Glycan biosynthesis relies on nucleotide-activated sugars, essential metabolites across all domains of life, yet their usage in microbes is poorly understood. Here we present SugarBase, a mass spectrometry and bioinformatic pipeline for untargeted exploration of microbial nucleotide sugar networks. SugarBase resolves the chemical complexity of microbial metabolism by combining narrow-window DIA fragmentation with a chemistry-informed parent ion identification algorithm. Applying SugarBase across a broad phylogenetic range of microbes revealed extensive, species-specific nucleotide sugar profiles, including many candidates with no existing annotation, generating the most comprehensive inventory of nucleotide sugars to date. SugarBase guided identification of gene clusters and allowed discrimination between pseudaminic- and legionaminic acid-producing strains, where genomic and proteomic data provided only ambiguous information. We resolved distinct nonulosonic acid profiles in several Campylobacter jejuni strains, sugars which may alter susceptibility towards distinct flagellotropic phages. We further identify previously undescribed CMP-activated higher-carbon ulosonic acids in Magnetospirillum, expanding the known chemical space in glycan biosynthesis. In summary, SugarBase supports scalable discovery of microbial nucleotide sugar pathways and enzymes, expanding access to chemically complex glycans and providing new targets for antimicrobial development.

β-Glucosidase (BGL), a pivotal enzyme in lignocellulosic saccharification, has been increasingly recognized as an “emerging green biocatalyst” in modern biorefinery processes. Here, Aspergillus niger An-BGL was rationally engineered to achieve high-level production of BGL under low-cost inducers. Corncob powder served as a cost-effective alternative inducer, enhancing BGL production to 14.2 U/mL. The knockout of CreA and the overexpression of XlnR increased the BGL yield by 75% and 27%, respectively. Combinatorial engineering of CreA and XlnR generated the XO–CK strain, which exhibited a derepression effect at high glucose concentrations. Supplementation with 1% glucose alleviated the delayed enzyme production in the engineered XO–CK strain, resulting in a BGL activity of 31.54 U/mL. Furthermore, integration of the bglA gene into the high-expression amyA site enhanced BGL to 40.68 U/mL. The rational modification strategy for A. niger strain established in this study offers an efficient and sustainable approach for transforming corncob agricultural waste into high-value enzymatic preparations.

Shotgun metagenomics has become a cornerstone of microbiome research, yet the complexity of existing workflows remains a major barrier for life scientists without dedicated bioinformatics support. Manual database setup, detailed sample sheet preparation, and management of software dependencies can make routine analysis difficult and time-consuming. Cross-study comparisons are further hampered by inconsistent processing pipelines, database versions, and profiling strategies, limiting reproducibility and the potential for large-scale meta-analyses. We present OpusTaxa, an open-source Snakemake workflow that provides end-to-end processing of short paired-end shotgun metagenomic data with minimal configuration. Users provide either FASTQ files or Sequence Read Archive accessions; OpusTaxa automatically downloads required databases, performs quality control, removes host reads, and executes taxonomic profiling, metagenome assembly, and functional analysis. All analysis modules can be independently toggled, and per-sample outputs are automatically merged into harmonised, cross-sample tables ready for downstream exploration. Across two public datasets, we demonstrate how OpusTaxa can be used to compare consistency across complementary taxonomic profilers and to estimate microbial load in addition to standard metagenomic workflows.

Non-model bacteria offer unique metabolic capabilities for sustainable bioproduction, yet their limited genetic accessibility hinders systematic strain development. Here we present conjugation-based serine recombinase-assisted genome engineering (cSAGE), a broad-host-range platform that enables predictable, iterative genomic integration in transformation-resistant bacteria. cSAGE combines conjugative DNA delivery, standardized low-copy vectors, orthogonal recombinases, and modular genetic parts to support rapid pathway assembly and cross-host benchmarking. Using purple nonsulfur bacteria as a testbed, we integrate promoter engineering, multi-payload genome modification, and genome-scale metabolic modeling to empirically evaluate host-dependent pathway performance. Applying this workflow, we identify strain-specific differences in photosynthetic conversion of lignin-derived p-coumarate to the thermoplastic precursor p-vinylphenol. By enabling genome engineering and functional comparison across diverse bacteria using a single plasmid system, cSAGE provides a general framework for non-model strain prototyping and biotransformation discovery.

16S rRNA amplicon sequencing is widely used to profile microbiome taxonomic composition and functional potential. Most 16S rRNA-based analysis methods depend on comparing sequenced reads against reference marker genes from previously characterized organisms. Thus, method accuracy declines in environments dominated by uncharacterized microbes. We uncovered a direct link between 16S rRNA and genome-encoded functions. Using fully sequenced bacterial genomes, we show that (i) whole-genome k-mer composition is predictive of functions encoded in the genome and (ii) 16S rRNA k-mer profiles reflect their source genome k-mer compositions. Leveraging these relationships, we developed embeRNA, a neural network-based framework that predicts functions directly from 16S rRNA k-mer embeddings, without taxonomy assignment or phylogenetic placement. Furthermore, by producing per-function probability scores rather than categorical assignments, embeRNA allows users to adapt decision thresholds to match study goals and sample characteristics, e.g. balancing precision vs. recall or accounting for community novelty. We trained embeRNA on a large collection of bacterial function-omes and evaluated it using a stringent novel microbes benchmark, where all test 16S rRNA sequences were dissimilar to those seen in training (all <97% identical). On this test set of phylogenetically novel organisms, embeRNA outperformed reference-based methods overall and achieved significantly better performance for the hard to label set of functions. In testing on soil metagenomes with paired 16S rRNA amplicon and whole metagenome shotgun (WMS) sequencing data, embeRNA recovered most WMS-inferred functions and yielded abundance profiles strongly correlated with WMS results. Together, our results indicate that 16S rRNA k-mer composition carries substantial functional signal and that 16S amplicon data can be used to complement WMS -based inference to broaden functional characterization of microbiomes, particularly in understudied environments.

Citrate is a central intermediate metabolite linking the tricarboxylic acid cycle and lipid biosynthesis. Tools for monitoring of spatiotemporal citrate dynamics are critical for getting a better understanding of cellular metabolism. Here, we develope genetically encoded excitation ratiometric biosensors for citrate, based on our previous intensiometric green fluorescence protein-based citrate biosensor, Citron1. We find that a single mutation in the Citron1 chromophore-forming tripeptide provided an excitation ratiometric response. Further rounds of directed evolution yield highly responsive variants, exhibiting citrate-dependent fluorescence changes between two excitation peaks. When expressed in mammalian cells, these biosensors enable citrate dynamics to be monitored in both the cytosol and mitochondria. Comparative analysis across multiple human breast cancer cell lines uncovers cell line-specific differences in citrate levels and their heterogeneity, which could be linked to their malignancy. Furthermore, flow cytometry-based measurements in mouse embryonic stem cells demonstrate the proteomics signatures underlying the population-level variability in citrate concentrations and citrate rewiring during stem cell differentiation. Together, these results show that these excitation ratiometric citrate biosensors enable quantitative, compartment-resolved, and population-scale analysis of cellular metabolism.

Defense-associated reverse transcriptases (DRTs) are widespread in bacteria, but how multi-domain DRTs containing RT and additional catalytic activities coordinate antiviral defense remains unclear. Here we show that DRT7, which contains both reverse transcriptase (RT) and primase-polymerase (PP) domains, provides broad-spectrum anti-phage immunity through abortive infection and can be activated by a phage-encoded putative transcriptional regulator. Upon activation, DRT7 synthesizes long, protein-primed, palindromic poly(A)/poly(T)-rich duplex-like DNA. Cryo-electron microscopy structures reveal that RT initiates protein-primed, protein-templated, sequence-specific poly(T) synthesis through an arginine-rich recognition pocket without requiring a complementary nucleic acid template, thereby converting DRT7 from an inactive closed dimer to an active open dimer. The RT-produced poly(T) then serves as both primer and template for PP-mediated poly(A) extension, with iterative handoff between RT and PP generating palindromic, alternating poly(A)/poly(T) ssDNA tracts that assemble into fold-back duplex-like DNA. These findings uncover an unexpected antiviral strategy based on protein self-templating, sequence-specific duplex-like DNA synthesis and reveal how coupling RTs with additional catalytic activities expands the functional scope of nucleic acid synthesis pathways.

Improving the effectiveness of microbial inoculants for soybean is essential to enhance biological nitrogen fixation and reduce fertilizer dependence; however, inoculated Bradyrhizobium strains frequently display inconsistent field performance. Inoculation is usually carried out with single-strain formulations, overlooking the possible influence of the native soil microbiota on nodulation success. This limitation may be addressed by formulating inoculants with consortia that include selected members of the soil microbiota. To this end, a synthetic microbial community (SynCom) was developed through a host-mediated microbiome engineering approach guided by leaf chlorophyll content as a rapid, non-destructive plant trait. The experiment was initiated by inoculating soybean plants with a consortium of 9 Bradyrhizobium spp. and 14 non-rhizobial soil isolates. Across eight consecutive selection rounds under gnotobiotic conditions, rhizosphere communities associated with superior plant performance were pooled and propagated. Recurrent selection induced significant shifts in community composition, consistently favoring Bradyrhizobium diazoefficiens as the dominant nodulating member and enriching taxa from Pseudomonadales, Burkholderiales, and Sphingomonadales. Sequencing-based profiling and network analysis suggested the emergence of a cohesive and functionally enriched community, with increased potential for nitrogen transformations and organic matter turnover. When evaluated in non-sterile soil, the SynCom derived from the sixth selection round increased nodule number and biomass relative to an uninoculated control and a commercial inoculant strain. These results suggest that plant-guided selection can steer rhizosphere community assembly toward beneficial configurations and support the development of improved soybean bioinoculants.

In heterogeneous environments, the hyphae of filamentous fungi and oomycetes can facilitate the dispersal of other microorganisms. The use of these fungal highways (FH) is regulated by both physical and biological factors with their interplay resulting in variable capabilities of different microbes to establish FH. Several devices have been developed to test the movement of bacteria across mycelium. However, these methods are usually time consuming and cannot be applied either at a large scale or in a high throughput format. In this study, we developed 3D-printed experimental devices that physically separate two environments while allowing hyphal networks to act as bridges for bacterial movement. The final design allows for the simultaneous testing of up to 10 pairs and the inclusion of any culturing media. With these devices, we investigated how fungal-bacterial pairing, nutrient conditions, and inoculation strategies influence FH formation. Bacterial transport was limited in nutrient-rich media but increased under poorer nutrient conditions, consistent with enhanced exploratory growth of the mycelium. Both cis- and trans-inoculation supported FH formation, although bacterial arrival was delayed in the absence of co-inoculation. The devices were used to demonstrate that transport of bacteria by FH was relevant for the colonization of a natural substrate. Finally, we established a novel in planta assay to evaluate FH formation during host colonization. This assay demonstrated that Fusarium graminearum can transport bacteria during wheat spike colonization. Together, these results provide accessible, scalable tools to study hyphal mediated bacterial dispersal and highlight the combined role of biological specificity and nutrient context in the establishment of FH.

The Prevotellaceae family comprises abundant, taxonomically diverse bacteria of the human microbiota that exhibit remarkable intraspecies variability and distinct phenotypes during host-microbe interactions. Yet functional investigations are hampered by the limited genetic tractability of this medically important bacterial family, rendering it understudied. Here, we apply antisense oligomer (ASO) technology to selectively inhibit translation of single or multiple mRNAs across nine Prevotellaceae species. Using ftsZ- and mreB-related phenotypes as morphogenic readouts, we demonstrate that ASOs can function as a tunable system to study essential gene function. Further, we show that ASOs can selectively deplete target species from a synthetic Bacteroidales community. These results establish ASOs as practical tools for functional genomics and community modulation in otherwise genetically intractable anaerobic microbiota members.

Polyethylene terephthalate (PET) waste remains a major environmental challenge due to its recalcitrance and low economic value. Here, we present an integrated biochemical approach that couples glycolysis with a synthetic microbial consortium to upcycle PET into polyhydroxyalkanoates (PHAs). Glycolysis efficiently depolymerized post-consumer PET into bis(2-hydroxyethyl) terephthalate (BHET) in 2 h, circumventing the limitations of in vivo PET degradation. We engineered a two-species microbial consortium composed of Comamonas testosteroni RW31, able to metabolize terephthalic acid, and Pseudomonas putida JM37, able to consume ethylene glycol, each modified for the extracellular secretion of PET- and MHET-hydrolases, employing different plasmid architectures. This division of labour creates a metabolic co-dependency, enabling rapid BHET hydrolysis and the subsequent upcycling of the released monomers into PHAs. The combination of the different strains allowed us to select C. testosteroni pSEVA354-MHETase and P. putida pSEVA234-PETase as the best consortium combination, based on growth and PHAs content. Overall, this work proposes a strategy for PET waste depolymerisation and valorisation, highlighting the potential of mixed chemical and biological approaches and the use of non-conventional microbial chassis within engineered consortia.