Biology subjects

Kyrpides, N.

Publications and source records attributed to Kyrpides, N..

15 recordsLinked to original sources

bioRxiv2026

Discovery of novel enzybiotic candidates targeting human bacterial pathogens through large-scale viral-host profiling

The rise of antibiotic-resistant bacteria demands alternative therapeutic strategies, with bacteriophage (phage) therapy and phage-derived enzybiotics emerging as promising approaches. However, identifying candidate phages against specific pathogens has historically been a bottleneck due to the need for cultivation methods to assess host range and lytic activity. Advances in metagenomic sequencing and the emergence of large-scale viral genome databases now provide an opportunity to accelerate this process computationally. Here, we present a large-scale mining of the MetaVR database to identify phages targeting human bacterial pathogens. By integrating direct host associations with CRISPR-spacer evidence, we linked 196,472 high-quality and complete viral genomes, representing 42,360 vOTUs, to 618 species of pathogenic and opportunistic bacteria. Functional enrichment analysis revealed distinct genomic signatures with viral lifestyle and host-range breadth: virulent phages were enriched in replication and structural functions, whereas temperate and broad host-range phages were enriched in anti-defense and regulatory modules. To characterize their lytic potential we annotated lysis-related protein families and their structural diversity, identifying 76 structurally novel lysis-associated proteins, including candidates targeting WHO priority pathogens. Focused analysis of endolysins revealed 592 structural clusters, with extensive sharing of endolysin repertoires among ESKAPE pathogens, suggesting candidates for broad-spectrum enzybiotic development. Selection analysis identified 167 endolysin families with sites under positive selection within functional domains, highlighting evolutionary diversification potentially associated with phage-host interactions. Together, our results establish a large-scale framework for connecting human bacterial pathogens to phages and their lytic machinery, providing a resource for prioritizing phage therapy and enzybiotic development.

bioinformatics↗

bioRxiv2026

ArthroVerse: mapping protein family diversity across arthropod-associated microbiomes

Metagenomic studies of arthropod-associated microbiomes have generated vast amounts of sequence data, yet the functional and structural organization of these proteins remains largely unexplored. Here, we present ArthroVerse, the first comprehensive database of protein families derived from arthropod-associated metagenomes. Non-redundant protein families were generated after rigorous filtering, deduplication, and clustering. The protein families were further annotated with microbial taxonomy, host associations, protein structural information, and Carbohydrate-active enzymes (CAZyme) predictions. The resulting dataset integrates both metagenomic and reference genome-derived proteins, enabling systematic exploration of functional diversity, evolutionary relationships, and host-microbe interactions in insect microbiomes. ArthroVerse provides a valuable resource for the study of microbial ecology and arthropod physiology, offering unprecedented insight into the protein landscape of insect-associated microbial communities.

bioinformatics↗

bioRxiv2026

WasteFams: A database of protein families from global wastewater microbiomes

Wastewater surveillance has emerged as a critical tool for global epidemiology, yet the functional diversity of wastewater microbiomes remains poorly characterized at the protein level. Here, we present WasteFams, the first comprehensive database dedicated to the systematic exploration of protein families in wastewater metagenomic and metatranscriptomic studies worldwide. Integrating data from 580 metagenomes, 132 metatranscriptomes, and 1,709 reference genomes, WasteFams catalogs 3,887 non-redundant protein families (containing {succeq}100 members) derived from over 105 million predicted proteins. Each protein family is enriched with multi-layered annotations, including AlphaFold3 structural predictions, taxonomic classifications, and biome-specific metadata. To further expand their functional annotation, we integrated deep genomic context analysis to link protein families to Mobile Genetic Elements (MGEs), Biosynthetic Gene Clusters (BGCs), Antibiotic Resistance Genes (ARGs), and CRISPR elements. Accessible through the EnvoFams portal, WasteFams provides a user-friendly interface featuring advanced search capabilities, sequence and structural similarity tools, and interactive visualization modules. As global initiatives increasingly leverage wastewater for public health and environmental insights, WasteFams can serve as a critical resource for discovering novel microbial functions, monitoring resistance mechanisms, and exploring the biotechnological potential of secondary metabolites within wastewater-engineered ecosystems.

bioinformatics↗

bioRxiv2026

VPF-Class 2.0: a taxonomy-centered framework for automatic viral classification

Rapid expansion of viral sequence data demands classifiers that scale, track ICTV updates, and provide interpretable evidence. We present VPF-Class 2.0, an updated successor to VPF-Class, centred on the taxonomic classification, that retains marker-driven protein domain detection but replaces rule-based voting with a lightweight supervised model on per-genome marker-composition features. In controlled benchmarks, VPF-Class 2.0 achieves near-perfect family-level performance and strong genus-level accuracy while increasing confident annotation coverage. Under a practical confidence threshold (0.3), performance improves and matches or exceeds representative tools within shared taxonomic scopes. We further introduce an interpretability study that relates errors to the genus specificity of activated markers. Finally, we demonstrate applicability on large real-world viromes with consistent labels and substantial agreement with graph-based classifications. The implementation of VPF-Class 2.0 can be downloaded from https://github.com/luisvidalj/VPFClass2.git.

bioinformatics↗

bioRxiv2025

Quadrupling the protein family space with global metagenomics

The known universe of protein families represents only a small fraction of natures molecular diversity. From 40.3 billion sequences across 40,446 metagenomes, 9,540 metatranscriptomes, and 539 million proteins from 167,415 reference genomes, we identified 608,258 previously uncharacterized protein families with [≥]100 members and 6.5 million families with [≥]25 members, none matching known Pfam domains or reference proteins. This effort doubles the known repertoire of large families and quadruples that of smaller families. Integration of AlphaFold2-based structural predictions with gene-neighborhood and taxonomic analyses enables the characterization of previously unannotated proteins, revealing candidates for both novel and known biological functions in understudied microbial lineages and biomes. This expanded repertoire provides insights into microbial adaptation and broadens the molecular toolkit available for biotechnology, highlighting the power of global metagenomics to uncover hidden protein diversity.

bioinformatics↗

bioRxiv2025

nf-core/proteinfamilies: A scalable pipeline for the generation of protein families

The growth of metagenomics-derived amino acid sequence data has transformed our understanding of protein function, microbial diversity and evolutionary relationships. However, the vast majority of these proteins remain functionally uncharacterized. Grouping the millions of such uncharacterised sequences with the few experimentally characterised ones allows the transfer of annotations, while the inspection of conserved residues with multiple sequence alignments can provide clues to function, even in the absence of existing functional information. To address the challenges associated with this data surge and the need to group sequences, we present a scalable, open-source, parametrizable Nextflow pipeline (nf-core/proteinfamilies) that generates protein nascent families or assigns new proteins to existing families. The computational benchmarks demonstrated that resource usage can scale approximately linearly with input size, while the biological benchmarks showed that the generated protein families closely resemble manually curated families found in widely used databases.

bioinformatics↗

bioRxiv2025

A genomic catalog of Earth's bacterial and archaeal symbionts

1Microbial symbiosis drives the functional and phylogenomic diversification of life on Earth, yet remains underexplored due to culturing challenges. This study employed machine learning (ML) to predict symbiotic lifestyles in hundreds of thousands of microbial genomes from diverse environmental metagenome samples and reference genomes. Predictions were performed using symclatron, a novel ML framework developed here to identify genomic signatures of symbionts. Predictions were deposited in a novel Symbiont Genomes catalog (SymGs). The results indicated that 15-23% of uncultivated microbes likely engage in symbiotic relationships with other organisms and are present in half of all known bacterial and archaeal phyla. We also identified genomic signatures of symbiotic lifestyles, including the loss of certain metabolic functions and the differential presence of others that may enable host-dependent living. The symclatron software and the SymGs catalog represent valuable resources for studying symbioses, facilitating future mechanistic investigations of host-microbe associations.

genomics↗

bioRxiv2025

metagRoot: A comprehensive database of protein families associated with plant root microbiomes

The plant root microbiome is vital in plant health, nutrient uptake, and environmental resilience. To explore and harness this diversity, we present metagRoot, a specialized and enriched database focused on the protein families of the plant root microbiome. MetagRoot integrates metagenomic, metatranscriptomic, and reference genome-derived protein data to characterize 71,091 enriched protein families, each containing at least 100 sequences. These families are annotated with multiple sequence alignments, CRISPR elements, Hidden Markov Models, taxonomic and functional classifications, ecosystem and geolocation metadata, and predicted 3D structures using AlphaFold2. MetagRoot is a powerful tool for decoding the molecular landscape of root-associated microbial communities and advancing microbiome-informed agricultural practices by enriching protein family information with ecological and structural context. The database is available at https://pavlopoulos-lab.org/metagroot/ or https://www.metagroot.org

bioinformatics↗

bioRxiv2023

Global Biogeography of the Soil Virosphere

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 (GSV) Atlas, a comprehensive dataset compiled from 2,953 previously sequenced soil metagenomes and comprised of 616,935 uncultivated viral genomes (UViGs) and 38,508 unique viral operational taxonomic units (vOTUs). Rarefaction curves from the GSV Atlas indicate that most soil viral diversity remains unexplored, further underscored by high spatial turnover and low rates of shared vOTUs 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.

ecology↗

bioRxiv2022

A vast world of viroid-like circular RNAs revealed by mining metatranscriptomes

Viroids and viroid-like agents are unique, minimal RNA replicators that typically encode no proteins and hijack cellular enzymes for their genome replication. As the extent and diversity of viroid-like agents are poorly understood, we developed a computational pipeline to identify viroid-like covalently closed circular (ccc) RNAs and applied it to 5,131 global metatranscriptomes and 1,344 plant transcriptomes. The search resulted in 11,420 viroid-like, ribozyme-containing cccRNAs spanning 4,409 species-level clusters, which is a five-fold increase compared to the previously known set of viroids and viroid-like RNA agents. Within this diverse collection, we identified numerous putative novel viroids, satellite RNAs, retrozymes, and ribozylike viruses. We also found previously unknown ribozyme combinations and unusual ribozymes within the cccRNAs. Self-cleaving ribozymes were identified in both RNA strands of ambiviruses and some mito-like viruses as well as in capsid-encoding satellite virus-like cccRNAs. The broad presence of viroid-like cccRNAs in diverse transcriptomes and ecosystems implies that their host range is not limited to plants, and matches between viroid-like cccRNAs and CRISPR spacers suggest that some of them might replicate in prokaryotes.

microbiology↗

bioRxiv2020

The DOE JGI Metagenome Workflow

The DOE JGI Metagenome Workflow performs metagenome data processing, including assembly, structural, functional, and taxonomic annotation, and binning of metagenomic datasets that are subsequently included into the Integrated Microbial Genomes and Microbiomes (IMG/M) comparative analysis system (I. Chen, K. Chu, K. Palaniappan, M. Pillay, A. Ratner, J. Huang, M. Huntemann, N. Varghese, J. White, R. Seshadri, et al, Nucleic Acids Rsearch, 2019) and provided for download via the Joint Genome Institute (JGI) Data Portal (https://genome.jgi.doe.gov/portal/). This workflow scales to run on thousands of metagenome samples per year, which can vary by the complexity of microbial communities and sequencing depth. Here we describe the different tools, databases, and parameters used at different steps of the workflow, to help with interpretation of metagenome data available in IMG and to enable researchers to apply this workflow to their own data. We use 20 publicly available sediment metagenomes to illustrate the computing requirements for the different steps and highlight the typical results of data processing. The workflow modules for read filtering and metagenome assembly are available as a Workflow Description Language (WDL) file (https://code.jgi.doe.gov/BFoster/jgi_meta_wdl.git). The workflow modules for annotation and binning are provided as a service to the user community at https://img.jgi.doe.gov/submit and require filling out the project and associated metadata descriptions in Genomes OnLine Database (GOLD) (S. Mukherjee, D. Stamatis, J. Bertsch, G. Ovchinnikova, H. Katta, A. Mojica, I Chen, and N. Kyrpides, and T. Reddy, Nucleic Acids Research, 2018). IMPORTANCEThe DOE JGI Metagenome Workflow is designed for processing metagenomic datasets starting from Illumina fastq files. It performs data pre-processing, error correction, assembly, structural and functional annotation, and binning. The results of processing are provided in several standard formats, such as fasta and gff and can be used for subsequent integration into the Integrated Microbial Genome (IMG) system where they can be compared to a comprehensive set of publicly available metagenomes. As of 7/30/2020 7,155 JGI metagenomes have been processed by the JGI Metagenome Workflow.

bioinformatics↗

bioRxiv2020

CheckV: assessing the quality of metagenome-assembled viral genomes

Over the last several years, metagenomics has enabled the assembly of millions of new viral sequences that have vastly expanded our knowledge of Earths 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.

bioinformatics↗

bioRxiv2019

Impact of soil salinity on the cowpea nodule-microbiome and the isolation of halotolerant PGPR strains to promote plant growth under salinity stress

Four soil samples (SS-1--SS-4) isolated from semi-arid soils in Punjab, Pakistan were used as inocula for cowpea (Vigna unguiculata L.) grown under salinity stress to analyze the composition of bacteria in the rhizosphere and within nodules through cultivation-dependent and cultivation-independent methods. Two cowpea varieties, 603 and the salt-tolerant CB 46, were each inoculated with four different native soil samples, and data showed that plants inoculated with soil samples SS-2 and SS-4 grew better than plants inoculated with soil samples SS-1 and SS-3. Bacteria were isolated from both soils and nodules, and 34 of the 51 original isolates tested positive for PGPR traits in plate assays with many exhibiting multiple plant growth-promoting properties. A number of isolates were positive for all PGPR traits tested. For the microbiome studies, environmental DNA (eDNA) was isolated from SS-1 and SS-4, which represented the extremes of the Pakistan soils to which the plants responded, and by 16S rRNA gene sequencing analysis were found to consist mainly of Actinobacteria, Firmicutes, and Proteobacteria. However, sequencing analysis of eDNA isolated from cowpea nodules established by the trap plants grown in the four Pakistan soils indicated that the nodule microbiome consisted almost exclusively of Proteobacterial sequences, particularly Bradyrhizobium. Yet, many other bacteria including Rhizobium, Mesorhizobium, Pseudomonas, as well as Paenibacillus, Bacillus as well as non-proteobacterial genera were isolated from the nodules of soil-inoculated cowpea plants. This discrepancy between the bacteria isolated from cowpea nodules (Proteobacteria and non-Proteobacteria) versus those detected in the nodule microbiome (Proteobacteria) needs further study.

plant biology↗

bioRxiv2019

Cryptic inoviruses are pervasive in bacteria and archaea across Earth's biomes

Bacteriophages from the Inoviridae family (inoviruses) are characterized by their unique morphology, genome content, and infection cycle. To date, a relatively small number of inovirus isolates have been extensively studied, either for biotechnological applications such as phage display, or because of their impact on the toxicity of known bacterial pathogens including Vibrio cholerae and Neisseria meningitidis. Here we show that the current 56 members of the Inoviridae family represent a minute fraction of a highly diverse group of inoviruses. Using a new machine learning approach leveraging a combination of marker gene and genome features, we identified 10,295 inovirus-like genomes from microbial genomes and metagenomes. Collectively, these represent six distinct proposed inovirus families infecting nearly all bacterial phyla across virtually every ecosystem. Putative inoviruses were also detected in several archaeal genomes, suggesting that these viruses may have occasionally transferred from bacterial to archaeal hosts. Finally, we identified an expansive diversity of inovirus-encoded toxin-antitoxin and gene expression modulation systems, alongside evidence of both synergistic (CRISPR evasion) and antagonistic (superinfection exclusion) interactions with co-infecting viruses which we experimentally validated in a Pseudomonas model. Capturing this previously obscured component of the global virosphere sparks new avenues for microbial manipulation approaches and innovative biotechnological applications.

microbiology↗

bioRxiv2018

Large-scale analyses of human microbiomes reveal thousands of small, novel genes and their predicted functions

Small proteins likely abound in prokaryotes, and may mediate much of the communication that occurs between organisms within a microbiome and their host. Unfortunately, small proteins are traditionally overlooked in biology, in part due to the computational and experimental difficulties in detecting them. To systematically identify novel small proteins, we carried out a large comparative genomics study on 1,773 HMP human-associated metagenomes from four different body sites (mouth, gut, skin and vagina). We describe more than four thousand conserved protein families, the majority of which are novel; ~30% of these protein families are predicted to be secreted or transmembrane. Over 90% of the small protein families have no known domain, and almost half are not represented in reference genomes, emphasizing the incompleteness of knowledge in this space. Our analysis exposes putative novel housekeeping small protein families, including a potential novel ribosomally associated protein, as well as mammalian-specific or human-specific protein families. By analyzing the genomic neighborhood of small genes, we pinpoint a subset of families that are potentially associated with defense against bacteriophage. Finally, we identify families that may be subject to horizontal transfer and are thus potentially involved in adaptation of bacteria to the changing human environment. Our study suggest that small proteins are highly abundant and that those of the human microbiome, in particular, may perform diverse functions that have not been previously reported.

microbiology↗