Literature DB >> 15906010

Mass spectrometric identification of modified urinary nucleosides used as potential biomedical markers by LC-ITMS coupling.

Bernd Kammerer1, Antje Frickenschmidt, Christa E Müller, Stefan Laufer, Christoph H Gleiter, Hartmut Liebich.   

Abstract

In diseases accompanied by strong metabolic disorders, like cancer and AIDS, modifying enzymes are up- or down-regulated. As a result, many different types of metabolic end-products, including abnormal amounts of modified nucleosides, are found in urine. These nucleosides are degradation products of an impaired ribonucleic acid (RNA) metabolism, which affects the nucleoside pattern in urine. In several basic experiments we elucidated the fragmentation pathways of 16 characteristic nucleosides and six corresponding nucleic bases that occur in urine using electrospray ionization ion trap MS(5) (ESI-ITMS) experiments operated in positive ionization mode. For urinary nucleoside analysis, we developed an auto-LC-MS3 method based on prepurification via boronate gel affinity chromatography followed by reversed phase chromatography. For this purpose, an endcapped LiChroCART Superspher RP 18 column with a gradient of ammonium formate and a methanol-water mixture was used. This method gives a limit of detection of between 0.1 and 9.6 pmol for 15 standard nucleosides, depending on the basicity of the nucleoside. Overall, the detection of 36 nucleosides from urine was feasible. It was shown that this auto-LC-MS3 method is a valuable tool for assigning nucleosides from complex biological matrices, and it may be utilized in the diagnosis of diseases associated with disorders in RNA metabolism.

Entities:  

Mesh:

Substances:

Year:  2005        PMID: 15906010     DOI: 10.1007/s00216-005-3232-2

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.142


  14 in total

1.  Revisiting the reactivity of uracil during collision induced dissociation: tautomerism and charge-directed processes.

Authors:  Daniel G Beach; Wojciech Gabryelski
Journal:  J Am Soc Mass Spectrom       Date:  2012-02-14       Impact factor: 3.109

2.  A nano-chip-LC/MSn based strategy for characterization of modified nucleosides using reduced porous graphitic carbon as a stationary phase.

Authors:  Anders Michael Bernth Giessing; Lincoln Greyson Scott; Finn Kirpekar
Journal:  J Am Soc Mass Spectrom       Date:  2011-04-15       Impact factor: 3.109

3.  Collisionally activated dissociation of protonated 2'-deoxycytidine, 2'-deoxyuridine, and their oxidatively damaged derivatives.

Authors:  Huachuan Cao; Yinsheng Wang
Journal:  J Am Soc Mass Spectrom       Date:  2006-07-26       Impact factor: 3.109

4.  Direct Mass Spectrometry Analysis of Untreated Samples of Ultralow Amounts Using Extraction Nano-Electrospray.

Authors:  Yue Ren; Jiangjiang Liu; Linfan Li; Morgan N McLuckey; Zheng Ouyang
Journal:  Anal Methods       Date:  2013-12-07       Impact factor: 2.896

5.  Unraveling the RNA modification code with mass spectrometry.

Authors:  Richard Lauman; Benjamin A Garcia
Journal:  Mol Omics       Date:  2020-04-14

6.  High information throughput analysis of nucleotides and their isotopically enriched isotopologues by direct-infusion FTICR-MS.

Authors:  Pawel Lorkiewicz; Richard M Higashi; Andrew N Lane; Teresa W-M Fan
Journal:  Metabolomics       Date:  2011-12-09       Impact factor: 4.290

7.  Identification of urinary modified nucleosides and ribosylated metabolites in humans via combined ESI-FTICR MS and ESI-IT MS analysis.

Authors:  Dino Bullinger; Richard Fux; Graeme Nicholson; Stefan Plontke; Claus Belka; Stefan Laufer; Christoph H Gleiter; Bernd Kammerer
Journal:  J Am Soc Mass Spectrom       Date:  2008-06-28       Impact factor: 3.109

Review 8.  The state-of-the-art determination of urinary nucleosides using chromatographic techniques "hyphenated" with advanced bioinformatic methods.

Authors:  Wiktoria Struck; Małgorzata Waszczuk-Jankowska; Roman Kaliszan; Michał J Markuszewski
Journal:  Anal Bioanal Chem       Date:  2011-02-27       Impact factor: 4.142

9.  Prediction of breast cancer by profiling of urinary RNA metabolites using Support Vector Machine-based feature selection.

Authors:  Carsten Henneges; Dino Bullinger; Richard Fux; Natascha Friese; Harald Seeger; Hans Neubauer; Stefan Laufer; Christoph H Gleiter; Matthias Schwab; Andreas Zell; Bernd Kammerer
Journal:  BMC Cancer       Date:  2009-04-05       Impact factor: 4.430

10.  Metabolic signature of breast cancer cell line MCF-7: profiling of modified nucleosides via LC-IT MS coupling.

Authors:  Dino Bullinger; Hans Neubauer; Tanja Fehm; Stefan Laufer; Christoph H Gleiter; Bernd Kammerer
Journal:  BMC Biochem       Date:  2007-11-29       Impact factor: 4.059

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.