Article

Comprehensive 2-dimensional gas chromatography fast quadrupole mass spectrometry (GC × GC-qMS) for urinary steroid profiling: mass spectral characteristics with chemical ionization.

Division of Nutritional Sciences, Cornell University, Ithaca, NY 14853, USA.
Drug Testing and Analysis (Impact Factor: 2.82). 12/2011; 3(11-12):857-67. DOI: 10.1002/dta.380
Source: PubMed

ABSTRACT Comprehensive 2-dimensional gas chromatography (GC × GC), coupled to either a time of flight mass spectrometry (TOF-MS) or a fast scanning quadrupole MS (qMS) has greatly increased the peak capacity and separation space compared to conventional GC-MS. However, commercial GC × GC-TOFMS systems are not equipped with chemical ionization (CI) and do not provide dominant molecular ions or enable single ion monitoring for maximal sensitivity. A GC × GC-qMS in mass scanning mode was investigated with electron ionization (EI) and positive CI (PCI), using CH(4) and NH(3) as reagent gases. Compared to EI, PCI-NH(3) produced more abundant molecular ions and high mass, structure-specific ions for steroid acetates. Chromatography in two dimensions was optimized with a mixture of 12 endogenous and 3 standard acetylated steroids (SM15-AC) relevant to doping control. Eleven endogenous target steroid acetates were identified in normal urine based on their two retention times, and EI and PCI-NH(3) mass spectra; nine of these endogenous target steroid acetates were identified in congenital adrenal hyperplasia (CAH) patients. The difference between the urinary steroids profiles of normal individuals and those from CAH patients can easily be visually distinguished by their GC × GC-qMS chromatograms. We focus here on the comparison and interpretation of the various mass spectra of the targeted endogenous steroids. PCI-NH(3) mass spectra were most useful for unambiguous molecular weight determination and for establishing the number of -OH by the losses of one or more acetate groups. We conclude that PCI-NH(3) with GC × GC-qMS provides improved peak capacity and pseudomolecular ions with structural specificity.

0 Bookmarks
 · 
137 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Lipids are diverse families of biomolecules that are involved in essential structural as well as signalling roles in biology. The analytical measurement of lipids and their identification & quantitation has become a major research area, in particular in biomedical science as many human pathologies are associated with lipid metabolism disorders. This review provides a brief overview over experimental workflows of lipid isolation and mass spectrometry based detection methods robust enough to study lipid profiles in a clinical context.
    Glycomics and Lipidomics. 01/2014; 4(2).
  • [Show abstract] [Hide abstract]
    ABSTRACT: A method capable of screening for multiple steroids in urine has been developed, using a series of twelve structurally similar, and commercially relevant compounds as target analytes. A molecularly imprinted solid phase extraction clean-up step was used to make the sample suitable for injection onto a GCxGC-MS setup. Significant improvements compared to a commercially available C-18 material were observed. Each individual steroid was able to be separated and identified, using both the retention profile and diagnostic fragmentation ion monitoring abilities of the comprehensive chromatographic-mass spectrometry method. Effective LODs of between 11.7 and 27.0 pg were calculated for individual steroids, effectively equivalent to concentration levels of between 0.234 and 0.540 ng mL-1 in urine, while the application of multiple screen was demonstrated using a 10 ng mL-1 mixed sample. The nature of this study also removes the need for sample derivitisation which speeds up the screening process.
    The Analyst 07/2014; · 3.91 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Urine has long been a "favored" biofluid among metabolomics researchers. It is sterile, easy-to-obtain in large volumes, largely free from interfering proteins or lipids and chemically complex. However, this chemical complexity has also made urine a particularly difficult substrate to fully understand. As a biological waste material, urine typically contains metabolic breakdown products from a wide range of foods, drinks, drugs, environmental contaminants, endogenous waste metabolites and bacterial by-products. Many of these compounds are poorly characterized and poorly understood. In an effort to improve our understanding of this biofluid we have undertaken a comprehensive, quantitative, metabolome-wide characterization of human urine. This involved both computer-aided literature mining and comprehensive, quantitative experimental assessment/validation. The experimental portion employed NMR spectroscopy, gas chromatography mass spectrometry (GC-MS), direct flow injection mass spectrometry (DFI/LC-MS/MS), inductively coupled plasma mass spectrometry (ICP-MS) and high performance liquid chromatography (HPLC) experiments performed on multiple human urine samples. This multi-platform metabolomic analysis allowed us to identify 445 and quantify 378 unique urine metabolites or metabolite species. The different analytical platforms were able to identify (quantify) a total of: 209 (209) by NMR, 179 (85) by GC-MS, 127 (127) by DFI/LC-MS/MS, 40 (40) by ICP-MS and 10 (10) by HPLC. Our use of multiple metabolomics platforms and technologies allowed us to identify several previously unknown urine metabolites and to substantially enhance the level of metabolome coverage. It also allowed us to critically assess the relative strengths and weaknesses of different platforms or technologies. The literature review led to the identification and annotation of another 2206 urinary compounds and was used to help guide the subsequent experimental studies. An online database containing the complete set of 2651 confirmed human urine metabolite species, their structures (3079 in total), concentrations, related literature references and links to their known disease associations are freely available at http://www.urinemetabolome.ca.
    PLoS ONE 09/2013; 8(9):e73076. · 3.53 Impact Factor