Data_Sheet_3_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.CSV

BackgroundIn 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 resultsIn 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.
ConclusionAlthough 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.

背景 在法医学领域，准确判定个体职业可极大助力刑事案件侦破、灾难受害者身份识别等案件的侦办工作。然而，职业与性别、年龄、居住环境、健康状况、用药情况，以及饮酒、吸烟等生活习惯等多种因素间存在复杂关联，使得职业推断颇具挑战。上述各类因素均可影响个体口腔或肠道微生物群落的组成。

方法与结果 本研究收集了不同职业群体（具体为学生与体力劳动者）的唾液及粪便样本。对提取自这些样本的DNA进行宏基因组测序（metagenomic sequencing），获取可通过五个不同数据库开展分类学与功能注释的数据。从α多样性和β多样性视角分析职业与微生物组信息的关联，结果显示两类职业个体的口腔及肠道微生物群落存在显著差异，且在本数据集范围内，该关联基本不受性别、饮酒与吸烟因素的影响。最终通过递归特征消除（recursive feature elimination, RFE）流程构建随机森林（random forest, RF）模型：基于唾液样本中的3个物种，或粪便样本中经京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）注释的单条通路（即"ko04145"或吞噬体（Phagosome））构建的模型，在训练集与测试集上均实现了100%的准确率。

结论 尽管本研究因样本量较小而代表性有限，但本研究为利用微生物组信息进行职业推断的潜在可行性提供了初步证据。