Advanced Analytical Techniques Applied in Cow Milk Metabolomics
Keywords:
biomarkers, cow, chromatography, milk, metabolomics, spectrometry.Abstract
Milk metabolomics provides a comprehensive analysis of the biochemical content of cow's milk, revealing both the animal's physiological condition and the quality of the end product. Through the identification and quantification of low-molecular-weight metabolites, such as amino acids, fatty acids, sugars, and organic acids, metabolomics enables the detection of biomarkers associated with mastitis, nutritional imbalances, and milk authenticity. The establishment of reliable metabolic profiles relies on advanced analytical techniques, including nuclear magnetic resonance spectroscopy and liquid or gas chromatography coupled with mass spectrometry. This study synthesizes and critically reviews recent research on bovine milk metabolomics employing these state-of-the-art methodologies, aiming to elucidate the biochemical diversity and metabolic complexity underlying milk composition.
References
Rocchetti, G., Gallo, A., Nocetti, M., Lucini, L., and Masoero, F., Milk metabolomics based on ultra-high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry to discriminate different cows feeding regimens. Food Res Int., 2020, 134:109279.
Sundekilde, U. K., Poulsen, N. A., Larsen, L. B., and Bertram, H. C., Nuclear magnetic resonance metabonomics reveals strong association between milk metabolites and somatic cell count in bovine milk. J Dairy Sci., 2013, 96(1):290–299.
Rochfort, S., Metabolomics reviewed: A new “omics” platform technology. J. Nat. Prod., 2005, 68(12):1813–1820.
Suh, J. H., Metabolomics in dairy science: Evaluation of milk and milk product quality. Food Res Int., 2022, 154:110984.
Klein, M. S., Almstetter, M. F., Schlamberger, G., Nürnberger, N., Dettmer, K., Oefner, P. J., Meyer, H.H.D., Wiedemann, S., and Gronwald, W., Nuclear magnetic resonance and mass spectrometry-based milk metabolomics in dairy cows during early and late lactation. J Dairy Sci., 2010, 93:1539–1550.
Hu, F., Furihata, K., Kato, Y., and Tanokura, M., Nondestructive quantification of organic compounds in whole milk without pretreatment by two-dimensional NMR spectroscopy. J. Agric. Food Chem., 2007, 55:4307–4311.
Sundekilde, U. K., Larsen, L. B., and Bertram, H. C., NMR-based milk metabolomics. Metabolites, 2013, 3:204–222.
Qin, C., Liu, L., Wang, Y., Leng, T., Zhu, M., Gan, B., Xie, J., Yu, Q., and Chen, Y., Advancement of omics techniques for chemical profile analysis and authentication of milk. Trends Food Sci Technol., 2022, 127:114–128.
Wang, Y., Li, S., Zhang, F., Lu, Y., Yang, B., Zhang, F., and Liang, X., Study of matrix effects for liquid chromatography–electrospray ionization tandem mass spectrometric analysis of four aminoglycoside residues in milk. J. Chromatogr. A., 2016, 1437:8–14.
Lv, Y., Zhao, J., Xue, H., and Ma, Q., Ambient ionization mass spectrometry for food analysis: Recent progress and applications. TrAC Trends Anal Chem., 2024, 178:117814.
Kang, M., Wang, H., Chen, C., Suo, R., Sun, J., Yue, Q., and Liu, Y., Analytical strategies based on untargeted and targeted metabolomics for the accurate authentication of organic milk from Jersey and yak. Food Chem.: X., 2023, 19:100786.
Fan, X., Li, C., Luo, J., Wang, R., and Zhang, H., Lipid composition and its molecular classes of milk fat globule membranes derived from yak, buffalo, and Holstein cow milk characterized based on UHPLC-MS/MS and untargeted lipidomics. LWT- Food Science and Technology, 2025, 219:117563.
Acquavia, M. A., Villone, A., Rubino, R., and Bianco, G., A comprehensive review of milk components: Recent developments on extraction and analysis methods. Molecules, 2025, 30:1994.
Djordjevic, J., Ledina, T., Baltic, M. Z., Trbovic, D., Babic, M., and Bulajic, S., Fatty acid profile of milk. In: IOP Conference Series: Earth and Environmental Science, Bristol (UK): Institute of Physics Publishing, 2019, 333.
Dominici, S., Marescotti, F., Sanmartin, C., Macaluso, M., Taglieri, I., Venturi, F., Zinnai, A., and Facioni, M. S., Lactose: Characteristics, food and drug-related applications, and its possible substitutions in meeting the needs of people with lactose intolerance. Foods, 2022, 11:1486.
Portnoy, M., Barbano, D. M., Lactose: Use, measurement, and expression of results. J Dairy Sci., 2021, 104:8314–8325.
Da Costa, S. L., Rossi, N. P., and Maldonado, R. R., Evaluation of lactose in milk and dairy products. Int J Innov Educ Res., 2013,1:1–4.
Bulgaru, V., Lactose intolerance and the importance of lactose-free dairy products in this condition. J Soc Sci., 2021, 4:119–133.
European Food Safety Authority (EFSA), Scientific opinion on dietary reference values for protein. EFSA J., 2012,10.
Wu, G., Dietary protein intake and human health. Food Funct., 2016, 7:1251–1265.
Heck, J. M. L., Schennink, A., Van, Valenberg, H. J. F., Bovenhuis, H., Visker, M. H. P. W., Van Arendonk, J. A. M., and Van Hooijdonk, A. C. M., Effects of milk protein variants on the protein composition of bovine milk. J Dairy Sci., 2009, 92:1192–1202.
Koonin, E., Wolf, Y., and Karev, G., The structure of the protein universe and genome evolution. Nature, 2002, 420:218.
Mentana, A., Zianni, R., Campaniello, M., Tomaiuolo, M., Chiappinelli, A., Iammarino, M., and Nardelli, V., Optimizing accelerated solvent extraction combined with liquid chromatography–Orbitrap massspectrometry for efficient lipid profile characterization of mozzarella cheese. Food Chem., 2022, 394:133542.
Rocchetti, G., Becchi, P. P., Salis, L., and Lucini, L., Impact of pasture-based diets on the untargeted metabolomics profile of Sarda sheep milk. Foods, 2023, 12:143.
Du, C., Zhao, X., Shujun Zhang, S., Chu, C., Xiaojian Zhang, X., and Teng, Z., Milk metabolite profiling of dairy cows as influenced by mastitis. Front. Vet. Sci., 2024, 11:1475397.
Ametaj, B. N., Zebeli, Q., Saleem, F., Psychogios, N., Lewis, M. J., Dunn, S.M., Xia, J., and Wishart, D.S., Metabolomics reveals unhealthy alterations in rumen metabolism with increased proportion of cereal grain in the diet of dairy cows. Metabolomics, 2010, 6:583–594.
Bonfatti, V., Bonsembiante, F., Giaretta, E., Vanzani, P., Gelain, M. E., Zecconi, A., Zennaro, L., Gabai, G., and Vianello, F., 1H NMR metabonomics and immune cell signature of milk may reveal insights into subclinical mastitis and quarter interdependence. Vet J., 2025, 313:106401.
Lisuzzo, A., Alterisio, M. C., Esposito, S., Laghi, L., Pesce, A., Ciaramella, P., Cecchini, F., Taio, G., Berlanda, M., Gianesella, M., Guccione, J., and Fiore, E., Milk metabolomic alterations correlated with intramammary infection in dairy cows: From healthy status to clinical mastitis. J Dairy Sci., 2026, 20: S0022-0302(26)00157-8.
Boccia, A. C., Cagliani, L. R., Iannone, D., and Consonni, R., NMR Profiling of Milk from Treated Dried off Cows. Foods, 2026, 15, 770.
Kandasamy, S., Park, W.-S., Bae, I.-S., Yoo, J., Yun, J., Hoa, V.-B., and Ham, J.-S., HRMAS-NMR-Based metabolomics approach to discover key differences in cow and goat milk yoghurt metabolomes. Foods, 2024, 13, 3483.
Homobono Brito de Moura, P., Leleu, G., Da Costa, G., Marti, G., Pétriacq, P., Valls Fonayet, J., and Richard, T., Integrating NMR and MS for Improved Metabolomic Analysis: From Methodologies to Applications. Molecules, 2025, 30, 2624.
Sen, C., Ray, P. R., and Bhattacharyya, M., A critical review on metabolomic analysis of milk and milk products. Int. J. Dairy Technol., 2021, 74: 17-31.
Lu, J., Fernandes, E. A. M., Cano, A. E. P., Vinitwatanakhun, J., Boeren, S., Van Hooijdonk, T., Van Knegsel, A., Vervoort, J., and Hettinga, K.A., Changes in milk proteome and metabolome associated with dry period length, energy balance, and lactation stage in postparturient dairy cows. J Proteome Res., 2013, 12(7).
Boudonck, K. J., Mitchell, M. W., Wulff, J., and Ryal, J.A., Characterization of the biochemical variability of bovine milk using metabolomics. Metabolomics, 2009, 5:375–386.
Smolinska, A., Blanchet, L., Buydens, L. M. C., and Wijmenga, S. S., N M R and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery - A review. Anal Chim Acta., 2012, 750:82–97.
Hajnajafi, K., Iqbal, M. A., Mass-spectrometry based metabolomics: an overview of workflows, strategies, data analysis and applications. Proteome Sci., 2025, 26; 23(1):5.
Ma, S., Wang, D., Zhang, M., Xu L., Fu, X., Zhang, T., Yan, M., and Huang, X., Untargeted metabonomic analysis reveals the composition and changes of milk metabolites in dual-purpose cattle (Bos taurus) population. Journal of Agriculture and Food Research, 2025, 21, 101922.
Becchi, P. P., Rocchetti, G., and Lucini, L., Advancing dairy science through integrated analytical approaches based on multi-omics and machine learning. Current Opinion in Food Science, 2025, 63(1):101289.
Li, Z., Baishanbieke, D., Dongjian, L. I., Xianglong, W., Yong, C., Changjiang, Z., and Fengming L. I., Comparative analysis of differences in metabolites between camel milk and cow milk using liquid Chromatography-Mass Spectrometry-Based metabolomics. Food Science, 2025, 46(4): 154-162.
Mangroliya, P. A., Patel, R., and Singh, S., Exploring the potential of metabolomics in the dairy industry: A mini review. Indian Journal of Animal Health, 2025, 64(2), 145–158.
Zhao, X., Liu, H., and Wang, Y., Applications of metabolomics in cow health assessment, Metabolomics. 2025, 21, 112–128.
Wang, Y., Lan, D., Beng, S., Liu, S., Mu, X., Chen, K., Li, Y., Xu, M., Li, J., and Fu, W., Untargeted metabolomics reveals stage-specific metabolic signatures in yak colostrum, transitional milk and mature milk. Food Chem: X, 2025, 28:102614.
Cao, J., Cui, X., Lu, H., Wang, H., Ma, W., Yue, Z., Zhen, K., Wei, Q., Li, H., Jiang, S., and Ying, W., Regional and longitudinal dynamics of human milk protein components assessed by proteome analysis on a fast and robust micro-flow LC–MS/MS system. Food Chemistry, 2025, 465, Part 1.
Zhang, B., Wang, J., and Wang, B., Metabolomics in ruminant food: Bridging nutritional quality and safety evaluation. Animal Nutriomics, 2025, Cambridge University Press.
