverse ecosystems revealed hundreds of huge phage genomes, between 200 kbp and 716 kbp in length. Thirty-four genomes were manually curated to completion, including the largest phage genomes yet reported. Expanded genetic repertoires include diverse and new CRISPR-Cas systems, tRNAs, tRNA synthetases, tRNA modification enzymes, translation initiation and elongation factors, and ribosomal proteins. Phage CRISPR-Cas systems have the capacity to silence host transcription factors and translational genes, potentially as part of a larger interaction network that intercepts translation to redirect biosynthesis to phage-encoded functions. In addition, some phage may repurpose bacterial CRISPR-Cas systems to eliminate competing phage. We phylogenetically define major clades of huge phage from human and other animal microbiomes, oceans, lakes, sediments, soils and the built environment. We conclude that their large gene inventories reflect a conserved biological strategy, observed over a broad bacterial host range and across Earths ecosystems.

microbiology↗

bioRxiv2018

Processing of grassland soil C-N compounds into soluble and volatile molecules is depth stratified and mediated by genomically novel bacteria and archaea

Soil microbial activity drives the carbon and nitrogen cycles and is an important determinant of atmospheric trace gas turnover, yet most soils are dominated by organisms with unknown metabolic capacities. Even Acidobacteria, among the most abundant bacteria in soil, remain poorly characterized, and functions across groups such as Verrucomicrobia, Gemmatimonadetes, Chloroflexi, Rokubacteria are understudied. Here, we resolved sixty metagenomic, and twenty proteomic datasets from a grassland soil ecosystem and recovered 793 near-complete microbial genomes from 18 phyla, representing around one third of all organisms detected. Importantly, this enabled extensive genomics-based metabolic predictions for these understudied communities. Acidobacteria from multiple previously unstudied classes have genomes that encode large enzyme complements for complex carbohydrate degradation. Alternatively, most organisms we detected encode carbohydrate esterases that strip readily accessible methyl and acetyl groups from polymers like pectin and xylan, forming methanol and acetate, the availability of which could explain high prevalences of C1 metabolism and acetate utilization in genomes. Organism abundances among samples collected at three soil depths and under natural and amended rainfall regimes indicate statistically higher associations of inorganic nitrogen metabolism and carbon degradation in deep and shallow soils, respectively. This partitioning decreased in samples under extended spring rainfall indicating long term climate alteration can affect both carbon and nitrogen cycling. Overall, by leveraging natural and experimental gradients with genome-resolved metabolic profiles, we link organisms lacking prior genomic characterization to specific roles in complex carbon, C1, nitrate, and ammonia transformations and constrain factors that impact their distributions in soil.

microbiology↗

bioRxiv2018

Connections between freshwater carbon and nutrient cycles revealed through reconstructed population genomes

Metabolic processes at the microbial scale influence ecosystem functions because microbes are responsible for much of the carbon and nutrient cycling in freshwater. One approach to predict the metabolic capabilities of microbial communities is to search for functional marker genes in metagenomes. However, this approach does not provide context about co-occurrence with other metabolic traits within an organism or detailed taxonomy about those organisms. Here, we combine a functional marker gene analysis with metabolic pathway prediction of microbial population genomes (MAGs) assembled from metagenomic time series in eutrophic Lake Mendota and humic Trout Bog to identify how carbon and nutrient cycles are connected in freshwater. We found that phototrophy, carbon fixation, and nitrogen fixation pathways co-occurred in Cyanobacteria MAGs in Lake Mendota and in Chlorobiales MAGs in Trout Bog. Cyanobacteria MAGs also had strong temporal correlations to functional marker genes for nitrogen fixation in several years. Genes encoding steps in the nitrogen and sulfur cycles varied in abundance and taxonomy by lake, potentially reflecting the availability and composition of inorganic nutrients in these systems. We were also able to identify which populations contained the greatest density and diversity of genes encoding glycoside hydrolases. Populations with many glycoside hydrolases also encoded pathways for sugar degradation. By using both MAGs and marker genes, we were better able to link functions to specific taxonomic groups in our metagenomic time series, enabling a more detailed understanding of freshwater microbial carbon and nutrient cycling.

microbiology↗

bioRxiv2018

Megaphage infect Prevotella and variants are widespread in gut microbiomes

Bacteriophage (phage) dramatically shape microbial community composition, redistribute nutrients via host lysis, and drive evolution through horizontal gene transfer. Despite their importance, much remains to be learned about phage in the human microbiome. We investigated gut microbiomes of humans from Bangladesh and Tanzania, two African baboon social groups, and Danish pigs, and report that many contain phage belonging to a clade with genomes >540 kb in length, the largest yet reported in the human microbiome and close to the maximum size ever reported for phage. We refer to these as Lak phage. CRISPR spacer targeting indicates that the Lak phage infect bacteria of the genus Prevotella. We manually curated to completion 15 distinct Lak phage genomes recovered from metagenomes. The genomes display several interesting features, including use of an alternative genetic code, large intergenic regions that are highly expressed, and up to 35 putative tRNAs, some of which contain enigmatic introns. Different individuals have distinct phage genotypes, and shifts in variant frequencies over consecutive sampling days reflect changes in relative abundance of phage sub-populations. Recent homologous recombination has resulted in extensive genome admixture of nine baboon Lak phage populations. We infer that Lak phage are widespread in gut communities that contain Prevotella species, especially in individuals in the developing world, and conclude that megaphage, with fascinating and underexplored biology, may be common but largely overlooked components of human and animal gut microbiomes.

microbiology↗