Investigating biomarkers, biochemical changes and metabolomic features associated with high ph lamb meat

Abstract

The quality of red meat is impacted by several livestock factors, including age, sex, feed type, nutrition, and exposure stressors. The primary predictive measure for meat processors is the pH at 24 hours post-mortem (ultimate pH). When the pH is high, the meat has not undergone the proper muscle-to-meat conversion and associated with undesirable meat quality traits. Lincoln University has developed a reproducible in vivo sheep model where moderate pre-slaughter farmyard stress, exercise in the presence of dogs, is associated with high meat pH This model has been used to investigate potential meat quality biomarkers (Lee et al., 2023). Li et al. (2018) identified four glycolytic enzymes which have shown potential as biomarkers for lamb meat with high pH. We investigated these enzymes using the exercise stress sheep model. Changes in the amount of these enzymes were measured in four different muscles, Longissimus lumborum (LL), Gracilis (G), Semimembranosus (SM), Supraspinatus (SS), using western blotting. Glyceraldehyde 3-phopshate dehydrogenase (GAPDH) was used as the reference protein and the blots analysed using Bio-Rad software (Image Lab 6.1®). Statistical differences were determined using 2-sample t-tests (Mintab21®). Pyruvate kinase (PKM2) was significantly lower in meat from animals subjected to exercise stress compared to control animals in the LL, SM, and SS muscle types but the differences were not significant in G. Phosphoglycerate kinase 1 (PGK1) was significantly greater following exercise stress in the SM muscle, while there were no differences under exercise in the other muscle types (LL, G, SS) The remaining enzymes, Phosphoglucomutase 1 (PGM1), and Beta enolase (ENO3), are currently under investigation. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) is a form of ambient ionisation mass spectrometry, resulting in a detailed mass spectral fingerprint of a sample aerosol, largely based on metabolites and lipids. REIMS been recently applied to many areas of meat science, including meat quality and origin. REIMS data from two trials using the exercise stress model is currently under investigation, with the aim to provide a machine learning model (using TensorFlow) which will offer a rapid assessment tool predicting meat quality for the meat industry. Current results suggest that there are alternative biomarkers to meat pH for predicting meat quality, although these may need to be tailored for individual muscles. Further work in this area will aid in efforts to improve speed and frequency of meat quality monitoring withing meat processing plants.