Estimating Postmortem Interval of Buried Pig Carcasses by Integrating Microbial Succession Patterns with Machine...

Area of Science:

• Forensic Science
• Microbiology
• Bioinformatics

Background:

• Microbial succession is a key indicator for estimating postmortem interval (PMI).
• Understanding microbial patterns in buried remains is crucial for forensic investigations.
• Previous studies have primarily focused on surface decomposition, leaving a gap in knowledge for buried scenarios.

Purpose of the Study:

• To investigate microbial succession patterns in buried versus surface pig carcasses.
• To compare microbial community dynamics across different decomposition stages in both environments.
• To develop and evaluate models for postmortem interval estimation based on microbial data.

Main Methods:

• Establishment of a pig carcass model with buried and surface groups.
• 16S ribosomal RNA (16S rRNA) gene sequencing for microbial community analysis.
• Random Forest modeling using genus-level microbial data for PMI estimation.

Main Results:

• Buried carcasses exhibited slower decomposition rates compared to surface carcasses.
• Alpha diversity decreased in buried remains post-early decomposition, similar to surface remains.
• Significant bacterial community shifts and Proteobacteria abundance changes were observed in buried remains, mirroring surface patterns.
• Unique microbial taxa associated with PMI were identified in both buried and surface groups.
• Random Forest models achieved mean absolute errors of approximately 5 days for PMI estimation in both buried and surface groups.

Conclusions:

• Microbial succession patterns are predictable in both buried and surface decomposition environments.
• The study demonstrates the potential of microbial analysis for estimating PMI in buried remains.
• Further research with larger sample sizes is needed to enhance model generalizability.