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基于树突状细胞枢纽基因的综合生物信息学分析揭示潜在的早期结核病诊断标志物。

Integrated bioinformatics analysis of dendritic cells hub genes reveal potential early tuberculosis diagnostic markers.

机构信息

Department of Bacteriology and Immunology, Beijing Chest Hospital, Capital Medical University, Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, P. R. China.

Department of Tuberculosis, Beijing Chest Hospital, Capital Medical University/Beijing Tuberculosis & Thoracic Tumor Research Institute, Beijing, 101149, P. R. China.

出版信息

BMC Med Genomics. 2023 Sep 8;16(1):214. doi: 10.1186/s12920-023-01646-0.

DOI:10.1186/s12920-023-01646-0
PMID:37684607
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10492340/
Abstract

BACKGROUND

Dendritic cells (DCs) are most potent antigen-processing cells and play key roles in host defense against Mycobacterium tuberculosis (MTB) infection. In this study, hub genes in DCs during MTB infection were first investigated using bioinformatics approaches and further validated in Monocyte-derived DCs.

METHODS

Microarray datasets were obtained from Gene Expression Omnibus (GEO) database. Principal component analysis (PCA) and immune infiltration analysis were performed to select suitable samples for further analysis. Differential analysis and functional enrichment analysis were conducted on DC samples, comparing live MTB-infected and non-infected (NI) groups. The CytoHubba plugin in Cytoscape was used to identify hub genes from the differentially expressed genes (DEGs). The expression of the hub genes was validated using two datasets and reverse transcription-quantitative polymerase chain reaction (RT-qPCR) in human monocyte-derived DCs. Enzyme-linked immunosorbent assay (ELISA) was used to validate interferon (IFN) secretion. Transcription factors (TFs) and microRNAs (miRNAs) that interact with the hub genes were predicted using prediction databases. The diagnostic value of the hub genes was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC) values.

RESULTS

A total of 1835 common DEGs among three comparison groups (18 h, 48 h, 72 h after MTB infection) were identified. Six DEGs (IFIT1, IFIT2, IFIT3, ISG15, MX1, and RSAD2) were determined as hub genes. Functions enrichment analysis revealed that all hub genes all related to IFN response. RT-qPCR showed that the expression levels of six hub genes were significantly increased after DC stimulated by live MTB. According to the results of ELISA, the secretion of IFN-γ, but not IFN-α/β, was upregulated in MTB-stimulated DCs. AUC values of six hub genes ranged from 84 to 94% and AUC values of 5 joint indicators of two hub genes were higher than the two hub genes alone.

CONCLUSION

The study identified 6 hub genes associated with IFN response pathway. These genes may serve as potential diagnostic biomarkers in tuberculosis (TB). The findings provide insights into the molecular mechanisms involved in the host immune response to MTB infection and highlight the diagnostic potential of these hub genes in TB.

摘要

背景

树突状细胞(DCs)是最有效的抗原处理细胞,在宿主防御结核分枝杆菌(MTB)感染中发挥关键作用。本研究首先采用生物信息学方法研究 MTB 感染时 DCs 中的枢纽基因,并在单核细胞衍生的 DCs 中进一步验证。

方法

从基因表达综合数据库(GEO)数据库中获取微阵列数据集。进行主成分分析(PCA)和免疫浸润分析,以选择适合进一步分析的样本。比较活 MTB 感染组和非感染(NI)组的 DC 样本进行差异分析和功能富集分析。使用 Cytoscape 中的 CytoHubba 插件从差异表达基因(DEGs)中识别枢纽基因。使用两个数据集和人单核细胞衍生的 DCs 中的逆转录定量聚合酶链反应(RT-qPCR)验证枢纽基因的表达。酶联免疫吸附试验(ELISA)用于验证干扰素(IFN)分泌。使用预测数据库预测与枢纽基因相互作用的转录因子(TFs)和 microRNAs(miRNAs)。使用接收器操作特征(ROC)曲线和曲线下面积(AUC)值评估枢纽基因的诊断价值。

结果

在三个比较组(MTB 感染后 18 小时、48 小时和 72 小时)中,共鉴定出 1835 个共同的 DEGs。确定了 6 个 DEGs(IFIT1、IFIT2、IFIT3、ISG15、MX1 和 RSAD2)作为枢纽基因。功能富集分析表明,所有枢纽基因均与 IFN 反应相关。RT-qPCR 显示,活 MTB 刺激后,六个枢纽基因的表达水平显著增加。根据 ELISA 结果,MTB 刺激的 DC 中 IFN-γ的分泌上调,但 IFN-α/β 没有上调。六个枢纽基因的 AUC 值范围为 84%至 94%,两个枢纽基因的五个联合指标的 AUC 值高于两个枢纽基因单独的 AUC 值。

结论

本研究鉴定了与 IFN 反应途径相关的 6 个枢纽基因。这些基因可能作为结核病(TB)的潜在诊断生物标志物。研究结果为宿主对 MTB 感染的免疫反应的分子机制提供了新的见解,并强调了这些枢纽基因在 TB 中的诊断潜力。

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