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通过代谢建模解析盐胁迫下水稻代谢通量重编程

Deciphering rice metabolic flux reprograming under salinity stress via metabolic modeling.

作者信息

Wanichthanarak Kwanjeera, Boonchai Chuthamas, Kojonna Thammaporn, Chadchawan Supachitra, Sangwongchai Wichian, Thitisaksakul Maysaya

机构信息

Siriraj Metabolomics and Phenomics Center, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand.

Metabolomics and Systems Biology, Department of Biochemistry, Faculty of Medicine Siriraj Hospital, Mahidol University, Bangkok 10700, Thailand.

出版信息

Comput Struct Biotechnol J. 2020 Nov 20;18:3555-3566. doi: 10.1016/j.csbj.2020.11.023. eCollection 2020.

Abstract

Rice is one of the most economically important commodities globally. However, rice plants are salt susceptible species in which high salinity can significantly constrain its productivity. Several physiological parameters in adaptation to salt stress have been observed, though changes in metabolic aspects remain to be elucidated. In this study, rice metabolic activities of salt-stressed flag leaf were systematically characterized. Transcriptomics and metabolomics data were combined to identify disturbed pathways, altered metabolites and metabolic hotspots within the rice metabolic network under salt stress condition. Besides, the feasible flux solutions in different context-specific metabolic networks were estimated and compared. Our findings highlighted metabolic reprogramming in primary metabolic pathways, cellular respiration, antioxidant biosynthetic pathways, and phytohormone biosynthetic pathways. Photosynthesis and hexose utilization were among the major disturbed pathways in the stressed flag leaf. Notably, the increased flux distribution of the photorespiratory pathway could contribute to cellular redox control. Predicted flux statuses in several pathways were consistent with the results from transcriptomics, end-point metabolomics, and physiological studies. Our study illustrated that the contextualized genome-scale model together with multi-omics analysis is a powerful approach to unravel the metabolic responses of rice to salinity stress.

摘要

水稻是全球经济上最重要的农作物之一。然而,水稻植株是盐敏感型物种,高盐度会显著限制其生产力。尽管已经观察到一些适应盐胁迫的生理参数,但代谢方面的变化仍有待阐明。在本研究中,对盐胁迫下剑叶的水稻代谢活动进行了系统表征。结合转录组学和代谢组学数据,以识别盐胁迫条件下水稻代谢网络中受干扰的途径、变化的代谢物和代谢热点。此外,还估计并比较了不同背景特异性代谢网络中的可行通量解。我们的研究结果突出了初级代谢途径、细胞呼吸、抗氧化剂生物合成途径和植物激素生物合成途径中的代谢重编程。光合作用和己糖利用是受胁迫剑叶中主要的受干扰途径。值得注意的是,光呼吸途径通量分布的增加可能有助于细胞氧化还原控制。几个途径中的预测通量状态与转录组学、终点代谢组学和生理学研究的结果一致。我们的研究表明,情境化的基因组规模模型与多组学分析相结合是揭示水稻对盐胁迫代谢响应的有力方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bbe0/7708941/57961166c4db/gr1.jpg

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