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Today, 6:43 PM
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The accuracy of protein structure prediction models such as AlphaFold2 is tightly coupled to the depth and quality of multiple sequence alignments (MSAs), posing a persistent challenge for proteins with few or no identifiable homologs. We present GhostFold, a method for conjuring structure-constrained synthetic MSAs from a single amino acid sequence, bypassing the need for traditional homology searches. Leveraging the ProstT5 protein language model and the 3Di structural alphabet, GhostFold projects a query sequence into a tokenized structural representation and iteratively back-translates to generate an ensemble of diverse, fold-consistent sequences. These synthetic alignments (pseudoMSAs) encode emergent coevolutionary constraints that are sufficient for high-accuracy structure prediction of difficult targets such as orphan proteins and hypervariable antibody loops. GhostFold consistently matches or exceeds the performance of MSA-based and language model-based structure predictors while being computationally lightweight and independent of large sequence databases. Notably, we observe a decoupling of confidence metrics (e.g., pLDDT) from prediction accuracy when using pseudoMSAs, suggesting that AlphaFold2’s internal confidence calibration is strongly influenced by the statistical properties of natural sequence alignments. These results establish that structure-guided synthetic MSAs can functionally substitute for evolutionary data, offering a scalable and generalizable solution to one of the central limitations in computational structural biology. GhostFold represents a shift from passive data mining to intelligent sequence synthesis, redefining how structural priors are encoded in deep learning-based protein folding.
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Today, 4:49 PM
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The diverse regulatory functions, protein production capacity, and stability of natural and synthetic RNAs are closely tied to their ability to fold into intricate structures. Determining RNA structure is thus fundamental to RNA biology and bioengineering. Among existing approaches to structure determination, computational secondary structure prediction offers a rapid and low-cost strategy and is thus widely used, especially when seeking to identify functional RNA elements in large transcriptomes or screen massive libraries of novel designs. While traditional approaches rely on detailed measurements of folding energetics and/or probabilistic modeling of structural data, recent years have witnessed a surge in deep learning methods, inspired by their tremendous success in protein structure prediction. However, the limited diversity and volume of known RNA structures can impede their ability to accurately predict structures markedly different from the ones they have seen. This is known as the generalization gap and currently poses a major barrier to progress in the field. In this Perspective article, we gauge method generalizability using a new benchmark dataset of structured RNAs we curated from the Protein Data Bank. We also discuss the emergence of deep learning methods for predicting structure probing data and use a new dataset to underscore generalization challenges unique to this domain along with directions for future improvement. Expanding beyond improving predictive accuracy, we review how advances in deep learning have recently enabled scalable and accessible optimization of traditional structure prediction methods and their seamless integration with modern neural networks.
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Today, 4:33 PM
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The human microbiome is crucial for health regulation and disease progression, presenting a valuable opportunity for health state classification. Traditional microbiome-based classification relies on pre-trained machine learning (ML) or deep learning (DL) models, which typically focus on microbial distribution patterns, neglecting the underlying relationships between microbes. As a result, model performance can be significantly affected by data sparsity, misclassified features, or incomplete microbial profiles. To overcome these challenges, we introduce Phylo-Spec, a phylogeny-driven deep learning algorithm that integrates multi-aspect microbial information for improved status recognition. Phylo-Spec fuses convolutional features of microbes within a phylogenetic hierarchy via a bottom-up iteration and significantly alleviates the challenges due to sparse data and inaccurate profiling. Additionally, the model dynamically assigns unclassified species to virtual nodes on the phylogenetic tree based on higher-level taxonomy, minimizing interferences from unclassified species. Phylo-Spec also captures the feature importance via an information gain-based mechanism through the phylogenetic structure propagation, enhancing the interpretability of classification decisions. Phylo-Spec demonstrated superior efficacy in microbiome status classification across two in silico synthetic data sets that simulate the aforementioned cases, outperforming existing ML and DL methods. Validation with real-world metagenomic and amplicon data further confirmed the model’s performance in multiple status classification, establishing a powerful framework for microbiome-based health state identification and microbe-disease association. The source code is available at https://github.com/qdu-bioinfo/Phylo-Spec.
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Today, 4:12 PM
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When cells encounter stress, they rapidly mount an adaptive response by switching from pro-growth to stress-responsive gene expression programs. How cells selectively silence pre-existing, pro-growth transcripts yet efficiently translate transcriptionally induced stress mRNA and whether these transcriptional and post-transcriptional responses are coordinated are poorly understood. Here, we show that following acute glucose withdrawal in S. cerevisiae, pre-existing mRNAs are not first degraded to halt protein synthesis, nor are they sequestered away in P-bodies. Rather, their translation is quickly repressed through a sequence-independent mechanism that differentiates between mRNAs produced before and after stress, followed by their decay. Transcriptional induction of endogenous transcripts and reporter mRNAs during stress is sufficient to escape translational repression, while induction prior to stress leads to repression. Our results reveal a timing-controlled coordination of the transcriptional and translational responses in the nucleus and cytoplasm, ensuring a rapid and wide-scale reprogramming of gene expression following environmental stress.
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Today, 3:57 PM
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Nonhomologous end-joining repairs chromosomal double strand breaks, but it is unknown whether both strands are repaired by this pathway, and if one strand break’s repair path impacts the other. Here, we show that nonhomologous end-joining employs both of two a priori possible strategies. Strand breaks that can be directly ligated are joined near-simultaneously, with no effect of one strand break’s repair path on the other. More complex end structures require obligatorily ordered repair. The first strand to be repaired is used as template for repair of the opposite/second strand break, with the latter repair reaction occurring fastest when also coupled to nonhomologous end-joining. Enforced asymmetry in repair of each strand break can extend to the gap-filling polymerase employed, and whether the polymerases incorporate RNA or DNA. Our results resolve questions about pathway mechanism and identify a requirement for flexibility of the nonhomologous end-joining machinery for efficient repair of both strand breaks within diverse cellular double strand breaks. Breakage of both chromosomal DNA strands creates unique problems for DNA repair. Here, Luthman et al. show that for some broken ends, the two strand breaks are repaired in parallel, while for other ends one strand must be repaired before the other.
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Today, 3:36 PM
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Advances in long-read sequencing (LRS) and assembly algorithms have made it possible to create highly complete genome assemblies for humans, animals and plants. However, ongoing development is needed to improve accessibility, affordability, and assembly quality and completeness. ‘Cornetto’ is a new strategy in which we use programmable selective nanopore sequencing to focus LRS data production onto the unsolved regions of a nascent assembly. This improves assembly quality and streamlines the process, both for humans and non-human vertebrates. Cornetto enables us to generate highly complete diploid human genome assemblies using only nanopore LRS data, surpassing the quality of previous efforts at a fraction of the cost. Cornetto enables genome assembly from challenging sample types like human saliva. Finally, we obtain accurate assemblies for clinically-relevant repetitive loci at the extremes of the genome, demonstrating valid approaches for genetic diagnosis in facioscapulohumeral muscular dystrophy (FSHD) and MUC1-autosomal dominant tubulointerstitial kidney disease (MUC1-ADTKD). Long-read sequencing enables high-quality genome assemblies, but challenges remain. Here, the authors introduce Cornetto, a method that improves assembly quality, enables genome sequencing from saliva, and accurately resolves medically-relevant repetitive genes.
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Today, 1:52 PM
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Organic acids such as fumaric acid are widely used in the food and beverage industry as acidulants and preservatives, while also serving as versatile precursors for industrially relevant compounds. Fumaric acid is still predominantly produced through petroleum-derived processes. To enhance production efficiency and diversify supply, we are engineering Kluyveromyces marxianus as a biosynthetic platform from renewable feedstocks. In previous work, we have established K. marxianus Y-1190 as a host for lactose valorization based on its high growth rate on lactose and its tolerance for acid conditions. Here, we establish a trifunctional genome-wide library for K. marxianus using CRISPR activation, interference, and deletion to allow identification of gene expression perturbations that enhance tolerance to fumaric acid. We determined that deletion of ATP7, encoding a subunit of the mitochondrial F1F0 ATP synthase, and overexpression of QDR2 and QDR3, two previously uncharacterized members of the 12-spanner H+ antiporter (DHA1) family in K. marxianus, can enhance fumaric acid tolerance. We also found that integrated overexpression of both QDR2 and QDR3 in a ΔFUM1 background strain improved titers of fumaric acid production from 0.26 to 2.16 g L–1. Together, these results highlight roles for membrane transport and mitochondrial function in enabling fumaric acid tolerance and production in K. marxianus.
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Today, 1:40 PM
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Reactive oxygen species (ROS) play crucial roles in many plant biological processes. ROS have emerged as major signaling molecules mediating various regulatory reactions in response to environmental stimuli. This signaling is mediated by a highly regulated process of ROS accumulation at specific cellular compartments. Therefore, this review focuses on the intricate ROS signaling in plant defense and strategic virulence effectors from pathogens hijacking ROS homeostasis. In addition, the ROS-mediated regulation of plant processes acts through post-translational modifications (PTMs) is discussed. We also provide a valuable roadmap for translating ROS research into climate-resilient cultivars by exploring the manipulation of pathogen effectors, ROS cascade genes through modern biotechnological approaches, and post-translational modifications against various environmental stressors. This framework can advance research in plant stress biology and agricultural practices.
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Today, 10:56 AM
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Over the past years, substantial numbers of microbial species’ genomes have been deposited outside of conventional INSDC databases. The GlobDB aggregates 14 independent genomic catalogues to provide a comprehensive database of species-dereplicated microbial genomes, with consistent taxonomy, annotations, and additional analysis resources. The GlobDB more than doubles the number of microbial species represented by genomes relative to the field standard genome taxonomy database. The GlobDB is available at https://globdb.org/.
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Today, 10:41 AM
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Sepsis is a life-threatening condition caused by polymicrobial infections and remains a global health emergency that requires rapid and broad-spectrum diagnostics. Existing CRISPR-based assays face two major limitations that restrict their application for sepsis: narrow protospacer adjacent motif (PAM) site compatibility and poor enzyme stability under clinical and environmental stresses. A modular diagnostic platform is presented, CRISPR-FLEXMO (CRISPR with flexible PAM in metal-organic framework encapsulation, MOF), which integrates a PAM-relaxed Cas12a variant (K607R) with a manganese-coordinated MOF (Mn-MOF) for stable and specific detection of sepsis-causing bacteria. The system targets a conserved region upstream of the Shine-Dalgarno sequence in the 16S rRNA gene containing a universal TTCC PAM, enabling broad-spectrum detection with a single universal primer pair across Gram-negative and Gram-positive pathogens. The K607R variant shows enhanced cis- and trans-cleavage activity, while Mn-MOF encapsulation maintains enzyme functionality under ambient, thermal, and chaotropic stress. The assay detects as low as 10 CFU mL−1 in bacterial lysates following amplification and achieves 100% sensitivity and specificity in serum samples from 15 sepsis patients and 3 healthy individuals, with no cross-reactivity to six respiratory viruses. The platform retains over 78% activity after 12 weeks of room-temperature storage, offering a field-deployable CRISPR diagnostic solution for next-generation infectious disease detection.
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Today, 10:23 AM
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GMrepo (Gut Microbiome Data Repository) is a curated and consistently annotated database of human gut metagenomes, designed to improve data reusability and enable cross-project and cross-disease comparisons. In this latest release, GMrepo v3 has been expanded to 890 projects and 118 965 runs/samples, including 87 048 16S rRNA and 31 917 metagenomic datasets. The number of annotated diseases has increased from 133 to 302, allowing more comprehensive disease-related microbiome analyses. We systematically identified microbial markers between phenotype pairs (e.g. healthy versus diseased) at the project level and compared them across datasets to detect reproducible signatures. As of this release, GMrepo v3 includes 1299 marker taxa (726 species and 573 genera) associated with 167 phenotype pairs, derived from 275 carefully curated projects. To assess biomarker stability, we developed the Marker Consistency Index (MCI), which summarizes the prevalence and directional consistency of markers across studies. Among 400 markers showing altered abundances in ≥10 projects, 143 were consistently enriched in healthy controls (MCI > 75%), while 85 were enriched in diseases (MCI < 25%). A marker-centric interface enables users to explore marker behavior across diseases. The GMrepo v3 database is freely accessible at https://gmrepo.humangut.info.
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Today, 12:55 AM
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Ulcerative colitis (UC) is a severe inflammatory bowel disease affecting millions of people worldwide, but the factors driving the condition are poorly understood. In tissue samples from individuals with UC, we found that macrophages were depleted from areas of the colon that did not yet exhibit overt epithelial inflammation. We hypothesized that toxins produced by bacteria could impair macrophages and that this could promote wider inflammation. We isolated a variant of Aeromonas genus from stool samples from UC patients, which we termed macrophage-toxic bacteria (MTB), because aerolysin secreted by MTB caused macrophage death. MTB colonized mice under pathogenic conditions and triggered colitis. Antibodies against aerolysin alleviated colitis induced by Aeromonas in mice. In a cohort, UC patients more frequently tested positive for Aeromonas than healthy controls did.
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Today, 12:43 AM
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The rapid advancement of synthetic biology has enabled the construction of artificial cells that closely mimic the morphology and functionality of their natural counterparts. However, significant limitations remain in engineering artificial cells capable of regulated protein expression. Here, we demonstrate that engineered polymers containing multivalent association motifs can reversibly regulate translational activity through liquid–liquid phase separation (LLPS)–induced protein aggregation, enabling precise temporal control of cell-free protein synthesis (CFPS) activity. This aggregation mechanism exerts a broad inhibitory effect on various enzymes and facilitates the construction of artificial cells with controllable reaction processes. Leveraging this phenomenon, we have developed a microfluidic platform to fabricate giant unilamellar vesicles (GUVs) that encapsulate CFPS systems, thereby constructing artificial cells with finely tunable protein expression. By incorporating targeted DNA templates, these artificial cells can selectively express specific proteins in response to pH adjustments. Furthermore, in vivo studies using a bile duct ligation mouse model with liver injury further confirmed significant differences in protein expression under alkaline conditions compared to neutral conditions. Our findings highlight the potential of leveraging aggregate dynamics for precise, in situ modulation of protein synthesis within artificial cells, thereby opening avenues for their advanced biomedical applications.
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Today, 5:19 PM
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Porins mediate the passage of hydrophilic nutrients and antibiotics across the outer membrane but might contribute to proton leak from the periplasm, suggesting that their conductance could be regulated. Here we show, using single-cell imaging, that porin permeability in Escherichia coli is controlled by changes in periplasmic H+ and K+ concentration. Conductance through porins increases with low periplasmic H+ caused by starvation, promoting nutrient uptake, and decreases with periplasmic acidification during growth in lipid media, limiting proton loss. High metabolic activity during growth in glucose media, however, activates the inner membrane voltage-gated potassium channel, Kch, increasing periplasmic potassium and enhancing porin permeability to dissipate reactive oxygen species. This metabolic control of porin permeability explains the observed increase in ciprofloxacin resistance of bacteria catabolizing lipids and clarifies the impact of mutations in central metabolism genes on drug resistance, identifying Kch as a therapeutic target to improve bacterial killing by antibiotics. The permeability of bacterial porins is dynamically regulated by periplasmic proton and potassium concentrations, altering antibiotic resistance.
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Today, 4:39 PM
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Global regulators (GRs) are key transcription factors that orchestrate the expression of multiple genes, playing essential roles in stress responses, virulence, secondary metabolism, and antibiotic resistance—traits that make them powerful tools for synthetic biology applications. However, conventional approaches often fail to detect remote homologs and novel GR types, limiting our understanding of their regulatory diversity and evolutionary dynamics across prokaryotes. Here, we present a large-scale, protein language model-driven framework to systematically chart the global regulatory landscape across 14,800 bacterial and archaeal type strain genomes—the most taxonomically diverse prokaryotic data set analyzed to date. Using a deep learning-based GR identification model trained on 74,872 curated GR sequences, we systematically identified over 270,000 GR-like proteins, including 173,256 homologs of 214 experimentally validated GR types, 52 putative GR types, and 76,113 proteins of unknown function. This model demonstrated high sensitivity and generalization capability, enabling the discovery of remote homologs and cryptic regulators beyond the reach of similarity- or domain-based methods. This expanded GR catalog revealed lineage-specific distribution patterns, functionally diverse regulons with both conserved and niche-specific targets, and hierarchical cross-regulatory networks with shared and phylum-enriched hubs. By unveiling the hidden diversity and evolutionary structure of prokaryotic global regulators, this landscape of GRs provides foundational insights into microbial gene regulation and offers a powerful toolkit for the rational design of tunable, modular, and orthogonal genetic circuits in synthetic biology.
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Today, 4:24 PM
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Bacteriophages (phages), the dominant prokaryotic viruses that specifically target bacteria in the human gut microbiome, play a crucial role in maintaining intestinal balance, regulating bacterial populations, and preserving microbial diversity within the gut microbiota. While prophages can enhance bacterial virulence and antibiotic resistance, potentially posing health risks, they also provide beneficial functions, including enhancing host fitness, promoting immune modulation, and contributing to ecosystem resilience, which supports intestinal homeostasis. Human gut microbiota is essential for various physiological functions, including digestion, vitamin synthesis, immune modulation, and protection against pathogens. Dysbiosis, or microbial imbalance, is associated with various disorders such as inflammatory bowel disease, obesity, diabetes, and mental health disorders. Consequently, prophages are important considerations for developing therapies to prevent intestinal diseases. Recently, there has been significant interest in prophage induction in the gut due to its functional impacts on microbial dynamics, gut health, and disease modulation. Prophage induction can be regulated by diet, antibiotics, metabolites, gut health, lifestyle, and intestinal environments. However, compared with lytic phages, prophages remain underexplored, leaving gaps in our understanding of their functions within the gut. Therefore, further research is needed to fully elucidate the complex interactions between phages, prophages, and the gut microbiota, and their effects on health and disease. This knowledge could inform the development of phage-based therapies and improve therapeutic strategies for gut health.
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Today, 4:05 PM
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Efficient cargo delivery is essential for plant trait engineering, yet existing methods are often species-specific and ineffective across diverse habitats. Here, we develop core-shell microneedles for targeted delivery of biomolecular cargoes and active microorganisms into both terrestrial and aquatic plants. The microneedle architecture is rationally engineered to resist water exposure and release cargo upon contact with plant interstitial fluid, enabling controlled delivery into tissues and cells. We demonstrate that these core-shell microneedles can efficiently transport diverse cargoes, from nanoscale biomolecules such as functional nucleic acids, proteins, and plant hormones to microscale bioactive Agrobacterium, leading to strong protein expression and enhanced plant growth. Underwater delivery of salt-tolerance genes into submerged freshwater plants further demonstrates the platform’s utility for engineering stress resilience in challenging environments. By facilitating the cellular uptake of diverse cargoes into intact plants across different habitats, this amphibious microneedle strategy offers a versatile cargo delivery tool to advance plant biotechnology and environmental applications. An efficient cargo delivery tool is essential for plant trait engineering. Here, the authors repot a core-shell microneedles for targeted delivery of nucleic acids, proteins, phytohormones, and Agrobacterium to both terrestrial and aquatic plants.
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Today, 3:46 PM
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Mass spectrometry is recognized as the gold standard for glycan analysis, yet the complexity of the generated data hampers progress in glycobiology, as existing tools lack full automation, requiring extensive manual effort. We introduce GlycoGenius, an open-source program offering an automated workflow for glycomics data analysis, featuring an intuitive graphical interface. With algorithms tailored to reduce manual workload, it allows for data visualization and automatically constructs search spaces, identifies, scores, and quantifies glycans, filters results, and annotates fragment spectra of N- and O-glycans, glycosaminoglycans and more. It seamlessly guides researchers of all expertise levels from raw data to publication-ready figures. Our findings demonstrate that GlycoGenius achieves results comparable to manual analysis or competing tools, identifying more glycans, including novel ones, while significantly reducing processing time. This groundbreaking tool represents a significant advancement in the study of glycoconjugates, empowering researchers to focus on insights rather than data processing. Researchers present GlycoGenius, an open-source tool that automates complex glycomics data analysis. It streamlines workflows, identifies known and previously unreported glycans, and enables faster, more accessible insights into glycobiology.
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Today, 2:43 PM
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Designing effective mRNA sequences for therapeutics remains a formidable challenge. Inspired by successes in protein design, language models (LMs) are now being applied to RNA, but progress is often impeded by the lack of comprehensive training data. Existing models are frequently limited to UTR or CDS regions, restricting their application for complete mRNA sequences. We introduce mRNABERT, a robust, all-in-one mRNA designer pre-trained on the largest available mRNA dataset. To enhance performance, we propose a dual tokenization scheme with a cross-modality contrastive learning framework to integrate semantic information from protein sequences. On a comprehensive benchmark, mRNABERT demonstrates state-of-the-art performance, outperforming previous models in the majority of tasks for 5’ UTR and CDS design, RNA-binding protein (RBP) site prediction, and full-length mRNA property prediction. It also surpasses large protein models in several related tasks. In conclusion, mRNABERT’s superior performance across these diverse tasks signifies a substantial leap forward in mRNA research and therapeutic development. Designing complete mRNA sequences for new vaccines and therapies is a complex challenge. Here, the authors develop mRNABERT, a foundational AI model that designs entire mRNA sequences and demonstrates superior performance across comprehensive benchmarks.
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Today, 1:43 PM
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In recent years, interest in the role of nutrient cycling in sustainable agriculture has significantly increased. The potential of arbuscular mycorrhizal fungi (AMF) in nutrient cycling and plant growth improvement has long been recognized. However, there have been only a few studies on the identification and exploration of AM symbiosis-related plant genes for sustainable agriculture. We have developed a new constructive model for using host plant-derived AM symbiosis-related genes to improve breeding and AMF utilization for sustainable agriculture, particularly in the context of climate change. This model include: 1) the discovery of AM symbiosis-related genes in crop wild-relatives for molecular breeding and 2) the screening and propagation of AMFs that can help improve water-use efficiency and nutrient-use efficiency by crops, thereby reducing chemical fertilizer use in agricultural production. The first approach uniquely facilitates the identification of host plant-derived AM symbiosis-related genes, such as CHITIN ELICITOR RECEPTOR KINASE 1 (OsCERK1) from Dongxiang (DY) wild rice (Oryza rufipogon) (OsCERK1DY), MILDEW RESISTANCE LOCUS 1 (MLO1) from wild barley (Hordeum spontaneum), and WRKY60 from wild soybean (Glycine soja), for breeding purposes. The second one involves identifying soil-borne AMF species, such as Rhizophagus intraradices and Glomus mosseae for practical applications in the field. This suggestive model presents an emerging biotechnological potential for engineering climate-resilient crops.
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Today, 1:03 PM
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Liposomes are microscale lipid vesicles used in pharmaceuticals, food products, and most recently, agriculture. Several studies have shown that liposomes can deliver nutrients to plant leaves, often more efficiently than traditional forms. However, the delivery of plant nutrients to soil via liposomes remains understudied. Interactions between liposomes and soil microbes, including metabolism of the lipid carbon (C) and assimilation of liposome-encapsulated nutrients into soil microbial biomass, could alter the availability of nutrients within the soil. We assessed the impact of lecithin liposomes with nitrogen (N) cargo on C and N cycling during a 7-day incubation experiment. We quantified changes in concentrations of carbon dioxide, nitrous oxide, oxygen, and soil inorganic N pools including soil extractable nitrate (NO3–-N) and ammonium (NH4+-N). Liposome additions increased microbial respiration and resulted in rapid soil NO3–-N immobilization, suggesting that liposomes may be a tool to immobilize N and reduce agricultural N losses.
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Today, 10:49 AM
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High-throughput sequencing (HTS) has become an integral part of routine analysis for microbiologists. The process of sequencing dozens of samples generates vast amounts of data that cannot be annotated manually. To address this challenge, numerous tools for bacterial genome analysis have been developed over the years. Using freely available databases, these tools enable users to significantly accelerate their analyses. However, many of these tools require advanced computer science expertise to operate effectively. To overcome this limitation, we developed BacExplorer. Featuring a user-friendly interface, a locally installable application, and an interactive HTML report, BacExplorer empowers users of all skill levels to perform their own analyses with ease and efficiency.
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Today, 10:38 AM
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CRISPR technology, originally developed as a genome-editing tool, has recently emerged as a powerful platform for intracellular biosensing. By harnessing the programmability and target specificity of CRISPR-associated proteins, such as Cas9, Cas12, and Cas13, researchers have engineered biosensors capable of detecting a wide array of intracellular signals, including nucleic acids, non-coding RNAs, and small-molecule metabolites. This review discusses the recent advancements in CRISPR-powered biosensors for real-time, dynamic monitoring of cellular processes and molecular events. Particular focus is given to the integration of nano-technology, which plays a crucial role in enhancing the delivery efficiency, signal amplification, and sensor stability. Nanomaterials such as gold nanoparticles, quantum dots, DNA nanostructures, and upconversion nanoparticles have been strategically employed to improve the intracellular transport of CRISPR components, facilitate signal readouts, and enable multimodal sensing in complex cellular environments. Additionally, we delve into how CRISPR-nanotechnology hybrids can be adapted for multiplex analysis and single-cell resolution. This review also addresses the current challenges in intracellular biosensing, including precise delivery, biocompatibility, and long-term monitoring, and outlines future directions for the application of these systems in precision medicine, synthetic biology, and advanced therapeutic monitoring. Through the convergence of gene-editing systems and nanotechnology, CRISPR-based intracellular biosensors are anticipated to revolutionize next-generation diagnostic and therapeutic strategies.
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Today, 10:03 AM
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Structural variations drive plant genome evolution and shape agronomic traits. Manipulating structural variations has great potential to improve complex plant traits and enhance agricultural sustainability. Genome editing technologies have evolved from gene knockouts and base editing to the modification of short DNA fragments, and are now advancing towards the precise manipulation of large DNA fragments. This advancement facilitates targeted, large-scale genomic changes such as deletions, insertions, replacements, inversions, translocations and duplications. In this Review, we summarize recent advances in developing technologies for large DNA fragment editing and highlight their key applications in plants as well as their potential to accelerate crop improvement. Finally, we discuss the current challenges and future prospects for these technologies in plant science. Engineering genome structural variations can improve plant traits and support sustainable agriculture. This Review summarizes recent advances in large DNA fragment editing and discusses their applications and future prospects in precise breeding.
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Today, 12:48 AM
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The genome of Arabidopsis thaliana consists of 10 chromosomes. By inducing CRISPR-Cas–mediated breaks at subcentromeric and subtelomeric sequences, we fused entire chromosome arms, obtaining two eight-chromosome lines. In one line, both arms of chromosome 3 were fused to chromosome 1. In another line, the arms were transferred to chromosomes 1 and 5. Both chromosome number–reduced lines were fertile. Phenotypic and transcriptional analyses revealed no differences compared with wild-type plants. After crossing with the wild type, the progeny showed reduced fertility. The meiotic recombination patterns of the transferred chromosome arms were substantially changed. Directed chromosome number changes in plants may enable new breeding strategies, redefining linkage groups and establishing genetic barriers. Moreover, our data indicate that plants are highly robust to engineered karyotype changes.
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