Phylogenomics and genetic analysis of solvent-producing Clostridium species.

The genus Clostridium is a large and diverse group within the Bacillota (formerly Firmicutes), whose members can encode useful complex traits such as solvent production, gas-fermentation, and lignocellulose breakdown. We describe 270 genome sequences of solventogenic clostridia from a comprehensive industrial strain collection assembled by Professor David Jones that includes 194 C. beijerinckii, 57 C. saccharobutylicum, 4 C. saccharoperbutylacetonicum, 5 C. butyricum, 7 C. acetobutylicum, and 3 C. tetanomorphum genomes. We report methods, analyses and characterization for phylogeny, key attributes, core biosynthetic genes, secondary metabolites, plasmids, prophage/CRISPR diversity, cellulosomes and quorum sensing for the 6 species. The expanded genomic data described here will facilitate engineering of solvent-producing clostridia as well as non-model microorganisms with innately desirable traits. Sequences could be applied in conventional platform biocatalysts such as yeast or Escherichia coli for enhanced chemical production. Recently, gene sequences from this collection were used to engineer Clostridium autoethanogenum, a gas-fermenting autotrophic acetogen, for continuous acetone or isopropanol production, as well as butanol, butanoic acid, hexanol and hexanoic acid production.

Whole community shotgun metagenomes of two biological soil crust types from the Mojave Desert.

We present six whole community shotgun metagenomic sequencing data sets of two types of biological soil crusts sampled at the ecotone of the Mojave Desert and Colorado Desert in California. These data will help us understand the diversity and function of biocrust microbial communities, which are essential for desert ecosystems.

Metatranscriptomes of two biological soil crust types from the Mojave desert in response to wetting.

We present eight metatranscriptomic datasets of light algal and cyanolichen biological soil crusts from the Mojave Desert in response to wetting. These data will help us understand gene expression patterns in desert biocrust microbial communities after they have been reactivated by the addition of water.

IMG/PR: a database of plasmids from genomes and metagenomes with rich annotations and metadata.

Plasmids are mobile genetic elements found in many clades of Archaea and Bacteria. They drive horizontal gene transfer, impacting ecological and evolutionary processes within microbial communities, and hold substantial importance in human health and biotechnology. To support plasmid research and provide scientists with data of an unprecedented diversity of plasmid sequences, we introduce the IMG/PR database, a new resource encompassing 699 973 plasmid sequences derived from genomes, metagenomes and metatranscriptomes. IMG/PR is the first database to provide data of plasmid that were systematically identified from diverse microbiome samples. IMG/PR plasmids are associated with rich metadata that includes geographical and ecosystem information, host taxonomy, similarity to other plasmids, functional annotation, presence of genes involved in conjugation and antibiotic resistance. The database offers diverse methods for exploring its extensive plasmid collection, enabling users to navigate plasmids through metadata-centric queries, plasmid comparisons and BLAST searches. The web interface for IMG/PR is accessible at https://img.jgi.doe.gov/pr. Plasmid metadata and sequences can be downloaded from https://genome.jgi.doe.gov/portal/IMG_PR.

Astrovirology: how viruses enhance our understanding of life in the Universe.

Viruses are the most numerically abundant biological entities on Earth. As ubiquitous replicators of molecular information and agents of community change, viruses have potent effects on the life on Earth, and may play a critical role in human spaceflight, for life-detection missions to other planetary bodies and planetary protection. However, major knowledge gaps constrain our understanding of the Earth's virosphere: (1) the role viruses play in biogeochemical cycles, (2) the origin(s) of viruses and (3) the involvement of viruses in the evolution, distribution and persistence of life. As viruses are the only replicators that span all known types of nucleic acids, an expanded experimental and theoretical toolbox built for Earth's viruses will be pivotal for detecting and understanding life on Earth and beyond. Only by filling in these knowledge and technical gaps we will obtain an inclusive assessment of how to distinguish and detect life on other planetary surfaces. Meanwhile, space exploration requires life-support systems for the needs of humans, plants and their microbial inhabitants. Viral effects on microbes and plants are essential for Earth's biosphere and human health, but virus-host interactions in spaceflight are poorly understood. Viral relationships with their hosts respond to environmental changes in complex ways which are difficult to predict by extrapolating from Earth-based proxies. These relationships should be studied in space to fully understand how spaceflight will modulate viral impacts on human health and life-support systems, including microbiomes. In this review, we address key questions that must be examined to incorporate viruses into Earth system models, life-support systems and life detection. Tackling these questions will benefit our efforts to develop planetary protection protocols and further our understanding of viruses in astrobiology.

Virus diversity and activity is driven by snowmelt and host dynamics in a high-altitude watershed soil ecosystem.

BACKGROUND: Viruses impact nearly all organisms on Earth, including microbial communities and their associated biogeochemical processes. In soils, highly diverse viral communities have been identified, with a global distribution seemingly driven by multiple biotic and abiotic factors, especially soil temperature and moisture. However, our current understanding of the stability of soil viral communities across time and their response to strong seasonal changes in environmental parameters remains limited. Here, we investigated the diversity and activity of environmental soil DNA and RNA viruses, focusing especially on bacteriophages, across dynamics' seasonal changes in a snow-dominated mountainous watershed by examining paired metagenomes and metatranscriptomes. RESULTS: We identified a large number of DNA and RNA viruses taxonomically divergent from existing environmental viruses, including a significant proportion of fungal RNA viruses, and a large and unsuspected diversity of positive single-stranded RNA phages (Leviviricetes), highlighting the under-characterization of the global soil virosphere. Among these, we were able to distinguish subsets of active DNA and RNA phages that changed across seasons, consistent with a "seed-bank" viral community structure in which new phage activity, for example, replication and host lysis, is sequentially triggered by changes in environmental conditions. At the population level, we further identified virus-host dynamics matching two existing ecological models: "Kill-The-Winner" which proposes that lytic phages are actively infecting abundant bacteria, and "Piggyback-The-Persistent" which argues that when the host is growing slowly, it is more beneficial to remain in a dormant state. The former was associated with summer months of high and rapid microbial activity, and the latter with winter months of limited and slow host growth. CONCLUSION: Taken together, these results suggest that the high diversity of viruses in soils is likely associated with a broad range of host interaction types each adapted to specific host ecological strategies and environmental conditions. As our understanding of how environmental and host factors drive viral activity in soil ecosystems progresses, integrating these viral impacts in complex natural microbiome models will be key to accurately predict ecosystem biogeochemistry. Video Abstract.

Unraveling the functional dark matter through global metagenomics.

Metagenomes encode an enormous diversity of proteins, reflecting a multiplicity of functions and activities1,2. Exploration of this vast sequence space has been limited to a comparative analysis against reference microbial genomes and protein families derived from those genomes. Here, to examine the scale of yet untapped functional diversity beyond what is currently possible through the lens of reference genomes, we develop a computational approach to generate reference-free protein families from the sequence space in metagenomes. We analyse 26,931 metagenomes and identify 1.17 billion protein sequences longer than 35 amino acids with no similarity to any sequences from 102,491 reference genomes or the Pfam database3. Using massively parallel graph-based clustering, we group these proteins into 106,198 novel sequence clusters with more than 100 members, doubling the number of protein families obtained from the reference genomes clustered using the same approach. We annotate these families on the basis of their taxonomic, habitat, geographical and gene neighbourhood distributions and, where sufficient sequence diversity is available, predict protein three-dimensional models, revealing novel structures. Overall, our results uncover an enormously diverse functional space, highlighting the importance of further exploring the microbial functional dark matter.

Solvent-Producing Clostridia Revisited.

The review provides an overview of the current status of the solvent-producing clostridia. The origin and development of industrial clostridial species, as well as the history of the industrial Acetone Butanol Ethanol fermentation process, is reexamined, and the recent resurgence of interest in the production of biobutanol is reviewed. Over 300 fully sequenced genomes for solvent-producing and closely related clostridial species are currently available in public databases. These include 270 genomes sourced from the David Jones culture collection. These genomes were allocated arbitrary DJ codes, and a conversion table to identify the species and strains has now been provided. The expanded genomic database facilitated new comparative genomic and phylogenetic analysis. A synopsis of the common features, molecular taxonomy, and phylogeny of solvent-producing clostridia and the application of comparative phylogenomics are evaluated. A survey and analysis of resident prophages in solvent-producing clostridia are discussed, and the discovery, occurrence, and role of novel R-type tailocins are reported. Prophage genomes with R-type tailocin-like features were detected in all 12 species investigated. The widespread occurrence of tailocins in Gram-negative species is well documented; this survey has indicated that they may also be widespread in clostridia.

Identification of mobile genetic elements with geNomad.

Identifying and characterizing mobile genetic elements in sequencing data is essential for understanding their diversity, ecology, biotechnological applications and impact on public health. Here we introduce geNomad, a classification and annotation framework that combines information from gene content and a deep neural network to identify sequences of plasmids and viruses. geNomad uses a dataset of more than 200,000 marker protein profiles to provide functional gene annotation and taxonomic assignment of viral genomes. Using a conditional random field model, geNomad also detects proviruses integrated into host genomes with high precision. In benchmarks, geNomad achieved high classification performance for diverse plasmids and viruses (Matthews correlation coefficient of 77.8% and 95.3%, respectively), substantially outperforming other tools. Leveraging geNomad's speed and scalability, we processed over 2.7 trillion base pairs of sequencing data, leading to the discovery of millions of viruses and plasmids that are available through the IMG/VR and IMG/PR databases. geNomad is available at https://portal.nersc.gov/genomad .

MArVD2: a machine learning enhanced tool to discriminate between archaeal and bacterial viruses in viral datasets.

Our knowledge of viral sequence space has exploded with advancing sequencing technologies and large-scale sampling and analytical efforts. Though archaea are important and abundant prokaryotes in many systems, our knowledge of archaeal viruses outside of extreme environments is limited. This largely stems from the lack of a robust, high-throughput, and systematic way to distinguish between bacterial and archaeal viruses in datasets of curated viruses. Here we upgrade our prior text-based tool (MArVD) via training and testing a random forest machine learning algorithm against a newly curated dataset of archaeal viruses. After optimization, MArVD2 presented a significant improvement over its predecessor in terms of scalability, usability, and flexibility, and will allow user-defined custom training datasets as archaeal virus discovery progresses. Benchmarking showed that a model trained with viral sequences from the hypersaline, marine, and hot spring environments correctly classified 85% of the archaeal viruses with a false detection rate below 2% using a random forest prediction threshold of 80% in a separate benchmarking dataset from the same habitats.

Long-term CRISPR locus dynamics and stable host-virus co-existence in subsurface fractured shales.

Viruses are the most ubiquitous biological entities on Earth. Even so, elucidating the impact of viruses on microbial communities and associated ecosystem processes often requires identification of unambiguous host-virus linkages-an undeniable challenge in many ecosystems. Subsurface fractured shales present a unique opportunity to first make these strong linkages via spacers in CRISPR-Cas arrays and subsequently reveal complex long-term host-virus dynamics. Here, we sampled two replicated sets of fractured shale wells for nearly 800 days, resulting in 78 metagenomes from temporal sampling of six wells in the Denver-Julesburg Basin (Colorado, USA). At the community level, there was strong evidence for CRISPR-Cas defense systems being used through time and likely in response to viral interactions. Within our host genomes, represented by 202 unique MAGs, we also saw that CRISPR-Cas systems were widely encoded. Together, spacers from host CRISPR loci facilitated 2,110 CRISPR-based viral linkages across 90 host MAGs spanning 25 phyla. We observed less redundancy in host-viral linkages and fewer spacers associated with hosts from the older, more established wells, possibly reflecting enrichment of more beneficial spacers through time. Leveraging temporal patterns of host-virus linkages across differing well ages, we report how host-virus co-existence dynamics develop and converge through time, possibly reflecting selection for viruses that can evade host CRISPR-Cas systems. Together, our findings shed light on the complexities of host-virus interactions as well as long-term dynamics of CRISPR-Cas defense among diverse microbial populations.

A functional microbiome catalog crowdsourced from North American rivers.

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. Specifically, GROWdb encompasses 1,469 microbial species from 27 phyla, including novel lineages from 10 families and 128 genera, and defines the core river microbiome for the first time at genome level. GROWdb analyses coupled to extensive geospatial information revealed local and regional drivers of microbial community structuring, while also presenting a myriad of foundational hypotheses about ecosystem function. Building upon the previously conceived River Continuum Concept 1 , we layer on microbial functional trait expression, which suggests the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures 2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.

A standardized quantitative analysis strategy for stable isotope probing metagenomics.

Stable isotope probing (SIP) facilitates culture-independent identification of active microbial populations within complex ecosystems through isotopic enrichment of nucleic acids. Many DNA-SIP studies rely on 16S rRNA gene sequences to identify active taxa, but connecting these sequences to specific bacterial genomes is often challenging. Here, we describe a standardized laboratory and analysis framework to quantify isotopic enrichment on a per-genome basis using shotgun metagenomics instead of 16S rRNA gene sequencing. To develop this framework, we explored various sample processing and analysis approaches using a designed microbiome where the identity of labeled genomes and their level of isotopic enrichment were experimentally controlled. With this ground truth dataset, we empirically assessed the accuracy of different analytical models for identifying active taxa and examined how sequencing depth impacts the detection of isotopically labeled genomes. We also demonstrate that using synthetic DNA internal standards to measure absolute genome abundances in SIP density fractions improves estimates of isotopic enrichment. In addition, our study illustrates the utility of internal standards to reveal anomalies in sample handling that could negatively impact SIP metagenomic analyses if left undetected. Finally, we present SIPmg, an R package to facilitate the estimation of absolute abundances and perform statistical analyses for identifying labeled genomes within SIP metagenomic data. This experimentally validated analysis framework strengthens the foundation of DNA-SIP metagenomics as a tool for accurately measuring the in situ activity of environmental microbial populations and assessing their genomic potential. IMPORTANCE Answering the questions, "who is eating what?" and "who is active?" within complex microbial communities is paramount for our ability to model, predict, and modulate microbiomes for improved human and planetary health. These questions can be pursued using stable isotope probing to track the incorporation of labeled compounds into cellular DNA during microbial growth. However, with traditional stable isotope methods, it is challenging to establish links between an active microorganism's taxonomic identity and genome composition while providing quantitative estimates of the microorganism's isotope incorporation rate. Here, we report an experimental and analytical workflow that lays the foundation for improved detection of metabolically active microorganisms and better quantitative estimates of genome-resolved isotope incorporation, which can be used to further refine ecosystem-scale models for carbon and nutrient fluxes within microbiomes.

Highly diverse and unknown viruses may enhance Antarctic endoliths' adaptability.

BACKGROUND: Rock-dwelling microorganisms are key players in ecosystem functioning of Antarctic ice free-areas. Yet, little is known about their diversity and ecology, and further still, viruses in these communities have been largely unexplored despite important roles related to host metabolism and nutrient cycling. To begin to address this, we present a large-scale viral catalog from Antarctic rock microbial communities. RESULTS: We performed metagenomic analyses on rocks from across Antarctica representing a broad range of environmental and spatial conditions, and which resulted in a predicted viral catalog comprising > 75,000 viral operational taxonomic units (vOTUS). We found largely undescribed, highly diverse and spatially structured virus communities which had predicted auxiliary metabolic genes (AMGs) with functions indicating that they may be potentially influencing bacterial adaptation and biogeochemistry. CONCLUSION: This catalog lays the foundation for expanding knowledge of virosphere diversity, function, spatial ecology, and dynamics in extreme environments. This work serves as a step towards exploring adaptability of microbial communities in the face of a changing climate. Video Abstract.

iPHoP: An integrated machine learning framework to maximize host prediction for metagenome-derived viruses of archaea and bacteria.

The extraordinary diversity of viruses infecting bacteria and archaea is now primarily studied through metagenomics. While metagenomes enable high-throughput exploration of the viral sequence space, metagenome-derived sequences lack key information compared to isolated viruses, in particular host association. Different computational approaches are available to predict the host(s) of uncultivated viruses based on their genome sequences, but thus far individual approaches are limited either in precision or in recall, i.e., for a number of viruses they yield erroneous predictions or no prediction at all. Here, we describe iPHoP, a two-step framework that integrates multiple methods to reliably predict host taxonomy at the genus rank for a broad range of viruses infecting bacteria and archaea, while retaining a low false discovery rate. Based on a large dataset of metagenome-derived virus genomes from the IMG/VR database, we illustrate how iPHoP can provide extensive host prediction and guide further characterization of uncultivated viruses.

Viruses interact with hosts that span distantly related microbial domains in dense hydrothermal mats.

Many microbes in nature reside in dense, metabolically interdependent communities. We investigated the nature and extent of microbe-virus interactions in relation to microbial density and syntrophy by examining microbe-virus interactions in a biomass dense, deep-sea hydrothermal mat. Using metagenomic sequencing, we find numerous instances where phylogenetically distant (up to domain level) microbes encode CRISPR-based immunity against the same viruses in the mat. Evidence of viral interactions with hosts cross-cutting microbial domains is particularly striking between known syntrophic partners, for example those engaged in anaerobic methanotrophy. These patterns are corroborated by proximity-ligation-based (Hi-C) inference. Surveys of public datasets reveal additional viruses interacting with hosts across domains in diverse ecosystems known to harbour syntrophic biofilms. We propose that the entry of viral particles and/or DNA to non-primary host cells may be a common phenomenon in densely populated ecosystems, with eco-evolutionary implications for syntrophic microbes and CRISPR-mediated inter-population augmentation of resilience against viruses.

Dataset of 143 metagenome-assembled genomes from the Arctic and Atlantic Oceans, including 21 for eukaryotic organisms.

This article presents metagenome-assembled genomes (MAGs) for both eukaryotic and prokaryotic organisms originating from the Arctic and Atlantic oceans, along with gene prediction and functional annotation for MAGs from both domains. Eleven samples from the chlorophyll-a maximum layer of the surface ocean were collected during two cruises in 2012; six from the Arctic in June-July on ARK-XXVII/1 (PS80), and five from the Atlantic in November on ANT-XXIX/1 (PS81). Sequencing and assembly was carried out by the Joint Genome Institute (JGI), who provide annotation of the assembled sequences, and 122 MAGs for prokaryotic organisms. A subsequent binning process identified 21 MAGs for eukaryotic organisms, mostly identified as Mamiellophyceae or Bacillariophyceae. The data for each MAG includes sequences in FASTA format, and tables of functional annotation of genes. For eukaryotic MAGs, transcript and protein sequences for predicted genes are available. A spreadsheet is provided summarising quality measures and taxonomic classifications for each MAG. These data provide draft genomes for uncultured marine microbes, including some of the first MAGs for polar eukaryotes, and can provide reference genetic data for these environments, or used in genomics-based comparison between environments.