The Retron-Eco8 system, comprising a reverse transcriptase (RT), a non-coding RNA (ncRNA), and an OLD-family nuclease effector, protects bacteria from phage infection via abortive infection upon sensing a phage single-stranded DNA-binding protein (SSB). However, the molecular basis of this immunity remained unclear. Here, we report cryo-electron microscopy (cryo-EM) structures of Retron-Eco8 in inactive and activated states, revealing mechanisms of phage-triggered activation and effector function. Retron-Eco8 assembles into a tetrameric complex in which each protomer contains an RT, msrRNA–msdDNA duplex, and effector in an autoinhibited conformation. Upon phage infection, phage SSB binds msdDNA, relieving autoinhibition and activating the nuclease effector to degrade both phage and host DNA, triggering cell death to block phage propagation. Host SSB fails to activate the system, while DNA binding and oligomerization of phage SSB are essential for this activation, highlighting its specificity. These findings elucidate the molecular mechanism of Retron-Eco8-mediated immunity, facilitating retron-based biotechnological applications. Bacterial Retron-Eco8 defends against phages via abortive infection. Here, Ji et al. reveal that phage SSB binding to msDNA relieves Retron-Eco8 autoinhibition, triggering cellular DNA degradation and cell death for population protection.

Microbial biomass fermentation, in which microbes are cultivated to produce nutrient-dense biomass, offers a scalable route to sustainable protein production with low land, water, and greenhouse gas footprints. However, its shift from a speciality to a mainstream food continues to be difficult. Here, we move beyond technological overviews and propose a three-phase adoption framework: novelty barrier, early trust-building, and mainstream normalization. This framework organises techno-economic, regulatory, and infrastructural barriers into a single trajectory. We trace single-cell proteins’ rise, decline and resurgence, map engineering and policy enablers by phase, and outline levers to move microbial proteins into resilient food systems. Microbial biomass fermentation offers a scalable route to sustainable protein production with a low environmental footprint. In this Perspective, the authors propose a three-phase adoption framework to help move microbial proteins into resilient food systems.

Fungal pathogens threaten the health of humans, animals, and plants. ITS sequencing offers an effective approach for detecting fungal pathogens; however, a comprehensive pathogen database and associated tailored pipeline are still lacking. This study introduces the multiple fungal pathogen detection (MFPD) pipeline, which incorporates an accurate and high-speed sequence alignment algorithm for broad-habitat pathogen identification. The curated MFPD database includes 95 660 full-length ITS sequences from 4924 reported fungal pathogen species. In silico experiments show that the full-length ITS achieves the highest accuracy in pathogen detection (average 99.34%), outperforming both the ITS1 and ITS2 subregions. Benchmarking against existing tools, including FUNGuild, FungalTraits, and ISHAM-ITS, shows that MFPD achieves the highest F1 scores in mock communities (0.89 for both plant and human–animal pathogens) and detects the broadest spectrum of pathogenic taxa in real samples. In addition to identifying causal pathogens, MFPD can also detect coinfecting pathogens in biological and environmental samples. Together, our work supports pathogen surveillance across diverse sectors, including clinical, agricultural, and livestock systems within a One Health framework.

Climate change demands accelerated plant adaptation and de novo domestication. Yet current enviromics focuses disproportionately on external environments, neglecting internal dynamics—gene expression, metabolic flux, and signal transduction—within predictive envirotyping frameworks. This gap constrains plant-environment adaptation research and crop improvement. Integrating multi-scale envirotyping with plant-environment interaction networks could catalyze a paradigm shift from empirical selection to mechanism-informed design breeding. Four challenges remain: (1) constructing adaptive multi-dimensional networks, (2) engineering transgenerational epigenetic reprogramming, (3) scaling domestication pipelines, and (4) predicting adaptive trajectories. Future efforts should converge on five domains: high-throughput microprobe envirotyping arrays, spatiotemporally resolved multi-omics, decoding epigenetic memory carriers, artificial intelligence (AI)-guided genome design, and phenotype prediction models. Ultimately, advancing from multi-omics dissection and mechanistic interpretation to targeted de novo design will enable the precise engineering of crop adaptive responses to environmental change.

Because mutation rates vary widely across genomes and environments, natural selection is typically presented with highly biased variation. Yet, the idea that mutational tendencies can influence adaptation is still controversial. While mutation-driven adaptation has been observed in diverse taxa, critics contend it reflects small populations or weak-effect mutations. Therefore, the importance and generality of this phenomenon remain unclear, largely due to a lack of empirical tests across broad population-size gradients and multiple fitness-relevant traits. Here, we address this gap using a system in which two E. coli mutator lineages evolve antibiotic resistance via two mutationally favored, yet genetically distinct, routes. Simulations and experiments show that the scaling of mutation-biased adaptation with population size is complex, highly dependent on biological details, and – most critically – on how closely mutation bias aligns with selection. Contrary to the common view, we find that mutation-biased adaptation may not wane in large populations, but instead intensify depending on the bias. Crucially, we demonstrate that distinct mutation biases produce markedly different collateral sensitivity profiles to multiple antibiotics, even at large population sizes. Our findings suggest that mutation-biased adaptation may be widespread, with far-reaching and unpredictable consequences both within and beyond the original selective context. Adaptation is assumed to proceed by survival of the fittest. The study shows that mutation bias can drive adaptation via survival of the likeliest, steering bacteria along divergent paths to resistance with major consequences for control strategies.

Intensive reliance on conventional synthetic agrochemicals has been linked to environmental degradation and human health risks. Integrating nano-agrochemicals into agricultural practices could boost yields and reduce environmental footprints. In this Review, we evaluate the functions, market penetration, and benefits and risks of nano-agrochemicals in terms of crop productivity, environmental outcomes and human health. Nano-agrochemical formulations, primarily nano-fertilizers and nano-pesticides, are designed for targeted delivery and enhanced efficacy. Despite their promise, nano-agrochemicals currently represent <1% share of the global agrochemical market. Nanoformulations can boost crop yields by approximately 20%, largely through increased nutrient-use efficiency. However, their performance depends on environmental factors, such as soil texture, pH and ionic strength, which govern nanoparticle stability. Application methods (foliar versus soil) further interact with biological factors, including the above-ground and below-ground microbiotas, leaf and root exudates, and soil fauna, to influence nano-agrochemical bioavailability and uptake by plants. Nanofertilizers reduce nutrient leaching and nanopesticides minimize non-target toxicity, collectively reducing environmental and human health risks. Monitoring and regulatory frameworks remain highly heterogeneous across regions, with contrasting approaches in major agricultural producers, including the European Union, USA, China, Brazil and India. Future work should prioritize a universal ‘One Health’ assessment framework coupled with comprehensive life-cycle analyses to harmonize risk evaluation and guide the responsible global deployment of nano-agrochemicals. Improving agrochemical efficacy is important for safely meeting increasing food demand and responding to environmental change. This Review examines how nano-agrochemicals could boost food production sustainably, discusses their risks and benefits, and outlines approaches to facilitate their safe deployment.

The rising prevalence of multidrug-resistant (MDR) pathogens necessitates the development of sustainable, biocompatible antimicrobial agents. Green synthesis of metal oxide nanoparticles using endophytic microorganisms offers an eco-friendly and bioactive alternative to conventional physical and chemical methods. In this study, zinc oxide nanoparticles (ZnO NPs) were biosynthesized using the cell-free supernatant of Streptomyces werraensis, a novel endophytic actinobacterium isolated from the medicinal plant Passiflora caerulea L. The formation of ZnO NPs was monitored via UV–visible spectroscopy and Fourier Transform Infrared (FTIR) spectroscopy. Morphological and structural characterizations were performed using Transmission Electron Microscopy (TEM), Selected Area Electron Diffraction (SAED), and Dynamic Light Scattering (DLS). The biological potential of ZnO NPs for human health was evaluated through antibacterial assays against a panel of human pathogens and antioxidant assays (DPPH and ABTS). UV–Vis spectra confirmed ZnONP formation with a characteristic band-gap absorption, while FTIR identified proteinaceous and phenolic capping agents. TEM and SAED revealed highly crystalline, predominantly spherical nanoparticles with an average diameter of 136 nm and a wurtzite crystal structure. The biosynthesized ZnO NPs exhibited potent, concentration-dependent antibacterial activity, particularly against Gram-negative strains; Salmonella paratyphi A and Proteus vulgaris showed maximum inhibition zones of 19.0 ± 0.64 mm and 16.4 ± 0.68 mm, respectively, which are comparable to those of commercial ampicillin. Antioxidant assays demonstrated significant radical-scavenging potential, with an IC50 of 22.15 ± 1.2 µg/mL in the ABTS assay, approaching that of ascorbic acid. The findings of the present study demonstrate that S. werraensis-mediated ZnO NPs serve as effective “nanogenerators” of oxidative stress, offering a dual-action therapeutic approach. These results highlight the potential of endophytic actinobacteria as sustainable bio-factories for producing functional nanoparticles with promising antimicrobial potential for treating MDR infections.

River ecosystems, crucial components of the global nitrogen cycle, are increasingly affected by antibiotic pollution. However, the mechanistic interplay between nitrogen cycling and antibiotic resistance genes (ARGs) dissemination remains poorly understood, limiting effective ecological risk assessments. Here, we identify nitrate-reducing bacteria (NRBs), key drivers of denitrification and greenhouse gas mitigation, as dual-functional hubs that co-regulate nitrogen turnover and ARG dissemination under antibiotic stress. By integrating 173 metagenomes and 10 metatranscriptomes from the Yangtze River, we reconstruct 4200 metagenome-assembled genomes (MAGs) and find that NRBs harbor ~69% of actively transcribed ARGs in river microbiomes, with antibiotic pressure as the dominant ecological driver. Simulated microcosms exposed to antibiotic gradients reveal a hormetic response, where environmentally relevant concentrations enhanced both NRB-driven denitrification efficiency and ARG dissemination. Multi-omics analyses further reveal antibiotic-driven horizontal gene transfer as the predominant selective force co-shaping ARG and nitrate reduction gene dynamics, accelerating both nitrogen cycling and ARG spread. These findings establish NRBs as central hubs bridging antibiotic resistance and nitrogen metabolism, providing a mechanistic framework for predicting co-selection dynamics and mitigating cascading ecological impacts. Our work highlights the need to integrate microbial co-metabolic functions into pollution control strategies and redefine ecological risk assessments in antibiotic-polluted ecosystems. Antibiotic pollution and subsequent antibiotic resistance gene dissemination has an unknown effect on nitrogen cycling within river ecosystems. Here, using multi-omics and simulated microcosms, the authors identified nitrate-reducing bacteria as critical mitigators of these two processes.

Genetic circuits for model bacteria often perform poorly in non-canonical hosts, limiting the deployment of regulatory programs in industrially relevant organisms. Here, we engineered an integrase-based cascading toggle switch that enables consistent and programmable gene expression in Pseudomonas putida. The system couples a rhamnose-inducible trigger module driving the Bxb1 serine integrase with a compact, insulated inversion module that provides binary OFF and ON transcriptional states. To expand both output range and modularity, the switching system controls expression of an orthogonal T7 RNA polymerase gene, thereby activating interchangeable PT7-driven target modules. Translation-level tuning of integrase and T7 RNA polymerase gene expression yielded tight OFF behavior and strong induction. Switching was efficient, and phenotypes were maintained stably after inducer removal, supporting its use as a genetic memory element. The platform was extended to control a bioprocess-relevant phenotype by modulating a hyperactive diguanylate cyclase that triggers biofilm formation. Engineering the system in a 2-fluoro-cis,cis-muconic acid production strain enabled switch-mediated catalytic biofilms operated in continuous mode, where the biofilm configuration supported stable chemical production. This work expands the synthetic biology toolbox for Pseudomonas by linking heritable genetic memory to stable microbial phenotypes useful for bioprocesses.