With the abuse of antibiotics, bacterial antibiotic resistance is becoming a major public healthcare issue. Natural plants, especially traditional Chinese herbal medicines, which have antibacterial activity, are important sources for discovering potential bacteriostatic agents. This study aimed to develop a fast and reliable method for screening out antimicrobial compounds targeting the MRSA membrane from Psoralea corylifolia Linn. seed. A UPLC-MS/MS method was applied to identify the prenylated flavonoids in major fractions from the extracts of Psoralea corylifolia Linn. seed. The broth microdilution method was used to determine the minimum inhibitory concentrations (MICs) of different fractions and compounds. The morphological and ultrastructural changes of MRSA were determined by scanning electron microscopy (SEM). The membrane-targeting mechanism of the active ingredients was explored by membrane integrity assays, membrane fluidity assays, membrane potential assays, ATP, and ROS determination. We identified eight prenylated flavonoids in Psoralea corylifolia Linn. seed. The antibacterial activity and mechanism studies showed that this type of compound has a unique destructive effect on MRSA cell membranes and does not result in drug resistance. The results revealed that prenylated flavonoids in Psoralea corylifolia Linn. seeds are promising candidates for the development of novel antibiotic agents to combat MRSA-associated infections.

Background: The fecal microbiota is closely coupled to host metabolism and nutritional physiology in ruminants, but longitudinal biochemical variation across defined sika deer developmental sampling stages remains incompletely characterized. We therefore integrated microbiome, metabolomic, short-chain fatty acid (SCFA), and Raman spectroscopic measurements to describe stage-associated fecal changes. Methods: Fecal specimens were collected from male sika deer at two predefined antler-cycle stages, the rapid antler-growth stage (G; 1 March 2024) and the mature/ossification stage (M; 28 June 2024), 119 days apart. Eight animals were followed longitudinally and contributed matched specimens at both stages; two additional single-time-point specimens per stage were included, so that 16S rRNA gene sequencing, untargeted metabolomics, and SCFA quantification comprised 10 specimens per stage (n = 20), whereas Raman spectroscopy comprised the eight matched pairs (n = 16). The animal was treated as the biological unit: 16S, metabolomic, and SCFA comparisons used independent-sample tests on the 10 specimens per stage, and Raman comparisons used paired procedures on the eight matched animals, each with multiplicity correction. For Raman classification, technical spectra were averaged within each specimen and validation was structured by deer so that both stage specimens from the held-out animal were excluded from model training. Results: The two sampling stages differed in fecal microbial composition and biochemical profiles. Alpha-diversity indices did not differ significantly (all FDR-adjusted q ≥ 0.220), but genus-level analysis with FDR correction identified three differentially abundant genera (q < 0.05): UCG-005 and UCG-010 were more abundant at the G stage, and Treponema was more abundant at the M stage. Fecal butyrate was higher at the M stage (p = 0.0065, Bonferroni-adjusted p = 0.019), whereas valerate and caproate were higher at the G stage (adjusted p = 0.029 and 0.0002, respectively). Untargeted metabolomics identified 5621 differential features across the two electrospray ionization modes (|log2 fold change| ≥ 2 and p < 0.01; positive-ion features additionally selected at PLS-DA VIP ≥ 1.0), of which 2311 were increased and 3310 were decreased at the M stage relative to G, with no evidence of PLS-DA overfitting (permutation R²Y-intercept = 0.318, Q²-intercept = −0.237). Raman spectra showed stage-associated variation, with seven candidate bands showing FDR-adjusted differences (q = 0.007–0.028). A leakage-controlled classifier evaluated by grouped leave-one-deer-out cross-validation achieved an AUC of 0.875 (deer-level 95% CI 0.69–0.98; paired-label permutation p = 0.023). Conclusions: This exploratory longitudinal study identifies stage-associated variation in fecal microbial, metabolomic, SCFA, and Raman profiles in sika deer. The findings are associative rather than mechanistic because the cohort was small and developmental stage was not separated from season. Raman spectroscopy may provide complementary non-invasive biochemical phenotyping, but the classification result requires confirmation in a larger independent cohort before practical use.