Raman Karthik, Bhat Ashwini Gurudas, Chandra Nagasuma
Bioinformatics Centre, Indian Institute of Science, Bangalore - 560012, India.
Mol Biosyst. 2010 Mar;6(3):516-30. doi: 10.1039/b912129c. Epub 2009 Dec 14.
The complex web of interactions between the host immune system and the pathogen determines the outcome of any infection. A computational model of this interaction network, which encodes complex interplay among host and bacterial components, forms a useful basis for improving the understanding of pathogenesis, in filling knowledge gaps and consequently to identify strategies to counter the disease. We have built an extensive model of the Mycobacterium tuberculosis host-pathogen interactome, consisting of 75 nodes corresponding to host and pathogen molecules, cells, cellular states or processes. Vaccination effects, clearance efficiencies due to drugs and growth rates have also been encoded in the model. The system is modelled as a Boolean network. Virtual deletion experiments, multiple parameter scans and analysis of the system's response to perturbations, indicate that disabling processes such as phagocytosis and phagolysosome fusion or cytokines such as TNF-alpha and IFN-gamma, greatly impaired bacterial clearance, while removing cytokines such as IL-10 alongside bacterial defence proteins such as SapM greatly favour clearance. Simulations indicate a high propensity of the pathogen to persist under different conditions.
宿主免疫系统与病原体之间复杂的相互作用网络决定了任何感染的结果。这个相互作用网络的计算模型编码了宿主和细菌成分之间的复杂相互作用，为增进对发病机制的理解、填补知识空白以及进而确定对抗疾病的策略提供了有用的基础。我们构建了一个广泛的结核分枝杆菌宿主-病原体相互作用组模型，该模型由75个对应于宿主和病原体分子、细胞、细胞状态或过程的节点组成。疫苗接种效果、药物清除效率和生长速率也已编码到模型中。该系统被建模为一个布尔网络。虚拟删除实验、多参数扫描以及对系统对扰动的响应分析表明，抑制诸如吞噬作用和吞噬溶酶体融合等过程或诸如肿瘤坏死因子-α和干扰素-γ等细胞因子，会极大地损害细菌清除，而同时去除诸如白细胞介素-10等细胞因子以及诸如SapM等细菌防御蛋白则极大地有利于清除。模拟表明病原体在不同条件下具有很高的持续存在倾向。
