Literature DB >> 16628593

Combining desorption electrospray ionization mass spectrometry and nuclear magnetic resonance for differential metabolomics without sample preparation.

Huanwen Chen1, Zhengzheng Pan, Nari Talaty, Daniel Raftery, R Graham Cooks.   

Abstract

Desorption electrospray ionization mass spectrometry (DESI-MS) and nuclear magnetic resonance (NMR) spectroscopy are used to provide data on urine examined without sample preparation to allow differentiation between diseased (lung cancer) and healthy mice. Principal component analysis (PCA) is used to shortlist compounds with potential for biomarker screening which are responsible for significant differences between control urine samples and samples from diseased animals. Similar PCA score plots have been achieved by DESI-MS and NMR, using a subset of common detected metabolites. The common compounds detected by DESI and NMR have the same changes in sign of their concentrations thereby indicating the usefulness of corroborative analytical methods. The effects of different solvents and surfaces on the DESI mass spectra are also evaluated and optimized. Over 80 different metabolites were successfully identified by DESI-MS and tandem mass spectrometry experiments, with no prior sample preparation. Copyright 2006 John Wiley & Sons, Ltd.

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Year:  2006        PMID: 16628593     DOI: 10.1002/rcm.2474

Source DB:  PubMed          Journal:  Rapid Commun Mass Spectrom        ISSN: 0951-4198            Impact factor:   2.419


  29 in total

1.  Advances in Nuclear Magnetic Resonance for Drug Discovery.

Authors:  Robert Powers
Journal:  Expert Opin Drug Discov       Date:  2009-10-01       Impact factor: 6.098

2.  Desorption electrospray ionization-mass spectrometry of proteins.

Authors:  Yong-Seung Shin; Barbara Drolet; Richard Mayer; Kurt Dolence; Franco Basile
Journal:  Anal Chem       Date:  2007-03-30       Impact factor: 6.986

3.  Internal energy distributions in desorption electrospray ionization (DESI).

Authors:  Marcela Nefliu; Jonell N Smith; Andre Venter; R Graham Cooks
Journal:  J Am Soc Mass Spectrom       Date:  2007-12-04       Impact factor: 3.109

4.  Transmission mode desorption electrospray ionization.

Authors:  Joseph E Chipuk; Jennifer S Brodbelt
Journal:  J Am Soc Mass Spectrom       Date:  2008-07-10       Impact factor: 3.109

5.  Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: application to the detection of breast cancer.

Authors:  Haiwei Gu; Zhengzheng Pan; Bowei Xi; Vincent Asiago; Brian Musselman; Daniel Raftery
Journal:  Anal Chim Acta       Date:  2010-11-26       Impact factor: 6.558

6.  Identification and quantification of metabolites in (1)H NMR spectra by Bayesian model selection.

Authors:  Cheng Zheng; Shucha Zhang; Susanne Ragg; Daniel Raftery; Olga Vitek
Journal:  Bioinformatics       Date:  2011-03-12       Impact factor: 6.937

7.  Mass spectral similarity for untargeted metabolomics data analysis of complex mixtures.

Authors:  Neha Garg; Clifford Kapono; Yan Wei Lim; Nobuhiro Koyama; Mark J A Vermeij; Douglas Conrad; Forest Rohwer; Pieter C Dorrestein
Journal:  Int J Mass Spectrom       Date:  2015-02-01       Impact factor: 1.986

8.  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

9.  Visualization of bile homeostasis using (1)H-NMR spectroscopy as a route for assessing liver cancer.

Authors:  G A Nagana Gowda; Narasimhamurthy Shanaiah; Amanda Cooper; Mary Maluccio; Daniel Raftery
Journal:  Lipids       Date:  2008-11-04       Impact factor: 1.880

10.  Altered regulation of metabolic pathways in human lung cancer discerned by (13)C stable isotope-resolved metabolomics (SIRM).

Authors:  Teresa W M Fan; Andrew N Lane; Richard M Higashi; Mohamed A Farag; Hong Gao; Michael Bousamra; Donald M Miller
Journal:  Mol Cancer       Date:  2009-06-26       Impact factor: 27.401

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