Polygonatum sibiricum polysaccharide ameliorates intestinal barrier dysfunction in aging mice via gut microbiota-metabolite modulation and TLR4/NF-κB pathway inhibition

This dataset comprises gut microbiota 16S rRNA gene sequencing data and untargeted fecal metabolomics data generated from a mouse model of natural aging to investigate the effects of Polygonatum sibiricum polysaccharides (PSP) on age-associated intestinal microbial composition and metabolic profiles.
Naturally aged C57BL/6 mice were maintained until 16 months of age and then randomly assigned to four experimental groups: an aged control group, a low-dose PSP treatment group (PSP-L, 200 mg/kg/day), a high-dose PSP treatment group (PSP-H, 400 mg/kg/day), and a positive drug control group treated with diosgenin (DG, 90 mg/kg/day). An additional group of 8-week-old mice served as the young control group. All treatments were administered by oral gavage once daily for 8 consecutive weeks. Fecal samples were collected at the end of the intervention period for microbiome and metabolomic analyses. All experimental procedures were conducted under randomized and blinded conditions.
Gut microbiota profiles were characterized by high-throughput sequencing of the V3–V4 hypervariable regions of the bacterial 16S rRNA gene using the Illumina NovaSeq 6000 platform with paired-end sequencing (2 × 250 bp). Raw sequencing reads were quality-filtered and clustered into operational taxonomic units (OTUs) at 97% sequence similarity. Taxonomic annotation was performed using the SILVA V138.1 reference database. The resulting dataset enables downstream analyses of microbial community structure, alpha and beta diversity, and differential taxonomic abundance among treatment groups.
Untargeted fecal metabolomic data were acquired using ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) in both positive and negative electrospray ionization modes. Metabolomic profiling captures a broad spectrum of endogenous metabolites related to host metabolism and microbial activity. Raw LC-MS data were processed for peak detection, alignment, normalization, and metabolite annotation based on public databases, including METLIN and HMDB.