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首页> 外文期刊>Comparative and functional genomics >Data Mining Mycobacterium tuberculosis Pathogenic Gene Transcription Factors and Their Regulatory Network Nodes
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Data Mining Mycobacterium tuberculosis Pathogenic Gene Transcription Factors and Their Regulatory Network Nodes

机译：数据挖掘结核分枝杆菌致病基因转录因子及其调控网络节点

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摘要

Tuberculosis (TB) is one of the deadliest infectious diseases worldwide. In Mycobacterium tuberculosis, changes in gene expression are highly variable and involve many genes, so traditional single-gene screening of M. tuberculosis targets has been unable to meet the needs of clinical diagnosis. In this study, using the National Center for Biotechnology Information (NCBI) GEO Datasets, whole blood gene expression profile data were obtained in patients with active pulmonary tuberculosis. Linear model-experience Bayesian statistics using the Limma package in R combined with t-tests were applied for nonspecific filtration of the expression profile data, and the differentially expressed human genes were determined. Using DAVID and KEGG, the functional analysis of differentially expressed genes (GO analysis) and the analysis of signaling pathways were performed. Based on the differentially expressed gene, the transcriptional regulatory element databases (TRED) were integrated to construct the M. tuberculosis pathogenic gene regulatory network, and the correlation of the network genes with disease was analyzed with the DAVID online annotation tool. It was predicted that IL-6, JUN, and TP53, along with transcription factors SRC, TNF, and MAPK14, could regulate the immune response, with their function being extracellular region activity and protein binding during infection with M. tuberculosis.
机译：结核病（TB）是世界上最致命的传染病之一。在结核分枝杆菌中，基因表达的变化是高度可变的并且涉及许多基因，因此传统的结核分枝杆菌靶标的单基因筛选已不能满足临床诊断的需要。在这项研究中，使用美国国家生物技术信息中心（NCBI）GEO数据集，获得了活动性肺结核患者的全血基因表达谱数据。使用在R中使用Limma软件包和t检验的线性模型经验贝叶斯统计数据对表达谱数据进行非特异性过滤，并确定了差异表达的人类基因。使用DAVID和KEGG，进行差异表达基因的功能分析（GO分析）和信号通路分析。基于差异表达基因，整合转录调控元件数据库（TRED），构建结核分枝杆菌致病基因调控网络，并利用DAVID在线注释工具分析网络基因与疾病的相关性。据预测，IL-6，JUN和TP53以及转录因子SRC，TNF和MAPK14可以调节免疫反应，其功能是感染结核分枝杆菌时的细胞外区域活性和蛋白质结合。

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