Literature DB >> 15828781

Use of selective TOCSY NMR experiments for quantifying minor components in complex mixtures: application to the metabonomics of amino acids in honey.

Peter Sandusky1, Daniel Raftery.   

Abstract

The application of the traditional methods of multivariate statistics, such as the calculation of principle components, to the analysis of NMR spectra taken on sets of biofluid samples is one of the central approaches in the field of metabonomics. While this approach has proven to be a powerful and widely applicable technique, it has an inherent weakness, in that it tends to be dominated by those chemical species present at relatively higher concentrations. Using a set of commercial honey samples, a comparison of this classical metabonomics approach to one based on the use of the selective TOCSY experiment is presented. While the NMR spectrum of honey and its classical metabonomic analysis is completely dominated by a very few chemical species, specifically alpha-glucose and fructose, the statistical signal carried by minor honey components, such as amino acids, may be accessed using a selective TOCSY-based approach. This approach has the intrinsic virtue that it focuses the statistical analysis on a set of predefined chemical species, which might be chosen for their metabolic significance, and could be composed of either major or minor mixture constituents. Furthermore, the selective TOCSY method allows for more certain chemical identification, acquisition times of approximately 1 min, and accurate quantification of the species contributing to the statistical discriminatory signal.

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Year:  2005        PMID: 15828781     DOI: 10.1021/ac0484979

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  26 in total

1.  Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids.

Authors:  Peter Sandusky; Emmanuel Appiah-Amponsah; Daniel Raftery
Journal:  J Biomol NMR       Date:  2011-03-10       Impact factor: 2.835

Review 2.  Using NMR spectroscopy to investigate the role played by copper in prion diseases.

Authors:  Rawiah A Alsiary; Mawadda Alghrably; Abdelhamid Saoudi; Suliman Al-Ghamdi; Lukasz Jaremko; Mariusz Jaremko; Abdul-Hamid Emwas
Journal:  Neurol Sci       Date:  2020-04-24       Impact factor: 3.307

3.  Improved identification of metabolites in complex mixtures using HSQC NMR spectroscopy.

Authors:  Yuanxin Xi; Jeffrey S de Ropp; Mark R Viant; David L Woodruff; Ping Yu
Journal:  Anal Chim Acta       Date:  2008-03-16       Impact factor: 6.558

Review 4.  Can NMR solve some significant challenges in metabolomics?

Authors:  G A Nagana Gowda; Daniel Raftery
Journal:  J Magn Reson       Date:  2015-08-18       Impact factor: 2.229

5.  Chemoselective 15N tag for sensitive and high-resolution nuclear magnetic resonance profiling of the carboxyl-containing metabolome.

Authors:  Tao Ye; Huaping Mo; Narasimhamurthy Shanaiah; G A Nagana Gowda; Shucha Zhang; Daniel Raftery
Journal:  Anal Chem       Date:  2009-06-15       Impact factor: 6.986

6.  1H NMR metabolomics study of age profiling in children.

Authors:  Haiwei Gu; Zhengzheng Pan; Bowei Xi; Bryan E Hainline; Narasimhamurthy Shanaiah; Vincent Asiago; G A Nagana Gowda; Daniel Raftery
Journal:  NMR Biomed       Date:  2009-10       Impact factor: 4.044

7.  NMR method for measuring carbon-13 isotopic enrichment of metabolites in complex solutions.

Authors:  Ian A Lewis; Ryan H Karsten; Mark E Norton; Marco Tonelli; William M Westler; John L Markley
Journal:  Anal Chem       Date:  2010-06-01       Impact factor: 6.986

Review 8.  Isotope enhanced approaches in metabolomics.

Authors:  G A Nagana Gowda; Narasimhamurthy Shanaiah; Daniel Raftery
Journal:  Adv Exp Med Biol       Date:  2012       Impact factor: 2.622

Review 9.  Metabolomics-based methods for early disease diagnostics.

Authors:  G A Nagana Gowda; Shucha Zhang; Haiwei Gu; Vincent Asiago; Narasimhamurthy Shanaiah; Daniel Raftery
Journal:  Expert Rev Mol Diagn       Date:  2008-09       Impact factor: 5.225

10.  Identification of 4-deoxythreonic acid present in human urine using HPLC and NMR techniques.

Authors:  Emmanuel Appiah-Amponsah; Narasimhamurthy Shanaiah; G A Nagana Gowda; Kwadwo Owusu-Sarfo; Tao Ye; Daniel Raftery
Journal:  J Pharm Biomed Anal       Date:  2009-06-12       Impact factor: 3.935

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