4.7 Article

Potential use of molecular and structural characterization of the gut bacterial community for postmortem interval estimation in Sprague Dawley rats

Journal

SCIENTIFIC REPORTS
Volume 11, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-020-80633-2

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Funding

  1. National Natural Sciences Foundation of China [81730056]

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This study investigated the changes in rectal microbiota composition at different time intervals after death, revealing significant shifts in microbial communities and identifying bacterial taxa crucial for estimating postmortem interval. The analysis found that the genus level provided the most information for estimating the time since death, and a prediction model using genus-level data from high-throughput sequencing was constructed, showing potential for estimating the shortest time since death.
Once the body dies, the indigenous microbes of the host begin to break down the body from the inside and play a key role thereafter. This study aimed to investigate the probable shift in the composition of the rectal microbiota at different time intervals up to 15 days after death and to explore bacterial taxa important for estimating the time since death. At the phylum level, Proteobacteria and Firmicutes showed major shifts when checked at 11 different intervals and emerged at most of the postmortem intervals. At the species level, Enterococcus faecalis and Proteus mirabilis showed a downward and upward trend, respectively, after day 5 postmortem. The phylum-, family-, genus-, and species-taxon richness decreased initially and then increased considerably. The turning point occurred on day 9, when the genus, rather than the phylum, family, or species, provided the most information for estimating the time since death. We constructed a prediction model using genus-level data from high-throughput sequencing, and seven bacterial taxa, namely, Enterococcus, Proteus, Lactobacillus, unidentified Clostridiales, Vagococcus, unidentified Corynebacteriaceae, and unidentified Enterobacteriaceae, were included in this model. The abovementioned bacteria showed potential for estimating the shortest time since death.

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