Sharma Mahesh, Shaikh Naeem, Yadav Shailendra, Singh Sushma, Garg Prabha
Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research (NIPER), Sector-67, S.A.S. Nagar, Punjab-160062, India.
Mol Biosyst. 2017 May 2;13(5):955-969. doi: 10.1039/c6mb00823b.
Visceral leishmaniasis, a lethal parasitic disease, is caused by the protozoan parasite Leishmania donovani. The absence of an effective vaccine, drug toxicity and parasite resistance necessitates the identification of novel drug targets. Reconstruction of genome-scale metabolic models and their simulation has been established as an important tool for systems-level understanding of a microorganism's metabolism. In this work, amalgamating the tools and techniques of computational systems biology with rigorous manual curation, a constraint-based metabolic model for Leishmania donovani BPK282A1 has been developed. New functional annotations for 18 formerly hypothetical or erroneously annotated genes (encountered during iterative refinement of the model) have been proposed. Further, to formulate an accurate biomass objective function, experimental determination of previously uncharacterized biomass constituents was performed. The developed model is a highly compartmentalized metabolic model, comprising 1159 reactions, 1135 metabolites and 604 genes. The model exhibited around 76% accuracy for the prediction of experimental phenotypes of gene knockout studies and drug inhibition assays. Employing in silico gene knockout studies, we identified 28 essential genes with negligible sequence identity to the human proteins. Moreover, by dissecting the functional interdependencies of metabolic pathways, 70 synthetic lethal pairs were identified. Finally, in order to delineate stage-specific metabolism, gene-expression data of the amastigote stage residing in human macrophages were integrated into the model. By comparing the flux distribution, we illustrated the stage-specific differences in metabolism and environmental conditions that are in good agreement with the experimental findings. The developed model can serve as a highly enriched knowledgebase of legacy data and an important tool for generating experimentally verifiable hypotheses.
内脏利什曼病是一种致命的寄生虫病，由原生动物寄生虫杜氏利什曼原虫引起。由于缺乏有效的疫苗、药物毒性和寄生虫耐药性，因此需要鉴定新的药物靶点。基因组规模代谢模型的重建及其模拟已成为系统层面理解微生物代谢的重要工具。在这项工作中，将计算系统生物学的工具和技术与严格的人工编目相结合，开发了杜氏利什曼原虫BPK282A1的基于约束的代谢模型。针对18个先前假设或注释错误的基因（在模型的迭代优化过程中遇到）提出了新的功能注释。此外，为了制定准确的生物量目标函数，对先前未表征的生物量成分进行了实验测定。所开发的模型是一个高度分区的代谢模型，包含1159个反应、1135个代谢物和604个基因。该模型在预测基因敲除研究和药物抑制试验的实验表型方面表现出约76%的准确率。通过计算机模拟基因敲除研究，我们鉴定出28个与人类蛋白质序列同一性可忽略不计的必需基因。此外，通过剖析代谢途径的功能相互依赖性，鉴定出70对合成致死对。最后，为了描绘阶段特异性代谢，将驻留在人类巨噬细胞中的无鞭毛体阶段的基因表达数据整合到模型中。通过比较通量分布，我们阐明了代谢和环境条件的阶段特异性差异，这与实验结果高度一致。所开发的模型可以作为一个高度丰富的遗留数据库知识库和生成可实验验证假设的重要工具。
