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首页> 外文期刊>The Journal of biological chemistry >Express Path Analysis Identifies a Tyrosine Kinase Src-centric Network Regulating Divergent Host Responses to Mycobacterium tuberculosis Infection
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Express Path Analysis Identifies a Tyrosine Kinase Src-centric Network Regulating Divergent Host Responses to Mycobacterium tuberculosis Infection

机译:Express路径分析识别酪氨酸激酶的SRC网络,其用于分枝杆菌性核心感染的分歧宿主反应

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Global gene expression profiling has emerged as a major tool in understanding complex response patterns of biological systems to perturbations. However, a lack of unbiased analytical approaches has restricted the utility of complex microarray data to gain novel system level insights. Here we report a strategy, express path analysis (EPA), that helps to establish various pathways differentially recruited to achieve specific cellular responses under contrasting environmental conditions in an unbiased manner. The analysis superimposes differentially regulated genes between contrasting environments onto the network of functional protein associations followed by a series of iterative enrichments and network analysis. To test the utility of the approach, we infected THP1 macrophage cells with a virulent Mycobacterium tuberculosis strain (H37Rv) or the attenuated non-virulent strain H37Ra as contrasting perturbations and generated the temporal global expression profiles. EPA of the results provided details of response-specific and time-dependent host molecular network perturbations. Further analysis identified tyrosine kinase Src as the major regulatory hub discriminating the responses between wild-type and attenuated Mtb infection. We were then able to verify this novel role of Src experimentally and show that Src executes its role through regulating two vital antimicrobial processes of the host cells (i.e. autophagy and acidification of phagolysosome). These results bear significant potential for developing novel anti-tuberculosis therapy. We propose that EPA could prove extremely useful in understanding complex cellular responses for a variety of perturbations, including pathogenic infections.
机译:全球基因表达分析是理解生物系统复杂反应模式的主要工具,以扰动。然而,缺乏无偏析的分析方法限制了复杂的微阵列数据的效用,以获得新的系统级别见解。在这里,我们报告了一种策略,表达路径分析(EPA),有助于建立差异招募的各种途径,以实现对比环境条件下的特定细胞反应以无偏见的方式。该分析将对比环境之间的差异调节基因叠加到功能蛋白联合网络网络中,然后是一系列迭代丰富和网络分析。为了测试该方法的效用,我们用毒性的分枝杆菌菌株(H37RV)或减毒的非毒菌菌株H37Ra感染了THP1巨噬细胞细胞,作为对比扰动并产生时间全局表达谱。结果的EPA提供了响应特定和时间依赖性宿主分子网络扰动的细节。进一步的分析确定酪氨酸激酶SRC作为鉴别野生型和减毒的MTB感染之间的反应的主要调节中心。然后,我们能够通过调节宿主细胞的两个重要抗微生物方法来验证SRC的这种新的SRC作用,并表明SRC通过调节宿主细胞的两个重要抗微生物方法来执行其作用(即吞噬肌瘤的自噬和酸化)。这些结果具有发展新型抗结核疗法的显着潜力。我们提出,EPA可以证明在理解各种扰动的复杂细胞反应中可能是非常有用的,包括致病感染。

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