Beef tenderness and intramuscular fat proteomic biomarkers: Effect of gender and rearing practices.

This study analyzed the effect of gender on the abundances of 20 protein biomarkers of tenderness and/or intramuscular fat content in five muscles: Longissimus thoracis, previously identified as biomarkers of tenderness and/or intramuscular Semimembranosus, Rectus abdominis, Triceps brachii and Semitendinosus, from cows and steers of the Protected Designation Origin Maine Anjou. The protein abundances were quantified using Reverse Phase Protein Array with specific validated antibodies. Among the 20 studied proteins, the abundance of 8 biomarkers involved in energetic metabolism, contraction and cellular stress, was different according to gender. The gender effect was different depending on the muscle type with greater abundances in Semitendinosus, Rectus abdominis and Longissimus thoracis muscles. On the basis of animal characteristics and rearing factors, three rearing practices classes were identified for cows. Among the factors, fattening duration modified the abundance of 12 proteins mainly in Triceps brachii muscle. A positive correlation between the abundance of the small HSP20 and slaughter age was observed in the 5 muscles. Two proteins, Four and a half LIM domains 1 (FHL1) and Glycogen phosphorylase (PYGB) appeared to be muscle, gender and rearing practices independent. These results constitute valuable data to understand how to manage beef quality by controlling these different factors. SIGNIFICANCE: This study is the first to compare the relative abundance of 20 proteins previously identified as biomarkers of tenderness and/or intramuscular fat (IMF) content of beef meat between cows and steers among 5 different muscles. Its originality is in the use of Reverse Phase Protein Array for fast quantification of the proteins and the integration of data from rearing factors, carcass characteristics and biomarkers of meat qualities. The findings provide evidence for modulating biomarker levels by controlling the choice of animal type and rearing factors according to the type of muscle that would produce animals with the desired meat qualities.

Contribution of nutrient fluxes to the evolution of the net energy systems, example of the INRA feeding system for beef cattle.

Energy feeding systems define energy as a whole, but progress made to define metabolizable energy (ME) as the sum of the metabolizable nutrients produced by digestion and available for tissue metabolism in a wide range of nutritional situations opens the way to quantitatively model and predict nutrient fluxes between and within tissues and organs and improve predictions of energy use. This review addresses the contribution of nutrient flux concepts and data to the evolution of the Institut de la Recherche Agronomique (INRA) energy feeding system for growing and fattening cattle and evaluates the outcomes on the net energy (NE) requirements. It summarizes recent progress made to quantitatively predict nutrient fluxes both at digestive and visceral levels. It reviews how nutrient flux concepts and results were introduced in the recently updated INRA feeding system, resulting in improvements in the accuracy of the revised digestible energy (DE) and ME value of diets. The use of an independent database showed that for diets fed to fattening cattle, DE and ME concentrations were downgraded for low-energy-dense diets and upgraded for high-energy-dense diets. We are also showing that compared with its previous version, the updated INRA system improves the quantitative relationship between ME supply and flows of metabolizable nutrients. Evidence is provided on how measured nutrient fluxes at portal level were used to evaluate the predicted flows of metabolizable nutrients. This review then revisits the NE values of diets for fattening cattle as defined by the INRA feeding system and not updated yet. Using an independent database and at similar ME intake, carcass composition was shown to be linearly related to the energy density of diets for fiber-rich diets but not for concentrate-rich diets, suggesting that the efficiency of energy utilization of ME into NE is not linearly related to differences in the composition of the gain. Accounting for the balance of metabolizable nutrients or their proxies in models used to predict carcass composition from ME intake can improve predictions. Overall partitioning aggregated energy fluxes into their subcomponent nutrient fluxes in a more physiological approach offers promising perspectives for the evolution of NE feeding systems.

Beef tenderness and intramuscular fat proteomic biomarkers: muscle type effect.

Tenderness and intramuscular fat content are key attributes for beef sensory qualities. Recently some proteomic analysis revealed several proteins which are considered as good biomarkers of these quality traits. This study focuses on the analysis of 20 of these proteins representative of several biological functions: muscle structure and ultrastructure, muscle energetic metabolism, cellular stress and apoptosis. The relative abundance of the proteins was measured by Reverse Phase Protein Array (RPPA) in five muscles known to have different tenderness and intramuscular lipid contents: Longissimus thoracis (LT), Semimembranosus (SM), Rectus abdominis (RA), Triceps brachii (TB) and Semitendinosus (ST). The main results showed a muscle type effect on 16 among the 20 analyzed proteins. They revealed differences in protein abundance depending on the contractile and metabolic properties of the muscles. The RA muscle was the most different by 11 proteins differentially abundant comparatively to the four other muscles. Among these 11 proteins, six were less abundant namely enolase 3 (ENO3), phosphoglucomutase 1 (PGK1), aldolase (ALDOA), myosin heavy chain IIX (MyHC-IIX), fast myosin light chain 1 (MLC1F), triosephosphate isomerase 1 (TPI1) and five more abundant: Heat shock protein (HSP27, HSP70-1A1, αB-crystallin (CRYAB), troponin T slow (TNNT1), and aldolase dehydrogenase 1 (ALDH1A1). Four proteins: HSP40, four and a half LIM domains protein 1 (FHL1), glycogen phosphorylase B (PYGB) and malate dehydrogenase (MDH1) showed the same abundance whatever the muscle. The correlations observed between the 20 proteins in all the five muscles were used to construct a correlation network. The proteins the most connected with the others were in the following order MyHC-IIX, CRYAB, TPI1, PGK1, ALDH1A1, HSP27 and TNNT1. This knowledge is important for understanding the biological functions related to beef tenderness and intramuscular fat content.