AUTHOR=Wang Linlin , Zhang Fuyuan , Zeng Kuo , Dong Wenwen , Yuan Huiya , Wang Ziwei , Liu Jin , Pan Jiaqing , Zhao Rui , Guan Dawei TITLE=Microbial communities in the liver and brain are informative for postmortem submersion interval estimation in the late phase of decomposition: A study in mouse cadavers recovered from freshwater JOURNAL=Frontiers in Microbiology VOLUME=13 YEAR=2022 URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2022.1052808 DOI=10.3389/fmicb.2022.1052808 ISSN=1664-302X ABSTRACT=Introduction

Bodies recovered from water, especially in the late phase of decomposition, pose difficulties to the investigating authorities. Various methods have been proposed for postmortem submersion interval (PMSI) estimation and drowning identification, but some limitations remain. Many recent studies have proved the value of microbiota succession in viscera for postmortem interval estimation. Nevertheless, the visceral microbiota succession and its application for PMSI estimation and drowning identification require further investigation.

Methods

In the current study, mouse drowning and CO2 asphyxia models were developed, and cadavers were immersed in freshwater for 0 to 14 days. Microbial communities in the liver and brain were characterized via 16S rDNA high-throughput sequencing.

Results

Only livers and brains collected from 5 to 14 days postmortem were qualified for sequencing. There was significant variation between microbiota from liver and brain. Differences in microbiota between the cadavers of mice that had drowned and those only subjected to postmortem submersion decreased over the PMSI. Significant successions in microbial communities were observed among the different subgroups within the late phase of the PMSI in livers and brains. Eighteen taxa in the liver which were mainly related to Clostridium_sensu_stricto and Aeromonas, and 26 taxa in the brain which were mainly belonged to Clostridium_sensu_stricto, Acetobacteroides, and Limnochorda, were selected as potential biomarkers for PMSI estimation based on a random forest algorithm. The PMSI estimation models established yielded accurate prediction results with mean absolute errors ± the standard error of 1.282 ± 0.189 d for the liver and 0.989 ± 0.237 d for the brain.

Conclusions

The present study provides novel information on visceral postmortem microbiota succession in corpses submerged in freshwater which sheds new light on PMSI estimation based on the liver and brain in forensic practice.