期刊
JOURNAL OF DAIRY SCIENCE
卷 104, 期 12, 页码 12553-12566出版社
ELSEVIER SCIENCE INC
DOI: 10.3168/jds.2021-20477
关键词
multiplatform metabolomics; methane biomarker; microbial metabolite; milk; dairy cow
资金
- CIFRE (Industrial Agreements of Training by Research) - ANRT (National Association of Research and Technology, Paris, France)
- Adisseo France SAS (Antony, France)
- Agrial (Caen, France)
- APIS-GENE (Paris, France)
- Deltavit (Janze, France)
- Moy Park Beef Orleans, (Fleury-les-Aubrais, France)
- Neovia (Saint Nolff, France)
- Techna France Nutrition (Coueron, France)
- Valorex (Combourtille, France)
- DSM Nutritional Products AG (Kaiseraugst, Switzerland)
- Institut de l'Elevage (Paris, France)
- Lallemand (Blagnac, France)
The study used a multiplatform metabolomics approach to investigate changes in milk metabolic profiles related to methanogenesis in dairy cows. Findings showed 38 discriminant metabolites affecting methane metabolism were identified, providing new insights on the potential role of milk metabolites as indicators of enteric methane modifications in dairy cows.
Metabolome profiling in biological fluids is an interesting approach for exploring markers of methane emissions in ruminants. In this study, a multiplatform me tab olomics approach was used for investigating changes in milk metabolic profiles related to methanogenesis in dairy cows. For this purpose, 25 primiparous Holstein cows at similar lactation stage were fed the same diet supplemented with (treated, n = 12) or without (control, n = 13) a specific antimethanogenic additive that reduced enteric methane production by 23% with no changes in intake, milk production, and health status. The study lasted 6 wk, with sampling and measures performed in wk 5 and 6. Milk samples were analyzed using 4 complementary analytical methods, including 2 untargeted (nuclear magnetic resonance and liquid chromatography coupled to a quadrupole-time-of-flight mass spectrometer) and 2 targeted (liquid chromatography-tandem mass spectrometry and gas chromatography coupled to a flame ionization detector) approaches. After filtration, variable selection and normalization data from each analytical platform were then analyzed using multivariate orthogonal partial least square discriminant analysis. All 4 analytical methods were able to differentiate cows from treated and control groups. Overall, 38 discriminant metabolites were identified, which affected 10 metabolic pathways including methane metabolism. Some of these metabolites such as dimethylsulfoxide, dimethylsulfone, and citramalic acid, detected by nuclear magnetic resonance or liquid chromatography-mass spectrometry methods, originated from the rumen microbiota or had a microbial host animal co-metabolism that could be associated with methanogenesis. Also, discriminant milk fatty acids detected by targeted gas chromatography were mostly of ruminal microbial origin. Other metabolites and metabolic pathways significantly affected were associated with AA metabolism. These findings provide new insight on the potential role of milk metabolites as indicators of enteric methane modifications in dairy cows.
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