Comparative Proteomic Analysis of Glycolytic and Oxidative Muscle in Pigs

Genes (Basel). 2023 Jan 30;14(2):361. doi: 10.3390/genes14020361.

Abstract

The quality of meat is highly correlated with muscle fiber type. However, the mechanisms via which proteins regulate muscle fiber types in pigs are not entirely understood. In the current study, we have performed proteomic profiling of fast/glycolytic biceps femoris (BF) and slow/oxidative soleus (SOL) muscles and identified several candidate differential proteins among these. We performed proteomic analyses based on tandem mass tags (TMTs) and identified a total of 26,228 peptides corresponding to 2667 proteins among the BF and SOL muscle samples. Among these, we found 204 differentially expressed proteins (DEPs) between BF and SOL muscle, with 56 up-regulated and 148 down-regulated DEPs in SOL muscle samples. KEGG and GO enrichment analyses of the DEPs revealed that the DEPs are involved in some GO terms (e.g., actin cytoskeleton, myosin complex, and cytoskeletal parts) and signaling pathways (PI3K-Akt and NF-kappa B signaling pathways) that influence muscle fiber type. A regulatory network of protein-protein interaction (PPI) between these DEPs that regulates muscle fiber types was constructed, which demonstrates how three down-regulated DEPs, including PFKM, GAPDH, and PKM, interact with other proteins to potentially control the glycolytic process. This study offers a new understanding of the molecular mechanisms in glycolytic and oxidative muscles as well as a novel approach for enhancing meat quality by transforming the type of muscle fibers in pigs.

Keywords: differentially expressed proteins; glycolytic muscle; meat quality; oxidative muscle; pig.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Muscle Fibers, Skeletal / metabolism
  • Muscle, Skeletal / metabolism
  • Oxidative Stress
  • Phosphatidylinositol 3-Kinases* / metabolism
  • Proteomics*
  • Swine

Substances

  • Phosphatidylinositol 3-Kinases

Grants and funding

This work was funded by the National Natural Science Foundation of China (No. 32002147), the Educational Department of Liaoning Province (No. LJKZ0671), the Natural Science Foundation of Liaoning Province (No. 2021-BS-140), the China Postdoctoral Science Foundation (No. 2021MD703855), and the Science and Technology Plan Project of Shenyang City (No. 21-116-3-40 and 21-110-3-10).