Metabolomics is a science of interest in food analysis to describe and predict properties of food products and processes. It includes the development of analytical methods with the ultimate goal being the identification of so-called 'quality markers', (i.e. sets of metabolites that correlate with, for example, quality, safety, taste, or fragrance of foodstuffs). In turn, these metabolites are influenced by factors as genetic differences of the raw food ingredients (such as animal breed or crop species differences), growth conditions (such as climate, irrigation strategy, or feeding) or production conditions (such as temperature, acidity, or pressure). In cases where the routine-based measurement of a food property faces some limitations such as the lack of knowledge regarding the target compounds to monitor, monitoring based on a limited set of crucial biomarkers is a good alternative, which is of great interest for food safety purposes regarding growth promoting practices. Such an approach may be more efficient than using a classic approach based on a limited set of known metabolites of anabolic compounds. In this context, screening strategies allowing detection of the physiological response resulting from anabolic compound administration are promising approaches to detect their misuse. The global metabolomics workflow implemented for such studies is presented and illustrated through various examples of biological matrices profiling (tissue, blood, urine) and for different classes of anabolic compounds (steroids, b-agonists and somatotropin).
Growth hormone (GH) is a polypeptide suspected of being used in horse racing to speed up physical performances. Despite scientific advances in the recent years, the control of its administration remains difficult. In order to improve it, a metabolomics study through LC-high resolution mass spectrometry measurements was recently initiated to assess the metabolic perturbations caused by recombinant equine growth hormone administration. Few tens of ions not identified structurally were highlighted as compounds responsible for the modification of metabolic profiling observed in treated animals. This previous work was based on the use of Uptisphere Strategy NEC as the chromatographic column. In parallel, more and more metabolomics studies showed the interest of the use of new chromatographic supports such as hydrophilic interaction chromatography for the analysis of polar compounds. It is in this context that an investigation was conducted on Uptisphere HDO and Luna hydrophilic interaction chromatography stationary phases to generate and process urinary metabolomics fingerprints, which could allow to establish a comparison with Uptisphere Strategy NEC. The chromatographic column the most adapted for the detection of new biomarkers of GH administration has been used to set up a relevant statistical model based on the analysis of more than hundred biological samples.
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