Deconstructing the pig sex metabolome: Targeted metabolomics in heavy pigs revealed sexual dimorphisms in plasma biomarkers and metabolic pathways1

Abstract

Metabolomics has opened new possibilities to investigate metabolic differences among animals. In this study, we applied a targeted metabolomic approach to deconstruct the pig sex metabolome as defined by castrated males and entire gilts. Plasma from 545 performance-tested Italian Large White pigs (172 castrated males and 373 females) sampled at about 160 kg live weight were analyzed for 186 metabolites using the Biocrates AbsoluteIDQ p180 Kit. After filtering, 132 metabolites (20 AA, 11 biogenic amines, 1 hexose, 13 acylcarnitines, 11 sphingomyelins, 67 phosphatidylcholines, and 9 lysophosphatidylcholines) were retained for further analyses. The multivariate approach of the sparse partial least squares discriminant analysis was applied, together with a specifically designed statistical pipeline, that included a permutation test and a 10 cross-fold validation procedure that produced stability and effect size statistics for each metabolite. Using this approach, we identified 85 biomarkers (with metabolites from all analyzed chemical families) that contributed to the differences between the 2 groups of pigs ( < 0.05 at the stability statistic test). All acylcarnitines and almost all biogenic amines were higher in castrated males than in gilts. Metabolites involved in tryptophan catabolism had the largest differences (i.e., delta = 20% for serotonin) between castrated males (higher) and gilts (lower). The level of several AA (Ala, Arg, Gly, His, Lys, Ser, Thr, and Trp) was higher in gilts (delta was from approximately 1.0 to approximately 4.8%) whereas products of AA catabolism (taurine, 2-aminoadipic acid, and methionine sulfoxide) were higher in castrated males (delta was approximately 5.0-6.0%), suggesting a metabolic shift in castrated males toward energy storage and lipid production. Similar general patterns were observed for most sphingomyelins, phosphatidylcholines, and lysophosphatidylcholines. Metabolomic pathway analysis and pathway enrichment identified several differences between the 2 sexes. This metabolomic overview opened new clues on the biochemical mechanisms underlying sexual dimorphism that, on one hand, might explain differences in terms of economic traits between castrated male pigs and entire gilts and, on the other hand, could strengthen the pig as a model to define metabolic mechanisms related to fat deposition.

Gene co-expression networks in liver and muscle transcriptome reveal sex-specific gene expression in lambs fed with a mix of essential oils

“…Genomic, transcriptomic and metabolic analysis reported sexual dimorphism in metabolic tissues and metabolite concentration profiles [ 59 – 61 ]. Moreover, sex-dependent activation of biological pathways in response to a specific diet has been previously described.…”

“…A sex-specific effect was also observed in our study in the lamb transcriptome. A possible explanation for this effect might be a potential different biotransformation of the essential oils in the two sexes, taking into account that in both cattle and pigs a sex-specific activation of several metabolic pathways has been reported [ 59 , 61 ].…”

Genome‐wide association study for the level of serum electrolytes in Italian Large White pigs

“…Pigs were slaughtered in the morning (7:00–8:00 a.m.), after overnight fasting of about 12 h on 25 different slaughtering dates, following standard procedures of commercial abattoirs (Bovo et al . ). Serum was prepared in serum separator tubes with gel separator and clot activator (Vacutest Kima s.r.l.)…”

A comparative analysis of label-free liquid chromatography-mass spectrometry liver proteomic profiles highlights metabolic differences between pig breeds

“…Differentially abundant proteins were detected by applying the multivariate approach of sparse Partial Least Squares Discriminant Analysis (sPLS-DA) [ 33 ] coupled with the validation procedure detailed in Bovo et al . [ 18 , 34 ]. sPLS-DA is a multivariate technique used in classification and discrimination problems especially when variables are highly correlated [ 35 ].…”