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

被引:15
作者
Bobbo, T. [1 ]
Meoni, G. [2 ,3 ,4 ]
Niero, G. [1 ]
Tenori, L. [2 ,3 ,4 ]
Luchinat, C. [2 ,3 ,4 ]
Cassandro, M. [1 ,5 ]
Penasa, M. [1 ]
机构
[1] Univ Padua, Dept Agron Food Nat Resources Anim & Environm, I-35020 Legnaro, PD, Italy
[2] Univ Florence, Magnet Resonance Ctr CERM, I-50019 Sesto Fiorentino, Italy
[3] Univ Florence, Dept Chem Ugo Schiff, I-50019 Sesto Fiorentino, Italy
[4] Consorzio Interuniv Risonanze Magnet Met Prot CIR, I-50019 Sesto Fiorentino, Italy
[5] Assoc Nazl Allevatori Razza Frisona Bruna & Jerse, I-26100 Cremona, CR, Italy
关键词
nuclear magnetic resonance; metabolome; mastitis; biomarker; SOMATIC-CELL COUNT; TECHNOLOGICAL PROPERTIES; INTRAMAMMARY INFECTION; SUBCLINICAL MASTITIS; METABOLOMICS; QUALITY; PROFILE; YIELD; INDICATORS; GLUTAMINE;
D O I
10.3168/jds.2021-20906
中图分类号
S8 [畜牧、 动物医学、狩猎、蚕、蜂];
学科分类号
0905 ;
摘要
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.
引用
收藏
页码:535 / 548
页数:14
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