Identification of intra- and inter-individual metabolite variation in plasma metabolite profiles of cats and dogs

Abstract

The purpose of the present study was first to identify drivers of variance in plasma metabolite profiles of cats and dogs that may affect the interpretation of nutritional metabolomic studies. A total of fourteen cats and fourteen dogs housed in environmentally enriched accommodation were fed a single batch of diet to maintain body weight. Fasting blood samples were taken on days 14, 16 and 18 of the study. Gas chromatography -mass spectrometry (GC-MS), liquid chromatography (LC) -MS/MS and solid-phase extraction-LC -MS/MS analyses were used for metabolite profiling. Principal component (PC) analysis that indicated 31 and 27 % of the variance was explained in PC1 and PC2 for cats and dogs, respectively, with most individuals occupying a unique space. As the individual was a major driver of variance in the plasma metabolome, the second objective was to identify metabolites associated with the individual variation observed. The proportion of intra-and inter-individual variance was calculated for 109 cat and 101 dog metabolites with a low intra-individual variance (SD ,0·05). Of these, fifteen cat and six dog metabolites had inter-individual variance accounting for at least 90 % of the total variance. There were four metabolites common to both species (campesterol, DHA, a cholestenol and a sphingosine moiety). Many of the metabolites with .75 % inter-individual variance were common to both species and to similar areas of metabolism. In summary, the individual is an important driver of variance in the fasted plasma metabolome, and specific metabolites and areas of metabolism may be differentially regulated by individuals in two companion animal species.Key words: Cats: Dogs: Plasma metabolites: Nutritional metabolomics Metabolomics may be defined as the measure of as many metabolites as possible in a biological sample. It has many applications such as identifying potential diagnostic biomarkers in disease pathology, establishing drug modes of action and investigating biological phenomena through datadriven hypothesis generation. A strength of the data-driven approach is that it enables investigations of complex, nonlinear, interactive multivariate systems which are difficult to control or where no clear hypothesis exists (1) . Nutrition is a multi-factorial and complex process, and nutritional metabolomics has been proposed as a powerful tool to investigate the interaction between the individual and their diet (2) , and the influence and roles of the individual, their genetics, lifestyle and gastrointestinal flora have been assessed (3) .In the USA and European Union, people are responsible for providing, at least in part, nutritional requirements of more than 250 million companion animals (4,5) , and responsible pet food manufacturers undertake research to ensure their products are nutritionally complete and safe. However, the role of the individual animal in determining their nutritional needs is yet to be elucidated. It is possible that the range of physiologies and genetic backgrounds in dogs makes size ...

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

“…It is possible to speculate that the identification of phosphatidylcholine as a robust marker of breed difference may indicate differences in lipid metabolism and lipid functionality between breeds. This finding parallels work which identified a group of lipids showing high inter-individual variance within individuals of both dogs and cats (Colyer et al 2011 ). The structural similarities and possible biochemical relationships are shown in Fig.…”

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

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Untargeted metabolomic analysis in naturally occurring canine diabetes mellitus identifies similarities to human Type 1 Diabetes

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