数字农科院2.0

Comparative Metabolic Profiling of Different Colored Rice Grains Reveals the Distribution of Major Active Compounds and Key Secondary Metabolites in Green Rice

文献类型: 外文期刊

作者: Zhao, Mingchao;Zhai, Linan;Tang, Qingjie;Ren, Junfang;Zhou, Shizhen;Wang, Huijian;Yun, Yong;Yang, Qingwen;Yan, Xiaowei;Xing, Funeng;Qiao, Weihua

作者机构:

关键词: pigmented rice;bioactive compounds;LC-MS;vitamin;metabolomics

期刊名称: FOODS

ISSN:

年卷期: 2024 年 13 卷 12 期

页码:

收录情况: SCIE(2024版)

摘要: Pigmented rice grains are important resources for health and nutritional perspectives. Thus, a thorough dissection of the variation of nutrients and bioactive metabolites in different colored rice is of global interest. This study applied LC-MS-based widely targeted metabolite profiling and unraveled the variability of metabolites and nutraceuticals in long grain/non-glutinous black (BR), red (RR), green (GR), and white rice (WR) grains. We identified and classified 1292 metabolites, including five flavonoid compounds specific to BR. The metabolite profiles of the four rice grains showed significant variation, with 275-543 differentially accumulated metabolites identified. Flavonoid (flavone, flavonol, and anthocyanin) and cofactor biosynthesis were the most differentially regulated pathways among the four rice types. Most bioactive flavonoids, anthocyanidins (glycosylated cyanidins and peonidins), phenolic acids, and lignans had the highest relative content in BR, followed by RR. Most alkaloids, amino acids and derivatives, lipids, and vitamins (B6, B3, B1, nicotinamide, and isonicotinic acid) had higher relative contents in GR than others. Procyanidins (B1, B2, and B3) had the highest relative content in RR. In addition, we identified 25 potential discriminatory biomarkers, including fagomine, which could be used to authenticate GR. Our results show that BR and RR are important materials for medicinal use, while GR is an excellent source of nutrients (amino acids and vitamins) and bioactive alkaloids. Moreover, they provide data resources for the science-based use of different colored rice varieties in diverse industries.

分类号:

  • 相关文献

[1]Metabolomic Insights into Primary and Secondary Metabolites Variation in Common and Glutinous Rice (Oryza sativa L.). Mingchao Zhao,Jingfen Huang,Junfang Ren,Xiaorong Xiao,Yapeng Li,Linan Zhai,Xiaowei Yan,Yong Yun,Qingwen Yang,Qingjie Tang,Funeng Xing,Weihua Qiao. 2024

[2]Nontargeted Analysis Using Ultraperformance Liquid Chromatography-Quadrupole Time-of-Flight Mass Spectrometry Uncovers the Effects of Harvest Season on the Metabolites and Taste Quality of Tea (Camellia sinensis L.). Dai, Weidong,Qi, Dandan,Yang, Ting,Lv, Haipeng,Guo, Li,Zhang, Yue,Zhu, Yin,Peng, Qunhua,Xie, Dongchao,Tan, Junfeng,Lin, Zhi.

[3]Nontargeted Modification-Specific Metabolomics Investigation of Glycosylated Secondary Metabolites in Tea (Camellia sinensis L.) Based on Liquid Chromatography-High-Resolution Mass Spectrometry. Dai, Weidong,Tan, Junfeng,Xie, Dongchao,Li, Pengliang,Lv, Haipeng,Zhu, Yin,Guo, Li,Zhang, Yue,Peng, Qunhua,Lin, Zhi,Lu, Meiling.

[4]Characterization of white tea metabolome: Comparison against green and black tea by a nontargeted metabolomics approach. Dai, Weidong,Xie, Dongchao,Li, Pengliang,Lv, Haipeng,Yang, Chen,Peng, Qunhua,Zhu, Yin,Guo, Li,Zhang, Yue,Tan, Junfeng,Lin, Zhi,Lu, Meiling.

[5]Study of the dynamic changes in the non-volatile chemical constituents of black tea during fermentation processing by a non-targeted metabolomics approach. Tan, Junfeng,Dai, Weidong,Lv, Haipeng,Guo, Li,Zhang, Yue,Zhu, Yin,Peng, Qunhua,Lin, Zhi,Lu, Meiling.

[6]Metabolomic characterization of the chemical compositions of Dracocephalum rupestre Hance. Jianjian Gao,Zhe Wang,Dan Chen,Jiakun Peng,Dongchao Xie,Zhiyuan Lin,Zhi Lin,Weidong Dai. 2022

[7]Nontargeted and targeted metabolomics analysis provides novel insight into nonvolatile metabolites in Jianghua Kucha tea germplasm (Camellia sinensis var. Assamica cv. Jianghua). Wenliang Wu,Meiling Lu,Jiakun Peng,Haipeng Lv,Jiang Shi,Shuguang Zhang,Zhen Liu,Jihua Duan,Dan Chen,Weidong Dai,Zhi Lin. 2022

[8]Identification of altered metabolic functional components using metabolomics to analyze the different ages of fruiting bodies of Sanghuangporus vaninii cultivated on cut log substrates. Xu, Congtao,Zhao, Shuang,Li, Zihao,Pan, Jinlong,Zhou, Yuanyuan,Hu, Qingxiu,Zou, Yajie. 2023

[9]Widely targeted metabolic profiling provides insights into variations in bioactive compounds and antioxidant activity of sesame, soybean, peanut, and perilla. Habtamu Kefale,Senouwa Segla Koffi Dossou,Feng Li,Nanjun Jiang,Rong Zhou,Lei Wang,Yanxin Zhang,Donghua Li,Jun You,Linhai Wang. 2023

[10]Metabolomic insights into pigment and bioactive metabolite alterations in Eucommia ulmoides leaves: A comparison between new variety and wild-type varieties. Tiannuo Hong,Jiayu Gu,Lu Chen,Xiaolu Wang,Libin Zhou,Xuehu Li,Wenke Bai,Linqi Gao,Xiaodong Li,Guangming Zhao,Juan Han,Luxiang Liu. 2025

[11]Comprehensive analysis of freeze-dried and sun-dried daylily in craft beer: Effects of addition levels on physicochemical properties, bioactivity, metabolomics, and volatile compounds. Yuwen Mu,Yonggang Wang,Yulong Ni,Shiyu Zhang,Jianbin Yang,Chaozhen Zeng. 2025

[12]控水处理对紫花苜蓿抗寒性影响的代谢组学分析. 徐洪雨,李向林. 2020

[13]基于分子印迹技术与液相色谱-质谱联用的抗病毒中药有效成分筛选方法学研究. 杨亚军,刘希望,刘玉荣,李冰,张继瑜,李剑勇. 2015

[14]二恶英暴露下奶牛血液代谢组学研究. 胡晓旭,许彤,陈旸升,谢群慧,郝艳芬,王楚,程劼,王璞,张庆华,徐丽,赵斌. 2022

[15]Deciphering the Genetic Architecture of Color Variation in Whole Grain Rice by Genome-Wide Association. Wenjun Wang,Xianjin Qiu,Ziqi Wang,Tianyi Xie,Wenqiang Sun,Jianlong Xu,Fan Zhang,Sibin Yu. 2023

[16]Comparative analysis of rice reveals insights into the mechanism of colored rice via widely targeted metabolomics. Lina Zhang,Di Cui,Xiaoding Ma,Bing Han,Longzhi Han. 2022

[17]Composition and Biological Activity of Colored Rice-A Comprehensive Review. Zhao, Mingchao,Xiao, Xiaorong,Jin, Dingsha,Zhai, Linan,Li, Yapeng,Yang, Qingwen,Xing, Funeng,Qiao, Weihua,Yan, Xiaowei,Tang, Qingjie. 2025

[18]Characterization and feature selection of volatile metabolites in Yangxian pigmented rice varieties through GC-MS and machine learning algorithms. Cheng, Kaiqi,Dong, Ruonan,Pan, Fei,Su, Wen,Xi, Lingjie,Zhang, Meng,Geng, Jingzhang,Gao, Ruichang,Jin, Wengang,Abd El-Aty, A. M.. 2025

[19]MINERAL, VITAMIN AND FATTY ACID CONTENTS IN THE CAMEL MILK OF DROMEDARIES IN THE ANXI GANSU CHINA. Liang, J. P.,Wang, S. Y.,Shao, W. J.,Wen, H.,Wang, S. Y.. 2011

[20]Gut microbiota bridges dietary nutrients and host immunity. Fan, Lijuan,Xia, Yaoyao,Wang, Youxia,Han, Dandan,Liu, Yanli,Li, Jiahuan,Fu, Jie,Wang, Leli,Gan, Zhending,Liu, Bingnan,Fu, Jian,Zhu, Congrui,Wu, Zhenhua,Zhao, Jinbiao,Han, Hui,Wu, Hao,He, Yiwen,Tang, Yulong,Zhang, Qingzhuo,Wang, Yibin,Zhang, Fan,Zong, Xin,Yin, Jie,Zhou, Xihong,Yang, Xiaojun,Wang, Junjun,Yin, Yulong,Ren, Wenkai. 2023

作者其他论文 更多>>