Sexual Dimorphism of Metabolite Profiles in Pigs Depends on the Genetic Background

Metabolites

卷:11

Björn Egert¹  ChristophH. Weinert¹  Manuela Peukert²  Sebastian Zimmermann²  DagmarA. Brüggemann²  Thomas Schwarzmann³ 

[1] Department of Quality and Safety of Fruit and Vegetables, Max Rubner-Institut, 76131 Karlsruhe, Germany;

[2] Department of Safety and Quality of Meat, Max Rubner-Institut, 95326 Kulmbach, Germany;

[3] Staatsgut Schwarzenau, Leistungsprüfungsanstalt für Schweinezucht Schwarzenau (LPA), 97359 Schwarzenau, Germany;

关键词: GC × GC qMS;    blood;    muscle;    liver;    pigs;    meat quality;   

DOI  :  10.3390/metabo11050261

来源: DOAJ

【 摘 要 】

The study aimed to investigate possible systematic effects in the basic underlying variability of individual metabolomic data. In this context, the extent of gender- and genotype-dependent differences reflected in the metabolic composition of three tissues in fattening pigs was determined. The 40 pigs belonged to the genotypes PIx(LWxGL) and PIxGL with gilts and boars, respectively. Blood and tissue samples from M. longissimus dorsi and liver were directly taken at the slaughtering plant and directed to GC × GC qMS metabolite analysis. Differences were observed for various metabolite classes like amino acids, fatty acids, sugars, or organic acids. Gender-specific differences were much more pronounced than genotype-related differences, which could be due to the close genetic relation of the fattening pigs. However, the metabolic dimorphism between gilts and boars was found to be genotype-dependent, and vice versa metabolic differences between genotypes were found to be gender-dependent. Most interestingly, integration into metabolic pathways revealed different patterns for carbon (C) and nitrogen (N) usage in boars and gilts. We suppose a stronger N-recycling and increased energy metabolism in boars, whereas, in gilts, more N is presumably excreted and remaining carbon skeletons channeled into lipogenesis. Associations of metabolites to meat quality factors confirmed the applicability of metabolomics approaches for a better understanding about the impact of drivers (e.g., gender, age, breed) on physiological processes influencing meat quality. Due to the huge complexity of the drivers-traits-network, the derivation of independent biomarkers for meat quality prediction will hardly be possible.

【 授权许可】

Unknown