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Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle

This study presents the application of metabolomics to evaluate changes in the rumen metabolites of beef cattle fed with three different diet types: forage-rich, mixed and concentrate-rich. Rumen fluid samples were analysed by (1)H-NMR spectroscopy and the resulting spectra were used to characterise...

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Autores principales: Bica, R., Palarea-Albaladejo, J., Kew, W., Uhrin, D., Pacheco, D., Macrae, A., Dewhurst, R. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7101347/
https://www.ncbi.nlm.nih.gov/pubmed/32221381
http://dx.doi.org/10.1038/s41598-020-62485-y
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author Bica, R.
Palarea-Albaladejo, J.
Kew, W.
Uhrin, D.
Pacheco, D.
Macrae, A.
Dewhurst, R. J.
author_facet Bica, R.
Palarea-Albaladejo, J.
Kew, W.
Uhrin, D.
Pacheco, D.
Macrae, A.
Dewhurst, R. J.
author_sort Bica, R.
collection PubMed
description This study presents the application of metabolomics to evaluate changes in the rumen metabolites of beef cattle fed with three different diet types: forage-rich, mixed and concentrate-rich. Rumen fluid samples were analysed by (1)H-NMR spectroscopy and the resulting spectra were used to characterise and compare metabolomic profiles between diet types and assess the potential for NMR metabolite signals to be used as proxies of methane emissions (CH(4) in g/kg DMI). The dataset available consisted of 128 measurements taken from 4 experiments with CH(4) measurements taken in respiration chambers. Predictive modelling of CH(4) was conducted by partial least squares (PLS) regression, fitting calibration models either using metabolite signals only as predictors or using metabolite signals as well as other diet and animal covariates (DMI, ME, weight, BW(0.75), DMI/BW(0.75)). Cross-validated R(2) were 0.57 and 0.70 for the two models respectively. The cattle offered the concentrate-rich diet showed increases in alanine, valerate, propionate, glucose, tyrosine, proline and isoleucine. Lower methane yield was associated with the concentrate-rich diet (p < 0.001). The results provided new insight into the relationship between rumen metabolites, CH(4) production and diets, as well as showing that metabolites alone have an acceptable association with the variation in CH(4) production from beef cattle.
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spelling pubmed-71013472020-03-31 Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle Bica, R. Palarea-Albaladejo, J. Kew, W. Uhrin, D. Pacheco, D. Macrae, A. Dewhurst, R. J. Sci Rep Article This study presents the application of metabolomics to evaluate changes in the rumen metabolites of beef cattle fed with three different diet types: forage-rich, mixed and concentrate-rich. Rumen fluid samples were analysed by (1)H-NMR spectroscopy and the resulting spectra were used to characterise and compare metabolomic profiles between diet types and assess the potential for NMR metabolite signals to be used as proxies of methane emissions (CH(4) in g/kg DMI). The dataset available consisted of 128 measurements taken from 4 experiments with CH(4) measurements taken in respiration chambers. Predictive modelling of CH(4) was conducted by partial least squares (PLS) regression, fitting calibration models either using metabolite signals only as predictors or using metabolite signals as well as other diet and animal covariates (DMI, ME, weight, BW(0.75), DMI/BW(0.75)). Cross-validated R(2) were 0.57 and 0.70 for the two models respectively. The cattle offered the concentrate-rich diet showed increases in alanine, valerate, propionate, glucose, tyrosine, proline and isoleucine. Lower methane yield was associated with the concentrate-rich diet (p < 0.001). The results provided new insight into the relationship between rumen metabolites, CH(4) production and diets, as well as showing that metabolites alone have an acceptable association with the variation in CH(4) production from beef cattle. Nature Publishing Group UK 2020-03-27 /pmc/articles/PMC7101347/ /pubmed/32221381 http://dx.doi.org/10.1038/s41598-020-62485-y Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Bica, R.
Palarea-Albaladejo, J.
Kew, W.
Uhrin, D.
Pacheco, D.
Macrae, A.
Dewhurst, R. J.
Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle
title Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle
title_full Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle
title_fullStr Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle
title_full_unstemmed Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle
title_short Nuclear Magnetic Resonance to Detect Rumen Metabolites Associated with Enteric Methane Emissions from Beef Cattle
title_sort nuclear magnetic resonance to detect rumen metabolites associated with enteric methane emissions from beef cattle
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7101347/
https://www.ncbi.nlm.nih.gov/pubmed/32221381
http://dx.doi.org/10.1038/s41598-020-62485-y
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