Comparative metabolomic profiling reveals salinity tolerance mechanisms in a rice introgression line.

IF 3.5 3区 医学 Q2 ENDOCRINOLOGY & METABOLISM
Chander Kant Chaudhary, Praveen Kumar Guttula, Kirti Agrawal, Prasanta Kumar Subudhi, Manas Ranjan Gartia
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Abstract

Introduction: Rice (Oryza sativa) is extremely sensitive to salinity, yet the metabolic mechanisms underlying salt tolerance remains incompletely understood.

Objective: In this study, we performed leaf tissue-specific untargeted metabolomic profiling of the salt-tolerant introgression line JN100 (JN), its donor parent Nona Bokra (NB), and its recurrent parent Jupiter (JU) to characterize metabolic responses to salt stress.

Results and conclusions: Comparative analysis identified differentially accumulated metabolites (DAMs) spanning diverse chemical classes, including amino acids, sugars and carbohydrates, lipids, organic acids, cofactors, electron carriers, and nucleotides. Under salt stress (SS), 201 DAMs (89 upregulated and 112 downregulated) were detected in JN relative to JU. Notably, metabolites such as allantoin, glycitin, nicotinamide ribotide, D-arabinono-1,4-lactone, violanthin, L-methionine S-oxide, ribitol, lysine, rutin, glutamine, pantothenic acid, and quinic acid, showed significant differential accumulation. Pathway enrichment analysis revealed significant enrichment of arginine biosynthesis, purine metabolism, and alanine, aspartate, and glutamate metabolism, indicating extensive reprogramming of nitrogen and energy-associated metabolic pathways under salinity stress. Integration of transcriptomic and metabolomic datasets from the SS experiments further identified ten differentially expressed genes (DEGs) associated with the metabolite network in the JN vs. JU comparison. Among these, OsDHQDT/SDH, OsFd-GOGAT, phenylalanyl-tRNA synthetase, OsP5CS1, OsP5CS2, and a pyridoxal phosphate-dependent transferase were linked to metabolites involved in shikimate, amino acid, and proline metabolism.

比较代谢组学分析揭示了水稻渗入系的耐盐机制。
水稻(Oryza sativa)对盐极其敏感,但其耐盐代谢机制尚不完全清楚。目的:在本研究中,我们对耐盐基因渗入系JN100 (JN)及其供体亲本Nona Bokra (NB)和复发亲本Jupiter (JU)进行了叶片组织特异性非靶向代谢组学分析,以表征其对盐胁迫的代谢反应。结果和结论:比较分析确定了不同化学类别的差异积累代谢物(dam),包括氨基酸、糖和碳水化合物、脂类、有机酸、辅助因子、电子载体和核苷酸。在盐胁迫(SS)下,JN中有201个dam,其中89个上调,112个下调。值得注意的是,尿囊素、胰甘素、烟酰胺核糖肽、d -阿拉伯豆-1,4-内酯、紫堇素、l -蛋氨酸s -氧化物、利比醇、赖氨酸、芦丁、谷氨酰胺、泛酸和奎宁酸等代谢物均表现出显著的差异积累。途径富集分析显示,精氨酸生物合成、嘌呤代谢、丙氨酸、天冬氨酸和谷氨酸代谢显著富集,表明盐度胁迫下氮和能量相关代谢途径广泛重编程。整合来自SS实验的转录组学和代谢组学数据集,进一步确定了JN和JU比较中与代谢物网络相关的10个差异表达基因(DEGs)。其中,OsDHQDT/SDH、OsFd-GOGAT、苯丙酰trna合成酶、OsP5CS1、OsP5CS2和吡哆醛磷酸依赖性转移酶与参与草酸盐、氨基酸和脯氨酸代谢的代谢物有关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Metabolomics
Metabolomics 医学-内分泌学与代谢
CiteScore
6.60
自引率
2.80%
发文量
84
审稿时长
2 months
期刊介绍: Metabolomics publishes current research regarding the development of technology platforms for metabolomics. This includes, but is not limited to: metabolomic applications within man, including pre-clinical and clinical pharmacometabolomics for precision medicine metabolic profiling and fingerprinting metabolite target analysis metabolomic applications within animals, plants and microbes transcriptomics and proteomics in systems biology Metabolomics is an indispensable platform for researchers using new post-genomics approaches, to discover networks and interactions between metabolites, pharmaceuticals, SNPs, proteins and more. Its articles go beyond the genome and metabolome, by including original clinical study material together with big data from new emerging technologies.
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