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.
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Two Gram-stain-negative, strictly aerobic, non-motile, rod-shaped bacteria, designated D3-12ᵀ and G2-2ᵀ, were isolated from the phycosphere of marine red algae. Both strains exhibited catalase- and oxidase-positive activities. Strain D3-12ᵀ grew optimally at 30°C, pH 7.0, and 2.0–3.0% (w/v) NaCl, while strain G2-2ᵀ showed optimal growth at 30°C, pH 7.0, and 2.0% NaCl. Ubiquinone-10 was the sole respiratory quinone in both strains. The major fatty acids (> 5%) in strain D3-12ᵀ were feature 8 (C18:1 ω7c and/or C18:1 ω6c), 11-methyl-C18:1 ω7c, and C16:0, while strain G2-2ᵀ contained summed feature 8 and C16:0. The predominant polar lipids in strain D3-12ᵀ were phosphatidylcholine, phosphatidylglycerol, and phosphatidylethanolamine, whereas strain G2-2ᵀ contained phosphatidylglycerol and diphosphatidylglycerol. The genomic DNA G + C content was 59.9% for strain D3-12ᵀ and 60.2% for strain G2-2ᵀ. Phylogenetic analyses based on 16S rRNA and whole-genome sequences placed both strains into distinct lineages within the family Roseobacteraceae, separate from previously described genera. Genome-based relatedness metrics, including average nucleotide identity, digital DNA-DNA hybridization, average amino acid identity, and percentage of conserved proteins, further confirmed that these strains represent novel genera. Based on phenotypic, chemotaxonomic, and molecular characteristics, strains D3-12ᵀ and G2-2ᵀ are proposed as novel genera: Phycobium rhodophyticola gen. nov., sp. nov. (D3-12ᵀ = KACC 22712ᵀ = JCM 35528ᵀ) and Aliiphycobium algicola gen. nov., sp. nov. (G2-2ᵀ = KACC 22602ᵀ = JCM 35752ᵀ). Additionally, metabolic features relevant to interactions with marine algae, including genes associated with carbohydrate-active enzymes, vitamin biosynthesis, phenylacetic acid production, and bacterioferritin synthesis, were bioinformatically investigated.
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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.
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