Predicting the postmortem interval using human intestinal microbiome data and random forest algorithm

Area of Science:

• Forensic microbiology
• Microbial ecology
• Decomposition studies

Background:

• Postmortem interval (PMI) estimation is crucial in forensic science.
• Gut microflora composition changes predictably after death.
• The vermiform appendix as a sampling site for PMI determination is under-explored.

Purpose of the Study:

• To investigate the potential of gut microbial succession in the human appendix for postmortem interval estimation.
• To identify predictable changes in gut microbiota composition during human decomposition.
• To develop a model for correlating gut microbial data with PMI.

Main Methods:

• Collection of gut microflora samples from the vermiform appendix and transverse colon of human cadavers.
• Analysis of microbial community composition and relative abundance over a postmortem interval range of 5 to 192 hours.
• Development of a Random Forest regression model to correlate gut microbiota with PMI.

Main Results:

• The appendix was identified as a suitable site for intestinal sampling for PMI estimation.
• A predictable succession rule was observed in the appendix flora during decomposition.
• Specific bacterial phyla (Firmicutes, Bacteroidetes) and their subclasses exhibited predictable abundance changes over time.
• The Random Forest model showed potential for correlating gut microbiota with PMI.

Conclusions:

• The study highlights the appendix as a valuable site for microbial sampling in forensic investigations.
• Microbial succession in the human appendix offers a promising new method for estimating the time of death.
• Findings contribute to the understanding of gut microbiota dynamics during human decomposition.