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通过对微阵列数据集进行综合生物信息学分析,确定利什曼病的生物标志物和 miRNA 调控网络。

An integrated bioinformatic analysis of microarray datasets to identify biomarkers and miRNA-based regulatory networks in leishmaniasis.

机构信息

Department of Medical Biotechnology, School of Advanced Medical Sciences and Technologies, Shiraz University of Medical Sciences, Shiraz, Iran.

Infertility Research Center, Shiraz University of Medical Sciences, Shiraz, Iran.

出版信息

Sci Rep. 2024 Jun 5;14(1):12981. doi: 10.1038/s41598-024-63462-5.

Abstract

Micro RNAs (miRNAs, miRs) and relevant networks might exert crucial functions during differential host cell infection by the different Leishmania species. Thus, a bioinformatic analysis of microarray datasets was developed to identify pivotal shared biomarkers and miRNA-based regulatory networks for Leishmaniasis. A transcriptomic analysis by employing a comprehensive set of gene expression profiling microarrays was conducted to identify the key genes and miRNAs relevant for Leishmania spp. infections. Accordingly, the gene expression profiles of healthy human controls were compared with those of individuals infected with Leishmania mexicana, L. major, L. donovani, and L. braziliensis. The enrichment analysis for datasets was conducted by utilizing EnrichR database, and Protein-Protein Interaction (PPI) network to identify the hub genes. The prognostic value of hub genes was assessed by using receiver operating characteristic (ROC) curves. Finally, the miRNAs that interact with the hub genes were identified using miRTarBase, miRWalk, TargetScan, and miRNet. Differentially expressed genes were identified between the groups compared in this study. These genes were significantly enriched in inflammatory responses, cytokine-mediated signaling pathways and granulocyte and neutrophil chemotaxis responses. The identification of hub genes of recruited datasets suggested that TNF, SOCS3, JUN, TNFAIP3, and CXCL9 may serve as potential infection biomarkers and could deserve value as prognostic biomarkers for leishmaniasis. Additionally, inferred data from miRWalk revealed a significant degree of interaction of a number of miRNAs (hsa-miR-8085, hsa-miR-4673, hsa-miR-4743-3p, hsa-miR-892c-3p, hsa-miR-4644, hsa-miR-671-5p, hsa-miR-7106-5p, hsa-miR-4267, hsa-miR-5196-5p, and hsa-miR-4252) with the majority of the hub genes, suggesting such miRNAs play a crucial role afterwards parasite infection. The hub genes and hub miRNAs identified in this study could be potentially suggested as therapeutic targets or biomarkers for the management of leishmaniasis.

摘要

微小 RNA(miRNAs,miRs)和相关网络可能在不同利什曼原虫物种对宿主细胞的差异感染中发挥关键作用。因此,进行了生物信息学分析微阵列数据集,以确定利什曼病的关键生物标志物和基于 miRNA 的调控网络。通过使用一组全面的基因表达谱微阵列进行转录组分析,以确定与利什曼原虫感染相关的关键基因和 miRNA。相应地,将健康人类对照的基因表达谱与感染墨西哥利什曼原虫、L. major、L. donovani 和 L. braziliensis 的个体的基因表达谱进行比较。通过使用 EnrichR 数据库和蛋白质-蛋白质相互作用(PPI)网络对数据集进行富集分析,以识别枢纽基因。通过使用接收器操作特征(ROC)曲线评估枢纽基因的预后价值。最后,使用 miRTarBase、miRWalk、TargetScan 和 miRNet 识别与枢纽基因相互作用的 miRNA。在本研究中比较的组之间鉴定出差异表达的基因。这些基因在炎症反应、细胞因子介导的信号通路和粒细胞和中性粒细胞趋化反应中显著富集。募集数据集的枢纽基因的鉴定表明,TNF、SOCS3、JUN、TNFAIP3 和 CXCL9 可能作为潜在的感染生物标志物,并值得作为利什曼病的预后生物标志物。此外,miRWalk 的推断数据显示,许多 miRNA(hsa-miR-8085、hsa-miR-4673、hsa-miR-4743-3p、hsa-miR-892c-3p、hsa-miR-4644、hsa-miR-671-5p、hsa-miR-7106-5p、hsa-miR-4267、hsa-miR-5196-5p 和 hsa-miR-4252)与大多数枢纽基因存在显著的相互作用,表明这些 miRNA 在寄生虫感染后发挥关键作用。本研究中鉴定的枢纽基因和枢纽 miRNA 可能被认为是治疗利什曼病的潜在靶点或生物标志物。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0dd6/11153516/07cdf367394a/41598_2024_63462_Fig1_HTML.jpg

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