Computational function prediction of bacteria and phage proteins.

SUMMARYUnderstanding protein functions is crucial for interpreting microbial life; however, reliable function annotation remains a major challenge in computational biology. Despite significant advances in bioinformatics methods, ~30% of all bacterial and ~65% of all bacteriophage (phage) protein sequences cannot be confidently annotated. In this review, we examine state-of-the-art bioinformatics tools and methodologies for annotating bacterial and phage proteins, particularly those of unknown or poorly characterized function.

SpeSpeNet: an interactive and user-friendly tool to create and explore microbial correlation networks.

Correlation networks are commonly used to explore microbiome data. In these networks, nodes are microbial taxa and edges represent correlations between their abundances. As clusters of correlating taxa (co-abundance clusters) often indicate a shared response to environmental drivers, network visualization contributes to the system understanding.

Summary of taxonomy changes ratified by the International Committee on Taxonomy of Viruses (ICTV) from the Bacterial Viruses Subcommittee, 2025.

This article summarises the activities of the International Committee on Taxonomy of Viruses Bacterial Viruses Subcommittee, detailing developments in the classification of bacterial viruses. We provide here an overview of all new, abolished, moved and renamed taxa proposed in 2024, approved by the Executive Committee, and ratified by membership vote in 2025. Through the collective efforts of 74 international contributors of taxonomy proposals in this round, 43 ratified proposals have led to the creation of one new phylum, one class, four orders, 33 families, 14 subfamilies, 194 genera and 995 species.

Chemical characteristics vectors map the chemical space of natural biomes from untargeted mass spectrometry data.

Untargeted metabolomics can comprehensively map the chemical space of a biome, but is limited by low annotation rates (< 10%). We used chemical characteristics vectors, consisting of molecular fingerprints or chemical compound classes, predicted from mass spectrometry data, to characterize compounds and samples. These chemical characteristics vectors (CCVs) estimate the fraction of compounds with specific chemical properties in a sample.

Ultrafast and accurate sequence alignment and clustering of viral genomes.

Viromics produces millions of viral genomes and fragments annually, overwhelming traditional sequence comparison methods. Here we introduce Vclust, an approach that determines average nucleotide identity by Lempel-Ziv parsing and clusters viral genomes with thresholds endorsed by authoritative viral genomics and taxonomy consortia. Vclust demonstrates superior accuracy and efficiency compared to existing tools, clustering millions of genomes in a few hours on a mid-range workstation.

Tunturi virus isolates and metagenome-assembled viral genomes provide insights into the virome of Acidobacteriota in Arctic tundra soils.

Background: Arctic soils are climate-critical areas, where microorganisms play crucial roles in nutrient cycling processes. Acidobacteriota are phylogenetically and physiologically diverse bacteria that are abundant and active in Arctic tundra soils. Still, surprisingly little is known about acidobacterial viruses in general and those residing in the Arctic in particular.

Improving genome-scale metabolic models of incomplete genomes with deep learning.

Deciphering microbial metabolism is essential for understanding ecosystem functions. Genome-scale metabolic models (GSMMs) predict metabolic traits from genomic data, but constructing GSMMs for uncultured bacteria is challenging due to incomplete metagenome-assembled genomes, resulting in many gaps. We introduce the deep neural network guided imputation of reactomes (DNNGIOR), which uses AI to improve gap-filling by learning from the presence and absence of metabolic reactions across diverse bacterial genomes.

Seasonal dynamics and diversity of Antarctic marine viruses reveal a novel viral seascape.

The Southern Ocean microbial ecosystem, with its pronounced seasonal shifts, is vulnerable to the impacts of climate change. Since viruses are key modulators of microbial abundance, diversity, and evolution, we need a better understanding of the effects of seasonality on the viruses in this region. Our comprehensive exploration of DNA viral diversity in the Southern Ocean reveals a unique and largely uncharted viral landscape, of which 75% was previously unidentified in other oceanic areas.

Graphite: painting genomes using a colored de Bruijn graph.

The recent growth of microbial sequence data allows comparisons at unprecedented scales, enabling the tracking of strains, mobile genetic elements, or genes. Querying a genome against a large reference database can easily yield thousands of matches that are tedious to interpret and pose computational challenges. We developed Graphite that uses a colored de Bruijn graph (cDBG) to paint query genomes, selecting the local best matches along the full query length.

Phylogeny and disease associations of a widespread and ancient intestinal bacteriophage lineage.

Viruses are core components of the human microbiome, impacting health through interactions with gut bacteria and the immune system. Most human microbiome viruses are bacteriophages, which exclusively infect bacteria. Until recently, most gut virome studies focused on low taxonomic resolution (e.

Structural color in the bacterial domain: The ecogenomics of a 2-dimensional optical phenotype.

Structural color is an optical phenomenon resulting from light interacting with nanostructured materials. Although structural color (SC) is widespread in the tree of life, the underlying genetics and genomics are not well understood. Here, we collected and sequenced a set of 87 structurally colored bacterial isolates and 30 related strains lacking SC.

Integrating taxonomic signals from MAGs and contigs improves read annotation and taxonomic profiling of metagenomes.

Metagenomic analysis typically includes read-based taxonomic profiling, assembly, and binning of metagenome-assembled genomes (MAGs). Here we integrate these steps in Read Annotation Tool (RAT), which uses robust taxonomic signals from MAGs and contigs to enhance read annotation. RAT reconstructs taxonomic profiles with high precision and sensitivity, outperforming other state-of-the-art tools.

Benchmarking bioinformatic virus identification tools using real-world metagenomic data across biomes.

Background: As most viruses remain uncultivated, metagenomics is currently the main method for virus discovery. Detecting viruses in metagenomic data is not trivial. In the past few years, many bioinformatic virus identification tools have been developed for this task, making it challenging to choose the right tools, parameters, and cutoffs.

A global survey of host, aquatic, and soil microbiomes reveals shared abundance and genomic features between bacterial and fungal generalists.

Environmental change, coupled with alteration in human lifestyles, is profoundly impacting the microbial communities critical to the health of the Earth and its inhabitants. To identify bacteria and fungi that are resistant and susceptible to habitat change, we analyze thousands of genera detected in 1,580 host, soil, and aquatic samples. This large-scale analysis identifies 48 bacterial and 4 fungal genera that are abundant across the three biomes, demonstrating fitness in diverse environmental conditions.

Taxonomic resolution of different 16S rRNA variable regions varies strongly across plant-associated bacteria.

Plant-microbiome research plays a pivotal role in understanding the relationships between plants and their associated microbial communities, with implications for agriculture and ecosystem dynamics. Metabarcoding analysis on variable regions of the 16S ribosomal RNA (rRNA) gene remains the dominant technology to study microbiome diversity in this field. However, the choice of the targeted variable region might affect the outcome of the microbiome studies.

Ultraconserved bacteriophage genome sequence identified in 1300-year-old human palaeofaeces.

Bacteriophages are widely recognised as rapidly evolving biological entities. However, knowledge about ancient bacteriophages is limited. Here, we analyse DNA sequence datasets previously generated from ancient palaeofaeces and human gut-content samples, and identify an ancient phage genome nearly identical to present-day Mushuvirus mushu, a virus that infects gut commensal bacteria.

Identifying and tracking mobile elements in evolving compost communities yields insights into the nanobiome.

Microbial evolution is driven by rapid changes in gene content mediated by horizontal gene transfer (HGT). While mobile genetic elements (MGEs) are important drivers of gene flux, the nanobiome-the zoo of Darwinian replicators that depend on microbial hosts-remains poorly characterised. New approaches are necessary to increase our understanding beyond MGEs shaping individual populations, towards their impacts on complex microbial communities.

Growth rate is a dominant factor predicting the rhizosphere effect.

The root microbiome is shaped by plant root activity, which selects specific microbial taxa from the surrounding soil. This influence on the microorganisms and soil chemistry in the immediate vicinity of the roots has been referred to as the rhizosphere effect. Understanding the traits that make bacteria successful in the rhizosphere is critical for developing sustainable agriculture solutions.