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基于非靶标代谢组学方法研究水稻种子的代谢物轮廓
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作者单位
王希越,明明,田媛媛,李有良,连丽丽,娄大伟 吉林化工学院化学与制药工程学院 
基金项目:国家自然科学基金(21375046,21605056);吉林省科技发展计划项目(20140203013GX)
中文摘要:建立了一种基于气相色谱-质谱联用的非靶标代谢组学方法,研究了不同品种水稻种子之间的代谢物差异。分别考察了3种提取方式及4种提取溶剂对水稻中代谢物提取效率的影响,发现涡旋提取方法及80%甲醇提取可获得较好的结果,该方法具有良好的稳定性和线性。将方法用于3种水稻种子(农大、稻花香、状元)的代谢轮廓分析,结果显示3种水稻的代谢特征不同。相对于农大种子,稻花香种子中脂肪酸(棕榈酸、油酸、亚油酸、硬脂酸)和糖类(葡萄糖、半乳糖、甘露醇)、天冬酰胺、柠檬酸的含量较高,此外,状元种子中乳酸含量也较高;稻花香种子中琥珀酸、果糖,状元种子中的苏氨酸含量低于农大种子。但相对于状元种子,稻花香中乳酸、琥珀酸、硬脂酸、果糖等物质含量较低。该方法可应用于不同品种、不同基因型或不同产地水稻种子的代谢表型分析,为改善水稻产量及质量等研究提供信息。
中文关键词:水稻  非靶标代谢组学  气相色谱-质谱联用  代谢表型
 
Investigation on Metabolite Profiling of Rice Seed by Non-targeted Metabolomics Method
Abstract:A non-targeted metabolomics method for investigation on metabolite profiling of rice seed was developed based on gas chromatography-mass spectrometry.The extraction efficiencies of three extraction methods and four extraction solvents were investigated.Results showed that vortex and methanol-water(80∶20,by volume) were highly efficient for metabolites extraction from rice.With good stability and linearity,This method was applied in investigation on metabolite profiling of rice,including Nongda,Daohuaxiang and Zhuangyuan.It was found that they have different metabolic phenotype.Compared with Nongda,Daohuaxiang contained more contents of hexadecanoic acid,oleic acid,linoleic acid,octadecanoic acid,glucose,galactose,mannitol,asparagine and citric acid,and Zhuangyuan also had more lactic acid.Nevertheless,Nongda had more succinic acid and fructose than daohuaxiang,and more threonine than Zhuangyuan.And the contents of lactic acid,succinic acid,octadecanoic acid and fructose in Daohuaxiang were lower than those in Zhuangyuan.The developed method could be used for investigation on the metabolic phenotype of rice with different types,genotypes or habitats.It was expected to provide useful information for improving rice production and quality.
Key Words:rice  non-targeted metabolomics  gas chromatography coupled with mass spectrometry  metabolic phenotype
引用本文:王希越,明明,田媛媛,李有良,连丽丽,娄大伟.基于非靶标代谢组学方法研究水稻种子的代谢物轮廓[J].分析测试学报,2018,37(3):341-345.
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