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mhryu@live.com
Today, 12:08 PM
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Gene drives offer revolutionary potential for the management of problematic plant populations, such as invasive weeds and herbicide-resistant species, by rapidly spreading desired genetic alterations. Two recent studies have provided experimental demonstrations of engineered CRISPR gene drive systems in plants (CAIN and ClvR). However, the successful application of such systems in the field will critically depend on an accurate understanding of plant-specific life-history traits, especially seed dormancy, a ubiquitous yet frequently overlooked eco-evolutionary force. In this study, we develop a comprehensive modelling framework for gene drives in plant populations that incorporates a persistent soil seed bank. We show how the presence of a seed bank can substantially slow gene drive spread but also reduce the genetic load required to achieve population elimination. Furthermore, we show that seed banks substantially increase the required introduction frequency of threshold-dependent gene drives, which could prevent establishment in some cases, yet also provide an intrinsic biosafety mechanism for confining a highly efficient drive to a target population. Our study highlights the need to incorporate seed-bank dynamics into gene drive strategies to ensure realistic predictions and successful field applications. The authors present a comprehensive plant-specific modelling framework for CRISPR gene drives: dormant seed banks can slow spread and require larger releases but can also ease weed elimination and limit unintended spread to nearby populations.
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mhryu@live.com
Today, 12:00 PM
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Mapping protein-protein interactions (PPI) at structural resolution is essential for understanding cellular machinery. While tools like AlphaFold enable proteome-wide structural predictions, the field lacks high-throughput experimental methods to verify these predictions at scale and establish empirical thresholds for confidence metrics, such as the widely used interface predicted Template Modeling (ipTM) score. We developed LUCIA (LUminescent Cell-free Interaction Assay), a rapid biochemical screening platform bypassing traditional cloning and protein expression to validate direct binary interactions within days. Applying this to herpesviruses, clinically relevant human pathogens with large proteomes, we generated an exhaustive computational interactome of 23,215 AlphaFold-predicted dimer models across three species (HSV-1, HCMV, and KSHV), accessible via our HerpesPPIs database. Using the HSV-1 interactome as a benchmark, testing 83 high-confidence predicted dimers with LUCIA yielded 23 novel, experimentally validated interactions. By calibrating AlphaFold metrics against this direct binding data, we demonstrated that an ipTM score ≥ 0.80 identifies bona fide interactions with a positive predictive value of 77%. To demonstrate the functional power of this pipeline, we characterized a previously unknown interaction between HSV-1 UL42 and UL8, linking the viral DNA polymerase and helicase-primase complexes. Structure-guided mutations at the predicted and LUCIA-verified UL42-UL8 interface strongly reduced binding in vitro and completely abolished viral replication in cell culture. Combining the scalable LUCIA platform with computational predictions enables researchers to rapidly translate atomic-level models into validated biological mechanisms without the need to solve experimental structures.
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mhryu@live.com
Today, 11:19 AM
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Transposable elements (TEs) are major drivers of genome evolution, yet their annotation and classification remain inconsistent and hard to reproduce across species. Fragmented repeats, lineage-specific innovations, and heterogeneous taxonomies across databases and tools complicate comparisons and slow progress in TE biology. To address this, we developed PanTEon, a cross-kingdom deep learning framework for reproducible TE classification that combines a harmonized database with an open, modular benchmarking platform. The PanTEon Database is an automatically curated, taxonomically broad TE repository spanning animals, plants, and fungi. The PanTEon platform standardizes training, evaluation, and inference across nine Machine Learning methods, while remaining extensible to user-defined architectures. Using this framework, we benchmark state-of-the-art Machine Learning-based TE classifiers across TE superfamilies and major eukaryotic lineages and find that performance varies markedly by kingdom and superfamily. Ensemble approaches and phylum-specific models improve predictive F1 scores, but cross-species generalization remains a major challenge. Together, PanTEon Database and PanTEon platform provide a reproducible, scalable, and extensible foundation for TE classification, enabling standardized evaluation of future AI methods and supporting community-driven annotation efforts.
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mhryu@live.com
April 4, 5:07 PM
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Gene regulation has emerged as an important determinant of phage infection outcomes. Host susceptibility and immunity are often governed by conditional gene expression, which allows reversible shifts in receptor availability and defence system activity that balance phage resistance with fitness costs. Phages likewise rely on tightly regulated gene expression, precisely timing counter-defence deployment and manipulating host transcriptional programmes as well as immune signalling pathways. These dynamics position gene regulation as a major determinant of bacteria-phage co-evolution, acting alongside the gain and loss of defence and counter-defence genes. Viewing phage–host interactions through gene regulation provides insight into variability in infection dynamics and helps explain why genomic information alone cannot accurately predict phage activity.
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mhryu@live.com
April 4, 4:58 PM
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Integrating semiconductors with microorganisms is attracting significant attention as a sustainable platform for solar-to-chemical conversion. This semibiological design combines the excellent light harvesting ability of semiconductor materials with intracellular biocatalytic pathways to enable efficient solar energy conversion into complex products with high selectivity. However, the effectiveness of this interdisciplinary biohybrid approach relies on a complex interfacial biotic–abiotic interaction, and it remains challenging to construct efficient and stable microbe–semiconductor systems for practical applications. In this review, we provide a systematic overview of the fundamental mechanisms behind microbe–semiconductor systems with an emphasis on interfacial electron transfer and highlight recent advancements in the assembly of biohybrids for solar-driven biosynthesis using nonphotosynthetic bacteria. First, we provide a comprehensive introduction of semibiological photosynthesis with an emphasis on extracellular electron transfer at the biotic–abiotic interfaces. Then, we discuss the engineering of biohybrid interfaces, the characterization of microbe–semiconductor interfacial electron transfer, and their deployment in solar-to-chemical conversion. We conclude by exploring the challenges in developing and optimizing biotic–abiotic interfaces as well as providing an outlook for potential future innovations. This review therefore presents the basic principles and provides guidance for the development of semibiological photosynthetic systems.
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mhryu@live.com
April 4, 4:32 PM
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Long-read sequencing has shown a rapid technological development during the last years. It has been established as the standard method for the sequencing of plant genomes and has also gained importance for full plasmid sequencing. As Sanger sequencing has a limited read length of about 1 kb, long read sequencing offers a great advantage, as the full plasmid can be sequenced in one read. Here, we present a cost-effective workflow to sequence full plasmids and compare the results against an expectation. The per plasmid cost of this workflow is determined by the number of plasmids investigated simultaneously, but can be lower than the price of a single Sanger sequencing reaction. We developed a workflow for automatic data processing, which allows us to complete sequencing and data analysis within a day.
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mhryu@live.com
April 4, 4:28 PM
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Polyethylene terephthalate (PET) hydrolases efficiently hydrolyze the ester bonds in PET, converting it into valuable monomers or oligomers, offering a sustainable biological solution to global PET plastic pollution. However, the large-scale development of high-performance PET hydrolases remains challenging due to limitations in traditional enzyme resource mining methods, including low throughput and lengthy cycles. Recent advances in artificial intelligence (AI) provide novel methodologies to overcome these challenges. This review systematically summarizes how AI empowers the high-throughput screening of PET hydrolases from mass biological databases, while allowing the accurate prediction of enzyme structures and functions. Furthermore, it critically analyzes AI-driven strategies for enzyme molecular engineering and highlights the emerging frontier of AI-assisted de novo enzyme design. By systematically evaluating the advantages and challenges of AI models in the research of PET hydrolases, this review provides an integrated technical framework and theoretical foundation to guide future innovation in enzyme mining and plastic biodegradation.
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mhryu@live.com
April 4, 3:20 PM
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Modern molecular analyses have revolutionized the study of microbial communities, yet DNA extraction and sequencing remain critical sources of bias. This study investigated the impact of seven different DNA extraction protocols and two 16S rRNA hypervariable regions (V1–V3 and V3–V4) on the profiling of a complex anaerobic fermentative biomass selected for medium-chain fatty acids production. Microscopic analysis established a baseline community dominated by Actinobacteria (53% ± 2%) and Firmicutes (47% ± 3%). The results demonstrate that Kit1 and Kit5 provided the highest DNA yields (up to 603 ng/μL) and the most effective recovery of these hard-to-lyse phyla, although they introduced a slight taxonomic bias toward Actinobacteria. In contrast, protocols relying on intensive chemical lysis without robust mechanical disruption (Kit4) significantly underestimated total bacterial abundance and showed the lowest purity. 16S rRNA gene sequencing revealed that the V3–V4 region provided higher alpha-diversity and a more balanced representation of the community core compared to V1–V3, which was more susceptible to extraction-related variability and overrepresented the genus Olsenella. Our multi methodological approach reveals significant biases introduced by both extraction technique and 16S rRNA gene region. This evidence highlights that protocol optimization is mandatory for achieving an accurate and comprehensive characterization of microbial ecosystems.
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mhryu@live.com
April 4, 3:05 PM
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Bacterial biofilms are complex, spatially organized microbial communities that exhibit enhanced resistance to antibiotics and contribute to chronic infections. Understanding their structure, especially during early formation stages, is critical for developing effective intervention strategies. Here, we present a high-resolution computational framework that models biofilms as undirected interaction graphs, where individual bacterial cells are vertices and predicted intercellular interactions are edges. Combining microscopy visualization and deep learning, we developed a pipeline that integrates Mask R-CNN for cell segmentation and a custom neural network (BINet) for interaction prediction. The described graph-based representation enables quantitative analysis of biofilm growth, identification of recurrent structural motifs, and classification of substrate-specific colonization patterns. We demonstrate the utility of this approach in predicting both the developmental stage and material type from image-derived graph features. This study provides the tool for revealing nonobvious patterns of biofilm organization and describes a scalable, high-information-content approach for the automated analysis of microbial communities, opening new possibilities for systems-level microbiological research.
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mhryu@live.com
April 4, 2:52 PM
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Using engineered microbial cells for chemical production from renewable resources could replace oil-based chemistry. However, it is underexplored how the chemical production by engineered microbial cells is affected by them being exposed to Darwinian selection. All proliferating cells are unavoidably subjected to Darwinian selection which favors fitness beneficial phenotypes that seldom include engineered chemical production. Here, adaptive laboratory evolution (ALE) was performed to characterize the effect of Darwinian selection on Saccharomyces cerevisiae strains expressing two different heterologous pigment producing pathways, blue-colored indigoidine and red-colored bikaverin. S. cerevisiae haploid S288C based strain had the genes for bikaverin synthesis integrated in the same locus as the genes for indigoidine synthesis in haploid and diploid S. cerevisiae CEN.PK-based strains. The ALE was performed as serial batch cultivations in rich and synthetic defined (without amino acids) media with respirative galactose as the sole carbon source for ∼200 and ∼175 generations, respectively. While indigoidine pigmentation was rapidly lost independent of growth medium or ploidy, bikaverin pigmentation was robust. The adaptive solutions detected in poor galactose utilizer S288C-based bikaverin producing lineages involved mutations in the galactose utilization pathway whereas the heterologous indigoidine pathway was recurrently mutated in the corresponding lineages. When the bikaverin producing S288C-based lineages were adaptively evolved on the favored glucose carbon source instead, clones having lost the pigmentation were detected. Thus, the robustness of the engineered traits appeared dependent on challenges in production environment and availability and fitness benefits of adaptive solutions.
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mhryu@live.com
April 3, 5:17 PM
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Aromatic amino acids—tryptophan, tyrosine, phenylalanine, and histidine—are essential for bacterial growth and are among the most energetically expensive metabolites to synthesize. Despite this cost, it has been recently shown that bacteria possess exporters for these amino acids. Here, we identify aexB (formerly yvjA) as a gene encoding a novel aromatic amino acid exporter in Bacillus subtilis. Using a transposon-based screen, we found that aexB overexpression confers resistance to the toxic tryptophan analog 5-fluorotryptophan. Additional analog screens revealed that AexB also promotes tolerance to toxic derivatives of tyrosine, phenylalanine, and histidine but not non-aromatic amino acids. LC-MS analysis showed that AexB specifically exports aromatic amino acids, and co-culture assays confirmed that overexpression of aexB can support the growth of aromatic amino acid auxotrophs. Furthermore, overexpression of aexB impaired growth when intracellular tryptophan was limiting. On the other hand, deletion of aexB exacerbated growth defects under excess tryptophan conditions, likely due to feedback inhibition of aromatic amino acid synthesis pathways. Our findings reveal that AexB is an aromatic amino acid exporter that functions as a metabolic safety valve.
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Scooped by
mhryu@live.com
April 3, 5:10 PM
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Adenosine-to-inosine (A-to-I) mRNA editing alters genetic information post-transcriptionally and can impact protein sequence and function, yet its regulation in bacteria remains unclear. Here, we profiled A-to-I editing in E. coli across nutrient-rich Luria-Bertani (LB) and minimal M9 media and different growth phases. Our analysis expanded the repertoire of TadA-dependent A-to-I edited mRNAs to 27, including 12 novel sites, and revealed that editing levels were dynamic and markedly increased at the stationary phase in LB but not in M9. Editing levels were independent of mRNA expression yet correlated with tRNA-Arg2 downregulation, and overexpressing tRNA-Arg2 reduced mRNA editing, demonstrating substrate competition for TadA, the sole bacterial tRNA adenosine deaminase. Mutants with TadA-deficient editing or reduced tRNA-Arg2 expression displayed similar LB-specific growth defects. Moreover, tRNA-Arg2 expression, tRNA-Arg2-dependent codon usage, and tRNA-Arg2 editing were all elevated in LB compared to M9. These findings establish regulatory principles for bacterial RNA editing, implicate tRNA editing in nutrient-responsive fitness, and provide a framework to explore the physiological roles of mRNA editing.
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mhryu@live.com
April 3, 4:57 PM
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Crop productivity under climate stress remains constrained by conventional agricultural approaches that underuse plant–microbiome interactions. A microbiome-centred, climate-responsive framework was proposed to enhance crop resilience and agro-sustainability by prioritizing targeted manipulation of crop-associated microbiomes, offering a scalable and adaptive pathway to buffer climate stresses and stabilize crop performance.
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Scooped by
mhryu@live.com
Today, 12:06 PM
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Metabolic engineering often treats microbial metabolism as an inventory of metabolites, reactions, and the enzymes that catalyze them. This Perspective argues that function emerges from metabolic architecture, the connectivities that bind reactions into stable regimes shaped, among other factors, by space and time. The Japanese Metabolism movement motivates an architectural view in which the same metabolites could lead to rather different phenotypes when cells reconfigure metabolic routing subjected to environmental constraints. Natural examples, including the native cyclic glycolytic wiring of Pseudomonas putida, show how redox supply and carbon flow depend on regime-level organization and space-influenced state changes. The same principles explain why microbial engineering often fails when intermediates leak, cofactors are misallocated, or timing breaks productive hand-offs. Serine-based synthetic cycles for one-carbon assimilation expose these limits as they must couple carbon entry, redox demand, and amino acid pool control around a chiral metabolite linked to translation. The emerging picture is that future designs should make routing, insulation, compartmentalization, and metabolic segregation explicit engineering targets.
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Scooped by
mhryu@live.com
Today, 11:22 AM
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During evolution, bacteria have developed the ability to interact intimately with eukaryotic hosts. These interactions span a dynamic continuum ranging from pathogenicity to mutualism, along which bacteria can rapidly evolve and shift their lifestyles. However, the molecular mechanisms that enable bacteria to adapt to new hosts and to transition between distinct interaction modes remain poorly understood. Here, using a unique combination of two independent evolution experiments, we identified and characterized parallel adaptive mutations in spoT, which encodes the bifunctional (p)ppGpp synthetase-hydrolase. These mutations promote the adaptation of the plant pathogen Ralstonia pseudosolanacearum to two distinct plant-associated environments and two distinct lifestyles, the xylem of both susceptible and tolerant host plants as a pathogen and the root nodules of a legume as a symbiont, without compromising virulence on susceptible hosts. These mutations enhance the utilization of multiple carbon and nitrogen sources, including substrates known to be abundant in xylem sap, and increase bacterial exponential growth rate in minimal medium, suggesting reduced basal (p)ppGpp levels. Assessment of a strain deficient in SpoT synthetase activity confirmed that lowering basal (p)ppGpp levels is adaptive in both plant environments. Together, our findings reveal that fine-tuning intracellular (p)ppGpp concentrations represents an efficient strategy for optimizing bacterial adaptation to complex host-associated environments.
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Scooped by
mhryu@live.com
Today, 11:17 AM
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Despite >50 years of methods development, specific antibodies are still generated at low throughput and remain in high demand across biotechnology. Most biologics and immunoprobes are monoclonal antibodies, developed using a combination of inoculating animals with a target antigen, engineered candidate libraries, and multiple rounds of selection using phage or yeast display. Here we introduce a synthetic biology scheme to eliminate the need for nearly all of these steps, by combining Surface display on E. coli and Phage display with the microvirus ΦX174, Assisting Continuous Evolution (SurPhACE). Instead of building libraries for screening, SurPhACE runs a closed evolutionary program. A typical experiment can have 1011 mutant candidates under active selection, with complete turnover of the mutant population every 30min, or >5x1012 unique mutants per day, using less than 100mL of bacterial culture media. We demonstrate SurPhACE for optimizing a nanobody to a related epitope, and develop novel nanobodies for an arbitrary target using a minimal starting library to establish a proof of concept and identify best practices for this scalable method for generating protein binders.
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Scooped by
mhryu@live.com
April 4, 5:01 PM
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Integrating semiconductors with microorganisms is attracting significant attention as a sustainable platform for solar-to-chemical conversion. This semibiological design combines the excellent light harvesting ability of semiconductor materials with intracellular biocatalytic pathways to enable efficient solar energy conversion into complex products with high selectivity. However, the effectiveness of this interdisciplinary biohybrid approach relies on a complex interfacial biotic–abiotic interaction, and it remains challenging to construct efficient and stable microbe–semiconductor systems for practical applications. In this review, we provide a systematic overview of the fundamental mechanisms behind microbe–semiconductor systems with an emphasis on interfacial electron transfer and highlight recent advancements in the assembly of biohybrids for solar-driven biosynthesis using nonphotosynthetic bacteria. First, we provide a comprehensive introduction of semibiological photosynthesis with an emphasis on extracellular electron transfer at the biotic–abiotic interfaces. Then, we discuss the engineering of biohybrid interfaces, the characterization of microbe–semiconductor interfacial electron transfer, and their deployment in solar-to-chemical conversion. We conclude by exploring the challenges in developing and optimizing biotic–abiotic interfaces as well as providing an outlook for potential future innovations. This review therefore presents the basic principles and provides guidance for the development of semibiological photosynthetic systems.
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Scooped by
mhryu@live.com
April 4, 4:36 PM
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Sliding-window phylogenetic analyses of multiple sequence alignments (MSAs) generate sequences of phylogenetic trees that can reveal recombination and other sources of phylogenetic conflict, yet comparing trees across genomic windows remains challenging. Phylo-Movies is a browser-based tool, also available as a standalone desktop application, that decomposes topological differences between consecutive phylogenetic trees into interpretable subtree migrations and animates these transformations. We demonstrate its utility in two contexts: identifying recombination breakpoints in norovirus genomes, where lineages shift from polymerase-based to capsid-based clustering at the ORF1/ORF2 junction, and detecting rogue taxa that change position across bootstrap replicates. Phylo-Movies complements summary statistics such as Robinson-Foulds distances by showing which lineages move, where they move from, and which new groupings they form. Phylo-Movies is freely available at https://github.com/enesberksakalli/phylo-movies, with a norovirus demonstration video at https://vimeo.com/1162400544, the first rogue taxon example at https://vimeo.com/1162561152, and the second example at https://vimeo.com/1162563101.
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mhryu@live.com
April 4, 4:30 PM
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Semi-permeable capsules (SPCs) create enclosed porous microenvironments, diffusible to only small proteins and macromolecules. This presents a powerful tool for single cell observation, isolation, and sequencing. However, their range of use for sustaining viable microbial eukaryotes is largely unexplored. Single-cell eukaryotes are often understudied, with a wealth of unknown lifecycles, culturing methods and inter-microbial interactions, which are difficult to visualize. Here, we show that eukaryotes from eight different supergroups can be captured and propagated in SPCs. Encapsulation allowed observations of cell stages, motility and growth in a traceable and parallelized manner.
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mhryu@live.com
April 4, 3:26 PM
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Extensive accumulation of polyethylene terephthalate (PET) plastic waste causes serious pollution to the global environment, and developing superior PET hydrolases is vital for the enzymatic degradation and biorecycling of PET. Here, we propose a “locking” strategy for the rational redesign of FAST-PETase, one of the best-performing PETase variants reported so far, to further improve its performance. The best variant, FAST-PETaseDC (A171C/S193C), exhibits 1.9-fold enhanced degradation efficiency compared with FAST-PETase at 50 °C, and a 4.1 °C increase in melting temperature (Tm). FAST-PETaseDC can almost completely depolymerize untreated post-consumer PET film within 3 d at 50 °C with periodic enzyme replenishment, two-fold faster than FAST-PETase. Molecular dynamics simulations reveal that the mutation locks Helix 5 and Loop 10 through a stable disulfide bond, and reduces the flexibility of the mutation sites and their connected regions. The structural changes consequently promote the substrate binding to the enzyme, facilitate the interaction within the catalytic triad, and rigidify the overall structure of the enzyme, leading to the improved degradation efficiency and thermostability. The study underscores the “locking” strategy as an effective way to enzyme redesign, and the engineered FAST-PETase variant is a promising hydrolase for the treatment and recycling of low-to-medium crystallinity PET plastic waste.
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mhryu@live.com
April 4, 3:13 PM
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The Ralstonia solanacearum species complex (RSSC) ranks among the most destructive plant pathogens worldwide, due to its broad host range, extensive geographic distribution and remarkable environmental adaptability. Its persistence in soil and colonization of plant vascular tissues severely limits the effectiveness of conventional chemical control, posing significant challenges for disease management. This review highlights recent advances in understanding the environmental adaptation mechanisms of RSSC. Key topics include the dynamic evolution of pathogenicity, niche-specific survival strategies and virulence regulation mediated by quorum sensing, and complex interactions with surrounding microbial communities that shape its behavior and fitness. We further provide a comprehensive assessment of current control strategies from an ecological perspective, encompassing physical, chemical, genetic, agronomic and microbial approaches, with critical evaluation of their mechanisms, potential and limitations. Meanwhile, we discuss the major challenges in bacterial wilt management and outline future directions, with an emphasis on multi-omics-informed precision breeding, microbiome engineering and intelligent integrated disease management (IDM). These emerging strategies hold promise for the sustainable and effective long-term control of bacterial wilt disease caused by RSSC.
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mhryu@live.com
April 4, 2:57 PM
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Culture-independent antibiotic resistance gene analyses enable broad explorations of microbial communities but often fail to link such genes to bacterial hosts and genetic contexts. This makes assessing prevalence of resistant pathogens and likelihood of further transmission or resistance evolution uncertain. There is an increasing interest in studying antibiotic resistance genes in microbial communities, however, there is no unified way to identify them in metagenomics datasets or to interpret the risks associated with them. In this Comment, the authors discuss current technical challenges and how to mitigate them.
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mhryu@live.com
April 3, 5:21 PM
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Soil microbial ecosystems are complex and difficult to replicate in laboratory settings. It is often unclear which pressures most strongly shape microbial survival and evolution in situ, and new methods are needed to intersect the manipulative power of the lab with the reality of field environments. One recent innovation was the “isolation chip,” in which many new microbial isolates could be cultured on agar within a buried diffusion chamber while exposed to environmental inputs through fine-pored membranes. Here, we created a modified version of this device containing biologically-cleared soil instead of agar, to trial an in situ reverse ecology experimental evolution approach. Using these “adaptation chips (aChips)” we exposed populations of two different soil-dwelling bacteria (Priestia megaterium and Streptomyces lydicus) to several farm soils in the Northeast US for up to two years, documenting mutations arising in the evolving populations. While evolution was remarkably slow in the field, P. megaterium populations accumulated many mutations pre-burial during aChip construction which seemingly reflected zinc limitation in the aChip carrier soil. Although post-burial mutations were observed in both P. megaterium and S. lydicus populations, they remained at low frequency and did not display parallelism between aChips buried at the same sites, indicating a lack of strong positive selection and/or limited generations of population growth within the aChip. We suggest several improvements to aChip design to facilitate greater evolutionary progression, including a larger within-aChip soil volume and fewer cells initially secured inside the aChip.
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mhryu@live.com
April 3, 5:14 PM
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Magnetotactic bacteria (MTB) are a group of gram-negative species that produce a lipid-bounded organelle, the magnetosome, in which a magnetic crystal is biomineralized. MTB use magnetosomes to align with the geomagnetic field for improved navigation of their environment. To optimize this alignment, these species linearly organize their magnetosomes using a handful of factors, including the bacterial actin-like protein MamK. Despite these shared features, there is a broad diversity of species-specific linear magnetosome chain arrangements within MTB, but the molecular mechanisms behind these phenotypic variations are unclear. Recently, genetic analyses showed that two proteins—McaA and McaB—interface with the chain organization machinery of Magnetospirillum magneticum AMB-1 to arrange magnetite crystals in a series of subchains rather than the single cohesive chains found in closely related MTB. Here, we use in vivo co-immunoprecipitation in AMB-1 to demonstrate protein-protein interactions between McaA, McaB, and MamK. Experiments with McaA truncation mutants and conditional control of McaB localization determined that McaA-McaB interactions are dependent on amino acids 530–665 of McaA and McaB localization to the magnetosome chain. We further show that disrupting the McaA-McaB interaction alters the spatial dynamics of MamK in vivo. We present a model in which protein-protein interactions between McaA, McaB, and MamK drive changes in MamK behavior to establish AMB-1’s magnetosome chain organization.
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Scooped by
mhryu@live.com
April 3, 5:06 PM
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The ongoing census of microbial life is hampered by disparate sampling across Earth’s habitats, challenges in isolating uncultivated organisms, limited resolution in taxonomic marker gene amplicons and incomplete recovery of metagenome-assembled genomes. Here we quantify discoverable Bacterial and Archaeal diversity in a comprehensive, curated cross-habitat dataset of 92,187 publicly available metagenomes. Clustering 502 million sequences of 130 marker genes, we predict ~705,000 Bacterial and ~27,000 Archaeal species-level clades, the vast majority of which were hidden among unbinned contigs. We estimate that ten and 145 previously undescribed Archaeal and Bacterial phyla, respectively, are discoverable in this dataset. We identify soils and aquatic environments as hotspots of discoverable lineages, but predict that undescribed taxa remain abundant across all habitats. Finally, we show that prokaryotic diversity appears to arise within common evolutionary patterns, as clade size distributions follow power laws, consistently across the Tree of Life. Re-analysis of over 92,000 metagenomes reveals hundreds of thousands of previously undescribed Bacterial and Archaeal clades hidden in plain sight.
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