JOURNAL ARTICLE
Transcriptomic and metabolomic analysis reveals that symbiotic nitrogen fixation enhances drought resistance in common bean.
Published In: Journal of Experimental Botany, 2023, v. 74, n. 10. P. 3203 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: López, Cristina Mª; Alseekh, Saleh; Torralbo, Fernando; Rivas, Félix J Martínez; Fernie, Alisdair R; Amil-Ruiz, Francisco; Alamillo, Josefa M 3 of 3
Abstract
This article investigates how the nitrogen source—symbiotic atmospheric nitrogen fixation (N₂ fixation) versus nitrate (NO₃⁻) fertilization—affects drought response in common bean (Phaseolus vulgaris L.), a key legume crop sensitive to water deficit. Using integrated transcriptomic and metabolomic analyses, the study found that although nitrate-fertilized plants exhibited more extensive gene expression changes under drought, N₂-fixing plants showed molecular and metabolic profiles more closely associated with drought tolerance, including higher accumulation of ureides, abscisic acid (ABA), proline, raffinose, amino acids, sphingolipids, and triacylglycerols. Physiologically, N₂-fixing plants maintained leaf relative water content better, exhibited stronger antioxidant enzyme activities, and recovered photosynthetic function and yield more effectively after drought compared to nitrate-fertilized plants. These findings suggest that symbiotic nitrogen fixation enhances drought resilience in common bean through coordinated molecular, metabolic, and physiological mechanisms, supporting its role in sustainable agriculture under water-limited conditions.
Additional Information
- Source:Journal of Experimental Botany. 2023/05, Vol. 74, Issue 10, p3203
- Document Type:Article
- Subject Area:Agriculture and Agribusiness
- Publication Date:2023
- ISSN:0022-0957
- DOI:10.1093/jxb/erad083
- Accession Number:163826745
- Copyright Statement:Copyright of Journal of Experimental Botany is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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