DOI QR코드

DOI QR Code

Nitrogen metabolism and mammary gland amino acid utilization in lactating dairy cows with different residual feed intake

  • Xie, Yunyi (Institute of Dairy Science, MOE Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University) ;
  • Miao, Chao (Institute of Dairy Science, MOE Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University) ;
  • Lu, Yi (Institute of Dairy Science, MOE Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University) ;
  • Sun, Huizeng (Institute of Dairy Science, MOE Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University) ;
  • Liu, Jianxin (Institute of Dairy Science, MOE Key Laboratory of Molecular Animal Nutrition, College of Animal Sciences, Zhejiang University)
  • 투고 : 2020.12.06
  • 심사 : 2021.01.30
  • 발행 : 2021.10.01

초록

Objective: This study was conducted to enhance our understanding of nitrogen (N) metabolism and mammary amino acid (AA) utilization in lactating cows with divergent phenotypes of residual feed intake (RFI). Methods: Fifty-three multiparous mid-lactation Holstein dairy cows were selected for RFI measurements over a 50-d experimental period. The 26 cows with the most extreme RFI values were classified into the high RFI (n = 13) and low RFI (n = 13) groups, respectively, for analysis of N metabolism and AA utilization. Results: Compared with the high RFI cows, the low RFI animals had lower dry matter intake (p<0.01) with no difference observed in milk yield between the two groups (p>0.10). However, higher ratios of milk yield to dry matter intake (p<0.01) were found in the low RFI cows than in the high RFI cows. The low RFI cows had significant greater ratios of milk protein to metabolizable protein (p = 0.02) and milk protein to crude protein intake than the high RFI cows (p = 0.01). The arterial concentration and mammary uptake of essential AA (p<0.10), branched-chain AA (p<0.10), and total AA (p<0.10) tended to be lower in the low RFI cows. Additionally, the low RFI cows tended to have a lower ratio of AA uptake to milk output for essential AA (p = 0.08), branched-chain AA (p = 0.07) and total AA (p = 0.09) than the high RFI cows. Conclusion: In summary, both utilization of metabolizable protein for milk protein and mammary AA utilization are more efficient in cows with lower RFI than in the high RFI cows. Our results provide new insight into the protein metabolic processes (related to N and AA) involved in feed efficiency.

키워드

과제정보

This research described herein was supported by grants from the National Natural Science Foundation of China (31872380) and the China Agricultural (Dairy) Research System (CARS-36, Beijing). The authors thank the staff of the Hangzhou Zhengxing Animal Industry Company (Hangzhou, China) for their assistance. We also acknowledge the members of the Institute of Dairy Science of Zhejiang University (Hangzhou, China) for their assistance in the field sampling and data analysis.

참고문헌

  1. Connor EE, Hutchison JL, Van Tassell CP, Cole JB. Defining the optimal period length and stage of growth or lactation to estimate residual feed intake in dairy cows. J Dairy Sci 2019;102:6131-43. https://doi.org/10.3168/jds.2018-15407
  2. Seymour DJ, Canovas A, Chud TCS, et al. The dynamic behavior of feed efficiency in primiparous dairy cattle. J Dairy Sci 2020;103:1528-40. https://doi.org/10.3168/jds.201917414
  3. Koch RM, Swiger LA, Chambers D, Gregory KE. Efficiency of feed use in beef cattle. J Anim Sci 1963;22:486-94. https://doi.org/10.2527/jas1963.222486x
  4. Liu E, VandeHaar MJ. Relationship of residual feed intake and protein efficiency in lactating cows fed high- or lowprotein diets. J Dairy Sci 2020;103:3177-90. https://doi.org/10.3168/jds.2019-17567
  5. Xi YM, Wu F, Zhao DQ, et al. Biological mechanisms related to differences in residual feed intake in dairy cows. Animal 2016;10:1311-8. https://doi.org/10.1017/S1751731116000343
  6. Macdonald KA, Pryce JE, Spelman RJ, et al. Holstein-Friesian calves selected for divergence in residual feed intake during growth exhibited significant but reduced residual feed intake divergence in their first lactation. J Dairy Sci 2014;97:142735. https://doi.org/10.3168/jds.2013-7227
  7. Djouvinov DS, Todorov NA. Influence of dry matter intake and passage rate on microbial protein synthesis in the rumen of sheep and its estimation by cannulation and a non-invasive method. Anim Feed Sci Technol 1994;48:289-304 https://doi.org/10.1016/0377-8401(94)90179-1
  8. National Research Council. Nutrient requirements of dairy cattle, 7th rev. ed. Washington, DC, USA: National Academies Press; 2001.
  9. Xie Y, Wu Z, Wang D, Liu J. Nitrogen partitioning and microbial protein synthesis in lactating dairy cows with different phenotypic residual feed intake. J Anim Sci Biotechnol 2019;10:54. https://doi.org/10.1186/s40104-019-0356-3
  10. Arriola Apelo SI, Knapp JR, Hanigan MD. Invited review: Current representation and future trends of predicting amino acid utilization in the lactating dairy cow. J Dairy Sci 2014;97:4000-17. https://doi.org/10.3168/jds.2013-7392
  11. Horwitz W, Latimer GW. Official methods of analysis of AOAC International. 18th ed. 281 Gaithersburg, MD, USA: AOAC International; 2005.
  12. Chen XB, Gomes MJ. Estimation of microbial protein supply to sheep and cattle based on urinary excretion of purine derivatives: an overview of technical details. Bucksburn, Aberdeen, UK: Rowett Research Institute; 1992.
  13. Rahmatullah M, Boyde TRC. Improvements in the determination of urea using diacetyl monoxime; methods with and without deproteinisation. Clin Chim Acta 1980;107:3-9. https://doi.org/10.1016/0009-8981(80)90407-6
  14. Mackle TR, Dwyer DA, Bauman DE. Effects of branched-chain amino acids and sodium caseinate on milk protein concentration and yield from dairy cows. J Dairy Sci 1999;82:161-71. https://doi.org/10.3168/jds.S0022-0302(99)75220-3
  15. Valadares RFD, Broderick GA, Valadares Filho SC, Clayton MK. Effect of replacing alfalfa silage with high moisture corn on ruminal protein synthesis estimated from excretion of total purine derivatives. J Dairy Sci 1999;82:2686-96. https://doi.org/10.3168/jds.S0022-0302(99)75525-6
  16. Gargallo S, Calsamiglia S, Ferret A. Technical note: a modified three-step in vitro procedure to determine intestinal digestion of proteins. J Anim Sci 2006;84:2163-67. https://doi.org/10.2527/jas.2004-704
  17. Mepham TB. Amino acid utilization by lactating mammary gland. J Dairy Sci 1982;65:287-98. https://doi.org/10.3168/jds.S0022-0302(82)82191-7
  18. Rius AG, McGilliard ML, Umberger CA, Hanigan MD. Interactions of energy and predicted metabolizable protein in determining nitrogen efficiency in the lactating dairy cow. J Dairy Sci 2010;93:2034-43. https://doi.org/10.3168/jds.20081777
  19. Bequette BJ, Backwell FRC, Crompton LA. Current concepts of amino acid and protein metabolism in the mammary gland of the lactating ruminant. J Dairy Sci 1998;81:254059. https://doi.org/10.3168/jds.S0022-0302(98)70147-X
  20. Doepel L, Lapierre H. Changes in production and mammary metabolism of dairy cows in response to essential and nonessential amino acid infusions. J Dairy Sci 2010;93:3264-74. https://doi.org/10.3168/jds.2009-3033
  21. Mackle TR, Dwyer DA, Ingvartsen KL, Chouinard PY, Ross DA, Bauman DE. Effects of insulin and postruminal supply of protein on use of amino acids by the mammary gland for milk protein synthesis. J Dairy Sci 2000;83:93-105. https://doi.org/10.3168/jds.S0022-0302(00)74860-0
  22. Omphalius C, Lapierre H, Guinard-Flament J, Lamberton P, Bahloul L, Lemosquet S. Amino acid efficiencies of utilization vary by different mechanisms in response to energy and protein supplies in dairy cows: Study at mammary-gland and whole-body levels. J Dairy Sci 2019;102:9883-901. https://doi.org/10.3168/jds.2019-16433
  23. Richardson CM, Baes CF, Amer PR, et al. Determining the economic value of daily dry matter intake and associated methane emissions in dairy cattle. Animal 2020;14:171-9. https://doi.org/10.1017/S175173111900154X
  24. Martineau R, Ouellet DR, Kebreab E, White RR, Lapierre H. Relationships between postruminal casein infusion and milk production, and concentrations of plasma amino acids and blood urea in dairy cows: a multilevel mixed-effects meta-analysis. J Dairy Sci 2017;100:8053-71. https://doi.org/10.3168/jds.2016-11813
  25. Wohlt JE, Clark JH, Derrig RG, Davis CL. Valine, leucine, and isoleucine metabolism by lactating bovine mammary tissue. J Dairy Sci 1977;60:1875-82. https://doi.org/10.3168/jds.S0022-0302(77)84118-0
  26. Li F, Yin Y, Tan B, Kong X, Wu G. Leucine nutrition in animals and humans: mTOR signaling and beyond. Amino Acids 2011;41:1185. https://doi.org/10.1007/s00726-011-0983-2
  27. Nichols K, Kim JJM, Carson M, Metcalf JA, Cant JP, Doelman J. Glucose supplementation stimulates peripheral branched-chain amino acid catabolism in lactating dairy cows during essential amino acid infusions. J Dairy Sci 2016;99:1145-60. https://doi.org/10.3168/jds.2015-9912
  28. Lapierre H, Berthiaume R, Raggio G, et al. The route of absorbed nitrogen into milk protein. Anim Sci 2005;80:1122. https://doi.org/10.1079/ASC41330011
  29. Sun HZ, Zhao K, Zhou M, Chen Y, Guan LL. Landscape of multi-tissue global gene expression reveals the regulatory signatures of feed efficiency in beef cattle. Bioinformatics 2019;35:1712-9. https://doi.org/10.1093/bioinformatics/bty883
  30. Salleh SM, Mazzoni G, Lovendahl P, Kadarmideen HN. Gene co-expression networks from RNA sequencing of dairy cattle identifies genes and pathways affecting feed efficiency. BMC Bioinformatics 2018;19:513. https://doi.org/10.1186/s12859018-2553-z