Literature DB >> 15595670

Algorithm for locating analytes of interest based on mass spectral similarity in GC x GC-TOF-MS data: analysis of metabolites in human infant urine.

Amanda E Sinha1, Janiece L Hope, Bryan J Prazen, Erik J Nilsson, Rhona M Jack, Robert E Synovec.   

Abstract

The developed algorithm reported herein, referred to as "DotMap," addresses the need to rapidly identify analyte peak locations in gas chromatography x gas chromatography-time of flight mass spectrometry (GC x GC-TOF-MS) data. The third-order structure of GC x GC-TOF-MS data is such that at each point in the GC x GC chromatogram, a complete mass spectrum is measured. DotMap utilizes this third-order structure to search for the location of a given spectrum of interest in a complete data set, or in a user selected portion of the complete data set. The algorithm returns a contour plot indicating the location of signal(s) with the most similar mass spectra to the analyte of interest. A spectrum from the region indicated is then subjected to an automated mass spectral search to give immediate feedback on the accuracy of the analysis. This algorithm was investigated with a trimethylsilyl (TMS) derivatized human infant urine sample that contained organic acid metabolites. One hundred percent of 12 selected TMS derivatized organic acid metabolites in human infant urine were located with the DotMap algorithm. A typical automated DotMap analysis takes 30 s on a 1.6 GHz PC with 1024 MB of RAM. Vanillic acid (TMS) was located by DotMap, but also exhibited overlap with other organic acids. The presence of vanillic acid (TMS) was confirmed by subjecting the appropriate GC x GC region to chemometric signal deconvolution by PARAFAC to yield pure component information suitable for subsequent quantification.

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Year:  2004        PMID: 15595670

Source DB:  PubMed          Journal:  J Chromatogr A        ISSN: 0021-9673            Impact factor:   4.759


  11 in total

1.  Between Metabolite Relationships: an essential aspect of metabolic change.

Authors:  Jeroen J Jansen; Ewa Szymańska; Huub C J Hoefsloot; Doris M Jacobs; Katrin Strassburg; Age K Smilde
Journal:  Metabolomics       Date:  2011-05-24       Impact factor: 4.290

2.  Comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry analysis of metabolites in fermenting and respiring yeast cells.

Authors:  Rachel E Mohler; Kenneth M Dombek; Jamin C Hoggard; Elton T Young; Robert E Synovec
Journal:  Anal Chem       Date:  2006-04-15       Impact factor: 6.986

Review 3.  Fast, comprehensive two-dimensional liquid chromatography.

Authors:  Dwight R Stoll; Xiaoping Li; Xiaoli Wang; Peter W Carr; Sarah E G Porter; Sarah C Rutan
Journal:  J Chromatogr A       Date:  2007-08-30       Impact factor: 4.759

4.  Identification and evaluation of cycling yeast metabolites in two-dimensional comprehensive gas chromatography-time-of-flight-mass spectrometry data.

Authors:  Rachel E Mohler; Benjamin P Tu; Kenneth M Dombek; Jamin C Hoggard; Elton T Young; Robert E Synovec
Journal:  J Chromatogr A       Date:  2007-10-25       Impact factor: 4.759

5.  DISCO: distance and spectrum correlation optimization alignment for two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics.

Authors:  Bing Wang; Aiqin Fang; John Heim; Bogdan Bogdanov; Scott Pugh; Mark Libardoni; Xiang Zhang
Journal:  Anal Chem       Date:  2010-06-15       Impact factor: 6.986

6.  Highly sensitive and selective analysis of urinary steroids by comprehensive two-dimensional gas chromatography combined with positive chemical ionization quadrupole mass spectrometry.

Authors:  Ying Zhang; Herbert J Tobias; J Thomas Brenna
Journal:  Analyst       Date:  2012-05-18       Impact factor: 4.616

7.  Toward a global analysis of metabolites in regulatory mutants of yeast.

Authors:  Elizabeth M Humston; Kenneth M Dombek; Benjamin P Tu; Elton T Young; Robert E Synovec
Journal:  Anal Bioanal Chem       Date:  2011-03-17       Impact factor: 4.142

8.  Time-dependent profiling of metabolites from Snf1 mutant and wild type yeast cells.

Authors:  Elizabeth M Humston; Kenneth M Dombek; Jamin C Hoggard; Elton T Young; Robert E Synovec
Journal:  Anal Chem       Date:  2008-10-01       Impact factor: 6.986

9.  OmicsVis: an interactive tool for visually analyzing metabolomics data.

Authors:  Philip Livengood; Ross Maciejewski; Wei Chen; David S Ebert
Journal:  BMC Bioinformatics       Date:  2012-05-18       Impact factor: 3.169

10.  Semi-automated non-target processing in GC × GC-MS metabolomics analysis: applicability for biomedical studies.

Authors:  Maud M Koek; Frans M van der Kloet; Robert Kleemann; Teake Kooistra; Elwin R Verheij; Thomas Hankemeier
Journal:  Metabolomics       Date:  2010-07-15       Impact factor: 4.290

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