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.

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.

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.

Microbial biosynthesis using yeast species offers numerous advantages to produce industrially relevant biofuels and biochemicals. Conventional metabolic engineering approaches in yeast focus on biosynthetic pathways in the cytoplasm, but these approaches are disturbed by various undesired factors including metabolic crosstalk, competing pathways and insufficient precursors. Given that eukaryotic cells contain subcellular organelles with distinct physicochemical properties, an emerging strategy to overcome cytosolic pathway engineering bottlenecks is through repurposing these organelles as specialized microbial cell factories for enhanced production of valuable chemicals. Here, we review recent progress and significant outcomes of harnessing organelle engineering for biofuels and biochemicals production in both conventional and non-conventional yeasts. We highlight key engineering strategies for the compartmentalization of biosynthetic pathways within specific organelles such as mitochondria, peroxisomes, and endoplasmic reticulum; involved in engineering of signal peptide, cofactor and energy enhancement, organelle biogenesis and dual subcellular engineering. Finally, we discuss the potential and challenges of organelle engineering for future studies and propose an automated pipeline to fully exploit this approach.

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.

Alcohol consumption can lead to the accumulation of harmful metabolites, such as acetaldehyde, contributing to various adverse health effects, including hangovers and liver damage. This study presents a comprehensive genomic and functional analysis of Leuconostoc suionicum VITA-PB2, a lactic acid bacterial strain isolated from kimchi, to elucidate its role in enhancing alcohol and acetaldehyde metabolism. Genomic characterization revealed key genes encoding alcohol dehydrogenase (ADH) and aldehyde dehydrogenase (ALDH), providing insights into the metabolic capabilities of strain VITA-PB2. Phylogenomic analyses confirmed its taxonomic classification and genetic similarity to other Leuconostoc species. Functional validation through in vitro and in vivo experiments demonstrated superior ethanol and acetaldehyde decomposition abilities of strain VITA-PB2, with significant reductions in blood ethanol and acetaldehyde levels observed in rats administered with the strain. Further analysis indicated that while hepatic ADH activity did not significantly increase; however, ALDH expression was elevated. This suggests that the microbial ADH of strain VITA-PB2 contributed to ethanol breakdown, while both microbial and host ALDH facilitated acetaldehyde detoxification. These findings highlight the potential of strain VITA-PB2 as a functional probiotic for mitigating the toxic effects of alcohol consumption.

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.

Tella is a traditional beverage widely accepted by consumers, despite the lack of product consistency owing to its reliance on natural fermentation. This study aimed to identify potential industrial lactic acid bacteria (LAB) starter cultures based on their technological properties. Seven LAB strains isolated from Tella were characterized for their carbohydrate utilization, salt content, temperature, and acid tolerances, growth and acidification rates, and metabolite profiles. Most strains efficiently utilized various carbohydrates, with Lactiplantibacillus plantarum TDM41 showing exceptional versatility. The strains exhibited similar growth characteristics. Principal component analysis of stress tolerance properties revealed that L. plantarum TDM41, Pediococcus pentosaceus TAA01, and Leuconostoc mesenteroides TDB22 exhibited superior tolerance ability. Strong acidification properties were detected in the L. plantarum TDM41, P. pentosaceus TAA01, and Leuconostoc mesenteroides TDB22 strains after 24 h incubation at 30°C. L. plantarum TDM41 displayed the fastest acidification rate throughout the analysis period. All LAB strains produced significant amounts of diverse organic acids, including lactic acid, citric acid, acetic acid, malic acid, and succinic acid, with lactic acid being the primary acid produced by each strain. Overall, strains L. plantarum TDM41 and P. pentosaceus TAA01 prove to be potential candidates for Tella industrial starter cultures and similar cereal products owing to their robust technological properties.