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Huang L, Liang X, Xiao G, Du J, Ye L, Su Q, Liu C, Chen L. Response of salivary microbiome to temporal, environmental, and surface characteristics under in vitro exposure. Forensic Sci Int Genet 2024; 70:103020. [PMID: 38286081 DOI: 10.1016/j.fsigen.2024.103020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 12/22/2023] [Accepted: 01/21/2024] [Indexed: 01/31/2024]
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.
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Affiliation(s)
- Litao Huang
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Xiaomin Liang
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Guichao Xiao
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Jieyu Du
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Linying Ye
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Qin Su
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China
| | - Chao Liu
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China; National Anti-Drug Laboratory Guangdong Regional Center, Guangzhou, China.
| | - Ling Chen
- Guangzhou Key Laboratory of Forensic Multi-Omics for Precision Identification, School of Forensic Medicine, Southern Medical University, Guangzhou, Guangdong 510515, China.
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Perspectives on Inequity and Health Disparities in Chile and Their Relationship to Microbial Ecology. mSystems 2022; 7:e0149621. [PMID: 36173132 PMCID: PMC9600356 DOI: 10.1128/msystems.01496-21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022] Open
Abstract
Among countries in the Organisation for Economic Cooperation and Development (OECD), Chile stands out as having important inequalities in income distribution, dietary quality, access to urban green spaces, and health outcomes. People in lower socioeconomic groups consistently show higher rates of noncommunicable chronic diseases and are being hit the hardest by the COVID-19 pandemic. These chronic conditions are increasingly considered to be shaped, or affected by, the human gut microbiome. Moreover, inequity as an overarching concept might also be associated with microbial patterns and if so, this may represent a novel pathway through which to address health and other disparities. Focusing on the case of Chile, our goal is to contribute to a critical discussion and motivate researchers and policymakers to consider the role of the microbiome in social equity in future endeavors.
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