Université Clermont Auvergne, INRAE, VetAgro Sup, UMR Herbivores, F-63122 Saint-Genes-Champanelle, France.
Université Clermont Auvergne, GReD, UMR CNRS 6293-Inserm U1103, 63001 Clermont-Ferrand, France.
Int J Mol Sci. 2020 Jan 19;21(2):664. doi: 10.3390/ijms21020664.
Beef quality is a complex phenotype that can be evaluated only after animal slaughtering. Previous research has investigated the potential of genetic markers or muscle-derived proteins to assess beef tenderness. Thus, the use of low-invasive biomarkers in living animals is an issue for the beef sector. We hypothesized that publicly available data may help us discovering candidate plasma biomarkers. Thanks to a review of the literature, we built a corpus of articles on beef tenderness. Following data collection, aggregation, and computational reconstruction of the muscle secretome, the putative plasma proteins were searched by comparison with a bovine plasma proteome atlas and submitted to mining of biological information. Of the 44 publications included in the study, 469 unique gene names were extracted for aggregation. Seventy-one proteins putatively released in the plasma were revealed. Among them 13 proteins were predicted to be secreted in plasma, 44 proteins as hypothetically secreted in plasma, and 14 additional candidate proteins were detected thanks to network analysis. Among these 71 proteins, 24 were included in tenderness quantitative trait loci. The in-silico workflow enabled the discovery of candidate plasma biomarkers for beef tenderness from reconstruction of the secretome, to be examined in the cattle plasma proteome.
牛肉质量是一种复杂的表型，只能在动物屠宰后进行评估。以前的研究已经调查了遗传标记或肌肉衍生蛋白在评估牛肉嫩度方面的潜力。因此，在活体动物中使用低侵入性生物标志物是牛肉行业的一个问题。我们假设公开可用的数据可能有助于我们发现候选血浆生物标志物。通过对文献的回顾，我们构建了一个关于牛肉嫩度的文章数据库。在收集、聚合和计算重建肌肉分泌组后，通过与牛血浆蛋白质组图谱进行比较来搜索假定的血浆蛋白，并提交生物信息挖掘。在纳入研究的 44 篇出版物中，共提取了 469 个独特的基因名称进行聚合。揭示了 71 种推定在血浆中释放的蛋白质。其中 13 种蛋白质被预测为在血浆中分泌，44 种蛋白质被假设为在血浆中分泌，另外 14 种候选蛋白质则通过网络分析检测到。在这 71 种蛋白质中，有 24 种被包含在嫩度数量性状基因座中。通过对分泌组的重建，再到对牛血浆蛋白质组的检验，这种计算机模拟工作流程可以发现用于牛肉嫩度的候选血浆生物标志物。
