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细菌和真菌性角膜炎差异表达基因分析。

Analysis of differentially expressed genes in bacterial and fungal keratitis.

机构信息

Department of Ophthalmology, The Second Hospital of Jilin University, Changchun, Jilin Province, China.

出版信息

Indian J Ophthalmol. 2020 Jan;68(1):39-46. doi: 10.4103/ijo.IJO_65_19.

Abstract

PURPOSE

This study was aimed at identifying differentially expressed genes (DEGs) in bacterial and fungal keratitis. The candidate genes can be selected and quantified to distinguish between causative agents of infectious keratitis to improve therapeutic outcomes.

METHODS

The expression profile of bacterial or fungal infection, and normal corneal tissues were downloaded from the Gene Expression Omnibus. The limma package in R was used to screen DEGs in bacterial and fungal keratitis. The Co-Express tool was used to calculate correlation coefficients of co-expressed genes. The "Advanced network merge" function of Cytoscape tool was applied to obtain a fusional co-expression network based on bacterial and fungal keratitis DEGs. Finally, functional enrichment analysis by DAVID software and KEGG analysis by KOBAS of DEGs in fusion network were performed.

RESULTS

In total, 451 DEGs in bacterial keratitis and 353 DEGs in fungal keratitis were screened, among which 148 DEGs were found only in bacterial keratitis and 50 DEGs only in fungal keratitis. Besides, 117 co-expressed gene pairs were identified among bacterial keratitis DEGs and 87 pairs among fungal keratitis DEGs. In total, nine biological pathways and seven KEGG pathways were screened by analyzing DEGs in the fusional co-expression network.

CONCLUSION

TLR4 is the representative DEG specific to bacterial keratitis, and SOD2 is the representative DEG specific to fungal keratitis, both of which are promising candidate genes to distinguish between bacterial and fungal keratitis.

摘要

目的

本研究旨在鉴定细菌性和真菌性角膜炎中的差异表达基因(DEGs)。可以选择候选基因并对其进行定量,以区分感染性角膜炎的病原体,从而改善治疗效果。

方法

从基因表达综合数据库中下载细菌性或真菌性感染以及正常角膜组织的表达谱。使用 R 中的 limma 包筛选细菌性和真菌性角膜炎中的 DEGs。使用 Co-Express 工具计算共表达基因的相关系数。应用 Cytoscape 工具的“高级网络合并”功能,基于细菌性和真菌性角膜炎 DEGs 获取融合的共表达网络。最后,使用 DAVID 软件进行功能富集分析,使用 KOBAS 进行融合网络中 DEGs 的 KEGG 分析。

结果

共筛选出 451 个细菌性角膜炎的 DEGs 和 353 个真菌性角膜炎的 DEGs,其中仅在细菌性角膜炎中发现 148 个 DEGs,仅在真菌性角膜炎中发现 50 个 DEGs。此外,还在细菌性角膜炎 DEGs 中鉴定出 117 对共表达基因对,在真菌性角膜炎 DEGs 中鉴定出 87 对共表达基因对。通过分析融合的共表达网络中的 DEGs,共筛选出 9 个生物学途径和 7 个 KEGG 途径。

结论

TLR4 是特异性针对细菌性角膜炎的代表性 DEG,SOD2 是特异性针对真菌性角膜炎的代表性 DEG,两者均是区分细菌性和真菌性角膜炎的有前途的候选基因。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9c58/6951210/a40b9e483c5b/IJO-68-39-g001.jpg

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