Effect of environmental variance-based resilience selection on the gut metabolome of rabbits

• Published in: Genetics selection evolution (Paris) 2023-03, Vol.55 (1), p.15-8, Article 15
• Main Authors: Casto-Rebollo, Cristina, Argente, María José, García, María Luz, Blasco, Agustín, Ibáñez-Escriche, Noelia
• Format: Article
• Language: English
• Subjects: Acetyllysine; Actors; Actresses; Analysis; Animals; Bayes Theorem; Bayesian analysis; Biomarkers; Chromatography; Composition; Datasets; Discriminant analysis; Divergence; Environmental effects; Gastrointestinal Microbiome; Health aspects; Immune system; Inflammation; Inflammatory response; Intestinal microflora; Ions; Lactic acid; Life Sciences; Litter size; Livestock; Mass spectrometry; Metabolism; Metabolites; Metabolome; Microbiomes; Microbiota; Microbiota (Symbiotic organisms); Microorganisms; Phenylalanine; Physiological aspects; Population studies; Populations; Quality control; Quality standards; Quantitative genetics; Rabbits; Resilience; Scientific imaging; Statistical analysis; Sustainable production; Tryptophan; Tyrosine; Variance
• ISSN: 1297-9686; 0999-193X; 1297-9686
• DOI: 10.1186/s12711-023-00791-5

Gut metabolites are key actors in host-microbiota crosstalk with effect on health. The study of the gut metabolome is an emerging topic in livestock, which can help understand its effect on key traits such as animal resilience and welfare. Animal resilience has now become a major trait of interest because of the high demand for more sustainable production. Composition of the gut microbiome can reveal mechanisms that underlie animal resilience because of its influence on host immunity. Environmental variance (V ), specifically the residual variance, is one measure of resilience. The aim of this study was to identify gut metabolites that underlie differences in the resilience potential of animals originating from a divergent selection for V of litter size (LS). We performed an untargeted gut metabolome analysis in two divergent rabbit populations for low (n = 13) and high (n = 13) V of LS. Partial least square-discriminant analysis was undertaken, and Bayesian statistics were computed to determine dissimilarities in the gut metabolites between these two rabbit populations. We identified 15 metabolites that discriminate rabbits from the divergent populations with a prediction performance of 99.2% and 90.4% for the resilient and non-resilient populations, respectively. These metabolites were suggested to be biomarkers of animal resilience as they were the most reliable. Among these, five that derived from the microbiota metabolism (3-(4-hydroxyphenyl)lactate, 5-aminovalerate, and equol, N6-acetyllysine, and serine), were suggested to be indicators of dissimilarities in the microbiome composition between the rabbit populations. The abundances of acylcarnitines and metabolites derived from the phenylalanine, tyrosine, and tryptophan metabolism were low in the resilient population and these pathways can, therefore impact the inflammatory response and health status of animals. This is the first study to identify gut metabolites that could act as potential resilience biomarkers. The results support differences in resilience between the two studied rabbit populations that were generated by selection for V of LS. Furthermore, selection for V of LS modified the gut metabolome, which could be another factor that modulates animal resilience. Further studies are needed to determine the causal role of these metabolites in health and disease.