RMH

Transfer RNAs (tRNAs) link mRNA codons to amino acids during translation. Their abundance and modification states are dynamically regulated and influence translation efficiency, mRNA stability, and proteostasis. Accurate profiling of tRNAs is essential, but deep sequencing suffers from modification-induced biases during cDNA synthesis, while nanopore direct RNA sequencing (DRS) still faces challenges in accurate tRNA profiling. Here, we develop an end-to-end deep learning model, termed nano tRNA classifier, that directly uses nanopore-DRS ionic current signals to classify tRNAs without basecalling. The model achieves 98.2% classification accuracy with high read retention across all E. coli tRNA species. Using an equimolar mixture of native tRNAs as a ground-truth reference, we correct read-count bias, enabling absolute quantification and profiling under diverse culture conditions. We further develop binary classifiers that detect specific tRNA modifications at the single-molecule level with high accuracy. This nanopore-based platform integrates accurate tRNA classification, absolute quantification, and single-molecule modification detection. Here the authors develop a nanopore-based method using deep learning to classify cellular tRNAs, quantify their absolute abundance, and detect chemical modifications at the single molecule level.

 Natural products (NPs) are structurally diverse bioactive molecules with broad applications in pharmaceuticals, nutraceuticals, cosmetics, and other high-value sectors. Microbial cell factories provide programmable platforms for NP production, but their performance is often constrained by dynamic bottlenecks that are not readily inferred from end-point titers, including limited precursor or cofactor supply, toxic intermediate accumulation, inefficient heterologous enzyme function, and competition with host metabolism. Genetically encoded biosensors translate NP molecules, pathway-relevant metabolites, or cellular states into measurable, selectable, or regulatory outputs. Here, we critically examine biosensor design principles and distinguish the variable detected, recognition modality, output, and implementation format. We then assess how direct product sensing, pathway-state monitoring, dynamic regulation, enzyme screening, genome-wide perturbation, and growth-coupled evolution can support microbial NP engineering. Emphasis is placed on the correspondence between sensor output and the intended engineering objective. This framework clarifies when biosensors can provide actionable information for rewiring NP-producing microbial hosts.

We argue that shifts in the abundance and composition of marine particles impacted horizontal gene transfer, consequently shaping the evolutionary landscape of the oceans throughout Earth’s history. We focus on two pivotal transitions — the emergence of cyanobacteria and the rise of eukaryotic algae.

CRISPR mediated genome engineering strategies were developed and applied for genome-wide mutagenesis. However, high-throughput gRNA libraries require design and synthesis, which limits their economy and versatility. In this study, we designed in vitro transcription strategy for artificially synthesizing random gRNA libraries, which were transformed into cells to guide the diverse mutations generated through Cas protein induced double stranded DNA breaks. As a proof of concept, the Saccharomyces cerevisiae strain C0 with overexpression of tHMG1 and β-carotene biosynthesis key genes was used as the original strain, and the β-carotene synthesis ability of strain C0 was increased to that of 5.8 times after three rounds of iterative mutation. Furthermore, for the mutated S. cerevisiae strain C7-143 with high-level β-carotene production, a mutant strain AgC8-174 with a 26% increase in β-carotene yield was obtained through one round of mutation. This strategy completely avoided the limitations of plasmid library, significantly shortened the experimental cycle, and improved the versatility of gRNA library across different species. The results fully demonstrated the feasibility of the technology and lays a solid foundation for its application in the field of microbial genetics and breeding.

Phyllosphere bacteria, occupying both epiphytic and endophytic habitats, constitute a critical plant-atmosphere interface. However, their community assembly and life-history strategies (LHSs) in response to temperature increase remain poorly understood. Here, we compared leaf phyllosphere bacterial communities with those in other plant compartments across four representative plant species from an alpine meadow on the Qinghai-Tibet Plateau. By combining observations along an elevational gradient with a controlled warming experiment, we found that temperature was closely associated with the deterministic assembly of leaf phyllosphere bacterial communities. Elevated temperature corresponded to shifts in taxonomic composition, diversity, assembly process, cross-compartment bacterial source, and co-occurrence network. Furthermore, elevated temperature was associated with a shift toward r-strategists in leaf phyllosphere bacterial LHSs, evidenced by higher ribosomal RNA operon (rrn) copy numbers for rapid growth potential and corroborated by genome assemblies of four warming-responsive epiphytic isolates and metagenomic sequencing. Based on 880 public 16S rRNA gene datasets from 45 locations on six continents, we identified a global increase in the rrn copy number in leaf epiphytic bacterial communities across diverse plant species, which was associated with elevated temperatures and enhanced diurnal fluctuation. Finally, we proposed a concept of four LHSs (growth, stress tolerance, competition, and resource acquisition) based on functional inference from 16S rRNA data, supported by the assembled epiphytic bacterial genomes and metagenomes. Collectively, our findings established a trait-based framework for understanding responses of leaf phyllosphere bacteria to future warming.

Persistent reductive stress and soil acidification impose strong environmental filtering in gleyed paddy soils, suppressing microbial activity and limiting phosphorus (P) bioavailability. Inspired by natural soil-water interface dynamics, we developed a restoration strategy combining slow-release CaO2, periphyton development, and phosphate-solubilizing bacteria (PSB) to alleviate habitat constraints and reactivate endogenous P cycling under field conditions. Slow-release CaO2 provided initial oxidative and alkalizing conditioning, effectively elevating soil pH and reducing total reducing substances (TRS). This initial habitat amelioration was accompanied by periphyton proliferation and a marked reduction in within-treatment community heterogeneity (microbiome convergence). Co-occurrence network analysis revealed topological realignments, with PSB taxa (Bacillus and Pseudomonas) occupying module hubs and periphytic microalgae acting as connectors between photoautotrophic and heterotrophic guilds. Metatranscriptomic profiling demonstrated coordinated upregulation of complementary P-cycling pathways, including pyrroloquinoline quinone (PQQ)-dependent inorganic P solubilization and organic P mineralization (phoD, pqq, phn, and bpp). These functional transcripts were positively correlated with soil pH, phosphatase activities, and available P, but negatively correlated with TRS. Overall, this integrated conditioning strategy alleviated environmental filtering and was associated with coupled multi-guild functional responses, ultimately boosting endogenous P-cycling potential in degraded paddy soils. These findings suggest that a functional complementary framework may help inform microbiome-assisted restoration of constrained agricultural soils.

The bacterial cell envelope is a complex superstructure that is an important target and a major barrier for antibiotics. To date, highest-resolution images of native cell envelopes have been obtained by atomic force microscopy (AFM), but its use is limited by challenges in bacterial immobilization. We establish glutaraldehyde-functionalized glass surfaces for reversible covalent attachment, enabling robust adhesion across species and cellular orientations while preserving cell viability and growth. This approach allowed imaging of E, coli both expressing O-antigen and fully lacking lipopolysaccharide (LPS) oligosaccharides, revealing that AFM contrast depends on LPS complexity and confirming previously observed outer membrane domains as LPS-enriched islands. It also enabled imaging of Pseudomonas aeruginosa and Acinetobacter baumannii outer membranes, which lack the characteristic protein trimers observed in model E. coli. Finally, we discovered growth-phase dependent alterations in E. coli pole morphology, where trimer networks typical of exponential-phase cells were unresolved and morphological defects appeared. The use of atomic force microscopy for high-resolution imaging of the surface of live bacterial cells is limited by challenges in cell immobilization. Here, Scheeder et al. present an improved immobilization method that allows imaging of diverse bacteria, including imaging of bacterial cell poles. tool

Circular RNAs (circRNAs) are emerging as important regulators in mammalian cells and promising substrates for RNA therapeutics, yet the trans-acting factors governing their metabolism remain poorly defined. Here we systematically evaluate 730 RNA-binding proteins (RBPs) using a tethered reporter assay and identify 281 RBPs that significantly modulate circRNA activity. Follow-up assays implicate these RBPs across key stages of the circRNA life cycle, including biogenesis, nuclear export, degradation and translation. We identify seven RBPs for tethered translation enhancement of therapeutically applicable circRNA vectors and highlight LARP4B as a potent enhancer of exogenous circRNA translation across multiple internal ribosomal entry sites and cell types. We uncover an evolutionarily conserved role for RBM15 in circRNA biogenesis in fly, mouse and human, further demonstrating a role in circRNA nuclear retention, and that perturbing RBM15 sites with dCasRx or antisense oligonucleotides modulates endogenous circRNA expression. Together, our study provides a global view of circRNA trans-regulation and describes practical entry points for therapeutic development. This study systematically evaluates proteins that control circular RNA production, stability and translation, revealing new regulators and strategies to enhance or suppress circular RNA activity for therapeutic development.

Heterotrophic bacterial metabolism is a globally critical component of the marine carbon cycle, but its progression within a complex network of compounds and organisms challenges our ability to quantify carbon fate. Currently unresolved are the genomic underpinnings that control the path of carbon through microbial food webs and the role of metabolic exchange in these dynamics. We hypothesized that genomes could predict which members initially affect carbon fate for a given compound. We also posited that exchange of breakdown products generated from that compound further alters the path of carbon through the ecosystem. Our experiments featured simplified organic matter and microbial communities that examined glycolate metabolism in a diverse set of sixteen heterotrophic marine bacterial isolates. Stable isotope probing and imaging mass spectrometry alongside genomic analyses and microscopy revealed relationships between taxonomy and carbon fluxes. Nine of thirteen strains genomically capable of glycolate metabolism directly assimilated and respired glycolate carbon in monoculture. We then co-cultivated glycolate-incorporators with non-incorporators and found several non-incorporators assimilated more glycolate carbon into biomass than incorporators. Carbon use efficiency, reflecting partitioning of carbon into biomass versus carbon dioxide, was distinct across co-cultures and ranged from 0.01 - 3.15% depending on the co-culture mixtures. These results suggest glycolate carbon fate is not driven solely by microbial taxa genomically capable of assimilation but rather by metabolic interactions that further impact the efficiency of carbon transfer. Quantifying these effects is critical to refine conceptual and numerical models of heterotrophic organic matter processing.