Dissecting the metabolic reprogramming of maize root under nitrogen-deficient stress conditions
Dissecting the metabolic reprogramming of maize root under nitrogen-deficient stress conditions
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DOI：
10.1093/jxb/erab435
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发表时间：
2021-09-23
影响因子：
6.9
通讯作者：
Saha, Rajib
中科院分区：
文献类型：
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作者：
Chowdhury, Niaz Bahar;Schroeder, Wheaton L.;Saha, Rajib
玉米(Zea Mays L.)这在很大程度上取决于它通过根部吸收的养分。因此，研究其生长、反应及相关的代谢重编程对应激条件的影响正成为一个重要的研究方向。为研究玉米根系在氮素胁迫条件下的代谢重编程，建立了玉米根系基因组水平的代谢模型。根据KEGG、UniProt和MaizeCyc提供的信息重建了模型。从水培玉米植株的根中获得的转录组分数据被用来在模型中加入调控约束，并模拟无氮限制(N+)和缺氮(N-)条件。模型预测的通量和变异性分析与代谢物水平的实验变化相比，准确率达到70%。除了预测中心碳、脂肪酸、氨基酸和其他次生代谢的重要代谢重排外，玉米根GSM还预测了几种代谢产物(L-蛋氨酸、L-天冬酰胺、L-赖氨酸、胆固醇和L-吡咯烷酸酯)在根生物量生长中发挥调节作用。此外，本研究还揭示了8种磷脂酰胆碱和磷脂酰甘油的代谢产物，它们即使不与生物量的生产相结合，也在缺氮条件下生物量的增加中发挥了关键作用。总体而言，整合了组学的GSM为玉米根部的逆境条件分析和设计更好的抗逆性玉米基因型提供了一个很有前途的工具。
The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N-) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes.