2016年5月17日，國際期刊《Biotechnology and Bioengineering》上在線發(fā)表了華東理工大學國家重點實驗室、國家生化工程技術研究中心（上海）儲炬教授課題組題為”Comprehensive reconstruction and in silico analysis of Aspergillus niger genome-scale metabolic network model that accounts for 1210 ORFs” 的研究論文。博士研究生（現(xiàn)瑞典查爾姆斯大學Jens Nielsen教授課題組博士后）魯洪中為論文第一作者，儲炬教授為論文通訊作者。相關研究為與荷蘭DSM集團共同開展，并且受益于國家生化工程技術研究中心（上海）與華大基因的合作項目輻射。
黑曲霉作為一種常見的且最為重要的細胞工廠，為工業(yè)生物過程及大宗生物產品提供了重要的發(fā)酵體系，常見的生產產品包括淀粉酶、有機酸等。而全基因組代謝網絡模型（GSMM）的建立無疑為這一重要菌株的機理研究及合成生物學研究奠定了基礎。GSMM的構建是一項復雜且繁瑣的工作，需要對基因測序后產生的大量數(shù)據進行分析處理，對開放閱讀框架進行辨識，同時需要準確定義相關反應中的元素、ATP及還原力守衡。
魯洪中等基于先期的研究成果，在iMA871模型上進行優(yōu)化，主要的優(yōu)化方向包括代謝反應的元素守衡及基因-蛋白-反應相關性（Gene-Protein-Reaction associations，GPRs），相關反應數(shù)由1380增加至1764，開放閱讀框架由871增加至1210。同時，通過額外的轉錄組學分析，68%的反應與63%的開放閱讀框架可以被準確定義。建立的模型經過了恒化動力學驗證及同位素13C代謝流分析驗證，保證了新構建的iHL1210模型的可靠性。
原文鏈接：
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.
