Research Progress on Microbial Community Succession in the Postmortem Interval Estimation.

Qing-qing Xiang; Li-fang Chen; Qin SU; Yu-kun DU; Pei-yan Liang; Xiao-dong Kang; He Shi; Qu-yi XU; Jian Zhao; Chao Liu; Xiao-hui Chen

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Research Progress on Microbial Community Succession in the Postmortem Interval Estimation.

Author: Qing-Qing XIANG ¹ ; Li-Fang CHEN ¹ ; Qin SU ² ; Yu-Kun DU ³ ; Pei-Yan LIANG ² ; Xiao-Dong KANG ² ; He SHI ² ; Qu-Yi XU ² ; Jian ZHAO ² ; Chao LIU ² ; Xiao-Hui CHEN ²
Author Information

1. College of Forensic Medicine, Kunming Medical University, Kunming 650500, China.
2. Key Laboratory of Forensic Pathology, Ministry of Public Security, Guangzhou Forensic Science Institute, Guangzhou 510442, China.
3. School of Forensic Medicine, Southern Medical University, Guangzhou 510515, China.
Publication Type:Journal Article
Keywords: forensic pathology; high-throughput sequencing; machine learning; microbial community; microbiomics; postmortem interval estimation; review
MeSH: Humans; Postmortem Changes; Artificial Intelligence; Autopsy; Cadaver; Microbiota
From: Journal of Forensic Medicine 2023;39(4):399-405
CountryChina
Language:English
Abstract: The postmortem interval (PMI) estimation is a key and difficult point in the practice of forensic medicine, and forensic scientists at home and abroad have been searching for objective, quantifiable and accurate methods of PMI estimation. With the development and combination of high-throughput sequencing technology and artificial intelligence technology, the establishment of PMI model based on the succession of the microbial community on corpses has become a research focus in the field of forensic medicine. This paper reviews the technical methods, research applications and influencing factors of microbial community in PMI estimation explored by using high-throughput sequencing technology, to provide a reference for the related research on the use of microbial community to estimate PMI.