Literature DB >> 20003623

Metabolite fingerprinting of urine suggests breed-specific dietary metabolism differences in domestic dogs.

Manfred Beckmann1, David P Enot, David P Overy, Ian M Scott, Paul G Jones, David Allaway, John Draper.   

Abstract

Selective breeding of dogs has culminated in a large number of modern breeds distinctive in terms of size, shape and behaviour. Inadvertently, a range of breed-specific genetic disorders have become fixed in some pure-bred populations. Several inherited conditions confer chronic metabolic defects that are influenced strongly by diet, but it is likely that many less obvious breed-specific differences in physiology exist. Using Labrador retrievers and miniature Schnauzers maintained in a simulated domestic setting on a controlled diet, an experimental design was validated in relation to husbandry, sampling and sample processing for metabolomics. Metabolite fingerprints were generated from 'spot' urine samples using flow injection electrospray MS (FIE-MS). With class based on breed, urine chemical fingerprints were modelled using Random Forest (a supervised data classification technique), and metabolite features (m/z) explanatory of breed-specific differences were putatively annotated using the ARMeC database (http://www.armec.org). GC-MS profiling to confirm FIE-MS predictions indicated major breed-specific differences centred on the metabolism of diet-related polyphenols. Metabolism of further diet components, including potentially prebiotic oligosaccharides, animal-derived fats and glycerol, appeared significantly different between the two breeds. Analysis of the urinary metabolome of young male dogs representative of a wider range of breeds from animals maintained under domestic conditions on unknown diets provided preliminary evidence that many breeds may indeed have distinctive metabolic differences, with significant differences particularly apparent in comparisons between large and smaller breeds.

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Year:  2009        PMID: 20003623     DOI: 10.1017/S000711450999300X

Source DB:  PubMed          Journal:  Br J Nutr        ISSN: 0007-1145            Impact factor:   3.718


  9 in total

1.  Genome-wide association studies of 74 plasma metabolites of German shepherd dogs reveal two metabolites associated with genes encoding their enzymes.

Authors:  Pamela Xing Yi Soh; Juliana Maria Marin Cely; Sally-Anne Mortlock; Christopher James Jara; Rachel Booth; Siria Natera; Ute Roessner; Ben Crossett; Stuart Cordwell; Mehar Singh Khatkar; Peter Williamson
Journal:  Metabolomics       Date:  2019-09-06       Impact factor: 4.290

Review 2.  Canine metabolomics advances.

Authors:  Graciela Carlos; Francisco Paulo Dos Santos; Pedro Eduardo Fröehlich
Journal:  Metabolomics       Date:  2020-01-18       Impact factor: 4.290

3.  Ultra high performance liquid chromatography-high resolution mass spectrometry plasma lipidomics can distinguish between canine breeds despite uncontrolled environmental variability and non-standardized diets.

Authors:  Amanda J Lloyd; Manfred Beckmann; Thomas Wilson; Kathleen Tailliart; David Allaway; John Draper
Journal:  Metabolomics       Date:  2017-01-05       Impact factor: 4.290

4.  The urine metabolome differs between lean and overweight Labrador Retriever dogs during a feed-challenge.

Authors:  Josefin Söder; Ragnvi Hagman; Johan Dicksved; Sanna Lindåse; Kjell Malmlöf; Peter Agback; Ali Moazzami; Katja Höglund; Sara Wernersson
Journal:  PLoS One       Date:  2017-06-29       Impact factor: 3.240

5.  Metabolomic profiling to identify effects of dietary calcium reveal the influence of the individual and postprandial dynamics on the canine plasma metabolome.

Authors:  David Allaway; Matt Gilham; Antje Wagner-Golbs; Sandra González Maldonado; Richard Haydock; Alison Colyer; Jonathan Stockman; Phillip Watson
Journal:  J Nutr Sci       Date:  2019-04-10

6.  Metabolomics shows the Australian dingo has a unique plasma profile.

Authors:  Sonu Yadav; Russell Pickford; Robert A Zammit; J William O Ballard
Journal:  Sci Rep       Date:  2021-03-04       Impact factor: 4.379

7.  Characterisation of the main drivers of intra- and inter- breed variability in the plasma metabolome of dogs.

Authors:  Amanda J Lloyd; Manfred Beckmann; Kathleen Tailliart; Wendy Y Brown; John Draper; David Allaway
Journal:  Metabolomics       Date:  2016-03-08       Impact factor: 4.290

8.  Metabolic Profiling Reveals Effects of Age, Sexual Development and Neutering in Plasma of Young Male Cats.

Authors:  David Allaway; Matthew S Gilham; Alison Colyer; Thomas J Jönsson; Kelly S Swanson; Penelope J Morris
Journal:  PLoS One       Date:  2016-12-12       Impact factor: 3.240

9.  Serum lipidome analysis of healthy beagle dogs receiving different diets.

Authors:  Felicitas S Boretti; Bo Burla; Jeremy Deuel; Liang Gao; Markus R Wenk; Annette Liesegang; Nadja S Sieber-Ruckstuhl
Journal:  Metabolomics       Date:  2019-12-03       Impact factor: 4.290

  9 in total

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