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宿主对呼吸道细菌病原体的反应,可通过综合分析人类基因表达数据来识别。

Host response to respiratory bacterial pathogens as identified by integrated analysis of human gene expression data.

机构信息

Computational Biology, Quantitative Sciences, GlaxoSmithKline, Collegeville, Pennsylvania, United States of America ; Institute for Genome Science, University of Maryland, Baltimore, Maryland, United States of America.

出版信息

PLoS One. 2013 Sep 27;8(9):e75607. doi: 10.1371/journal.pone.0075607. eCollection 2013.

Abstract

Respiratory bacterial pathogens are one of the leading causes of infectious death in the world and a major health concern complicated by the rise of multi-antibiotic resistant strains. Therapeutics that modulate host genes essential for pathogen infectivity could potentially avoid multi-drug resistance and provide a wider scope of treatment options. Here, we perform an integrative analysis of published human gene expression data generated under challenges from the gram-negative and Gram-positive bacteria pathogens, Pseudomonas aeruginosa and Streptococcus pneumoniae, respectively. We applied a previously described differential gene and pathway enrichment analysis pipeline to publicly available host mRNA GEO datasets resulting from exposure to bacterial infection. We found 72 canonical human pathways common between four GEO datasets, representing P. aeruginosa and S. pneumoniae. Although the majority of these pathways are known to be involved with immune response, we found several interesting new interactions such as the SUMO1 pathway that might have a role in bacterial infections. Furthermore, 36 host-bacterial pathways were also shared with our previous results for respiratory virus host gene expression. Based on our pathway analysis we propose several drug-repurposing opportunities supported by the literature.

摘要

呼吸道细菌病原体是世界上导致感染性死亡的主要原因之一,也是一个主要的健康关注点,尤其是由于多抗生素耐药株的出现。能够调节宿主基因的治疗方法对于病原体感染是必需的,这可能避免多药耐药性,并提供更广泛的治疗选择范围。在这里,我们对发表的人类基因表达数据进行了综合分析,这些数据是在分别受到革兰氏阴性和革兰氏阳性细菌病原体铜绿假单胞菌和肺炎链球菌挑战时产生的。我们应用了先前描述的差异基因和途径富集分析管道,对来自细菌感染暴露的公共可用宿主 mRNA GEO 数据集进行了分析。我们发现了 72 个常见于四个 GEO 数据集的经典人类途径,代表了铜绿假单胞菌和肺炎链球菌。尽管这些途径中的大多数已知与免疫反应有关,但我们发现了一些有趣的新相互作用,例如 SUMO1 途径,它可能在细菌感染中起作用。此外,36 个宿主-细菌途径也与我们之前关于呼吸道病毒宿主基因表达的结果共享。基于我们的通路分析,我们提出了一些有文献支持的药物再利用机会。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d551/3785471/b2954cbdd762/pone.0075607.g001.jpg

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