Abstract #93
Section: Production, Management and the Environment
Session: Production, Management & the Environment I
Format: Oral
Day/Time: Monday 10:00 AM–10:15 AM
Location: 324
Session: Production, Management & the Environment I
Format: Oral
Day/Time: Monday 10:00 AM–10:15 AM
Location: 324
# 93
1H Nuclear magnetic resonance-based metabolomics of urine in heat-stressed dairy goats.
A. Contreras-Jodar*1, N. Nayan1,2, A. A. K. Salama1, S. Hamzaoui1,3, G. Caja1, 1University Autonoma of Barcelona, Bellaterra, Barcelona, Spain, 2Wageningen University, Wageningen, the Netherlands, 3University of Bouira, Bouira, Algeria.
Key Words: heat stress, urine metabolomics, dairy goats
1H Nuclear magnetic resonance-based metabolomics of urine in heat-stressed dairy goats.
A. Contreras-Jodar*1, N. Nayan1,2, A. A. K. Salama1, S. Hamzaoui1,3, G. Caja1, 1University Autonoma of Barcelona, Bellaterra, Barcelona, Spain, 2Wageningen University, Wageningen, the Netherlands, 3University of Bouira, Bouira, Algeria.
With the aim of completing a previous study on whole blood transcriptomics of heat stressed dairy goats (Contreras-Jodar et al., 2016; EAAP Annual Meeting, Belfast, UK, p. 126), urine biomarkers were investigated by 1H nuclear magnetic resonance (1H-NMR) spectroscopy in the same goats. Eight adult Murciano-Granadina dairy does in mid-lactation (42.8 ± 1.3 kg BW, 1.73 ± 0.15 L/d) were placed in metabolic cages and milked once-a-day. Does were fed a TMR and exposed to 2 climatic treatments according to a crossover design with periods of 19 d. Treatments and temperature-humidity index (THI; NRC, 1971) were: 1) thermal neutral (TN: 15 to 20°C, 40 to 45% HR; THI = 59 to 65), and 2) heat stress (HS: 37°C-40% HR day; 30°C-40% HR night; THI = 86 and 77, respectively). Day-night was 12–12 h. Urine samples were collected at d 19 and analyzed by 1H-NMR spectroscopy (Bruker Avance-III; 600.13 MHz and 298°K). Multivariate data analyses included PCA (principal component analysis) and PLS-DA (partial least square–discriminant analysis) assessment with cross validation to identify HS biomarkers. The metabolites were assigned using the Human Metabolome Data Base (www.hmdb.ca). PLS-DA revealed 2 separated clusters corresponding to TN and HS goats (R2 = 0.45; Q2 = 0.43). Metabolites that most discriminate between TN and HS were phenylalanine metabolic derivative compounds, such as hydroxyphenylacetate (7.27 ppm), hydroxyphenylacetylglycine (7.20 ppm) and phenylglyoxylic acid (7.62 ppm), which were increased in HS does (P < 0.001). A greater excretion of these compounds in urine together with the previously observed most downregulated gene in blood cells, HGD (homogentisate 1,2-dioxygenase; FC = −3.66), suggest that HS decreased the capability of goats to synthesize tyrosine from its precursor phenylalanine. Consequently, HS impaired milk production may be a consequence of the reduced synthesis of catecholamines (i.e., L-DOPA, epinephrine, norepinephrine) and thyroid hormones. In conclusion, heat stress caused significant changes in the urine metabolomic profile of dairy goats. These changes may be related to the synthesis of neurotransmitters and to the hormonal regulation of nutrient metabolism.
Key Words: heat stress, urine metabolomics, dairy goats