Molecular mechanisms contributing to the development of beef sensory texture and flavour traits and related biomarkers: Insights from early post-mortem muscle using label-free proteomics

Abstract

Beef sensory quality comprises a suite of traits, each of which manifests its ultimate phenotype through interaction of muscle physiology with environment, both in vivo and post-mortem. Understanding variability in meat quality remains a persistent challenge, but omics studies to uncover biological connections between natural variability in proteome and phenotype could provide validation for exploratory studies and offer new insights. Multivariate analysis of proteome and meat quality data from Longissimus thoracis et lumborum muscle samples taken early post-mortem from 34 Limousin-sired bulls was conducted. Using for the first-time label-free shotgun proteomics combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS), 85 proteins were found to be related with tenderness, chewiness, stringiness and flavour sensory traits. The putative biomarkers were classified in five interconnected biological pathways; i) muscle contraction, ii) energy metabolism, iii) heat shock proteins, iv) oxidative stress, v) regulation of cellular processes and binding. Among the proteins, PHKA1 and STBD1 correlated with all four traits, as did the GO biological process 'generation of precursor metabolites and energy'. Optimal regression models explained a high level (58-71%) of phenotypic variability with proteomic data for each quality trait. The results of this study propose several regression equations and biomarkers to explain the variability of multiple beef eating quality traits. Thanks to annotation and network analyses, they further suggest protein interactions and mechanisms underpinning the physiological processes regulating these key quality traits. SIGNIFICANCE: The proteomic profiles of animals with divergent quality profiles have been compared in numerous studies; however, a wide range of phenotypic variation is required to better understand the mechanisms underpinning the complex biological pathways correlated with beef quality and protein interactions. We used multivariate regression analyses and bioinformatics to analyse shotgun proteomics data to decipher the molecular signatures involved in beef texture and flavour variations with a focus on multiple quality traits. We developed multiple regression equations to explain beef texture and flavour. Additionally, potential candidate biomarkers correlated with multiple beef quality traits are suggested, which could have utility as indicators of beef overall sensory quality. This study explained the biological process responsible for determining key quality traits such as tenderness, chewiness, stringiness, and flavour in beef, which will provide support for future beef proteomics studies.

Keywords: Beef eating quality; Biomarkers; Interactome; Regression models; Shotgun proteomics.