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利用核磁共振波谱技术研究奶牛乳中代谢物与乳房健康状况之间的关系。

Nuclear magnetic resonance spectroscopy to investigate the association between milk metabolites and udder quarter health status in dairy cows.

机构信息

Department of Agronomy, Food, Natural resources, Animals and Environment, University of Padova, 35020 Legnaro (PD), Italy.

Magnetic Resonance Center (CERM) and Department of Chemistry "Ugo Schiff," University of Florence, 50019 Sesto Fiorentino, Italy; Consorzio Interuniversitario Risonanze Magnetiche Metallo Proteine (CIRMMP), 50019 Sesto Fiorentino, Italy.

出版信息

J Dairy Sci. 2022 Jan;105(1):535-548. doi: 10.3168/jds.2021-20906. Epub 2021 Oct 14.

Abstract

Nuclear magnetic resonance spectroscopy was applied to investigate the association between milk metabolome and udder quarter health status in dairy cows. Mammary gland health status was defined by combining information provided by traditional somatic cell count (SCC) and differential SCC (DSCC), which expresses the percentage of neutrophils and lymphocytes over total SCC. Quarter milk samples were collected in triplicate (d 1 to 3) from 10 Simmental cows, 5 defined as cases and 5 defined as controls according to SCC levels at d 0. A total of 120 samples were collected and analyzed for bacteriology, milk composition, SCC, DSCC, and milk metabolome. Bacteriological analysis revealed the presence of mostly coagulase-negative staphylococci in quarter milk samples of cows defined as cases. Nuclear magnetic resonance spectra of all quarter samples were first analyzed using the unsupervised multivariate approach principal component analysis, which revealed a specific metabolomic fingerprint of each cow. Then, the supervised cross-validated orthogonal projections to latent structures discriminant analysis unquestionably showed that each cow could be very well identified according to its milk metabolomic fingerprint (accuracy = 95.8%). The comparison of 12 different models, built on bucketed 1-dimensional NOESY spectra (noesygppr1d, Bruker BioSpin) using different SCC and DSCC thresholds, corroborated the assumption of improved udder health status classification ability by joining information provided by both SCC and DSCC. Univariate analysis performed on the 34 quantitated metabolites revealed lower levels of riboflavin, galactose, galactose-1-phosphate, dimethylsulfone, carnitine, hippurate, orotate, lecithin, succinate, glucose, and lactose, and greater levels of lactate, phenylalanine, choline, acetate, O-acetylcarnitine, 2-oxoglutarate, and valine, in milk samples with high somatic cells. In the 5 cases, results of the udder quarter with the highest SCC compared with its symmetrical relative were in line with quarter-level findings. Our study suggests that increased SCC is associated with changes in milk metabolite fingerprint and highlights the potential use of different metabolites as novel indicators of udder health status and milk quality.

摘要

应用核磁共振波谱技术研究牛奶代谢组与奶牛乳房健康状况之间的关系。乳房健康状况通过结合传统的体细胞计数(SCC)和差异 SCC(DSCC)信息来定义,DSCC 表示中性粒细胞和淋巴细胞总数 SCC 的百分比。从 10 头西门塔尔奶牛中采集了 3 份(第 1 天至第 3 天)乳房 quarter 牛奶样本,根据第 0 天的 SCC 水平,5 头奶牛被定义为病例,5 头奶牛被定义为对照。共采集并分析了 120 个样本,用于细菌学、牛奶成分、SCC、DSCC 和牛奶代谢组学。细菌学分析显示,病例奶牛的 quarter 牛奶样本中主要存在凝固酶阴性葡萄球菌。使用无监督多元方法主成分分析对所有 quarter 样本的核磁共振光谱进行了分析,结果显示每个奶牛都有特定的代谢组指纹。然后,通过有监督的交叉验证正交投影到潜在结构判别分析,毫无疑问地表明可以根据牛奶代谢组指纹很好地识别每个奶牛(准确率=95.8%)。基于不同 SCC 和 DSCC 阈值构建的 12 个不同模型的比较,使用 bucketed 1 维 NOESY 谱(noesygppr1d,Bruker BioSpin),证实了通过结合 SCC 和 DSCC 提供的信息来提高乳房健康状况分类能力的假设。对 34 种定量代谢物进行的单变量分析显示,高体细胞牛奶样本中核黄素、半乳糖、半乳糖-1-磷酸、二甲基砜、肉碱、马尿酸、乳酰、卵磷脂、琥珀酸、葡萄糖和乳糖的水平较低,而乳酸、苯丙氨酸、胆碱、乙酸盐、乙酰肉碱、2-氧代戊二酸和缬氨酸的水平较高。在 5 个病例中,与相对应的对称 quarter 相比,SCC 最高的 quarter 的结果与 quarter 级别的发现一致。我们的研究表明,SCC 的增加与牛奶代谢产物指纹的变化有关,并强调了不同代谢产物作为乳房健康状况和牛奶质量的新型指标的潜力。

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