Protein Array-Based Approach to Evaluate Biomarkers of Beef Tenderness and Marbling in Cows: Understanding of the Underlying Mechanisms and Prediction

Abstract

This study evaluated the potential of a panel of 20 protein biomarkers, quantified by Reverse Phase Protein Array (RPPA), to explain and predict two important meat quality traits, these being beef tenderness assessed by Warner–Bratzler shear force (WBSF) and the intramuscular fat (IMF) content (also termed marbling), in a large database of 188 Protected Designation of Origin (PDO) Maine-Anjou cows. Thus, the main objective was to move forward in the progression of biomarker-discovery for beef qualities by evaluating, at the same time for the two quality traits, a list of candidate proteins so far identified by proteomics and belonging to five interconnected biological pathways: (i) energy metabolic enzymes, (ii) heat shock proteins (HSPs), (iii) oxidative stress, (iv) structural proteins and (v) cell death and protein binding. Therefore, three statistical approaches were applied, these being Pearson correlations, unsupervised learning for the clustering of WBSF and IMF into quality classes, and Partial Least Squares regressions (PLS-R) to relate the phenotypes with the 20 biomarkers. Irrespective of the statistical method and quality trait, seven biomarkers were related with both WBSF and IMF, including three small HSPs (CRYAB, HSP20 and HSP27), two metabolic enzymes from the oxidative pathway (MDH1: Malate dehydrogenase and ALDH1A1: Retinal dehydrogenase 1), the structural protein MYH1 (Myosin heavy chain-IIx) and the multifunctional protein FHL1 (four and a half LIM domains 1). Further, three more proteins were retained for tenderness whatever the statistical method, among which two were structural proteins (MYL1: Myosin light chain 1/3 and TNNT1: Troponin T, slow skeletal muscle) and one was glycolytic enzyme (ENO3: β-enolase 3). For IMF, two proteins were, in this trial, specific for marbling whatever the statistical method: TRIM72 (Tripartite motif protein 72, negative) and PRDX6 (Peroxiredoxin 6, positive). From the 20 proteins, this trial allowed us to qualify 10 and 9 proteins respectively as strongly related with beef tenderness and marbling in PDO Maine-Anjou cows.

A Proteomic Study for the Discovery of Beef Tenderness Biomarkers and Prediction of Warner–Bratzler Shear Force Measured on Longissimus thoracis Muscles of Young Limousin-Sired Bulls

“…A positive relationship between HSPD1 and tenderness might be hypothesised by its function in the energy metabolism pathway to maintain energy supply during proteolysis of myofibril proteins ( Figure 3 ). As with HSPB1, HSPD1 was also associated with beef colour, which deepened our knowledge of the influential role of HSP proteins in post-mortem muscle events and consequences on meat quality [ 14 ].…”

“…Default settings were used, i.e., medium confidence of 0.4 and 4 criteria for linkage: co-occurrence, experimental evidence, existing databases, and text mining. As the bovine Gene Ontology (GO) had limits, orthologous human Uniprot IDs, following the procedure by Gagaoua et al [ 14 ], were used for this analysis to take advantage of the most complete annotations available.…”

“…There have been a number of studies using omics tools to, firstly, enhance our understanding of the pathways and processes contributing to beef tenderness variation [ 12 , 13 ] and secondly, to propose prediction equations to explain the observed variability in this important quality trait [ 14 ]. Thus, omics-related analytical technologies and bioinformatics tools have been applied in recent decades, resulting in a deeper understanding of gene expression, physiological responses, and other metabolic processes that are involved in meat quality determination, especially tenderness [ 2 , 12 , 15 ].…”

“…Among the many foodomics approaches, proteomics played an important role in the discovery of candidate biomarkers of several meat quality attributes [ 2 , 13 , 17 ]. A pipeline to search for proteomic biomarkers of beef tenderness was proposed [ 12 , 14 ]. Compared with traditional evaluation methods for beef tenderness using instrumental or sensory methods, an optimised protocol for quality monitoring using rapid methods to record the abundance of specific proteins of interest would offer an advantage to predict the meat quality before consumption.…”

Comparison of Meat Quality Characteristics and Proteolysis Trends associated with Muscle Fiber Type Distribution between Duck Pectoralis Major and Iliotibialis Muscles

“…Recently, new insights into tenderness and meat color changes through proteomics and the importance of proteomics research in postmortem metabolic activities have been proposed (Purslow et al, 2021). Previous studies have demonstrated the proteome change and its relationship with beef or pork quality change postmortem (Gagaoua et al, 2020;Gagaoua et al, 2021;Jia et al, 2006;Lametsch & Bendixen, 2001;Lametsch et al, 2003).…”