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mhryu@live.com
Today, 1:20 AM
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Profiling microbiomes is an important way to understand the function and composition of communities in the wild, but natural microbiomes are often highly complex and often unamendable to experimentation to reveal cause and effect relationships. By using a small group of cultivable strains to represent those found in the wild, synthetic communities are one solution to this problem. Here we describe the MAize Rhizosphere Synthetic Community (MARSc), a genome-enabled 31-member bacterial community representative of the diversity found on the roots of maize grown in Iowa soils. This community is built around Pseudomonas putida KT2440, a model maize rhizosphere colonist and synthetic biology chassis. We characterized microbe-microbe interactions and biofilm formation of MARSc members in a variety of environmental contexts, finding that both behaviors are broadly controlled by nutrient levels. Genomic analysis and microbiome profiling of these organisms revealed that annotated biofilm genes (such as surface attachment and exopolysaccharide production) correlated to rhizosphere colonization, but neither trait correlated to in vitro biofilm formation. In vitro interactions assay findings were surprisingly consistent with co-correlations of rhizosphere abundance amongst MARSc members on roots. Finally, we found that when applied to the roots, MARSc can increase maize growth under nitrogen-limiting conditions. Altogether, MARSc is a useful tool for identifying some of the factors influencing rhizosphere microbiome assembly and will be a strong foundation for further work in this area.
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mhryu@live.com
Today, 1:11 AM
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Mechanistic ordinary differential equation models are widely used in systems biology to represent biochemical networks, population dynamics, cell-state transitions, and other biological processes; however, their predictive value depends critically on accurate parameter estimation from noisy and often sparse experimental data. In this tutorial, we present the Weak-form Estimation of Nonlinear Dynamics (WENDy) method as a forward-solver-free approach that reformulates parameter estimation as a covariance-corrected weak-form regression problem by integrating the model equations against compactly supported test functions. We present the background on the methodology through the lens of the familiar logistic equation, and we demonstrate applications of the method on real experimental data through two systems biology examples: a glycolytic oscillator with relatively dense time-course data and a sparse epithelial-mesenchymal cellstate transition model with multiple experimental replicates. Ultimately, using WENDy, we estimate interpretable biological parameters with uncertainty for systems with noisy and sometimes sparse available experimental data.
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mhryu@live.com
Today, 1:06 AM
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Bacterial bioremediation involves bacterial strains and communities and their complex interactions with the environment, aiming to restore ecological balance by degrading contaminants in natural systems (soil, water, air). These processes rely on coordinated gene clusters encoding catabolic pathways. Many xenobiotic-catabolic gene clusters (XGCs) reside on mobile genetic elements (MGE), enabling horizontal gene transfer (HGT) and genome rearrangements that drive rapid microbial adaptation to anthropogenic contaminants. Here we review the evolutionary and ecological roles of HGT and genome restructuring in assembling and optimizing biodegradative functions. We introduce the concept of metabolic HGT hubs—microbial taxa, mobile elements, and ecological features that serve as central nodes for gene exchange—facilitating metabolic innovation and cooperation within microbial consortia. These processes enhance ecosystem resilience and pollutant degradation efficiency by promoting functional redundancy and metabolic division of labor. Understanding these dynamics informs strategies for engineering microbial communities and genetic bioaugmentation to improve bioremediation outcomes. Our perspective highlights bioremediation as an extension of metabolic network evolution under anthropogenic selection, emphasising both its potential and the need to consider ecological and biosafety implications.
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mhryu@live.com
Today, 12:41 AM
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Programmable molecular biology increasingly requires strategies for converting engineered recognition or proximity modules into measurable outputs, particularly within transcriptional regulation, RNA imaging, and CRISPR-associated systems. Synthetic chemically induced dimerization (CID) systems provide a class of programmable recognition modules for such applications, yet generalized strategies for coupling structurally diverse CIDs to functional readouts remain limited. Here, we introduce a CID-to-output conversion strategy based on engineering of the linker-mediated coupling interface. Using single-fluorescent-protein sensors as an experimentally tractable optical model readout, we systematically varied paired N- and C-terminal linkers flanking circularly permuted green fluorescent protein (cpGFP) to map coupling landscapes across synthetic CID systems derived from combinatorial selection and computational protein design. The results revealed strong non-additive interactions across paired linkers and suggest that linker length is a first-order determinant of CID-to-output coupling. Across nanobody-, monobody-, and de novo-designed CID architectures, this framework yielded functional sensors with dynamic ranges up to 1270% and robust responses in mammalian cells. Together, this work demonstrates that effective CID-to-output conversion can be achieved by empirically mapping the linker-mediated coupling interface, providing a practical route for adapting synthetic CID to diverse programmable molecular readouts and nucleic-acid-associated synthetic biology systems
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mhryu@live.com
Today, 12:35 AM
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Protein-quality-control systems are essential for cells to maintain protein homeostasis during both steady-state growth and acute stress. Yet, how individual chaperone molecules dynamically reorganize in living cells as protein unfolding and aggregation rates change, remains poorly understood. Here, we use super-resolution imaging and single-molecule tracking to define the in vivo dynamics of the bacterial heat shock protein 70 (Hsp70) DnaK in live E. coli. We found that majority of DnaK molecules actively engage with the proteome already at the optimal growth temperature, while heat stress induces the accumulation of a distinct slow-moving DnaK population with increased dwell times. These interactions occupy different intracellular regions, suggesting spatially separated chaperone activities. Finally, DnaK folding activity becomes burdened in cells lacking co-chaperones, such as IbpAB, HtpG or DnaJ. Overall, our findings reveal transient proteome interactions as a main chaperone mode of action, enabling DnaK to sense and mitigate proteotoxic stress in living cells.
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mhryu@live.com
July 9, 11:41 PM
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Currently, fossil fuels are the main and dominant sources for producing fuels and commodity chemicals. The rising demand for fossil fuels continues to entrench global dependency on non-renewable sources creating the climate risk, the economic instability and sustainability challenges. Hence, there is a need to shift towards globally available, sustainable and renewable resources such as lignocellulosic biomass (LCB) that offers a sustainable pathway for producing biofuels and chemicals. Though various technologies are available for LCB conversion to biofuels and chemicals, scaling up of biorefineries remains stifled by its recalcitrance nature and volatile supply chain economics. LCB processing often requires pretreatment to disrupt the rigid lignin–hemicellulose barrier and decrystallize cellulose. This structural opening is essential to maximize the enzymatic hydrolysis and sugar yields for biofuel production. The pretreatment process is energy-intensive and expensive accounting for 40% of the overall biofuel production cost followed by hydrolysis using expensive enzyme cocktails. These economic barriers currently limit the adoption of LCB as a cost-competitive fuel resource. The promising strategy for low cost LCB derived ethanol production is to adopt integrated biorefinery approach utilizing physical, chemical and biological processes. The integrated biorefinery approach tackles the high costs of second generation ethanol production by mimicking traditional petroleum refineries. It valorizes all three LCB components to marketable fuels and high-value chemicals maximizing the overall process profitability. This review discusses on the latest developments in biofuels production processes especially in relation to ethanol and butanol production.
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mhryu@live.com
July 9, 11:10 PM
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"Aerobic glycolysis” is a widely used term whose current meaning has drifted from its original usage in a way that has created confusion and inaccuracy. This drift has weakened “aerobic glycolysis” as a hypothesis-testing framework, despite the critical importance of glycolysis in understanding cellular bioenergetic behavior. Here, we examine the historical and contemporary uses of “aerobic glycolysis” and the related “Warburg effect”. We argue that “aerobic glycolysis” as originally investigated was essentially a bioenergetic phenomenon. We review the bioenergetic model of glycolysis and mitochondrial respiration as ATP supply pathways operating together to meet cellular ATP demand. A bioenergetic view of aerobic glycolysis clarifies that it is not a less desirable contingency or indicator of pathology, but rather a part of a kinetically regulated system of cellular energy supply. On this basis, the operation of glycolysis under many different physiological and pathological conditions can be better interrogated and understood. This Perspective examines how “aerobic glycolysis” originally described a bioenergetic system behavior. Reintroducing a bioenergetic conceptual framework to this term could strengthen its meaning and resolve confusion in the field.
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mhryu@live.com
July 9, 10:57 PM
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Millions of phage genomes have been mined from metagenomic data recently but the genome completeness remains poor because of the limitations of existing phage detection methods, which rely on metagenomic contigs that fragment phage genomes. Here, we present PALACE, a conjugate-graph-based framework for assembling high-quality phage genomes from metagenomes. PALACE incorporates homology-based and deep-learning-based methods to detect phage signals and constructs a conjugate graph from the metagenomic sample. On simulated data, PALACE generates accurate and complete phage genomes, achieving an F1 score of 0.92–1.00 across simulation settings, outperforming the second-best method by 0.21–0.48. Applying PALACE to 914 gut metagenomic samples from healthy controls and participants with colorectal cancer (CRC) yielded 5,306 high-quality phage genomes, outperforming the second-best benchmark method by 55.98% in median genome completeness. We observed a high degree of functional organization for genes within phage genomes. Phages from participants with CRC exhibited a notable enrichment of metabolic factors, suggesting their adaptation to nutrient availability in the CRC gut environment. PALACE combines homology features and deep learning to improve phage assembly from metagenomics.
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mhryu@live.com
July 9, 4:46 PM
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Cas12a2 CRISPR nucleases, including SuCas12a2, have been shown to have extensive collateral activity towards RNA, ssDNA, and dsDNA. This collateral activity results in targeted cell elimination and has applications across biotechnology, agriculture, and human health. We explored the natural genetic diversity of Cas12a2 nucleases and characterized nine novel orthologs in a DNA damage kinetic assay in E. coli. Three new Cas12a2 orthologs (RsCas12a2, SdCas12a2, and HmCas12a2) were shown to have high collateral activity towards DNA. These nucleases are highly divergent from SuCas12a2, have conserved core RuvC catalytic residues, and have sequence diversity in the previously reported aromatic clamp residues required for nucleic acid positioning in the active site. We defined PFS preferences and mismatch tolerance for each high-activity Cas12a2 nuclease, expanding the available Cas12a2 toolbox, and discovered functional differences with obvious impacts on downstream applications.
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mhryu@live.com
July 9, 4:34 PM
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Sustainable hydrogen production from microalgae remains limited by intrinsic physiological constraints and the need to preserve biomass value for food and feed applications. Transgenic approaches to overcome these limitations were proven successful, yet result in genetically modified (GMO) strains that face major regulatory and deployment barriers. Here, we present a non-GMO experimental platform that enables systematic isolation of hydrogen-producing phenotypes through high-throughput UV mutagenesis pipline coupled with targeted physiological screening. Applying this approach across phylogenetically distinct algal species, including the industrial strain Chlorella vulgaris and the extremophile Chlorella ohadii, we achieve high discovery efficiency, recovering 0.4-0.6% validated hydrogen-producing mutants and achieving 6.7-25% validation rates among screen-positive candidates, indicating strong enrichment at the primary screening stage. We show that sustained hydrogen production represents a physiologically accessible state emerging across diverse genetic backgrounds. This state is consistently associated with reorganization of photosynthetic electron partitioning, yet arises through multiple distinct configurations that differentially balance hydrogen production, oxygen metabolism, and carbon fixation. This framework provides a scalable route to identify hydrogen-producing strains in industrially relevant algae without introducing foreign DNA and expands the accessible design space for photobiological hydrogen production.
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mhryu@live.com
July 9, 4:24 PM
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Genomic pathogen surveillance is a powerful tool for public health and research, but is costly and unachievable in low-resource settings. Most sub-genomic typing methods sacrifice resolution whilst remaining costly. We developed “Phylo-Plex”, a novel approach that identifies information-rich genomic regions to maximise phylogenetic information whilst minimising the number of regions. Applied to Treponema pallidum and Neisseria gonorrhoeae, we designed a high-resolution multiplex PCR sequencing scheme for lineage tracking pathogens with different extremes of genome variation. For Treponema pallidum, we also designed and evaluated the Phylo-Plex scheme in the laboratory and field settings by sequencing 72 clinical samples using MinION Flongle cells. Our T. pallidum scheme comprising 59 multiplex amplicons achieved high discrimination of fine-scale sublineages comparable to those defined using whole genomes, and demonstrating a qPCR detection limit ≤Ct 32. Variant calls from MinION amplicon sequencing were highly correlated with Illumina whole genome sequencing. We successfully deployed the method in a low-resource laboratory in Zimbabwe, costed at <£300/24 samples (£12.47/sample). Phylo-Plex enables low-cost tracking of priority pathogenic lineages in low resource settings and at scale. Whole genome sequencing of pathogens is costly to implement, and partial sequencing sacrifices information. Here, the authors present Phylo-Plex, a method for identifying information-rich genomic regions to enable sequencing of a subset of regions whilst maximising phylogenetic information.
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mhryu@live.com
July 9, 2:31 PM
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Viruses interact with all domains of life and play fundamental roles in shaping biological systems from individual hosts to global ecosystems. Yet their identification remains difficult due to a lack of a universal marker gene and the extensive diversity of viral genomes. Despite this, the speed of viral discovery is quickly increasing, driven by the growing number of virome studies, improved sequencing technologies and the decreased cost of sequencing. In this review, we examine the evolution of virus identification approaches from classical and molecular methods to contemporary genome-resolved and computational frameworks. By aggregating genome-resolved virome studies from 2010 to early 2026 that meet defined criteria (n=502), we synthesize the current landscape of virus identification methods, including similarity-based, sequence-based artificial intelligence (AI) and hybrid approaches. We also highlight the key limitations of the current methods, particularly biases in reference databases that contribute to persistent viral ‘dark matter’. Finally, we identify emerging opportunities for the field in structure-based and AI-driven approaches that extend detection beyond sequence similarity and outline how these integrative frameworks are poised to improve virus discovery across ecosystems.
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mhryu@live.com
July 9, 2:17 PM
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This book presents experimental and computational methods for constructing and interrogating synthetic gene circuits across multiple organizational scales.
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Scooped by
mhryu@live.com
Today, 1:17 AM
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CRISPR systems have revolutionized microbial genome editing. However, their reliance on DNA double-strand breaks (DSBs) and homologous recombination limits applications such as large DNA integration and engineering nonmodel microorganisms. CRISPR-associated transposase (CAST) systems provide a promising alternative, enabling DSB-free, recombination-independent, and programmable integration of large DNA fragments. This review summarizes the discovery and characterization of diverse CAST systems, the engineering strategies to enhance integration efficiency and specificity, and their applications in microbial engineering. Current limitations and future directions are also discussed. Overall, CAST systems hold great potential for advancing microbial genome editing, particularly in multi-copy DNA integration and genetic reprogramming of nonmodel microorganisms and complex microbial communities.
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Scooped by
mhryu@live.com
Today, 1:09 AM
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Recent advances in large-scale sequence mining have expanded our knowledge of RNA virus diversity. Most genome mining approaches for detecting RNA viruses rely on identifying the conserved RNA-dependent RNA polymerase (RdRp) by scanning sequencing datasets with specialized profile Hidden Markov Models (pHMMs). Recently, several new pHMM databases for RdRp detection have been released, each following distinct design principles. However, their relative performance remains unclear, and their accessibility to users without advanced computational expertise is limited. Here, we introduce the RdRp Collaborative Analysis Tool with Collections of pHMMs (RdRpCATCH: https://github.com/dimitris-karapliafis/RdRpCATCH), a platform that consolidates publicly available RdRp pHMM resources into a single, user-friendly framework. RdRpCATCH enables the scanning of (meta)transcriptomic assemblies to discover RNA viruses and provides subsequent taxonomic annotation of detected contigs. A comparative analysis of RdRp pHMM databases reveals that most are highly effective at detecting the known diversity of RNA viruses while minimizing false positives, supporting their joint use within RdRpCATCH. RdRpCATCH is distributed as both a conda package and a web server application (https://rdrpcatch.bioinformatics.nl), facilitating access for researchers with diverse levels of computational expertise. By integrating multiple pHMM resources, this unified framework addresses fragmentation in the field and reduces technical barriers, enabling comprehensive viral discovery.
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Scooped by
mhryu@live.com
Today, 12:52 AM
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Artificial intelligence is rapidly transforming everyday life and driving major advances across science. De novo enzyme design is an area of particular promise, with implications for medicine, biotechnology, and industry. Recent applications of AI-enhanced methodologies have yielded a range of enzymes with catalytic activities that were previously unattainable through conventional approaches. This perspective surveys emerging strategies and computational models that are redefining enzyme engineering and examines the opportunities and challenges on the path toward truly on-demand enzyme design.
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mhryu@live.com
Today, 12:38 AM
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The bacterial three-hybrid (B3H) assay is a powerful genetic tool for detecting interactions between RNA and RNA-binding proteins (RBPs) and assessing the consequences of RBP mutations. This transcription-based system connects the strength of an RNA–protein interaction to the expression of a lacZ reporter gene in E. coli cells. This in vivo approach allows researchers to dissect RNA-protein interactions within a cellular environment, bypassing the need for biochemical purification of RNAs or proteins. This chapter details a three-day protocol for generating quantitative B3H data. Since a significant challenge in B3H assays is RNA misfolding, we describe a recently optimized set of B3H constructs that mitigates this issue by isolating bait RNAs as discrete folding units.
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Scooped by
mhryu@live.com
Today, 12:09 AM
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Plant viruses, once viewed as harmful agricultural pathogens, are now powerful tools in biotechnology. Their nanoscale structure, self-assembly, and biocompatibility enable applications in agriculture, medicine, and environmental sustainability. They serve in gene delivery, genome editing, diagnostics, and nanomaterials for vaccines and drug delivery. Integration with AI, ML, and bioinformatics enhances virus discovery and prediction. Despite challenges, plant viruses are emerging as versatile, sustainable resources for global biotechnological innovations.
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mhryu@live.com
July 9, 11:37 PM
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Membrane-associated biomolecules, primarily proteins, are key enablers of communication, responsiveness, and complexity in natural living cells. Aiming to mimic these capabilities, there is growing interest in equipping bottom-up synthetic cells with membrane-associated biomolecular components. In this review, we focus on how proteins and nucleic acids have been associated with synthetic cell membranes, particularly lipid vesicles, to enable the transmission of signals across the membrane. We discuss strategies for anchoring these biomolecules into lipid bilayers and review how they can enable essential signalling mechanisms in synthetic cells, including cell tethering, the generation and fusion of vesicles, and signal transmission and transduction. We highlight how proteins offer native biological functionality, while nucleic acids may bring more modularity and control. Advancing this area will be essential for realising synthetic systems capable of studying natural communication mechanisms and unlocking applications in biosensing, therapeutics, and synthetic tissue engineering.
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mhryu@live.com
July 9, 11:02 PM
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Cells are the fundamental unit of life. Yet there is no natural cell for which all its life-essential functions are understood. Here we demonstrate a complete cell cycle for a synthetic cell undergoing selection, with genome replication, growth, resource acquisition via feeding, and genetically encoded division. The cell is encoded via a 90kb genome that includes functions needed for resource uptake, transcription, translation, growth, genome replication, and division. The resulting synthetic cell is sufficiently encouraging to support routinization of synthetic cell engineering workflows, and will ultimately underlie diverse applications across all of biotechnology.
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mhryu@live.com
July 9, 4:51 PM
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Genetic manipulation of bacteriophages is essential for interrogating phage biology and advancing antimicrobial therapies. However, current genome editing approaches can be inefficient, require multiple steps, or drastically reduce phage titers. Here, we show that targeted DNA nicking enables template-mediated editing of phage genomes in one step without reducing phage titers. Using T7 phage, we show that Cas9-mediated nicking achieved up to 100% recombination across multiple loci, including substitutions and deletions of up to 200 bp and insertions of up to 500 bp, all while preserving phage titers. Editing in T7 was RecA-independent and extended to other phages. Leveraging high titers, we engineered a T7 library of over 440,000 tail-fiber mutants, with isolated mutants restoring infection of two LPS-deficient E. coli hosts by shifting recognition to core LPS components. Overall, DNA nicking is a simple and distinct editing strategy that can advance phage genome engineering, genetic interrogation, and antimicrobial development.
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mhryu@live.com
July 9, 4:37 PM
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Many bacterial antiphage defence systems are encoded by mobile genetic elements, yet much of this antiviral repertoire remains undiscovered. Antimicrobial-resistance plasmids are well known for disseminating antibiotic-resistance genes, but their contribution to bacterial immunity remains largely unexplored. Using phenotype-guided interrogation of a naturally occurring methicillin-resistant Staphylococcus aureus plasmid, we identify Evangelion, a widespread family of single-gene anti-phage defence systems in which a conserved DUF4062 core is coupled to a diversified auxiliary region required for defence activity. Evangelion systems are enriched on antimicrobial-resistance plasmids but are distributed across diverse bacterial hosts and mobile genetic elements, revealing an evolutionarily conserved defence architecture that has diversified through horizontal gene transfer and adaptation to distinct phage environments. Genetic, structural and evolutionary analyses support a model in which Eva01 senses intracellular phage replication-associated processes and couples activation of a DUF4062 effector to NAD⁺ depletion and abortive infection. Together, our findings define a previously unrecognised family of mobile anti-phage defence systems, establish DUF4062 proteins as a new component of the bacterial anti-phage repertoire, and demonstrate that phenotype-guided interrogation of mobile genetic elements provides a powerful strategy for discovering defence systems beyond the reach of current computational approaches.
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mhryu@live.com
July 9, 4:26 PM
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The basidiomycete Ustilago maydis is a well-characterized model organism for studying pathogen-host interactions and of great interest for a broad spectrum of biotechnological applications. We set here to develop light inducible molecular tools to enable dynamic studies on signaling networks and fungi-host communication, and for metabolic engineering approaches. In particular, light-controlled, optogenetic switches provide quantitative, spatio-temporal control capabilities, are minimal invasive and reversible. We engineered two blue light-inducible LOV-domain-based gene expression switches, to up- (Blue-ON) and down-regulate (Blue-OFF) gene expression, and performed a functional characterization in sporidia and hyphae of U. maydis. Profiting from the dynamic control ranges and rapid kinetics, we implemented the optogenetic switches to control cell morphology by initiating the transition from a haploid sporidial cellular morphotype to filaments upon regulation of the levels of the polarity factor Rac1 and its constitutive active mutant Q61L. In addition to showing how expression level of effectors can be precisely regulated as an approach to understand fungi-plants interaction, we show in two proof-of-principle applications targeted control over U. maydis filamentous fungal invasion of plant tissue and the mechanisms of tumor formation. For this we placed under Blue-ON and Blue-OFF control two U. maydis effectors, See1 (Seedling efficient effector 1) and TIN2 (Tumor inducing 2), and tumor formation was assayed on maize leaves. Taken together, this study established blue-light switches as effective tools to control morphogenesis and pathogenesis in U. maydis.
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mhryu@live.com
July 9, 4:03 PM
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Correct folding of outer membrane proteins (OMPs) by the β-barrel assembly machinery (BAM) is essential for maintaining the outer membrane (OM) barrier function of diderm bacteria. When OMP biogenesis is perturbed, the β-barrel assembly enhancing protease A (BepA) binds to BAM to mediate quality control, but how BepA interacts with BAM and degrades substrate OMPs remains unclear. Here, cryoEM structures of BAM-bound BepA reveals that BepA induces large conformational changes in the BAM complex enabling the enzyme to poise its active site within the periplasmic ring of BAM, beneath the BamA barrel. The lid of BepA is dynamic, embedding two of its water-soluble helices deep into the membrane bilayer when BAM-bound, which readies BepA for proteolysis of misfolding OMPs. Movement of BepA’s plug is triggered by OMP binding rather than interaction with BAM, activating the enzyme for cleavage. We reveal BepA preferentially recognises Aromatic-X-Aromatic (Ar-X-Ar) motifs which are enriched in OMP sequences. The results reveal a mechanism for proteolytic degradation by BepA in OMP quality control which requires interaction with BAM, the membrane, and its OMP substrates. Here the authors show that BepA is activated to degrade stalled outer membrane proteins on BAM through binding to BAM, inducing conformational changes, membrane embedding its water-soluble lid, and triggering plug movement upon substrate binding to enable proteolysis.
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mhryu@live.com
July 9, 2:22 PM
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Metrics such as alpha diversity, inferred functional potential and network complexity have become standard metrics in microbiome research. While they offer convenient ways to summarize complex data, these metrics may sometimes obscure more than they reveal. Alpha diversity, for example, measures richness and evenness. However, two samples may exhibit identical diversity scores, yet one could be dominated by beneficial taxa and the other by pathogens. Similarly, the presence of genes associated with particular functions does not guarantee that those functions are expressed or ecologically relevant under given conditions. Functional inference is also limited by database bias and often lacks empirical validation. Likewise, correlation-based network analyses can produce spurious associations driven by shared environmental covariates, sequencing depth or batch effects. These issues are routinely encountered in genomic workflows – from 16S/ITS amplicon surveys to shotgun metagenomics, genome-resolved metagenomics and gene-centric network analyses – where apparently ‘clean’ summary metrics can mask very different ecological realities. Here, we use simple, domain-relevant examples to illustrate how over-reliance on these metrics can lead to misinterpretation. Rather than rejecting these approaches, we outline when they are most informative, when they require caution and what complementary analyses can strengthen ecological inference. We propose a practical framework based on four questions: what exactly is being summarized, at what biological level, under which ecological conditions and with what form of validation? While acknowledging their value, we argue for greater critical scrutiny in their application and interpretation, and advocate for approaches that prioritize functional validation, temporal resolution and systems thinking to support more meaningful ecological insight.
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predict gene, not function