Sequential window acquisition of all theoretical mass spectra (SWATH-MS) as an emerging proteomics approach for the discovery of dark-cutting beef biomarkers

IF 7.1 1区 农林科学 Q1 Agricultural and Biological Sciences Meat Science Pub Date : 2024-07-31 DOI:10.1016/j.meatsci.2024.109618
Laura González-Blanco , Mamen Oliván , Yolanda Diñeiro , Susana B. Bravo , Verónica Sierra , Mohammed Gagaoua
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Abstract

Recent advances in “omics” technologies have enabled the identification of new beef quality biomarkers and have also allowed for the early detection of quality defects such as dark-cutting beef, also known as DFD (dark, firm, and dry) beef. However, most of the studies conducted were carried out on a small number of animals and mostly applied gel-based proteomics. The present study proposes for the first time a Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) proteomics approach to characterize and comprehensively quantify the post-mortem muscle proteome of DFD (pH24 ≥ 6.2) and CONTROL (5.4 ≤ pH24 ≤ 5.6) beef samples within the largest database of DFD/CONTROL beef samples to date (26 pairs of the Longissimus thoracis muscle samples of young bulls from Asturiana de los Valles breed, n = 52). The pairwise comparison yielded 35 proteins that significantly differed in their abundances between the DFD and CONTROL samples. Chemometrics methods using both PLS-DA and OPLS-DA revealed 31 and 36 proteins with VIP > 2.0, respectively. The combination of different statistical methods these being Volcano plot, PLS-DA and OPLS-DA allowed us to propose 16 proteins as good candidate biomarkers of DFD beef. These proteins are associated with interconnected biochemical pathways related to energy metabolism (DHRS7B and CYB5R3), binding and signaling (RABGGTA, MIA3, BPIFA2B, CAP2, APOBEC2, UBE2V1, KIR2DL1), muscle contraction, structure and associated proteins (DMD, PFN2), proteolysis, hydrolases, and activity regulation (AGT, C4A, GLB1, CAND2), and calcium homeostasis (ANXA6). These results evidenced the potential of SWATH-MS and chemometrics to accurately identify novel biomarkers for meat quality defects, providing a deeper understanding of the molecular mechanisms underlying dark-cutting beef condition.

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所有理论质谱的顺序窗口采集(SWATH-MS)是发现暗割牛肉生物标记物的一种新兴蛋白质组学方法
近来,"omics "技术的进步使人们能够识别新的牛肉质量生物标志物,并能及早发现质量缺陷,如黑切牛肉,也称为 DFD(深色、坚硬和干燥)牛肉。然而,大多数研究都是在少数动物身上进行的,而且大多采用凝胶蛋白质组学。本研究首次在迄今为止最大的 DFD/CONTROL 牛肉样本数据库(26 对来自 Asturiana de los Valles 品种的年轻公牛样本,= 52)中提出了一种顺序窗口获取所有理论质谱(SWATH-MS)的蛋白质组学方法,用于表征和全面量化 DFD(pH ≥ 6.2)和 CONTROL(5.4 ≤ pH ≤ 5.6)牛肉样本的肌肉蛋白质组。通过成对比较,发现有 35 种蛋白质在 DFD 和 CONTROL 样品之间的丰度存在显著差异。使用 PLS-DA 和 OPLS-DA 的化学计量学方法发现,分别有 31 和 36 个蛋白质的 VIP 值大于 2.0。结合火山图、PLS-DA 和 OPLS-DA 等不同的统计方法,我们提出了 16 种蛋白质作为 DFD 牛肉的候选生物标记物。这些蛋白质与能量代谢(DHRS7B 和 CYB5R3)、结合和信号转导(RABGGTA、MIA3、BPIFA2B、CAP2、APOBEC2、UBE2V1、KIR2DL1)、肌肉收缩、结构和相关蛋白(DMD、PFN2)、蛋白水解、水解酶和活性调节(AGT、C4A、GLB1、CAND2)以及钙稳态(ANXA6)。这些结果证明了 SWATH-MS 和化学计量学在准确鉴定肉质缺陷的新型生物标记物方面的潜力,从而加深了对黑切牛肉状况的分子机制的理解。
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来源期刊
Meat Science
Meat Science 工程技术-食品科技
CiteScore
12.60
自引率
9.90%
发文量
282
审稿时长
60 days
期刊介绍: The aim of Meat Science is to serve as a suitable platform for the dissemination of interdisciplinary and international knowledge on all factors influencing the properties of meat. While the journal primarily focuses on the flesh of mammals, contributions related to poultry will be considered if they enhance the overall understanding of the relationship between muscle nature and meat quality post mortem. Additionally, papers on large birds (e.g., emus, ostriches) as well as wild-captured mammals and crocodiles will be welcomed.
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