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mhryu@live.com
October 1, 12:04 AM
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Metagenomic sequencing allows for detection of any number of pathogenic viruses from a single sample without a priori knowledge of its contents. This has created a substantial opportunity to characterize pathogens in humans and their environment, but the field is held back by a lack of bioinformatics tools for taxonomic profiling and reconstructing virus genomes. The ideal profiler would simultaneously do two things: report viruses at single-read sensitivity so that ultra-low-abundance pathogens are not missed and hold near-perfect specificity so that a pathogen is never falsely reported. Here we present EsViritu, a taxonomic profiler that pairs an iterative greedy clustering algorithm and lowest-common-ancestor taxonomic refinement with a curated Virus Pathogen Database to reconstruct virus genomes and generate virome profiles directly from reads. We benchmarked EsViritu against four leading metagenomic profilers (Kraken2, Centrifuger, Metabuli, and Sylph), running each program across a full parameter sweep and against the same Virus Pathogen Database for an apples-to-apples comparison. Across synthetic positive controls, pathogen-free negative controls, and mutated mock communities, EsViritu was the most accurate tool at reconstructing community composition: it led or tied every tool on relative abundance accuracy at all taxonomic ranks and led or tied on detection across ranks. Importantly, other tools frequently report the presence of multiple related taxa when only reads for a single genome are present, but EsViritu faithfully records the correct, single taxon and genome. EsViritu achieves read-level sensitivity for sequences as low as 85% average nucleotide identity to the nearest reference and reports essentially no false positives in pathogen-free host and synthetic samples. EsViritu also returns reconstructed consensus genomes whose nucleotide identity to the nearest reference closely tracks ground truth, yielding both a profile and genomes from a single run.
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mhryu@live.com
September 30, 11:40 PM
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Domestication of crops, such as rice, has resulted in the loss of beneficial root-associated microbiota central to plant nitrogen-use efficiency. Whether these microbes can be inherited through hybridization of wild and cultivated plants and the host genes involved is unclear. Here we used two recombinant inbred line populations, derived from cultivated rice (Oryza sativa) and its wild relative Oryza rufipogon to map host quantitative trait loci associated with core bacterial taxa. Integrating microbiome profiling, quantitative trait loci mapping, population genomics and transgenic validation, we identified 113 candidate plant genes. The receptor-like kinase-encoding gene OsRLK, found predominantly in wild rice, was significantly associated with Acinetobacter, which enhances plant nitrogen uptake. Knockout and overexpression of OsRLK, inoculated with an Acinetobacter synthetic community, validated their role in nitrogen-use efficiency. In field trials, the overexpression line significantly increased yield-related traits. These findings establish the genetic basis of microbiome re-domestication and provide a framework for microbiome-guided breeding of nutrient-efficient crops. Hybridization of wild and cultivated rice plants improves nitrogen use efficiency through microbiome re-domestication.
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mhryu@live.com
September 30, 4:27 PM
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Accurate prediction of effector proteins secreted by Gram-negative bacteria is important for elucidating bacterial pathogenic mechanisms and developing precise anti-infective strategies. Although existing methods have benefited from the strong sequence feature extraction capacity of pretrained protein language models, reliance on linear sequence information alone often fails to fully capture the three-dimensional conformational signals required for virulence functions. Meanwhile, conventional structure-based methods are limited by the scarcity of experimentally resolved protein structures. To address these challenges, we propose GeoEPred, a multimodal deep learning framework designed for the synergistic modeling of protein sequence and structure to identify Gram-negative bacterial effector proteins. Specifically, the model integrates sequence-contextual embeddings from a pretrained protein language model with three-dimensional structural representations predicted by ESMFold. A feature projection network refines fine-grained sequence signals associated with effector functions, while geometric vector perceptrons characterize inter-residue orientations, distances, and local spatial topology to capture potential structural conformational motifs. To further enable effective cross-modal fusion, we design a cross-modal alignment and feature-tokenized self-attention module. This module enhances consistency between the sequence-semantic and structural-geometric spaces through contrastive learning and models associations between linear functional motifs and spatial conformational patterns at a fine-grained token level. Extensive evaluations on multiple benchmark datasets show that GeoEPred achieves better predictive performance than existing leading models in T3SE, T4SE, and T6SE prediction tasks, while maintaining stable performance in remote homolog recognition scenarios. Moreover, the modular and extensible architecture of GeoEPred demonstrates strong generalization ability and substantial application potential for genome-scale effector protein discovery.
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mhryu@live.com
September 30, 4:02 PM
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PROteolysis TArgeting Chimeras (PROTACs) are bifunctional molecules that catalyze degradation of selected proteins by inducing protein:protein interactions (PPIs) between E3 ubiquitin ligases and the protein of interest. A critical limitation is undesired effects in untargeted tissues, necessitating approaches to impose spatiotemporal control over PROTAC function. Here we present Ru(II) photocages that can be released with low energy light, providing triggered PROTAC activity on demand. The systems, termed Ruthenium-based PHOToActivated Chimeras (RuPHOTAC), were validated by targeting bromodomain-containing proteins, which act as crucial epigenetic regulators, and also strongly reduced levels of c-MYC and PIM1. RuPHOTACs demonstrate that the incorporation of metal components within organic PROTACs confers multiple advantages for light-controlled systems for chemical biology applications, including the highest selectivity for activation in the light vs. the dark, improved potency against the target proteins of interest, and increased efficacy in vivo using low energy red light. To efficiently monitor protein degradation via optical means, a strategy was implemented by creating a fusion of a photoconvertible protein, Dendra2, with the proteins of interest. This bifunctional reporter system for live cell analysis decouples protein degradation efficiency and rates from signals arising from new protein production, and is superior to prior reporter systems described for PROTACs because it directly measures the true degradation rate of the target protein in intact, viable cells while simultaneously tracking newly synthesized protein without perturbing translation, proteostasis, or cell health. PROTACs offer a powerful strategy to eliminate disease-relevant proteins, but off-target activity in healthy tissues remains a major challenge. Here, the authors introduce Ruthenium-based PHOToActivated Chimeras (RuPHOTACs), a new class of light-responsive PROTACs that remain inactive until triggered by low-energy light.
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mhryu@live.com
September 30, 3:09 PM
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Single-stranded DNA (ssDNA) is used as a readout of replication stress, yet it arises in several contexts. It is a normal intermediate of DNA replication but can accumulate and persist after replication challenges and is also generated by replication-independent processes. These structures differ in strand origin, architecture, biological consequence, and therapeutic response, so ssDNA detection alone rarely identifies the underlying molecular intermediate or how it was generated. Here, we describe the principal sources of replication-associated ssDNA and review how different methods capture distinct aspects of these intermediates, including ssDNA exposure and accessibility, DNA termini, and their broader structural and replication context. As these features are shared across intermediates, individual readouts often capture multiple structures rather than uniquely identifying one. Reliable interpretation therefore requires integrating complementary signals with experimental perturbations and replication context. Future methods combining these features on individual DNA molecules may enable direct molecular classification of replication intermediates.
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mhryu@live.com
September 30, 3:01 PM
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Muconic acid is an industrially valuable molecule that can be biologically produced from diverse biogenic and waste-derived feedstocks, including sugars and lignin- and plastic-derived aromatic compounds. However, accumulation of protocatechuate (PCA) has been observed in multiple microbes engineered for muconate production when the PCA decarboxylase, AroY, is used. This raises the question of whether PCA decarboxylation represents a rate-limiting step and how this bottleneck might be alleviated, especially given the toxicity and reactivity of PCA and catechol intermediates. To address this, we performed adaptive laboratory evolution (ALE) on a strain of Pseudomonas putida originally engineered for muconate production from aromatic compounds, but with catBC restored, to select for improved conversion of PCA and, in separate lineages, 4-hydroxybenzoate. Contrary to our expectations, the predominant beneficial mutations localized to the catA1 cassette encoding catechol 1,2-dioxygenase, rather than aroY or its associated cofactor biosynthesis genes. Transcriptomic analysis revealed elevated catA1 expression in evolved isolates from ALE, and introduction of these mutations improved productivity in strains designed for muconate production from both aromatic and sugar substrates. Quantitative proteomics and biochemical assays demonstrated that the mutations also led to increased CatA1 protein abundance and modest enhancements in catalytic efficiency, respectively, with strain phenotypes largely driven by high CatA1 levels and potentially synergistic kinetic improvements. Additional reverse-engineering studies identified variants with modest effects on muconate accumulation, including those with potential to enhance biosynthesis of the prenylated FMN cofactor of AroY. Collectively, these results indicate that CatA, not AroY, is the main rate-controlling step in muconate production via the PCA decarboxylation route originally demonstrated by Draths et al., refining our understanding of pathway limitations and offering new strategies for improving rate and strain resilience in muconate bioproduction.
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mhryu@live.com
September 30, 1:24 PM
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Agrobacterium-mediated transformation is a cornerstone of plant genetic engineering, yet many crops remain recalcitrant to transformation and its efficiency is highly species- and genotype-dependent. The limited diversity of disarmed agrobacterial strains available for biotechnology, and the technically challenging workflows typically required for strain modification, constrain efforts to develop improved plant transformation platforms. Here, we describe the development of AGROtools-a versatile, expandable, and user-friendly modular cloning plasmid collection comprising more than 75 individual components, that is designed to simplify genetic engineering of agrobacteria. Constructs assembled with this toolkit couple visual reporters with selectable and counterselectable markers to facilitate identification of recombinant clones, thereby reducing reliance on PCR-based screening. We constructed and tested reporter cassettes that are functional across diverse agrobacterial strains and genomic contexts. By linking a visual reporter combinatorially with various antibiotic resistance markers and orthogonal site-specific recombinase recognition sequences, AGROtools can enable marker removal and recycling for up to four successive genomic modifications. We demonstrate the utility of AGROtools by disarming 10 novel wild-type strains, and accomplishing serial modifications within individual strain backgrounds. In addition to conventional recA-mediated homologous recombination, the collection incorporates components for applying contemporary strain engineering approaches, including CRISPR/dCas9 base editing, INTEGRATE-mediated targeted insertion, and phage-derived recombineering systems. Constructs can be assembled and deployed rapidly, enabling isolation of strains carrying an intended modification in less than two weeks. AGROtools provides a broadly applicable resource for accelerating strain development and genetic studies in agrobacteria, with potential to advance plant biotechnology by aiding improvement of disarmed strains.
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mhryu@live.com
September 30, 1:24 PM
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Microalgae represent a crucial, multifunctional microbial cell factory platform for renewable energy and climate change mitigation. Their notably high lipid content (often exceeding 70% DCW) and rapid growth rates, which significantly surpass those of traditional terrestrial crops, making them an ideal feedstock for diverse bioenergy applications. This review critically evaluates advanced conversion pathways for biofuels such as biodiesel and bioethanol, as well as biohydrogen production and bioelectricity generation via microbial fuel cell technology. It further explores key technical paradigms, including photobioreactor and open-pond cultivation systems, extraction techniques, and the critical role of transesterification for biodiesel synthesis. Uniquely, microalgae synergistically sequester atmospheric carbon dioxide (CO2) during the photosynthetic process and remediate nutrient-rich wastewater, positioning them as an effective feedstock model within a circular bioeconomy framework. Finally, this work delineates persistent techno-economic hurdles, such as high operational costs and harvesting inefficiencies, while proposing strategic future research directions in genetic engineering and system integration necessary to achieve global commercial scalability. Graphical Abstract
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Scooped by
mhryu@live.com
September 30, 1:24 PM
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Surface layers (S-layers) are paracrystalline protein lattices that form the outermost boundary of many archaeal and bacterial cells. Interest in S-layer biology has grown rapidly in recent years, driven by advances in structural and bioinformatic studies that have revealed new insights into lattice organization and function. In contrast, the mechanisms that anchor these lattices to the underlying cell envelope during growth, division, and cellular morphogenesis remain comparatively understudied. Because anchoring is dictated by the chemistry and architecture of the underlying cell envelope, we propose that S-layer anchoring strategies provide valuable insights into prokaryotic evolution. Based on recent experimental work and bioinformatic predictions, we summarize the major anchoring mechanisms found across archaea and bacteria. Our analysis reveals a recurring feature of S-layers: the arrangement of lattice-forming and envelope-proximal anchoring regions, frequently connected by linkers, generates an enclosed space near the underlying cell envelope, with an enigmatic biological role. We discuss possible contributions of this enclosed ‘epiplasmic’ space to mechanical scaffolding, chemical compartmentalization, and substrate harvesting.
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Scooped by
mhryu@live.com
September 30, 1:23 PM
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Diet shapes the composition of the gut microbiota; however, the specific effects of distinct food groups on microbiome dynamics are unclear, particularly in circumstances of extreme perturbation. Here we evaluated the relationship between diet and intestinal microbiome dynamics by precisely tracking 9,419 meals consumed by 173 patients who were hospitalized for haematopoietic cell transplantation and analyzing subsequent microbiome changes. Bayesian inference applied to data from 158 patients with paired longitudinal microbiome samples revealed that the intake of sweets and sugars during antibiotic exposure predicted exacerbated microbial dysbiosis, manifesting as lowered α-diversity and greater expansion of the pathobiont Enterococcus. Experiments in mice also showed that sucrose supplementation increased and prolonged antibiotic-induced Enterococcus expansion. These data suggest that avoiding a diet rich in simple sugars during antibiotic treatment may mitigate microbiota disruption. Further studies in independent cohorts will offer opportunities to generalize these findings and evaluate microbiota-sparing interventions. Avoiding a diet rich in simple sugars during treatment with antibiotics may mitigate microbiota disruption.
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mhryu@live.com
September 30, 12:47 PM
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The increasing demands of synthetic biology have shifted the central bottleneck from DNA assembly to DNA writing. As engineered systems grow in complexity, progress increasingly depends on the ability to write, test, and rewrite regulatory DNA to support fast design−build−test−learn cycles and precise control of gene expression. In this regard, enzymatic DNA synthesis offers a promising route toward next-generation DNA writing technologies for on-demand benchtop implementation. In particular, terminal deoxynucleotidyl transferase (TdT), a template-independent DNA polymerase, provides a unique mechanism for generating sequence diversity without predefined templates. Here, we establish a programmable TdT-based enzymatic platform for the in-house synthesis of random-sequence oligonucleotide libraries with tunable base composition. Systematic kinetic characterization of TdT revealed a substrate-dependent bias, which we mitigated through optimization of divalent cofactors and dNTP input ratios, enabling user-defined nucleotide distributions. Using this platform, we expanded and screened composition-controlled libraries of promoters, 5′-UTRs, and transcription terminators in Escherichia coli, identifying functional bioparts spanning wide dynamic ranges of transcriptional and translational activity. Integration of TdT-synthesized regulatory libraries into a streamlined enzymatic workflow enabled rapid cloning and screening within hours. As a proof of concept, targeted promoter diversification of a lycopene biosynthetic operon yielded a 124.7-fold range in production and identified variants achieving up to 1.43-fold higher titers than those of the parental strain. These results establish TdT-mediated enzymatic DNA synthesis as a controllable DNA writing modality for rapid regulatory-part engineering in synthetic biology and metabolic engineering.
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mhryu@live.com
September 30, 12:21 PM
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Cell-penetrating peptides (CPPs) and quorum-sensing peptides (QSPs) represent peptide functions related to intracellular delivery and microbial signaling. Sequence-based prediction remains difficult because benchmark embeddings often show uneven local support, overlapping class regions, and high dimensionality. A single classifier may therefore miss either local or global structure. We propose Stack-DCL, an out-of-fold stacking framework for CPP and QSP classification with fixed UniRep embeddings. Stack-DCL combines a density-aware weighted random forest, a cosine-neighborhood model, and an L2-regularized logistic regression classifier. The meta-learner is also logistic regression and fuses only positive-class probabilities generated from held-out folds, which reduces fusion-stage leakage. On benchmark train/test splits with five-fold cross-validation on training data and final held-out testing, Stack-DCL achieves independent-test AUC values of 0.980 for QSP and 0.974 for CPP. Ablation results indicate that the three branches capture local support, directional neighborhood similarity, and global linear separability as different representation-level signals. These results support Stack-DCL as a benchmark-level stacking design for the two evaluated peptide tasks.
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mhryu@live.com
September 30, 11:35 AM
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Polyethylene terephthalate (PET) is a widely used synthetic polymer that persists in the environment because of its resistance to biological degradation. Although engineered PET hydrolases have shown improved catalytic performance, translating these advances into effective whole-cell degradation remains challenging because cells and enzymes must interact with an insoluble polymer surface. We developed a synthetic bacterial consortium to investigate early PET surface colonization and biofilm formation. The system combined E. coli Nissle 1917 engineered for PETase expression with a biofilm-forming Pseudomonas putida strain evolved for growth on ethylene glycol. PET film incubation experiments, microscopy, biofilm quantification, and surface characterization were used to evaluate how extracellular enzyme targeting, consortium composition, and PET surface roughness influence microbial attachment. Co-culture experiments with PET films showed that surface attachment was strongly influenced by extracellular enzyme targeting and consortium composition. The strongest and most persistent attachment was observed when extracellular enzyme availability was paired with the biofilm-forming partner. Quantitative analysis showed an approximately 1.5-fold increase in biofilm formation in the engineered consortium relative to the control. In addition, mechanical roughening of PET surfaces further increased biofilm formation, indicating that surface accessibility is an important determinant of microbial attachment. Our findings show that PETase secretion, consortium composition, and polymer surface roughness may collectively influence biofilm formation on PET and could therefore be considered when designing future whole-cell PET bioprocessing systems.
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Scooped by
mhryu@live.com
September 30, 11:46 PM
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Recent advances in artificial intelligence have enabled models to capture protein sequence and structural features. We present PeTriPPI2, a hybrid framework for protein--protein interaction (PPI) prediction that combines sequence embeddings from ESM-2 with structural representations from PeTriBERT, an encoder originally designed for inverse folding. We evaluate this sequence--structure approach on the Pinder dataset. On a test set of 2,342 protein pairs, the selected checkpoint achieves 0.898 accuracy, 0.917 precision, 0.876 recall, and 0.896 F1 score for the interacting class (AUROC 0.963). Compared with SpatialPPIv2 on the same test data, PeTriPPI2 has higher precision (0.917 versus 0.886) but lower recall (0.876 versus 0.942) and F1 score (0.896 versus 0.913). Component ablations indicate that both the sequence and structural pathways contribute to this configuration.
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Scooped by
mhryu@live.com
September 30, 11:18 PM
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Bacterial spores pose a significant challenge to the food industry due to their ability to germinate from dormancy and their extreme resistance. Spores are encased by a multilayered proteinaceous structure termed the spore coat. Previous studies on spore coat assembly have predominantly focused on the interactions among coat proteins, while the involvement of broader protein quality control systems remains poorly understood. Here, we demonstrate that the molecular chaperone DnaK is essential for the proper assembly of the inner spore coat in Bacillus subtilis. Deletion of dnaK leads to mislocalization of key morphogenetic protein SafA, reduced accumulation of full-length SafA, altered transcriptional dynamics of spoIIID and sigK, and ultimately impaired coat integrity and function. Our findings reveal that DnaK facilitates spore coat assembly through both transcriptional and post-translational mechanisms, uncovering a previously unrecognized regulatory layer in spore coat morphogenesis.
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mhryu@live.com
September 30, 4:16 PM
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Proviruses are widespread components of prokaryotic genomes, yet their characterization is impeded by border identification errors. We developed ProBord (Provirus Border Delimiter), a tool achieving single-base-precision border mapping via cross-genome attB site alignment. Using ProBord, we built a database of 430,134 border-delimited proviruses (BDPs). Our analysis revealed that BDPs carry diverse functional genes, including virulence and antibiotic resistance determinants, as well as defense and antidefense systems, with position-specific distributions. Furthermore, comparing BDPs with border-undelimited proviruses (BUPs), whose boundaries could not be precisely delimited by ProBord, revealed a universal pattern of proviral domestication: BUPs selectively lose viral core genes but retain host-beneficial functions through rapid deletion or progressive mutation. Critically, integrating the tool ProAct (Provirus Activity Detector) with ProBord enabled reverse mining of 101 “dark” proviruses (DPs), which are overlooked by mainstream prediction tools. Most of these DPs were associated with pathogenic bacterial hosts. This integrated framework combines tools, theory, and resources—including more than 430,000 BDPs, 4910 active proviruses, and 101 DPs—to decipher the composition, function, and evolution of proviruses in prokaryotes.
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mhryu@live.com
September 30, 3:11 PM
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DMSO reductase (DMSOR) family found in prokaryotes is the most diverse group of molybdenum cofactor (Moco) containing enzymes from the structural as well as the catalytic viewpoints. While DMSOR, the prototype member of its family, is well characterized thanks to decades of rigorous research, a large majority of this family are yet to be characterized. These enzymes are important in biogeochemical cycles, biotechnology and health. With the discovery of new DMSOR family members, the family continues to grow further underscoring their importance. This review will focus on the latest developments in the DMSOR reductase family.
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mhryu@live.com
September 30, 3:06 PM
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Deep learning has substantially advanced structure-based enzyme design, yet reliably creating highly efficient enzymes remains out of reach. One emerging enzyme design strategy combines diffusion-based scaffold generation around active-site models with sequence design. Such structure-based approaches have expanded the accessible reaction space and enabled the emergence of enzymes with diverse catalytic functions and complex catalytic motifs. Despite notable catalytic efficiencies (kcat/KM), turnover rates (kcat) often remain limited, suggesting that current approaches typically yield tight substrate binders rather than enzymes that selectively stabilize the chemical transition state. Computational design of electrostatic catalysis, multistate behavior, and conformational dynamics could potentially enhance transition-state stabilization and improve catalytic activity. More reliable activity oracles, integration of evolutionary information, protein language models, and lab-in-the-loop optimization could further enhance design performance. Ultimately, advancing structure-based enzyme design will require directly targeting the physicochemical drivers of catalysis to move beyond substrate binding toward the reliable design of efficient catalysts.
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mhryu@live.com
September 30, 2:42 PM
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Post-translational modifications (PTM) provide molecular variety beyond the gene or amino acid codes. Diversity stems from a vast number of chemical species or physical changes that are regulated either enzymatically or non-enzymatically to provide transient or prolonged alterations to protein structure and function. Bacteria are wrongly considered “simple” due to their relatively small genomes; however, application of high-resolution methods in enrichment, identification, and quantitation by mass spectrometry (MS) has unleashed a plethora of site-specific PTM data unequivocally demonstrating that bacteria can undertake almost all modifications seen in eukaryotes, while also maintaining novel PTMs that occur specifically in these organisms. Despite this, our ability to exploit omics-level PTM data has not been comparable; determining site stoichiometry, understanding the roles conferred by PTMs, and characterizing the functions of identified PTM sites remain to be routinely achievable at scale. This review examines major PTMs and their importance in generating functional variations in bacterial proteins.
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mhryu@live.com
September 30, 1:24 PM
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Crohn’s disease (CD) is characterized by low microbial richness and diversity of the gut microbiome, shifts in the abundance of specific taxa, reduced presence of C2-C6 organic acid producers, especially butyrate-forming bacteria, and alterations in gut metabolites. This study aimed to demonstrate differences in the dynamics and fermentation activity of the fecal microbiota of CD patients and healthy individuals (HI) grown in vitro on glucose or a mixture of acetate and lactate (fecal microbiota batch cultures). Glucose was used as a substrate for glycolytic fermentation, whereas a mixture of acetate and lactate supported related pathways leading to the production of C2–C6 organic acids, particularly butyrate via the conversion of lactate and acetate. HI fecal microbiota cultures produced butyrate mainly through lactate and acetate transformation rather than via glucose fermentation. This pathway was impaired in the CD fecal microbiota cultures, which exhibited reduced synthesis of butyrate, valerate, caproate and propionate, and excessive production of ethanol and certain amino acids. These distinct fermentation activities stemmed from differences in the original CD and HI fecal microbiota composition that were further accentuated in batch cultures. The number of beneficial commensal bacteria (e.g., Coprococcus catus, Ruminococcus torques, Gemmiger formicilis, Eubacterium rectale, Fusicatenibacter saccharivoransi, Faecalibacterium prausnitzii) were significantly lower in the CD fecal microbiota cultures and correlated with reduced butyrate, valerate and caproate levels. Conversely, an overabundance of the recognized CD dysbiosis-associated bacteria, such as Escherichia coli, was reflected in elevated ethanol and amino acid levels in post-fermentation liquids. Metabolic potential analysis further indicated an enrichment of genes encoding enzymes involved in ethanol and amino acid biosynthesis in CD fecal microbiota cultures and highlighted the metabolic versatility of E. coli. Fermentation patterns of fecal microbiotas in batch cultures can distinguish CD-associated dysbiosis from a healthy microbiome, with particular emphasis on lactate and acetate conversion to butyrate as a key pathway of butyrate production. The differences are observed under standardized in vitro conditions without the need to reconstruct the intestinal environment. These findings, pending further validation, may offer novel diagnostic opportunities and have implications for strategies aimed at restoring a healthy gut microbiome.
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mhryu@live.com
September 30, 1:24 PM
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Regulatory RNAs have long been recognized as major post-transcriptional regulators of bacterial physiology, controlling diverse processes including metabolism, stress adaptation, quorum sensing, and virulence. Recent discoveries have expanded their functional repertoire, revealing that both bacterial and phage-encoded regulatory RNAs contribute to multiple aspects of host-bacteriophage interactions. Beyond regulating cellular physiology, regulatory RNAs influence bacterial defense through immune regulation, RNA-guided immunity, dormancy, and abortive infection pathways, while phage-encoded regulatory RNAs can reprogram host gene expression, promote lysogeny, and allow evasion of bacterial defense mechanisms. In this article, we discuss recent advances in the roles of regulatory RNAs during host–phage interactions, focusing on emerging mechanisms through which RNA-mediated regulation influences both bacterial defense and phage counter-defense.
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Scooped by
mhryu@live.com
September 30, 1:24 PM
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Anti-CRISPR (Acr) proteins inhibit CRISPR-Cas immunity and are key targets for precise control of CRISPR-based genome editing and phage–host coevolution research. Their experimental identification is costly and low-throughput, so computational predictors are used to prioritise candidates for testing. In this setting validated positives number in the hundreds while phage-derived putative negatives reach tens of thousands, producing extreme class imbalance. Yet existing classification-based predictors train and evaluate on 1:1 balanced datasets and allow high-similarity sequences between training and test, overestimating real-world performance. We present AcrSeek, a metric-learning framework that trains a projection head over a frozen protein language model (PLM) encoder with hybrid negative mining (offline global plus online semi-hard) under a joint triplet–focal objective. Under nested 5-fold cross-validation with leakage controlled by 40% identity clustering, AcrSeek improved AUPRC on the imbalanced (1:383) test set from 0.017 to 0.355 over AcrNET (matched PLM backbone), reaching 0.508 with ESM-2 3B. AcrSeek therefore remains structurally robust under extreme class imbalance and may also serve other protein-function detection problems with scarce positives.
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Scooped by
mhryu@live.com
September 30, 1:11 PM
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Generative artificial intelligence (AI) models are revolutionizing biology, with tools such as AlphaFold 3 and protein design models accelerating breakthroughs in protein structure prediction and the creation of new functional proteins. Tracking and establishing the provenance of AI-generated protein sequences and structures is becoming increasingly important to tackle a range of emerging challenges, including biosecurity and concerns about information veracity. Here we introduce SynthIDBio, a family of methods for watermarking protein sequences and structures to establish the provenance of those generated with AI. SynthIDBio-sequence actively embeds a watermark into protein sequences while preserving function. We demonstrate this by creating watermarked, functional designed protein binders with binding affinity comparable with non-watermarked counterparts and near-perfect watermark detection accuracy. Furthermore, SynthIDBio-structure, a fine-tuned AlphaFold3 model, embeds an imperceptible watermark into biomolecular structures. Our work is a proof-of-concept that function-preserving biological watermarking is feasible, introducing a potential tool for provenance in the rapidly expanding era of AI-driven biological engineering. SynthIDBio watermarks AI-generated protein sequences and structures while preserving function, enabling provenance detection and offering a proof-of-concept tool for biosecurity and information integrity.
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Scooped by
mhryu@live.com
September 30, 12:27 PM
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l-Glutamic acid is conventionally produced by bacteria from starch-derived sugar, while its production in eukaryotic hosts remains rarely reported. The thermophilic ascomycete fungus Myceliophthora thermophila has been developed as a platform for producing value-added chemicals from lignocellulosic biomass. In this study, we explored the feasibility of engineering M. thermophila for l-glutamate production from biomass-derived carbon sources. Genome-scale metabolic modeling indicated that M. thermophila has the stoichiometric capacity to synthesize l-glutamate from glucose and ammonia. Experimental fermentation confirmed extracellular l-glutamate accumulation, and medium optimization revealed that nitrogen source selection and extracellular pH homeostasis strongly affected l-glutamate accumulation. Overexpression of the native NADPH-dependent glutamate dehydrogenase gene gdh1 markedly increased glutamate production. Additional engineering strategies targeting membrane-associated metabolism, glutamate transport, mitochondrial precursor transport, and competing α-ketoglutarate-consuming pathways provided insights into the regulation of glutamate metabolism in filamentous fungi. The engineered strain produced 3.41 g/L l-glutamate from glucose. Moreover, 1.50 g/L and 1.49 g/L l-glutamate were obtained directly from cellulose and raw corncob, respectively. This study establishes M. thermophila as a proof-of-concept thermophilic fungal platform for l-glutamate production from lignocellulosic carbon sources and provides a framework for engineering amino acid biosynthesis in cellulolytic fungi.
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mhryu@live.com
September 30, 12:18 PM
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Microbial taxa in the soil microbiome with specific ecological functions play crucial roles in plant health. Flavobacterium is found closely associated with physiological functions that promote plant growth and enhance disease resistance. While cooperative interactions mediated by metabolite exchange can stabilize microbial consortia, the specific interactions between these consortia and plants remain understudied, particularly regarding their application in plant disease control. Here, we isolate a natural microbial consortium comprising Achromobacter, Flavobacterium, and Bacillus strains from cucumber rhizosphere soil, and identify the Flavobacterium strain as a methionine auxotroph. This study reveals the metabolic interactions among strains within a cross-feeding-based consortium. The Achromobacter and Bacillus primarily metabolize carbon and nitrogen sources, respectively, whereas the relevant genes in the Flavobacterium are significantly downregulated. The consortium develops significantly enhanced biofilms with a distinct stratified architecture, facilitating root endophytic colonization by Achromobacter and Flavobacterium. Endophytic Flavobacterium induces systemic resistance in plants, thereby enhancing resistance against phytopathogenic fungal infections. Our findings reveal a novel ecological strategy employed by auxotrophic Flavobacterium species for both microbial interactions and root endophytic colonization and provide a theoretical foundation for microbial consortium-based microbial inoculants in plant disease management.
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