Literature DB >> 32617663

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

Lin-Lin Wang1,2, Fu-Yuan Zhang1,2, Wen-Wen Dong1, Chang-Liang Wang2,3, Xue-Ying Liang4, Long-Long Suo1, Miao Zhang1,2, Xiang-Shen Guo1, Peng-Hao Jiang1, Da-Wei Guan5,6, Rui Zhao7,8.   

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.

Entities:  

Keywords:  Drowning diagnosis; Forensic medicine; Forensic microbiology; NGS; PCoA

Year:  2020        PMID: 32617663     DOI: 10.1007/s00414-020-02358-1

Source DB:  PubMed          Journal:  Int J Legal Med        ISSN: 0937-9827            Impact factor:   2.686


  4 in total

1.  Next-Generation Sequencing Results Vary Between Cultured and Uncultured Microbes.

Authors:  Hee Sang You; Song Hee Lee; Young Ju Lee; Han Lee; Sang Sun Kang; Sung Hee Hyun
Journal:  Curr Microbiol       Date:  2022-05-07       Impact factor: 2.188

2.  A preliminary study on early postmortem submersion interval (PMSI) estimation and cause-of-death discrimination based on nontargeted metabolomics and machine learning algorithms.

Authors:  Fu-Yuan Zhang; Lin-Lin Wang; Wen-Wen Dong; Miao Zhang; Dilichati Tash; Xin-Jie Li; Shu-Kui Du; Hao-Miao Yuan; Rui Zhao; Da-Wei Guan
Journal:  Int J Legal Med       Date:  2022-01-31       Impact factor: 2.686

3.  Epidemiological Analysis of Drowning Deaths Among Different Groups in Jordan - a Retrospective Study (2015-2019).

Authors:  Ali M Shotar; Mahmoud Halalsheh; Rashed Shatnawi; Hadeel Abu-El-Rub; Nahd A Hussein; Sarah Shoter; Hassan Mahafdhah
Journal:  Med Arch       Date:  2022-02

Review 4.  Advances in artificial intelligence-based microbiome for PMI estimation.

Authors:  Ziwei Wang; Fuyuan Zhang; Linlin Wang; Huiya Yuan; Dawei Guan; Rui Zhao
Journal:  Front Microbiol       Date:  2022-10-04       Impact factor: 6.064

  4 in total

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