Dynamic fecal microenvironment properties enable predictions and understanding of peripartum blood oxidative status and nonesterified fatty acids in dairy cows.

Autor:	Zhu SL; Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China., Gu FF; Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China., Tang YF; Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China., Liu XH; Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China., Jia MH; Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China., Valencak TG; Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China., Liu JX; Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China; Ministry of Education Innovation Team of Development and Function of Animal Digestive System, Zhejiang University, Hangzhou 310058, China., Sun HZ; Key Laboratory of Dairy Cow Genetic Improvement and Milk Quality Research of Zhejiang Province, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China; Ministry of Education Key laboratory of Molecular Animal Nutrition, Zhejiang University, Hangzhou 310058, China; Ministry of Education Innovation Team of Development and Function of Animal Digestive System, Zhejiang University, Hangzhou 310058, China. Electronic address: huizeng@zju.edu.cn.
Jazyk:	angličtina
Zdroj:	Journal of dairy science [J Dairy Sci] 2024 Jan; Vol. 107 (1), pp. 573-592. Date of Electronic Publication: 2023 Sep 09.
DOI:	10.3168/jds.2022-23066
Abstrakt:	The transition period in dairy cows is a critical stage and peripartum oxidative status, negative energy balance (NEB), and inflammation are highly prevalent. Fecal microbial metabolism is closely associated with blood oxidative status and nonesterified fatty acids (NEFA) levels. Here, we investigated dynamic changes in total oxidative status markers and NEFA in blood, fecal microbiome, and metabolome of 30 dairy cows during transition (-21, -7, +7, +21 d relative to calving). Then the Bayesian network and 9 machine-learning algorithms were applied to dismantle their relationship. Our results show that the oxidative status indicator (OSI) of -21, -7, +7 d was higher than +21 d. The plasma concentration of NEFA peaked on +7 d. For fecal microenvironment, a decline in bacterial α diversity was observed at postpartum and in bacterial interactions at +7 d. Conversely, microbial metabolites involved in carbohydrate, lipid, and energy metabolism increased on +7 d. A correlation analysis revealed that 11 and 10 microbial metabolites contributed to OSI and NEFA variations, respectively (arc strength >0.5). The support vector machine (SVM) radial model showed the highest average predictive accuracy (100% and 88.9% in the test and external data sets) for OSI using 1 metabolite and 3 microbiota. The SVM radial model also showed the highest average diagnostic accuracy (100% and 91% in the test and external data sets) for NEFA with 2 metabolites and 3 microbiota. Our results reveal a relationship between variation in the fecal microenvironment and indicators of oxidative status, NEB, and inflammation, which provide a theoretical basis for the prevention and precise regulation of peripartum oxidative status and NEB. (© 2024, The Authors. Published by Elsevier Inc. and Fass Inc. on behalf of the American Dairy Science Association®. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).)
Databáze:	MEDLINE
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