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Estimating Postmortem Interval Using Intestinal Microbiota Diversity Based on 16S rRNA High-throughput Sequencing Technology. / 基于16S rRNA高通量测序技术的肠道菌群多样性推断死亡时间.
Cao, Jie; Li, Wen-Jin; Wang, Yi-Fei; An, Guo-Shuai; Lu, Xiao-Jun; DU, Qiu-Xiang; Li, Jin; Sun, Jun-Hong.
Afiliação
  • Cao J; School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China.
  • Li WJ; School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China.
  • Wang YF; School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China.
  • An GS; School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China.
  • Lu XJ; School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China.
  • DU QX; Criminal Investigation Detachment, Baotou Public Security Bureau, Baotou 014030, Inner Mongolia Autonomous Region, China.
  • Li J; School of Forensic Medicine, Shanxi Medical University, Taiyuan 030001, China.
  • Sun JH; Second Hospital of Shanxi Medical University, Taiyuan 030001, China.
Fa Yi Xue Za Zhi ; 37(5): 621-626, 2021 Oct 25.
Article em En, Zh | MEDLINE | ID: mdl-35187912
ABSTRACT

OBJECTIVES:

To explore the correlation between intestinal microbiota and postmortem interval(PMI) in rats by using 16S rRNA high-throughput sequencing technology.

METHODS:

Rats were killed by anesthesia and placed at 16 ℃, and DNA was extracted in caecum at 14 time points of 0, 1, 2, 3, 5, 7, 9, 12, 15, 18, 21, 24, 27 and 30 d after death. The 16S rRNA high-throughput sequencing technology was used to detect intestinal microbiota in rat cecal contents, and the results were used to analyze the rat intestinal microbiota diversity and differences.

RESULTS:

The total number of intestinal microbial communities did not change significantly within 30 days after death, but the diversity showed an upward trend. A total of 119 bacterial communities were significantly changed at 13 time points after death. The models for PMI estimation were established by using partial least squares (PLS) regression at all time points, before 9 days and after 12 days, reaching an R2 of 0.795, 0.767 and 0.445, respectively; and the root mean square errors (RMSEs) were 6.57, 1.96 and 5.37 d, respectively.

CONCLUSIONS:

Using 16S rRNA high-throughput sequencing technology, the composition and structure of intestinal microbiota changed significantly within 30 d after death. In addition, the established PLS regression model suggested that the PMI was highly correlated with intestinal microbiota composition, showing a certain time series change.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Microbiota / Microbioma Gastrointestinal Idioma: En / Zh Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Microbiota / Microbioma Gastrointestinal Idioma: En / Zh Ano de publicação: 2021 Tipo de documento: Article