文献类型：期刊文献

英文题名：Reconstruction of genome-scale metabolic model of Yarrowia lipolytica and its application in overproduction of triacylglycerol

作者：Wei, Songsong[1];Jian, Xingxing[1];Chen, Jun[1];Zhang, Cheng[1,2];Hua, Qiang[1,3]

机构：[1]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China;[2]KTH Royal Inst Technol, Sci Life Lab, SE-17121 Stockholm, Sweden;[3]Shanghai Collaborat Innovat Ctr Biomfg Technol, 130 Meilong Rd, Shanghai 200237, Peoples R China

年份：2017

卷号：4

期号：1

外文期刊名：BIORESOURCES AND BIOPROCESSING

收录：EI(收录号：20224513076830);WOS:【ESCI(收录号:WOS:000461105300051)】；

基金：This study was financially supported by National Natural Science Foundation of China (21776081, 21576089).

语种：英文

外文关键词：Yarrowia lipolytica; Genome-scale metabolic model; iYL_2.0; Triacylglycerol; Gene-level prediction targets

摘要：Background: Yarrowia lipolytica is widely studied as a non-conventional model yeast owing to the high level of lipid accumulation. Therein, triacylglycerol (TAG) is a major component of liposome. In order to investigate the TAG biosynthesis mechanism at a systematic level, a novel genome-scale metabolic model of Y lipolytica was reconstructed based on a previous model iYL619_PCP published by our lab and another model iYali4 published by Kerkhoven et al. Results: The novel model iYL_2.0 contains 645 genes, 1083 metabolites, and 1471 reactions, which was validated more effective on simulations of specific growth rate. The precision of 29 carbon sources utilities reached up to 96.6% when simulated by iYL_2.0. In minimal growth medium, 111 genes were identified as essential for cell growth, whereas 66 essential genes were identified in yeast extract medium, which were verified by database of essential genes, suggesting a better prediction ability of iYL_2.0 in comparison with other existing models. In addition, potential metabolic engineering targets of improving TAG production were predicted by three in silico methods developed in-house, and the effects of amino acids supplementation were investigated based on model iYL_2.0. Conclusions: The reconstructed model iYL_2.0 is a powerful platform for efficiently optimizing the metabolism of TAG and systematically understanding the physiological mechanism of Y. lipolytica.