Influence of sire fertility on the metabolism of in vitro produced embryos.

Abstract

Abstract: Bull field fertility varies greatly and is largely influenced by differences in early embryo survival rather than fertilization failure alone. We, therefore, investigated whether sire fertility status is reflected in the metabolomic profile of embryo-conditioned culture media. Six Holstein-Friesian bulls were selected from a population of 840 sires and classified using an adjusted sire fertility index. Mean (±SD) values were 4.27 ± 0.61% for highly fertile bulls (HF, n = 3) and -13.1 ± 1.85% for sub-fertile bulls (SF, n = 3). Cumulus-oocyte complexes were fertilized using frozen-thawed semen from individual bulls. On day 7 post-fertilization, grade 1 blastocysts (pools of n = 15 per bull; n = 3 replicates) were transferred to fresh culture medium for 24 h. On day 8, embryo-conditioned media from both fertility treatments and unconditioned media were collected, snap-frozen, and subjected to high-throughput untargeted metabolomic profiling. A total of 149 metabolites were detected. Unsupervised analysis revealed substantial overlap between HF and SF sire-derived embryo-conditioned media, while both differed from unconditioned media. The relative abundance of 30 metabolites was altered by embryo presence, irrespective of sire fertility. Direct comparison of HF vs SF sire-derived embryo-conditioned media identified only three differentially abundant metabolites. However, multivariate machine learning analysis identified a panel of eight N-acetylated amino acids, which discriminated embryos derived using semen from bulls of divergent fertility status with high accuracy (AUROC = 0.903). In conclusion, sire fertility status imparts a subtle but detectable metabolic imprint on the early embryo, which can be exploited to non-invasively discriminate embryos according to potential developmental competence.

Lay summary: Reproductive efficiency is fundamental to productive and profitable cattle farming. Even bulls that pass routine fertility assessments can achieve very different pregnancy rates. Understanding the biological basis of this variation has important practical implications. We studied whether differences in early embryo metabolism might help explain why some bulls consistently outperform others in fertility. We created embryos in the laboratory using sperm from highly fertile and sub-fertile bulls. Then, we analyzed hundreds of small molecules that reflect metabolic activity in the fluid surrounding the embryo, and we detected very few differences between the two groups. However, using a machine learning approach, we identified a panel of eight molecules that distinguished embryos by sire fertility status with high accuracy. These findings suggest that a bull's fertility leaves a subtle but detectable metabolic imprint on early embryos, with potential future applications in non-invasive embryo quality assessment.