Carboxysomes are polyhedral protein organelles that microorganisms use to facilitate carbon dioxide assimilation. They are composed of a modular protein shell that envelops an enzymatic core mainly composed of physically coupled Rubisco and carbonic anhydrase. While the modular construction principles of carboxysomes make them attractive targets as customizable metabolic platforms, their size and complexity can be a hindrance. In this work, we design and validate a plasmid set, the pXpressome toolkit, in which α-carboxysomes are robustly expressed and remain intact and functional after purification. We tested this toolkit by introducing mutations that influence carboxysome structure and performance. We find that deletion of vertex-capping genes results in formation of larger carboxysomes, while deletion of facet forming genes produces smaller particles, suggesting that adjusting the ratio of these proteins can rationally affect morphology. Through a series of fluorescently labeled constructs, we observe that this toolkit leads to more uniform expression and better cell health than previously published carboxysome expression systems. Overall, the pXpressome toolkit facilitates the study and redesign of carboxysomes with robust performance and improved phenotype uniformity. The pXpressome toolkit will support efforts to remodel carboxysomes for enhanced carbon fixation or serve as a platform for other nanoencapsulation goals.

Plant growth-promoting rhizobacteria (PGPR) represent a sustainable method to improve crop productivity. Synthetic microbial consortia have emerged as a powerful tool for engineering rhizosphere microbiomes. However, designing functionally stable consortia remains challenging due to an insufficient understanding of bacterial social interactions. In this study, we investigated the effects of Bacillus velezensis SQR9 (i.e., a commercially important PGPR) on social interactions within the rhizosphere community, particularly among Bacillus species. SQR9 inoculation significantly enhanced cucumber plant growth and altered the structure of rhizosphere Bacillus and its related bacterial communities. The results of swarm boundary and carbon utilization assays, revealed that phylogenetically closer Bacillus strains exhibited increased social cooperation and increased metabolic niche overlap. Building on these social interactions, we designed 30 consortia comprising both highly related (HR) and moderately related (MR) types across four richness levels (1, 2, 3, and 4 strains), with MR consortia demonstrating superior PGP effects through enhanced plant growth, root colonization, indole-3-acetic acid production, and siderophore production, than the HR consortia. Expanding these findings to 300 consortia across four richness levels (1, 2, 4, and 8 strains) confirmed enhanced PGP effects in MR consortia with increasing richness. These findings highlight the importance of bacterial interactions and phylogenetic relationships in shaping rhizosphere communities and designing synthetic microbial consortia. Specifically, this study provides a framework for assembling Bacillus consortia that enhance cooperation, which would aid in improving their stability and effectiveness in agricultural applications.

Plants participate in intricate interactions with a multitude of microorganisms, many of which also influence each other. This holobiont is situated in a chemical soil environment that is defined, in parts, by the specialized metabolite legacy of proximal and preceding organisms, including other plants. Here, we investigated the influence of external plant-derived specialised metabolites on the interactions among root-associated bacterial strains, and between these strains and a plant host. Using benzoxazinoids and their derivatives as a model in both simplified pairwise experiments and more complex multi-organism analyses, we show that these chemicals can modulate bacteria-bacteria, as well as bacteria-plant interactions. While the chemical environment alone had little effect on the plant at the molecular level, it differentially affected plant chemical defences, immunity, and sugar transport when combined with single-isolate or micro-community inoculums. Our study underlines the importance of the chemical environment in modulating organismic interactions and illustrates the value of combining reduced-complexity, bottom-up reconstruction approaches with top-down holobiont profiling.

Enhancing acid tolerance of industrial microorganisms is critical for improving fermentation efficiency and sustainability. This study presents a synthetic biology approach that employs toehold switch-based acid-tolerance modules to engineer acid-tolerant strains. This toehold switch-based approach enables the construction of modules consisting of a trigger block and a switch block, generating a synthetic module library of ~105 constructs that integrate four acid-responsive promoters and 18 acid-resistance genes. Through stepwise evaluation, we identified two best synthetic modules, RE-6 and RE-38, which enabled an industrial lysine-producing strain to maintain lysine titers and yields at pH 5.5 comparable to those observed in the parent strain at pH 6.8. Transcriptional analyses revealed that upregulation of key acid-resistance genes involved in protein quality control, reactive oxygen species scavenging and redox homeostasis contributed to the enhanced acid tolerance of the engineered strains. Our study offers a powerful toehold switch-based approach for constructing synthetic modules of interest, particularly for enhancing the robustness and productivity of industrial strains.

In Saccharomyces cerevisiae, glucose depletion induces metabolic reprogramming through widespread transcriptional and translational reorganization. We report that initial, very rapid translational silencing is driven by a specialized metabolic mechanism. Following glucose withdrawal, intracellular NTP levels drop drastically over 30 sec, before stabilizing at a regulated, post-stress set-point. Programmed translational control results from the differential NTP affinities of key enzymes; ATP falls below the (high) binding constants for DEAD-box helicase initiation factors, including eIF4A, driving mRNA release and blocking 80S assembly. Contrastingly, GTP levels always greatly exceed the (low) binding constants for elongation factors, allowing ribosome run-off and orderly translation shutdown. Translation initiation is immediately lost on all pre-existing mRNAs, before being preferentially re-established on newly synthesized, upregulated stress-response transcripts. We conclude that enzymatic constants are tuned for metabolic remodeling. This response counters energy depletion, rather than being glucose-specific, allowing hierarchical inhibition of energy-consuming processes on very rapid timescales.

There is a critical gap in the development of new therapeutic platforms designed to treat gynecologic and obstetric diseases. Compared to systemic drug delivery, vaginal drug administration of nanoparticle formulations limits off-target side effects while increasing therapeutic concentration in target tissues, showing promise for clinical translation. However, these formulations suffer from limited scalability, high-cost reagents, and long optimization timelines. Recent work highlights the potential of bacterial extracellular vesicles (bEVs) as a low-cost, tunable platform for therapeutic applications. Here, we evaluate bEVs as a therapeutic carrier for vaginal drug delivery. We demonstrate the loading of the model protein moxNeonGreen into Escherichia coli Nissle 1917 bEVs. By optimizing growth parameters, we increase protein loading into bEVs. We evaluate the effect of bEVs on the vaginal microenvironment, and observe no negative impact on vaginal epithelial cells, endocervical cells, or vaginal bacteria in vitro. Additionally, we observe the retention of bEVs in the murine female reproductive tract for more than six hours. This study provides a framework for using genetically engineered bEVs to rapidly generate customizable therapies for a range of gynecologic and obstetric conditions, addressing longstanding challenges in women's health therapeutics. omv

The secondary metabolites produced by the gut microbiota serve as crucial signaling molecules and substrates for gastrointestinal metabolic reactions, thereby playing a pivotal role in human physiological and pathological processes. In this study, we explore the complex symbiotic relationship between the gut microbiota and the human host by systematically annotating the biosynthetic gene clusters (BGCs) across 4,744 human gut microbiota genomes, sourced from the Unified Human Gastrointestinal Genome database. Our comprehensive analysis compares the differential biosynthetic potentials of microbiota from diverse continents and phyla while also elucidating the biosynthetic profiles of gut archaea. Notably, our findings identify Paenibacillus as a dominant genus within the human gut microbiota, characterized by its extensive biosynthetic capacity. This study presents the first global atlas of BGCs within the human gut microbiome, offering valuable insights into gut-derived secondary metabolic pathways and their intricate interactions with host physiology. These results lay the groundwork for future investigations into the microbiota’s role in health and disease, underscoring the importance of understanding microbiota-derived metabolites in microbiology and gastroenterology.

Vitamin B12 metabolism differs among members of the Mycobacterium genus. While non-tuberculous mycobacterial species are B12 producers, tuberculous mycobacteria lack endogenous production and rely on the host supply of this vitamin. Here, we hypothesise that this discrepant phenotype might impact the function of B12-dependent enzymes. We specifically focused on methionine synthases MetH and MetE. Both enzymes showed genetic differences in the Mycobacterium genus, resulting in a clear divergence between tuberculous and non-tuberculous species. Unexpectedly, the dependency of MetH on B12 was indistinguishable between M. tuberculosis and M. smegmatis, assayed as representative members of tuberculous and non-tuberculous species, respectively. However, MetE showed robust phenotypic differences between these species, displaying a finely tuned B12 regulation in M. tuberculosis, in contrast to a more permissive regulation in M. smegmatis. Both orthologs differ in the vitamin isoform specifically recognized, and the B12 threshold level required for MetE regulation. Since the B12 regulatory element in the metE gene is an RNA riboswitch, we analysed the polymorphisms in this region, with a special focus on loss-of-function mutations identified after in vitro selection. We used this information to engineer a whole-cell B12 biosensor in the genetically fastidious Mycobacterium genus, being able to detect vitamin B12 concentration in the range of micrograms per millilitre.

Mobile genetic elements (MGEs) play a critical role in shaping the response and evolution of microbial populations and communities. Despite distinct maintenance mechanisms, different types of MGEs can form nested structures. Using bioinformatics analysis of 14,338 plasmids in the NCBI RefSeq database, we found transposons to be widespread and significantly enriched on plasmids relative to chromosomes, highlighting the prevalence of transposon-plasmid nesting. We hypothesized that this nested structure provides unique adaptive advantages by combining transposition-driven genetic mobility with plasmid-mediated copy number amplification. Using engineered transposon systems, we demonstrated that nesting enables rapid and tunable responses of transposon-encoded genes in fluctuating environments. Specifically, transposition maintains a reservoir of the encoded genes, while plasmid copy number fluctuations further amplify the dynamic range of gene dosage, thus enhancing the response speed and stability of transposon-encoded traits. Our findings demonstrate an adaptive benefit of transposon-plasmid nesting and provide insights into their ecological persistence and evolutionary success.

Accurate prioritization of near-native protein-protein interaction (PPI) models remains a major bottleneck in structural biology. Here we present SAKE-PP, a physics-inspired, spatial-attention equivariant graph neural network that directly regresses interface RMSD (iRMSD) without any native references. Trained on docking decoys generated through our novel hierarchical sampling strategy applied to the PDBBind dataset, SAKE-PP combines force-field-like attention with Laplacian-eigenvector orientation to couple local interaction forces with global topology. On the 2024PDB benchmark comprising 176 heterodimers, SAKE-PP demonstrates effective optimization and selection of AF3 decoys, achieving improvements of 13.75% based on iRMSD statistics and 12.5% based on DockQ scores. It consistently outperforms the AF3 ranking score across multiple metrics, including overlap, hit rate, and correlation. In zero-shot evaluation of 139 antibody-antigen complexes, SAKE-PP increases the score-iRMSD correlation by 0.4. By unifying geometric deep learning with physics-based realism, SAKE-PP provides a robust, plug-and-play scoring function that streamlines reliable PPI evaluation and accelerates downstream structure-guided drug-design workflows.