Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-22T22:41:20.109Z Has data issue: false hasContentIssue false
  • English
  • Français

Carbohydrate and amino acid metabolism and oxidative status in Holstein heifers precision-fed diets with different forage to concentrate ratios

Published online by Cambridge University Press:  30 June 2020

J. Zhang Open the ORCID record for J. Zhang [Opens in a new window] ,
H. T. Shi ,
Y. C. Wang ,
S. L. Li ,
Z. J. Cao ,
H. J. Yang  and
Y. J. Wang
J. Zhang
Affiliation:
Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing100193, China
H. T. Shi
Affiliation:
Department of Animal Science, College of Life Science and Technology, Southwest Minzu University, 16# First Ring Road, Chengdu, Sichuan610041, China
Y. C. Wang
Affiliation:
Department of Animal Breeding and Genetics, Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture and Rural Affairs, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing100193, China
S. L. Li
Affiliation:
Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing100193, China
Z. J. Cao
Affiliation:
Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing100193, China
H. J. Yang
Affiliation:
Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing100193, China
Y. J. Wang*
Affiliation:
Department of Animal Nutrition and Feed Science, State Key Laboratory of Animal Nutrition, Beijing Engineering Technology Research Center of Raw Milk Quality and Safety Control, College of Animal Science and Technology, China Agricultural University, No. 2 Yuanmingyuan West Road, Beijing100193, China
*
†E-mail: [email protected]
Get access

Abstract

Previous work led to the proposal that the precision feeding of a high-concentrate diet may represent a potential method with which to enhance feed efficiency (FE) when rearing dairy heifers. However, the physiological and metabolic mechanisms underlying this approach remain unclear. This study used metabolomics analysis to investigate the changes in plasma metabolites of heifers precision-fed diets containing a wide range of forage to concentrate ratios. Twenty-four half-sib Holstein heifers, with a similar body condition, were randomly assigned into four groups and precision fed with diets containing different proportions of concentrate (20%, 40%, 60% and 80% based on DM). After 28 days of feeding, blood samples were collected 6 h after morning feeding and gas chromatography time-of-flight/MS was used to analyze the plasma samples. Parameters of oxidative status were also determined in the plasma. The FE (after being corrected for gut fill) increased linearly (P < 0.01) with increasing level of dietary concentrate. Significant changes were identified for 38 different metabolites in the plasma of heifers fed different dietary forage to concentrate ratios. The main pathways showing alterations were clustered into those relating to carbohydrate and amino acid metabolism; all of which have been previously associated with FE changes in ruminants. Heifers fed with a high-concentrate diet had higher (P < 0.01) plasma total antioxidant capacity and superoxide dismutase but lower (P ≤ 0.02) hydroxyl radical and hydrogen peroxide than heifers fed with a low-concentrate diet, which might indicate a lower plasma oxidative status in the heifers fed a high-concentrate diet. Thus, heifers fed with a high-concentrate diet had higher FE and antioxidant capacity but a lower plasma oxidative status as well as changed carbohydrate and amino acid metabolism. Our findings provide a better understanding of how forage to concentrate ratios affect FE and metabolism in the precision-fed growing heifers.

Keywords

metabolomicshigh concentratefeed efficiencyredoxheifer
Type
Research Article
Information
animal , Volume 14 , Issue 11 , November 2020 , pp. 2315 - 2325
Copyright
© The Author(s), 2020. Published by Cambridge University Press on behalf of The Animal Consortium

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Alexandre, PA, Kogelman, LJ, Santana, MH, Passarelli, D, Pulz, LH, Fantinato-Neto, P, Silva, PL, Leme, PR, Strefezzi, RF, Coutinho, LL, Ferraz, JB, Eler, JP, Kadarmideen, HN and Fukumasu, H 2015. Liver transcriptomic networks reveal main biological processes associated with feed efficiency in beef cattle. BMC Genomics 16, 1073.CrossRefGoogle ScholarPubMed
Bhuiyan, SH, Itami, Y, Rokui, Y, Katayama, T and Izumori, K 1998. d-Allose production from d-psicose using immobilized l-rhamnose isomerase. Journal of Fermentation and Bioengineering 85, 539–541.Google Scholar
Cao, XF, Bai, ZZ, Ma, L, Ma, S and Ge, RL 2017. Metabolic alterations of Qinghai-Tibet Plateau Pikas in adaptation to high altitude. High Altitude Medicine & Biology 18, 219–225.CrossRefGoogle ScholarPubMed
Da Poian, AT and Castanho, MARB 2015. Integrative human biochemistry: a textbook for medical biochemistry. Springer-Verlag, New York, NY, USA.Google Scholar
de Almeida Santana, MH, Junior, GA, Cesar, AS, Freua, MC, da Costa Gomes, R, da Luz, ESS, Leme, PR, Fukumasu, H, Carvalho, ME, Ventura, RV, Coutinho, LL, Kadarmideen, HN and Ferraz, JB 2016. Copy number variations and genome-wide associations reveal putative genes and metabolic pathways involved with the feed conversion ratio in beef cattle. Journal of Applied Genetics 57, 495–504.CrossRefGoogle ScholarPubMed
Haque, MN, Rulquin, H and Lemosquet, S 2013. Milk protein responses in dairy cows to changes in postruminal supplies of arginine, isoleucine, and valine. Journal of Dairy Science 96, 420–430.Google ScholarPubMed
Hoffman, PC, Simson, CR and Wattiaux, M 2007. Limit feeding of gravid Holstein heifers: effect on growth, manure nutrient excretion, and subsequent early lactation performance. Journal of Dairy Science 90, 946–954.Google ScholarPubMed
Jiang, H, Song, JM, Gao, PF, Qin, XJ, Xu, SZ and Zhang, JF 2017. Metabolic characterization of the early stage of hepatic fibrosis in rat using GC-TOF/MS and multivariate data analyses. Biomedical Chromatography 31, e3899.CrossRefGoogle ScholarPubMed
Karisa, BK, Thomson, J, Wang, Z, Li, C, Montanholi, YR, Miller, SP, Moore, SS and Plastow, GS 2014. Plasma metabolites associated with residual feed intake and other productivity performance traits in beef cattle. Livestock Science 165, 200–211.CrossRefGoogle Scholar
Kuhla, B, Albrecht, D, Kuhla, S and Metges, CC 2009. Proteome analysis of fatty liver in feed-deprived dairy cows reveals interaction of fuel sensing, calcium, fatty acid, and glycogen metabolism. Physiological Genomics 37, 88–98.Google ScholarPubMed
Lascano, GJ, Koch, LE and Heinrichs, AJ 2016. Precision-feeding dairy heifers a high rumen-degradable protein diet with different proportions of dietary fiber and forage-to-concentrate ratios. Journal of Dairy Science 99, 7175–7190.Google ScholarPubMed
Lascano, GJ, Zanton, GI, Suarez-Mena, FX and Heinrichs, AJ 2009. Effect of limit feeding high- and low-concentrate diets with Saccharomyces cerevisiae on digestibility and on dairy heifer growth and first-lactation performance. Journal of Dairy Science 92, 5100–5110.CrossRefGoogle ScholarPubMed
Li, Y, Ding, HY, Wang, XC, Feng, SB, Li, XB, Wang, Z, Liu, GW and Li, XW 2016. An association between the level of oxidative stress and the concentrations of NEFA and BHBA in the plasma of ketotic dairy cows. Journal of Animal Physiology And Animal Nutrition 100, 844–851.CrossRefGoogle ScholarPubMed
Luo, ZZ, Shen, LH, Jiang, J, Huang, YX, Bai, LP, Yu, SM, Yao, XP, Ren, ZH, Yang, YX and Cao, SZ 2019. Plasma metabolite changes in dairy cows during parturition identified using untargeted metabolomics. Journal of Dairy Science 102, 4639–4650.Google ScholarPubMed
Nordberg, J and Arner, ES 2001. Reactive oxygen species, antioxidants, and the mammalian thioredoxin system. Free Radical Biology & Medicine 31, 1287–1312.CrossRefGoogle ScholarPubMed
NRC 2001. Nutrient requirements of dairy cattle. National Academy Press, Washington, DC, USA.Google Scholar
Pino, F and Heinrichs, AJ 2017. Sorghum forage in precision-fed dairy heifer diets. Journal of Dairy Science 100, 224–235.CrossRefGoogle ScholarPubMed
R Core Team 2014. R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna.Google Scholar
Russell, JR 2015. Feed efficiency in beef cattle: relationship with digestibility, antioxidant activity, oxidative stress, growth performance, and carcass characteristics. In Animal Science, pp. 163. Iowa State University, Ames.Google Scholar
Salleh, MS, Mazzoni, G, Hoglund, JK, Olijhoek, DW, Lund, P, Lovendahl, P and Kadarmideen, HN 2017. RNA-Seq transcriptomics and pathway analyses reveal potential regulatory genes and molecular mechanisms in high- and low-residual feed intake in Nordic dairy cattle. BMC Genomics 18, 258.CrossRefGoogle ScholarPubMed
Schaff, C, Borner, S, Hacke, S, Kautzsch, U, Albrecht, D, Hammon, HM, Rontgen, M and Kuhla, B 2012. Increased anaplerosis, TCA cycling, and oxidative phosphorylation in the liver of dairy cows with intensive body fat mobilization during early lactation. Journal of Proteome Research 11, 5503–5514.CrossRefGoogle ScholarPubMed
Sejersen, H, Sorensen, MT, Larsen, T, Bendixen, E and Ingvartsen, KL 2012. Liver protein expression in dairy cows with high liver triglycerides in early lactation. Journal of Dairy Science 95, 2409–2421.CrossRefGoogle ScholarPubMed
Shi, H, Zhang, J, Li, S, Ji, S, Cao, Z, Zhang, H and Wang, Y 2018. Effects of a wide range of dietary forage-to-concentrate ratios on nutrient utilization and hepatic transcriptional profiles in limit-fed Holstein heifers. BMC Genomics 19, 148.Google ScholarPubMed
Song, H and Lee, SY 2006. Production of succinic acid by bacterial fermentation. Enzyme and Microbial Technology 39, 352–361.CrossRefGoogle Scholar
Sun, HZ, Shi, K, Wu, XH, Xue, MY, Wei, ZH, Liu, JX and Liu, HY 2017. Lactation-related metabolic mechanism investigated based on mammary gland metabolomics and 4 biofluids’ metabolomics relationships in dairy cows. BMC Genomics 18, 936.CrossRefGoogle ScholarPubMed
Tian, H, Wang, W, Zheng, N, Cheng, J, Li, S, Zhang, Y and Wang, J 2015. Identification of diagnostic biomarkers and metabolic pathway shifts of heat-stressed lactating dairy cows. Journal of Proteomics 125, 17–28.Google ScholarPubMed
Wang, H, Zhang, H, Yao, L, Cui, L, Zhang, L, Gao, B, Liu, W, Wu, D, Chen, M, Li, X, Ji, A and Li, Y 2018. Serum metabolic profiling of type 2 diabetes mellitus in Chinese adults using an untargeted GC/TOFMS. Clinica Chimica Acta 477, 39–47.CrossRefGoogle ScholarPubMed
Wang, Y, Gao, Y, Xia, C, Zhang, H, Qian, WD and Cao, Y 2016. Pathway analysis of plasma different metabolites for dairy cow ketosis. Italian Journal of Animal Science 15, 545–551.CrossRefGoogle Scholar
Williams, CB, Keele, JW and Waldo, DR 1992. A computer model to predict empty body weight in cattle from diet and animal characteristics. Journal of Animal Science 70, 3215–3222.Google ScholarPubMed
Xia, J, Sinelnikov, IV, Han, B and Wishart, DS 2015. MetaboAnalyst 3.0--making metabolomics more meaningful. Nucleic Acids Research 43, W251–257.Google ScholarPubMed
Young, JW 1977. Gluconeogenesis in cattle: significance and methodology. Journal of Dairy Science 60, 1–15.Google ScholarPubMed
Zanton, GI and Heinrichs, AJ 2007. The effects of controlled feeding of a high-forage or high-concentrate ration on heifer growth and first-lactation milk production. Journal of Dairy Science 90, 3388–3396.Google ScholarPubMed
Zanton, GI and Heinrichs, AJ 2009. Digestion and nitrogen utilization in dairy heifers limit-fed a low or high forage ration at four levels of nitrogen intake. Journal of Dairy Science 92, 2078–2094.CrossRefGoogle ScholarPubMed
Zanton, GI and Heinrichs, AJ 2016. Efficiency and rumen responses in younger and older Holstein heifers limit-fed diets of differing energy density. Journal of Dairy Science 99, 2825–2836.CrossRefGoogle ScholarPubMed
Zhang, J, Shi, H, Li, S, Cao, Z, Yang, H and Wang, Y 2019. Integrative hepatic metabolomics and proteomics reveal insights into the mechanism of different feed efficiency with high or low dietary forage levels in Holstein heifers. Journal of Proteomics 194, 1–13.Google ScholarPubMed
Zhang, J, Shi, H, Wang, Y, Li, S, Cao, Z, Ji, S, He, Y and Zhang, H 2017. Effect of dietary forage to concentrate ratios on dynamic profile changes and interactions of ruminal microbiota and metabolites in Holstein heifers. Frontiers in Microbiology 8, 2206.CrossRefGoogle ScholarPubMed
Zhang, J, Shi, H, Wang, Y, Li, S, Zhang, H, Cao, Z and Yang, K 2018. Effects of limit-feeding diets with different forage-to-concentrate ratios on nutrient intake, rumination, ruminal fermentation, digestibility, blood parameters and growth in Holstein heifers. Animal Science Journal 89, 527–536.Google ScholarPubMed
Zheng, C, Yao, J, Guo, L, Cao, Y, Liang, Z, Yang, X and Cai, C 2019. Leucine-induced promotion of post-absorptive EAA utilization and hepatic gluconeogenesis contributes to protein synthesis in skeletal muscle of dairy calves. Journal of Animal Physiology And Animal Nutrition 103, 705–712.CrossRefGoogle ScholarPubMed
Supplementary material: File

Zhang et al. Supplementary Materials

Zhang et al. Supplementary Materials 1

Download Zhang et al. Supplementary Materials(File)
File 109.6 KB
Supplementary material: File

Zhang et al. Supplementary Materials

Zhang et al. Supplementary Materials 2

Download Zhang et al. Supplementary Materials(File)
File 760.7 KB