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Integrating the salivary microbiome in the forensic toolkit by 16S rRNA gene: potential application in body fluid identification and biogeographic inference

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Abstract

Saliva is a common body fluid with significant forensic value used to investigate criminal cases such as murder and assault. In the past, saliva identification often relied on the α-amylase test; however, this method has low specificity and is prone to false positives. Accordingly, forensic researchers have been working to find new specific molecular markers to refine the current saliva identification approach. At present, research on immunological methods, mRNA, microRNA, circRNA, and DNA methylation is still in the exploratory stage, and the application of these markers still has various limitations. It has been established that salivary microorganisms exhibit good specificity and stability. In this study, 16S rDNA sequencing technology was used to sequence the V3-V4 hypervariable regions in saliva samples from five regions to reveal the role of regional location on the heterogeneity in microbial profile information in saliva. Although the relative abundance of salivary flora was affected to a certain extent by geographical factors, the salivary flora of each sample was still dominated by Streptococcus, Neisseria, and Rothia. In addition, the microbial community in the saliva samples in this study was significantly different from that in the vaginal secretions, semen, and skin samples reported in our previous studies. Accordingly, saliva can be distinguished from the other three body fluids and tissues. Moreover, we established a prediction model based on the random forest algorithm that could distinguish saliva between different regions at the genus level even though the model has a certain probability of misjudgment which needs more in-depth research. Overall, the microbial community information in saliva stains might have prospects for potential application in body fluid identification and biogeographic inference.

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Acknowledgements

We are grateful to all volunteers who contributed samples for this study.

Funding

This study was supported by the Natural Science Foundation of Guangdong Province (Grant No. 2020A1515010938), the Science and Technology Program of Guangzhou, China (Grant No. 2019030016), and the Opening Fund of Shanghai Key Laboratory of Forensic Medicine (Institute of Forensic Science, Ministry of Justice, China) (Grant No. KF1914).

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Author notes

  1. Xiaomin Liang, Xiaolong Han, and Changhui Liu contributed equally to this work.

Authors and Affiliations

  1. Multi-Omics Innovative Research Center of Forensic Identification, Department of Forensic Genetics, School of Forensic Medicine, Southern Medical University, Guangzhou, 510515, People’s Republic of China

    Xiaomin Liang, Weian Du, Peiwen Zhong, Litao Huang, Manling Huang, Linhe Fu, Chao Liu & Ling Chen

  2. Guangzhou Forensic Science Institute, Guangzhou, 510030, People’s Republic of China

    Xiaolong Han, Changhui Liu & Chao Liu

Authors
  1. Xiaomin Liang
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  2. Xiaolong Han
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  4. Weian Du
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  7. Manling Huang
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  9. Chao Liu
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  10. Ling Chen
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Corresponding authors

Correspondence to Chao Liu or Ling Chen.

Ethics declarations

The project was approved by the Ethics Committee of Southern Medical University (No. 2019–0011), and it was carried out in strict accordance with the ethical research principle of Southern Medical University.

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The authors declare no competing interests.

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Liang, X., Han, X., Liu, C. et al. Integrating the salivary microbiome in the forensic toolkit by 16S rRNA gene: potential application in body fluid identification and biogeographic inference. Int J Legal Med 136, 975–985 (2022). https://doi.org/10.1007/s00414-022-02831-z

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  • DOI: https://doi.org/10.1007/s00414-022-02831-z

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