Bacteria encode diverse defence systems, including restriction–modification and CRISPR–Cas, that cleave nucleic acid to protect against phage infection. Bioinformatic analyses demonstrate that many recently identified antiphage defence operons comprise a nuclease and NTPase protein, suggesting that additional nucleic acid-targeting systems remain to be understood. Here we develop large-scale comparative cell biology and biochemical approaches to analyse 16 nuclease–NTPase systems and define molecular features that control antiphage defence. Purification, biochemical characterization and in vitro reconstitution of nucleic acid degradation demonstrates that protein–protein complex formation is a shared feature of multigene nuclease–NTPase systems. We show that PaAbpAB, BtHachiman and EcPD-T4-8 system nucleases use highly degenerate recognition site preferences to enable broad nucleic acid degradation, and the Azaca system exhibits specific phage targeting through the recognition of modified phage genomic DNA. Our results uncover principles of antiphage defence system function and highlight the mechanistic diversity of nuclease–NTPase systems in bacterial immunity. A large-scale, comparative cell biology and biochemical screen defines the molecular features controlling antiphage defence systems that encode nuclease effectors and accessory NTPase proteins.

Dissecting the functional impact of genetic mutations is essential to advancing our understanding of genotype-phenotype relationships and identifying therapeutic targets. Despite progress in sequencing and genome editing technologies, proteome-wide mutation effect prediction remains challenging. Here we show that evolutionary information alone enables accurate prediction of mutation effects across entire proteomes. ProteoCast is a scalable and interpretable computational method that leverages protein sequence conservation to classify genetic variants and identify functionally important protein sites. We apply ProteoCast to the complete Drosophila melanogaster proteome (22,000 isoforms, 300 million mutations) and validate it against nearly 400,000 natural and experimental variants. It correctly classifies 85% of known lethal mutations as functionally impactful versus 13-18% of population variants. ProteoCast-guided genome editing experiments confirm these predictions. Moreover, ProteoCast successfully identifies functionally important protein modification sites and binding motifs. ProteoCast provides a publicly available resource and deployable pipeline for studying gene function and mutations in any organism. This study introduces ProteoCast, which uses protein sequence conservation to predict mutation effects proteome-wide. Validated on 400,000 Drosophila variants and genome editing experiments, it accurately identifies functionally critical sites in any organism.

Bacterial metabolism is a complex system of interwoven pathways coordinated by an intricate, multilayered regulatory network. Dissecting the metabolism at single bacterial level is highly challenging. Herein, we greatly increase the sensitivity of the bacterial measurement with our home-made single-bacterium metabolome (SinBactM) mass spectrometry platform, which combines micro-extraction with induced nanoelectrospray ionization mass spectrometry, for mapping metabolites of the primary bacterium. The universal applicability of the SinBactM platform is demonstrated by successfully discriminating distinct metabolic profiles across different bacterial species. By measuring the bacterial uptake of antibiotics and observing the dynamic metabolic changes in response to external stimuli, the accuracy and reliability of SinBactM platform are further validated. We apply SinBactM to characterize clinical heteroresistant K. pneumoniae strains metabolic alteration under antibiotic perturbation. Several different subpopulations resulting from antibiotic perturbation are classified based on their metabolome, while pseudotemporal ordering reveals a trajectory of metabolic change across subpopulations. Thus, SinBactM platform paves the way for profiling metabolomics of individual bacterial cells, which might provide an exciting dimension to a thorough understanding of antibiotic-resistant evolution for in-depth interrogation of resistant mechanisms. Here the authors present a single-bacterium metabolomics platform that enables sensitive metabolic profiling of individual bacteria, revealing metabolic heterogeneity in heteroresistant K. pneumoniae strains and providing insights into bacterial survival and resistance.

CRISPR–Cas12a is a versatile RNA-guided nuclease that has rapidly gained prominence for its dual functionality in genome editing and nucleic acid detection. In this Review, we discuss the structural, biochemical and mechanistic features of Cas12a that underpin its autonomous processing of the guide RNA and indiscriminate cleavage of single-stranded DNA, which enable Cas12a applications ranging from gene therapy to rapid diagnostics. We discuss key allosteric regulators and functional modules that orchestrate Cas12a activity, focusing on the core regulatory structural elements that control maturation of the guide RNA, target specificity, and both cis-cleavage and trans-cleavage activities, including the determinants of off-target cleavage. We provide a comparative analysis of Cas12a and the widely used Cas9, which further illuminates the distinctive attributes of Cas12a, and discuss recent advances in the characterization of its orthologues and in the development of engineered variants that expand its capabilities. Collectively, we present a comprehensive understanding of Cas12a and its increasing impact on biotechnology, therapeutics and molecular diagnostics. This Review discusses the unique features of the functionally versatile nuclease Cas12a, including allosteric regulation, structural elements controlling guide RNA maturation, target specificity, cis-cleavage and trans-cleavage activities and determinants of off-target cleavage. These features increase the applicability of Cas12a in biotechnology, therapeutics and molecular diagnostics

Microbial electrochemical technologies connect living microorganisms with electrical systems to enable sustainable processes. These systems use the natural electron transfer abilities of microbes to support clean energy generation, transform waste and pollutants, and recover valuable resources. Microorganisms act as living catalysts whose biological traits and energy requirements determine system performance. Recent advances have expanded these technologies toward chemical production and new electronic applications, while improved engineering has increased their readiness for practical use. At the same time, these systems offer a powerful platform for studying fundamental microbial processes in real time. This review outlines the biological foundations of microbe–electrode interactions, highlights current applications relevant to circular resource use, and identifies scientific and engineering challenges that must be addressed to unlock broader societal and economic benefits. The goal is to emphasize the growing potential of microbe–electrical interfaces to support transformative solutions for environmental sustainability. Microbial electrochemical technologies can enable clean energy, waste conversion, and resource recovery, according to a literature synthesis on microbe-electrode interactions and engineered bioelectrochemical systems.

A common procedure for studying the microbiome is binning the sequenced contigs into metagenome-assembled genomes. State-of-the-art binning methods use coabundance and sequence-based motifs such as tetranucleotide frequencies, whereas taxonomic labels derived from alignment based classification have not been widely used. Here we propose TaxVAMB, a metagenome binning tool based on semisupervised bimodal variational autoencoders, combining tetranucleotide frequencies and contig coabundances with taxonomic information. TaxVAMB outperformed all other binners on CAMI2 human microbiome datasets, returning on average 29% more high-quality assemblies than the next best binner, and performed on par with the best binners on short-read datasets. On a human gut long-read dataset, TaxVAMB recovered 29% more high-quality bins. In a typical single-sample setup, TaxVAMB on average returns 83% more high-quality bins compared to VAMB. Lastly, TaxVAMB binned incomplete genomes better than any other tool, returning on average 300% more high-quality bins of incomplete genomes than the next best binner. TaxVAMB combines sequence features with taxonomic information for improved metagenome binning.

Gram-negative bacteria use a plethora of virulence factors to infect eukaryotic cells. CE-clan protease-related virulence factors were reported to act as deubiquitinases/ubiquitin-like specific proteases. Some have an additional acetyl-transferase activity. The molecular mechanisms underlying this dual activity and the physiological consequences are only marginally understood. Here, we report crystal structures for the Simkania negevensis virulence factor SnCE1 in apo-states and in complex with SUMO1. We confirm SnCE1 acting as an efficient deSUMOylase and discover an intrinsic autoacetyltransferase activity. Acetylation impairs SnCE1 tetramer formation structurally being incompatible with SUMO1 binding. We provide a model for regulation of SnCE1-mediated virulence by lysine acetylation modulating autoproteolytic processing and its subcellular distribution in the host cell. SnCE1 localizes to the endoplasmic reticulum in human cells and increases fragmentation of mitochondria. Our data provide mechanistic insights into how lysine acetylation of virulence factors is used to reprogram virulence adjusting it to the host cells’ metabolic state. Gram-negative bacteria use diverse virulence factors to infect eukaryotic cells. Here, the authors perform structure-function analyses on the S. negevensis deSUMOylase SnCE1 and provide mechanistic insights how lysine acetylation reprograms virulence adjusting it to the host cells’ metabolic state.

Since their discovery, bacteriophages—viruses that infect bacteria—have been invaluable to molecular biology and biotechnology. Renewed interest in phage-based antimicrobials, driven by the global antibiotic resistance crisis, highlights the need for improved quantitative tools. While conventional double-layer plaque assays (DLA) have provided foundational insights, they are limited by their inability to monitor infection dynamics over time and the inflexibility in experimental setups. Here, we present a high-throughput droplet microfluidics platform to quantify individual phage infection events. By co-encapsulating individual phages and bacteria in microfluidic droplets, we precisely control key experimental parameters such as exposure time and the ratio of phages to bacteria. This approach enables direct quantification of lysis events and measurement of lysis kinetics without interference from further progeny-driven infection processes inherent to bulk cultures. Applicable to diverse phage-host systems, this method offers a dynamic and accurate framework for studying phage biology and supports the development of phage-based antimicrobial strategies. Bacteriophages are key tools in molecular biology and promising agents against antibiotic-resistant bacteria. Here, the authors present a high-throughput droplet microfluidics platform that co-encapsulates single phages and bacteria to quantify individual infection events and lysis kinetics under precisely controlled conditions.

Plant-based platforms offer a sustainable alternative to chemical synthesis for producing high-value biological products, including therapeutic proteins and peptides, vaccines, antibodies, nutraceuticals, and specialised metabolites. Peptide-based therapeutics in particular hold enormous potential due to their specificity, safety, and efficacy in treating a wide range of diseases. Peptides that are comprised of the 20 canonical amino acids can be produced in plants, but challenges such as toxicity to host cells, aggregation, misfolding, susceptibility to proteolytic degradation, low expression levels, and challenges in dealing with post-translational modifications can limit successful biosynthesis. This review provides a comprehensive analysis of current successes and limitations in the field, and potential biotechnological strategies and exogenous treatments to overcome limitations, to enhance peptide production in plants.

Soil and sediment microbiomes have a central role in biogeochemical cycling, climate regulation and ecosystem resilience. However, they are increasingly degraded by land use change, pollution and climate change. Despite their foundational roles in ecosystems, these microbiomes remain under-represented in ecosystem restoration science, practice and policy. Improving the integration of microbiomes across the restoration science–practice–policy nexus is essential for achieving more effective and resilient restoration outcomes. Without this, global restoration risks neglecting the microbial foundations of functional ecosystems and long-term resilience. In this Review, we synthesize the current state of knowledge of soil and sediment microbiome restoration. We describe the major anthropogenic stressors that are degrading these microbiomes, highlighting the linked and context-dependent nature of these impacts, and evaluate existing strategies to restore them. To improve restoration effectiveness, we propose a research workflow that encompasses baseline establishment, degradation diagnostics, designing and testing interventions, research methodology selection and best practice principles. We also outline key theoretical frameworks and propose future research priorities to help soil and sediment microbiome restoration to move towards a predictive, theory-led discipline. In this Review, Wood and colleagues discuss how anthropogenic pressures are degrading soil and sediment microbiomes, propose restoration strategies and emphasize the importance of integrating microbiome science into global ecosystem restoration efforts.

The HMMER web server, available at https://www.ebi.ac.uk/Tools/hmmer, provides online access to tools from the HMMER software suite (http://hmmer.org/) for protein analysis using profile hidden Markov models. Users can perform sequence similarity searches against a range of regularly updated protein sequence databases or annotate protein sequences with domains and families using profile HMM libraries from protein family databases. Since the 2018 update, the continued exponential growth of sequence databases has necessitated substantial infrastructural improvements to maintain search performance speed and service reliability. To achieve this, the web interface has been completely reengineered using modern web technologies (JavaScript and React), providing users with an enhanced experience, including session-based search history and streamlined results visualization. The web application programming interface has been rewritten to better support programmatic access with updated endpoints and JSON-based responses. The infrastructure has been redesigned to efficiently handle searches against much larger databases through horizontal scaling and asynchronous job processing. Target database offerings have been updated to reflect current usage patterns and data availability. The HMMER web server is free and open to all users, and there is no login requirement.