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Related Experiment Video

Updated: Oct 3, 2025

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
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Estimating Postmortem Interval Using Intestinal Microbiota Diversity Based on 16S rRNA High-throughput Sequencing

Jie Cao1, Wen-Jin Li1, Yi-Fei Wang1

  • 1School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China.

Fa Yi Xue Za Zhi
|February 21, 2022
PubMed
Summary
This summary is machine-generated.

The composition of rat intestinal microbiota changes significantly within 30 days postmortem. This study demonstrates a strong correlation between intestinal microbiota and postmortem interval (PMI) estimation using 16S rRNA sequencing.

Keywords:
16S rRNAforensic pathologyhigh-throughput sequencingintestinal microbial communitypostmortem interval estimationrats

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Area of Science:

  • Forensic Science
  • Microbiology
  • Molecular Biology

Background:

  • The postmortem interval (PMI) is crucial in forensic investigations.
  • Intestinal microbiota composition undergoes dynamic changes after death.
  • 16S rRNA high-throughput sequencing offers a powerful tool for microbial community analysis.

Purpose of the Study:

  • To investigate the correlation between intestinal microbiota and PMI in rats.
  • To evaluate the potential of using microbial community shifts for PMI estimation.
  • To analyze changes in intestinal microbiota diversity and structure over 30 days postmortem.

Main Methods:

  • Rats were maintained at 16°C post-anesthesia.
  • Cecal DNA was extracted at 14 distinct time points (0-30 days postmortem).
  • 16S rRNA high-throughput sequencing was employed to profile microbial communities.

Main Results:

  • Intestinal microbial diversity showed an increasing trend within 30 days.
  • Significant alterations in 119 bacterial communities were observed.
  • Partial least squares (PLS) regression models accurately estimated PMI (R² up to 0.795).

Conclusions:

  • Intestinal microbiota composition and structure significantly change within 30 days postmortem.
  • PLS regression models based on microbiota data provide reliable PMI estimation.
  • Intestinal microbiota exhibits time-series changes, offering a valuable forensic biomarker.