Coronaviruses cause a wide range of diseases, ranging from the common cold to severe illnesses such as COVID-19. Although vaccines and therapeutics against COVID-19 have been developed, recent reports have documented the emergence of viral variants with reduced susceptibility to these interventions, suggesting that coronaviruses may continue to circulate persistently, similar to influenza viruses. Cirsium japonicum var. spinossimum Kitam. (hereafter referred to as C. japonicum) has traditionally been used to treat various medical conditions, including inflammatory diseases; however, its antiviral properties remain poorly understood. In this study, we demonstrated that C. japonicum extract inhibited human coronavirus replication and alleviated virus-induced cytotoxicity. Analysis of the chemical constituents of the extract identified cirsimaritin, a major flavonoid present in C. japonicum, as an active compound with antiviral activity against human coronavirus. The antiviral effects of both C. japonicum extract and cirsimaritin were further confirmed using scanning electron microscopy and a three-dimensional spheroid model. Finally, we demonstrated that C. japonicum extract and cirsimaritin inhibited coronavirus papain-like protease activity. These findings suggest that C. japonicum extract and cirsimaritin have potential as therapeutic candidates for coronavirus-associated diseases.

Antimicrobial resistance (AMR) in marine environments remains difficult to assess under standard antimicrobial susceptibility testing conditions, which may not adequately reflect the physiological requirements of marine-derived bacteria. In this study, we applied NaCl-supplemented susceptibility testing conditions to bacterial isolates recovered from coastal environments and marine organism guts to evaluate their practical applicability and limitations. A total of 927 isolates were obtained from lagoon, seawater, soil, and gut samples of abalone, crab, eel, halibut, and salmon. Of these, 365 isolates grew on standard Mueller-Hinton (MH) medium, whereas 562 isolates were not evaluable under standard MH conditions. Taxonomic analysis showed that the isolate collection was dominated by Proteobacteria and Firmicutes, with Vibrio as the most abundant genus. Disk diffusion assays of the 365 MH-grown isolates revealed differences in screening-level reduced susceptibility profiles among sample groups, and putative multidrug resistance was frequently observed in Vibrio isolates from abalone and seawater. For isolates not evaluable under standard MH conditions, minimum inhibitory concentration (MIC) analysis was performed using 2% NaCl-supplemented MH broth. Under these conditions, 115 isolates showed stable growth and distinct antibiotic-dependent MIC profiles. Chloramphenicol and tetracycline inhibited most isolates at relatively low concentrations, whereas reduced susceptibility to penicillin was relatively high in isolates from seawater, abalone, and eel. Overall, these findings suggest that standard MH conditions alone may be insufficient for evaluating antibiotic responses in marine- and brackish-origin bacteria, and that 2% NaCl-supplemented MH broth can serve as a practical supplementary condition for selected marine-derived isolates.

Fecal microbiota transplantation (FMT) has been successfully applied on clinical aspects, but its clinical outcomes remain unpredictable due to inconsistent donor screening protocols across hospitals, institutions, and countries. Hence, a retrospective analysis of metagenomic data from published studies on FMT donors via a unified bioinformatics workflow might contribute to the understanding of the safety considerations for donor screening and the fecal microbial profiles of qualified donors. In this study, we reanalyzed metagenomic data of 475 screened donor fecal samples from 24 studies spanning China, the USA, Canada, New Zealand, and the Netherlands. The genomic safety risks were evaluated by profiling antibiotic resistance genes (ARGs) and virulence factors (VFs), the results of which showed that no major toxin-associated virulence genes, such as Shiga toxin, Shiga-like toxin, or botulinum neurotoxin (BoNTs) genes harbored in the detected Escherichia coli, Clostridium butyricum, and Streptococcus pneumoniae, but several high-risk ARGs remained insufficiently addressed. The distribution of ARG-harboring bacteria in eligible FMT donors was country-specific. The alpha-diversity and microbial community structure were comparable between donor fecal samples from China and the USA. Interestingly, the core microbiome in fecal samples from Canada, the Netherlands, and New Zealand formed a single guild, while that from China and the USA formed two guilds, with predominantly positive intra-guild and negative inter-guild correlations, indicating that the co-abundance patterns of the core microbiome were conserved among certain countries. Furthermore, an exploratory retrospective classifier was developed based on core microbiome profiles to distinguish eligible FMT donors from general healthy individuals. These results provide evidence for integrating metagenomic sequencing into future FMT donor screening strategies.

The convergence of synthetic biology and artificial intelligence is widening the gap between technological advancement and existing regulatory frameworks - a phenomenon known as regulatory lag. As global competition intensifies to capture a synthetic biology market projected to reach approximately $70 billion by 2030, nations are responding to this challenge through markedly different approaches. This study applies a comparative legal methodology, drawing on co-evolutionary theory and the Law 1.0/2.0/3.0 framework, to analyze the regulatory responses of the United States, United Kingdom, Japan, and South Korea. The analysis reveals that national differences stem less from institutional design choices than from the triggers that initiate regulatory change, yielding four distinct co-evolutionary pathways. In the United States, a shift in the judicial environment prompted regulatory adaptation; in the United Kingdom, a political transition created the conditions for legislative reform; and in Japan, administrative reinterpretation of existing rules enabled regulatory adjustment. South Korea represents a fundamentally different case. By enacting the world's first standalone synthetic biology legislation prior to full technological maturation, Korea has pursued a top-down co-evolutionary model in which institutional design precedes and shapes the trajectory of technological development. Three conclusions emerge from this analysis: there is no single optimal co-evolutionary pathway; institutional flexibility determines the sustainability of co-evolution; and co-evolution can itself be an object of proactive design. For Korea's preemptive model to prove effective, it requires a sufficient scientific foundation, institutional flexibility, and coherence with existing regulatory frameworks - conditions that offer a reference point for other nations confronting similar governance challenges.

Human adenovirus type 55 (HAdV-55) is an emerging respiratory pathogen associated with severe pneumonia, for which no licensed vaccines are currently available. The lack of physiologically relevant small-animal models has limited preclinical evaluation of vaccine candidates. In this study, we generated a transgenic mouse model co-expressing human CD46 and desmoglein-2 (DSG-2), key entry receptors for HAdV-55, and evaluated its utility for vaccine efficacy testing. A bicistronic expression system enabling simultaneous expression of CD46 and DSG-2 was constructed and functionally validated in vitro, demonstrating enhanced susceptibility to HAdV-55 infection. The transgenic mice exhibited dose-dependent weight loss, robust viral replication in lung tissues, and characteristic histopathological changes following intranasal challenge, recapitulating key features of human adenoviral pneumonia. Using this model, we assessed the immunogenicity and protective efficacy of an inactivated HAdV-55 (iHAdV-55) vaccine formulated with alum. Vaccination induced strong HAdV-55-specific IgG and neutralizing antibody responses, which increased over time following prime-boost immunization. Upon viral challenge, vaccinated mice showed significantly reduced weight loss and accelerated recovery compared to controls. Viral load analysis demonstrated effective control of viral replication and clearance in vaccinated animals. Collectively, these findings establish the CD46/DSG-2 transgenic mouse as a physiologically relevant and translationally valuable model for HAdV-55 infection and demonstrate that iHAdV-55 vaccination confers robust humoral immunity and protective efficacy. This platform provides a critical tool for the development and preclinical evaluation of adenovirus-targeted vaccines and therapeutics.

Microbiome studies require multiple analytical steps after initial sequence processing. These steps commonly include data harmonization, preprocessing, taxonomic profiling, diversity analysis, differential abundance testing, predictive modeling, network inference, and preparation of publication-ready outputs. Although robust packages are available for many of these tasks, routine use often depends on command-line workflows, repeated data reformatting, and method-specific scripting. These requirements can limit accessibility for experimental researchers and complicate consistent analysis across interdisciplinary teams. We developed SimpleMicrobiome, a web-based R Shiny platform that integrates established microbiome analysis methods into a single interactive downstream workflow. The application accepts standard abundance, taxonomy, and metadata tables, supports interactive preprocessing and sample filtering, and provides modules for taxa profile visualization, alpha and beta diversity analysis, ANCOM-BC2 and MaAsLin2 differential abundance testing, Random Forest modeling with SHAP-based interpretation, microbial association network inference using SparCC and SPIEC-EASI through NetCoMi, correlation heatmaps, and dbRDA/CAP-style association biplots. The platform is implemented as a modular Shiny application so that preprocessing choices are propagated across downstream analyses, results can be exported as figures and tables, and the same application can be run through the public server, source-code installation, or a Docker image. SimpleMicrobiome consolidates major downstream microbiome analysis tasks in an accessible browser-based environment while retaining links to established analytical frameworks. The platform may reduce technical barriers for non-programming users, improve consistency across exploratory and reporting-oriented analyses, and support collaborative microbiome research. The public application is available at https://simplemicrobiome.mglab.org, the source code is available at https://github.com/yjcho2252/SimpleMicrobiome, and a Docker image for local deployment is available at https://hub.docker.com/r/mglab2252/simplemicrobiome.

Mycobacterium tuberculosis (Mtb) encounters diverse and fluctuating microenvironments during infection, including changes in nutrient availability and pH. While adaptation to individual host-associated conditions has been extensively studied, the impact of repeated environmental fluctuations on bacterial physiology and antibiotic survival remains unclear. In this study, we investigated how long-term adaptation to stable or fluctuating environments influences Mtb growth and drug responses. Mtb populations were serially passaged for six consecutive passages under combinations of different carbon sources and pH conditions that were either maintained consistently or altered across passages. Environmental history significantly affected bacterial growth dynamics and antibiotic survival. Notably, under identical final condition with cholesterol as a sole carbon source, populations adapted to a stable environment exhibited higher survival following bedaquiline and rifampicin treatment than populations exposed to fluctuating environments. These findings suggest that stable environments promote the optimization of growth and stress-response programs, whereas environmental fluctuations limit such optimization despite potentially increasing phenotypic heterogeneity and a possibility of survival. Together, our results identify environmental history as an important determinant of antibiotic survival in Mtb and highlight the need to consider dynamic host-like environments when investigating tuberculosis physiology and drug responses.

Plastic waste in marine environments provides novel habitats for diverse organisms, forming distinct microbial ecosystems known as the 'plastisphere'. Although bacteria of the plastisphere have been widely studied, the role of fungi in plastisphere formation and plastic degradation remains largely unexplored. Thus, we investigated temporal changes in culturable fungal community composition on three common plastic types-high-density polyethylene, low-density polyethylene, and polypropylene-across the early (seven days) and mature (30 days) plastisphere developmental stages through a marine mesocosm experiment. In total, 436 fungal strains were isolated and identified as belonging to 179 taxa, with Penicillium, Cladosporium, Trichoderma, Aspergillus, and Fusarium as the dominant genera. Temporal shifts in the species richness of the dominant genera were observed: Cladosporium showed higher species richness at the early stage, whereas that of Trichoderma increased at the mature stage. Plastic degradation assays revealed that 54.6% of the strains exhibited measurable degradation capacity, with patterns varying by plastic type rather than fungal developmental stage. Scanning electron microscope observations revealed surface damage patterns including cracks, pitting, and erosion on the plastic surfaces. These findings provide novel insights into the composition and functional heterogeneity of culturable fungal communities in the marine plastisphere and suggest that plastisphere fungi play diverse ecological roles beyond direct plastic degradation.

While shotgun metagenomics is often used to profile antibiotic resistome in gut microbial communities, few studies have investigated if the choice of sequencing platform and assembly strategy affect what mobile genetic elements and antimicrobial resistance genes are recovered. In this study, we compared three platforms (Illumina, Oxford Nanopore, and PacBio HiFi) and seven assembly strategies on gut metagenomes from cattle, pig, and human as case studies. Long-read assemblies recovered 5- to 7-fold more plasmid sequence than Illumina in cattle and pig (mean 17.0 Mb vs. 3.1 Mb), while Illumina performed comparably in the less diverse human gut where high per-species coverage enabled effective short-read plasmid assembly. Long reads also detected more resistance genes on plasmid contigs. Hybrid assembly results depended on the algorithm: scaffolding-based OPERA-MS preserved long-read contiguity and recovered more plasmid-borne resistance genes, while the short-read-centric metaSPAdes hybrid mode produced fragmented assemblies. After collapsing haplotype redundancy, PacBio HiFi identified 2 and 49 unique multi-drug resistance plasmid lineages in cattle and pig, respectively. On the other hand, only 2 and 4 were identified from Illumina. Long reads also placed far more ARGs in a putative mobilization context (50-73%) compared to 14-21% for short reads. Platform and assembly strategy are thus key variables in mobilome and resistome characterization and should be accounted for in antimicrobial resistance surveillance.

Hypervirulent Klebsiella pneumoniae (hvKp) is an emerging pathogen that causes severe community-acquired infections; however, the immune mechanisms controlling intracellular hvKp have yet to be clearly defined. In this study, we investigated the therapeutic potential of berberine against hvKp infection and elucidated the underlying molecular mechanisms using macrophage cell models and in vivo zebrafish models. Berberine significantly reduced intracellular hvKp survival in macrophages and improved survival in hvKp-infected zebrafish. Berberine markedly attenuated proinflammatory cytokine production and inhibited the c-Jun N-terminal kinase (JNK) and extracellular signal-regulated kinase (ERK) signaling pathways. Notably, we found that hvKp exploited host lipid droplets (LD) biosynthesis to support its intracellular survival, and berberine effectively suppressed LD accumulation. Mechanistically, berberine promoted the nuclear translocation of transcription factor EB (TFEB), thereby enhancing lipolysis. Although berberine upregulated autophagy-related gene expression during hvKp infection, it did not induce lipophagy, the selective autophagic degradation of LD. Collectively, these findings indicate that berberine has potential as a therapeutic agent against hvKp infection by modulating host lipid metabolism to restrict bacterial intracellular survival.

Antimicrobial resistance poses a major global health challenge, and infections caused by multidrug-resistant Gram-negative bacteria are associated with substantial morbidity and mortality. In contrast to many Gram-positive pathogens, Gram-negative bacteria combine intrinsic barriers with acquired determinants, including enzymatic drug inactivation, reduced outer membrane permeability, active efflux, and target modifications, which collectively compromise the efficacy of multiple antibiotic classes. Previous reviews have largely catalogued resistant pathogens or antimicrobial agents. This review provides a mechanism-focused overview of antimicrobial resistance in clinically important Gram-negative bacteria and explains how dominant resistance determinants translate into clinically relevant failure modes, such as delayed effective therapy, limited treatment options, and increased reliance on toxic last-line agents. Current and emerging therapeutic strategies are discussed through a mechanism-based lens, emphasizing newer β-lactam/β-lactamase inhibitor combinations and nontraditional approaches, including phages, antivirulence, and microbiome-based interventions. This review highlights the conceptual links between resistance mechanisms, clinical impact, and rational therapeutic choices and identifies priorities for future research aimed at mitigating antimicrobial-resistant Gram-negative infections.

Pathogenic Escherichia coli is a major cause of foodborne illness worldwide and includes strains capable of causing severe disease. To establish a genome-informed framework for foodborne outbreak surveillance, we analyzed 1,029 E. coli isolates from clinical, food, livestock, and environmental sources using whole-genome sequencing. Pathogenic isolates obtained from human clinical cases or linked to documented outbreaks were classified as epidemiologically defined high-risk (EpiHR), whereas the remaining pathogenic isolates were classified as non-EpiHR. Virulence-associated genomic features were extracted using a bioinformatics pipeline, and four machine learning (ML) algorithms, including gradient boosting machine, random forest (RF), and support vector machines with linear and radial basis function kernels, were evaluated. Among them, the RF model showed the best performance, achieving an area under the curve (AUC) of 0.98 and accuracy of 0.93 in 10-fold cross-validation. Additional leave-one-group-out validation showed retained discrimination across held-out sequence types and serotypes, although performance was reduced when isolates were grouped by isolation source. Evaluation using an independent test dataset of 1,908 publicly available pathogenic E. coli genomes showed an AUC of 0.97 and a sensitivity of 0.98. Feature importance analysis using Shapley additive explanations identified influential predictive features, including traT, etpB, and enterotoxin-associated genes. A reduced 10-feature model achieved an AUC of 0.79 in the independent test dataset, supporting its exploratory use for future simplified screening approaches. These results indicate that genome-based ML provides a sensitive framework for surveillance-oriented prioritization of EpiHR pathogenic E. coli isolates, with model predictions interpreted together with epidemiological information.

Fungal extracellular vesicles (EVs) have emerged as critical mediators of fungal physiology, virulence, and host-pathogen interactions. Since their first description in Cryptococcus neoformans, EVs have been identified in several fungal species and shown to transport a broad repertoire of bioactive cargo. Increasing evidence indicates that fungal EVs participate in multiple biological processes, including cell wall remodeling, stress adaptation, biofilm formation, antifungal resistance, and modulation of host immune responses. Recent advances in cryo-electron microscopy, multi-omics approaches, and functional genetics have substantially expanded our understanding of the molecular mechanisms governing EV biogenesis, cargo selection, and extracellular trafficking. These studies have further revealed that EV cargo loading is a highly regulated process linked to intracellular proteostasis, glycosylation, lipid homeostasis, and environmental adaptation. In parallel, the intrinsic immunogenicity and structural stability of fungal EVs have highlighted their translational potential as diagnostic biomarkers, vaccine platforms, therapeutic targets, and nanoscale delivery systems. Given the increasing global burden of invasive fungal infections, this review focuses on EVs derived from clinically relevant human fungal pathogens. We summarize recent advances in EV biogenesis, cargo regulation, their roles in pathogenesis, highlight emerging translational applications, and discuss key unresolved questions and future research directions in the field.

The global rise of multidrug-resistant bacteria poses a critical threat to public health, and bacteriophage-derived endolysins have emerged as promising alternatives to conventional antibiotics. The engineered endolysin LNT113, derived from the Escherichia coli phage PBEC131 endolysin EC340, exhibits potent lytic activity against Gram-negative bacteria. This study investigated the transcriptomic responses of E. coli to sublethal LNT113 stress and identified genetic determinants required for bacterial adaptation to endolysin-induced stress. Transcriptomic analysis identified 552 differentially expressed genes (DEGs) following sublethal LNT113 exposure. Thirteen DEGs associated with stress response and envelope maintenance were individually deleted to generate thirteen mutant strains and to functionally evaluate their roles in bacterial stress tolerance. Among these, the ΔfabB and Δ(prmB-yfcL) mutants exhibited significantly reduced survival under sublethal LNT113 exposure, indicating increased susceptibility to the endolysin. Regarding the prmB-yfcL operon, individual genes were deleted to determine the gene critical for bacterial tolerance. Deletion of aroC and mepA rendered E. coli more susceptible to LNT113. Furthermore, 1-N-phenylnaphthylamine uptake assays demonstrated increased membrane permeability in the ΔfabB, ΔaroC, and ΔmepA mutants. Complementation with pWSK129::fabB, pWSK129::aroC, and pWSK129::mepA restored membrane integrity in the respective mutant strains. These findings suggest that fabB-mediated unsaturated fatty acid biosynthesis and mepA-dependent peptidoglycan remodeling are critical for maintaining envelope integrity under endolysin stress, whereas aroC may indirectly support bacterial tolerance to LNT113 via metabolic adaptation. This study provides insights into bacterial responses to LNT113 and offers a foundation for optimizing endolysin-based therapeutic strategies.