Literature DB >> 11078872

An NMR-based metabonomic approach to investigate the biochemical consequences of genetic strain differences: application to the C57BL10J and Alpk:ApfCD mouse.

C L Gavaghan1, E Holmes, E Lenz, I D Wilson, J K Nicholson.   

Abstract

As the human genome sequencing projects near completion, there is an active search for technologies that can provide insights into the genetic basis for physiological variation and interpreting gene expression in terms of phenotype at the whole organism level in order to understand the pathophysiology of disease. We present a novel metabonomic approach to the investigation of genetic influences on metabolic balance and metabolite excretion patterns in two phenotypically normal mouse models (C57BL10J and Alpk:ApfCD). Chemometric techniques were applied to optimise recovery of biochemical information from complex (1)H NMR urine spectra and to determine metabolic biomarker differences between the two strains. Differences were observed in tricarboxylic acid cycle intermediates and methylamine pathway activity. We suggest here a new 'metabotype' concept, which will be of value in relating quantitative physiological and biochemical data to both phenotypic and genetic variation in animals and man.

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Year:  2000        PMID: 11078872     DOI: 10.1016/s0014-5793(00)02147-5

Source DB:  PubMed          Journal:  FEBS Lett        ISSN: 0014-5793            Impact factor:   4.124


  51 in total

Review 1.  Metabolomics--the link between genotypes and phenotypes.

Authors:  Oliver Fiehn
Journal:  Plant Mol Biol       Date:  2002-01       Impact factor: 4.076

Review 2.  Metabolic profiles to define the genome: can we hear the phenotypes?

Authors:  Julian L Griffin
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2004-06-29       Impact factor: 6.237

3.  Influence of common preanalytical variations on the metabolic profile of serum samples in biobanks.

Authors:  Ophélie Fliniaux; Gwenaelle Gaillard; Antoine Lion; Dominique Cailleu; François Mesnard; Fotini Betsou
Journal:  J Biomol NMR       Date:  2011-10-02       Impact factor: 2.835

Review 4.  The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball?

Authors:  Julian L Griffin
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-01-29       Impact factor: 6.237

5.  Effects of a prolonged standardized diet on normalizing the human metabolome.

Authors:  Jason H Winnike; Marjorie G Busby; Paul B Watkins; Thomas M O'Connell
Journal:  Am J Clin Nutr       Date:  2009-10-28       Impact factor: 7.045

Review 6.  Metabolomics, pathway regulation, and pathway discovery.

Authors:  Guo-Fang Zhang; Sushabhan Sadhukhan; Gregory P Tochtrop; Henri Brunengraber
Journal:  J Biol Chem       Date:  2011-05-12       Impact factor: 5.157

7.  Nutriome-metabolome relationships provide insights into dietary intake and metabolism.

Authors:  Joram M Posma; Isabel Garcia-Perez; Gary Frost; Ghadeer S Aljuraiban; Queenie Chan; Linda Van Horn; Martha Daviglus; Jeremiah Stamler; Elaine Holmes; Paul Elliott; Jeremy K Nicholson
Journal:  Nat Food       Date:  2020-06-22

Review 8.  Opening up the "Black Box": metabolic phenotyping and metabolome-wide association studies in epidemiology.

Authors:  Magda Bictash; Timothy M Ebbels; Queenie Chan; Ruey Leng Loo; Ivan K S Yap; Ian J Brown; Maria de Iorio; Martha L Daviglus; Elaine Holmes; Jeremiah Stamler; Jeremy K Nicholson; Paul Elliott
Journal:  J Clin Epidemiol       Date:  2010-01-08       Impact factor: 6.437

9.  A metabonomic comparison of urinary changes in Zucker and GK rats.

Authors:  Liang-Cai Zhao; Xiao-Dong Zhang; Shi-Xian Liao; Hong-Chang Gao; He-Yao Wang; Dong-Hai Lin
Journal:  J Biomed Biotechnol       Date:  2010-10-13

10.  A novel R-package graphic user interface for the analysis of metabonomic profiles.

Authors:  Jose L Izquierdo-García; Ignacio Rodríguez; Angelos Kyriazis; Palmira Villa; Pilar Barreiro; Manuel Desco; Jesús Ruiz-Cabello
Journal:  BMC Bioinformatics       Date:  2009-10-29       Impact factor: 3.169

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