Nutrition plays a fundamental role in shaping human health across the life course, influencing both host physiology and the composition and function of the gut microbiota. In turn, the gut microbiota modulates the effects of dietary intake, creating complex bidirectional interactions with profound implications for metabolic health. Although the concept of personalized nutrition offering tailored dietary advice based on observable traits, environmental factors, and genotype has gained prominence, growing evidence supports the promise of precision nutrition that also considers individual microbiome profiles. This approach is particularly relevant for addressing diet-related conditions such as obesity and type 2 diabetes, where interindividual variability in response to the same diet is well documented. Advances in high-throughput sequencing, metabolomics, and machine learning are driving predictive models that can forecast personalized dietary outcomes. However, methodological heterogeneity, lack of consistency, and limited representation of diverse populations in current studies present significant barriers. Ethical challenges, including data privacy and equitable access to personalized nutrition tools, also warrant urgent attention. To realize the full potential of microbiome-informed nutrition, greater harmonization of research methods, robust validation across large and diverse cohorts, and an interdisciplinary framework are essential.

Host specificity of a plant pathogen is defined by its effector complement. However, it remains unclear whether the full complement is required for pathogenicity. Pseudomonas syringae pv. actinidiae (Psa) is an emerging model pathogen of kiwifruit with over 30 functional effectors, providing a unique opportunity to understand how host-mediated selection shapes pathogen evolution. The majority of Psa’s effectors previously appeared nonessential in single knockout contexts. Why, then, does Psa maintain such a large repertoire? We sought to examine effector requirements, redundancies, and repertoire refinement across host genotypes through a mutated effector-leveraging evolution experiment (MELEE), serially passaging competitive populations of effector knockout strains. Competition suggests that all effectors are collectively required for successful virulence, demonstrated by the dominance of wild-type. Host-specific effector requirements identified may further explain the maintenance of this large effector repertoire, providing important insights into the dynamics of effector redundancy following incursions.

Nanopore direct RNA sequencing offers a versatile approach for detecting multiple types of RNA modifications at a single-base resolution. In this study, we systematically evaluate 86 computational tools for detecting six RNA modifications (m6A, Ψ, m5C, A-to-I editing, m7G and m1A) using direct RNA sequencing data from both RNA002 and RNA004 chemistries. We demonstrate that retraining tools with a combination of in vitro transcription and real biological samples notably enhances both accuracy and generalizability over their original implementations, especially for Ψ, m5C and A-to-I. Evaluations on real biological samples reveal that while m6A detection tools generally achieve high accuracy, non-m6A tools struggle with precision–recall balance, quantification accuracy and biological validity. Our findings highlight the importance of incorporating diverse training data and stress the need for tools capable of reliably distinguishing between modification types at single-base resolution. These insights provide a foundation for advancing RNA modification detection. This analysis benchmarked computational tools for RNA modification detection using nanopore direct RNA sequencing and showed that retraining with mixed in vitro transcription and real data improves performance.

Protein Data Bank in Europe (PDBe) is a founding member of the worldwide Protein Data Bank (wwPDB), delivering open access to experimentally determined macromolecular structures. PDBe also delivers enriched annotations contributed by the PDBe-Knowledge Base (PDBe-KB) consortium. The macromolecular entry pages are the primary interface for millions of users who explore experimental structure data. Here, we describe the redesign of the PDBe entry pages that organize content into logical views, thereby improving usability and facilitating the use of structure models, driving fundamental and applied research, and supporting education. The new design introduces several enhancements, including integrated and central 3D visualization, sequence feature exploration, standardized molecular scenes, AI-driven residue-level annotations from text mining of the literature, and streamlined annotation access via refactored APIs. Importantly, researchers can now upload their own residue-level features and visualize them directly in structural context, displayed alongside PDBe-KB annotations. This functionality enables scientists to interpret unpublished or private data in relation to high-quality structural information, lowering barriers for those without prior expertise in structural biology. Together, these updates create a more accessible, flexible, and scalable framework for interacting with structural data, expanding the resource’s value to both domain specialists and the wider life sciences community.

Drug-resistant bacterial infections, exacerbated by antibiotic resistance and biofilm resilience, disrupt tissue repair through dysregulated inflammation and impaired regeneration. Neutrophil extracellular traps (NETs) play a crucial role in endogenous immunity by entrapping and eliminating pathogens, inspiring the development of synthetic biomaterials that replicate this function. However, current synthetic NETs face challenges in complexity, biocompatibility, structural integrity and effectiveness. Here, we present a NETs-mimicking hydrogel composed of reversible lysozyme amyloid flexible nanofibrils (FFs) enabling pathogen elimination and tissue regeneration. The FFs therein self-assemble from natural egg-white lysozyme endowing these nanoNETs with bioactivity against pathogens, and when duly labeled to respond to near-infrared irradiation, they disassemble into unfolded lysozyme monomers with antimicrobial activity. Notably, the hydrogel disassembly is followed by the controlled release of pre-dissolved Mg²⁺ ions, reprogramming macrophages toward a pro-regenerative phenotype and mitigating inflammation. In both murine and porcine models, these biocompatible nanoNETs demonstrate excellent antibacterial performance, accelerating healing of wounds infected by methicillin-resistant Staphylococcus aureus (MRSA). Moreover, these nanoNETs boost in-vivo healing of MRSA-infected periprosthetic joints, preserving osteogenic and regenerative microenvironments. These results build on the reversible nature of flexible amyloids to introduce stimuli-responsive biocompatible nanoNETs with significant potential for antimicrobial and regenerative therapies in bacterial-resistant infections. Drug-resistant bacterial infections hinder tissue repair and regeneration. Here, authors present a lysozyme nanofibril-based hydrogel that mimics neutrophil extracellular traps, enabling pathogen elimination and promoting tissue regeneration.

DNA methylation is a crucial epigenetic mechanism that regulates gene expression. Precise editing of DNA methylation has emerged as a promising tool for dissecting its biological function. However, challenges in delivery have limited most applications of DNA methylation editing to in vitro systems. Here, we develop two transgenic mouse lines harboring an inducible dCas9-DNMT3A or dCas9-TET1 editor to enable tissue-specific DNA methylation editing in vivo. We demonstrate that targeted methylation of the Psck9 promoter in the liver of dCas9-DNMT3A mice results in decreased Pcsk9 expression and a subsequent reduction in serum low-density lipoprotein cholesterol level. Targeted demethylation of the Mecp2 promoter in dCas9-TET1 mice reactivates Mecp2 expression from the inactive X chromosome and rescues neuronal nuclear size in Mecp2+/- mice. Genome-wide sequencing analyses reveal minimal transcriptional off-targets, demonstrating the specificity of the system. These results demonstrate the feasibility and versatility of methylation editing, to functionally interrogate DNA methylation in vivo. Precise editing of DNA methylation has emerged as a promising tool in disease biology but most applications are limited to in vitro systems. Here, we develop two transgenic mouse lines harboring an inducible dCas9-DNMT3A or dCas9-TET1 editor to enable tissue-specific DNA methylation editing in vivo.

The incidence of cardiometabolic diseases is increasing globally, and both poor diet and the human gut microbiome have been implicated. However, the field lacks large-scale, comprehensive studies exploring these links in diverse populations. Here, in over 34,000 US and UK participants with metagenomic, diet, anthropometric and host health data, we identified known and yet-to-be-cultured gut microbiome species associated significantly with different diets and risk factors. We developed a ranking of species most favorably and unfavorably associated with human health markers, called the ‘ZOE Microbiome Health Ranking 2025’. This system showed strong and reproducible associations between the ranking of microbial species and both body mass index and host disease conditions on more than 7,800 additional public samples. In an additional 746 people from two dietary interventional clinical trials, favorably ranked species increased in abundance and prevalence, and unfavorably ranked species reduced over time. In conclusion, these analyses provide strong support for the association of both diet and microbiome with health markers, and the summary system can be used to inform the basis for future causal and mechanistic studies. It should be emphasized, however, that causal inference is not possible without prospective cohort studies and interventional clinical trials. Comprehensive large-scale studies of multi-national populations identified microbiome species consistently associated with favorable and unfavorable health markers, informing future studies of the human gut microbiome and its association with diet and cardiometabolic conditions.

Fluorescent pseudomonads catabolize purines via uric acid and allantoin, a pathway whose end-product is glyoxylate. In this work, we show that in Pseudomonas aeruginosa strain PAO1, the ORFs PA1498–PA1502 encode a pathway that converts the resulting glyoxylate into pyruvate. The expression of this cluster of ORFs was stimulated in the presence of allantoin, and mutants containing transposon insertions in the cluster were unable to grow on allantoin as a sole carbon source. The likely operonic structure of the cluster is elucidated. We also show that the purified proteins encoded by PA1502 and PA1500 have glyoxylate carboligase (Gcl) and tartronate semialdehyde (TSA) reductase (GlxR) activity, respectively, in vitro. Gcl condenses two molecules of glyoxylate to yield TSA, which is then reduced by GlxR to yield d-glycerate. GlxR displayed much greater specificity (kcat/KM) for Gcl-derived TSA than it did for the TSA tautomer, hydroxypyruvate. This is relevant because TSA can potentially spontaneously tautomerize to yield hydroxypyruvate at neutral pH. However, kinetic and [1H]-NMR evidence indicate that PA1501 (which encodes a putative hydroxypyruvate isomerase, Hyi) increases the rate of the Gcl-catalysed reaction, possibly by minimizing the impact of this unwanted tautomerization. Finally, we use X-ray crystallography to show that apo-GlxR is a configurationally flexible enzyme that can adopt two distinct tetrameric assemblies in vitro.

R-pyocins are phage tail-like protein complexes produced by Pseudomonas aeruginosa that deliver a single, lethal hit by depolarizing the target cell membrane. Unlike phages, R-pyocins lack capsids and DNA, and their killing is highly specific, being determined by tail fibre proteins that recognize subtype-specific LPS receptors on susceptible strains. Five known subtypes (R1–R5) vary in host range, with R5 displaying the broadest activity. R-pyocin expression is tightly regulated by the SOS response, linking their release to environmental stress. Their non-replicative mechanism and metabolic independence make them especially promising for targeting multidrug-resistant and biofilm-associated P. aeruginosa infections, such as those seen in cystic fibrosis and chronic wounds. Preclinical studies support their therapeutic potential, and bioengineering approaches have extended their target range. With their high specificity, rapid action and adaptability, R-pyocins are strong candidates for next-generation precision antimicrobials.

Module swapping is an emerging strategy for creating transcriptional regulators with tailored combinations of signal detection and promoter recognition. By hybridizing DNA-binding modules (DBMs) and ligand-binding modules (LBMs) from the same protein family, resulting regulators can be harnessed to establish new genetic connections. This approach has been applied to a range of regulator families; however, a portion of resulting hybrid regulators are poorly functional, which can be due to incompatibility between DBMs and LBMs, as critical module–module interactions are lost after hybridization. To address this issue, we developed an approach to design modular regulators and applied it to the TtgR/AcrR regulator family. Our approach involves identifying key residue pairs for DBM–LBM interactions by statistical analyses of coevolutionary traits among family members and experimental results from hybrid regulator characterization. These residue pairs were harnessed to develop a computational model for predicting compatibility between DBMs and LBMs. Using this predictive model, we designed mutations to reinstall critical interactions, which rescued protein activities. These hybrid regulators were harnessed to construct a genetic circuit for a three-input logic AND operation, demonstrating that our approach is effective for studying and designing new TtgR/AcrR modular regulators.

Steroids are among the most valuable and widely used pharmaceuticals. The cholesterol side-chain cleavage enzyme (P450scc) is critical for steroid metabolism and hormone biosynthesis. While mammalian eukaryotic P450scc enzymes are well-characterized, bacterial counterparts remain underexplored despite their industrial promise and potential contributions to bacterial steroid catabolism. Here, we identify a series of CYP204 family P450 enzymes, widely distributed across diverse steroid-degrading bacterial species, that catalyze the side-chain cleavage of cholesterol, phytosterol, and cholestenone to produce pregnenolone and progesterone. Unlike mammalian enzymes, which exhibit strict cholesterol specificity, bacterial P450scc enzymes display relaxed substrate specificity, preferentially converting cholestenone to progesterone—a key precursor in steroid drug semi-synthesis. Structural and mechanistic analyses demonstrate that CYP204 enzymes employ a flexible, dual-regioselective C–H activation mechanism distinct from the sequential hydroxylation of mammalian P450scc enzymes. Iterative saturation mutagenesis identified critical residues for side-chain cleavage, improving catalytic efficiency up to 6.5-fold, and computational analyses clarified sequence–function relationships. This finding of bacterial P450scc enzymes not only underscores their potential function in bacterial steroid catabolism but also lays a foundation for promising biocatalytic strategies for pregnenolone and progesterone synthesis. Genome mining identified bacterial P450 that cleave cholesterol side-chains via dual C-H activation, differing from mammalian P450scc. Engineered CYP204A5 efficiently converts cholestenone to progesterone for biocatalysis.

Self-assembly is a fundamental property of living matter that drives the three-dimensional organization of cell collectives such as tissues and organs. Here, the co-assembly of synthetic and natural cells is leveraged to create hybrid living 3D cancer cultures. We screen a range of synthetic cell models for their ability to form augmented tumoroids with artificial but controllable micro-environments, and show that the balance of inter- and extracellular adhesion and synthetic cell surface tension are key material properties driving integrated co-assembly. We demonstrate that synthetic cells based on droplet-supported lipid bilayers can establish artificial tumor immune microenvironments (ART-TIMEs), mimicking immunogenic signals within tumoroids and eliminating the need to integrate complex living immune cells. Using the ART-TIME approach, we identify a AhR-ARNT-mediated co-signaling mechanism between PD-1 and CD2 as a driver in immune evasion of pancreatic ductal adenocarcinoma. Our study advances the field of hybrid organoid engineering, offers opportunities for the construction and modelling of artificial tumour environments, and marks a step towards the design of functional living/non-living cytomimetic materials. Synthetic cells have huge potential in model systems. Here, the authors engineer synthetic–living hybrid tumoroids that replicate tumour-immune interactions in 3D, study synthetic cells integration, and demonstrate systematic studies of immune evasion and T cell engager therapies.

Transcription factors regulate gene expression by binding specific DNA motifs, yet only a fraction of putative sites is occupied in vivo. Intrinsically disordered regions have emerged as key contributors to promoter selectivity, but the underlying mechanisms remain incompletely understood. Here, we use single-molecule optical tweezers to dissect how disordered regions influence DNA binding by Msn2, a yeast stress-response regulator. We show that these regions power a search mechanism, facilitating initial non-specific association with DNA and promoting one-dimensional scanning toward target motifs, supported by charge-mediated interactions. Remarkably, this mechanism displays sequence sensitivity, with promoter-derived sequences enhancing both initial binding and scanning rates, demonstrating that Msn2–DNA interactions alone are sufficient to confer promoter selectivity in the absence of chromatin or cofactors. Our findings provide direct mechanistic evidence for how intrinsically disordered regions tune transcription factor search dynamics for Msn2 and expand sequence recognition beyond canonical motifs, supporting promoter selectivity in complex genomic contexts. The study reveals how intrinsically disordered regions enable a yeast transcription factor to locate and selectively bind its target promoters by promoting DNA association outside its motif and sequence-dependent search dynamics.