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1.
Microbiol Spectr ; : e0012524, 2024 Jul 09.
Article in English | MEDLINE | ID: mdl-38980015

ABSTRACT

Semen is one of the common body fluids in sexual crime cases. The current methods of semen identification have certain limitations, so it is necessary to search for other methods. In addition, there are few reports of microbiome changes in body fluids under simulated crime scenes. It is essential to further reveal the changes in semen microbiomes after exposure to various simulated crime scenes. Semen samples from eight volunteers were exposed in closed plastic bags, soil, indoor, cotton, polyester, and wool fabrics. A total of 68 samples (before and after exposure) were collected, detected by 16S rDNA sequencing, and analyzed for the microbiome signature. Finally, a random forest model was constructed for body fluid identification. After exposure, the relative abundance of Pseudomonas and Rhodococcus changed dramatically in almost all groups. In addition, the treatment with the closed plastic bags or soil groups had a greater impact on the semen microbiome. According to the Shannon indices, the alpha diversity of the closed plastic bags and soil groups was much lower than that of the other groups. Attention should be given to the above two scenes in practical work of forensic medicine. In this study, the accuracy of semen recognition was 100%. The exposed semen can still be correctly identified as semen based on its microbiota characteristics. In summary, semen microbiomes exposed to simulated crime scenes still have good application potential for body fluid identification. IMPORTANCE: In this study, the microbiome changes of semen exposed to different environments were observed, and the exposed semen microbiome still has a good application potential in body fluid identification.

2.
Forensic Sci Int Genet ; 70: 103020, 2024 May.
Article in English | MEDLINE | ID: mdl-38286081

ABSTRACT

The microbiome of saliva stains deposited at crime scenes and in everyday settings is valuable for forensic investigations and environmental ecology. However, the dynamics and applications of microbial communities in these saliva stains have not been fully explored. In this study, we analyzed saliva samples that were exposed to indoor conditions for up to 1 year and to different carriers (cotton, sterile absorbent cotton swab, woolen, dacron) in both indoor and outdoor environments for 1 month using high-throughput sequencing. The analysis of microbial composition and Mfuzz clustering showed that the salivary flora, specifically Streptococcus (cluster7), which was associated with microbial contamination, remained stable over short periods of time. However, prolonged exposure led to significant differences due to the invasion of environmental bacteria such as Pseudomonas and Achromobacter. The growth and colonization of environmental flora were promoted by humidity. The neutral model predictions indicated that the assembly of salivary microbial communities in outdoor environments was significantly influenced by stochastic processes, with environmental characteristics having a greater impact on community change compared to surface characteristics. By incorporating data from previous studies on fecal and vaginal secretion microbiology, we developed RF and XGBoost classification models that achieved high accuracy (>98 %) and AUC (>0.8). Additionally, a RF regression model was created to determine the time since deposition (TsD) of the stains. Time inference models yielded a mean absolute error (MAE) of 7.1 days for stains exposed for 1 year and 14.2 h for stains exposed for 14 days. These findings enhance our understanding of the changes in the microbiome of saliva stains over time, in different environments, and on different surfaces. They also have potential applications in assessing potential microbial contamination, identifying body fluids, and inferring the time of deposition.


Subject(s)
Body Fluids , Microbiota , Humans , Female , Saliva/microbiology , Humidity , Bacteria/genetics
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