Urine metabolomics of heat-stressed dairy goats supplemented with soybean oil

Abstract Text:

Biofluids assessment by ¹H Nuclear Magnetic Resonance (NMR) Spectroscopy would highlight the physiological mechanisms which may have occurred in goats when exposed to different management and environmental conditions. Our objective was to detect metabolomic changes in the urine of heat-stressed goats supplemented with soybean oil (SBO) for alleviating fat depression. Murciano-Granadina dairy goats (n = 8; 42.8 ± 1.3 kg BW) kept in metabolic cages were used in a replicated 4 × 4 Latin square design with 4 periods; 19 d each (14 d adaptation, 5 d for measurements). Goats were allocated to one of 4 treatments in a 2 × 2 factorial arrangement. Factors were no oil (C) or 4% SBO, and thermal neutral (TN; 15 to 20°C) or heat stress (HS; 12 h/d at 37°C and 12 h/d at 30°C) conditions, resulting in 4 treatments: TN-C, TN-SBO, HS-C, and HS-SBO. Urine samples were collected and analyzed with ¹H NMR spectroscopy for a qualitative metabolomic study. Principal component analysis (PCA) and partial least square–discriminant analysis (PLS-DA) were used to detect possible outliers and to identify possible metabolite markers of HS and SBO. The PLS-DA revealed that there were 2 separated clusters corresponding to TN (TN-C + TN-SBO) and HS (HS-C + HS-SBO) groups. Metabolites increased (P < 0.01) by HS were: hippurate, isoleucine, acetate, glutamate, glycine, and 3-hydroxybutyrate. On the other hand, L-phenylalanine and creatinine decreased (P< 0.01) by HS.  Changes in those metabolites could be related to physiological responses to HS, including increased harmful gut microbiota activity (hippurate), increased catecholamine activity (conversion of L-phenylalanine to catecholamines), neurotransmitter inhibition (glycine), and decreased degradation of energy-related metabolites (acetate, isoleucine and glutamate). No significant regression model was found for the effects of SBO supplementation. We conclude that urine metabolomics could help in understanding the responses to heat stress and establishment of new alleviation strategies.

Keywords: heat stress, metabolomics, multivariate analysis