Serum metabolomics study of nutrient metabolic variations in chronic heat-stressed broilers

Br J Nutr. 2018 Apr;119(7):771-781. doi: 10.1017/S0007114518000247.

Abstract

To investigate the effects of heat stress on broiler metabolism, we assigned 144 broilers to normal control (NC), heat stress (HS) or pair-fed (PF) groups and then monitored the effects using growth performance, carcass characteristics, biochemical assays and GC-MS-based metabolomics. The up-regulation of cloacal temperature confirmed that our experiment was successful in inducing chronic heat stress. The average daily gain and average daily feed intake of the HS group were significantly lower than those of the NC group, by 28·76 and 18·42 %, respectively (P1 and P<0·05). The greater feed:gain ratio of the HS group was significantly positively correlated with the leg, abdominal fat, subcutaneous fat and intramuscular fat proportions and levels of some free amino acids (proline, l-cysteine, methionine and threonine) but was negatively correlated with breast proportion and levels of some NEFA (stearic acid, arachidonic acid, palmitic acid and oleic acid). These findings indicated that the heat-stressed broilers were in negative energy balance and unable to effectively mobilise fat, thereby resulting in protein decomposition, which subsequently affected growth performance and carcass characteristics.

Keywords: ADFI average daily feed intake; ADG average daily gain; F:G feed:gain ratio; HS heat stress; NC normal control; OPLS-DA orthogonal projections to latent structures discriminant analyses; PF pair-fed; VIP variable importance in the projection; Broilers; Chronic heat stress; GC-MS; Growth performance; Metabolomics.

Publication types

  • Clinical Trial, Veterinary
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animal Feed
  • Animal Nutritional Physiological Phenomena
  • Animals
  • Chickens / blood*
  • Diet / veterinary
  • Heat-Shock Response*
  • Hot Temperature / adverse effects*
  • Male
  • Metabolomics*
  • Nutrients
  • Principal Component Analysis
  • Random Allocation
  • Time Factors

Substances

  • Nutrients