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While numerous computational frameworks and workflows are available for recovering prokaryote and eukaryote genomes from metagenome data, only a limited number of pipelines are designed specifically for viromics analysis. With many viromics tools developed in the last few years alone, it can be challenging for scientists with limited bioinformatics experience to easily recover, evaluate quality, annotate genes, dereplicate, assign taxonomy, and calculate relative abundance and coverage of viral genomes using state-of-the-art methods and standards. Here, we describe Modular Viromics Pipeline (MVP) v.1.0, a user-friendly pipeline written in Python and providing a simple framework to perform standard viromics analyses. MVP combines multiple tools to enable viral genome identification, characterization of genome quality, filtering, clustering, taxonomic and functional annotation, genome binning, and comprehensive summaries of results that can be used for downstream ecological analyses. Overall, MVP provides a standardized and reproducible pipeline for both extensive and robust characterization of viruses from large-scale sequencing data including metagenomes, metatranscriptomes, viromes, and isolate genomes. As a typical use case, we show how the entire MVP pipeline can be applied to a set of 20 metagenomes from wetland sediments using only 10 modules executed via command lines, leading to the identification of 11,656 viral contigs and 8,145 viral operational taxonomic units (vOTUs) displaying a clear beta-diversity pattern. Further, acting as a dynamic wrapper, MVP is designed to continuously incorporate updates and integrate new tools, ensuring its ongoing relevance in the rapidly evolving field of viromics. MVP is available at https://gitlab.com/ccoclet/mvp and as versioned packages in PyPi and Conda.IMPORTANCEThe significance of our work lies in the development of Modular Viromics Pipeline (MVP), an integrated and user-friendly pipeline tailored exclusively for viromics analyses. MVP stands out due to its modular design, which ensures easy installation, execution, and integration of new tools and databases. By combining state-of-the-art tools such as geNomad and CheckV, MVP provides high-quality viral genome recovery and taxonomy and host assignment, and functional annotation, addressing the limitations of existing pipelines. MVP's ability to handle diverse sample types, including environmental, human microbiome, and plant-associated samples, makes it a versatile tool for the broader microbiome research community. By standardizing the analysis process and providing easily interpretable results, MVP enables researchers to perform comprehensive studies of viral communities, significantly advancing our understanding of viral ecology and its impact on various ecosystems.

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 .

Historically neglected by microbial ecologists, soil viruses are now thought to be critical to global biogeochemical cycles. However, our understanding of their global distribution, activities and interactions with the soil microbiome remains limited. Here we present the Global Soil Virus Atlas, a comprehensive dataset compiled from 2,953 previously sequenced soil metagenomes and composed of 616,935 uncultivated viral genomes and 38,508 unique viral operational taxonomic units. Rarefaction curves from the Global Soil Virus Atlas indicate that most soil viral diversity remains unexplored, further underscored by high spatial turnover and low rates of shared viral operational taxonomic units across samples. By examining genes associated with biogeochemical functions, we also demonstrate the viral potential to impact soil carbon and nutrient cycling. This study represents an extensive characterization of soil viral diversity and provides a foundation for developing testable hypotheses regarding the role of the virosphere in the soil microbiome and global biogeochemistry.

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.

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.

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 .

Petabases of environmental metagenomic data are publicly available, presenting an opportunity to characterize complex environments and discover novel lineages of life. Metagenome coassembly, in which many metagenomic samples from an environment are simultaneously analyzed to infer the underlying genomes' sequences, is an essential tool for achieving this goal. We applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 terabases (Tbp) of metagenome data from a tropical soil in the Luquillo Experimental Forest (LEF), Puerto Rico. The resulting coassembly yielded 39 high-quality (>90% complete,

The substrates of the Brazilian campos rupestres, a grassland ecosystem, have extremely low concentrations of phosphorus and nitrogen, imposing restrictions to plant growth. Despite that, this ecosystem harbors almost 15% of the Brazilian plant diversity, raising the question of how plants acquire nutrients in such a harsh environment. Here, we set out to uncover the taxonomic profile, the compositional and functional differences and similarities, and the nutrient turnover potential of microbial communities associated with two plant species of the campos rupestres-dominant family Velloziaceae that grow over distinct substrates (soil and rock). Using amplicon sequencing data, we show that, despite the pronounced composition differentiation, the plant-associated soil and rock communities share a core of highly efficient colonizers that tend to be highly abundant and is enriched in 21 bacterial families. Functional investigation of metagenomes and 522 metagenome-assembled genomes revealed that the microorganisms found associated to plant roots are enriched in genes involved in organic compound intake, and phosphorus and nitrogen turnover. We show that potential for phosphorus transport, mineralization, and solubilization are mostly found within bacterial families of the shared microbiome, such as Xanthobacteraceae and Bryobacteraceae. We also detected the full repertoire of nitrogen cycle-related genes and discovered a lineage of Isosphaeraceae that acquired nitrogen-fixing potential via horizontal gene transfer and might be also involved in nitrification via a metabolic handoff association with Binataceae. We highlight that plant-associated microbial populations in the campos rupestres harbor a genetic repertoire with potential to increase nutrient availability and that the microbiomes of biodiversity hotspots can reveal novel mechanisms of nutrient turnover.

Viroids and viroid-like covalently closed circular (ccc) RNAs are minimal replicators that typically encode no proteins and hijack cellular enzymes for replication. The extent and diversity of viroid-like agents are poorly understood. We developed a computational pipeline to identify viroid-like cccRNAs and applied it to 5,131 metatranscriptomes and 1,344 plant transcriptomes. The search yielded 11,378 viroid-like cccRNAs spanning 4,409 species-level clusters, a 5-fold increase compared to the previously identified viroid-like elements. Within this diverse collection, we discovered numerous putative viroids, satellite RNAs, retrozymes, and ribozy-like viruses. Diverse ribozyme combinations and unusual ribozymes within the cccRNAs were identified. Self-cleaving ribozymes were identified in ambiviruses, some mito-like viruses and capsid-encoding satellite virus-like cccRNAs. The broad presence of viroid-like cccRNAs in diverse transcriptomes and ecosystems implies that their host range is far broader than currently known, and matches to CRISPR spacers suggest that some cccRNAs replicate in prokaryotes.

Viruses are widely recognized as critical members of all microbiomes. Metagenomics enables large-scale exploration of the global virosphere, progressively revealing the extensive genomic diversity of viruses on Earth and highlighting the myriad of ways by which viruses impact biological processes. IMG/VR provides access to the largest collection of viral sequences obtained from (meta)genomes, along with functional annotation and rich metadata. A web interface enables users to efficiently browse and search viruses based on genome features and/or sequence similarity. Here, we present the fourth version of IMG/VR, composed of >15 million virus genomes and genome fragments, a ≈6-fold increase in size compared to the previous version. These clustered into 8.7 million viral operational taxonomic units, including 231 408 with at least one high-quality representative. Viral sequences in IMG/VR are now systematically identified from genomes, metagenomes, and metatranscriptomes using a new detection approach (geNomad), and IMG standard annotation are complemented with genome quality estimation using CheckV, taxonomic classification reflecting the latest taxonomic standards, and microbial host taxonomy prediction. IMG/VR v4 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.

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.

High-throughput RNA sequencing offers broad opportunities to explore the Earth RNA virome. Mining 5,150 diverse metatranscriptomes uncovered >2.5 million RNA virus contigs. Analysis of >330,000 RNA-dependent RNA polymerases (RdRPs) shows that this expansion corresponds to a 5-fold increase of the known RNA virus diversity. Gene content analysis revealed multiple protein domains previously not found in RNA viruses and implicated in virus-host interactions. Extended RdRP phylogeny supports the monophyly of the five established phyla and reveals two putative additional bacteriophage phyla and numerous putative additional classes and orders. The dramatically expanded phylum Lenarviricota, consisting of bacterial and related eukaryotic viruses, now accounts for a third of the RNA virome. Identification of CRISPR spacer matches and bacteriolytic proteins suggests that subsets of picobirnaviruses and partitiviruses, previously associated with eukaryotes, infect prokaryotic hosts.

Transcription Factor 4 (TCF4) has been associated with autism, schizophrenia, and other neuropsychiatric disorders. However, how pathological TCF4 mutations affect the human neural tissue is poorly understood. Here, we derive neural progenitor cells, neurons, and brain organoids from skin fibroblasts obtained from children with Pitt-Hopkins Syndrome carrying clinically relevant mutations in TCF4. We show that neural progenitors bearing these mutations have reduced proliferation and impaired capacity to differentiate into neurons. We identify a mechanism through which TCF4 loss-of-function leads to decreased Wnt signaling and then to diminished expression of SOX genes, culminating in reduced progenitor proliferation in vitro. Moreover, we show reduced cortical neuron content and impaired electrical activity in the patient-derived organoids, phenotypes that were rescued after correction of TCF4 expression or by pharmacological modulation of Wnt signaling. This work delineates pathological mechanisms in neural cells harboring TCF4 mutations and provides a potential target for therapeutic strategies for genetic disorders associated with this gene.

Millions of new viral sequences have been identified from metagenomes, but the quality and completeness of these sequences vary considerably. Here we present CheckV, an automated pipeline for identifying closed viral genomes, estimating the completeness of genome fragments and removing flanking host regions from integrated proviruses. CheckV estimates completeness by comparing sequences with a large database of complete viral genomes, including 76,262 identified from a systematic search of publicly available metagenomes, metatranscriptomes and metaviromes. After validation on mock datasets and comparison to existing methods, we applied CheckV to large and diverse collections of metagenome-assembled viral sequences, including IMG/VR and the Global Ocean Virome. This revealed 44,652 high-quality viral genomes (that is, >90% complete), although the vast majority of sequences were small fragments, which highlights the challenge of assembling viral genomes from short-read metagenomes. Additionally, we found that removal of host contamination substantially improved the accurate identification of auxiliary metabolic genes and interpretation of viral-encoded functions.

Over the last several years, metagenomics has enabled the assembly of millions of new viral sequences that have vastly expanded our knowledge of Earth’s viral diversity. However, these sequences range from small fragments to complete genomes and no tools currently exist for estimating their quality. To address this problem, we developed CheckV, which is an automated pipeline for estimating the completeness of viral genomes as well as the identification and removal of non-viral regions found on integrated proviruses. After validating the approach on mock datasets, CheckV was applied to large and diverse viral genome collections, including IMG/VR and the Global Ocean Virome, revealing that the majority of viral sequences were small fragments, with just 3.6% classified as high-quality (i.e. > 90% completeness) or complete genomes. Additionally, we found that removal of host contamination significantly improved identification of auxiliary metabolic genes and interpretation of viral-encoded functions. We expect CheckV will be broadly useful for all researchers studying and reporting viral genomes assembled from metagenomes. CheckV is freely available at: http://bitbucket.org/berkeleylab/CheckV .

The rocky, seasonally-dry and nutrient-impoverished soils of the Brazilian campos rupestres impose severe growth-limiting conditions on plants. Species of a dominant plant family, Velloziaceae, are highly specialized to low-nutrient conditions and seasonal water availability of this environment, where phosphorus (P) is the key limiting nutrient. Despite plant-microbe associations playing critical roles in stressful ecosystems, the contribution of these interactions in the campos rupestres remains poorly studied. Here we present the first microbiome data of Velloziaceae spp. thriving in contrasting substrates of campos rupestres. We assessed the microbiomes of Vellozia epidendroides, which occupies shallow patches of soil, and Barbacenia macrantha, growing on exposed rocks. The prokaryotic and fungal profiles were assessed by rRNA barcode sequencing of epiphytic and endophytic compartments of roots, stems, leaves and surrounding soil/rocks. We also generated root and substrate (rock/soil)-associated metagenomes of each plant species. We foresee that these data will contribute to decipher how the microbiome contributes to plant functioning in the campos rupestres, and to unravel new strategies for improved crop productivity in stressful environments.

Background: In patients with transthyretin cardiac amyloidosis (ATTR‐CA), renal dysfunction is a poor prognostic indicator. Limited data are available on variables that portend worsening renal function (wRF) among ATTR‐CA patients. Objectives: This study assesses which characteristics place patients at higher risk for the development of wRF (defined as a drop of ≥10% in glomerular filtration rate [GFR]) within the first year following diagnosis of ATTR‐CA. Methods: We included patients with ATTR‐CA (n = 134) evaluated between 2/2016 and 12/2022 and followed for up to 1 year at our amyloid clinic. Patients were stratified into two groups: a group with maintained renal function (mRF) and a group with wRF and compared using appropriate testing. Significant variables in the univariate analysis were included in the multivariable logistic regression model to determine characteristics associated with wRF. Results: Within a follow‐up period of 326 ± 118 days, the median GFR% change measured −6% [−18%, +8]. About 41.8% (n = 56) had wRF, while the remainder had mRF. In addition, in patients with no prior history of chronic kidney disease (CKD), 25.5% developed de novo CKD. On multivariable logistic regression, only New York Heart Association (NYHA) class ≥III (odds ratio [OR]: 3.9, 95% confidence interval [CI]: [1.6–9.3]), history of ischemic heart disease (IHD) (OR: 0.3, 95% CI: [0.1–0.7]), and not receiving SGLT‐2i (OR: 0.1, 95% CI: [0.02–0.5]) were significant predictors of wRF. Conclusion: Our study demonstrated that the development of de novo renal dysfunction or wRF is common following the diagnosis of ATTR‐CA. Additionally, we identified worse NYHA class and no prior history of IHD as significant predictors associated with developing wRF, while receiving SGLT‐2i therapy appeared to be protective in this population. [ABSTRACT FROM AUTHOR]