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人类念珠菌感染的共表达网络分析揭示了负责宿主-病原体相互作用的关键模块和枢纽基因。

Coexpression network analysis of human candida infection reveals key modules and hub genes responsible for host-pathogen interactions.

作者信息

Naik Surabhi, Mohammed Akram

机构信息

Department of Surgery, James D. Eason Transplant Institute, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States.

Center for Biomedical Informatics, College of Medicine, University of Tennessee Health Science Center, Memphis, TN, United States.

出版信息

Front Genet. 2022 Nov 22;13:917636. doi: 10.3389/fgene.2022.917636. eCollection 2022.

Abstract

Invasive fungal infections are a significant reason for morbidity and mortality among organ transplant recipients. Therefore, it is critical to investigate the host and candida niches to understand the epidemiology of fungal infections in transplantation. is an opportunistic fungal pathogen that causes fatal invasive mucosal infections, particularly in solid organ transplant patients. Therefore, identifying and characterizing these genes would play a vital role in understanding the complex regulation of host-pathogen interactions. Using 32 RNA-sequencing samples of human cells infected with , we developed WGCNA coexpression networks and performed DESeq2 differential gene expression analysis to identify the genes that positively correlate with human candida infection. Using hierarchical clustering, we identified 5 distinct modules. We studied the inter- and intramodular gene network properties in the context of sample status traits and identified the highly enriched genes in the correlated modules. We identified 52 genes that were common in the most significant WGCNA turquoise module and differentially expressed genes in human endothelial cells (HUVEC) infection vs. control samples. As a validation step, we identified the differentially expressed genes from the independent Candida-infected human oral keratinocytes (OKF6) samples and validated 30 of the 52 common genes. We then performed the functional enrichment analysis using KEGG and GO. Finally, we performed protein-protein interaction (PPI) analysis using STRING and CytoHubba from 30 validated genes. We identified 8 hub genes () that were enriched in response to hypoxia, angiogenesis, vasculogenesis, hypoxia-induced signaling, cancer, diabetes, and transplant-related disease pathways. The discovery of genes and functional pathways related to the immune system and gene coexpression and differential gene expression analyses may serve as novel diagnostic markers and potential therapeutic targets.

摘要

侵袭性真菌感染是器官移植受者发病和死亡的重要原因。因此,研究宿主和念珠菌生态位对于了解移植中真菌感染的流行病学至关重要。白色念珠菌是一种机会性真菌病原体,可导致致命的侵袭性黏膜感染,尤其是在实体器官移植患者中。因此,鉴定和表征这些基因对于理解宿主-病原体相互作用的复杂调控将发挥至关重要的作用。利用32个人类细胞感染白色念珠菌的RNA测序样本,我们构建了加权基因共表达网络分析(WGCNA)共表达网络,并进行了DESeq2差异基因表达分析,以鉴定与人类念珠菌感染呈正相关的基因。通过层次聚类,我们确定了5个不同的模块。我们在样本状态特征的背景下研究了模块间和模块内的基因网络特性,并确定了相关模块中高度富集的基因。我们在最显著的WGCNA绿松石模块中鉴定出52个常见基因,这些基因在人内皮细胞(HUVEC)感染与对照样本中差异表达。作为验证步骤,我们从独立的念珠菌感染的人类口腔角质形成细胞(OKF6)样本中鉴定出差异表达基因,并验证了52个常见基因中的30个。然后,我们使用京都基因与基因组百科全书(KEGG)和基因本体论(GO)进行功能富集分析。最后,我们使用STRING和CytoHubba对30个验证基因进行蛋白质-蛋白质相互作用(PPI)分析。我们鉴定出8个中心基因,这些基因在缺氧、血管生成、血管发生、缺氧诱导信号、癌症、糖尿病和移植相关疾病途径中富集。与免疫系统相关的基因和功能途径的发现以及基因共表达和差异基因表达分析可能作为新的诊断标志物和潜在的治疗靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0fee/9722774/674ce08ecb15/fgene-13-917636-g001.jpg

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