Scientia Agricultura Sinica ›› 2019, Vol. 52 ›› Issue (18): 3163-3176.doi: 10.3864/j.issn.0578-1752.2019.18.009

• Standard and Evaluation Research • Previous Articles     Next Articles

Review on the Application of Metabolomic Approaches to Investigate and Analysis the Nutrition and Quality of Agro-Products

XU YanYang1,YAO GuiXiao1,3,LIU PingXiang1,ZHAO Jie1,WANG XinLu1,SUN JunMao2(),QIAN YongZhong1()   

  1. 1. Institute of Quality Standards and Testing Technology for Agro-Products, Chinese Academy of Agricultural Sciences/Key Laboratory of Agro-Product Quality and Safety, Ministry of Agriculture and Rural Affairs, Beijing 100081
    2. Institute of Food and Nutrition Development, Ministry of Agriculture and Rural Affairs, Beijing 100081
    3. Xi’an University of Technology, Xi’an 710048;
  • Received:2019-02-22 Accepted:2019-04-23 Online:2019-09-16 Published:2019-09-23
  • Contact: JunMao SUN,YongZhong QIAN E-mail:sunjunmao@caas.cn;qianyongzhong@caas.cn

Abstract:

Scientific evaluation of the nutrition and quality of agricultural products is essential for improving the nutrition level of agro-products. Because of the complex composition of nutrients in agro-products, the existing analytical methods can only analyze the concentration and function of known nutrients but cannot analyze and identify a large number of unknown functional substances. On the basis of high-throughput chemical analyses, metabolomics can qualitatively and quantitatively analyze endogenous and exogenous metabolites of biological samples. Therefore, metabolomics has outstanding advantages in the analysis of small molecular substances with special nutritional functions in agricultural products; it has advantages like providing new methods for the characterization and differential analysis of nutrient components, traceability and authenticity of identification, variation analysis of functional substances during growth and storage, and the effect mechanisms of functional components. It also provides new strategies for structural optimization of dietary requirements. In this paper, the recent advances in metabolomics research, including sample preparation, metabolite analysis, data processing, differential metabolite identification, and metabolic pathway analysis were reviewed. This work summed up the application of metabolomics in the characterization and difference analysis of metabolites, traceability and authenticity identification of origin, metabolite variation in the process of storage, and the evaluation of nutritional functions to provide theoretical bases and practical references for high-quality agricultural development in China. In the field of sample preparation, the activity of metabolism-related enzymes is first terminated by rapidly changing the environmental conditions, such as adding strong acid (alkali) or freezing in liquid nitrogen. Different extraction solvents are selected based on the polarities of the metabolites to obtain a higher extraction rate. In the field of sample analysis methods, technologies, such as nuclear magnetic resonance spectroscopy, chromatography mass spectrometry and capillary electrophoresis-mass spectrometry, have been widely used. Among them, the combination of chromatography and mass spectrometry has become the most commonly used analytical technique in metabolomics. In the field of data processing and analysis, principal component analysis and orthogonal partial least squares-discriminant analysis are the most common data analysis techniques. Through enrichment and topological analysis, the metabolic pathway with the highest correlation to differential metabolites can be identified, and the reason of differential metabolites can be explained and analyzed. In the field of evaluation of nutrition and quality of agricultural products, through the comprehensive characterization of primary metabolites and secondary metabolites in agricultural products, unique fingerprints of agricultural products are established and used for differential analysis, whereas through non-specific target analysis and unsupervised analysis methods, differences between groups and relating metabolites can be identified. Via concentration analysis of key components in the growth process of agricultural products, the best harvest periods can be provided. Interaction studies between functional components and metabolism of organisms based on the detection of humoral metabolism and biomarkers can provide valuable information for dietary guidance.

Key words: metabolomics, agro-product, nutrition, quality

Table 1

Applications of Metabolomics to investigate and analysis nutrition and quality of agro-products"

应用
Application
农产品种类
Agro-product
检测技术
Detection technology
数据处理方法
Data analysis
生物标志物
Biomarker
参考文献
Reference
营养成分表征及差异性分析
Characterization and difference analysis of nutritional components
番茄
Tomato
LC-MS/MS PCA 氨基酸(Amino acid)、6-甲基-5-庚烯-2-酮(6- Methyl-5-hepten-2-one)、香叶基丙酮(Geranyl acetone)等 [67]
洋葱
Onion
LC/ ESI-QTOF-MS ANOVA, HC, PCA 低聚果糖(Fructooligosaccharides)、氨基酸(Proteinogenic amino acids)、多肽(Peptides)、S-半胱氨酸(S-substituted cysteine conjugates)、黄酮(Flavonoids)及皂苷类(Flavonoids) [68]
葡萄
Grapevine berry
UHPLC-ESI-QTOF-MS PCA, OPLS-DA 花色苷(Anthocyanins)、芪类化合物(Stilbenoids)、原花青素(Procyanidin)等 [69]

Crab
1H-NMR PCA 谷氨酸(Glutamate)、丙氨酸(Alanine)、甘氨酸(Glycine)、龙虾碱(Lobsterine)、乳酸(Lactic acid)、甜菜碱(Betaine)和牛磺酸(Taurine) [70]
番茄
Tomato
HS/SPME/GC-MS ANOVA, MCA, PCA, HCA 邻甲基苯乙酮(O-methylacetophenone)、苯甲酮(Benzophenone)等 [71]
芜菁
Brassica crops
GC-MS PCA, PLS regression analysis, ANOVA L-谷氨酰胺(L-glutamine)、L-天冬酰胺(L- asparagine)、棉子糖(Raffinose)、麦芽糖(Maltose)、苹果酸(Malic acid)和异硫氰酸烯丙酯(Allyl isothiocyanate) [72]
蔓越莓
Cranberry
UPLC-TOF-MS PCA, PLS-DA 花青素(Procyanidin) [73]
树莓
Raspberries
UPLC-TOF-MS Pattern analysis 花青素(Procyanidin) [74]
马铃薯 Potatoes HPLC,GC-TOF-MS ANOVA, PCA 花青素(Procyanidin) [75]
番茄
Tomato
1H-NMR,LC-FID, GC-FID PCA, SOM 甘露糖(Mannose)、胆碱(Choline)、油酸(Oleic)、硬脂酸(Stearic)、亚油酸(Linoleic)、亚麻酸(Linolenic)、棕榈酸(Palmitic)、淀粉(Amylum) [76]
玉米
Maize
UPLC-MS/MS,GC-MS PCA, PLS-DA 二氢山萘酚(Dihydrokaempferol)和柚皮素(Naringenin) [78]
番茄
Tomato
1H-NMR PCA, PLS, ANOVA 谷氨酸(Glutamic acid)、果糖(Fructose)、缬氨酸(Valine)、山奈酚(Kaempferol)、桂皮素苷(Cinnamrin)、γ-氨基丁酸(Gamma-aminobutyric acid)、柠檬酸(Citric acid)、蔗糖(Sucrose)、苯丙氨酸(Phenylalanine)和葫芦巴碱(Trigonelline) [79]
产地溯源及真伪鉴别
Origin traceability and authenticity identification
大白菜
Cabbage
1H-NMR PCA 氨基丁酸(Aminobutyric acid)、天冬酰胺(Asparagine)、亮氨酸(Leucine)、异亮氨酸(Isoleucine)、O-磷酸胆碱(O-phosphocholine)、乙酸苯酯(Phenylacetate)、苯丙氨酸(Phenylalanine)、琥珀酸盐(Succinate)、蔗糖(Sucrose)、酪氨酸(Tyrosine)、缬氨酸(Valine) [81]
枸杞
Lycium barbarum
LC-QTOF-MS PLS-DA, HCA 槲皮素(Quercetin)、山奈酚糖苷(Kaempferol glycosides)、二咖啡酰奎宁酸(Dicaffeoylquinic acid)和酚酸(Phenolic acids) [82]
大蒜
Garlic
DART-HRMS,
HPLC-ESI-HRMS,
DI-ESI-HRMS
OPLS-DA 蒜氨酸(Alliin)、PC (16:0/18:2) (Phosphatidylcholine)和精氨酸(Arginine) [83]
大蒜
Garlic
HRMAS-NMR PLS-DA 烯丙基含硫化合物(Allyl-organosulphurs)、大蒜素(Allicin) [84]
榛子
Hazelnut
UPLC-QTOF-MS PCA-LDA 磷脂酰胆碱(Phosphatidylcholines)、磷脂酰乙醇胺(Phosphatidylethanolamines)、甘油二酯(Diacylglycerols)、三酰基甘油(Triacylglycerols)和γ-生育酚(γ-tocopherol) [90]

Table 1

Applications of Metabolomics to investigate and analysis nutrition and quality of agro-products(Continued)"

应用
Application
农产品种类
Agro-product
检测技术
Detection technology
数据处理方法
Data analysis
生物标志物
Biomarker
参考文献
Reference
榛子
Hazelnut
LC-ESI-QqQ-MS PCA-LDA, ANOVA PE(18:2/18:2) (1,2-dilinoleoyl-sn glycero-3- phosphoethanolamine)、PC(18:2/18:2) (1,2- dilinoleoyl-sn-glycero-3-phosphocholine)、DG (18:2/18:2) (1,3-100 dilinoleoyl-rac-glycerol) [91]
生长储藏过程中营养成分变化规律
Changes of nutritional components during growth and storage
草莓 Strawberry GC-MS,HPLC-MS PCA, PLS-DA 游离氨基酸(Free amino acids) [92]
葡萄
Grapevine berry
GC-MS HCA, PCA, PLS-DA, ANOVA 糖类(Sugars)和氨基酸(Amino acids) [93]
番茄
Tomato
GC-MS PLS-DA, ANOVA 甘露糖(Mannose)、柠檬酸(Citramalic)、葡萄糖酸(Gluconic)和酮-1-古洛糖酸(Keto-l-gulonic acids)等 [94]
鸡蛋
Chicken eggs
HPLC-QTOF-MS PCA 胆碱(Choline) [48]
大豆 Soybean 1H-NMR PCA, PLS-DA 脯氨酸(Proline)、赖氨酸(Lysine)和硫(Sulfur) [96]
营养功能成分作用机制及对代谢的影响 Functional mechanism of nutritional components and their effects on metabolism 生姜
Ginger
HPLC-QTOF-MS ANOVA D-葡糖醛酸-6 (D-glucurono-6)、3-内酯(3- lactone)、甘油-3-磷酸(Glycerol-3-phosphate)、丙酮酸(Pyruvic acid)、石胆酸(Lithocholic acid)、2-吡啶甲酸(2-pyrocatechuic acid)和前列腺素E1 (Prostaglandin El)等 [100]
枸杞
Lycium barbarum
GC-TOF-MS PCA, OPLS-DA 丙氨酸(Alanine)、胸腺嘧啶脱氧核苷酸(Thymidine deoxynucleotide) [101]
绿茶
Green tea
LC-MS PCA, OPLS-DA, PLS regression analysis 多酚(Polyphenol) [102]
苦瓜
Bitter gourd
NMR PCA, PLS-DA 柠檬酸(Citramalic)、琥珀酸(Succinate)、肌氨酸(Sarcosine)、丙酮酸(Pyruvic acid)等 [107]
白茶
Origanum dictamnus tea
1H-NMR PCA, OPLS-DA 马尿酸(Hippurate)和肌酐(Creatinine) [108]
饮食模式
Dietary modulation
1H-NMR OPLS-DA 肉碱(Carnitine)、乙酰肉碱(Acetylcarnitine)、三甲胺-N-氧化物(Trimethylamine-N-oxid)、对-羟基苯乙酸酯(p-hydroxyphenylacetate) [109]
[1] 吴永宁 . 我国食品安全科学研究现状及"十三五"发展方向. 农产品质量与安全, 2015(6):3-6.
WU Y N . The research status of food safety science in China and the development direction in “13th Five-year Plan”. Quality and Safety of Agro-Products, 2015(6):3-6. (in Chinese)
[2] 唐华俊 . 中国营养型农业发展正当其时. 高科技与产业化, 2018,266(7):3.
TANG H J . China's nutritious agriculture is developing at the right time. High-Technology & Industrialization, 2018,266(7):3. (in Chinese)
[3] 韩娟, 孙君茂, 秦玉昌 . 农产品质量与营养功能风险评估研究方向探讨. 农产品质量与安全, 2016(2):45-48.
HAN J, SUN J M, QIN Y C . Discussion on the research direction of risk assessment in agricultural product quality and nutrition function. Quality and Safety of Agro-Products, 2016(2):45-48. (in Chinese)
[4] 许国旺, 路鑫, 杨胜利 . 代谢组学研究进展. 中国医学科学院学报, 2007,29(6):701-711.
XU G W, LU X, YANG S L . Recent advances in metabonomics. Acta Academiae Medicinae Sinicae, 2007,29(6):701-711. (in Chinese)
[5] NICHOLSON J K, LINDON J C, HOLMES E . ''Metabonomics'': understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica, 1999,29(11):1181-1189.
[6] FIEHN O . Metabolomics-the link between genotypes and phenotypes. Plant Molecular Biology, 2002,48(1/2):155-171.
[7] COCCI P, MOSCONI G, PALERMO F A . Changes in expression of microRNA potentially targeting key regulators of lipid metabolism in primary gilthead sea bream hepatocytes exposed to phthalates or flame retardants. Aquatic Toxicology, 2019,209:81-90.
[8] EVERETT J R . Pharmacometabonomics in humans: A new tool for personalized medicine. Pharmacogenomics, 2015,16(7):737-754.
[9] POTRATZ S, TARNOW P, JUNGNICKEL H, BAUMANN S, VON BERGEN M, TRALAU T, LUCH A . Combination of metabolomics with cellular assays reveals new biomarkers and mechanistic insights on xenoestrogenic exposures in MCF-7 Cells. Chemical Research in Toxicology, 2017,30(4):883-892.
[10] JIANG G T, KANG H Y, YU Y Q . Cross-platform metabolomics investigating the intracellular metabolic alterations of HaCaT cells exposed to phenanthrene. Journal of Chromatogr B Analytical Technologies in the Biomedical & Life Sciences, 2017,1060:15-21.
[11] ZOTTI M, DE PASCALI S A, DEL COCO L, MIGONI D, CARROZZO L, MANCINELLI G, FANIZZI F P. 1H NMR metabolomic profiling of the blue crab (Callinectes sapidus) from the Adriatic Sea (SE Italy): A comparison with warty crab(Eriphia verrucosa), and edible crab (Cancer pagurus). Food Chemistry 2016,196:601-609.
[12] CHEN J P, CHAN P H, LAM C T W, LI Z G, LAM K Y C, YAO P, DONG T T X, LIN H Q, LAM H, TSIM K W K . Fruit of ziziphus jujuba (Jujube) at two stages of maturity: Distinction by metabolic profiling and biological assessment. Journal of Agricultural and Food Chemistry, 2015,63(2):739-744.
[13] CEVALLOS-CEVALLOS J M, REYES-DE-CORCUERA J I, ETXEBERRIA E, DANYLUK M D, RODRICK G E . Metabolomic analysis in food science: A review. Trends in Food Science & Technology, 2009,20(11):557-566.
[14] 赵春霞, 许国旺 . 基于液相色谱-质谱技术的代谢组学分析方法新进展. 分析科学学报, 2014,30(5):761-766.
ZHAO C X, XU G W . Progress of metabonomics technique based on liquid chromatography-mass spectrometry. Journal of Analytical Science, 2014,30(5):761-766. (in Chinese)
[15] 马宁, 杨亚军, 刘希望, 李剑勇 . 基于液质平台代谢组学生物样本的采集和制备. 中国兽医学报, 2017,37(6):1193-1200.
MA N, YANG Y J, LIU X W, LI J Y . Biological sample collection and preparation for metabonomic study with LC-MS platform. Chinese Journal of Veterinary Science, 2017,37(6):1193-1200. (in Chinese)
[16] KNOLHOFF A M, CROLEY T R . Non-targeted screening approaches for contaminants and adulterants in food using liquid chromatography hyphenated to high resolution mass spectrometry. Journal of Chromatography A, 2016,1428:86-96.
[17] LIU Y Y, HU X L, BAO Y F, YIN D Q . Simultaneous determination of 29 pharmaceuticals in fish muscle and plasma by ultrasonic extraction followed by SPE-UHPLC-MS/MS. Journal of Separation Science, 2018,41(10):2139-2150.
[18] ANDRADE-EIROA A, CANLE M, LEROY-CANCELLIERI V, CERDÀ V . Solid-phase extraction of organic compounds: A critical review (Part I). TrAC Trends in Analytical Chemistry, 2016,80:641-654.
[19] WANG C H, SU H, CHOU J H, HUANG M Z, LIN H J, SHIEA J . Solid phase microextraction combined with thermal-desorption electrospray ionization mass spectrometry for high-throughput pharmacokinetics assays. Analytica Chimica Acta, 2018,1021:60-68.
[20] SHAMSIPUR M, YAZDANFAR N, GHAMBARIAN M . Combination of solid-phase extraction with dispersive liquid-liquid microextraction followed by GC-MS for determination of pesticide residues from water, milk, honey and fruit juice. Food Chemistry, 2016,204:289-297.
[21] GIL-RAMIREZ A, AL-HAMIMI S, ROSMARK O, HALLGREN O, LARSSON-CALLERFELT A K, RODRíGUEZ-MEIZOSO I . Efficient methodology for the extraction and analysis of lipids from porcine pulmonary artery by supercritical fluid chromatography coupled to mass spectrometry. Journal of Chromatography A, 2019,1592:173-182.
[22] VARGAS L H G, NETO J C R, RIBEIRO J A D, RICCI-SILVA M E, SOUZA M T, RODRIGUES C M, OLIVEIRA A E, ABDELNUR P V . Metabolomics analysis of oil palm (Elaeis guineensis) leaf: Evaluation of sample preparation steps using UHPLC-MS/MS. Metabolomics, 2016,12(10):153.
[23] 徐佳, 刘其南, 翟园园, 单进军, 张丽 . 细胞代谢组学样品前处理研究进展. 中国细胞生物学学报, 2018,40(3):418-425.
XU J, LIU Q N, ZHAI Y Y, SHAN J J, ZHANG L . The Research development of sample pretreatment in cell metabolomics. Chinese Journal of Cell Biology, 2018,40(3):418-425. (in Chinese)
[24] WANG X, XU Y, SONG X, JIA Q, ZHANG X, QIAN Y, QIU J . Analysis of glycerophospholipid metabolism after exposure to PCB153 in PC12 cells through targeted lipidomics by UHPLC- MS/MS. Ecotoxicology and Environmental Safety, 2019,169:120-127.
[25] BLIGH E G, DYER W J . A rapid mmethord of total lipid extraction and purification. Canadian Journal of Biochemistry and Physiology, 1959,37(8):911.
[26] FOLCH J, LEES M, SLOANE STANLEY G H . A simple method for the isolation and purification of total lipides from animal tissues. Journal of Biological Chemistry, 1957,226(1):497-509.
[27] SARAFIAN M H, GAUDIN M, LEWIS M R, MARTIN F P, HOLMES E, NICHOLSON J K, DUMAS M E . Objective set of criteria for optimization of sample preparation procedures for ultra-high throughput untargeted blood plasma lipid profiling by ultra performance liquid chromatography-mass spectrometry. Analytical Chemistry, 2014,86(12):5766-5774.
[28] MATYASH V, LIEBISCH G, KURZCHALIA T V, SHEVCHENKO A, SCHWUDKE D . Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics. Journal of Lipid Research, 2008,49(5):1137-1146.
[29] MOROS G, CHATZIIOANNOU A C, GIKA H G, RAIKOS N, THEODORIDIS G . Investigation of the derivatization conditions for GC-MS metabolomics of biological samples. Bioanalysis, 2017,9(1):53-65.
[30] 焦宏 . 核磁共振技术在代谢组学中的应用. 山西医药杂志, 2011(4):335-336.
JIAO H . Application of nuclear magnetic resonance technology in metabolomics. Shanxi Medical Journal, 2011(4):335-336. (in Chinese)
[31] 王超, 涂文志, 王穆, 让蔚清 . 代谢组学分析技术及代谢物鉴定. 国际药学研究杂志, 2010,37(5):355-360.
WANG C, TU W Z, WANG M, RANG W Q . Metabonomics analytical technologies and metabolite identification. International Journal of Pharmaceutical Research, 2010,37(5):355-360. (in Chinese)
[32] 夏建飞, 梁琼麟, 胡坪, 王义明, 罗国安 . 代谢组学研究策略与方法的新进展. 分析化学, 2009,37(1):136-143.
doi: 10.1016/S1872-2040(08)60081-X
XIA J F, LIAGN Q L, HU P, WANG Y M, LUO G A. recent trends in strategies and methodologies for metabonomics. Chinese Journal of Analytical Chemistry, 2009,37(1):136-143. (in Chinese)
doi: 10.1016/S1872-2040(08)60081-X
[33] 许茜, 王磊, 张杰, 许卉 . 基于核磁代谢组学的阿胶原料来源鉴别. 食品科技, 2018,43(1):316-319.
XU Q, WANG L, ZHANG J, XU H . Origin identification of Colla Corii Asini based on 1H-NMR metabolomics . Food Science and Technology, 2018,43(1):316-319. (in Chinese)
[34] BRENNAN L . NMR-based metabolomics: From sample preparation to applications in nutrition research. Progress in Nuclear Magnetic Resonance Spectroscopy, 2014,83:42-49.
[35] SANDUSKY P, APPIAH-AMPONSAH E, RAFTERY D . Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids. Journal of Biomolecular NMR, 2011,49(3/4):281-290.
[36] STURM S, SEGER C . Liquid chromatography-nuclear magnetic resonance coupling as alternative to liquid chromatography-mass spectrometry hyphenations: curious option or powerful and complementary routine tool? Journal of Chromatography A, 2012,1259(19):50-61.
[37] BRAUNBERGER C, ZEHL M, CONRAD J, FISCHER S, ADHAMI H R, BEIFUSS U, KRENN L. LC-NMR , NMR, and LC-MS identification and LC-DAD quantification of flavonoids and ellagic acid derivatives in drosera peltata. Journal of Chromatography B Analytical Technologies in the Biomedical & Life Sciences, 2013,932(15):111-116.
[38] GARCIA C J, GARCíA-VILLALBA R, GARRIDO Y, GIL M I, TOMáS-BARBERáN F A. Untargeted metabolomics approach using UPLC-ESI-QTOF-MS to explore the metabolome of fresh-cut iceberg lettuce. Metabolomics, 2016,12(8):138.
[39] SARABIA L D, BOUGHTON B A, RUPASINGHE T, VAN DE MEENE A M L, CALLAHAN D L, HILL C B, ROESSNER U. High-mass-resolution MALDI mass spectrometry imaging reveals detailed spatial distribution of metabolites and lipids in roots of barley seedlings in response to salinity stress. Metabolomics, 2018,14(5):1-16.
[40] FARNETI B, KHOMENKO I, CAPPELLIN L, TING V, ROMANO A, BIASIOLI F, COSTA G, COSTA F . Comprehensive VOC profiling of an apple germplasm collection by PTR-ToF-MS. Metabolomics, 2015,11(4):838-850.
[41] KIM H J, SEO Y T, PARK S-I, JEONG S H, KIM M K, JANG Y P . DART-TOF-MS based metabolomics study for the discrimination analysis of geographical origin of Angelica gigas roots collected from Korea and China. Metabolomics, 2015,11(1):64-70.
[42] GONG Z G, HU J, WU X, XU Y J . The Recent developments in sample preparation for mass spectrometry-based metabolomics. Critical Reviews in Analytical Chemistry, 2017,47(4):1-7.
[43] BEALE D J, PINU F R, KOUREMENOS K A, POOJARY M M, NARAYANA V K, BOUGHTON B A, KANOJIA K, DAYALAN S, JONES O A H, DIAS D A. Review of recent developments in GC-MS approaches to metabolomics-based research. Metabolomics, 2018,14(11):152.
[44] MARI A, LYON D, FRAGNER L, MONTORO P, PIACENTE S, WIENKOOP S, EGELHOFER V, WECKWERTH W . Phytochemical composition of Potentilla anserina L. analyzed by an integrative GC-MS and LC-MS metabolomics platform. Metabolomics, 2013,9(3):599-607.
[45] SMITH E D, WHITING M D, RUDELL D R . Metabolic profiling of ethephon-treated sweet cherry (Prunus avium L.). Metabolomics, 2011,7(1):126-133.
[46] WONG Y F, PERLMUTTER P, MARRIOTT P J . Untargeted metabolic profiling of Eucalyptus spp. leaf oils using comprehensive two-dimensional gas chromatography with high resolution mass spectrometry: Expanding the metabolic coverage. Metabolomics, 2017,13(5):46.
[47] TOFFALI K, ZAMBONI A, ANESI A, STOCCHERO M, PEZZOTTI M, LEVI M, GUZZO F . Novel aspects of grape berry ripening and post-harvest withering revealed by untargeted LC-ESI-MS metabolomics analysis. Metabolomics, 2011,7(3):424-436.
[48] JOHNSON A E, SIDWICK K L, PIRGOZLIEV V R, EDGE A, THOMPSON D F . Metabonomic profiling of chicken eggs during storage using high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry. Analytical Chemistry, 2018,90(12):7489-7494.
[49] MOLINA-CALLE M, SáNCHEZ DE MEDINA V, CALDERóN- SANTIAGO M, PRIEGO-CAPOTE F, LUQUE DE CASTRO M D. Untargeted analysis to monitor metabolic changes of garlic along heat treatment by LC-QTOF MS/MS. Electrophoresis, 2017,38(18):2349-2360.
[50] IBÁÑEZ C, SIMÓ C, GARCÍA-CAÑAS V, CIFUENTES A, CASTRO- PUYANA M . Metabolomics, peptidomics and proteomics applications of capillary electrophoresis-mass spectrometry in foodomics: A review. Analytica Chimica Acta, 2013,802:1-13.
[51] BAN E, PARK S H, KANG M J, LEE H J, SONG E J, YOO Y S . Growing trend of CE at the omics level: The frontier of systems biology-An update. Electrophoresis, 2012,33(1):2-13.
[52] LAN K, ZHANG Y, YANG J Y, XU L . Simple quality assessment approach for herbal extracts using high performance liquid chromatography-UV based metabolomics platform. Journal of Chromatography A, 2010,1217(8):1414-1418.
[53] FIEHN O . Metabolomics--the link between genotypes and phenotypes. Plant Molecular Biology, 2002,48(1/2):155-171.
[54] 徐淑玲, 魏芳, 董绪燕, 陈洪 . 脂质组学在脂质膳食营养与健康研究中的应用. 中国食物与营养, 2017,23(11):5-10.
XU S L, WEI F, DONG X Y, CHEN H . The Application of lipidomics in lipids dietary nutrition and health research. Food and Nutrition in China, 2017,23(11):5-10. (in Chinese)
[55] GIKA H G, THEODORIDIS G A, PLUMB R S, WILSON I D . Current practice of liquid chromatography-mass spectrometry in metabolomics and metabonomics. Journal of Pharmaceutical and Biomedical Analysis, 2014,87:12-25.
[56] GUO Q, WU W, MASSART D L, BOUCON C, JONG S D . Feature selection in principal component analysis of analytical data. Chemometrics and Intelligent Laboratory Systems, 2002,61(1):123-132.
[57] ARROIO A, HONóRIO K M, SILVA A B F D . A theoretical study on the analgesic activity of cannabinoid compounds. Journal of Molecular Structure Theochem, 2004,709(1):223-229.
[58] BOULESTEIX A L, STRIMMER K . Partial least squares: a versatile tool for the analysis of high-dimensional genomic data. Briefings in Bioinformatics, 2007,8(1):32-44.
[59] DAYGON V D, PRAKASH S, CALINGACION M, RIEDEL A, OVENDEN B, SNELL P, MITCHELL J, FITZGERALD M . Understanding the Jasmine phenotype of rice through metabolite profiling and sensory evaluation. Metabolomics, 2016,12(4):63.
[60] CAI Y, WENG K, GUO Y, PENG J, ZHU Z-J . An integrated targeted metabolomic platform for high-throughput metabolite profiling and automated data processing. Metabolomics, 2015,11(6):1575-1586.
[61] RAFIEI A, SLENO L . Comparison of peak-picking workflows for untargeted liquid chromatography/high-resolution mass spectrometry metabolomics data analysis. Rapid Communications in Mass Spectrometry, 2015,29(1):119-127.
[62] 王昕璐 . 基于脂质组学的PCB153和PCB95对PC12细胞联合毒性效应研究[D]. 中国农业科学院, 2018.
WANG X L . PCB153 and PCB95 in combined exposure modulate PC12 cells as defined by targeted lipidomics analysis[D]. Chinese Academy of Agricultural Sciences, 2018. (in Chinese)
[63] WISHART D S, JEWISON T, GUO A C, WILSON M, KNOX C, LIU Y, DJOUMBOU Y, MANDAL R, AZIAT F, DONG E . HMDB 3.0-The human metabolome database in 2013. Nucleic Acids Research, 2013,41:801-807.
[64] SMITH C A . METLIN: A metabolite mass spectral database. Therapeutic Drug Monitoring, 2005,27(6):747-751.
[65] PAUPIÈRE M J, MÜLLER F, LI H, RIEU I, TIKUNOV Y M, VISSER R G F, BOVY A G . Untargeted metabolomic analysis of tomato pollen development and heat stress response. Plant Reproduction, 2017,30(2):81-94.
[66] WANG L, YE H, SUN D, MENG T, CAO L J, WU M Q, ZHAO M, WANG Y, CHEN B Q, XU X W, WANG G J, HAO H P . Metabolic pathway extension approach for metabolomic biomarker identification. Analytical Chemistry, 2017,89(2):1229-1237.
[67] ZHU G T, WANG S C, HUANG Z J, ZHANG S B, LIAO QBG, ZHANG C Z, LIN T, QIN M, PENG M, YANG C K, CAO X, HAN X, WANG X X, VAN DER KNAAP E, ZHANG Z H, CUI X, KLEE H, FERNIE A R, LUO J, HUANG S W . Rewiring of the fruit metabolome in tomato breeding. Cell, 2018,172(1/2):6-8.
[68] BÖTTCHER C, KRÄHMER A, STÜRTZ M, WIDDER S, SCHULZ H . Comprehensive metabolite profiling of onion bulbs (Allium cepa) using liquid chromatography coupled with electrospray ionization quadrupole time-of-flight mass spectrometry. Metabolomics, 2017,13(4):35.
[69] NARDUZZI L, STANSTRUP J, MATTIVI F . Comparing wild American grapes with Vitis vinifera: A metabolomics study of grape composition. Journal of Agricultural and Food Chemistry, 2015,63(30):6823-6834.
[70] ZOTTI M, COCO L D, PASCALI S A D, MIGONI D, VIZZINI S, MANCINELLI G, FANIZZI F P. Comparative analysis of the proximate and elemental composition of the blue crab callinectes sapidus, the warty crab eriphia verrucosa, and the edible crab cancer pagurus. Heliyon, 2016,2(2):e00075.
[71] CORTINA P R, SANTIAGO A N, SANCE M M, PERALTA I E, CARRARI F, ASIS R . Neuronal network analyses reveal novel associations between volatile organic compounds and sensory properties of tomato fruits. Metabolomics, 2018,14(5):57.
[72] FUKUDA T, OKAZAKI K, WATANABE A, SHINANO T, OKA N . GC-MS based metabolite profiling for flavor characterization of brassica crops grown with different fertilizer application. Metabolomics, 2015,12(2):20.
[73] BROWN P N, MURCH S J, SHIPLEY P . Phytochemical diversity of cranberry (Vaccinium macrocarpon Aiton) cultivars by anthocyanin determination and metabolomic profiling with chemometric analysis. Journal of Agricultural and Food Chemistry, 2012,60(1):261-271.
[74] CARVALHO E, FRANCESCHI P, FELLER A, HERRERA L, PALMIERI L, ARAPITSAS P, RICCADONNA S, MARTENS S . Discovery of A-type procyanidin dimers in yellow raspberries by untargeted metabolomics and correlation based data analysis. Metabolomics, 2016,12(9):144.
[75] INOSTROZA-BLANCHETEAU C, DE OLIVEIRA SILVA F M, DURáN F, SOLANO J, OBATA T, MACHADO M, FERNIE A R, REYES-DíAZ M, NUNES-NESI A. Metabolic diversity in tuber tissues of native Chiloé potatoes and commercial cultivars of Solanum tuberosum ssp. tuberosum L. Metabolomics, 2018,14(10):138.
[76] MOUNET F, LEMAIRE-CHAMLEY M, MAUCOURT M, CABASSON C, GIRAUDEL J-L, DEBORDE C, LESSIRE R, GALLUSCI P, BERTRAND A, GAUDILLèRE M, ROTHAN C, ROLIN D, MOING A. Quantitative metabolic profiles of tomato flesh and seeds during fruit development: complementary analysis with ANN and PCA. Metabolomics, 2007,3(3):273-288.
[77] 张晓磊, 张瑞英 . 代谢组学及其在农作物研究中的应用. 生物技术通讯, 2018,29(3):446-450.
ZHAGN X L, ZHANG R Y . Metabolomics and its application in the crop research. Letters in Biotechnology, 2018,29(3):446-450. (in Chinese)
[78] RAO J, YANG L T, GUO J C, QUAN S, CHEN G H, ZHAO X X, ZHANG D B, SHI J X . Metabolic changes in transgenic maize mature seeds over-expressing the Aspergillus niger phyA2. Plant Cell Reports, 2016,35(2):429-437.
[79] LE GALL G, COLQUHOUN I J, DAVIS A L, COLLINS G J, VERHOEYEN M E . Metabolite profiling of tomato (Lycopersicon esculentum) using 1H NMR spectroscopy as a tool to detect potential unintended effects following a genetic modification. Journal of Agricultural and Food Chemistry , 2003,51(9):2447-2456.
[80] LI Y, PANG T, LI Y, WANG X L, LI Q H, LU X, XU G W . Gas chromatography-mass spectrometric method for metabolic profiling of tobacco leaves. Journal of Separation Science, 2011,34(12):1447-1454.
[81] KIM J, JUNG Y, SONG B, BONG Y S, RYU D H, LEE K S, HWANG G S . Discrimination of cabbage (Brassica rapa ssp. pekinensis) cultivars grown in different geographical areas using 1H NMR-based metabolomics. Food Chemistry , 2013,137(1):68-75.
[82] BONDIA-PONS I, SAVOLAINEN O, TÖRRÖNEN R, MARTINEZ J A, POUTANEN K, HANHINEVA K. Metabolic profiling of Goji berry extracts for discrimination of geographical origin by non- targeted liquid chromatography coupled to quadrupole time-of-flight mass spectrometry. Food Research International, 2014,63(Part B):132-138.
[83] HRBEK V, REKTORISOVA M, CHMELAROVA H, OVESNA J, HAJSLOVA J . Authenticity assessment of garlic using a metabolomic approach based on high resolution mass spectrometry. Journal of Food Composition and Analysis, 2018,67:19-28.
[84] RITOTA M, CASCIANI L, HAN B Z, COZZOLINO S, LEITA L, SEQUI P, VALENTINI M . Traceability of Italian garlic (Allium sativum L.) by means of HRMAS-NMR spectroscopy and multivariate data analysis. Food Chemistry, 2012,135(2):684-693.
[85] CAMARGO A B, RESNIZKY S, MARCHEVSKY E J, LUCO J M . Use of the Argentinean garlic (Allium sativum L.) germplasm mineral profile for determining geographic origin. Journal of Food Composition and Analysis, 2010,23(6):586-591.
[86] VADALÀ R, MOTTESE A F, BUA G D, SALVO A, MALLAMACE D, CORSARO C, VASI S, GIOFRÈ S V, ALFA M, CICERO N, DUGO G . Statistical analysis of mineral concentration for the geographic identification of garlic samples from sicily (Italy), Tunisia and Spain. Foods, 2016,5(1):20.
[87] SMITH R G . Determination of the country of origin of garlic (Allium sativum) using trace metal profiling. Journal of Agricultural and Food Chemistry, 2005,53(10):4041-4045.
[88] DU H Y, FU J L, WANG S Q, LIU H L, ZENG Y C, YANG J R, XIONG S B . 1H-NMR metabolomics analysis of nutritional components from two kinds of freshwater fish brain extracts . Rsc Advances, 2018,8(35):19470-19478.
[89] 陈羽红, 张东杰, 张桂芳, 王颖, 王长远 . 代谢组学技术在食品产地溯源中的研究进展. 粮食与饲料工业, 2016,12(7):16-19.
CHEN Y H, ZHANG D J, ZHANG G F, WANG Y, WAGN C Y . Review on metabonomics techniques in food origin traceability. Cereal & Feed Industry, 2016,12(7):16-19. (in Chinese)
[90] KLOCKMANN S, REINER E, BACHMANN R, HACKL T, FISCHER M . Food fingerprinting: metabolomic approaches for geographical origin discrimination of hazelnuts ( Corylus avellana) by UPLC-QTOF-MS. Journal of Agricultural and Food Chemistry, 2016,64(48):9253-9262.
[91] KLOCKMANN S, REINER E, CAIN N, FISCHER M . Food targeting: Geographical origin determination of hazelnuts (Corylus avellana) by LC-QqQ-MS/MS-based targeted metabolomics application. Journal of Agricultural and Food Chemistry, 2017,65(7):1456-1465.
[92] ZHANG J J, WANG X, YU O, TANG J J, GU X G, WAN X C, FANG C B . Metabolic profiling of strawberry (Fragaria×ananassa Duch.) during fruit development and maturation. Journal of Experimental Botany, 2011,62(3):1103-1118.
[93] CUADROS-INOSTROZA A, RUíZ-LARA S, GONZÁLEZ E, ECKARDT A, WILLMITZER L, PEÑA-CORTÉS H. GC-MS metabolic profiling of Cabernet Sauvignon and Merlot cultivars during grapevine berry development and network analysis reveals a stage- and cultivar-dependent connectivity of primary metabolites. Metabolomics, 2016,12(2):39.
[94] OMS-OLIU G, HERTOG M L A T M, VAN DE POEL B, AMPOFO- ASIAMA J, GEERAERD A H, NICOLAï B M. Metabolic characterization of tomato fruit during preharvest development, ripening, and postharvest shelf-life. Postharvest Biology and Technology, 2011,62(1):7-16.
[95] MARTINS N, PETROPOULOS S, FERREIRA I C F R. Chemical composition and bioactive compounds of garlic (Allium sativum L.) as affected by pre- and post-harvest conditions: A review. Food Chemistry, 2016,211:41-50.
[96] DENG J C, YANG C Q, ZHANG J, ZHANG Q, YANG F, YANG W Y, LIU J . Organ-specific differential NMR-based metabonomic analysis of soybean [Glycine max(L.) Merr.] fruit reveals the metabolic shifts and potential protection mechanisms involved in field mold infection. Frontiers in Plant Science, 2017,8(508).
[97] 许腾, 张玥, 张海丽, 辛凤姣, 王艳, 王凤忠 . 代谢组学技术在营养学研究中的应用. 中国食物与营养, 2017,23(11):11-16.
XU T, ZHANG Y, ZHAGN H L, XIN F J, WANG Y, WANG F Z . Applications of metabonomics in nutriology research. Food and Nutrition in China, 2017,23(11):11-16. (in Chinese)
[98] 张双庆, 黄振武 . 营养代谢组学技术在营养学研究中的应用. 卫生研究, 2013,42(6):1041-1046.
ZHAGN S Q, HUANG Z W . Application of nutritional metabolomics technology in nutrition research. Journal of Hygiene Research, 2013,42(6):1041-1046. (in Chinese)
[99] 何庆华, 任萍萍, 王玉兰 . 代谢组学在营养学研究中的应用. 食品科学, 2011,32(5):317-320.
HE Q H, REN P P, WANG Y L . Applications of metabolomics in nutrition research: A review. Food Science, 2011,32(5):317-320. (in Chinese)
[100] LIU C T, RAGHU R, LIN S H, WANG S Y, KUO C H, TSENG Y F J, SHEEN L Y. Metabolomics of ginger essential oil against alcoholic fatty liver in mice. Journal of Agricultural and Food Chemistry, 2013,61(46):11231-11240.
[101] 唐华丽, 夏惠, 王锋, 孙桂菊 . 枸杞多糖作用于2型糖尿病大鼠的血清代谢组学研究. 食品科学, 2017,38(13):160-166.
TANG H L, XIA H, WANG F, SUN G J . Serum metabonomics study of type 2 diabetic rats administrated with lycium barbarum polysaccharides. Food Science, 2017,38(13):160-166. (in Chinese)
[102] FUJIMURA Y, KURIHARA K, IDA M, KOSAKA R, MIURA D, WARIISHI H, MAEDA-YAMAMOTO M, NESUMI A, SAITO T, KANDA T, YAMADA K, TACHIBANA H . Metabolomics-driven nutraceutical evaluation of diverse green tea cultivars, PLoS ONE. 2011,6(8):e23426.
[103] ACCARDI C J, WALKER D I, UPPAL K, QUYYUMI A A, ROHRBECK P, PENNELL K D, MALLON C T, JONES D P . High-resolution metabolomics for nutrition and health assessment of armed forces personnel. Journal of Occupational & Environmental Medicine, 2016,58(8S Suppl 1):S80-S88.
[104] RAI A, SAITO K, YAMAZAKI M . Integrated omics analysis of specialized metabolism in medicinal plants. The Plant Journal, 2017,90(4):764-787.
[105] 侯绍英, 黄放放, 刘鑫妍, 彭雪 . 基于UPLC-MS技术的人体内芒果苷代谢组学研究. 哈尔滨医科大学学报, 2016,50(4):315-318.
HOU S Y, HUANG F F, LIU X Y, PENG X . Metabolomics study of mangiferin in human based on UPLC-MS. Journal of Harbin Medical University, 2016,50(4):315-318. (in Chinese)
[106] LLORACH R, URPI-SARDA M, TULIPANI S, GARCIA-ALOY M, MONAGAS M, ANDRES-LACUEVA C . Metabolomic fingerprint in patients at high risk of cardiovascular disease by cocoa intervention. Molecular Nutrition & Food Research, 2013,57(6):962-973.
[107] 边会喜 . 基于代谢组学与多光谱成像技术对苦瓜影响高脂饮食肥胖小鼠能量代谢的有效组分的研究[D]. 合肥: 合肥工业大学, 2016.
BIAN H X . The energy metabolism study of effective componets from bitter melon (Momordica charantia) on DIO mice based on metabolomics and multispectral imaging techonogy[D]. Hefei: Hefei University of Technology, 2016. (in Chinese)
[108] TAKIS P G, ORAIOPOULOU M E, KONIDARIS C, TROGANIS A N . (1)H-NMR based metabolomics study for the detection of the human urine metabolic profile effects of Origanum dictamnus tea ingestion. Food & Function, 2016,7(9):4104-4115.
[109] STELLA C, BECKWITH-HALL B, CLOAREC O, HOLMES E, LINDON J C, POWELL J, VAN DER OUDERAA F, BINGHAM S, CROSS A J, NICHOLSON J K. Susceptibility of human metabolic phenotypes to dietary modulation. Journal of Proteome Research, 2006,5(10):2780-2788.
[1] TANG YuLin, ZHANG Bo, REN Man, ZHANG RuiXue, QIN JunJie, ZHU Hao, GUO YanSheng. Evaluation of Regulatory Effect of Guiqi Yimu Oral Liquid on Rumen of Postpartum Dairy Cows Based on UPLC-MS/MS Metabolomics Technology [J]. Scientia Agricultura Sinica, 2023, 56(2): 368-378.
[2] WANG CaiXiang,YUAN WenMin,LIU JuanJuan,XIE XiaoYu,MA Qi,JU JiSheng,CHEN Da,WANG Ning,FENG KeYun,SU JunJi. Comprehensive Evaluation and Breeding Evolution of Early Maturing Upland Cotton Varieties in the Northwest Inland of China [J]. Scientia Agricultura Sinica, 2023, 56(1): 1-16.
[3] FENG XiangQian,YIN Min,WANG MengJia,MA HengYu,CHU Guang,LIU YuanHui,XU ChunMei,ZHANG XiuFu,ZHANG YunBo,WANG DanYing,CHEN Song. Effects of Meteorological Factors on Quality of Late Japonica Rice During Late Season Grain Filling Stage Under ‘Early Indica and Late Japonica’ Cultivation Pattern in Southern China [J]. Scientia Agricultura Sinica, 2023, 56(1): 46-63.
[4] LIN XinYing,WANG PengJie,YANG RuXing,ZHENG YuCheng,CHEN XiaoMin,ZHANG Lei,SHAO ShuXian,YE NaiXing. The Albino Mechanism of a New High Theanine Tea Cultivar Fuhuang 1 [J]. Scientia Agricultura Sinica, 2022, 55(9): 1831-1845.
[5] LI QingLin,ZHANG WenTao,XU Hui,SUN JingJing. Metabolites Changes of Cucumber Xylem and Phloem Sap Under Low Phosphorus Stress [J]. Scientia Agricultura Sinica, 2022, 55(8): 1617-1629.
[6] ZHU DaWei,ZHANG LinPing,CHEN MingXue,FANG ChangYun,YU YongHong,ZHENG XiaoLong,SHAO YaFang. Characteristics of High-Quality Rice Varieties and Taste Sensory Evaluation Values in China [J]. Scientia Agricultura Sinica, 2022, 55(7): 1271-1283.
[7] LÜ XinNing,WANG Yue,JIA RunPu,WANG ShengNan,YAO YuXin. Effects of Melatonin Treatment on Quality of Stored Shine Muscat Grapes Under Different Storage Temperatures [J]. Scientia Agricultura Sinica, 2022, 55(7): 1411-1422.
[8] PENG Xue,GAO YueXia,ZHANG LinXuan,GAO ZhiQiang,REN YaMei. Effects of High-Energy Electron Beam Irradiation on Potato Storage Quality and Bud Eye Cell Ultrastructure [J]. Scientia Agricultura Sinica, 2022, 55(7): 1423-1432.
[9] YAN LeLe,BU LuLu,NIU Liang,ZENG WenFang,LU ZhenHua,CUI GuoChao,MIAO YuLe,PAN Lei,WANG ZhiQiang. Widely Targeted Metabolomics Analysis of the Effects of Myzus persicae Feeding on Prunus persica Secondary Metabolites [J]. Scientia Agricultura Sinica, 2022, 55(6): 1149-1158.
[10] ZONG Cheng, WU JinXin, ZHU JiuGang, DONG ZhiHao, LI JunFeng, SHAO Tao, LIU QinHua. Effects of Additives on the Fermentation Quality of Agricultural By-Products and Wheat Straw Mixed Silage [J]. Scientia Agricultura Sinica, 2022, 55(5): 1037-1046.
[11] FENG XuanJun, PAN LiTeng, XIONG Hao, WANG QingJun, LI JingWei, ZHANG XueMei, HU ErLiang, LIN HaiJian, ZHENG HongJian, LU YanLi. Investigation on Important Target Traits and Breeding Potential of 120 Sweet and Waxy Maize Inbred Lines in the South of China [J]. Scientia Agricultura Sinica, 2022, 55(5): 856-873.
[12] JIANG JingJing,ZHOU TianYang,WEI ChenHua,WU JiaNing,ZHANG Hao,LIU LiJun,WANG ZhiQin,GU JunFei,YANG JianChang. Effects of Crop Management Practices on Grain Quality of Superior and Inferior Spikelets of Super Rice [J]. Scientia Agricultura Sinica, 2022, 55(5): 874-889.
[13] LIU Miao,LIU PengZhao,SHI ZuJiao,WANG XiaoLi,WANG Rui,LI Jun. Critical Nitrogen Dilution Curve and Nitrogen Nutrition Diagnosis of Summer Maize Under Different Nitrogen and Phosphorus Application Rates [J]. Scientia Agricultura Sinica, 2022, 55(5): 932-947.
[14] BIAN NengFei, SUN DongLei, GONG JiaLi, WANG Xing, XING XingHua, JIN XiaHong, WANG XiaoJun. Evaluation of Edible Quality of Roasted Peanuts and Indexes Screening [J]. Scientia Agricultura Sinica, 2022, 55(4): 641-652.
[15] PENG JiaKun, DAI WeiDong, YAN YongQuan, ZHANG Yue, CHEN Dan, DONG MingHua, LÜ MeiLing, LIN Zhi. Study on the Chemical Constituents of Yongchun Foshou Oolong Tea Based on Metabolomics [J]. Scientia Agricultura Sinica, 2022, 55(4): 769-784.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!