Insights on meat quality from combining traditional studies and proteomics

Abstract

Following a century of major discoveries on the mechanisms determining meat colour and tenderness using traditional scientific methods, further research into complex and interactive factors contributing to variations in meat quality is increasingly being based on data-driven "omics" approaches such as proteomics. Using two recent meta-analyses of proteomics studies on beef colour and tenderness, this review examines how knowledge of the mechanisms and factors underlying variations in these meat qualities can be both confirmed and extended by data-driven approaches. While proteomics seems to overlook some sources of variations in beef toughness, it highlights the role of post-mortem energy metabolism in setting the conditions for development of meat colour and tenderness, and also points to the complex interplay of energy metabolism, calcium regulation and mitochondrial metabolism. In using proteomics as a future tool for explaining variations in meat quality, the need for confirmation by further hypothesis-driven experimental studies of post-hoc explanations of why certain proteins are biomarkers of beef quality in data-driven studies is emphasised.

Keywords: Beef; Colour; Data integration; Glycolysis; Meat quality; Mitochondria; Muscle to meat conversion; Omics; Proteomics; Tenderness.