Individual identification and time since deposition estimation based on community structure and absolute abundance of the exposed vaginal microbiome.

Vaginal secretions are crucial forensic evidence in sexual assault cases, and accurate identification of the individual source and estimation of the time since deposition (TsD) are essential for case investigation. There are obvious challenges in human genetic markers, especially for trace and degraded low-quality forensic samples. Microbiomes possess high quantity, distinct individual specificity, and temporal succession, showing potential for forensic traceability and TsD estimation. In this study, vaginal swabs were exposed to a constant temperature environment for 90 days across 13 sampling time points. The dynamic changes in the vaginal microbiome were analyzed using high-throughput absolute quantitative sequencing. The results showed that while the overall community structure remained relatively stable after exposure, the ASV composition exhibited significant individual specificity. Furthermore, the absolute abundance of microorganisms decreased over time, demonstrating a clear time-dependent pattern. Based on these characteristics, a Random Forest model was constructed to accurately identify the individual source of the samples. Additionally, a Support Vector Regression (SVR) model, built upon the dynamics of microbial load, effectively estimated the TsD, achieving an MAE of 8.01 days (R² = 0.859). In conclusion, this study clarifies the dynamic evolutionary characteristics of community structure and biomass of vaginal microorganisms after environmental exposure, providing theoretical basis and analytical strategies for the practical forensic application of vaginal secretion samples.