Université Clermont Auvergne , INRA, VetAgro Sup, UMR Herbivores , F-63122 Saint-Genès-Champanelle , France.
J Agric Food Chem. 2018 Dec 26;66(51):13552-13563. doi: 10.1021/acs.jafc.8b05744. Epub 2018 Dec 14.
This study is based on an integromic approach of 71 young bulls' data from the farmgate-to-meat continuum including omics-based biomarkers, to understand beef tenderness variability in two muscle cuts that differ by their contractile and metabolic properties. By the means of chemometrics using partial least-squares (PLS) and principal component regressions (PCR), important variables from a list of 49 that characterize four levels of the continuum (rearing factors-carcass-muscle-meat) were identified to explain tenderness of Longissimus thoracis (LT) and Semitendinosus (ST) muscles evaluated by a sensory panel and instrumental Warner-Bratzler shear force (WBSF). The PLS and PCR analyses validated 16 and 15 variables for LT and 12 and 14 for ST from the whole continuum to explain sensory tenderness and WBSF, respectively. Among the explanatory variables in the four models and in line with the role of apoptosis in tenderness determinism, HSP70-1A/B (a heat shock protein) was retained to explain beef tenderness irrespective of muscle and evaluation method. Similarly, dressing percentage from the carcass level was another robust predictor but in a muscle-dependent direction manner. HSP20, ENO3, and MyHC-I as three muscle protein biomarkers and dry matter intake (DMI) as a rearing factor were involved in three models to explain beef tenderness. This study highlighted also that several variables were muscle-specific irrespective of the evaluation method of tenderness. For LT muscle, six variables including three carcass traits (fatness score, fat carcass %, and muscle carcass %), two muscle biomarkers (HSP70-8 and MyHC-IIx/b), and one meat quality trait (pH) were found. For ST muscle, five variables were validated from two rearing factors (average daily gain and feed efficiency) and three structural protein biomarkers (α-actin, MyBP-H, and CapZ-β). Finally, for WBSF only, lactate dehydrogenase chain B (LDH-B) was retained positively for LT and negatively for ST muscles. Overall, this trial showed that tenderness of LT and ST muscle cuts is influenced by variables belonging to the whole continuum with relationships that depend on both the muscle type and the evaluation method. It further highlighted the potential of integromic/chemometric approaches on the farmgate-to-meat continuum data to better understand the sophisticated biological processes that orchestrate the conversion of muscle into meat and tenderness determinism.
本研究基于从农场到餐桌连续体中 71 头年轻公牛的数据的整合组学方法,包括基于组学的生物标志物,以了解两种肌肉切块的牛肉嫩度变异性,这两种肌肉切块的收缩和代谢特性不同。通过使用偏最小二乘法(PLS)和主成分回归(PCR)的化学计量学方法,从特征化连续体四个水平(饲养因素-胴体-肌肉-肉)的 49 个变量列表中确定了重要变量,以解释通过感官小组和仪器 Warner-Bratzler 剪切力(WBSF)评估的胸最长肌(LT)和半腱肌(ST)肌肉的嫩度。PLS 和 PCR 分析分别从整个连续体中验证了 16 个和 15 个用于 LT 的变量以及 12 个和 14 个用于 ST 的变量,以分别解释感官嫩度和 WBSF。在四个模型中的解释变量中,与凋亡在嫩度决定中的作用一致,HSP70-1A/B(热休克蛋白)被保留下来,以解释无论肌肉和评估方法如何,牛肉的嫩度。同样,来自胴体水平的屠宰率是另一个稳健的预测因子,但在肌肉依赖的方向上。HSP20、ENO3 和 MyHC-I 作为三种肌肉蛋白生物标志物以及干物质摄入量(DMI)作为饲养因素,参与了三个模型以解释牛肉的嫩度。本研究还强调,有几个变量是肌肉特异性的,而与嫩度评估方法无关。对于 LT 肌肉,发现了包括三个胴体特征(脂肪评分、脂肪胴体%和肌肉胴体%)、两个肌肉生物标志物(HSP70-8 和 MyHC-IIx/b)和一个肉质特性(pH)在内的六个变量。对于 ST 肌肉,从两个饲养因素(平均日增重和饲料效率)和三个结构蛋白生物标志物(α-肌动蛋白、MyBP-H 和 CapZ-β)中验证了五个变量。最后,对于 WBSF,仅保留了乳酸脱氢酶链 B(LDH-B),其对 LT 肌肉呈正相关,对 ST 肌肉呈负相关。总体而言,该试验表明,LT 和 ST 肌肉切块的嫩度受属于整个连续体的变量的影响,这些关系取决于肌肉类型和评估方法。它进一步强调了在农场到餐桌连续体数据上整合组学/化学计量学方法的潜力,以更好地理解协调肌肉转化为肉和嫩度决定的复杂生物学过程。