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Metabolic and Proteomic Responses to Long-Term Protein Restriction in a Pig Model.

Yuying LiJie YinHui HanGang LiuDun DengSung Woo KimGuoyao WuTiejun LiYulong Yin
Published in: Journal of agricultural and food chemistry (2018)
Protein restriction is associated with extended lifespan and reduced incidence and progression of multiple age-related diseases. The underlying mechanism of metabolic and proteomic responses to the long-term dietary protein restriction, however, has not been fully uncovered. The present study aimed to identify the metabolic and proteomic profiles in a low-protein diet-fed pig model. Intestinal and liver metabolomics showed that amino acid metabolism was highly associated with dietary protein restriction. Interestingly, blood was characterized by markedly higher abundances of Ser, Gly, Glu, Thr, Ala, Lys, and Met levels, and lower abundances of His, Val, and Ile levels regardless of the age of pigs from piglets to adult pigs. Amino acid transporters might contribute to the changed amino acid pools and serve as a feedback regulatory mechanism in response to protein restriction. iTRAQ-based quantitative proteomics approach identified more than 10 differently expressed proteins in protein restricted pigs and KEGG pathway analysis showed that significant enrichment of proteins involved in metabolic pathways, PI3K-Akt signaling pathway, lysosome, spliceosome, oxidative phosphorylation, phagosome, and DNA replication. Western blot analysis further confirmed that protein restriction markedly inactivated Akt and mTOR signals in pigs. This study indicates that dietary protein restriction leads to a shift in the host metabolism in a pig model, especially for amino acid metabolism. Along with proteomics, our findings unveil potential mechanisms for integrating how protein restriction modulates host metabolism.
Keyphrases
  • amino acid
  • signaling pathway
  • protein protein
  • pi k akt
  • binding protein
  • mass spectrometry
  • small molecule
  • young adults
  • tyrosine kinase
  • risk assessment
  • human health
  • data analysis