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DOI 10.3390/ani14132000

Медицинская библиотека · Animals : an open access journal from MDPI · 2024

Proteomic Identification and Quantification of Basal Endogenous Proteins in the Ileal Digesta of Growing Pigs.

Ávila-Arres Iris Elisa, Rodríguez Hernández Elba, Gómez Rosales Sergio, Reis de Souza Tércia Cesária, Mariscal-Landín Gerardo

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Аннотация

The accurate estimation of basal endogenous losses (BEL) of amino acids at the ileum is indispensable to improve nutrient utilization efficiency. This study used a quantitative proteomic approach to identify variations in BEL in the ileal digesta of growing pigs fed a nitrogen-free diet (NFD) or a casein diet (CAS). Eight barrow pigs (39.8 ± 6.3 kg initial body weight (BW)) were randomly assigned to a 2 × 2 crossover design. A total of 348 proteins were identified and quantified in both treatments, of which 101 showed a significant differential abundance between the treatments (p < 0.05). Functional and pathway enrichment analyses revealed that the endogenous proteins were associated with intestinal metabolic function. Furthermore, differentially abundant proteins (DAPs) in the digesta of pigs fed the NFD enriched terms and pathways that suggest intestinal inflammation, the activation of innate antimicrobial host defense, an increase in cellular autophagy and epithelial turnover, and reduced synthesis of pancreatic and intestinal secretions. These findings suggest that casein diets may provide a more accurate estimation of BEL because they promote normal gastrointestinal secretions. Overall, proteomic and bioinformatic analyses provided valuable insights into the composition of endogenous proteins in the ileal digesta and their relationship with the functions, processes, and pathways modified by diet composition.

Для цитирования: Ávila-Arres Iris Elisa, Rodríguez Hernández Elba, Gómez Rosales Sergio, Reis de Souza Tércia Cesária, Mariscal-Landín Gerardo. Proteomic Identification and Quantification of Basal Endogenous Proteins in the Ileal Digesta of Growing Pigs.. Animals : an open access journal from MDPI. 2024. DOI: 10.3390/ani14132000.
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