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Erschienen in: International Journal of Legal Medicine 6/2020

02.07.2020 | Original Article

A novel approach for the forensic diagnosis of drowning by microbiological analysis with next-generation sequencing and unweighted UniFrac-based PCoA

verfasst von: Lin-Lin Wang, Fu-Yuan Zhang, Wen-Wen Dong, Chang-Liang Wang, Xue-Ying Liang, Long-Long Suo, Jian Cheng, Miao Zhang, Xiang-Shen Guo, Peng-Hao Jiang, Da-Wei Guan, Rui Zhao

Erschienen in: International Journal of Legal Medicine | Ausgabe 6/2020

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Abstract

The diagnosis of drowning is one of the major challenges in forensic practice, especially when the corpse is in a state of decomposition. Novel indicators of drowning are desired in the field of forensic medicine. In the past decade, aquatic bacteria have attracted great attention from forensic experts because they can easily enter the blood circulation with drowning medium, and some of them can proliferate in the corpse. Recently, the advent of next-generation sequencing (NGS) has created new opportunities to efficiently analyze whole microbial communities and has catalyzed the development of forensic microbiology. We presumed that NGS could be a potential method for diagnosing drowning. In the present study, we verified this hypothesis by fundamental experiments in drowned and postmortem-submersed rat models. Our study revealed that detecting the bacterial communities with NGS and processing the data in a transparent way with unweighted UniFrac-based principal coordinates analysis (PCoA) could clearly discriminate the skin, lung, blood, and liver specimens of the drowning group and postmortem submersion group. Furthermore, the acquired information could be used to identify new cases. Taken together, these results suggest that we could build a microbial database of drowned and postmortem-submersed victims by NGS and subsequently use a bioinformatic method to diagnose drowning in future forensic practice.
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Metadaten
Titel
A novel approach for the forensic diagnosis of drowning by microbiological analysis with next-generation sequencing and unweighted UniFrac-based PCoA
verfasst von
Lin-Lin Wang
Fu-Yuan Zhang
Wen-Wen Dong
Chang-Liang Wang
Xue-Ying Liang
Long-Long Suo
Jian Cheng
Miao Zhang
Xiang-Shen Guo
Peng-Hao Jiang
Da-Wei Guan
Rui Zhao
Publikationsdatum
02.07.2020
Verlag
Springer Berlin Heidelberg
Erschienen in
International Journal of Legal Medicine / Ausgabe 6/2020
Print ISSN: 0937-9827
Elektronische ISSN: 1437-1596
DOI
https://doi.org/10.1007/s00414-020-02358-1

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