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.

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.

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 global spread of COVID-19 has underscored the urgent need for advanced tools to study emerging coronaviruses. Reverse genetics systems have become indispensable for dissecting viral gene functions, developing live-attenuated vaccine candidates, and identifying antiviral targets. In this study, we describe a robust and efficient reverse genetics platform for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The system is based on the assembly of a full-length infectious cDNA clone from seven overlapping fragments, each flanked by homologous sequences to facilitate seamless assembly using the Gibson assembly method. Individual cloning of each fragment into plasmids enables modular manipulation of the viral genome, allowing rapid site-directed mutagenesis by fragment exchange. Infectious recombinant virus was successfully recovered from the assembled cDNA, exhibiting uniform plaque morphology and genetic homogeneity compared to clinical isolates. Additionally, fluorescent reporter viruses were generated to enable real-time visualization of infection, and the effects of different mammalian promoters on viral rescue were evaluated. This reverse genetics platform enables efficient generation and manipulation of recombinant SARS-CoV-2, providing a valuable resource for virological research and the development of preventive and therapeutic antiviral measures.

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.

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.

Pectin-rich biomass, derived from fruit and citrus processing waste, presents a promising yet underutilized resource for sustainable biofuel and biochemical production. Its low lignin content and high concentrations of fermentable sugars, including D-galacturonic acid, L-arabinose, and D-xylose, make it an attractive feedstock. Unlike lignocellulosic biomass, pectin-rich hydrolysates require milder pretreatment, improving sugar recovery efficiency. However, industrial strains such as Saccharomyces cerevisiae exhibit strong glucose preference, limiting the efficient co-fermentation of mixed sugars. While prior reviews have broadly addressed lignocellulosic biomass utilization, this mini-review uniquely centers on the specific metabolic challenges and opportunities associated with pectin-rich feedstocks. In addition to incorporating established strategies for the co-utilization of cellobiose and xylose, we highlight recent advances that allow S. cerevisiae to metabolize carbon sources specifically from pectin-rich biomass, such as L-arabinose and D-galacturonic acid—monomers not prevalent in traditional lignocellulosic biomass. By integrating discussions on sugar transport engineering, redox balancing, and pathway optimization, this review offers a comprehensive framework to overcome glucose repression and support efficient co-fermentation of carbon sources from conventional and pectin-rich biomass. Drawing on these advances, we outline practical strategies to enhance fermentation performance and expand the valorization of food processing residues in biomanufacturing.

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.

Two rod-shaped, Gram-positive, spore-forming, motile, and strictly anaerobic bacteria, FM7315^T and FM7330^T were isolated from Myeolchi-jeot, a traditional Korean fermented anchovy. Phylogenetic and phylogenomic analyses based on the 16S rRNA gene and genome sequences revealed that strains FM7315^T and FM7330^T represent novel species within the genus Haloimpatiens. The genome sizes of strains FM7315^T and FM7330^T were 3,052,517 bp and 4,194,114 bp, respectively, with G + C contents of 29.7 mol% and 28.0 mol%, respectively. Strain FM7315^T exhibited growth at 20–37°C, 0–2% NaCl, and pH range of 5.0–8.0, whereas strain FM7330^T grew at 25–45°C, 0–4% NaCl, and pH range of 5.0–9.0. Strain FM7315^T contains C_14:0, C_16:0, C_18:1 ω9c, Summed Feature 3 (C_16:1 ω7c/C_16:1 ω6c), and Summed Feature 8 (C_18:1 ω7c/C_18:1 ω6c) as major fatty acids, along with diphosphatidylglycerol, phosphatidylglycerol, glycolipid, two aminophospholipids, and five unidentified lipids. Strain FM7330^T contains C_16:0, C_17:1 ω8c, and C_18:1 ω9c as major fatty acids, along with diphosphatidylglycerol, two phosphatidylglycerols, four aminophospholipids, and six unidentified lipids. Based on their phenotypic, chemotaxonomic, and molecular characteristics, strains FM7315^T and FM7330^T represent two novel species of the genus Haloimpatiens, for which the names Haloimpatiens sporogenes sp. nov. (FM7315^T = KCTC 25939^T = JCM 37574^T) and Haloimpatiens myeolchijeotgali sp. nov. (FM7330^T = KCTC 25938^T = JCM 37575^T) have been proposed.

The innate immune system relies on innate immune sensors, such as pattern recognition receptors (PRRs), to detect pathogens and initiate immune responses, crucial for controlling infections but also implicated in inflammatory diseases. These innate immune sensors, including Toll-like receptors (TLRs), nod-like receptors (NLRs), RIG-I-like receptors (RLRs), absent in melanoma 2 (AIM2), and Z-DNA binding protein 1 (ZBP1) trigger signaling pathways that produce cytokines, modulating inflammation and cell death. Traditional therapies focus on directly targeting pathogens; however, host-targeting therapeutic strategies have emerged as innovative approaches to modulate innate immune sensor activity. These strategies aim to fine-tune the immune response, either enhancing antiviral defenses or mitigating hyperinflammation to prevent tissue damage. This review explores innate immune sensor-based therapeutic approaches, including inhibitors, agonists, and antagonists, that enhance antiviral defense or suppress harmful inflammation, highlighting innate immune sensors as promising targets in infectious and inflammatory disease treatment.

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.

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.

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.

Strains Mo2-6^T, S9, KG4-3^T, and 50Mo3-2, identified as coagulase-negative, Gram-stain-positive, halotolerant, non-motile coccoid bacteria, were isolated from traditional Korean soybean foods. Strains Mo2-6^T and S9 were both catalase- and oxidase-negative, whereas KG4-3^T and 50Mo3-2 were catalase-positive but oxidase-negative. The optimal growth conditions for Mo2-6^T and S9 were 30°C, 2% NaCl, and pH 7.0, while KG4-3^T and 50Mo3-2 grew best at 35°C, 2% NaCl, and pH 7.0. All strains contained menaquinone-7 as the predominant isoprenoid quinone, with anteiso-C_15:0 and iso-C_15:0 as the major cellular fatty acids (> 10%). Additionally, anteiso-C_13:0 was a major fatty acid in strain KG4-3^T. The DNA G + C contents of strains Mo2-6^T, S9, KG4-3^T, and 50Mo3-2 were 33.4%, 33.3%, 32.5%, and 32.7%, respectively. Phylogenetic analyses based on the 16S rRNA gene and whole-genome sequences revealed that strains Mo2-6^T and S9, as well as KG4-3^T and 50Mo3-2, formed distinct lineages within the genus Staphylococcus. Digital DNA-DNA hybridization (dDDH) and average nucleotide identity (ANI) analyses confirmed that strains Mo2-6^T and S9, as well as KG4-3^T and 50Mo3-2, belonged to the same species. Meanwhile, dDDH and ANI values between strains Mo2-6^T and KG4-3^T, as well as comparisons with other Staphylococcus type strains, were below the species delineation thresholds, indicating they represent novel species. Based on phenotypic, chemotaxonomic, and molecular data, we propose strain Mo2-6^T as the type strain of Staphylococcus parequorum sp. nov. (=KACC 23685^T =JCM 37038^T) and strain KG4-3^T as the type strain of Staphylococcus halotolerans sp. nov. (=KACC 23684^T =JCM 37037^T).