Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling

© 2020 The Author(s) 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 ch...

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Main Authors: Kwanjeera Wanichthanarak, Chuthamas Boonchai, Thammaporn Kojonna, Supachitra Chadchawan, Wichian Sangwongchai, Maysaya Thitisaksakul
Other Authors: Chulalongkorn University
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Published: 2020
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Online Access:https://repository.li.mahidol.ac.th/handle/123456789/60414
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spelling th-mahidol.604142020-12-28T11:58:16Z Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling Kwanjeera Wanichthanarak Chuthamas Boonchai Thammaporn Kojonna Supachitra Chadchawan Wichian Sangwongchai Maysaya Thitisaksakul Chulalongkorn University Khon Kaen University Faculty of Medicine, Siriraj Hospital, Mahidol University Biochemistry, Genetics and Molecular Biology Computer Science © 2020 The Author(s) 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. 2020-12-28T04:27:56Z 2020-12-28T04:27:56Z 2020-01-01 Article Computational and Structural Biotechnology Journal. Vol.18, (2020), 3555-3566 10.1016/j.csbj.2020.11.023 20010370 2-s2.0-85096865058 https://repository.li.mahidol.ac.th/handle/123456789/60414 Mahidol University SCOPUS https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85096865058&origin=inward
institution Mahidol University
building Mahidol University Library
continent Asia
country Thailand
Thailand
content_provider Mahidol University Library
collection Mahidol University Institutional Repository
topic Biochemistry, Genetics and Molecular Biology
Computer Science
spellingShingle Biochemistry, Genetics and Molecular Biology
Computer Science
Kwanjeera Wanichthanarak
Chuthamas Boonchai
Thammaporn Kojonna
Supachitra Chadchawan
Wichian Sangwongchai
Maysaya Thitisaksakul
Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling
description © 2020 The Author(s) 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.
author2 Chulalongkorn University
author_facet Chulalongkorn University
Kwanjeera Wanichthanarak
Chuthamas Boonchai
Thammaporn Kojonna
Supachitra Chadchawan
Wichian Sangwongchai
Maysaya Thitisaksakul
format Article
author Kwanjeera Wanichthanarak
Chuthamas Boonchai
Thammaporn Kojonna
Supachitra Chadchawan
Wichian Sangwongchai
Maysaya Thitisaksakul
author_sort Kwanjeera Wanichthanarak
title Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling
title_short Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling
title_full Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling
title_fullStr Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling
title_full_unstemmed Deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling
title_sort deciphering rice metabolic flux reprograming under salinity stress via in silico metabolic modeling
publishDate 2020
url https://repository.li.mahidol.ac.th/handle/123456789/60414
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