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A Combined Metabolomic and Metagenomic Approach to Discriminate Raw Milk for the Production of Hard Cheese

机译:一种组合的代谢组和偏见方法以辨别奶酪生产的原料牛奶

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摘要

The chemical composition of milk can be significantly affected by different factors across the dairy supply chain, including primary production practices. Among the latter, the feeding system could drive the nutritional value and technological properties of milk and dairy products. Therefore, in this work, a combined foodomics approach based on both untargeted metabolomics and metagenomics was used to shed light onto the impact of feeding systems (i.e., hay vs. a mixed ration based on hay and fresh forage) on the chemical profile of raw milk for the production of hard cheese. In particular, ultra-high-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) was used to investigate the chemical profile of raw milk (n = 46) collected from dairy herds located in the Po River Valley (Italy) and considering different feeding systems. Overall, a total of 3320 molecular features were putatively annotated across samples, corresponding to 734 unique compound structures, with significant differences (p < 0.05) between the two feeding regimens under investigation. Additionally, supervised multivariate statistics following metabolomics-based analysis allowed us to clearly discriminate raw milk samples according to the feeding systems, also extrapolating the most discriminant metabolites. Interestingly, 10 compounds were able to strongly explain the differences as imposed by the addition of forage in the cows’ diet, being mainly glycerophospholipids (i.e., lysophosphatidylethanolamines, lysophosphatidylcholines, and phosphatidylcholines), followed by 5-(3′,4′-Dihydroxyphenyl)-gamma-valerolactone-4′-O-glucuronide, 5a-androstan-3a,17b-diol disulfuric acid, and N-stearoyl glycine. The markers identified included both feed-derived (such as phenolic metabolites) and animal-derived compounds (such as lipids and derivatives). Finally, although characterized by a lower prediction ability, the metagenomic profile was found to be significantly correlated to some milk metabolites, with Staphylococcaceae, Pseudomonadaceae, and Dermabacteraceae establishing a higher number of significant correlations with the discriminant metabolites. Therefore, taken together, our preliminary results provide a comprehensive foodomic picture of raw milk samples from different feeding regimens, thus supporting further ad hoc studies investigating the metabolomic and metagenomic changes of milk in all processing conditions.
机译:牛奶的化学成分可能受到乳制品供应链中不同因素的显着影响,包括主要生产实践。在后者中,饲养系统可以推动牛奶和乳制品的营养价值和技术特性。因此,在这项工作中,基于未确定的代谢组和偏心组学的组合的食谱方法用于缩小喂养系统的影响(即干草基于干草的混合饲料和新鲜饲料的混合饲料)对原料的化学曲线的影响牛奶生产硬奶酪。特别地,超高效液相色谱四极血压飞行时间质谱(UHPLC-QTOF)用于研究从位于PO River Valley(意大利)收集的原料牛奶(n = 46)的化学曲线(N = 46)(意大利)和考虑不同的喂养系统。总体而言,在样品中,总共3320个分子特征,对应于734个独特的复合结构,两种饲养方案在调查中具有显着差异(P <0.05)。另外,基于代谢组的分析后,监督多元统计数据允许我们根据饲养系统清楚地鉴别原料牛奶样品,还推断出最判别最判别的代谢物。有趣的是,10种化合物能够强烈地解释在奶牛饮食中添加饲料中饲料所施加的差异,主要是甘油磷脂(即溶血磷脂酰乙醇胺,溶血磷脂酰胆碱和磷脂酰胆碱),其次是5-(3',4'-二羟基苯基)-Gamma-valerolodone-4'-O-葡糖醛酸,5a-androstan-3a,17b-diol unulcuric acid和n-searoyl甘氨酸。鉴定的标记包括饲料衍生的(例如酚醛代谢物)和动物衍生的化合物(例如脂质和衍生物)。最后,尽管以较低的预测能力为特征,但发现偏心细胞谱与一些牛奶代谢物显着相关,葡萄球菌与葡萄球菌,假单胞菌酵e和Dermabacteraceae与判别代谢物建立了更高数量的显着相关性。因此,我们的初步结果与不同喂养方案一起提供了综合的原料牛奶样品的综合植物样本,从而支持进一步的临时研究,研究所有加工条件下牛奶的代谢组和均衡变化。

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