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PubMed2026

Alleviation of allergic rhinitis symptoms in an animal model by Lactiplantibacillus plantarum BGI-N6.

Allergic rhinitis (AR) is a chronic inflammatory disease with rising global prevalence and a substantial public health burden. Current treatments have limited efficacy and tolerability, highlighting the need for new strategies. Probiotics represent a promising approach due to their ability to modulate gut microbiota and host immunity. Here, we investigated the preventive potential of Lactiplantibacillus plantarum BGI-N6 in an OVA/ALUM-induced AR rat model. BGI-N6 administration alleviated AR symptoms and nasal mucosal pathology, reduced key allergic mediators, shifted serum immunoglobulin and cytokine levels toward normal, and restored the Th1/Th2/Th17/Treg balance. Metagenomic sequencing of cecal contents showed that these effects were accompanied by expansion of Bacteroidota-affiliated SCFA-producing taxa, restoration of microbial functional capacity, and identification of 41 core functional genes (KEGG Orthologues) consistently shifted across all three dose groups, with Bacteroides showing the strongest enrichment. Correlation analyses further connected these microbial shifts with immune parameters. These findings support BGI-N6 as a probiotic intervention for AR and implicate gut microbiota remodeling as a central correlate of probiotic-induced immunomodulation.

Animals↗

PubMed2026

Associations between gut microbiota on carcass traits and meat quality in Neijiang pigs, Yorkshire pigs, and their hybrids.

This study was designed as an exploratory analysis to compare carcass performance, meat quality traits, and gut microbiota of Neijiang pigs (NN), Yorkshire pigs (YY), and Yorkshire × Neijiang hybrid pigs (YN), with the goal of generating testable hypotheses regarding potential links between gut microbial composition and production phenotypes. Compared with NN pigs, YN hybrids exhibited improved carcass performance while inheriting the favorable meat quality characteristics of Neijiang pigs. The results of 16S rRNA sequencing analysis showed that the relative abundance of the microbiota was similar to that of NN pigs. LDA effect size (LEfSe) results showed that Streptococcus, Treponema, probable_genus_10 and Fibrobacter were the differentially enriched taxa in YN pigs (p < 0.05). Correlation analysis was performed on carcass, meat quality and intestinal microbiota screened out by LEfSe. The results showed that Akkermansia tended to positively associate with body length and oblique length in YN pigs; Dialister correlated positively with dressing rate and pH45min; Treponema showed positive trends with a*45min and a*24h (p < 0.05). Finally, the correlation network model preliminarily mapped associations among production traits, gut microbiota, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways for exploratory screening. Nine core microbial taxa exhibited close correlations with phenotypic indicators, which implied that these microbes might modulate metabolic pathways to shape pig performance. Overall, hybrids inherited superior parental carcass and meat quality but harbored unique gut microbial communities relative to purebreds-these preliminary correlative observations generate new hypotheses that gut microbiota may contribute to heterosis-associated phenotypic advantages, which require further targeted validation.

Animals↗

PubMed2026

Natural products alleviate exercise-induced fatigue by modulating gut microbiota: a systematic review.

BACKGROUND: Exercise-induced fatigue critically impairs athletic performance and training quality. The gut microbiota, as a key regulator of the "gut-muscle axis," has emerged as a promising anti-fatigue target. Natural products - owing to their diverse sources, structural complexity, and favorable safety profiles - have attracted growing research interest. However, a systematic synthesis comparing their anti-fatigue effects via gut microbiota modulation across different sources is lacking. SCOPE AND APPROACH: We systematically searched PubMed, Web of Science, the Cochrane Library, and CNKI for original studies that administered natural products and concurrently assessed gut microbiota changes and anti-fatigue outcomes. Twenty-six studies (25 animal experiments and 1 human trial) were included and categorized into seven groups by source and chemical characteristics. A descriptive systematic review was conducted to identify common mechanisms and source-specific differentiations. KEY FINDINGS AND CONCLUSIONS: The enrichment of short-chain fatty acid (SCFA)-producing bacteria and the activation of the SCFA-AMPK/PGC-1α axis were shared core events across all product categories. However, source-dependent mechanistic divergences emerged: polysaccharides acted primarily as fermentable substrates with an optimal dose window; polyphenols and saponins exerted dual modulation on both microbiota and host signaling pathways; compound extracts achieved systemic synergy through functional complementation; marine- and animal-derived products exhibited unique targeting profiles and rapid action. Intestinal barrier maintenance and brain-gut axis regulation further extended the anti-fatigue repertoire. Collectively, natural products possess a solid mechanistic basis for alleviating exercise-induced fatigue via gut microbiota remodeling. The differentiated characteristics of these methods in targeting precision and pathway engagement provide a theoretical foundation for designing precision intervention strategies tailored to specific fatigue contexts.

Humans↗

PubMed2024

Pangenomes of human gut microbiota uncover links between genetic diversity and stress response.

The genetic diversity of the gut microbiota has a central role in host health. Here, we created pangenomes for 728 human gut prokaryotic species, quadrupling the genes of strain-specific genomes. Each of these species has a core set of a thousand genes, differing even between closely related species, and an accessory set of genes unique to the different strains. Functional analysis shows high strain variability associates with sporulation, whereas low variability is linked with antibiotic resistance. We further map the antibiotic resistome across the human gut population and find 237 cases of extreme resistance even to last-resort antibiotics, with a predominance among Enterobacteriaceae. Lastly, the presence of specific genes in the microbiota relates to host age and sex. Our study underscores the genetic complexity of the human gut microbiota, emphasizing its significant implications for host health. The pangenomes and antibiotic resistance map constitute a valuable resource for further research.

Humans↗

PubMed2026

Gut microbiota-derived metabolites target C5AR1/KDM2A/HCAR3 axis in inflammatory bowel disease: a multi-machine learning algorithms and molecular docking study.

BACKGROUND: Inflammatory bowel disease (IBD) is a chronic recurrent disorder. Gut microbiota-derived metabolites regulate intestinal homeostasis, but their molecular mechanisms in IBD remain unclear. Current studies lack systematic "microbiota-metabolite-target" network mining with multi-method validation. This study integrates network pharmacology, three machine learning algorithms, and molecular docking to construct this regulatory network in IBD. METHODS: Transcriptome data were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using limma (p < 0.05, |log2FC| > 0.5). Weighted gene co-expression network analysis (WGCNA) with an optimal soft threshold of β = 7 was performed to identify key module genes. Candidate genes were obtained by intersecting DEGs, gut microbiota-associated genes from the gutMGene database, and WGCNA module genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted to explore the functional roles of candidate genes. Core genes were identified using three machine learning algorithms (LASSO, Boruta, and SVM-RFE), followed by protein-protein interaction (PPI) network analysis. Molecular docking was performed to assess the binding affinities between hub proteins and gut microbiota-derived metabolites. RESULTS: A total of 885 DEGs were identified between the IBD and control groups, including 463 upregulated and 422 downregulated genes. WGCNA identified 280 key module genes from the purple and yellow modules. The intersection of DEGs, gut microbiota-associated genes, and WGCNA module genes yielded 19 core candidate genes. PPI network analysis combined with three machine learning algorithms jointly identified C5AR1, KDM2A, and HCAR3 as core hub genes. ROC curve analysis demonstrated that all three hub genes achieved AUC values greater than 0.7 in both the training and validation sets, indicating excellent diagnostic performance for IBD. Enrichment analysis revealed significant associations with the TNF, NF-κB, and IL-17 signaling pathways. Molecular docking confirmed stable binding of C5AR1 with 1,3-Diphenylpropan-2-Ol (-7.87 ± 0.83 kcal·mol-¹) and HCAR3 with 3-Indolepropionic Acid (-6.35 ± 0.70 kcal·mol-¹), both below -5.0 kcal·mol-¹. CONCLUSION: This study first constructs a "gut microbiota-metabolite-hub gene" axis in IBD, providing a computational framework for microbiota-targeted precision therapy, and identifying C5AR1/KDM2A/HCAR3 as computationally predicted diagnostic biomarkers and 1,3-Diphenylpropan-2-Ol/3-Indolepropionic Acid as candidate intervention molecules that warrant further experimental validation.

Molecular Docking Simulation↗

PubMed2026

Comparison of clinical efficacy and gut microbiota characteristics in children with ASD treated with fecal microbiota transplantation and ketogenic diet.

OBJECTIVE: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by impairments in social communication and interaction, along with restricted, repetitive patterns of behavior. It is often accompanied by gastrointestinal dysfunction and gut microbiota dysbiosis. Fecal Microbiota Transplantation (FMT) and the Ketogenic Diet (KD) are interventions targeting the gut microbiota for ASD. METHODS: 30 participants were diagnosed with ASD according to DSM-5 and ADOS-2. ASD core symptoms were evaluated with CARS and ABC. Gut microbiota composition was analyzed by shotgun metagenomic sequencing. RESULTS: Both groups demonstrated significant improvements in core symptoms. In the FMT group, the mean CARS score significantly decreased from 34.87 to 33.53 (p < 0.01); in the KD group, it declined from 35.13 to 33 (p < 0.01). The mean ABC score reduced from 79.93 to 69.33 (p = 0.064) in the FMT group and from 63.07 to 42.73 (p < 0.01) in the KD group. Following the intervention, no statistically significant changes were observed in α-diversity or β-diversity within either group. LEfSe analysis revealed distinct post-intervention microbial signatures: FMT significantly enriched butyrate-producing taxa (Wujia chipingensis, Eubacterium sp. MSJ-33, and Butyrivibrio crossotus), while KD elevated Blautia massiliensis and decreased propionate metabolism -associated taxa (Veillonella sp. S12025-13 and Veillonella nakazawae). KEGG enrichment analysis revealed that KD enriched propionate metabolism (Fold enrichment = 3.747, q = 0.010) and aromatic compound degradation (Fold enrichment = 3.591, q = 0.010). CONCLUSIONS: Both interventions significantly improved clinical symptoms among children with ASD, potentially through distinct patterns of gut microbiota modulation. CLINICAL TRIALS NUMBER: NCT06348433 (03/21/2024).

Child↗