An original methodology for the selection of biomarkers of tenderness in five different muscles

Marie-Pierre Ellies (1) , Hadrien Lorenzo (2) , Christophe Denoyelle (3) , Jérôme Saracco (4) , Brigitte Picard (1)

1 UMRH - Unité Mixte de Recherche sur les Herbivores - UMR 1213
2 Inserm U1219, Population Health Research Center
3 Service Qualite des Carcasses et des Viandes
4 IMB - Institut de Mathématiques de Bordeaux

For several years, studies conducted for discovering tenderness biomarkers have proposed a list of 20 candidates. The aim of the present work was to develop an innovative methodology to select the most predictive among this list. The relative abundance of the proteins was evaluated on five muscles of 10 Holstein cows: gluteobiceps, semimembranosus, semitendinosus, Triceps brachii and Vastus lateralis. To select the most predictive biomarkers, a multi-block model was used: The Data-Driven Sparse Partial Least Square. Semimembranosus and Vastus lateralis muscles tenderness could be well predicted (R2 = 0.95 and 0.94 respectively) with a total of 7 out of the 5 times 20 biomarkers analyzed. An original result is that the predictive proteins were the same for these two muscles: µ-calpain, m-calpain, h2afx and Hsp40 measured in m. gluteobiceps and µ-calpain, m-calpain and Hsp70-8 measured in m. Triceps brachii. Thus, this method is well adapted to this set of data, making it possible to propose robust candidate biomarkers of tenderness that need to be validated on a larger population.

Mots clés: h2afx; calpain; biomarker; predictive model; tenderness; meat

Mots clés: modèle prédictif; biomarqueur; viande; muscle; tendrete de la viande; calpaine

Domaines: Sciences du Vivant [q-bio]; Alimentation et Nutrition; Statistiques [stat]

Marie-Pierre Ellies, Hadrien Lorenzo, Christophe Denoyelle, Jérôme Saracco, Brigitte Picard. An original methodology for the selection of biomarkers of tenderness in five different muscles. Foods, 2019, 8 (6), pp.206. ⟨10.3390/foods8060206⟩. ⟨hal-02164157⟩