Untargeted tandem mass spectrometry (MS/MS)-based metabolomics enables broad characterization of small molecules in complex samples, yet the majority of spectra in a typical experiment remain unannotated, limiting biological interpretation. Reference data-driven (RDD) metabolomics addresses this gap by contextualizing spectra through comparison to curated, metadata-annotated reference datasets, allowing inference of spectrum origins without requiring exact structural identification. Here, we present an open-source RDD metabolomics platform comprising a user-friendly web application and a Python software package that perform RDD analyses directly from molecular networking outputs generated by GNPS. The tools support visualization and statistical analysis of RDD results, including interactive bar plots, heat maps, principal component analysis, and Sankey diagrams. We illustrate the approach using a hierarchical reference dataset of 3,500 food items to derive dietary patterns from stool metabolomics data of omnivore and vegan participants. The analysis reveals clear dietary group separation, demonstrating how RDD metabolomics can extract biologically meaningful patterns from otherwise unannotated spectra. Thus, the RDD metabolomics platform removes technical barriers for the metabolomics community to adopting reference data-driven analysis, with the functionality freely available at https://github.com/bittremieuxlab/gnps-rdd and https://gnps-rdd.streamlit.app/.

In Escherichia coli, RNase E, a central enzyme in RNA processing and mRNA degradation, contains a catalytic N-terminal domain, a membrane-targeting sequence (MTS), and a C-terminal domain (CTD). We investigated how MTS and CTD influence RNase E localization, diffusion, and function. Super-resolution microscopy revealed that ~93% of RNase E localizes to the inner membrane and exhibits slow diffusion similar to polysomes. Comparing the native amphipathic MTS with a transmembrane motif showed that the MTS confers slower diffusion and stronger membrane binding. The CTD further slows diffusion by increasing mass but unexpectedly weakens membrane association. RNase E mutants with partial cytoplasmic localization displayed enhanced co-transcriptional degradation of lacZ mRNA. These findings indicate that variations in the MTS and the presence of the CTD shape the spatiotemporal organization of RNA processing in bacterial cells, providing mechanistic insight into how RNase E domain architecture influences its cellular function.

The emergence of eukaryotes from a merger between an archaeon and a bacterial cell ~two billion years ago involved a profound change in cellular organization. While the order in which different features of the eukaryotic cell arose remains a matter of controversy, close archaeal relatives of eukaryotes have recently been identified that possess homologues of eukaryotic trafficking machinery and a complex cell architecture. The members of this phylum, the Asgard archaea (syn. Prometheoarchaeota) described so far, however, lack internal membrane-bound compartments, and therefore have shed little light on origins of the hallmark eukaryotic endomembrane system. Here we report the cell biological analysis of a member of the Heimdallarchaeia, Candidatus "Yibarchaeum umbracryptum" in enriched mixed microbial communities. Possessing a small genome encoding few homologues of eukaryotic membrane remodelling machinery, Ca. Y. umbracryptum cells in late-stage cultures resemble previously described Asgard archaea with extensive cellular protrusions. Surprisingly, during early stages of culture growth Ca. Y. umbracryptum cells have fewer protrusions but possess numerous intracellular vesicles, most of which have a luminal surface that morphologically resembles the outer coat of the plasma membrane. These data alter our view of eukaryogenesis by identifying a close archaeal relative of eukaryotes with a regulated endomembrane system.

Electron transfer coupled to redox chemistry is at the heart of metabolism. The proteins responsible for moving electrons (protein electron carriers) must have emerged at the origin of life. The small iron–sulfur-binding bacterial ferredoxins were likely among these first proteins. Embedded within the ferredoxin sequence and structure is a symmetry that points to an ancient gene duplication event. Little is understood about the nature of ferredoxins prior to this duplication event or what environmental factors may have driven the selection for more complex forms. The deep-time molecular history of ferredoxins goes back billions of years and cannot be reconstructed by phylogenetic analyses based on amino acid sequences. Here, we use structure-guided protein design to model a fossil half-ferredoxin stage in the evolution of this fold, the semidoxins, and their symmetric full-length counterparts, the symdoxins. Semidoxin designs homodimerize, exhibiting structural, thermodynamic, and electrochemical behaviors in most cases identical to cognate symdoxins. However, the semi- and symdoxin fossil stages behave differently when incorporated into an in vivo electron transfer complementation assay. Both can support bacterial growth dependent on protein expression. Growth rates of bacteria expressing the semidoxins are much more sensitive to oxygen than those of bacteria expressing symdoxins. Motivated by the in vivo functionality of designed semidoxins, we identified putative naturally occurring semidoxins in extant anaerobic microorganisms. This is consistent with the observed in vivo oxygen sensitivity of the semidoxin designs. One natural semidoxin is shown to be folded and redox active. However, it exists as a mixture of monomers and dimers, suggesting a potential connection between semidoxins and even simpler single iron–sulfur cluster-binding peptides.

Surfactin, a lipopeptide antibiotic and quorum-sensing (QS) mediator from Bacillus subtilis, has dual functions in microbial ecology and plant disease suppression. This study engineered B. subtilis R31 to overproduce comK and phrC, key regulators of surfactin biosynthesis, increasing surfactin yield by 45% compared to the WT strain. While elevated surfactin enhanced antimicrobial potential, comK-mediated overproduction impaired biofilm formation and swarming motility, but rhizosphere colonization was mostly unaffected. 16S rRNA sequencing of banana rhizospheres showed that surfactin selectively shaped the microbial community by enriching beneficial Bacillus species. Mechanistic studies confirmed surfactin's dual role as an antimicrobial and an intercellular signalling molecule for coordinated development in Bacillus populations. These results reveal the molecular mechanisms of R31-mediated suppression of banana Fusarium wilt and offer a strategy for engineering synthetic microbial consortia by manipulating metabolic signalling pathways.

Complex microbial ecosystems harbor extensive intra-species diversity, but the fitness consequences of this genetic variation are poorly understood in community settings. Here we address this question by competing in vitro gut communities derived from different human donors, revealing the emergent fitness differences between conspecific strains as they competed within larger communities. Most pairs of strains experienced strong and context-dependent selection, even when their parent communities were originally selected in the same nutrient environment. However, these fitness differences typically attenuated over time due to biotic interactions within the community, leading to extended coexistence within many species, and competitive exclusion in others. These results support the view that conspecific strains can fulfill distinct ecological roles when competing within a diverse community, even when their genomic diversity exhibits the hallmarks of a single biological species.

Natural products are a major source of bioactive compounds, yet elucidating their biosynthetic pathways remains a major challenge due to complex genotype–phenotype relationships. Recent advances in computational approaches, particularly artificial intelligence (AI) and mechanistic modeling, are transforming this field. This highlight examines key databases that underpin computational studies, AI-driven methods for predicting biosynthetic pathways and enzyme–substrate interactions, and mechanistic simulations that provide energetic and structural insights. We also discuss current challenges and future opportunities for integrating these strategies to accelerate discovery, engineering, and application of natural products in drug discovery, biotechnology, and synthetic biology.

A synthetic cell is a membrane-bound vesicle that encapsulates cell-free transcription/translation (TXTL) systems. It represents a transformative platform for advancing bacteriophage therapy. Building on experimental work that demonstrates (i) modular genome assembly, (ii) high-yield phage TXTL systems, and (iii) smart hydrogel encapsulation, we explore how synthetic cells can address major limitations in phage therapy. The promising advances include point-of-care phage manufacturing, logic-responsive antimicrobial biomaterials, and new chassis to dissect the dynamics of phage-host interactions. We also propose a roadmap for the deployment of synthetic cells as programmable and evolvable tools in the context of laboratory research and translational clinical adoption. droplet