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用于揭示高威胁病原体分子机制的全基因组规模代谢建模

Genome-Scale Metabolic Modeling for Unraveling Molecular Mechanisms of High Threat Pathogens.

作者信息

Sertbas Mustafa, Ulgen Kutlu O

机构信息

Department of Chemical Engineering, Bogazici University, Istanbul, Turkey.

Department of Chemical Engineering, Istanbul Technical University, Istanbul, Turkey.

出版信息

Front Cell Dev Biol. 2020 Nov 3;8:566702. doi: 10.3389/fcell.2020.566702. eCollection 2020.

Abstract

Pathogens give rise to a wide range of diseases threatening global health and hence drawing public health agencies' attention to establish preventative and curative solutions. Genome-scale metabolic modeling is ever increasingly used tool for biomedical applications including the elucidation of antibiotic resistance, virulence, single pathogen mechanisms and pathogen-host interaction systems. With this approach, the sophisticated cellular system of metabolic reactions inside the pathogens as well as between pathogen and host cells are represented in conjunction with their corresponding genes and enzymes. Along with essential metabolic reactions, alternate pathways and fluxes are predicted by performing computational flux analyses for the growth of pathogens in a very short time. The genes or enzymes responsible for the essential metabolic reactions in pathogen growth are regarded as potential drug targets, as guide to researchers in the pharmaceutical field. Pathogens alter the key metabolic processes in infected host, ultimately the objective of these integrative constraint-based context-specific metabolic models is to provide novel insights toward understanding the metabolic basis of the acute and chronic processes of infection, revealing cellular mechanisms of pathogenesis, identifying strain-specific biomarkers and developing new therapeutic approaches including the combination drugs. The reaction rates predicted during different time points of pathogen development enable us to predict active pathways and those that only occur during certain stages of infection, and thus point out the putative drug targets. Among others, fatty acid and lipid syntheses reactions are recent targets of new antimicrobial drugs. Genome-scale metabolic models provide an improved understanding of how intracellular pathogens utilize the existing microenvironment of the host. Here, we reviewed the current knowledge of genome-scale metabolic modeling in pathogen cells as well as pathogen host interaction systems and the promising applications in the extension of curative strategies against pathogens for global preventative healthcare.

摘要

病原体引发了一系列威胁全球健康的疾病,因此引起了公共卫生机构的关注,促使其建立预防和治疗方案。基因组规模代谢建模在生物医学应用中越来越常用,包括阐明抗生素耐药性、毒力、单一病原体机制以及病原体-宿主相互作用系统。通过这种方法,病原体内部以及病原体与宿主细胞之间复杂的代谢反应细胞系统与其相应的基因和酶一起被呈现出来。除了基本的代谢反应外,通过对病原体生长进行计算通量分析,可在极短时间内预测替代途径和通量。负责病原体生长中基本代谢反应的基因或酶被视为潜在的药物靶点,为制药领域的研究人员提供指导。病原体改变受感染宿主中的关键代谢过程,最终这些基于约束的整合上下文特异性代谢模型的目标是为理解感染的急性和慢性过程的代谢基础、揭示发病机制的细胞机制、识别菌株特异性生物标志物以及开发包括联合药物在内的新治疗方法提供新的见解。在病原体发育的不同时间点预测的反应速率使我们能够预测活跃途径以及仅在感染的特定阶段发生的途径,从而指出假定的药物靶点。其中,脂肪酸和脂质合成反应是新型抗菌药物最近的靶点。基因组规模代谢模型有助于更好地理解细胞内病原体如何利用宿主现有的微环境。在此,我们综述了目前关于病原体细胞以及病原体-宿主相互作用系统中基因组规模代谢建模的知识,以及其在扩展针对病原体的治疗策略以实现全球预防性医疗保健方面的前景应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b5a5/7673413/69f9b6721ce4/fcell-08-566702-g0001.jpg

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