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An AI system to help scientists write expert-level empirical software | nat

The cycle of scientific discovery is frequently bottlenecked by the slow, manual creation of software to support computational experiments. To address this, we present Empirical Research Assistance (ERA), an AI system that creates expert-level scientific software whose goal is to maximize a quality metric. The system uses a Large Language Model (LLM) and Tree Search (TS) to systematically improve the quality metric and intelligently navigate the large space of possible solutions. ERA achieves expert-level results when it explores and integrates complex research ideas from external sources. The effectiveness of tree search is demonstrated across a diverse range of tasks. In bioinformatics, ERA discovered 40 novel methods for single-cell data analysis that outperformed the top human-developed methods on a public leaderboard. In epidemiology, ERA generated 14 models that outperformed the CDC ensemble and all other individual models for forecasting COVID-19 hospitalizations. ERA also produced expert-level software for geospatial analysis, neural activity prediction in zebrafish, and numerical solution of integrals, and a novel rule-based construction for time series forecasting. By devising and implementing novel solutions to diverse tasks, ERA represents a significant step towards accelerating scientific progress.

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The effects of plastic pollution on biodiversity | Nrd

The effects of plastic pollution on biodiversity | Nrd | RMH | Scoop.it

As plastic is increasingly found in natural environments, concern has grown about its biological effects beyond individual-level impacts, particularly on species health, food-web dynamics and ecosystem functioning. In this Review, we summarize current evidence on plastic exposure pathways, organismal responses and potential effects at higher levels of biological organization. Impacts on individual organisms can be acute or chronic, and include physiological stress, disrupted locomotion, feeding and reproduction, internal injury, and death. Sublethal effects might not be immediately detectable but can have profound implications for individual fitness. Although macroplastics can cause mortality, their role in population declines remains largely uncertain, and demonstrated impacts beyond the individual level are rare. Clear evidence of population-level harm from microplastics to wild organisms is lacking. Nevertheless, emerging research demonstrates a growing likelihood of broader effects, particularly for species with high plastic-encounter rates. Connecting environmental exposure to individual-level fitness and population-level consequences is a critical frontier. Future research must prioritize long-term monitoring, demographic modelling and high-throughput methods to accurately quantify risks to biodiversity. Effective solutions must be context-specific, span local to global scales, account for interactions with other stressors and integrate plastic pollution mitigation policies with broader conservation strategies to safeguard biodiversity in the Anthropocene. Plastic pollution is pervasive across ecosystems, but its impacts on biodiversity remain poorly understood. This Review assesses current understanding of exposure and biological effects, evaluating the evidence for broader biodiversity impacts and outlining priorities for research, monitoring and mitigation.

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Mechanistic insights into activation of bacterial Retron-Eco8 immunity by phage protein SSB | Ncm

Mechanistic insights into activation of bacterial Retron-Eco8 immunity by phage protein SSB | Ncm | RMH | Scoop.it

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.

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Navigating adoption barriers for microbial proteins in future food | Ncm

Navigating adoption barriers for microbial proteins in future food | Ncm | RMH | Scoop.it

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.

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Far-red chlorophyll d clusters extend photosystem I absorption toward the red limit | sadv

Far-red chlorophyll d clusters extend photosystem I absorption toward the red limit | sadv | RMH | Scoop.it
Oxygenic photosynthesis is usually limited to visible light, but the marine cyanobacterium Acaryochloris marina pushes this boundary by harvesting far-red photons with chlorophyll d. The best-studied strain, MBIC11017, unexpectedly lacks low-energy chlorophylls (“red forms”) in photosystem I, limiting absorption beyond 740 nanometers. Here, we show that another strain, A. marina NIES-2412, has evolved a strategy to absorb far-red photons up to 760 nanometers. Combining time-resolved fluorescence spectroscopy with cryo–electron microscopy at 2.64-angstrom resolution, we identify two distinct classes of chlorophyll d red forms in its photosystem I. One class originates from classical charge-transfer–exciton mixing, while the other arises purely from excitonic interactions. Mapping all 96 chlorophylls d reveals the precise pigments responsible for these far-red states. We also uncover a previously unreported subunit, PsaX2, which stabilizes the photosystem I complex and shapes pigment geometry and energetics to enable the formation of red forms. Last, we show that the protein modifications responsible for binding and tuning these red forms are widespread across the Acaryochloris genus but not within the model MBIC11017 strain. Far-red photons lie close to the energetic limit of oxygenic photosynthesis; their efficient use therefore requires fine-tuning of the photosynthetic machinery. To our knowledge, our findings provide the structural and mechanistic basis of one of the most red-shifted photosystem I complexes identified to date, highlighting a distinct adaptive strategy in far-red light environments and offering design principles for extending photosynthesis in crops into the infrared.
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Modeling Cancer with Bacteria-Integrated Tumor Microenvironments Using Biomaterials: Emerging Concepts and Opportunities | mtb

Modeling Cancer with Bacteria-Integrated Tumor Microenvironments Using Biomaterials: Emerging Concepts and Opportunities | mtb | RMH | Scoop.it
The tumor microenvironment (TME) is a dynamic and heterogeneous ecosystem in which cancer, stromal, immune, and physicochemical components collectively regulate disease progression and therapeutic response. Recent evidence further indicates that intratumoral bacteria are active contributors to tumor metabolism, immune modulation, and treatment outcomes, revealing a previously underexplored multi-kingdom dimension of solid tumors. However, mechanistic understanding of tumor–microbe interactions remain limited by the absence of experimental platforms that integrate microbial components into physiologically relevant and controllable tumor models. Here, we propose bacteria-integrated tumor microenvironments as an emerging bioengineering framework for modeling cancer as a multi-kingdom system with biomaterials. We first lay out the existence of bacteria in our body and outline key design principles for these systems, including control of microbial localization, nutrient and oxygen gradients, and interkingdom signaling within engineered matrices. We further discuss applications in studying microbial contributions to therapeutic resistance, evaluating engineered bacterial therapies, and developing patient-specific tumor–microbiome models for precision oncology. Finally, we highlight challenges in standardizing multi-kingdom tumor platforms and integrating them with advanced imaging, sequencing, and computational tools. Collectively, bacteria-integrated tumor microenvironments establish a new paradigm for engineering cancer as a multi-kingdom system with translational potential in oncology.
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hydrogel

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The genetic repertoire of deep-sea microbiome: From sequence to structure and function | chm

The genetic repertoire of deep-sea microbiome: From sequence to structure and function | chm | RMH | Scoop.it
The deep sea, as the largest and maybe most hostile environment on Earth, is still underexplored, especially regarding its genetic repertoire. Yet, previous work has revealed significant habitat-specific deep-sea biodiversity. Here, we present an integrated deep-sea microbial genetic dataset comprising 502 million nonredundant genes from 2,138 samples and 2.4 million predicted structures and use it to link specific protein structures with genetic variants associated with life in the deep sea and to assess their biotechnology potential. Combining global sequence analysis with biophysical and biochemical measurements revealed unprecedented sequence diversity and substantial structural conservation of proteins. Especially, proteins involved in replication, recombination, and repair were identified as being under rapid evolution and with specialized properties. Among these, a structurally divergent helicase exhibited advantages in controlling nanopore sequencing speed. Thus, our work positions the deep sea as an evolutionary engine that generates and hosts genetic diversity and bridges genetic knowledge with biotechnology.
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A DNA damage-activated kinase phosphorylates a transcriptional repressor to control bacterial immune pathway expression | embo

A DNA damage-activated kinase phosphorylates a transcriptional repressor to control bacterial immune pathway expression | embo | RMH | Scoop.it

Bacteria encode numerous stress-response pathways that protect their hosts against both internal and external threats. A key question is how these pathways are regulated, especially anti-phage immune pathways that mediate host-cell killing. Here, we identify two proteins termed CapK and CapS that are encoded upstream of diverse immune operons, and regulate these operons’ expression in response to DNA damage. CapK resembles bacterial anti-sigma factor kinases, and CapS resembles STAS-domain antagonists of these proteins. CapS is a DNA-binding transcriptional repressor, and phosphorylation of CapS by CapK results in dissociation of a CapS homodimer and de-repression of transcription. The CapK kinase is directly activated by single-stranded DNA generated as a byproduct of DNA repair. Finally, we show that CapK and CapS-like proteins have been co-opted into an antiphage toxin-antitoxin system with a VapC-like protein, where they similarly respond to DNA damage to activate VapC nuclease activity. Overall, our results reveal how a kinase-substrate pair can regulate expression of an adjacent operon in response to DNA damage, and highlight the modularity of immune and other stress-response pathways.

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dna damage sensor (sense ssDNA produced as a byproduct of DNA repair)

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Gut microbes compensate for protein-deficient diets | tin

Gut microbes compensate for protein-deficient diets | tin | RMH | Scoop.it
By coupling natural variation in carbon stable isotope signatures with amino acid-specific analysis, Mertz et al. demonstrate the substantive contribution of the gut microbiome in improving diet quality through the production of essential amino acids that are absorbed by the host (deer mouse) and incorporated into muscle tissue.
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identified the contribution of the gut microbiome in generating essential amino acids used by the host to produce muscle tissue using δ13C stable isotope analysis of individual amino acids at their natural abundances to trace whether essential amino acids in host tissues were of dietary or microbial origin.  Metagenomic analyses of microbes suggests that Muribaculaeae and Lachospiraceae may play a critical role in this process

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MFPD: A Multiple Fungal Pathogen Detection Pipeline Across Diverse Habitats | advS

MFPD: A Multiple Fungal Pathogen Detection Pipeline Across Diverse Habitats | advS | RMH | Scoop.it

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.

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Enviromics crosstalk between internal and external plant environments for enhanced adaptation and de novo domestication | iMeta

Enviromics crosstalk between internal and external plant environments for enhanced adaptation and de novo domestication | iMeta | RMH | Scoop.it

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.

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Towards coevolution-aware ancestral sequence reconstruction | brve

Towards coevolution-aware ancestral sequence reconstruction | brve | RMH | Scoop.it

Ancestral sequence reconstruction (ASR) is a powerful approach for studying molecular evolution and the emergence of protein function. Yet most ASR methods assume that sites evolve independently, neglecting the epistatic constraints that shape protein structure, stability, and function. This simplification affects both ancestral inference and its evaluation: maximum-a-posteriori reconstructions may over-concentrate probability into a single over-idealized sequence, whereas independent posterior sampling can generate implausible or poorly functional ancestors. Here, we introduce a coevolution-aware ASR framework that combines standard phylogenetic inference with Direct Coupling Analysis (DCA), thereby preserving site-wise ancestral uncertainty while enforcing residue-residue constraints learned from extant protein families. To benchmark the method, we develop a controlled forward-evolution framework based on a DCA evolutionary sampler, allowing reconstructed ancestors to be compared with known ground-truth sequences generated under realistic epistatic constraints. Applied to beta-lactamases and DNA-binding domains, the approach improves reconstruction when ancestral states are epistatically constrained, and yields ensembles of candidate ancestors that are both phylogenetically consistent and statistically compatible with natural protein families. This framework bridges the gap between single-sequence MAP reconstruction and unconstrained posterior sampling, providing a practical route toward ancestral reconstructions that better reflect the coupled nature of protein evolution.

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1str, 

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Autoinducer-2 functions as both a quorum sensing and metabolic signal in Escherichia coli | brvm

Autoinducer-2 functions as both a quorum sensing and metabolic signal in Escherichia coli | brvm | RMH | Scoop.it

Bacteria integrate diverse environmental signals to coordinate behavior, yet the relationship between nutrient sensing and quorum sensing (QS) remains incompletely understood. Autoinducer-2 (AI-2) is unique among QS signals in that its production is tightly linked to central metabolism, raising fundamental questions about the boundary between metabolic and signaling functions. In Escherichia coli, AI-2 coordinates collective behaviors through the lsr operon, whose expression is controlled not only by the AI-2-responsive repressor LsrR but also by the cAMP receptor protein (CRP), placing it at the intersection of carbon sensing and population-level signaling. While inhibition of lsr operon expression by PTS sugars such as glucose was previously established, we demonstrate that non-PTS sugars similarly suppress lsr expression through CRP, further decoupling QS activation from cell density and coupling it to carbon source availability. Systematic analysis of Enterobacteriaceae genomes reveals that CRP binding sites in the lsr promoter region are broadly conserved, indicating that metabolic modulation of AI-2 signaling is an ancestral regulatory feature. Importantly, using a FRET-based biosensor, we show that AI-2 uptake modulates intracellular cAMP levels in a manner resembling non-PTS carbon source transport, suggesting that AI-2 may have originally functioned as a nutrient substrate, with its signaling role emerging subsequently or co-evolving alongside. In support of this hypothesis, we isolated soil- and phyllosphere-associated bacteria capable of utilizing AI-2 as a sole carbon source. Our findings reveal an underappreciated metabolic dimension of AI-2 QS and suggest an evolutionary trajectory in which AI-2 signaling emerged from ancestral carbon utilization pathways.

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Prion-based protein self-assembly tunes mutagenesis to enable rapid adaptation | CEL

Prion-based protein self-assembly tunes mutagenesis to enable rapid adaptation | CEL | RMH | Scoop.it
Mutations supply the raw material for evolution, yet because most are neutral or deleterious, elevated mutation rates are typically transient. Nonetheless, modeling predicts that a mechanism for heritable but reversible “mutagenesis switches” would be advantageous in some selective contexts. Here, we report that frequent prion-based switching of DNA repair and recombination proteins alters mutagenesis in Saccharomyces cerevisiae populations from diverse ecological niches, including the laboratory and clinic, providing adaptive benefits in short-term evolution under strong selective pressure. Self-templating protein assembly alters the activities and interactions of multiple DNA-fidelity factors, reshaping adaptive outcomes while maintaining resilience to genotoxic stress. In the WHO priority pathogen Candida albicans, which diverged from S. cerevisiae ∼300 million years ago, a key regulator of prion inheritance accelerates the rapid emergence of fluconazole resistance. These findings suggest that protein self-assembly can generate epigenetic memory that tunes genome diversification over multiple generations, enabling rapid adaptation in challenging environments.
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prion is a protein that can fold into an alternative conformation that has the property of being self-templating — when it contacts a natively folded copy of the same protein it converts that copy to the same alternative conformation. The converted copies then aggregate together. This aggregate is the prion state.

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Nano-agrochemical use in sustainable agriculture and environmental protection | Nature Reviews Earth & Environment nree

Nano-agrochemical use in sustainable agriculture and environmental protection | Nature Reviews Earth & Environment nree | RMH | Scoop.it

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.

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Biosynthesis of antibacterial zinc oxide nanoparticles from endophytic Streptomyces werraensis | Srep

Biosynthesis of antibacterial zinc oxide nanoparticles from endophytic Streptomyces werraensis | Srep | RMH | Scoop.it

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.

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The cell-free supernatant approach was selected to utilize extracellular metabolites (proteins, enzymes, and organic acids) secreted during bacterial growth.

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Nitrate-reducing bacteria bridge nitrogen cycling and antibiotic resistance in river ecosystems | Ncm

Nitrate-reducing bacteria bridge nitrogen cycling and antibiotic resistance in river ecosystems | Ncm | RMH | Scoop.it

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.

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Bacterial extracellular vesicles promote membrane repair and tolerance to polymyxin B | SAdv

Bacterial extracellular vesicles promote membrane repair and tolerance to polymyxin B | SAdv | RMH | Scoop.it
Bacterial extracellular vesicles (EVs) are nanosized lipid structures released under stress, yet their interactions with antibiotics remain poorly understood. We tracked real-time interactions between E. coli, EVs, and fluorescent polymyxin B (Pmb) using single-cell imaging and cytometric approaches. EVs rapidly sequester Pmb, facilitating its removal from bacterial envelopes, and act as plugs by adhering to or fusing with damaged sites. Pmb triggers early Cpx/σE- and Rcs-dependent stress responses, linked to a ∼25% reduction in cell surface area, a ∼50-fold increase in vesiculation, and remodeling of membrane properties. After an adaptive lag phase, sustained EV release supports detoxification and envelope repair, enabling growth recovery and transient tolerance to Pmb. Together, these findings reveal previously unrecognized functions of EVs in membrane repair and tolerance to membrane-active antibiotics.
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omv

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Rational design of T-DNA vectors enables predictable, single-copy integration in Arabidopsis thaliana | brvt

Rational design of T-DNA vectors enables predictable, single-copy integration in Arabidopsis thaliana | brvt | RMH | Scoop.it

Agrobacterium-mediated transformation is the dominant method for plant transgenesis, yet it frequently produces multi-copy, structurally complex T-DNA insertions associated with transgene silencing, unpredictable expression, and genome instability. Here, leveraging a high-throughput phenotypic reporter, we systematically dissect how T-DNA vector architecture, plasmid biology, and regulatory element choice shape transformation outcomes in Arabidopsis thaliana. We discover a pronounced trade-off between transformation efficiency and T-DNA copy number, uncovering the virulence enhancing overdrive sequence as a major determinant of this relationship. Guided by these insights, we engineered a new T-DNA vector that balances efficient transformation with predominantly single-copy integration. Additionally, we replaced viral elements, such as the widely used CaMV 35S promoter, with Arabidopsis-derived regulatory elements to minimise undesired enhancer effects, and developed a streamlined workflow for efficient T-DNA insertion mapping in the genome. Together, these advances form the T1 vector series, an Arabidopsis-optimised T-DNA vector system that enables clean, single-copy, and readily mappable transgene integration with predictable expression in the first generation after transformation.

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2st, khalil, methods, the use of the RUBY reporter to distinguish predominantly single-copy T-DNA integration events. Higher T-DNA vector copy number in Agrobacterium increases integration copy number in Arabidopsis

RepA R106H mutation in the pVS1 replicon, which roughly doubles plasmid copy number in Agrobacterium. In pCAMBIA-R106H, median T-DNA copy number in Arabidopsis nearly doubled (4->7) compared to unmodified pCAMBIA. The overdrive is a cis-acting virulence enhancer located immediately upstream (external) of the right border (RB) sequence. It enhances VirD2 recruitment to the RB, promoting efficient nicking and T-strand production.

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RNA structure programs endogenous ADAR for precise and efficient editing | CEL

RNA structure programs endogenous ADAR for precise and efficient editing | CEL | RMH | Scoop.it
Leveraging endogenous adenosine deaminase (ADAR) enzymes through engineered ADAR-recruiting RNAs (arRNAs) offers a safe, programmable strategy for RNA editing without exogenous enzyme delivery. Yet an incomplete understanding of ADAR’s mechanistic basis has hindered the rational design of arRNAs with improved efficiency and precision. Here, we present LEAPER 3.0 (leveraging endogenous ADAR for programmable editing of RNA), a next-generation RNA-editing platform that integrates AlphaFold 3 structural predictions with systematic biochemical and cellular assays to define the molecular interface between ADAR1 or ADAR2 and double-stranded RNA. These insights enabled the rational optimization of arRNAs to expand the editable sequence range to previously refractory sites, suppress bystander editing within duplex regions, and achieve single-nucleotide discrimination among adjacent adenosines. This work elucidates the structural and mechanistic principles underlying arRNA-mediated editing and establishes a framework for the rational design of highly efficient and precise A-to-I RNA-editing tools.
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Engineered bulges expand the editable RNA sequence space for endogenous ADAR editing
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Cascading recombinase memory switch for programmable and stable gene expression in Pseudomonas putida | nar

Cascading recombinase memory switch for programmable and stable gene expression in Pseudomonas putida | nar | RMH | Scoop.it

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.

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nikel pi

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Acoustic modulation of fungal friends and foes | tin

Acoustic modulation of fungal friends and foes | tin | RMH | Scoop.it
Targeted acoustic stimulation can modulate fungal growth, metabolism, and molecular activity. It offers a promising route to influence fungal performance in agriculture, biotechnology, ecosystem restoration, and medicine. In this opinion article, we review studies showing that acoustic waves can either enhance or suppress fungal processes depending on species and acoustic parameters. Proposed mechanisms include activation of mechanosensitive membrane channels, calcium signalling, and shifts in the pentose phosphate pathway and coenzyme A biosynthetic pathways. Responses vary widely, yet this variation may create opportunities to tailor species- and industry-specific applications. Progress will accelerate with more consistent reporting of acoustic settings, exposure conditions, and fungal traits, thereby improving repeatability and comparability. Acoustic modulation represents an emerging, versatile tool with substantial potential to modulate fungal activity.
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vibration

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BioPipelines: Accessible Computational Protein and Ligand Design for Chemical Biologists | csb

BioPipelines: Accessible Computational Protein and Ligand Design for Chemical Biologists | csb | RMH | Scoop.it
Deep learning methods for protein structure generation, sequence design, and structure and property prediction have created unprecedented opportunities for protein engineering and drug discovery. However, using these tools often requires navigating incompatible software environments, diverse input/output formats, and high-performance computing infrastructure, any of which may hinder adoption by primarily experimental chemical biology laboratories. Here, we present BioPipelines, an open-source Python framework that allows researchers to define multistep computational design workflows in a few lines of code. Additionally, its robust yet modular architecture provides a straightforward way to expand the tool kit with different functionalities, particularly by leveraging coding agents, with little effort. The framework currently integrates over 40 tools encompassing structure generation, sequence design, structure prediction, compound screening, and analysis. The same workflow code can be prototyped interactively in a Jupyter notebook and then submitted for production-scale runs without modification. We demonstrate applications in inverse folding, gene synthesis, de novo protein design, compound library screening, iterative binding site optimization, and fusion-protein linker optimization. We hope that this framework will empower researchers, allowing them to focus on the scientific question rather than computational logistics. BioPipelines is available under the MIT license at https://github.com/locbp-uzh/biopipelines.
mhryu@live.com's insight:

4st, protein design software, 1. Inverse folding, sequence redesign — ProteinMPNN → AlphaFold2 → codon-optimized DNA synthesis (DNAEncoder via CoCoPUTs). 2. De novo protein domain redesign — RFdiffusion → ProteinMPNN → AlphaFold2 (demonstrated on adenylate kinase LID domain) 3. Compound library screening — combinatorial library generation → Boltz-2 cofolding → binding affinity/probability ranking → PoseBusters validation 4. Fusion protein / linker optimization — Fuse (linker length combinations) → Boltz-2 (apo and holo) → Distance/Angle analysis → FRET geometry comparison 5. Iterative binding site optimization — LigandMPNN → mutation profile → candidate generation → Boltz-2 scoring → iterative selection (5 cycles demonstrated on NocT/histopine)

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Targeting Cancer-Specific Mutations with RNA-Triggered Chromatin Shredding | nat

Targeting Cancer-Specific Mutations with RNA-Triggered Chromatin Shredding | nat | RMH | Scoop.it

Genetic mutations that drive cancer often occur in tumor suppressor proteins, including the p53 transcription factor which is altered in ~40-50% of cases. However, current therapies fail to target most such mutations because the mutant proteins typically lack defined drug-binding pockets, and restoring the endogenous function has proven challenging. Here, we programmed CRISPR-Cas12a2, an RNA-guided nuclease with trans-nucleolytic cleavage activities to selectively kill cancer cells by targeting cancer-specific transcripts. This approach limits cell growth by inducing trans shredding of chromatin, triggering DNA damage responses and cell death. Unlike existing methods, RNA-guided Cas12a2 senses cellular RNA signatures, enabling precise targeting of undruggable mutations. Transcript-activated chromatin shredding provides a new approach to precision disease treatments for undruggable targets.

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doudna

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The origin and evolution of auxin as a plant signaling molecule | CurB

The origin and evolution of auxin as a plant signaling molecule | CurB | RMH | Scoop.it
The plant signaling molecule auxin is key to plant growth and development, and has been connected to numerous processes. Yet, auxin is by no means a plant-specific compound, but is found ubiquitously across all domains of life. In this review, we trace the evolutionary steps that allowed this small molecule to gain control over plant biology. We explore the ecological context in which its plant signaling function arose, and review recent insights into the evolution of the known signaling mediators in plants. What emerges is a scenario in which coordinated changes in a small number of pre-existing proteins ushered in the assembly of a simple intracellular perception/response system that, along with the gained capacity to synthesize auxin, converted an environmental signal into an endogenous signaling molecule.
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AEGIS: an annotation extraction and genomic integration resource | bft

AEGIS: an annotation extraction and genomic integration resource | bft | RMH | Scoop.it

Genome annotation files (GFF3/GTF) are the standard for storing genomic feature data, yet their flexibility often results in formatting inconsistencies that create bottlenecks for downstream bioinformatics analyses. A robust, unified framework is required to parse, standardize, and validate these files to ensure interoperability and facilitate complex comparative genomic tasks. We present AEGIS (Annotation Extraction and Genomic Integration Suite), a comprehensive toolkit designed to parse, correct, and standardise genome annotations. Beyond quality control, AEGIS provides advanced modules for flexible feature extraction (e.g., coding sequences, promoters) and comparative genomic analysis. Uniquely, it integrates multiple lines of evidence, including sequence homology, synteny, and coordinate-based lift-overs, to assess gene model correspondence and infer orthology. We demonstrate the utility of AEGIS by quantifying complex structural changes between Arabidopsis annotation versions and identifying high-confidence orthologues across diverse plant genomes.

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