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Uterine fluid proteomic and metabolomic profiles associated with soft-shelled egg formation in laying hens

Sep 2026 · Frontiers in Veterinary Science · Vol 13 · 0 citations · 44 references
Medicine

Abstract

Introduction Soft-shelled eggs are a major eggshell defect in poultry production, yet the underlying mechanisms of their formation remain unclear. The objective of this study was to characterize biological changes associated with soft-shelled egg formation in laying hens by integrating quantitative proteomics and untargeted metabolomics analyses of uterine fluid (UF), combined with morphological and physiological assessments. Methods Normal-shelled egg-producing hens (NE) and soft-shelled or shell-less egg-producing hens (SE) were selected from Langshan laying hens maintained under the same feeding and management conditions. Egg quality traits, serum biochemical indicators, duodenal and uterine morphology, TMT-based proteomics, and LC–MS-based untargeted metabolomics of UF were analyzed. Results Compared with the NE group, the SE group exhibited significantly reduced eggshell thickness and disrupted eggshell ultrastructure (p < 0.05). No significant differences were detected in the measured serum calcium-related indicators or duodenal morphology between the two groups (p > 0.05). In contrast, the NE group showed significantly greater endometrial villus length, uterine mucosal fold height, and mucosal fold area than the SE group (p < 0.05). Proteomic and metabolomic analyses revealed changes in UF protein and metabolite profiles, and the differential proteins and metabolites were mainly enriched in pathways related to amino acid metabolism and mitochondrial energy metabolism, including aminoacyl-tRNA biosynthesis and L-cysteine-related metabolism. Conclusion Soft-shelled egg formation in laying hens was associated with compromised uterine morphology and changes in the UF metabolic microenvironment. These findings provide insight into uterine fluid protein and metabolite profiles related to eggshell defects and identify candidate pathways for future validation.

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