With the rise of antimicrobial resistance, urinary tract infections (UTIs) have become increasingly more difficult to treat, prompting renewed interest in bacteriophage (phage) therapy as an alternative or adjunct to antibiotics. UTIs are an attractive target for phage therapy because they generate a high density of actively replicating bacteria that supports phage propagation, and because the urinary tract is readily accessible for administration and monitoring. Yet studies of phage therapy for UTIs report mixed outcomes, including failures to meet clinical and microbiological endpoints. Here we follow the population dynamics of a clinical Escherichia coli UTI strain and two phages, HP3 and ES19, to which the strain appears susceptible by standard testing. Despite this apparent susceptibilty, both phages fail to suppress the strain, with resistance emerging almost immediately. Using the measured mutation rate, our mathematical model shows that traditional resistance cannot account for these dynamics. We instead demonstrate, including by a phage-specific population analysis profile assay we developed, that heteroresistance drives this rapid failure, offering a plausible explanation for treatment failures in UTI phage therapy

Assembly-line polyketide synthases (PKSs) are among the most sophisticated catalysts in nature, responsible for the biosynthesis of many medicinally important natural products including antibiotics, anticancer agents, immunosuppressants and veterinary agents. While conventional methods for polyketide natural product discovery have fallen out of favor, the rapid expansion of microbial genome sequencing has revealed a vast untapped diversity of assembly-line PKSs, most of which can be regarded as “orphans” in that their product identity is unknown. A clear picture of how this sequence diversity reflects the evolutionary history of assembly-line PKSs could enable judicious prioritization of experimental efforts aimed at decoding these orphans. To this end we have used a scalable curation workflow to hand-curate an updated catalogue, PKSClusterDB, that includes 16 633 non-redundant assembly-line PKSs. We have also formulated an automatable “anchor-window” framework based on conserved multimodular segments of assembly-line PKSs to identify and interrogate PKS families of interest. Application of this framework to three different PKS families extracted from PKSClusterDB revealed lineage-dependent patterns of diversification, ranging from broadly diversified families to more compact or sharply bounded lineages. PKSClusterDB has also proven useful in exploring other aspects of PKS diversity, including scaffold architecture, extender-unit specificity, reductive-state programming, stereochemical control and modular organization. In closing, we consider how advances in machine learning could be harnessed to accelerate our understanding of assembly-line PKS evolution, diversity and biosynthetic mechanisms.

Trichoderma is a genus of beneficial fungi widely used in agriculture disease suppression, plant growth promotion, and soil health improvement. Although some studies have shown that Trichoderma spp. can be seed-borne, albeit at low frequency, no specific study has so far focused on the diversity of Trichoderma isolates capable of adapting to this particular environment. Over 2 years of routine seed health analyses, we isolated 107 Trichoderma strains associated with seeds from 32 cultivated plant species, and we investigated the diversity of this specific library using multi-locus analysis. These isolates are distributed among 18 different species, but Trichoderma atroviride is by far the most frequent. Representative strains of each species all have the ability to parasitise damping-off agents, although the intensity of parasitism can vary greatly from one strain to another and depending on the targeted plant pathogens. For two isolates of T. atroviride, we showed that these fungi can be transmitted from fruit to seed and limit the transmission of the plant pathogen Alternaria brassicicola. Furthermore, these strains stimulated seedling growth and provided protection against Globisporangium ultimum. Together, these findings support the benefits of focusing on certain selected seed-borne Trichoderma which seem particularly well suited to improving seed health.

Microbial community assembly is shaped by the nature of available resources, with labile carbon sources like glucose often expected to support low diversity due to rapid growth and competitive exclusion. In contrast, recalcitrant substrates like cellulose are thought to support higher diversity through slower growth and increased niche partitioning. In previous work, we showed that compost-derived microbial communities propagated on cellulose maintained high diversity over nearly a year. To determine whether such diversity is specific to recalcitrant substrates or reflects more general features of assembly, we tracked community dynamics in three environments—cellulose paper, cellulose broth and glucose—using daily 16S rRNA profiling. Communities maintained through four bi-weekly serial transfers, with five replicates per treatment, yielded a high-resolution dataset of over 800 samples. Despite originating from the same inoculum, communities diverged sharply in both taxonomic and functional composition. Cellulose environments yielded stable communities enriched in specialists, while glucose environments exhibited rapid succession and dominance by generalists. Surprisingly, all environments sustained comparably high levels of taxonomic diversity. Functional inference suggested extensive cross-feeding and resource salvaging in both cases. Our results reveal distinct assembly trajectories under simple carbon regimes and provide a foundation for future mechanistic study.

Healthy plant leaves potentially host both commensal bacteria and opportunistic pathogens, which, under some circumstances, may cause disease. The interactions between commensals and opportunistic pathogens are generally poorly understood, but such understanding is crucial for developing effective biocontrol strategies. In Arabidopsis thaliana, isothiocyanates (ITCs) are defense metabolites that suppress most bacteria; commensals are especially affected as they do not express ITC resistance genes. The ITC hydrolase SaxA detoxifies ITCs, making it an important virulence factor for bacterial and fungal pathogens. To investigate pathogen-commensal interactions based on SaxA-mediated ITC degradation, we used five ITC-sensitive bacterial commensals and the opportunistic pathogen Pseudomonas viridiflava 3D9 (PS). All strains were isolated from healthy A. thaliana leaves. PS degrades 4-methylsulfinylbutyl-ITC (4MSOB-ITC) with SaxA. We examined commensal growth in the presence of 4MSOB-ITC, both in monoculture and in coculture with PS or a saxA-deficient mutant (PSKO). We used the growth data to develop a generalizable consumer-resource mathematical model incorporating ITC toxicity, ITC degradation, and nutrient use. We predicted and confirmed experimentally that the extent to which SaxA benefits the pathogen depends on its effects on commensals. In some contexts, commensal rescue and the resultant nutrient competition limit pathogen growth. In addition, we tested in silico how commensal ITC susceptibility, pathogen ITC degradation rates, and growth parameters affect the trade-off between SaxA-mediated virulence (strong pathogen growth) and commensal rescue (commensal growth). Our findings suggest that the effects of microbial traits—traditionally viewed as either virulence or plant-beneficial factors—are constrained in the microbiome context. This underscores the need to reconsider how such traits are classified in the context of plant-microbiome interactions.

Enhancers activate specific target promoters, but whether intrinsic enhancer-promoter compatibility contributes to this specificity is debated. Recent studies using different reporter assays have reached contradictory conclusions. We compare six reporter assay designs, identify confounders that bias compatibility measurements, and apply improved assays to test 25,000 enhancer-promoter pairs. Promoters differ in their responsiveness to enhancers (>100-fold versus 1.1-fold activation) while enhancers activate all promoters in a similar rank order. Promoter output scales with enhancer activity following a power law, with the exponent varying across promoters. Incorporating this exponent into the Activity-by-Contact model improves prediction of endogenous enhancer effects, explaining why certain active genes are insensitive to distal perturbations and "skipped" by enhancers. Responsiveness is modulated by transcription factor motifs in the core promoter. This work establishes responsiveness as an intrinsic promoter property that enables specific promoters to be highly activated in a landscape of broadly compatible enhancers, while others remain unaffected.

Organisms have continuously evolved in response to environmental conditions. Pathogenic bacteria evolve under host and environmental pressures, reshaping their genomes through insertions, inversions, deletions, and duplications during infection. In clinical settings, phenotypic traits of pathogenic bacteria such as virulence or antimicrobial resistance directly affect disease severity, transmission, and treatment. Conventional genotyping provides insights into genomic relatedness but does not always align with these clinically relevant traits, limiting its utility for phenotype-driven interventions. Here, we develop ABComp (Assembly polishing and Bacterial whole-genome Comparison for multi-group clinical isolates), a modular and Snakemake-based workflow for phenotype-driven comparative genomics. ABComp automates assembly polishing, group-wise pangenome analysis, and enables flexible pathogenic marker discovery through user-defined comparisons. We validated ABComp using a Klebsiella pneumoniae ground truth dataset stratified by yersiniabactin presence and successfully recovered the entire locus as a group-specific core marker. By applying ABComp to another dataset of clinical isolates with experimentally measured virulence, we discovered the ferric citrate (Fec) uptake system as a potential marker specific to a hypervirulent group. These results demonstrate ABComp's utility in uncovering phenotype-linked genomic markers with clinical significance, supporting targeted treatments and rapid diagnosis.

Protein self-assembly is a fundamental biological process of great importance for the design and synthesis of biomaterials. Developing the ability to precisely manipulate protein assembly would greatly expand both our understanding of the process and our biotechnological capabilities. Within bacteria, proteins that self-organize to form bacterial microcompartments (MCPs) offer an excellent model system for studying protein self-assembly and advancing biomaterial design capabilities. MCPs consist of irregular polyhedral shells that encase an enzyme core that acts as enzymatic nanoreactors. In isolation, the abundant shell proteins of the 1,2-propanediol utilization (Pdu) MCP, PduA and PduJ, have a high propensity to self-assemble into tubular structures, analogous in form to carbon nanotubes. Here, we modulate higher-order assembly of PduA and PduJ hexamers by systematically altering their charge through charge inversion and supercharging across multiple platforms including heterologous overexpression and cell-free protein synthesis. Overexpression and cell-free experiments show that increasing the overall negative charge of assembling subunits consistently promotes self-assembly into tubular structures. Using molecular simulations, we determined the preferred bending angle adopted by the hexameric proteins to predict the most probable self-assembled structures, including honeycomb-like sheets and nanotubes. Simulations of closed PduA and PduJ tubes show the interactions responsible for tube stability, chirality, and radius. In vivo, we find that these charge-altered hexamers are assembly competent within the native MCPs in Salmonella enterica LT2. Our results collectively reveal that both electrostatic interactions and fields generated by charges on proteins can be leveraged to control protein-based nanostructures.

Designing binders against novel protein targets remains a central challenge in computational drug discovery. Here we introduce BoltzProt-1, a pipeline for generating protein binders, including nanobodies, with improved hit rates and favorable developability properties. At its core lie a refined iteration of BoltzGen's generative model and a novel protein-protein interaction prediction model, BoltzPPI. Employing BoltzPPI instead of BoltzGen's standard structure-prediction confidence metrics to rank nanobody (VHH) designs increases the confirmed-binder hit rate from 3.3% to 8.0% across 10 novel targets. Assessed on 10 additional targets used in prior literature, the BoltzProt-1 pipeline obtains nanobody screening hits for 7 of 10 targets, surpassing the 6 of 10 previously reported by Chai-2. Finally, evaluating the developability of BoltzProt-1-designed nanobodies in terms of stability, aggregation, purity, polyspecificity and hydrophobicity reveals that 58% of its confirmed binders pass every criterion, exceeding both BoltzGen (40%) and clinical-stage VHH controls (21%).

The 5′ untranslated region (5′ UTR) is a key regulatory element that governs mRNA translation and protein output. However, existing computational methods typically address isolated tasks such as functional prediction or sequence optimization, limiting their ability to support rational design across the full 5′ UTR engineering workflow. Here, we present UTRGen, a unified modeling framework for 5′ UTRs that integrates sequence generation, multi-property prediction, and constrained function-guided design. UTRGen is pre-trained autoregressively on large-scale 5′ UTR datasets from multiple species and subsequently adapted to diverse downstream regulatory tasks. Across systematic evaluations, UTRGen generates novel and diverse 5′ UTRs while preserving sequence, structural, and functional characteristics of natural UTRs. After task-specific fine-tuning, UTRGen achieves state-of-the-art performance across 14 benchmark datasets, improving translation efficiency prediction by up to 11.1%, expression level prediction by up to 13.2%, and mean ribosome load prediction by up to 3.0% relative to the strongest baselines. It also achieved the best overall performance for internal ribosome entry site identification. To enable controllable design, we formulate function-guided 5′ UTR design as a GRPO-based refinement process over a pre-trained autoregressive sequence prior, using composite rewards to encode functional objectives and biological constraints while regularizing toward the natural 5′ UTR distribution. The resulting sequences show consistently improved predicted translation efficiency and expression levels across cellular contexts, and reveal interpretable sequence features associated with high activity, including reduced C content, fewer upstream AUGs, and depletion of inhibitory motifs. Together, our results establish a unified modeling strategy for 5′ UTR design and lay a foundation for programmable control of translation.

Cell-to-cell communication in microbial systems is known for its vital role in cellular signalling and gene expression. A specific form termed Quorum Sensing (QS) has received considerable attention since its discovery in the marine symbiont Aliivibrio fischeri. QS-controlled microbial functions are associated with bacterial virulence, pathogenicity, host–microbe interactions, and biofilm development. Interference in these signaling systems can modulate microbial virulence and pathogenicity, and microbial infection caused by drug-resistant pathogens. Plant-derived phytochemicals are considered a promising candidate, with coumarins emerging as significant plant-derived signalling molecules shaping microbiome dynamics and pathogen behaviors from a broad spectrum of ecosystems. Here we explored the role of natural and synthetic coumarin compounds in the control of signalling and virulence traits in Pseudomonas aeruginosa and other priority bacterial pathogens, including the fungal opportunist Aspergillus fumigatus. We uncovered an important ‘hydroxylation-bias’ favoring coumarin, umbelliferone (7-OH), and 6-hydroxy-coumarin (6-OH) in the specific competitive inhibition of the Pseudomonas Quinolone Signal (PQS), associated with reduced activity of a PqsR translational fusion and suppression of pyocyanin production. Conversely, while esculetin (6,7-OH) was most effective at Acyl Homoserine Lactone (AHL) QS biosensor inhibition, it did not affect PQS production. Anti-biofilm activity of coumarins against P. aeruginosa was independent of initial attachment but linked to changes in exopolysaccharide production. As the very real threat posed by antimicrobial resistance persists, these data support a role for phytochemicals such as coumarins in delivering an ecological solution to dysbiosis in the host–microbe interaction.

Horizontal gene transfer (HGT) shapes bacterial evolution and microbial ecosystems, yet detecting HGT within microbiomes remains a challenge due to fragmented metagenomic assemblies, reference bias, reliance on gene boundaries, and limited ability to model structural mosaicism and patterns across genomes. We present Kente, a novel pangenome graph-based framework designed for HGT detection that aligns metagenomic assembly contigs to a curated database of >600 genus-level bacterial pangenome graphs constructed using minigraph. Kente infers local taxonomic composition along contigs using alignment evidence and classifies candidate transfers using structured clade-transition topologies (e.g., A-B-A sandwich, open tips, and mosaic patterns). A complementary intra-genus module detects inter-species transfers within a single genus graph using segment-level clade annotations. Across simulated intra- and inter-genus transfer scenarios, Kente achieves higher precision and comparable recall relative to existing gene-centric microbiome HGT detection approaches while reducing false positives from fragmented assemblies. Application to real human gut metagenomes (HMP2, n = 26) demonstrates Kente's ability to detect candidate cross-lineage transfer regions in complex microbial communities. Runtime profiling shows near-linear scaling with input size, enabling efficient analysis of large metagenomic assemblies. Availability and Implementation: https://github.com/treangenlab/Kente

Bacteria in natural environments frequently encounter nutrient limitation leading to growth arrest and must balance the potential benefits of continuing to respond to the environment by making new proteins against the costs of depleting limited resources. We previously showed that the RNA polymerase-binding regulator SutA enhances transcription of hundreds of genes during nutrient limitation in Pseudomonas aeruginosa, suggesting that it might be part of a regulatory network facilitating limited new protein synthesis. Here, we sought to expand our understanding of this network by identifying transcriptional regulators influencing sutA expression. Using northern blotting, western blotting, and reporter assays, we found that the sigma factors FliA and RpoS, and the DNA-binding regulator Lrp, impact expression from a proximal sutA promoter during the transition to stationary phase. This constellation of regulators and the dynamics of SutA expression lead us to propose that SutA is part of a regulatory network that facilitates scavenging. Scavenging includes motility toward possible nutrient sources and uptake mechanisms for these nutrients, activities which require an investment of resources but can yield important benefits during starvation. In vitro transcription experiments, proteomic analysis and reporter assays suggest that SutA directly supports new protein synthesis driven by RpoS and indirectly supports flagellar motility, perhaps by helping maintain protein biosynthetic capacity against the metabolic costs of motility. SutA expression is controlled by multiple regulatory inputs, including negative autoregulation, and the protein appears to be short-lived. These properties are consistent with a role in supporting short, controlled bursts of gene expression during nutrient limitation.

Genetic diversification serves as the foundation for in vivo molecular evolution. The fusion of a cytidine deaminase with T7 RNA polymerase (MutaT7) enables efficient diversification of DNA sequences downstream of the T7 promoter in model microbial hosts E. coli and S. cerevisiae. Vibrio natriegens, currently the fastest-growing nonpathogenic bacterium with a doubling time half that of E. coli, emerged as a promising alternative chassis for synthetic biology. Here, we report the establishment of MutaT7 in V. natriegens (dubbed VnMutaT7), achieving rapid evolution of the model protein TEM-1 to confer high-level ceftazidime resistance in just 36 h. This work establishes the potential of V. natriegens as an accelerated platform for protein engineering.