Mixotrophy offers a promising strategy for biosynthesis by simultaneously utilizing organic carbon and CO2; however, mixotrophic microorganisms are rarely isolated outside of photoautotrophic microalgae. In this study, the chemoautotroph Cupriavidus necator H16 was found to preferentially consume fructose when coexisting with CO2 and H2, switching to utilization of only CO2 and H2 after fructose depletion. Transcriptomic analysis revealed significant differences in genes involved in energy metabolism, electron generation, and the respiratory chain. The molecular mechanism underlying the inability of C. necator H16 to simultaneously utilize carbohydrates and CO2 was identified as the suppression of hydrogenase expression in the presence of fructose. By inducing regulator hoxA to activate hydrogenase expression, an engineered C. necator strain capable of mixotrophic growth was developed. This engineered strain can simultaneously utilize fructose, CO2, and H2, maintain optimal growth, and approach carbon-neutral cultivation. This work provides insights for the mixotrophic cultivation of C. necator and serves as a reference for developing mixotrophic microorganisms in future studies.

Invasive fungal infections claim over two million lives annually, a problem exacerbated by rising resistance to current antifungal treatments and an increasing population of immunocompromised individuals. Despite this, antifungal drug development has stagnated, with few novel agents and fewer novel targets explored in recent decades. Here, we validate acetolactate synthase (ALS), an enzyme critical for branched-chain amino acid biosynthesis and absent in humans, as a promising target for new therapeutics. Using resistance gene-guided genome mining, we discovered a biosynthetic gene cluster BGC in Aspergillus terreus encoding HB-35018 (1), a novel spiro-cis-decalin tetramic acid that potently inhibits ALS. Biochemical and antifungal assays demonstrate that 1 surpasses existing ALS inhibitors in efficacy against Aspergillus fumigatus and other pathogenic fungi. Structural studies via cryo-electron microscopy reveal a unique covalent binding interaction between compound 1 and ALS, distinct from known inhibitors, and finally, we demonstrate that ALS is essential for virulence in a mouse model of invasive aspergillosis. These findings position ALS as a promising target for antifungal development and demonstrate the potential of resistance gene-guided genome mining for antifungal discovery.

Glycosyltransferases (GTs) catalyze the formation of new glycosidic bonds and thus are vital for synthesizing nature's vast repertoire of glycans and glycoconjugates and for engineering glycan-related medicines and materials. However, obtaining detailed structural and functional insights for the >750,000 known GTs is limited by difficulties associated with their efficient recombinant expression. Members of the GT-C fold, in particular, pose the most significant expression challenges due to the integration and folding requirements of their multiple membrane-spanning regions. Here, we address this challenge by engineering water-soluble variants of an archetypal GT-C fold enzyme, namely the oligosaccharyltransferase PglB from Campylobacter jejuni (CjPglB), which possesses 13 hydrophobic transmembrane helices. To render CjPglB water-soluble, we leveraged two advanced protein engineering methods: one that is universal called SIMPLEx (solubilization of IMPs with high levels of expression) and the other that is custom tailored called WRAPs (water-soluble RFdiffused amphipathic proteins). Each approach was able to transform CjPglB into a water-soluble enzyme that could be readily expressed in the cytoplasm of E. coli cells at yields in the 3-6 mg/L range. Importantly, solubilization was achieved without the need for detergents and with retention of catalytic function. Collectively, our findings demonstrate that both SIMPLEx and WRAPs are promising platforms for advancing the molecular characterization of even the most structurally complex GTs, while also enabling broader GT-mediated glycosylation capabilities within synthetic glycobiology applications.

Microorganisms colonize all environments on Earth, yet it remains unclear which taxa merely broadly persist and which consistently outperform others across environments. Here we introduce the Baas-Becking score (BB-score), a performance metric to rank taxa across communities that integrates occupancy, relative abundance, and penalized absences. Applying BB-scores to 576,531 microbial communities spanning 24 biomes (categorized as either host-associated or free-living), we found that most species-level operational taxonomic units (OTUs) were widespread, but their success was substantially more restricted. Although 64% of OTUs were detected in at least one host-associated and one free-living biome, only six taxa ranked within the top 1% of performers in >50% of biomes: Aerococcus viridans, Faucicola (previously: Moraxella) osloensis, Lawsonella clevelandensis, Methylorubrum populi, Sphingobium yanoikuyae, and Pseudomonas fluorescens complex. These globally successful taxa were present in a quarter of all airborne communities, consistent with the atmosphere acting as a dispersal corridor. Network analysis of shared top 5% performers identified the phyllosphere and freshwaters as hubs linking animal-associated, plant-associated, and soil biomes. BB-score provides a scalable framework to map microbial success across Earth's biomes and to put new focus on globally successful yet woefully understudied taxa.

CRISPR-Cas9 is natively present in the adaptive immune systems of a multitude of bacteria and has been adapted as an effective genome engineering tool. The Cas9 effector enzyme, which is composed of a single Cas9 protein and a single-guide RNA (sgRNA), identifies and cleaves double-stranded DNA targets through a series of conformational changes that require DNA distortion and unwinding. While most studies of Cas9 specificity have focused on the DNA sequence, the role of intrinsic DNA physical properties (“DNA shape”) in modulating Cas9 activity remains insufficiently defined. We previously showed that with a 16-nucleotide (-nt) truncated guide, the intrinsic DNA duplex dissociation energy at the PAM+(17–20) segment beyond the RNA–DNA hybrid tunes Cas9 cleavage rates of linear substrates. Here, we examined the impact of DNA supercoiling on Cas9 cleavage with the 16-nt truncated guide. Enzyme kinetic analysis revealed that PAM+(17–20) DNA sequences beyond the RNA/DNA hybrid preserve their effects on Cas9 cleavage in the supercoiled state. Furthermore, combining a novel asymmetric hairpin construct with a parallel-sequential kinetics model, rates for first-step nicking and second-step cleavage by Cas9 were obtained for both supercoiled and linear substrates. With both topologies, it was found that first-step nicking is clearly impacted by PAM+(17–20) DNA sequences, and the effects can be correlated with DNA unwinding, which dictates R-loop dynamics. This work expands our understanding of DNA target recognition by Cas9, and the methods developed, in particular those for analyzing the progression of Cas9-induced nicks, will aid in further in-depth mechanistic investigation.

Genetic manipulation of core gut probiotics remains challenging due to endogenous cellular barriers and a scarcity of efficient molecular tools, limiting progress in live biotherapeutic development. Here, we characterized the native type II-C CRISPR-Cas system in Bifidobacterium longum subsp. longum GNB (B. longum GNB). Through integrated bioinformatic analysis and high-throughput protospacer adjacent motif (PAM) screening, we identified a novel 5′-NNRMAT-3′ (where R = A/G, M = A/C) motif recognized by its compact Cas9 nuclease (BLCas9). The stringent PAM dependency of BLCas9 was unequivocally confirmed by in vitro cleavage assays. Leveraging this endogenous mechanism, we developed a dual-plasmid editing platform for robust and multiplex genome engineering in the probiotic strain E. coli Nissle 1917. Application of this system notably enhanced extracellular γ-aminobutyric acid (GABA) production in EcN through targeted metabolic engineering. Our work provides the first molecular dissection of a type II-C system in Bifidobacterium longum and establishes a generalizable framework for the discovery and application of compact programmable nucleases, suggesting a viable strategy for modulating host physiology via the gut-brain axis.

Cyclic dinucleotide (CDN) signaling molecules, such as cyclic di-GMP (c-di-GMP) and 3',3' cyclic GMP-AMP (cGAMP), are second messengers that play critical roles in phenotypic regulation, such as biofilm formation, host colonization, and bacterial virulence. Recently, hybrid promiscuous (Hypr) GGDEF proteins have been identified in certain bacteria to produce both cyclic dinucleotides. One such enzyme, Bd0367, from the predatory Bdellovibrio bacteriovorus, switches between synthesizing c-di-GMP and cGAMP to regulate the bacterial predation cycle and prey exit. However, the molecular mechanism controlling this switch remains unknown. Here, we introduce an RNA-based ratiometric, dual metabolite biosensor that enables simultaneous detection of c-di-GMP and cGAMP in live cells. This sensor integrates a Pepper-based biosensor for c-di-GMP detection and a Spinach2-based biosensor for cGAMP detection into a single transcript, producing distinct fluorescent outputs. In E. coli, the dual metabolite sensor reliably reported shifts in c-di-GMP/cGAMP production ratios from various CDN synthases, including Bd0367. Additionally, a histidine kinase was discovered as the probable regulatory partner of Bd0367. These findings demonstrate the sensor's capacity to assess relative CDN levels and to uncover complex signaling pathways. Together, this ratiometric dual metabolite biosensor provides a foundation for broader applications of fluorogenic RNA biosensors in dissecting bacterial signaling networks, microbial ecology, and host-pathogen interactions.

Alternative splicing expands proteomic diversity and is shaped by interactions between RNA‑binding proteins (RBPs) and multivalent RNA motifs. Linking sequence elements to regulatory proteins remains difficult from sequence information alone. Here we present RNAMaRs, a interpretable statistical framework that combines motif discovery with in vivo binding and splicing responses to infer motif-RBP relationships. RNAMaRs learns RBP binding principles, weights signal quality, and optimizes motif discovery in an RBP-specific manner. Across ENCODE datasets RNAMaRs consistently prioritizes the perturbed regulator, especially for large splicing effects. Independent validation in prostate cancer cells recapitulates HNRNPK binding signatures, supporting transferability across an unseen cellular context.

Antibiotics are known to induce new persister cells during treatment, yet the inability to distinguish and quantify pre-existing versus drug-induced persisters has long obscured how antibiotics and genes shape persistence. Here, we develop a quantitative framework integrating kinetic modeling with serial-dilution time-kill (SDTK) assays to resolve persister population dynamics and accurately quantify both persister types. We show that antibiotic exposure dynamically generates a substantial number of persisters that are heterogeneous and distributed along a persistence spectrum. Across antibiotics, we uncover pronounced differences in rates of persister induction and elimination, with ampicillin inducing persisters at the highest rate and kanamycin at the lowest. Depending on dilution history, drug-induced persisters can dominate the persister pool. Our framework enables identification of genetic determinants specific to pre-existing and/or drug-induced persistence and reveals drug-dependent pre-existing persister fractions. Systematic sequential-drug treatments demonstrate that kanamycin persisters form the most tolerant subset, embedded within ciprofloxacin persisters that in turn are nested within the broader ampicillin persister subpopulation. Together, we propose a Drug-Induced Persistence-Spectrum (DIPS) model in which antibiotics differentially induce and select for persister subsets along a tolerance continuum.