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  

Estimating Postmortem Interval Using Intestinal Microbiota Diversity Based on 16S rRNA High-throughput Sequencing Technology

作　　者：曹洁[1] 李文晋 王一飞 安国帅 卢晓军 杜秋香[1] 李晋[3] 孙俊红[1] CAO Jie;LI Wen-jin;WANG Yi-fei;AN Guo-shuai;LU Xiao-jun;DU Qiu-xiang;LI Jin;SUN Jun hong(School of Forensic Medicine,Shanxi Medical University,Taiyuan 030001,China;Criminal Investigation Detachment,Baotou Public Security Bureau,Baotou 014030,Inner Mongolia Autonomous Region,China;Second Hospital of Shanxi Medical University,Taiyuan 030001,China)

机构地区：[1]山西医科大学法医学院,山西太原030001 [2]包头市公安局刑事侦查支队,内蒙古包头014030 [3]山西医科大学第二医院,山西太原030001

出　　处：《法医学杂志》2021年第5期621-626,共6页Journal of Forensic Medicine

基　　金：国家自然科学基金面上资助项目(81971795);山西省应用基础研究青年科技资助项目(201801D221264)。

摘　　要：目的采用16S rRNA高通量测序技术探究大鼠肠道菌群变化与死亡时间(postmortem interval,PMI)之间的关系。方法大鼠腹腔麻醉致死后置于16℃,提取死后0、1、2、3、5、7、9、12、15、18、21、24、27和30 d共14个时间点的盲肠内容物DNA,采用16S rRNA高通量测序技术,检测大鼠盲肠内容物中的肠道菌群,对数据进行多样性及差异性分析。结果死后30 d内大鼠肠道微生物菌群总数未发生明显变化,但菌群多样性呈上升趋势。在死后13个时间点共筛选出119个具有显著差异的细菌群落。构建全部时间点、9 d前、12 d后PMI推断的偏最小二乘(partial least squares,PLS)回归模型,其决定系数(R2)分别为0.795、0.767和0.445;交叉验证均方根误差分别为6.57、1.96和5.37 d。结论利用16S rRNA高通量测序技术探究死后30 d内肠道菌群的变化规律,其组成和结构出现了明显的变化,且建立的PLS回归模型表明PMI与肠道菌群之间高度相关,呈一定时序性变化。Objective 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 tech-nology was used to detect intestinal microbiota in rat cecal contents,and the results were used to ana-lyze the rat intestinal microbiota diversity and differences.Results The total number of intestinal micro-bial 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,respec-tively;and the root mean square errors(RMSEs)were 6.57,1.96 and 5.37 d,respectively.Conclusion Using 16S rRNA high-throughput sequencing technology,the composition and structure of intestinal mi-crobiota 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.

关 键 词：法医病理学 16S rRNA 死亡时间推断 肠道菌群 高通量测序 大鼠 

分 类 号：D919.1[医药卫生—法医学]