4.5 Article

Metabolomic assessment with CE-MS of the nutraceutical effect of Cystoseira spp extracts in an animal model

期刊

ELECTROPHORESIS
卷 32, 期 15, 页码 2055-2062

出版社

WILEY-BLACKWELL
DOI: 10.1002/elps.201000546

关键词

Diabetic rats; Fingerprinting; Metabolomics; Metabonomics; Urine

资金

  1. EADS-CASA
  2. Ministry of Science and Innovation (MICINN) [CTQ2008-03779]
  3. Comunidad de Madrid [S-GEN-0247-2006]

向作者/读者索取更多资源

There is a need of scientific evidence of claimed nutraceutical effects, but also there is a social movement towards the use of natural products and among them algae are seen as rich resources. Within this scenario, the development of methodology for rapid and reliable assessment of markers of efficiency and security of these extracts is necessary. The rat treated with streptozotocin has been proposed as the most appropriate model of systemic oxidative stress for studying antioxidant therapies. Cystoseira is a brown alga containing fucoxanthin and other carothenes whose pressure-assisted extracts were assayed to discover a possible beneficial effect on complications related to diabetes evolution in an acute but short-term model. Urine was selected as the sample and CE-TOF-MS as the analytical technique to obtain the fingerprints in a non-target metabolomic approach. Multivariate data analysis revealed a good clustering of the groups and permitted the putative assignment of compounds statistically significant in the classification. Interestingly a group of compounds associated to lysine glycation and cleavage from proteins was found to be increased in diabetic animals receiving vehicle as compared to control animals receiving vehicle (N6, N6, N6-trimethyl-L-lysine, N-methylnicotinamide, galactosylhydroxylysine, L-carnitine, N6-acetyl-N6-hydroxylysine, fructose-lysine, pipecolic acid, urocanic acid, amino-isobutanoate, formylisoglutamine. Fructoselysine significantly decreased after the treatment changing from a 24% increase to a 19% decrease. CE-MS fingerprinting of urine has provided a group of compounds different to those detected with other techniques and therefore proves the necessity of a cross-platform analysis to obtain a broad view of biological samples.

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