Integrating identification and targeted proteomics to discover the potential indicators of postmortem lamb meat quality

Abstract

The aim of this study was to identify the potential indicators of lamb meat quality by TMT and PRM-based proteomics combined with bioinformatic analysis. Lamb muscles were divided into three different meat quality groups (high, middle and low) according to tenderness (shear force, MFI value), colour (a* value, R630/580), and water-holding capacity (cooking loss, drip loss) at 24 h postmortem. The results showed that the abundance of phosphoglycerate kinase 1 (PGK1), β-enolase (ENO3), myosin-binding protein C (MYBPC1) and myosin regulatory light chain 2 (MYLPF) was significantly different in the three groups and could be used as potential indicators to characterize meat quality. Moreover, the postmortem processes of glycolysis, oxidative phosphorylation, and muscle contraction remarkably changed in different groups, and were the key biological pathways influencing meat quality. Overall, this study depicted the proteomic landscape of meat that furthers our understanding of the molecular mechanism of meat quality and provides a reference for developing non-destructive detection technology for meat quality.