Streptomyces are a crucial source of bioactive secondary metabolites with significant clinical applications. Recent studies of bacterial and metagenome-assembled genomes have revealed that Streptomyces harbors a substantial number of uncharacterized silent secondary metabolite biosynthetic gene clusters (BGCs). These BGCs represent a vast diversity of biosynthetic pathways for natural product synthesis, indicating significant untapped potential for discovering new metabolites. To exploit this potential, genome mining using comprehensive strategies that leverage extensive genomic databases can be conducted. By linking BGCs to their encoded products and integrating genetic manipulation techniques, researchers can greatly enhance the identification of new secondary metabolites with therapeutic relevance. In this context, we present a step-by-step guide for using the antiSMASH pipeline to identify secondary metabolite-coding BGCs within the complete genome of a novel Streptomyces strain. This protocol also outlines gene manipulation methods that can be applied to Streptomyces to activate cryptic clusters of interest and validate the functions of biosynthetic genes. By following these guidelines, researchers can pave the way for discovering and characterizing valuable natural products.

16S rRNA gene amplicon sequencing is the most widely used approach for characterizing microbial communities, yet analyzing such data requires navigating a fragmented landscape of bioinformatics tools with distinct installation requirements, parameter settings, and data formats. Here we present 16S-Pipeline, an open-source, web-based platform that provides a complete workflow from raw FASTQ files to publication-ready statistical analyses. 16S-Pipeline automatically detects sequencing type (paired-end, single-end, long-read), variable region, and sequencing platform (Illumina, PacBio HiFi, Nanopore), then performs quality filtering, primer trimming, amplicon sequence variant (ASV) inference via DADA2, taxonomy assignment against SILVA v138.1, phylogenetic tree construction, and optional functional prediction via PICRUSt2. Downstream analyses include alpha and beta diversity, taxonomic composition visualization, differential abundance testing using five complementary methods (ALDEx2, DESeq2, ANCOM-BC2, LinDA, MaAsLin2) with consensus reporting, and KEGG pathway mapping. Built-in NCBI SRA integration enables downloading public datasets for re-analysis and generates submission metadata spreadsheets for data deposition. The interactive web interface built on FastAPI and Plotly Dash enables researchers to perform complex microbiome analyses without command-line expertise. 16S-Pipeline is freely available at https://github.com/tatsu1207/16S-Pipeline under the MIT License.

Skin aging increases transepidermal water loss (TEWL), reduces elasticity, and perturbs the skin microbiome. Adipose tissue-derived stem cell exosomes (ASCE) show regenerative potential; however, their clinical effects on skin physiology and microbiome remain unclear. We conducted a split-face, randomized controlled trial in 16 adults aged ≥ 40 years with visible facial aging. One facial side received ultrasound-assisted transdermal delivery of a human ASCE-containing solution (HACS), whereas the other side received normal saline, at two-week intervals for three sessions. Biophysical outcomes (TEWL, stratum corneum hydration, and elasticity parameters R2/R5/R7) were assessed at baseline and week 2, 4, and 8. Wrinkles, pigmentation, and sebum levels were quantified using Mark-Vu imaging, and the Physician’s Global Aesthetic Improvement Scale (PGAIS) and patient satisfaction assessment scores were recorded. Skin swabs from ten participants were subjected to 16S rRNA and ITS1 sequencing. HACS treatment significantly reduced TEWL (p = 0.006 at week 2; p = 0.009 at week 8) and increased hydration (p < 0.001 at all time points) with a significant increase in elasticity (R2/R5/R7 values, p < 0.001). Both the PGAIS and patient satisfaction scores were significantly higher on the experimental side. Bacterial α/β-diversity remained largely unchanged, and no bacterial taxa remained significantly associated with skin parameters after FDR correction. In contrast, several fungal taxa showed significant positive associations with skin parameters after FDR correction, detectable only on the HACS-treated side. No significant adverse events were observed. HACS improved barrier function, elasticity, and aesthetic outcomes, whereas microbiome analyses suggested a modest fungal response associated with treatment-related skin changes in aging skin.

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.

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.

Obesity is increasingly recognized as a systemic pro-inflammatory condition that influences not only metabolic and cardiovascular health but also the development and exacerbation of cutaneous inflammatory diseases. This review examines the interplay between obesity, microbial dysbiosis, and two archetypal inflammatory skin disorders—hidradenitis suppurativa (HS) and psoriasis. We highlight how obesity-induced changes in immune signaling, gut permeability, and microbiota composition—both in the gut and the skin—contribute to cutaneous inflammation. Special emphasis is placed on shared pathways such as the Th17/IL-23 and IL-22 signaling axes, adipokine imbalance, and microbial metabolites like short-chain fatty acids and lipopolysaccharides. The review critically evaluates the current literature, distinguishing preclinical insights from clinical evidence, and underscores the potential of microbiota-targeted therapies and metabolic interventions as adjunctive treatment strategies. By integrating metabolic, immunologic, and microbiome data, we synthesize emerging evidence to better understand the gut–skin–obesity interplay and guide future therapeutic innovations.

Small regulatory RNAs (sRNAs) are short noncoding RNAs that can fine-control the expression of target genes in trans at the post-transcriptional level in prokaryotes. Since there is a big challenge in constructing gene-knockout libraries, synthetic sRNAs have attracted considerable interest in synthetic biology and metabolic engineering, as they enable targeted gene knockdown without requiring chromosomal modifications. However, the development of high-efficiency synthetic sRNAs remains a demanding task that requires careful consideration of multiple design factors. Here, we provide a detailed protocol for the design and construction of synthetic sRNAs, detailing key design principles and critical optimization factors, including scaffold selection, target mRNA binding affinity, target mRNA secondary structure, and Hfq expression levels. This strategy can be broadly applied across E. coli and other bacterial hosts to modulate gene expression, thereby supporting versatile applications in synthetic biology and metabolic engineering.

Triterpenoids are natural products widely found in the plant kingdom and have various pharmacological effects such as anti-inflammatory, antioxidant and anti-tumour. However, the content of triterpenoids in medicinal plants is low, and it is difficult to purify and isolate them due to their complex structure. The efficient production of some triterpenoids in chassis organisms has been achieved by constructing a heterologous triterpenoid synthesis pathway in engineered strains such as yeast, modifying the key enzymes in the pathway, and adjusting the metabolism of yeast. Modification of key enzymes in the synthetic pathway is currently an effective strategy to enhance the heterologous synthesis of triterpenoids. This paper reviews the current research progress on the modification of key enzymes downstream in the synthetic pathway and the design of key enzymes around them to enhance triterpenoid production in five main areas: 1) increasing the supply of triterpenoid precursors; 2) inhibition of the natural sterol pathway; 3) fusion expression of related enzymes; 4) compartmentalisation of the metabolic pathway; and 5) tapping and enhancing the triterpenoid efflux pump. Finally, recent advances and applications of artificial intelligence (AI) in enzyme engineering and pathway design for triterpenoid biosynthesis are highlighted. Challenges and perspectives for further increasing the yield of triterpenoid synthesis in Saccharomyces cerevisiae are presented.

Antimicrobial resistance (AMR) poses an ongoing threat to global health, with the number of deaths directly attributable to AMR projected to rise to 8 million. One of the main reasons for the current crisis is the depletion of antibiotic candidates in clinical pipelines. To address this, more preclinical candidates must be advanced into development. However, the scientific challenges and limited economic incentives associated with antibiotic research have further aggravated the situation. Antibiotic hybrids, which combine two antibiotics with different modes of action, have emerged as a promising strategy to overcome AMR and are already being developed for clinical use. This approach takes advantage of the strong selective pressure exerted when two bactericidal agents act simultaneously. Importantly, because hybrids are administered as a single chemical entity, they may offer advantages over conventional combination therapies, such as simplified pharmacokinetics and dosing. Furthermore, since clinically validated antibiotics are used as the building blocks of hybrids, this strategy provides an efficient platform for generating new lead compounds. Recently, the concept of antibiotic hybrids has expanded beyond antibiotic–antibiotic conjugates to include the attachment of functional molecules designed to mitigate the disadvantages of the parent antibiotics. In this review, we summarize the definition of antibiotic hybrids, highlight representative compounds that have entered clinical evaluation, and discuss recent advances in their development.

Dual specificity phosphatases (DUSPs) are a subfamily of protein tyrosine phosphatases that regulate diverse cellular processes through dephosphorylation of phosphorylated substrates. DUSPs are commonly found in eukaryotes, bacteria, archaea, and viruses. However, structural and biochemical characterization of bacterial DUSP remains limited, as only one bacterial DUSP has been identified thus far. In this study, we investigated a novel putative bacterial DUSP from Candidatus Chlorohelix allophototropha, referred to as CCaDUSP. The crystal structure of CCaDUSP showed the presence of a well-conserved catalytic motif with a characteristic phosphate-binding loop. Biochemical analyses further confirmed that CCaDUSP exhibits phosphatase activity and contains dual general acid/base residues, both of which contribute to its enzymatic activity. These findings not only represent the first characterization of a novel bacterial DUSP with dual general acid/base residues but also provide a foundation for understanding the diversity of DUSP proteins in bacteria.

Dengue, caused by four serotypes of dengue viruses (DENV-1 to DENV-4), is the most prevalent and widely mosquito-borne viral disease affecting humans. Dengue virus (DENV) infection has been reported in over 100 countries, and approximately half of the world's population is now at risk. The paucity of universally licensed DENV vaccines highlights the urgent need to address this public health concern. Action and attention to antibody-dependent enhancement increase the difficulty of vaccine development. With the worsening dengue fever epidemic, Dengvaxia^® (CYD-TDV) and Qdenga^® (TAK-003) have been approved for use in specific populations in affected areas. However, these vaccines do not provide a balanced immune response to all four DENV serotypes and the vaccination cannot cover all populations. There is still a need to develop a safe, broad-spectrum, and effective vaccine to address the increasing number of dengue cases worldwide. This review provides an overview of the existing DENV vaccines, as well as potential candidates for future studies on DENV vaccine development, and discusses the challenges and possible solutions in the field.

Extracellular vesicles derived from probiotics have received considerable attention for their pivotal role in bacterial‒host communication. These nanosized, bilayer-encapsulated vesicles carry diverse bioactive molecules, such as proteins, lipids, nucleic acids, and metabolites. Currently, ample evidence has emerged that probiotic extracellular vesicles may modulate several processes of host physiological hemostasis and offer therapeutic benefits. This review examines the biogenesis, composition, and immunomodulatory functions of probiotic-derived extracellular vesicles in probiotic–host interactions, highlighting the therapeutic potential of probiotic extracellular vesicles in the diagnosis and treatment of conditions such as cancer and inflammatory bowel disease. We further summarize the techniques for the separation and purification of extracellular vesicles, providing a methodological foundation for future research and applications. Although the field of probiotic extracellular vesicle research is still in its infancy, the prospects for their application in the biomedical field are broad, potentially emerging as a novel therapeutic approach.

Protein solubility is a critical factor in the production of recombinant proteins, which are widely used in various industries, including pharmaceuticals, diagnostics, and biotechnology. Predicting protein solubility remains a challenging task due to the complexity of protein structures and the multitude of factors influencing solubility. Recent advances in computational methods, particularly those based on machine learning, have provided powerful tools for predicting protein solubility, thereby reducing the need for extensive experimental trials. This review provides an overview of current computational approaches to predict protein solubility. We discuss the datasets, features, and algorithms employed in these models. The review aims to bridge the gap between computational predictions and experimental validations, fostering the development of more accurate and reliable solubility prediction models that can significantly enhance recombinant protein production.

The widespread use of antibiotics in aquaculture has led to the emergence of multidrug-resistant pathogens and environmental concerns, highlighting the need for sustainable, eco-friendly alternatives. In this study, we isolated and characterized three novel bacteriophages from aquaculture effluents in Korean shrimp farms that target the key Vibrio pathogens, Vibrio harveyi, and Vibrio parahaemolyticus. Bacteriophages were isolated through environmental enrichment and serial purification using double-layer agar assays. Transmission electron microscopy revealed that the phages infecting V. harveyi, designated as vB_VhaS-MS01 and vB_VhaS-MS03, exhibited typical Siphoviridae morphology with long contractile tails and icosahedral heads, whereas the phage isolated from V. parahaemolyticus (vB_VpaP-MS02) displayed Podoviridae characteristics with an icosahedral head and short tail.

Whole-genome sequencing produced complete, circularized genomes of 81,710 bp for vB_VhaS-MS01, 81,874 bp for vB_VhaS-MS03, and 76,865 bp for vB_VpaP-MS02, each showing a modular genome organization typical of Caudoviricetes. Genomic and phylogenetic analyses based on the terminase large subunit gene revealed that although vB_VhaS-MS01 and vB_VhaS-MS03 were closely related, vB_VpaP-MS02 exhibited a distinct genomic architecture that reflects its unique morphology and host specificity. Collectively, these comparative analyses demonstrated that all three phages possess genetic sequences markedly different from those of previously reported bacteriophages, thereby establishing their novelty. One-step growth and multiplicity of infection (MOI) experiments demonstrated significant differences in replication kinetics, such as burst size and lytic efficiency, among the phages, with vB_VhaS-MS03 maintaining the most effective bacterial control, even at an MOI of 0.01. Additionally, host range assays showed that vB_VhaS-MS03 possessed a broader spectrum of activity, supporting its potential use as a stand-alone agent or key component of phage cocktails. These findings highlight the potential of region-specific phage therapy as a targeted and sustainable alternative to antibiotics for controlling Vibrio infections in aquaculture.

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) technologies have emerged as powerful tools for precise genome editing, leading to a revolution in genetic research and biotechnology across diverse organisms including microalgae. Since the 1950s, microalgal production has evolved from initial cultivation under controlled conditions to advanced metabolic engineering to meet industrial demands. However, effective genetic modification in microalgae has faced significant challenges, including issues with transformation efficiency, limited target selection, and genetic differences between species, as interspecies genetic variation limits the use of genetic tools from one species to another. This review summarized recent advancements in CRISPR systems applied to microalgae, with a focus on improving gene editing precision and efficiency, while addressing organism-specific challenges. We also discuss notable successes in utilizing the class 2 CRISPR-associated (Cas) proteins, including Cas9 and Cas12a, as well as emerging CRISPR-based approaches tailored to overcome microalgal cellular barriers. Additionally, we propose future perspectives for utilizing CRISPR/Cas strategies in microalgal biotechnology.

Protein quality control systems are increasingly recognized as a critical determinant of bacterial survival and antibiotic tolerance. Conventional antibiotics predominantly target nucleic acids, protein synthesis, or cell wall synthesis, yet bacterial adaptation and resistance emergence remain major challenges. Targeting the bacterial protein quality control machineries including molecular chaperones and proteases offers a promising strategy to overcome these limitations. Recent advances include small molecules and adaptor/degron mimetics that modulate the activities of chaperones and proteases, aggregation-prone peptides (APPs) that induce proteotoxic stress, and bacterial PROTAC (BacPROTAC) strategies that redirect endogenous proteases. Notably, persister and viable-but-non-culturable (VBNC) cells, which tolerate conventional antibiotics, remain susceptible to proteostasis-targeted approaches, thereby enabling killing in both actively dividing and dormant populations. Furthermore, synergistic strategies combining chaperone inhibition or protease activation with conventional antibiotics enhance bactericidal efficacy, suggesting a potential avenue to mitigate antimicrobial resistance. This review summarizes the mechanistic basis, recent developments, and translational potential of proteostasis-centered antibacterial strategies.

The escalating threat of antimicrobial resistance has renewed global interest in peptide-based antibiotics as adaptable and effective alternatives to conventional small molecules. Peptides possess diverse mechanisms of action, high target specificity, and structural flexibility, which collectively limit the emergence of resistance. This review outlines recent advances spanning the discovery, optimization, and application of peptide antibiotics, from their biological origins and structural classifications to emerging strategies involving artificial intelligence, synthetic biology, and modern delivery technologies. Peptide antibiotics can be categorized by origin as natural, semi-synthetic, or fully synthetic, and further organized by structural class such as α-helical, β-sheet, cyclic, and extended forms. They are also grouped by function into membrane-targeted and non-membrane-targeted types. These classification schemes are not only descriptive but also critical for understanding the therapeutic potential of peptides, as each category presents distinct advantages and engineering challenges that influence stability, specificity, and overall clinical performance. Advances in artificial intelligence, synthetic biology, and continuous manufacturing are reshaping how peptide drugs are designed and produced, while innovations in drug delivery systems are addressing critical issues of stability and bioavailability. Together, these developments are laying the foundation for a new generation of peptide-based therapeutics capable of meeting the evolving challenges of antimicrobial resistance.

I53-50 is a computationally designed, self-assembling protein nanoparticle (NP) that forms a stable icosahedral structure composed of 120 protein subunits coordinated through precise interfacial interactions. Through unique intelligent regulation, I53-50 exhibits sensitivity to environmental signals and display multimodal “nano-smart” properties. I53-50 has a variety of modifiable surface-active sites, which facilitates precise chemical modification, gene fusion, tag coupling, and other functionalizations, thereby promoting effective lymphatic uptake and optimizing the immune response. I53-50 NPs show great potential in vaccine development, drug delivery, and biomaterials, representing a model fusion of computational biology and nanomedicine and offering a versatile tool for precision medicine.

Existing microbial engineering strategies—encompassing metabolic engineering, systems biology, and systems metabolic engineering—have significantly enhanced the potential of microbial cell factories as sustainable alternatives to the petrochemical industry by optimizing metabolic pathways. Recently, systems metabolic engineering, which integrates tools from synthetic biology, enzyme engineering, omics technology, and evolutionary engineering, has been successfully developed. By leveraging modern engineering strategies within the Design-Build-Test-Learn (DBTL) cycle framework, these advancements have revolutionized the biosynthesis of valuable compounds. This review highlights recent progress in the metabolic engineering of Corynebacterium glutamicum, a versatile microbial platform, achieved through various approaches from traditional metabolic engineering to advanced systems metabolic engineering, all within the DBTL cycle. A particular focus is placed C5 platform chemicals derived from L-lysine, one of the key amino acid production pathways of C. glutamicum. The development of DBTL cycle-based metabolic engineering strategies for this process is discussed.

The escalating antibiotic resistance crisis poses a significant challenge to global public health, threatening the efficacy of current treatments and driving the emergence of multidrug-resistant pathogens. Among the various factors associated with bacterial antibiotic resistance, small regulatory RNAs (sRNAs) have emerged as pivotal post-transcriptional regulators which orchestrate bacterial adaptation to antibiotic pressure via diverse mechanisms. This review consolidates the current knowledge on sRNA-mediated mechanisms, focusing on drug uptake, drug efflux systems, lipopolysaccharides, cell wall modification, biofilm formation, and mutagenesis. Recent advances in transcriptomics and functional analyses have revealed novel sRNAs and their regulatory networks, expanding our understanding of resistance mechanisms. These findings highlight the potential of targeting sRNA-mediated pathways as an innovative therapeutic strategy to combat antibiotic resistance, and offer promising avenues for managing challenging bacterial infections.

Reliable quantification of neutralizing antibodies (nAb) against human adenovirus type 55 (HAdV-55) is critical for the evaluation of emerging vaccine candidates. While the plaque reduction neutralization test (PRNT) is currently the reference standard, its utility for large-scale studies is limited by low throughput, labor-intensive plaque counting, and prolonged assay times. In this study, we established and analytically validated a microneutralization assay based on cytopathic effect (MN-CPE) as a scalable alternative for HAdV-55-specific nAb quantification. Comparative performance analysis revealed that both assays maintain high dilution linearity, with coefficients of determination (R²) of 0.988 for MN-CPE and 0.9926 for PRNT. Relative accuracy assessments using high-, middle-, and low-titer reference sera demonstrated acceptable responses across the dynamic range. Notably, the MN-CPE assay allowed for the definition of a negative-control acceptance range, providing a distinct statistical advantage over PRNT, where negative-control values were consistently zero. Furthermore, both assays successfully detected HAdV-55-specific nAbs in immunized cynomolgus macaques, with no cross-reactivity observed against other HAdV types such as HAdV-4. These findings indicate that the MN-CPE assay is analytically comparable to PRNT and serves as a practical, relatively high-capacity alternative for HAdV-55 neutralization testing in clinical and preclinical vaccine research.

Recent advances in sequencing technologies, particularly long-read platforms, have substantially improved contiguity of bacterial genome assemblies and enabled the routine generation of near-complete or circular genomes. However, achieving a contiguous assembly does not necessarily guarantee accuracy. Assembly errors, including structural misassemblies, collapsed repeats, incorrect circularization, plasmid reconstruction errors, and nucleotide-level inaccuracies, remain prevalent and may lead to misleading biological interpretations if not properly identified. In this review, we provide a comprehensive overview of bacterial genome assembly from a validation-centered perspective and examine the underlying causes of draft genome formation and assembly uncertainty, highlighting the roles of repetitive genomic structures, platform-specific error profiles, and algorithmic limitations. We further emphasize that the central challenge in contemporary bacterial genomics is no longer simply to maximize assembly contiguity, but to determine whether apparently complete genomes are truly correct and sufficiently reliable for their intended downstream applications. We propose a practical decision-making framework that links sequencing strategy, assembly workflow, polishing, and validation rigor, and introduce a tiered confidence classification to guide the interpretation of genome assembly reliability. As bacterial genome sequencing becomes increasingly routine and large-scale, future efforts should prioritize accuracy, reproducibility, transparent reporting, and evidence-supported validation over completeness alone.

Meiotic recombination is initiated by programmed DNA double-strand breaks (DSBs), which are subsequently processed to generate single-stranded DNA (ssDNA). Replication protein A (RPA), a heterotrimeric ssDNA-binding complex, plays essential roles in DNA replication, repair, and recombination; however, the specific functions of RPA in meiotic recombination progression and chromosome morphogenesis remain unclear. Here, we investigate the role of RPA in recombination and meiotic progression by conditionally depleting Rfa1, the large subunit of the RPA complex, using an auxin-inducible degron (AID) system in Saccharomyces cerevisiae. We show that Rfa1 depletion causes severe defects in meiotic recombination, including impaired DSB processing, defective chromosome axis assembly, compromised synaptonemal complex formation, and failure of ZMM-dependent crossover recombination. Notably, inhibition of Mek1 protein kinase activity, which bypasses the recombination checkpoint, does not rescue these defects in Rfa1-depleted cells. Together, these findings identify RPA as a key factor that stabilizes recombination intermediates and coordinates prophase I events with chromosome synapsis and crossover formation during meiosis.

β-Lactam antibiotics marked the beginning of an era of effective and safe treatment for bacterial infections and remain the most widely prescribed antibacterial agents today. However, the emergence of antibiotic-resistant bacteria threatens a return to the pre-antibiotic era. In particular, bacterial expression of β-lactamases inactivating β-lactam antibiotics presents a challenge in antimicrobial therapy. While inhibitors against β-lactamases have been developed to protect the therapeutic efficacy of β-lactam antibiotics, the clinical use of β-lactamase inhibitors is constrained due to their limited inhibition spectrum and the emergence of inhibitor-resistant β-lactamase variants. As an effort to tackle this issue, here we reviewed the structural and mechanistic features of β-lactamases and their FDA-approved inhibitors. Moreover, mutations in clinically isolated β-lactamases that confer resistance against their inhibitors are compiled. The comprehensive overview offered in this review aims to support and stimulate the design of next-generation β-lactamase inhibitors for combating β-lactamase-mediated antibiotic resistance.

This review explores current advancements in microbiome functional analysis enabled by next-generation sequencing technologies, which have transformed our understanding of microbial communities from mere taxonomic composition to their functional potential. We examine approaches that move beyond species identification to characterize microbial activities, interactions, and their roles in host health and disease. Genome-scale metabolic models allow for in-depth simulations of metabolic networks, enabling researchers to predict microbial metabolism, growth, and interspecies interactions in diverse environments. Additionally, computational methods for predicting metabolite profiles offer indirect insights into microbial metabolic outputs, which is crucial for identifying biomarkers and potential therapeutic targets. Functional pathway analysis tools further reveal microbial contributions to metabolic pathways, highlighting alterations in response to environmental changes and disease states. Together, these methods offer a powerful framework for understanding the complex metabolic interactions within microbial communities and their impact on host physiology. While significant progress has been made, challenges remain in the accuracy of predictive models and the completeness of reference databases, which limit the applicability of these methods in under-characterized ecosystems. The integration of these computational tools with multi-omic data holds promise for personalized approaches in precision medicine, allowing for targeted interventions that modulate the microbiome to improve health outcomes. This review highlights recent advances in microbiome functional analysis, providing a roadmap for future research and translational applications in human health and environmental microbiology.

The increasing environmental concerns regarding conventional plastics have led to a growing demand for sustainable alternatives, such as biodegradable plastics. Yeast cell factories, specifically Saccharomyces cerevisiae and Yarrowia lipolytica, have emerged as promising platforms for bioplastic production due to their scalability, robustness, and ease of manipulation. This review highlights synthetic biology approaches aimed at developing yeast cell factories to produce key biodegradable plastics, including polylactic acid (PLA), polyhydroxyalkanoates (PHAs), and poly (butylene adipate-co-terephthalate) (PBAT). We explore recent advancements in engineered yeast strains that utilize various synthetic biology strategies, such as the incorporation of new genetic elements at the gene, pathway, and cellular system levels. The combined efforts of metabolic engineering, protein engineering, and adaptive evolution have enhanced strain efficiency and maximized product yields. Additionally, this review addresses the importance of integrating computational tools and machine learning into the Design-Build-Test-Learn cycle for strain development. This integration aims to facilitate strain development while minimizing effort and maximizing performance. However, challenges remain in improving strain robustness and scaling up industrial production processes. By combining advanced synthetic biology techniques with computational approaches, yeast cell factories hold significant potential for the sustainable and scalable production of bioplastics, thus contributing to a greener bioeconomy.

Methane gas is recognized as a promising carbon substrate for the biosynthesis of value-added products due to its abundance and low price. Methanotrophs utilized methane as their sole source of carbon and energy, thus they can serve as efficient biocatalysts for methane bioconversion. Methanotrophs-catalyzed microbial bioconversion offer numerous advantages, compared to chemical processes. Current indirect chemical conversions of methane suffer from their energy-intensive processes and high capital expenditure. Methanotrophs can be cell factories capable of synthesizing various value-added products from methane such as methanol, organic acids, ectoine, polyhydroxyalkanoates, etc. However, the large-scale commercial implementation using methanotrophs remains a formidable challenge, primarily due to limitations in gas-liquid mass transfer and low metabolic capacity. This review explores recent advancements in methanotroph research, providing insights into their potential for enabling methane bioconversion.

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.

This study compared the rhizosphere microbial communities of two closely related Monotropastrum species (M. humile, Mh; and M. humile var. glaberrima, Mhg) and identified key soil factors associated with their assembly. Bacterial and fungal communities were profiled by Illumina high-throughput sequencing, and soil physicochemical properties were assessed across multiple sites in Zhejiang Province, China. The bacterial communities of both species were dominated by Proteobacteria and Acidobacteriota at the phylum level, while the dominant fungal groups belonged to Ascomycota and Basidiomycota. The two plants shared several dominant bacterial genera, including Serratia, Burkholderia-Caballeronia-Paraburkholderia, and Bradyrhizobium, as well as common dominant fungal genera such as Saitozyma and Podila. Despite these similarities, species-specific enrichment patterns were observed. The rhizosphere of Mhg contained higher abundances of Acidothermus and Lactarius, whereas Mh preferentially enriched Cedecea, Klebsiella, and Russula. Bacterial communities were shaped by pH, soil organic matter (SOM), available potassium (AK), and available phosphorus (AP), whereas fungal communities were primarily influenced by pH, alkali-hydrolyzable nitrogen (AN), and SOM (p < 0.05). These results suggest that both host identity and soil properties contribute to rhizosphere microbial assembly, with clear host-associated differentiation in microbial communities. Notably, the identified host-associated microbial taxa, particularly key mycorrhizal fungi, may serve as potential microbial inoculants, providing new opportunities for the conservation and cultivation of mycoheterotrophic plants.

Antibiotic resistance poses a serious challenge to public health worldwide; however, the development of new antibiotic classes for combating bacterial infections, especially those caused by Gram-negative pathogens, has slowed in recent years. Dual-acting hybrid antibiotics with a metabolically non-cleavable covalent bond represent an emerging strategy for developing novel antibiotic classes to overcome antibiotic resistance. The covalent connection between two antibiotics results in a fixed pharmacokinetic profile of a single molecule and can impede bacterial efflux. However, as most antibiotics do not have membrane-destabilizing activity, the resulting increase in molecular weight by connection of two antibiotics could limit their activity against Gram-negative bacteria, whose outer membrane forms a strong barrier blocking the penetration of high-molecular weight antibiotics. Here, we review recent developments in dual-acting hybrid antibiotics targeting Gram-negative bacteria, with a focus on their antibacterial efficacy. We also discuss combination therapy strategies in which the underlying molecular mechanisms of synergy have been characterized. Finally, we outline future directions for the rational design of hybrid antibiotics against Gram-negative pathogens.

The global rise in obesity and its associated metabolic complications underscores the urgent need for safe and effective interventions. This study investigated the anti-obesity efficacy of a probiotic mixture containing Bifidobacterium breve BR3 and Lactiplantibacillus plantarum LP3 in C57BL/6 mice with high-fat diet (HFD)-induced obesity. After obesity was established by feeding a 60% kcal HFD, the probiotic mixture was administered orally for 4 weeks. Compared with the control group, mice receiving the L. plantarum LP3 and B. breve BR3 mixture exhibited significant reductions in body weight and total fat mass, as assessed by Dual-energy X-ray Absorptiometry (DXA) and Echo Magnetic Resonance Imaging (EchoMRI). The probiotic treatment also lowered serum Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT), and glucose levels, and attenuated lipid accumulation in both hepatic and epididymal adipose tissues. Transcriptomic profiling revealed upregulation of lipolytic genes (Sirt1, Pparα) and downregulation of lipogenic genes (Srebp1c, Fas), suggesting that the probiotic mixture promotes lipid catabolism while suppressing lipid synthesis. Additionally, serum adipokine levels were favorably modulated, indicating improved metabolic homeostasis. Gut microbiota analysis demonstrated an increased relative abundance of beneficial genera, including Akkermansia and Bacteroides, highlighting a microbiome-mediated contribution to the observed metabolic benefits. Overall, our findings indicate that the combined administration of Lactiplantibacillus plantarum LP3 and Bifidobacterium breve BR3 exerts multi-faceted anti-obesity effects by enhancing lipolysis, regulating lipid metabolism, and restoring a healthy gut microbial balance. This probiotic mixture represents a promising therapeutic approach for managing obesity and related metabolic disorders.

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.

CRISPR-Cas technologies have emerged as powerful and versatile tools in gene therapy. In addition to the widely used SpCas9 system, alternative platforms including modified amino acid sequences, size-optimized variants, and other Cas enzymes from diverse bacterial species have been developed to apply this technology in various genetic contexts. In addition, base editors and prime editors for precise gene editing, the Cas13 system targeting RNA, and CRISPRa/i systems have enabled diverse and adaptable approaches for genome and RNA editing, as well as for regulating gene expression. Typically, CRISPR-Cas components are transported to the target in the form of DNA, RNA, or ribonucleoprotein complexes using various delivery methods, such as electroporation, adeno-associated viruses, and lipid nanoparticles. To amplify therapeutic efficiency, continued developments in targeted delivery technologies are required, with increased safety and stability of therapeutic biomolecules. CRISPR-based therapeutics hold an inexhaustible potential for the treatment of many diseases, including rare congenital diseases, by making permanent corrections at the genomic DNA level. In this review, we present various CRISPR-based tools, their delivery systems, and clinical progress in the CRISPR-Cas technology, highlighting its innovative prospects for gene therapy.

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.

Truncal acne significantly impairs quality of life yet remains underexplored relative to facial acne, particularly with respect to fungal ecology. The trunk represents a distinct cutaneous niche characterized by thicker epidermis, larger follicular units, and frequent occlusion, and harbors a high abundance of Malassezia species. In this study, we used internal transcribed spacer 2 (ITS2) amplicon sequencing to characterize the truncal mycobiome in patients with acne and in healthy controls and to compare fungal community features across doxycycline exposure groups. Although serial sampling was planned, seven participants contributed a single follow-up sample after doxycycline treatment, and only two participants contributed multiple follow-up samples sufficient for true within-subject longitudinal analyses; therefore, most analyses represent exposure-stratified cross-sectional comparisons rather than confirmed temporal change. At baseline, truncal acne lesions exhibited increased fungal richness and distinct community composition compared with controls. Acne lesions were more frequently enriched for Malassezia globosa, whereas healthy controls were dominated by M. sympodialis. Across doxycycline exposure groups, fungal communities remained Malassezia-dominant with substantial inter-individual variability. Doxycycline exposure was associated with partial and heterogeneous differences in Malassezia species composition without uniform normalization toward control profiles. Because only fungal sequencing was performed, bacterial–fungal interactions were inferred from prior literature and not directly measured. These findings indicate that truncal acne is associated with a distinct fungal community structure and highlight the need for integrated, longitudinal multi-omics studies to clarify treatment-associated microbial dynamics.

Collagenase and keratinase are two important proteolytic enzymes with recognized applications in biotechnology and medicine, particularly in the enzymatic removal of necrotic tissue and the control of infection. In the present work, a soil isolate of Bacillus subtilis strain AB2 (PX453297.1) was optimized for enzyme production under different nutritional and physicochemical conditions. The enzymes were recovered by ammonium sulphate precipitation and dialysis, examined by SDS-PAGE and zymography, and further assessed for pH and temperature optima, stability, the influence of metal ions, and kinetic parameters. Maximum collagenase activity (4.41 ± 0.22 U/ml) was observed at 37°C and pH 7.5 in a glucose–peptone medium, whereas keratinase production was enhanced between 37 and 40°C at pH 7.5 in lactose–peptone medium. Protein bands of approximately 55 and 33 kDa were detected, representing 6.2- and 5.5-fold purification. Collagenase showed an alkaline optimum (pH 10.0, 37–45°C) with K_m 0.31% and V_max 1.92 U/ml, while keratinase exhibited dual optima (pH 3.0 and ~7.0) with K_m 0.27% and V_max 0.84 U/ml. Biofilm assays revealed that collagenase reduced pre-formed biomass by 62–68% and viable counts by 1.1–1.7 log₁₀, clearly outperforming keratinase (41–57%, 0.7–1.2 log₁₀). When combined with conventional antibiotics, both enzymes potentiated activity, with notable synergy between collagenase and oxacillin against Staphylococcus aureus (FICI 0.31–0.37), ciprofloxacin against Pseudomonas aeruginosa (FICI 0.37–0.50), and meropenem against Klebsiella pneumoniae (FICI 0.28–0.44). These results indicate that B. subtilis AB2 produces collagenase and keratinase with distinct biochemical characteristics and strong antibiofilm properties, underscoring their promise as adjuncts in chronic wound care as well as in industrial applications.

Chimeric antigen receptor (CAR)-T cell therapy holds significant potential for the treatment of solid tumors. However, immune suppression and tumor-specific barriers limit its application. Claudin 18.2 (CLDN18.2), a gastric lineage-specific tight junction protein highly expressed in gastric and pancreatic cancers, is a promising therapeutic target. In this study, we aimed to develop a next-generation tri-cistronic CLDN18.2-directed CAR-T cell platform that integrates a programmed cell death protein 1 (PD-1)/CD28 chimeric switch receptor with cyclophilin A (CypA). This platform sought to counteract PD-1–mediated immunosuppression and enhance T-cell activation and persistence. We generated CLDN18.2 CAR-T cells incorporating costimulatory inducible T-cell costimulator (ICOS) domains using lentiviral vector-based recombinant engineering. We further evaluated their cytokine release, cytotoxic activity, and safety profiles. In vitro, tri-cistronic CAR-T cells exhibited markedly increased interferon γ and tumor necrosis factor α secretion and enhanced cytotoxicity against CLDN18.2-positive gastric cancer cells compared with conventional CAR-T constructs. In vivo, these cells showed superior antitumor efficacy and sustained tumor regression without observable toxicity in xenograft gastric cancer models. Collectively, these findings demonstrate that the integration of PD-1/CD28 signaling and CypA within a tri-cistronic framework significantly reinforces CAR-T cell functionality and durability. This suggests strong clinical potential as a next-generation immunotherapy for solid tumors.

Two novel bacterial strains, designated CJ20^T and CJ99^T, belonging to the genus Sphingomonas, were isolated from the Han River in South Korea and a wetland in South Korea, respectively. Cells of both strains were Gram-stain-negative, aerobic, non-motile and yellow-pigmented. Strains were shown to grow optimally at 30˚C and pH 7 in the absence of NaCl on tryptic soy medium. Phylogenetic analysis based on 16S rRNA gene sequences showed that strains CJ20^T and CJ99^T belonged to the genus Sphingomonas and were most closely related to S. asaccharolytica Y-345^T and Sphingomonas koreensis JSS26^T with 97.87% and 97.58% 16S rRNA gene sequence similarities, respectively. Average nucleotide identity and digital DNA-DNA hybridization values of strain CJ20^T with S. asaccharolytica Y-345^T were 74.1% and 15.9%, respectively and those values of strain CJ99^T with S. koreensis JSS26^T were 73.9% and 15.6%, respectively. Both strains contained ubiquinone (Q-10) as the predominant respiratory quinone. The major polar lipids of strains CJ20^T and CJ99^T comprised phosphatidylethanolamine, diphosphatidylglycerol, phosphatidylglycerol, and sphingoglycolipid. The predominant fatty acids of both strains were summed feature 8 (C_18:1 ω7c and/or C_18:1 ω6c) and C_16:0. Based on polyphasic taxonomic analyses, strains CJ20^T and CJ99^T represent novel species of the genus Sphingomonas, for which names Sphingomonas degradans sp. nov. and Sphingomonas paludis are proposed, respectively. The type strains are CJ20^T (= KACC 23909 = JCM 37720) and CJ99^T (= KACC 24077 = JCM 37956).

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.

The increase of sequence data in public nucleotide databases has made DNA sequence-based identification an indispensable tool for fungal identification. However, the large proportion of mislabeled sequence data in public databases leads to frequent misidentifications. Inaccurate identification is causing severe problems, especially for industrial and clinical fungi, and edible mushrooms. Existing species identification pipelines require separate validation of a dataset obtained from public databases containing mislabeled taxonomic identifications. To address this issue, we developed FunVIP, a fully automated phylogeny-based fungal validation and identification pipeline (https://github.com/Changwanseo/FunVIP). FunVIP employs phylogeny-based identification with validation, where the result is achievable only with a query, database, and a single command. FunVIP command comprises nine steps within a workflow: input management, sequence-set organization, alignment, trimming, concatenation, model selection, tree inference, tree interpretation, and report generation. Users may acquire identification results, phylogenetic tree evidence, and reports of conflicts and issues detected in multiple checkpoints during the analysis. The conflicting sample validation performance of FunVIP was demonstrated by re-iterating the manual revision of a fungal genus with a database with mislabeled sequences, Fuscoporia. We also compared the identification performance of FunVIP with BLAST and q2-feature-classifier with two mass double-revised fungal datasets, Sanghuangporus and Aspergillus section Terrei. Therefore, with its automatic validation ability and high identification performance, FunVIP proves to be a highly promising tool for achieving easy and accurate fungal identification.

Actinobacillus pleuropneumoniae (APP) is the etiological agent of porcine pleuropneumoniae (PP), a high contagious respiratory disease with significant impact on the swine industry in both clinically and economically. Despite of the several attempts to control APP, the emergence of novel serotypes and antimicrobial resistance (AMR) strains highlights the importance of monitoring the genetic characteristics of APP at single nucleotide level. Despite the importance of genomic surveillance of APP to develop effective control strategies, genetic information on the recent Korean isolates of APP is not available at whole genome level. Therefore, in this study, six APP strains were isolated from porcine lungs with characteristic lesions of PP from 2022 to 2024. And their whole genomic sequences, serotypes, virulence factors, and AMR traits were investigated using combined short- and long-read sequencing methods. In silico PCR serotyping identified the isolates as serotype 1, 7, and 15, while one isolate was non-typeable. Multiple AMR genes including Hinf_PBP3_BLA, Ecol_EFTu_PLV, tet(B), tet(O), tetR, sul2, aph(3'')-Ib, aph(6)-Id, and aph(3')-Ia were detected. Also, these genes were located with adjacent to mobile genetic elements, suggesting the possibility of horizontal gene transfer. Phylogenetic comparison with 40 global APP complete genomes, presented that Korean isolates were closely related with China and Switzerland strains. This study provides the whole genome sequences based genetic characterization on the recent Korean isolates of APP, and this study emphasizes that continuous monitoring of APP genomic variation to support effective control of porcine pleuropneumoniae.

The COVID-19 pandemic highlighted the critical role of reliable molecular diagnostics in outbreak response and the vulnerabilities of existing systems to delays and reagent instability. Armored RNA technology, which packages RNA within bacteriophage-derived capsids, offers a robust solution by combining nuclease resistance, safety, and versatility into a single platform. Armored RNA has become a trusted internal and external control for RT-qPCR and RT-LAMP, enabling accurate detection across a wide range of viral pathogens. Also, recent advances in alternative expression systems, such as plant-based and cell-free platforms, as well as the use of more stable scaffolds from bacteriophage Qβ, are enhancing yield, stability, and accessibility of armored RNA. Engineering innovations, including capsid polymorphism and optimized downstream purification, further improve efficiency and broaden possible applications. Looking ahead, armored RNA holds promise not only as a diagnostic standard but also as a delivery vehicle for vaccines and therapeutics. Encapsulation of self-amplifying RNA, small interfering RNA, or microRNA could open new pathways for rapid-response vaccines and targeted therapies, aligning this technology with the future of precision medicine. By uniting stability, scalability, and adaptability, armored RNA represents a critical component of global health preparedness, with the potential to strengthen diagnostic resilience and accelerate biomedical countermeasures in future pandemics.

Synbiotics have become a new-age treatment tool for limiting the progression of metabolic dysfunction-associated steatotic liver disease; however, inclusive comparisons of various synbiotic treatments are still lacking. Here, we have explored and evaluated multiple synbiotic combinations incorporating three distinctive prebiotics, lactitol, lactulose and fructooligosaccharides. Of the synbiotic treatments evaluated, a combination of fructooligosaccharides and probiotics (FOS+Pro) exhibited superior protection against western diet-induced liver degeneration. This synbiotic (FOS+Pro) combination resulted in the lowest body weight gains, liver weights and liver/body weight ratios. The FOS+Pro synbiotic combination substantially alleviated liver histopathological markers and reduced serum AST and cholesterol levels. FOS+Pro ameliorated hepatic inflammation by lowering expression of proinflammatory markers including TNF-α, IL-1β, IL-6, and CCL2. FOS+Pro significantly improved steatosis by restricting the expression of lipid metabolic regulators (ACC1, FAS) and lipid transporters (CD36) in the liver. These findings are critical in suggesting that synbiotic treatments are capable of restraining western diet-induced metabolic dysfunction in the liver. Additionally, this study demonstrated that adding probiotic strains amplified the effectiveness of fructooligosaccharides but not all prebiotics.

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.

Three Gram-stain-negative, strictly aerobic, motile bacterial strains, designated IMCC44359^T, IMCC44632^T, and IMCC44653, were isolated from coastal surface seawater collected near Jangbong Island in the Yellow Sea. Phylogenetic analyses based on 16S rRNA gene and whole-genome sequences assigned the isolates to the genus Aliikangiella. Strains IMCC44632^T and IMCC44653 shared identical 16S rRNA gene sequences and exhibited high genomic relatedness (99.0% average nucleotide identity and 92.0% digital DNA-DNA hybridization), indicating that they represent a single species. In contrast, strain IMCC44359^T showed low genomic relatedness to these strains and to previously validly published Aliikangiella species, supporting its recognition as a distinct species. The genome of IMCC44359^T (5.95 Mbp; 36.5 mol% G + C) is substantially larger than those of IMCC44632^T and IMCC44653 (~3.75 Mbp; 40.1–40.2 mol% G + C), and all genomes encode aerobic chemoorganotrophic metabolism and biochemical capacities consistent with adaptation to marine environments. The isolates grew under mesophilic and moderately halophilic conditions typical of coastal seawater bacteria, with growth occurring at ranges at 10–40℃, pH 6.0–9.0, and 0.5–7.5% NaCl (optimum, 30℃, pH 7.0–8.0, and 2.0–3.0% NaCl). All strains contained ubiquinone-8 (Q-8) as the sole respiratory quinone, and phosphatidylethanolamine, phosphatidylglycerol, and diphosphatidylglycerol were the major polar lipids. The dominant cellular fatty acids were iso-C_15:0 and summed feature 9 (iso-C_17:1 ω9c and/or C_16:0 10-methyl). Integrated phylogenetic, genomic, phenotypic evidence supported the recognition of two novel species within the genus Aliikangiella, for which the names Aliikangiella litoralis sp. nov. (type strain IMCC44359^T = KCTC 18089^T = JCM 37879^T = HNIBRBA19635^T) and Aliikangiella aequoris sp. nov. (type strain IMCC44632^T = KCTC 18090^T = JCM 37880^T = HNIBRBA19636^T) are proposed.

Antibiotic resistance has become a critical global health challenge due to the decreased efficacy of existing antibiotics and the emergence of multidrug-resistant pathogens. In particular, the rapid horizontal transfer of resistance genes and the diverse mechanisms by which bacteria acquire resistance have significantly undermined the effectiveness of conventional therapeutic strategies, revealing fundamental limitations in current infectious disease management. In this context, synthetic biology provides a promising framework to overcome the limitations of conventional antibiotics by integrating engineering principles with bioengineering approaches, thereby enabling precise and programmable control of biological processes. These synthetic biology-based approaches offer substantial potential for developing sustainable and highly specific antimicrobial strategies. This review comprehensively examines recent advances in synthetic biology-assisted antimicrobial strategies, including CRISPR-Cas systems, bacteriophage engineering, microbiome engineering, and metabolic engineering-driven antibiotic discovery. Collectively, these approaches represent a precision antimicrobial paradigm that enables selective targeting of resistant bacteria while preserving microbiome homeostasis. These strategies also provide new directions for limiting resistance dissemination and guiding the development of next-generation therapeutics.

Basal cell carcinoma (BCC) is the most common form of skin cancer, with ultraviolet radiation recognized as the primary environmental driver; however, the potential contribution of alterations in the skin microbiota remains incompletely understood, particularly in Asian populations. This exploratory pilot study describes bacterial community patterns in BCC lesions compared with contralateral clinically normal skin in 20 Korean patients. Lesional and contralateral samples were obtained using paired skin swabs and punch biopsies and analyzed by full-length 16S rRNA gene sequencing, with targeted quantitative PCR (qPCR) of the roxP antioxidant gene of Cutibacterium acnes. Given the low-biomass nature of skin samples and the exploratory design, analyses focused on descriptive trends rather than confirmatory inference. Across available samples, C. acnes was the dominant taxon, with a trend toward lower relative abundance in BCC lesions, particularly in biopsy-derived datasets. Microbial evenness appeared higher in lesions than controls. Predictive functional profiling suggested reduced representation of vitamin B6 metabolism pathways in lesions, while qPCR analysis of swab samples showed a trend toward lower roxP/16S rRNA ratios in BCC-associated microbiota. These findings should be interpreted cautiously in light of methodological constraints, including sample heterogeneity, lidocaine exposure prior to biopsy, absence of sequencing-based negative controls, and reliance on predictive functional inference. Overall, this pilot study highlights potential differences in skin bacterial community structure between BCC lesions and contralateral skin in a Korean cohort. Larger, methodologically optimized studies incorporating metagenomic and functional validation will be required to determine whether these microbiota shifts contribute to, or result from, BCC-associated changes in the cutaneous environment.

Prebiotics are indigestible dietary components that improve host health by stimulating the growth and metabolic activity of beneficial intestinal microbes. The whole grains are rich in non-digestible carbohydrates, which may confer prebiotic potential. Among them, millet and quinoa have gained attention as dietary alternatives due to the growing popularity of gluten-free diets. In this study, we examined the effects of proso millet and quinoa on the human gut microbiota using an in vitro fecal incubation model. Both grains altered alpha diversity metrics, including microbial richness, evenness, and phylogenetic diversity. Beta diversity analysis showed that the proso millet and quinoa treatment groups exhibited distinct clustering patterns compared to the control, highlighting their impact on microbial community structure. Taxonomic analysis showed an increase in beneficial genera, including Bifidobacterium, and a decrease in taxa such as Enterobacteriaceae and Flavonifractor. To assess metabolic changes associated with microbial fermentation, short-chain fatty acid (SCFA) intensities were measured. The intensities of acetic acid, propionic acid, and butyric acid were significantly higher in the proso millet- and quinoa-treated groups compared to the control group. Spearman correlation analysis showed that the abundances of Bifidobacterium and Blautia were significantly positively associated with SCFA intensities. Furthermore, predicted functional pathway analysis identified enrichment of carbohydrate-related pathways in proso millet and quinoa treatments. Quinoa supplementation led to a broader enhancement of metabolic pathways, including glycolysis/gluconeogenesis, starch and sucrose metabolism, and pentose phosphate pathways, whereas proso millet enriched galactose metabolism, and starch and sucrose metabolism. These findings suggest that proso millet and quinoa influence gut microbial diversity, composition, and function.