Literature DB >> 15890484

Progress toward automated metabolic profiling of human serum: comparison of CPMG and gradient-filtered NMR analytical methods.

Laura H Lucas1, Cynthia K Larive, Patricia Stone Wilkinson, Stephen Huhn.   

Abstract

The investigation of drug delivery and metabolism requires the analysis of molecules in complicated biological matrices such as human serum. In NMR-based metabonomic analysis, T(2) relaxation editing with a CPMG filter is commonly used to suppress background signals from proteins and other endogenous components. Radio frequency pulse imperfections and incomplete irradiation across the spectral bandwidth can cause phase and baseline distortions in CPMG spectra. These distortions are exacerbated by water suppression techniques. Baseline correction methods included in commercially available data processing software packages may be incapable of producing artifact-free spectra. To increase the analytical precision of metabolic profiling, one NMR spectroscopist may be responsible for manually phasing and baseline correcting hundreds of spectra individually to remove operator-dependent variations, significantly reducing throughput. For metabonomic analysis of human serum, it was observed that the application of a pulsed field gradient filter produced (1)H NMR spectra well suited to automatic phasing routines. Superior baseline characteristics, an increased tolerance to radio frequency pulse imperfections, and improved water suppression were achieved. A concomitant reduction in signal intensity compared with the CPMG method was easily recovered by increasing the number of scans. Principal component analysis (PCA) of spectra, acquired under a variety of experimental conditions, revealed the improved reproducibility and robustness of (1)H NMR pulsed field gradient-filtered metabonomic analyses of serum compared to the CPMG method.

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Year:  2005        PMID: 15890484     DOI: 10.1016/j.jpba.2004.09.060

Source DB:  PubMed          Journal:  J Pharm Biomed Anal        ISSN: 0731-7085            Impact factor:   3.935


  4 in total

1.  1H nuclear magnetic resonance-based extracellular metabolomic analysis of multidrug resistant Tca8113 oral squamous carcinoma cells.

Authors:  Hui Wang; Jiao Chen; Yun Feng; Wenjie Zhou; Jihua Zhang; Y U Yu; Xiaoqian Wang; Ping Zhang
Journal:  Oncol Lett       Date:  2015-04-21       Impact factor: 2.967

2.  Evaluation of Fumaric Acid and Maleic Acid as Internal Standards for NMR Analysis of Protein Precipitated Plasma, Serum, and Whole Blood.

Authors:  G A Nagana Gowda; Natalie N Hong; Daniel Raftery
Journal:  Anal Chem       Date:  2021-02-04       Impact factor: 6.986

3.  Analysis of plasma metabolic biomarkers in the development of 4-nitroquinoline-1-oxide-induced oral carcinogenesis in rats.

Authors:  Xiangli Kong; Xiaoqin Yang; Jinglin Zhou; Sixiu Chen; Xiaoyu Li; Fan Jian; Pengchi Deng; Wei Li
Journal:  Oncol Lett       Date:  2014-10-15       Impact factor: 2.967

4.  Comparative metabonomics of Wenxin Keli and Verapamil reveals differential roles of gluconeogenesis and fatty acid β-oxidation in myocardial injury protection.

Authors:  Miaomiao Jiang; Qiuying Wang; Jingrui Chen; Yanan Wang; Guanwei Fan; Yan Zhu
Journal:  Sci Rep       Date:  2017-08-18       Impact factor: 4.379

  4 in total

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