Isarankura Na Ayudhya Nattapat, Laoteng Kobkul, Song Yuanda, Meechai Asawin, Vongsangnak Wanwipa
Department of Chemical Engineering, Faculty of Engineering, King Mongkut's Institute of Technology Thonburi, Bangkok, Thailand.
Functional Ingredients and Food Innovation Research Group, National Center for Genetic Engineering and Biotechnology (BIOTEC), National Sciences and Technology Development Agency (NSTDA), Khong Luang, Pathum Thani, Thailand.
PeerJ. 2019 Jun 7;7:e7015. doi: 10.7717/peerj.7015. eCollection 2019.
The genome-scale metabolic model of a lipid-overproducing strain of WJ11 was developed. The model (NI1159) contained 1,159 genes, 648 EC numbers, 1,537 metabolites, and 1,355 metabolic reactions, which were localized in different compartments of the cell. Using flux balance analysis (FBA), the NI1159 model was validated by predicting the specific growth rate. The metabolic traits investigated by phenotypic phase plane analysis (PhPP) showed a relationship between the nutrient uptake rate, cell growth, and the triacylglycerol production rate, demonstrating the strength of the model. A putative set of metabolic reactions affecting the lipid-accumulation process was identified when the metabolic flux distributions under nitrogen-limited conditions were altered by performing fast flux variability analysis (fastFVA) and relative flux change. Comparative analysis of the metabolic models of the lipid-overproducing strain WJ11 (NI1159) and the reference strain CBS277.49 (WV1213) using both fastFVA and coordinate hit-and-run with rounding (CHRR) showed that the flux distributions between these two models were significantly different. Notably, a higher flux distribution through lipid metabolisms such as lanosterol, zymosterol, glycerolipid and fatty acids biosynthesis in NI1159 was observed, leading to an increased lipid production when compared to WV1213. In contrast, WV1213 exhibited a higher flux distribution across carbohydrate and amino acid metabolisms and thus generated a high flux for biomass production. This study demonstrated that NI1159 is an effective predictive tool for the pathway engineering of oleaginous strains for the production of diversified oleochemicals with industrial relevance.
构建了产脂菌株WJ11的基因组规模代谢模型。该模型(NI1159)包含1159个基因、648个酶委员会编号、1537种代谢物和1355个代谢反应,这些分布于细胞的不同区室中。利用通量平衡分析(FBA),通过预测比生长速率对NI1159模型进行了验证。通过表型相平面分析(PhPP)研究的代谢特征显示了养分摄取率、细胞生长和三酰甘油生产率之间的关系,证明了该模型的优势。通过进行快速通量变异性分析(fastFVA)和相对通量变化,改变氮限制条件下的代谢通量分布时,确定了一组影响脂质积累过程的假定代谢反应。使用fastFVA和带舍入的坐标随机游走(CHRR)对产脂菌株WJ11(NI1159)和参考菌株CBS277.49(WV1213)的代谢模型进行比较分析,结果表明这两个模型之间的通量分布存在显著差异。值得注意的是,观察到NI1159中通过羊毛甾醇、酵母甾醇、甘油脂和脂肪酸生物合成等脂质代谢的通量分布更高,与WV1213相比,脂质产量增加。相比之下,WV1213在碳水化合物和氨基酸代谢中表现出更高的通量分布,因此产生了用于生物量生产的高通量。本研究表明,NI1159是用于工程改造产油菌株以生产具有工业相关性的多种油脂化学品的有效预测工具。