Abstract
BACKGROUND & AIMS: Limited understanding exists regarding the characteristics and biological significance of the salivary microbiome in healthy individuals experiencing physiological fatigue. This study aimed to delineate the structural and functional alterations in the salivary microbiome of healthy individuals undergoing physiological fatigue compared to energetic controls, and to explore its potential as a biomarker for fatigue status. METHODS: A cohort of 7 healthy individuals experiencing acute physiological fatigue (induced by prolonged study and confirmed via electroencephalography; Fatigue group, FTG) and 63 energetic healthy controls (Energetic group, ENG) were enrolled. Saliva samples were collected, from which microbial DNA was extracted. The V3-V4 hypervariable region of the 16S rRNA gene was subsequently sequenced using high-throughput technology. Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. Microbial community phenotypes and potential functional pathways were predicted using BugBase and PICRUSt2, respectively. RESULTS: The FTG group exhibited significantly diminished alpha diversity (Simpson index, p=0.01071) relative to the ENG group. Beta diversity analysis demonstrated significant dissimilarities in microbial community structure between the groups (p<0.05). Taxonomic profiling revealed a significant enrichment in the relative abundance of potential periodontopathogenic genera, including Streptococcus and Filifactor, within the FTG group, concomitantly with a significant depletion of health-associated genera such as Rothia and Neisseria. A predictive model constructed using the Boruta-SHAP algorithm, based on 15 key genera, effectively discriminated between fatigue and non-fatigue states, achieving an area under the receiver operating characteristic curve (AUC) of 0.948. Phenotypic predictions indicated a significant increase in the proportion of bacteria harboring Mobile Genetic Elements (MGEs) (p=0.048), alongside significant reductions in the proportion of aerobic bacteria (p=0.006) and biofilm-forming capacity (p=0.002) in the FTG group. Functional pathway analysis (PICRUSt2) revealed an enrichment of pathways such as "Neuroactive ligand-receptor interaction" in the FTG group, whereas pathways pertinent to energy metabolism (e.g., Citrate cycle (TCA cycle), Oxidative phosphorylation) and amino acid metabolism (e.g., Phenylalanine metabolism, Histidine metabolism) were significantly enriched in the ENG group. CONCLUSION: This study provides novel evidence that physiological fatigue induces significant structural and functional alterations in the salivary microbiome of healthy individuals. These perturbations include diminished microbial diversity, disrupted community architecture, enrichment of potential opportunistic pathogens, and marked shifts in key metabolic pathways, particularly those governing neuroactivity and energy metabolism. These findings suggest that the salivary microbiome may be implicated in the physiological regulation of fatigue, potentially via an "oral-microbiome-brain axis," and underscore its potential as a source of non-invasive biomarkers for assessing fatigue status. Further mechanistic investigations are warranted to elucidate these interactions.