Literature DB >> 23596967

Multicompartmental nontargeted LC-MS metabolomics: explorative study on the metabolic responses of rye fiber versus refined wheat fiber intake in plasma and urine of hypercholesterolemic pigs.

Natalja P Nørskov1, Mette Skou Hedemann, Helle Nygaard Lærke, Knud Erik Bach Knudsen.   

Abstract

A multicompartmental nontargeted LC-MS metabolomics approach was used to study the metabolic responses on plasma and urine of hypercholesterolemic pigs after consumption of diets with contrasting dietary fiber composition (whole grain rye with added rye bran versus refined wheat). To study the metabolic responses, we performed a supervised multivariate data analyses used for pattern recognition, which revealed marked effects of the diets on both plasma and urine metabolic profiles. Diverse pools of metabolites were responsible for the discrimination between the diets. Elevated levels of phenolic compounds and dicarboxylic acids were detected in urine of pigs after rye consumption compared to refined wheat. Furthermore, consumption of rye was characterized by lower levels of linoleic acid derived oxylipins and cholesterol in the plasma metabolic profiles. These results indicate that higher consumption of nonrefined dietary fiber is reflected in higher excretion of phenolic compounds and dicarboxylic acids in urine and lower levels of linoleic acid derived oxylipins and cholesterol in plasma, which can be linked to beneficial health effects of rye components. On the other hand, pro-inflammatory lipid mediators were detected in higher concentration after rye consumption compared to refined wheat, which is opposite to what would be expected. These may indicate that even though a positive lowering effect with respect to cholesterol and fatty acids was achieved, this effect of rye dietary fiber was not sufficient to prevent inflammation in pigs. Moreover, we performed an alignment of the metabolic profiles between the breads consumed by pigs, plasma, and urine with the purpose to follow the metabolic fate of the compounds and to identify their pathways. One metabolite was identified in all three compartments, 16 metabolites were similar between bread and plasma, 3 were similar between plasma and urine, and 2 were similar between bread and urine. The use of multicompartmental metabolomics offered higher order information, including intercompartment relationships, and provided novel targets for future research.

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Year:  2013        PMID: 23596967     DOI: 10.1021/pr400164b

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  9 in total

1.  Multiplatform metabolomic fingerprinting as a tool for understanding hypercholesterolemia in Wistar rats.

Authors:  Diana González-Peña; Danuta Dudzik; Clara Colina-Coca; Begoña de Ancos; Antonia García; Coral Barbas; Concepción Sánchez-Moreno
Journal:  Eur J Nutr       Date:  2015-05-13       Impact factor: 5.614

Review 2.  Targeted lipidomic strategies for oxygenated metabolites of polyunsaturated fatty acids.

Authors:  Giuseppe Astarita; Alexandra C Kendall; Edward A Dennis; Anna Nicolaou
Journal:  Biochim Biophys Acta       Date:  2014-12-05

3.  Targeted and Untargeted Metabolic Profiling to Discover Bioactive Compounds in Seaweeds and Hemp Using Gas and Liquid Chromatography-Mass Spectrometry.

Authors:  Natalja P Nørskov; Annette Bruhn; Andrew Cole; Mette Olaf Nielsen
Journal:  Metabolites       Date:  2021-04-22

4.  Pea fiber and wheat bran fiber show distinct metabolic profiles in rats as investigated by a 1H NMR-based metabolomic approach.

Authors:  Guangmang Liu; Liang Xiao; Tingting Fang; Yimin Cai; Gang Jia; Hua Zhao; Jing Wang; Xiaoling Chen; Caimei Wu
Journal:  PLoS One       Date:  2014-12-26       Impact factor: 3.240

Review 5.  Standardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review.

Authors:  Abdul-Hamid Emwas; Claudio Luchinat; Paola Turano; Leonardo Tenori; Raja Roy; Reza M Salek; Danielle Ryan; Jasmeen S Merzaban; Rima Kaddurah-Daouk; Ana Carolina Zeri; G A Nagana Gowda; Daniel Raftery; Yulan Wang; Lorraine Brennan; David S Wishart
Journal:  Metabolomics       Date:  2014-11-21       Impact factor: 4.290

6.  Urinary Biomarkers of Whole Grain Wheat Intake Identified by Non-targeted and Targeted Metabolomics Approaches.

Authors:  Yingdong Zhu; Pei Wang; Wei Sha; Shengmin Sang
Journal:  Sci Rep       Date:  2016-11-02       Impact factor: 4.379

7.  Comprehensive Secondary Metabolite Profiling Toward Delineating the Solid and Submerged-State Fermentation of Aspergillus oryzae KCCM 12698.

Authors:  Su Y Son; Sunmin Lee; Digar Singh; Na-Rae Lee; Dong-Yup Lee; Choong H Lee
Journal:  Front Microbiol       Date:  2018-05-25       Impact factor: 5.640

8.  Integrative analysis of indirect calorimetry and metabolomics profiling reveals alterations in energy metabolism between fed and fasted pigs.

Authors:  Hu Liu; Yifan Chen; Dongxu Ming; Ji Wang; Zhen Li; Xi Ma; Junjun Wang; Jaap van Milgen; Fenglai Wang
Journal:  J Anim Sci Biotechnol       Date:  2018-05-16

9.  Dynamic changes of postprandial plasma metabolites after intake of corn-soybean meal or casein-starch diets in growing pigs.

Authors:  Tiantian Li; Shimeng Huang; Juntao Li; Hu Liu; Wei Wang; Na Li; Meng Shi; Shiyu Tao; Shuai Zhang; Zhen Li; Junjun Wang
Journal:  J Anim Sci Biotechnol       Date:  2019-05-28
  9 in total

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