Literature DB >> 14674455

Screening of biomarkers in rat urine using LC/electrospray ionization-MS and two-way data analysis.

Helena Idborg-Björkman1, Per-Olof Edlund, Olav M Kvalheim, Ina Schuppe-Koistinen, Sven P Jacobsson.   

Abstract

Biofluids, like urine, form very complex matrixes containing a large number of potential biomarkers, that is, changes of endogenous metabolites in response to xenobiotic exposure. This paper describes a fast and sensitive method of screening biomarkers in rat urine. Biomarkers for phospholipidosis, induced by an antidepressant drug, were studied. Urine samples from rats exposed to citalopram were analyzed using solid-phase extraction (SPE) and liquid chromatography mass spectrometry (LC/MS) analysis detecting negative ions. A fast iterative method, called Gentle, was used for the automatic curve resolution, and metabolic fingerprints were obtained. After peak alignment principal component analysis (PCA) was performed for pattern recognition, PCA loadings were studied as a means of discovering potential biomarkers. In this study a number of potential biomarkers of phospholipidosis in rats are discussed. They are reported by their retention time and base peak, as their identification is not within the scope of the study. In addition to the fact that it was possible to differentiate control samples from dosed samples, the data were very easy to interpret, and signals from xenobiotic-related substances were easily removed without affecting the endogenous compounds. The proposed method is a complement or an alternative to NMR for metabolomic applications.

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Year:  2003        PMID: 14674455     DOI: 10.1021/ac0341618

Source DB:  PubMed          Journal:  Anal Chem        ISSN: 0003-2700            Impact factor:   6.986


  9 in total

1.  Nonlinear data alignment for UPLC-MS and HPLC-MS based metabolomics: quantitative analysis of endogenous and exogenous metabolites in human serum.

Authors:  Anders Nordström; Grace O'Maille; Chuan Qin; Gary Siuzdak
Journal:  Anal Chem       Date:  2006-05-15       Impact factor: 6.986

Review 2.  Mass spectrometry-based metabolomics.

Authors:  Katja Dettmer; Pavel A Aronov; Bruce D Hammock
Journal:  Mass Spectrom Rev       Date:  2007 Jan-Feb       Impact factor: 10.946

3.  apLCMS--adaptive processing of high-resolution LC/MS data.

Authors:  Tianwei Yu; Youngja Park; Jennifer M Johnson; Dean P Jones
Journal:  Bioinformatics       Date:  2009-05-04       Impact factor: 6.937

4.  Analyzing LC/MS metabolic profiling data in the context of existing metabolic networks.

Authors:  Tianwei Yu; Yun Bai
Journal:  Curr Metabolomics       Date:  2013-01-01

Review 5.  LC-MS-based metabolomics.

Authors:  Bin Zhou; Jun Feng Xiao; Leepika Tuli; Habtom W Ressom
Journal:  Mol Biosyst       Date:  2011-11-01

6.  Multiplatform Metabolomics Studies of Human Cancers With NMR and Mass Spectrometry Imaging.

Authors:  Anya B Zhong; Isabella H Muti; Stephen J Eyles; Richard W Vachet; Kristen N Sikora; Cedric E Bobst; David Calligaris; Sylwia A Stopka; Jeffery N Agar; Chin-Lee Wu; Mari A Mino-Kenudson; Nathalie Y R Agar; David C Christiani; Igor A Kaltashov; Leo L Cheng
Journal:  Front Mol Biosci       Date:  2022-04-08

7.  Hybrid feature detection and information accumulation using high-resolution LC-MS metabolomics data.

Authors:  Tianwei Yu; Youngja Park; Shuzhao Li; Dean P Jones
Journal:  J Proteome Res       Date:  2013-02-12       Impact factor: 4.466

8.  Metabolic Fingerprinting in Toxicological Assessment Using FT-ICR MS.

Authors:  Mina Hasegawa; Mika Ide; Mitsuru Kuwamura; Jyoji Yamate; Shigeo Takenaka
Journal:  J Toxicol Pathol       Date:  2010-06-30       Impact factor: 1.628

Review 9.  Metabolomics and its Applications in Cancer Cachexia.

Authors:  Pengfei Cui; Xiaoyi Li; Caihua Huang; Qinxi Li; Donghai Lin
Journal:  Front Mol Biosci       Date:  2022-02-07
  9 in total

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