Quantitative analysis of blood plasma metabolites using isotope enhanced NMR methods.
Quantitative analysis of blood plasma metabolites using isotope enhanced NMR methods.
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DOI:
10.1021/ac101938w
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发表时间:
2010-11-01
影响因子:
7.4
通讯作者:
Raftery, Daniel
中科院分区:
文献类型:
--
作者:
Gowda, G. A. Nagana;Tayyari, Fariba;Ye, Tao;Suryani, Yuliana;Wei, Siwei;Shanaiah, Narasimhamurthy;Raftery, Daniel
NMR spectroscopy is a powerful analytical tool for both qualitative and quantitative analysis. However, accurate quantitative analysis in complex fluids such as human blood plasma is challenging, and analysis using one-dimensional NMR is limited by signal overlap. It is impractical to use heteronuclear experiments involving natural abundance 13C on a routine basis due to low sensitivity, despite their improved resolution. Focusing on circumventing such bottlenecks, this study demonstrates the utility of a combination of isotope tagged NMR experiments to analyze metabolites in human blood plasma. 1H-15N HSQC and 1H-13C HSQC experiments on the isotope tagged samples combined with the conventional 1H one-dimensional and 1H-1H TOCSY experiments provide quantitative information on a large number of metabolites in plasma. The methods were first tested on a mixture of 28 synthetic analogues of metabolites commonly present in human blood; twenty-seven metabolites in a standard NIST (National Institute of Standards and Technology) human blood plasma were then identified and quantified with an average coefficient of variation of 2.4 % for 17 metabolites and 5.6% when all the metabolites were considered. Carboxylic acids and amines represent a majority of the metabolites in body fluids and their analysis by isotope tagging enables a significant enhancement of the metabolic pool for biomarker discovery applications. Improved sensitivity and resolution of NMR experiments imparted by 15N and 13C isotope tagging is attractive for both the enhancement of the detectable metabolic pool and accurate analysis of plasma metabolites. The approach can be easily extended to many additional metabolites in almost any biological mixture.
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影响因子:
14.9
作者:
Wishart, David S;Tzur, Dan;Knox, Craig;Eisner, Roman;Guo, An Chi;Young, Nelson;Cheng, Dean;Jewell, Kevin;Arndt, David;Sawhney, Summit;Fung, Chris;Nikolai, Lisa;Lewis, Mike;Coutouly, Marie-Aude;Forsythe, Ian;Tang, Peter;Shrivastava, Savita;Jeroncic, Kevin;Stothard, Paul;Amegbey, Godwin;Block, David;Hau, David D;Wagner, James;Miniaci, Jessica;Clements, Melisa;Gebremedhin, Mulu;Guo, Natalie;Zhang, Ying;Duggan, Gavin E;Macinnis, Glen D;Weljie, Alim M;Dowlatabadi, Reza;Bamforth, Fiona;Clive, Derrick;Greiner, Russ;Li, Liang;Marrie, Tom;Sykes, Brian D;Vogel, Hans J;Querengesser, Lori
通讯作者:
Querengesser, Lori
影响因子:
7.4
作者:
de Graaf, RA;Behar, KL
通讯作者:
Behar, KL
影响因子:
7.4
作者:
Rai, Ratan Kumar;Tripathi, Pratima;Sinha, Neeraj
通讯作者:
Sinha, Neeraj
影响因子:
1.8
作者:
Nicholson, JK;Lindon, JC;Holmes, E
通讯作者:
Holmes, E
影响因子:
7.4
作者:
Fonville, Judith M.;Maher, Anthony D.;Nicholson, Jeremy K.
通讯作者:
Nicholson, Jeremy K.