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BIOTECHNOL BIOE: 储炬课题组优化重建黑曲霉菌株的全基因组网络模型

2016年5月17日,国际期刊《Biotechnology and Bioengineering》上在线发表了华东理工大学国家重点实验室、国家生化工程技术研究中心(上海)储炬教授课题组题为”Comprehensive reconstruction and in silico analysis of Aspergillus niger genome-scale metabolic network model that accounts for 1210 ORFs” 的研究论文。博士研究生(现瑞典查尔姆斯大学Jens Nielsen教授课题组博士后)鲁洪中为论文第一作者,储炬教授为论文通讯作者。相关研究为与荷兰DSM集团共同开展,并且受益于国家生化工程技术研究中心(上海)与华大基因的合作项目辐射。

黑曲霉作为一种常见的且最为重要的细胞工厂,为工业生物过程及大宗生物产品提供了重要的发酵体系,常见的生产产品包括淀粉酶、有机酸等。而全基因组代谢网络模型(GSMM)的建立无疑为这一重要菌株的机理研究及合成生物学研究奠定了基础。GSMM的构建是一项复杂且繁琐的工作,需要对基因测序后产生的大量数据进行分析处理,对开放阅读框架进行辨识,同时需要准确定义相关反应中的元素、ATP及还原力守衡。

鲁洪中等基于先期的研究成果,在iMA871模型上进行优化,主要的优化方向包括代谢反应的元素守衡及基因-蛋白-反应相关性(Gene-Protein-Reaction associations,GPRs),相关反应数由1380增加至1764,开放阅读框架由871增加至1210。同时,通过额外的转录组学分析,68%的反应与63%的开放阅读框架可以被准确定义。建立的模型经过了恒化动力学验证及同位素13C代谢流分析验证,保证了新构建的iHL1210模型的可靠性。

原文链接:
http://onlinelibrary.wiley.com/doi/10.1002/bit.26195/full
DOI: 10.1002/bit.26195

原文摘要:

Aspergillus niger is one of the most important cell factories for industrial enzymes and organic acids production. A comprehensive genome-scale metabolic network model (GSMM) with high quality is crucial for efficient strain improvement and process optimization. The lack of accurate reaction equations and gene-protein-reaction associations (GPRs) in the current best model of A. niger named GSMM iMA871, however, limits its application scope. To overcome these limitations, we updated the A. niger GSMM by combining the latest genome annotation and literature mining technology. Compared with iMA871, the number of reactions in iHL1210 was increased from 1,380 to 1,764, and the number of unique ORFs from 871 to 1,210. With the aid of our transcriptomics analysis, the existence of 63% ORFs and 68% reactions in iHL1210 can be verified when glucose was used as the only carbon source. Physiological data from chemostat cultivations, 13C-labeled and molecular experiments from the published literature were further used to check the performance of iHL1210. The average correlation coefficients between the predicted fluxes and estimated fluxes from 13C-labeling data were sufficiently high (above 0.89) and the prediction of cell growth on most of the reported carbon and nitrogen sources was consistent. Using the updated genome-scale model, we evaluated gene essentiality on synthetic and yeast extract medium, as well as the effects of NADPH supply on glucoamylase production in A. niger. In summary, the new A. niger GSMM iHL1210 contains significant improvements with respect to the metabolic coverage and prediction performance, which paves the way for systematic metabolic engineering of A. niger.
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