Microbiome research reports最新文献

Polyphenols are food components with antioxidant and anti-inflammatory properties, and their health benefits are increasingly recognized in the context of noncommunicable diseases such as type 2 diabetes. However, their role in regulating immunity to infection is not well understood. Here, we highlight the various mechanisms by which polyphenols may enhance mucosal immunity via both adaptive and innate immune responses. Polyphenols may directly interact with host receptors on mucosal epithelial and/or immune cells to regulate production of cytokines and antimicrobial peptides. They can also modify gut microbiota composition, yielding microbial-derived metabolites that play a key role in fine-tuning immune function at mucosal surfaces. We provide examples of how these immunological changes may alter the outcome of pathogen infection and propose that an increased understanding of polyphenol-microbiota-immune interaction will provide a framework for the application of new nutrition-based strategies in the management and prevention of infectious diseases.

Background: The human gut microbiome is closely linked to disease states, offering substantial potential for novel disease detection tools based on machine learning (ML). However, variations in feature types, data preprocessing strategies, feature selection strategies, and classification algorithms can all influence the model's predictive performance and robustness. Methods: To develop an optimized and systematically evaluated workflow, we conducted a comprehensive evaluation of ML methods for classifying colorectal cancer and adenoma using 4,217 fecal samples from diverse global regions. The area under the receiver operating characteristic curve was used to quantify model performance. We benchmarked 6,468 unique analytical pipelines, defined by distinct tools, parameters, and algorithms, utilizing a dual validation strategy that included both cross-validation and leave-one-dataset-out validation. Results: Our findings revealed that shotgun metagenomic (WGS) data generally outperformed 16S ribosomal RNA gene (16S) sequencing data, with features at the species-level genome bin, species, and genus levels demonstrating the greatest discriminatory power. For 16S data, Amplicon Sequence Variant-based features yielded the best disease classification performance. Furthermore, the application of specific feature selection tools, such as the Wilcoxon rank-sum test method, combined with appropriate data normalization, also optimized model performance. Finally, in the algorithm selection phase, we identified ensemble learning models (eXtreme Gradient Boosting and Random Forest) as the best-performing classifiers. Conclusion: Based on the comprehensive evaluation results, we developed an optimized Microbiome-based Detection Framework (MiDx) and validated its robust generalizability on an independent dataset, offering a systematic and practical framework for future 16S and WGS-based intestinal disease detection.

Aim: Plant-derived proteins have emerged as promising alternatives to animal-based proteins, offering not only environmental and nutritional benefits to the human host but also potential effects on the gut microbiota. Yellow pea (Pisum sativum) represents an attractive source due to its balanced amino acid composition and suitability for food applications. This preliminary study was designed to evaluate the effects of two commercial pea-derived protein preparations - a wet-extracted protein isolate (PPI) and a dry-fractionated protein concentrate (PPC) - on the human gut microbiota using a dual in vitro approach. Methods: We combined monoculture assays on selected representative intestinal bacterial strains with in vitro cultivation models of stabilized microbial communities derived from human fecal samples. Results: Monoculture experiments revealed selective growth responses in certain taxa, such as Bacteroides thetaiotaomicron and Bifidobacterium spp. Moreover, in silico genomic predictions of amino acid biosynthesis and proteolytic capabilities further supported these findings, highlighting functional differences among the tested strains. Furthermore, analysis based on stabilized microbial communities revealed moderate shifts in microbial richness and composition. Notably, PPC was associated with greater variation in taxonomic profiles across samples. Both protein ingredients exhibited similar directional effects on specific taxa, including increases in the load of Bifidobacterium longum and Faecalibacterium duncaniae, and decreases in members of Bacteroides, Parabacteroides, and Phocaeicola. Conclusion: These findings indicate that pea-derived proteins, especially when used as concentrates, exert selective pressure on gut microbial communities.

The gut virome, particularly its viral and phage components, is increasingly recognized as a key modulator of intestinal microbial dynamics in gastrointestinal inflammatory diseases. Beyond well-characterized bacterial dysbiosis, growing evidence suggests that virome alterations contribute to the development and progression of inflammatory bowel disease, metabolic dysfunction-associated steatohepatitis, alcoholic hepatitis, primary sclerosing cholangitis, primary biliary cholangitis, and pancreatitis. As the most abundant viruses in the gut, bacteriophages influence microbial ecosystem stability and host immune responses through lytic and lysogenic interactions with bacterial populations. Amid the growing burden of multidrug-resistant infections and heightened interest in microbiota-based interventions, phage therapy has re-emerged as a viable strategy in both preclinical and translational contexts. This review synthesizes recent insights into bacteriophage dynamics in the context of major gastrointestinal and hepatopancreatic inflammatory diseases, highlighting potential compositional shifts, proposed mechanisms of phage-microbe interactions, and supportive evidence from animal models and early clinical applications. We also discussed the critical challenges that had to be addressed to enable clinical translation, including host range restrictions, resistance and safety concerns, immunogenicity, and delivery limitations, while emphasizing emerging strategies such as phage engineering, encapsulation technologies, and standardized regulatory frameworks.

The gastrointestinal tract is the major ecological niche in which gut microbes interact with epithelial and immune cells to maintain homeostasis in mammals. Moreover, probiotics modulate the gut microbiota and exert various health benefits after oral administration and persistence in the gut. Until now, animal models have been the gold standard for unravelling the mechanisms implicated in host-microbe interactions. However, their translational relevance to clinical trials and the associated ethical concerns underscore the need for alternative models. The emergence of microfluidic organ-on-chip technologies provides promising new alternative models to explore human host-microbe interactions while maintaining the tissue-level complexity and inter-individual variability. In this perspective, we discuss the potential of using mice, non-rodent models and gut-on-chip technologies to better characterize the interactions between the host, the gut microbiota, and orally administered probiotics, and to monitor microbial spatiotemporal dynamics at the tissue level.

Background: Aging may be associated with low-grade chronic inflammation ("inflammaging") and gut microbiome alterations. Dietary polyphenols have been proposed as modulators of these processes. This study aimed to explore the effects of a polyphenol-rich diet (PR-diet) on inflammatory markers, gut microbiota, and metabolomic profiles in subjects aged ≥ 60 years stratified by baseline inflammation levels. Methods: In this post-hoc analysis of the MaPLE (Microbiome mAnipulation through Polyphenols for managing Leakiness in the Elderly) randomized crossover trial, 50 subjects aged ≥ 60 years were categorized into two subgroups: high inflammation (cH) and low inflammation (cL). Participants received a PR-diet or a control diet for 8 weeks, with a washout period in between. Fecal, blood, and urine samples were analyzed using shallow shotgun metagenomics and untargeted metabolomics. Results: The PR-diet was associated with a significant reduction in key inflammatory markers [e.g., interleukin-6 (IL-6), C-reactive protein] in the cH group. Distinct microbial shifts were observed, including an increase in Blautia and Dorea and a modest improvement in microbial diversity in cH subjects. Metabolomic analysis revealed group-specific changes, notably in polyphenol-derived metabolites. Conclusion: These findings suggest that PR-diets may beneficially modulate inflammation and the gut microbial ecosystem in subjects aged ≥ 60 years with elevated baseline inflammation. Stratification by inflammatory status may improve the targeting and personalization of dietary interventions to support healthy aging.

B-group vitamins and vitamin K are essential micronutrients required for numerous cellular processes in both microbial and human physiology. While traditionally considered to originate predominantly from dietary sources, the biosynthetic capacity of the human gut microbiota has recently been recognized as a valuable, though historically underappreciated, endogenous source of these vitamins. In particular, the microbial contribution to the host vitamin pool is increasingly acknowledged as a functionally relevant aspect of vitamin homeostasis, especially in the colon, where microbiota-derived vitamins may be absorbed via specific transport mechanisms. This review provides a comprehensive overview of our current understanding of the biosynthesis of B-group vitamins and vitamin K by human gut-associated bacteria, with particular emphasis on key methodologies employed to assess if, how and to what extent members of the gut microbiota supply their host with such micronutrients. Through an integrated overview of available evidence, we highlight both the progress made and the outstanding challenges in elucidating the microbial contribution to the host vitamin metabolism.

Postoperative insulin resistance (PIR) is a common metabolic complication that significantly affects patient recovery and long-term outcomes. Recent studies have revealed a robust association between the gut microbiota and PIR, underscoring the potential role of microbial communities in modulating insulin sensitivity. In this comprehensive review, we synthesize current literature on the interplay between PIR and the gut microbiota, delve into the underlying mechanisms linking the two, and provide an overview of recent research progress in this field. Evidence suggests that the gut microbiota may influence PIR through mechanisms involving metabolic endotoxins, short-chain fatty acids, branched-chain amino acids, and other metabolites. Overall, the gut microbiota plays a crucial role in the onset and progression of PIR. This review aims to provide a theoretical basis for developing PIR intervention strategies based on microbiome regulation.

The rising prevalence of multidrug-resistant (MDR) bacterial infections, coupled with the diminishing efficacy of antibiotics, has reinvigorated interest in bacteriophage (phage) therapy as a promising alternative, leveraging its unique bactericidal mechanisms and precise targeting capabilities. Concurrently, phage display technology has advanced tumor diagnostics and targeted drug delivery through high-throughput peptide screening. This review systematically evaluates the mechanisms, strategies, and clinical progress of phage-based applications in anti-infective and oncological therapies. Clinical evidence highlights its efficacy against respiratory, oral, wound, bloodstream, and urinary tract infections, alongside solid tumors. However, challenges persist, including limited host range, bacterial resistance, immunogenicity, inefficient delivery systems, and regulatory uncertainties. Future efforts should prioritize AI-driven phage optimization, standardized pharmacokinetic assessment, and interdisciplinary collaboration to accelerate clinical translation. Despite current limitations, phage therapy represents a transformative and scalable approach for combating antimicrobial resistance and advancing precision oncology, positioning it as a pivotal tool in addressing global health crises.

Aim: This study aimed to screen Lactococcus lactis strains with varying gamma-aminobutyric acid (GABA) production and evaluate their effects on intestinal dysfunction and neurobehavioral abnormalities in an irritable bowel syndrome (IBS) mouse model, with a focus on GABAergic signaling and dose-dependent mechanisms. Methods: Three Lactococcus lactis strains were selected based on GABA yield and genetic analysis. IBS was induced in mice via Citrobacter rodentium infection and water avoidance stress. Intestinal integrity, inflammation, histopathology, and behavior were assessed. GABA levels in the colon and serum were measured by liquid chromatography-mass spectrometry (LC-MS). GABA receptor subunit expression in the colon, hippocampus, and amygdala was analyzed via quantitative real-time polymerase chain reaction and Western blotting. Results: GABA-producing strains alleviated intestinal dysfunction in IBS mice by reducing IL-6 gene expression and iNOS activity, upregulating CLDN2, and improving tissue integrity. Anxiety-like behaviors and cognitive deficits were also attenuated. Colonic GABA levels, GABRA13 mRNA, and GABRA3 protein expression increased in a dose-dependent manner, whereas TRPV1 mRNA and TRPV1 protein levels were downregulated. Serum GABA remained unchanged. In the central nervous system, the expression of hippocampal GABA_A and GABA_B receptors was elevated, with both GABRA13 mRNA and GABRA3 protein levels positively correlating with colonic GABA concentrations. GABRA15 expression was upregulated in the amygdala. Conclusion: GABA-producing Lactococcus lactis effectively alleviates IBS-related intestinal dysfunction and neurobehavioral abnormalities by coordinately modulating GABAergic signaling in both the gut and the central nervous system, exhibiting a clear dose-dependent effect across multiple key phenotypes.