Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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    Substructure-based annotation of high-resolution multistage MSn spectral trees
    Ridder, L.O. ; Hooft, J.J.J. van der; Verhoeven, S. ; Vos, R.C.H. de; Schaik, R. van; Vervoort, Jacques - \ 2012
    Rapid Communications in Mass Spectrometry 26 (2012)20. - ISSN 0951-4198 - p. 2461 - 2471.
    tandem mass-spectrometry - metabolite identification - discriminating signals - fragmentation trees - accurate mass - metabolomics - dissociation - elucidation - information - software
    RATIONALE High-resolution multistage MSn data contains detailed information that can be used for structural elucidation of compounds observed in metabolomics studies. However, full exploitation of this complex data requires significant analysis efforts by human experts. In silico methods currently used to support data annotation by assigning substructures of candidate molecules are limited to a single level of MS fragmentation. METHODS We present an extended substructure-based approach which allows annotation of hierarchical spectral trees obtained from high-resolution multistage MSn experiments. The algorithm yields a hierarchical tree of substructures of a candidate molecule to explain the fragment peaks observed at consecutive levels of the multistage MSn spectral tree. A matching score is calculated that indicates how well the candidate structure can explain the observed hierarchical fragmentation pattern. RESULTS The method is applied to MSn spectral trees of a set of compounds representing important chemical classes in metabolomics. Based on the calculated score, the correct molecules were successfully prioritized among extensive sets of candidates structures retrieved from the PubChem database. CONCLUSIONS The results indicate that the inclusion of subsequent levels of fragmentation in the automatic annotation of MSn data improves the identification of the correct compounds. We show that, especially in the case of lower mass accuracy, this improvement is not only due to the inclusion of additional fragment ions in the analysis, but also to the specific hierarchical information present in the MSn spectral trees. This method may significantly reduce the time required by MS experts to analyze complex MSn data. Copyright (c)proves 2012 John Wiley & Sons, Ltd.
    Structural elucidation and quantification of phenolic conjugates present in human urine after tea intake
    Hooft, J.J.J. van der; Vos, R.C.H. de; Mihaleva, V. ; Bino, R.J. ; Ridder, L.O. ; Roo, N. de; Jacobs, D.M. ; Duynhoven, J.P.M. van; Vervoort, J.J.M. - \ 2012
    Analytical Chemistry 84 (2012)16. - ISSN 0003-2700 - p. 7263 - 7271.
    tandem mass-spectrometry - green tea - black tea - metabolite identification - ellagic acid - metabolomics - polyphenols - nmr - ingestion - phytochemicals
    In dietary polyphenol exposure studies, annotation and identification of urinary metabolites present at low (micromolar) concentrations are major obstacles. In order to determine the biological activity of specific components, it is necessary to have the correct structures and the quantification of the polyphenol-derived conjugates present in the human body. We present a procedure for identification and quantification of metabolites and conjugates excreted in human urine after single bolus intake of black or green tea. A combination of a solid phase extraction (SPE) preparation step and two high pressure liquid chromatography (HPLC)-based analytical platforms was used; namely, accurate mass fragmentation (HPLC-FTMSn) and mass-guided SPE-trapping of selected compounds for nuclear magnetic resonance spectroscopy (NMR) measurements (HPLC-TOFMS-SPE-NMR). HPLC-FTMSn analysis led to the annotation of 138 urinary metabolites, including 48 valerolactone and valeric acid conjugates. By combining the results from MSn fragmentation with the one dimensional (1D)-1H-NMR spectra of HPLC-TOFMS-SPE trapped compounds, we elucidated the structures of 36 phenolic conjugates, including the glucuronides of 3’,4’-di, and 3’,4’,5’-trihydroxyphenyl-¿-valerolactone, three urolithin glucuronides, and indole-3-acetic acid glucuronide. We also obtained 26 hours of quantitative excretion profiles for specific valerolactone conjugates. The combination of the HPLC-FTMSn and HPLC-TOFMS-SPE-NMR platforms results in the efficient identification and quantification of low abundant phenolic conjugates down to nanomoles of trapped amounts of metabolite corresponding to micromolar metabolite concentrations in urine
    Preventive doping control screening analysis of prohibited substances in human urine using rapid-resolution liquid chromatography/high-resolution time-of-flight mass spectrometry
    Vonaparti, A. ; Lyris, E. ; Angelis, Y.S. ; Panderi, I. ; Koupparis, M. ; Tsantili- Kakoulidou, A. ; Peters, R.J.B. ; Nielen, M.W.F. ; Georgakopoulos, C.G. - \ 2010
    Rapid Communications in Mass Spectrometry 24 (2010)11. - ISSN 0951-4198 - p. 1595 - 1609.
    solid-phase extraction - anabolic-steroids - metabolite identification - high-throughput - olympic games - drugs - stimulants - ionization - validation - diuretics
    Unification of the screening protocols for a wide range of doping agents has become an important issue for doping control laboratories. This study presents the development and validation of a generic liquid chromatography/time-of-flight mass spectrometry (LC/TOFMS) screening method of 241 small molecule analytes from various categories of prohibited substances (stimulants, narcotics, diuretics, ß2-agonists, ß-blockers, hormone antagonists and modulators, glucocorticosteroids and anabolic agents). It is based on a single-step liquid-liquid extraction of hydrolyzed urine and the use of a rapid-resolution liquid chromatography/high-resolution time-of-flight mass spectrometric system acquiring continuous full scan data. Electrospray ionization in the positive mode was used. Validation parameters consisted of identification capability, limit of detection, specificity, ion suppression, extraction recovery, repeatability and mass accuracy. Detection criteria were established on the basis of retention time reproducibility and mass accuracy. The suitability of the methodology for doping control was demonstrated with positive urine samples. The preventive role of the method was proved by the case where full scan acquisition with accurate mass measurement allowed the retrospective reprocessing of acquired data from past doping control samples for the detection of a designer drug, the stimulant 4-methyl-2-hexanamine, which resulted in re-reporting a number of stored samples as positives for this particular substance, when, initially, they had been reported as negatives.
    Screening in veterinary drug analysis and sports doping control based on full-scan, accurate-mass spectrometry
    Peters, R.J.B. ; Stolker, A.A.M. ; Mol, J.G.J. ; Lommen, A. ; Lyris, E. ; Angelis, Y.S. ; Vonaparti, A. ; Stamou, M. ; Georgakopoulos, C.G. ; Nielen, M.W.F. - \ 2010
    TrAC : Trends in Analytical Chemistry 29 (2010)11. - ISSN 0165-9936 - p. 1250 - 1268.
    growth-promoting agents - horse urine analysis - uplc-tof-ms - liquid-chromatography - residue analysis - gas-chromatography - metabolite identification - threshold substances - organic pollutants - unknown pesticides
    A common trend in food contaminants and sports doping control is towards a limited number of targeted, full-scan, accurate-mass spectrometry (MS) methods based on time-of-flight (TOF) or Fourier-transform orbital trap (Orbitrap) mass analyzers. Retrospective analysis of the full-scan datasets of signals from emerging contaminants, novel metabolites and illegal designer substances is a major step forward. We present data from recent applications of gas chromatography with TOF-MS, ultra-high-performance liquid chromatography (LC) with TOF-MS and LC-Orbitrap MS in the screening of European Commission-regulated veterinary drugs and other contaminants in foods, and World Anti-Doping Agency-prohibited substances. We discuss the potential impact of these new approaches on future developments.
    Accurate mass error correction in liquid chromatography time-of-flight mass spectrometry based metabolomics
    Mihaleva, V.V. ; Vorst, O.F.J. ; Maliepaard, C.A. ; Verhoeven, H.A. ; Vos, C.H. de; Hall, R.D. ; Ham, R.C.H.J. van - \ 2008
    Metabolomics 4 (2008)2. - ISSN 1573-3882 - p. 171 - 182.
    metabolite identification - database - tomato - tool
    Compound identification and annotation in (untargeted) metabolomics experiments based on accurate mass require the highest possible accuracy of the mass determination. Experimental LC/TOF-MS platforms equipped with a time-to-digital converter (TDC) give the best mass estimate for those mass signals with an intensity similar to that of the lock-mass used for internal calibration. However, they systematically underestimate the mass obtained at higher signal intensity and overestimate it at low signal intensities compared to that of the lock-mass. To compensate for these effects, specific tools are required for correction and automation of accurate mass calculations from LC/MS signals. Here, we present a computational procedure for the derivation of an intensity-dependent mass correction function. The chromatographic mass signals for a set of known compounds present in a large number of samples were reconstructed over consecutive scans for each sample. It was found that the mass error is a linear function of the logarithm of the signal intensity adjusted to the associated lock-mass intensity. When applied to all mass data points, the correction function reduced the mass error for the majority of the tested compounds to ¿1 ppm over a wide range of signal intensities. The mass correction function has been implemented in a Python 2.4 script, which accepts raw data in NetCDF format as input, corrects the detected masses and returns the corrected NetCDF files for subsequent (automated) processing, such as mass signal alignment and database searching
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