Dissecting the metabolic reprogramming of maize root under nitrogen-deficient stress conditions

被引:12
|
作者
Chowdhury, Niaz Bahar [1 ]
Schroeder, Wheaton L. [1 ]
Sarkar, Debolina [2 ]
Amiour, Nardjis [3 ]
Quillere, Isabelle [3 ]
Hirel, Bertrand [3 ]
Maranas, Costas D. [2 ]
Saha, Rajib [1 ,4 ]
机构
[1] Univ Nebraska, Dept Chem & Biomol Engn, Lincoln, NE 68588 USA
[2] Penn State Univ, Dept Chem Engn, University Pk, PA 16802 USA
[3] Ctr Versailles Grignon, Inst Natl Rech Agriculure Alimentat & Envionnemen, RD 10, F-78026 Versailles, France
[4] Univ Nebraska, Ctr Root & Rhizobiome Innovat, Lincoln, NE USA
基金
美国国家科学基金会;
关键词
Abiotic stress; genome-scale metabolic modeling; maize root; metabolomics; nitrogen-deficient stress; transcriptomics; FLUX BALANCE ANALYSIS; AMINO-ACIDS; CARBON METABOLISM; OSMOTIC-STRESS; ACCUMULATION; ARABIDOPSIS; ADAPTATION; NETWORK; PLANTS; MODEL;
D O I
10.1093/jxb/erab435
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
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.
引用
收藏
页码:275 / 291
页数:17
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