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Updated: Jul 12, 2025

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing

Published on: October 15, 2019

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

Qing-Qing Xiang¹, Li-Fang Chen^1,2, Qin Su^3,4

¹College of Forensic Medicine, Kunming Medical University, Kunming 650500, China.

Fa Yi Xue Za Zhi

|October 20, 2023

Summary

This summary is machine-generated.

Estimating the time since death (postmortem interval) is challenging. Microbial community analysis using high-throughput sequencing offers a promising, objective method for accurate postmortem interval estimation.

Keywords:

forensic pathology high-throughput sequencing machine learning microbial community microbiomics postmortem interval estimation review

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Area of Science:

Forensic Science
Microbiology
Bioinformatics

Background:

Accurate postmortem interval (PMI) estimation is crucial in forensic medicine but remains challenging.
Traditional methods for PMI estimation often lack objectivity and precision.
The succession of microbial communities on decomposing remains presents a novel avenue for PMI determination.

Approach:

This review examines high-throughput sequencing technologies for analyzing microbial communities.
It explores the application of microbial succession patterns in forensic science for PMI estimation.
Artificial intelligence is investigated for its role in developing robust PMI models.

Key Points:

High-throughput sequencing enables comprehensive analysis of microbial communities.
Microbial community dynamics on corpses are influenced by various environmental and biological factors.
AI-driven models show potential for improving the accuracy and objectivity of PMI estimation.

Conclusions:

Microbial community analysis, particularly with high-throughput sequencing, is a rapidly advancing field in forensic science.
Further research is needed to refine models and account for influencing factors for reliable PMI estimation.
This approach offers a powerful tool for objective and quantifiable postmortem interval determination.