Bacterial pathogenicity arises from complex genetic interactions that are difficult to characterise through single-gene deletions. CRISPR base editors can generate multiplexed gene knockouts, yet this technology remains unexplored for dissecting bacterial pathogenicity. Here, we developed a base-editing pipeline for multi-gene knockouts while revealing that target-independent editing can contribute to variability in clonal fitness. In the model pathogen Salmonella Typhimurium, we employed curable plasmids containing a cytidine deaminase base editor and a multi-spacer CRISPR array to introduce premature stop codons in up to nine genes encoding SPI-2 T3SS effector proteins. Target bases were efficiently edited, producing a multi-knockout strain that showed reduced virulence in vivo relative to single knockouts. However, whole-genome sequencing revealed off-target cytidine deaminase activity, which affected virulence in vivo in a clone-dependent manner. A statistical power analysis predicted how many edited mutants are needed to confidently measure fitness functions in the face of off-target mutations. Our work shows the potential and current limitations of multiplexed base editing in bacterial pathogens and highlights the need for properly addressing off-target mutations when deploying base editors to interrogate genotype-phenotype relationships.

In multicellular systems, organized phenotypic heterogeneity emerges from the interplay of processes spanning scales from molecular to population-level. Using Bacillus subtilis, we investigated feedback between the collective process of colony expansion and the distribution of spore development among individual cells, a process triggered by starvation. Biofilms are commonly studied using a strain with inhibited sporulation. Intact regulation yielded high-frequency sporulation early in biofilm growth. Biofilm composition was organized by a wave of sporulation driving biofilms toward dormancy from within. However, expansion was also maintained by non-sporulating cells in a narrow front at the external edge. Along with mathematical modeling, we also used mutants with altered biofilm morphogenesis to probe the relationship between colony expansion and sporulation. Sporulation dynamics were patterned by radial expansion, but the faster biofilms spread, the greater the separation of growth and sporulation distributions. We demonstrate essential interplay between cell behavior and the physics of collective expansion that organizes differentiation among cells.

The rapidly growing universe of predicted protein structures offers opportunities for data driven exploration but requires computationally scalable and interpretable tools. We developed a method to detect catalytic features in protein structures, providing insights into enzyme function and mechanism. A library of 6780 3D coordinate sets describing enzyme catalytic sites, referred to as templates, has been collected from manually curated examples of 762 enzyme catalytic mechanisms described in the Mechanism and Catalytic Site Atlas. For template searching we optimized the geometric-matching algorithm Jess. We implemented RMSD and residue orientation filters to differentiate catalytically informative matches from spurious ones. We validated this approach on a non-redundant set of high quality experimental (n=3751, <40% amino acid identity) enzyme structures with well annotated catalytic sites as well as predicted structures of the human proteome. We show matching catalytic templates solely on structure is more sensitive than sequence- and 3D-structure-based approaches in identifying homology between distantly related enzymes. Since geometric matching does not depend on conserved sequence motifs or even common evolutionary history, we are able to identify examples of structural active site similarity in highly divergent and possibly convergent enzymes. Such examples make interesting case studies into the evolution of enzyme function. Though not intended for characterizing substrate-specific binding pockets, the speed and knowledge-driven interpretability of our method make it well suited for expanding enzyme active-site annotation across large predicted proteomes. We provide the method and template library as a Python module, Enzyme Motif Miner, at https://github.com/rayhackett/enzymm.

The greening of electronics remains a grand societal challenge, with no radical improvement within sight. Sustainable solutions for electronics, such as biobased and transient materials, are hence receiving growing attention. Presently, there are no biobased alternatives to conventional conductors such as metals and organic polymers, as their conductivity is too low. The discovery of cable bacteria, which are filamentous microorganisms capable of conducting electricity over centimeter-scale distances, has the potential to change this. In cable bacteria, conductivity occurs through thin wires embedded in the cell envelope, displaying conductivities comparable to those of the best highly doped organic polymers. However, exposure to ambient air leads to a gradual loss of their conductivity. To enhance stability, a bioderived protective coating could be useful, thus retaining a fully biobased system. To this end, we investigated pullulan, a polysaccharide polymer primarily used in food packaging that is known for its excellent oxygen-barrier properties. Cable bacterium filaments protected with a film derived from a 10 wt % pullulan solution exhibited a 10-fold increase in conduction stability under ambient conditions compared to uncoated controls. Reducing ambient moisture also preserved the long-term conductivity of the cable bacteria, even in the absence of a protective coating, indicating that humidity plays a critical role in conductance deterioration. Our findings provide an important step toward further technological implementation of the highly conductive wires of cable bacteria and offer practical guidelines for developing biobased coatings for O2-sensitive materials in electronics, thus contributing to the advancement of next-generation green technologies.

Natural products (NPs) produced by actinobacteria, particularly Streptomyces species, represent a rich source of bioactive compounds and have yielded many clinically important compounds. Actinobacterial genomes are characterized by high GC content and typically harbor 20–40 biosynthetic gene clusters (BGCs) per genome, which encode diverse NPs such as polyketides, peptides, and glycosides. CRISPR/Cas-based genome editing has emerged as a promising tool to activate silent BGCs and engineer NP biosynthesis. However, the efficiency of multiplex editing drastically decreases as the number of targeted sites increases. Here, we report a novel one-pot DNA assembly method, termed direct pathway synthesis and editing (DiPaSE), for the efficient synthesis and multiplex editing of long, high-GC BGCs. DiPaSE accurately assembles multiple high-GC DNA fragments up to 60 kb and enables simultaneous deletions and insertions within a target BGC without compromising the assembly efficiency. Using this approach, we identified functions of previously uncharacterized genes in the aureothin BGC and significantly enhanced the titer of the corresponding NP. The workflow employs conventional polymerase chain reaction, type IIP restriction enzymes, commercially available DNA assembly reagents, and E. coli, providing a simple, cost-effective, and broadly applicable platform for genome mining, BGC refactoring, and rational design of artificial biosynthetic pathways.

The skin microbiome, consisting of a vast array of microorganisms, is essential for human skin health, aiding in barrier protection, immune regulation, wound repair, and defense against pathogens. Disruptions in this microbial balance are closely linked to the onset and worsening of various skin disorders. This review evaluates the potential of skin microbiome engineering as a therapeutic strategy for treating skin diseases. We discuss nontargeted approaches like probiotics and fecal microbiota transplantation that aim to reshape the microbial community, as well as targeted methods such as phage therapy, phage lysins, and engineered bacteria, which specifically modulate microbial populations or influence the skin environment. These approaches open new avenues for personalized dermatological treatments. Despite significant progress, challenges remain in the clinical translation of microbiome-based therapies. Safety, standardization, regulatory approval, and long-term ecological stability must be addressed to ensure efficacy and reproducibility in clinical settings, underscoring the critical need for further research in their dermatological applications.

Advances in metagenomic sequencing over the past two decades have identified vast numbers of previously uncharacterised small open reading frames that may encode microproteins (<50aa). Although computational tools have accelerated gene sequence prediction from metagenomic data, the function of most annotated proteins remains unknown and untested, especially in the context of host-microbiome interactions. Here, we present a scalable phenotypic screening pipeline to identify gut microbiome-derived proteins that modulate host function. Using the nematode worm Caenorhabditis elegans as a whole animal model that is amenable to systematic screening approaches, our pipeline integrates high-throughput cloning, expression and delivery to worms via feeding, followed by behavioral phenomics screening. We apply this approach to a pilot library of 126 uncharacterised microproteins (< 50 aa) from healthy human gut metagenomes, identifying a set of high-interest targets with potential activity and ultimately validating a microprotein that modulates host fatty acid metabolism when expressed. With protein-based therapies increasingly recognised as a promising alternative to traditional small molecules, this work highlights the potential of a target-agnostic approach for the systematic screening and discovery of novel bioactive proteins.

The inherent barriers posed by bacterial outer membranes, efflux pumps, and biofilm matrices significantly limit the clinical efficacy of antimicrobial agents, underscoring the urgent need for strategies to enhance drug penetration. Integrating pathogen-specific exogenous nutrients with conventional antibiotics has emerged as a promising approach, facilitating the targeted delivery and enhanced efficacy of antimicrobial compounds. In this study, we aimed to improve antimicrobial efficacy by enhancing transmembrane transport. First, we comprehensively compared various genome-scale metabolic reconstruction methods to identify the optimal approach. Subsequently, we enhanced our previous approach to identify exogenous nutrients by integrating topological screening, flux scoring, and chemical structure analysis. Key exogenous nutrients were identified for three pathogens: urea for Acinetobacter baumannii, acetamide for Pseudomonas aeruginosa, and succinic acid for Salmonella enterica. Growth assays confirmed that these nutrients significantly promoted bacterial proliferation. Leveraging these findings, four novel antimicrobial compounds (NC, NA, MA, and MN) were synthesized by conjugating membrane-resistant nalidixic acid or magnolol with the respective nutrients. MN enhanced the antimicrobial activity against wild-type S. enterica by 56.5%, while MA and NA boosted the activity against wild-type P. aeruginosa by 51.4% and 70.4%, respectively. Moreover, NC improved efficacy against drug-resistant A. baumannii by fourfold. These results demonstrate that conjugating exogenous nutrients with antibiotics can effectively enhance antimicrobial activity and help overcome membrane-associated resistance. This nutrient-conjugation strategy offers a promising avenue for developing new antimicrobial agents.

Biomolecular condensates formed via liquid-liquid phase separation (LLPS) play vital roles in cellular organization and function. Computational prediction of phase-separating proteins (PSPs) is increasingly used to prioritize candidates at proteome scale, making robust, well-designed benchmarks essential for fair evaluation and iterative improvement of PSP predictors. We first show that a recently released PSP benchmark is substantially confounded by the imbalances in taxonomic origin and intrinsic-disorder compositions between positive and negative sets, allowing predictors to achieve high apparent performance by exploiting non-LLPS shortcuts and obscuring their true ability to distinguish PSPs. To minimize these effects, we construct a taxonomy-aware, disorder-matched PSP benchmark. Using this benchmark, we find that absolute sequence and biophysical feature values of PSPs differ markedly across taxa, whereas LLPS-associated feature shifts relative to taxon-specific proteome backgrounds are comparatively conserved. Benchmarking twenty PSP predictors under this framework reveals pronounced taxon-dependent variation in performance. Moreover, PSPs lacking IDRs consistently constitute a more challenging regime across methods, motivating routine disorder-stratified evaluation. Our taxonomy-aware, disorder-matched benchmarking framework reduces shortcut-driven biases, enables more interpretable evaluation of PSP predictors, and provides guidance for developing models that capture transferable LLPS-associated signals rather than dataset- or taxon-specific shortcuts.

Fungal secondary metabolites have historically provided important applications in a variety of industries. Penicillium camemberti, a fungus with a role in cheese production, was domesticated to food use partly due to its metabolically depleted characteristic, minimizing the risk of toxic compound formation. However, antiSMASH analysis of the genome reveals that strains of the species do contain various cryptic biosynthetic gene clusters and, thus, have the potential capability of producing multiple secondary metabolites despite its limited compound production under normal laboratory conditions. Here, we genetically engineered Penicillium camemberti strain IMV00769, which is genetically similar to cheese-making isolates, by deleting negative global regulator, mcrA. This deletion resulted in the production of secondary metabolites not previously produced by this strain, including fumigermin, a compound patented for cosmetic applications for the reduction of skin wrinkles, enhancement of skin elasticity, and skin whitening. Our findings highlight the power of global regulator manipulation to activate cryptic biosynthetic pathways and expand the range of natural products accessible from domesticated fungal strains.