Rocchetti Gabriele, Ghilardelli Francesca, Masoero Francesco, Gallo Antonio
Department of Animal Science, Food and Nutrition, Faculty of Agricultural, Food and Environmental Sciences, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy.
Department for Sustainable Food Process, Faculty of Agricultural, Food and Environmental Sciences, Università Cattolica del Sacro Cuore, 29122 Piacenza, Italy.
Foods. 2021 Aug 28;10(9):2025. doi: 10.3390/foods10092025.
In this work, a retrospective screening based on ultra-high-performance liquid chromatography (UHPLC) coupled with high-resolution mass spectrometry (HRMS) based on Orbitrap-Q-Exactive Focus™ was used to check the occurrence of regulated and emerging mycotoxins in bulk milk samples. Milk samples were collected from dairy farms in which corn silage was the main ingredient of the feeding system. The 45 bulk milk samples were previously analyzed for a detailed untargeted metabolomic profiling and classified into five clusters according to the corn silage contamination profile, namely: (1) low levels of - and -mycotoxins; (2) low levels of fumonisins and other -mycotoxins; (3) high levels of -mycotoxins; (4) high levels of non-regulated -mycotoxins; (5) high levels of fumonisins and their metabolites. Multivariate statistics based on both unsupervised and supervised analyses were used to evaluate the significant fold-change variations of the main groups of mycotoxins detected when comparing milk samples from clusters 3, 4, and 5 (high contamination levels of the corn silages) with cluster 1 and 2 (low contamination levels of the corn silages). Overall, 14 compounds showed a significant prediction ability, with antibiotic Y (VIP score = 2.579), bikaverin (VIP score = 1.975) and fumonisin B2 (VIP score = 1.846) being the best markers. The k-means clustering combined with supervised statistics showed two discriminant groups of milk samples, thus revealing a hierarchically higher impact of the whole feeding system (rather than the only corn silages) together with other factors of variability on the final mycotoxin contamination profile. Among the discriminant metabolites we found some mycotoxins, together with the tetrapeptide tentoxin (an toxin), the α-zearalenol (a catabolite of zearalenone), mycophenolic acid and apicidin. These preliminary findings provide new insights into the potential role of UHPLC-HRMS to evaluate the contamination profile and the safety of raw milk to produce hard cheese.
在本研究中，基于超高效液相色谱（UHPLC）与基于Orbitrap-Q-Exactive Focus™的高分辨率质谱（HRMS）联用的方法进行回顾性筛查，以检测散装牛奶样品中受监管和新出现的霉菌毒素的存在情况。牛奶样品采自以玉米青贮饲料为主要饲喂体系成分的奶牛场。之前对45份散装牛奶样品进行了详细的非靶向代谢组学分析，并根据玉米青贮饲料污染情况分为五个类别，即：（1）低水平的α-和β-霉菌毒素；（2）低水平的伏马菌素和其他β-霉菌毒素；（3）高水平的α-霉菌毒素；（4）高水平的非受监管的β-霉菌毒素；（5）高水平的伏马菌素及其代谢产物。基于无监督和有监督分析的多变量统计方法用于评估在比较第3、4和5组（玉米青贮饲料高污染水平）与第1和2组（玉米青贮饲料低污染水平）的牛奶样品时，所检测到的主要霉菌毒素组的显著倍数变化差异。总体而言，14种化合物显示出显著的预测能力，其中抗生素Y（VIP分数=2.579）、比卡维林（VIP分数=1.975）和伏马菌素B2（VIP分数=1.846）是最佳标志物。k均值聚类结合有监督统计显示出两组具有判别力的牛奶样品，从而揭示了整个饲喂体系（而非仅玉米青贮饲料）以及其他可变因素对最终霉菌毒素污染情况具有更高层次的影响。在具有判别力的代谢产物中，我们发现了一些β-霉菌毒素，以及四肽展青霉素（一种α-毒素）、α-玉米赤霉醇（玉米赤霉烯酮的一种分解代谢产物）、霉酚酸和阿皮西丁。这些初步研究结果为UHPLC-HRMS在评估生牛奶污染情况及用于生产硬质奶酪的安全性方面的潜在作用提供了新的见解。
