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口腔与肠道宏基因组学在预测个体职业中的应用价值初步探索性研究——以学生与农民工的区分为例

Preliminary exploratory research on the application value of oral and intestinal meta-genomics in predicting subjects' occupations-A case study of the distinction between students and migrant workers.

作者信息

Dou Shujie, Ma Guanju, Liang Yu, Fu Guangping, Shen Jie, Fu Lihong, Wang Qian, Li Tao, Cong Bin, Li Shujin

机构信息

College of Forensic Medicine, Hebei Medical University, Hebei Key Laboratory of Forensic Medicine, Research Unit of Digestive Tract Microecosystem Pharmacology and Toxicology, Chinese Academy of Medical Sciences, Shijiazhuang, China.

Institute of Intelligent Medical Research (IIMR), BGI Genomics, Shenzhen, China.

出版信息

Front Microbiol. 2024 Feb 6;14:1330603. doi: 10.3389/fmicb.2023.1330603. eCollection 2023.

Abstract

BACKGROUND

In the field of forensic science, accurately determining occupation of an individual can greatly assist in resolving cases such as criminal investigations or disaster victim identifications. However, estimating occupation can be challenging due to the intricate relationship between occupation and various factors, including gender, age, living environment, health status, medication use, and lifestyle habits such as alcohol consumption and smoking. All of these factors can impact the composition of oral or gut microbial community of an individual.

METHODS AND RESULTS

In this study, we collected saliva and feces samples from individuals representing different occupational sectors, specifically students and manual laborers. We then performed metagenomic sequencing on the DNA extracted from these samples to obtain data that could be analyzed for taxonomic and functional annotations in five different databases. The correlation between occupation with microbial information was assisted from the perspective of α and β diversity, showing that individuals belonging to the two occupations hold significantly different oral and gut microbial communities, and that this correlation is basically not affected by gender, drinking, and smoking in our datasets. Finally, random forest (RF) models were built with recursive feature elimination (RFE) processes. Models with 100% accuracy in both training and testing sets were constructed based on three species in saliva samples or on a single pathway annotated by the KEGG database in fecal samples, namely, "ko04145" or Phagosome.

CONCLUSION

Although this study may have limited representativeness due to its small sample size, it provides preliminary evidence of the potential of using microbiome information for occupational inference.

摘要

背景

在法医学领域,准确确定个人职业有助于解决诸如刑事调查或灾难遇难者身份识别等案件。然而,由于职业与包括性别、年龄、生活环境、健康状况、药物使用以及饮酒和吸烟等生活方式习惯在内的各种因素之间存在复杂关系,估计职业可能具有挑战性。所有这些因素都会影响个体口腔或肠道微生物群落的组成。

方法与结果

在本研究中,我们从代表不同职业领域的个体,即学生和体力劳动者那里收集了唾液和粪便样本。然后,我们对从这些样本中提取的DNA进行宏基因组测序,以获得可在五个不同数据库中进行分类和功能注释分析的数据。从α和β多样性的角度辅助分析职业与微生物信息之间的相关性,结果表明属于这两种职业的个体拥有显著不同的口腔和肠道微生物群落,并且在我们的数据集中这种相关性基本不受性别、饮酒和吸烟的影响。最后,通过递归特征消除(RFE)过程构建了随机森林(RF)模型。基于唾液样本中的三种物种或粪便样本中由KEGG数据库注释的单一通路,即“ko04145”或吞噬体,构建了在训练集和测试集中准确率均为100%的模型。

结论

尽管本研究由于样本量小可能代表性有限,但它为利用微生物组信息进行职业推断的潜力提供了初步证据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/25cc/10883652/624e7a9908fe/fmicb-14-1330603-g0005.jpg

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