文献类型：期刊文献

英文题名：Metabolome analysis and pathway abundance profiling of Yarrowia lipolytica cultivated on different carbon sources

作者：Zhao, Chen[1];Gu, Deqing[1];Nambou, Komi[1];Wei, Liujing[1];Chen, Jun[1];Imanaka, Tadayuki[1];Hua, Qiang[1,2]

机构：[1]E China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China;[2]SCICBT, Shanghai 200237, Peoples R China

年份：2015

卷号：206

起止页码：42

外文期刊名：JOURNAL OF BIOTECHNOLOGY

收录：;EI(收录号：20151800804801);WOS:【SCI-EXPANDED(收录号:WOS:000355090900007)】；

基金：This work was financially supported by National Basic Research Program of China (973 Program) (2012CB721101) and National Special Fund for State Key Laboratory of Bioreactor Engineering (2060204).

语种：英文

外文关键词：Yarrowia lipolytica; Metabolomics; Pathway abundance; Carbon sources; Lipid production

摘要：Yarrowia lipolytica, a model microorganism of oleaginous yeasts with developed sophisticated genetic tools, is able to metabolize a wide range of substrates and accumulate large amounts of lipids. However, there is a lack of literature reporting the metabolic characteristics of Y. lipolytica metabolizing these substrates in a systematic view. In this study, Y. lipolytica was cultivated on a variety of carbon sources, among which cell growth and production characteristics on two representative substrates (glucose and oleic acid) were investigated in detail at metabolomic level. Metabolic pathway abundance was computed to interpret the metabolome data in a straightforward way. The results showed that most pathway abundances decreased in the shift from growth to production phase. Specifically, when cultivated on glucose, abundances of twelve pathways decreased markedly between the growth and lipid production phases, while thirteen pathways reduced and only three pathways increased significantly in abundances on oleic acid. In comparison, for the same cultivation phase only a few pathways exhibited significant changes between glucose-grown and oleic acid-grown cells. This study revealed that the pathway abundance could be used to effectively show the activity changes of pathways, providing a new perspective to employ metabolomics data for understanding cell metabolism and enhancing the production of target metabolites. (C) 2015 Elsevier B.V. All rights reserved.