Although it is increasingly recognized that anthropogenic chemicals modulate horizontal gene transfer (HGT), the nature of these interactions is often more complex than a simple promotion or inhibition. The potential for a single chemical to exert opposing, concentration-dependent effects represent a critical and less-explored frontier in microbial ecology. Here, we investigate the last-resort antibiotic polymyxin B, a membrane-targeting peptide, and reveal a concentration-dependent, biphasic regulation of plasmid conjugation. Sub-inhibitory concentrations (0.125-0.5 mg/L) consistently inhibited the transfer of antibiotic resistance genes (ARGs) by up to 65.4%, whereas bactericidal concentrations (≥ 1 mg/L) strongly promoted it by up to 15.9-fold. This regulatory switch is driven by distinct physiological states: low-level exposure triggers defensive responses including reduced membrane permeability, whereas high-level exposure causes catastrophic membrane damage, inducing a synergistic stress response involving oxidative damage (>2-fold ROS increase) and a surge in cellular energy (up to 83.0% ATP increase) that facilitates HGT. High-concentration polymyxin B also promotes plasmid transfer in complex microbial communities derived from activated-sludge biofilms. Our findings reveal a new paradigm for the interaction between chemical stressors and microbial evolution, demonstrating that the ecological impact of contaminants on HGT cannot be predicted by monotonic models and highlighting the role of environmental hotspots in shaping the dissemination of antibiotic resistome.

Characterizing CRISPR interference (CRISPRi) phenotypes presents a fundamental temporal challenge: pre–existing overabundance of target proteins can mask early silencing, requiring extended growth for dilution, yet prolonged repression rapidly selects for escaper mutants. To resolve this, we integrated a tightly regulated CRISPRi system in Pseudomonas putida with an automated mini-bioreactor platform operating in turbidostat mode. By maintaining continuous exponential growth, we mapped the exact temporal dynamics of essential gene silencing. We identified a critical observation window between 17 and 27 hours (7–9.5 cell doublings) where repression exerts its maximum physiological impact, directly preceding population takeover by target-site mutated escapers. Applying this workflow to the arginine biosynthesis pathway, multi-omics profiling disentangled transient physiological buffering from long-term mutational events, and revealing that argH and argG knockdowns trigger highly diverse metabolomic perturbations. This scalable framework overcomes batch culture limitations, ensuring precise temporal control for accurate phenotypic characterization and reliable functional genomics.

Wood, once regarded primarily as a structural material, possesses rich physicochemical complexity that has long been underexplored. In the context of industrialization and carbon imbalance, it is now emerging as a renewable and multifunctional platform for green nano-technologies. Recent advances in wood nanotechnology have enabled the transformation of natural wood into programmable substrates with tailored nanoarchitectures, establishing it as a representative class of bio-based nanomaterials. This review systematically categorizes wood-specific nanoengineering strategies—including thermal carbonization, laser-induced graphenization, targeted delignification, nanomaterial integration, and mechanical processing—highlighting their mechanisms and impacts on wood’s multiscale structural and functional properties. Importantly, these functionalization strategies can be flexibly combined in a modular, “Lego-like” manner, enabling wood to be reconfigured and optimized for diverse application scenarios. We summarize recent progress in applying functionalized wood to sustainable technologies such as energy storage (e.g., metal-ion batteries, Zn–air systems, supercapacitors), water treatment (e.g., adsorption, photothermal filtration, catalytic degradation), and energy conversion (e.g., solar evaporation, ionic thermoelectrics, hydrovoltaics, and triboelectric nanogenerators). These studies reveal how nanoengineered wood structures can enable efficient charge transport, selective adsorption, and enhanced light-to-heat conversion. Finally, the review discusses current challenges—such as scalable fabrication, material integration, and long-term environmental stability—and outlines future directions for the development of wood-based platforms in next-generation green energy and environmental systems.

Whole-genome sequencing (WGS) data are an invaluable resource for understanding antimicrobial resistance (AMR) mechanisms. However, WGS data are high-dimensional and the lack of standardized genomic representations is a key barrier to AMR phenotype prediction. To fully explore these high-resolution data, we propose AMR-GNN, a graph deep learning-based framework that integrates multiple genomic representations with graph neural networks (GNN) to enable AMR phenotype prediction from genomic sequence data. We test AMR-GNN with Pseudomonas aeruginosa, a clinically relevant Gram-negative bacterial pathogen known for its complex AMR mechanisms. We present AMR-GNN as a proof-of-concept framework designed to address several key problems in AMR phenotype prediction with data-driven machine learning (ML) approaches, including using multiple genomic representations to enhance performance, to mitigate the influence of clonal relationships and to identify informative biomarkers to provide explainability. Follow-up validation on the largest publicly available dataset spanning both Gram-negative and Gram-positive pathogens highlights AMR-GNN’s broad applicability in detecting AMR in diverse and clinically relevant pathogen-drug combinations. Predicting antimicrobial resistance from bacterial genomic data is challenging. Here, the authors introduce AMR-GNN, a graph neural network that integrates multiple genomic representations to improve prediction, reduce clonal bias, and identify biomarkers.

Third-generation long-read sequencing technologies, significantly improve metagenome assemblies. Highly accurate PacBio HiFi reads can yield hundreds of near-complete metagenome-assembled genomes (MAGs) from a single sample. Recently, the accuracy of the more cost-effective Oxford Nanopore Technologies (ONT) platform has increased to a per-base error rate of 1-2%. However, current metagenome assemblers are optimized for HiFi and do not scale to the large data sets that ONT enables. We present nanoMDBG, an evolution of metaMDBG, which supports the latest ONT reads through an error correction pre-processing step in minimizer-space. Across a range of ONT datasets, including a large 400 Gbp soil sample, nanoMDBG reconstructs up to twice as many high-quality MAGs as the next best ONT assembler, metaFlye, while requiring a third of the CPU time and memory. Critically, the latest ONT technology can now produce comparable MAG construction results as those obtained using PacBio HiFi at the same sequencing depth. Benoit et al. present nanoMDBG, a scalable metagenome assembler for the latest ONT long reads, developed by adding error correction to metaMDBG. They demonstrate superior performance to the state-of-the-art and equivalent results to PacBio HiFi reads.

Intermicrobial and host–microbial interactions are critical for the functioning of the gut microbiome, but few tools are available to measure these interactions in situ. Here we report a method for broad spatial sampling of microbiome–host interactions in the gut at high resolution (1 µm). This method combines enzymatic in situ polyadenylation of both bacterial and host RNA with spatial RNA sequencing to increase bacterial RNA recovery and enable transcriptomic analysis of low-abundance and spatially restricted microbial taxa. We benchmark the method against existing spatial transcriptomic workflows, demonstrating improved sensitivity and resolution. Application of this method in a mouse model of intestinal neoplasia revealed the biogeography of the mouse gut microbiome as function of location in the intestine, frequent strong intermicrobial interactions at short length scales and tumor-associated changes in the architecture of the host–microbiome interface. This method is compatible with widely available commercial platforms for spatial RNA sequencing and can therefore be readily adopted to study the role of short-range, bidirectional host–microbe interactions in microbiome health and disease. Bulk polyadenylation improves the capture of microbial RNA, enabling host–microorganism interactions to be visualized at a high resolution when combined with commercially available spatial transcriptomics platforms.

Plastics drive twin crises: persistent pollution and greenhouse gas emissions. Bio-based approaches using enzymes and microorganisms to depolymerise plastics and valorise monomers show promise but raise societal, ethical and regulatory questions central to Responsible Research and Innovation (RRI). In this Perspective, we reflect on RRI implications of bio-based plastic degradation, informed by stakeholder discussions across the plastics value chain and public engagement. We identify broad support alongside concerns about scalability, interaction with existing recycling, governance and containment of genetically modified organisms, management of additives and contaminants, and the roles of regulation and economic incentives in enabling adoption. Bio-based approaches to plastic degradation have been an intense area of research in recent years, and although they show great promise, they also raise societal, ethical and regulatory questions. Here the authors reflect on the Responsible Research and Innovation (RRI) implications of this growing field, sharing insights they have gained through engagement with stakeholders and the broader public.

Plants use light both as a resource for photosynthesis and as a signal about their environment. In response to light cues, plants can move their organs via directional growth driven by cell expansion. In dense vegetation where light is available in spatially heterogeneous patterns, plants need to navigate this space to improve the position of their photosynthetic tissues. In canopies blue light irradiance and red to far-red light ratio decrease due to absorption by chloroplasts, and these changes regulate distinct processes within the plant. Changes in light environment are detected by cryptochrome and phytochrome photoreceptors, both regulating Phytochrome Interacting Factors (PIFs) and thereby enhancing elongation in hypocotyls, stems and leaves, and inducing upward leaf movement (hyponasty). An additional class of photoreceptors, phototropins, decode horizontal light gradients to produce directional growth towards the light source (phototropism). Here we review the current state of knowledge on these differential growth responses to light cues, with specific emphasis on the regulatory pathways that translate light signaling in differential cell expansion. Downstream of the photoreceptors, the phytohormone auxin induces cell growth in shoot tissues, but also other phytohormones contribute to balancing light responses. Cell expansion is regulated primarily at the level of cell walls and a comparison of different transcriptome datasets reveals that only a small group of cell wall modifying genes are tightly regulated by shade cues. It remains poorly understood which cell layers are causal to the initiation of cellular expansion. Here we combine insights from different differential growth behaviors in different species and organs to generate different hypotheses for the cellular underpinnings of light-driven leaf movements.

Spatially regulated membrane constriction is an important milestone in reconstituting minimal cell division. In giant lipid vesicles, bottom-up approaches have reproduced the assembly, mid-cell positioning, and the initial constriction of an FtsZ-based minimal divisome. However, progressive deformation towards giant vesicle scission by near-equatorial Z rings could so far never be observed. One obvious major limitation has been the scale mismatch, as pure reconstituted FtsZ rings typically exhibit bacterial diameters, too small to constrict typical cell-sized vesicles. Therefore, we explore the potential of other key divisome factors to scale up FtsZ-ring functionality in vitro to match the dimensions required for synthetic cell division. We here focus on cytoFtsN, the cytosolic domain of FtsN, and its effect on FtsZ self-organization. Remarkably, a molar excess of cytoFtsN promotes the formation of large, closed equatorial FtsZ rings on giant vesicle membranes, which are able to constrict to almost full closure. By fluorescence imaging and biochemical analysis, we show that cytoFtsN regulates the spatial organization of the FtsZ network primarily by aligning FtsZ filaments while reducing filament depolymerization. Our findings help to define key requirements in a minimal filament-based system for progressive membrane constriction and thus represent a major step forward towards constructing synthetic cells capable of self-division. Spatially regulated membrane constriction is an important milestone in reconstituting minimal cell division. Here the authors engineer a truncated system where the cytosolic domain of FtsN forms large, closed equatorial FtsZ rings on giant vesicle membranes and regulate the FtsZ network formation.

Bio-pesticides constitute a category of natural products and organisms effective against pests. Given their advantages, such as easier clearance and degradation compared to chemical pesticides, along with their lack of detrimental effects on ecosystem health, they represent a promising alternative for sustainable pest management and crop protection. The development of natural biopesticides to substitute synthetic pesticides is therefore of paramount importance for securing food safety and advancing agricultural production. Monoterpenes, primarily present in plant volatile oils, are characterized by a strong aroma and a range of biological activities-including insecticidal, antimicrobial, antiviral, anti-inflammatory, antioxidant, antitumor, and anticancer effects. This profile renders them a promising platform for the research and development of new, more effective pesticides. This article reviews the biosynthetic pathways of monoterpenes and contemporary engineering strategies for their microbial synthesis. Additionally, an evolutionary analysis database for monoterpene synthases (MTPS) has been established. Finally, the biological activities of monoterpenes are summarized and analyzed, with particular emphasis on their potential and advantages as biopesticides, thereby providing direction for the future development of monoterpene-based biopesticides.