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Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry
BACKGROUND: Ketosis is an important problem for dairy cows` production performance. However, it is still little known about plasma metabolomics details of dairy ketosis. RESULTS: A gas chromatography/mass spectrometry (GC/MS) technique was used to investigate plasma metabolic differences in cows tha...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3849279/ https://www.ncbi.nlm.nih.gov/pubmed/24070026 http://dx.doi.org/10.1186/1746-6148-9-186 |
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author | Zhang, Hongyou Wu, Ling Xu, Chuang Xia, Cheng Sun, Lingwei Shu, Shi |
author_facet | Zhang, Hongyou Wu, Ling Xu, Chuang Xia, Cheng Sun, Lingwei Shu, Shi |
author_sort | Zhang, Hongyou |
collection | PubMed |
description | BACKGROUND: Ketosis is an important problem for dairy cows` production performance. However, it is still little known about plasma metabolomics details of dairy ketosis. RESULTS: A gas chromatography/mass spectrometry (GC/MS) technique was used to investigate plasma metabolic differences in cows that had clinical ketosis (CK, n=22), subclinical ketosis (SK, n=32), or were clinically normal controls (NC, n=22). The endogenous plasma metabolome was measured by chemical derivatization followed by GC/MS, which led to the detection of 267 variables. A two-sample t-test of 30, 32, and 13 metabolites showed statistically significant differences between SK and NC, CK and NC, and CK and SK, respectively. Orthogonal signal correction-partial least-square discriminant analysis (OPLS-DA) revealed that the metabolic patterns of both CK and SK were mostly similar, with the exception of a few differences. The development of CK and SK involved disturbances in many metabolic pathways, mainly including fatty acid metabolism, amino acid metabolism, glycolysis, gluconeogenesis, and the pentose phosphate pathway. A diagnostic model arbitrary two groups was constructed using OPLS-DA and receiver–operator characteristic curves (ROC). Multivariate statistical diagnostics yielded the 19 potential biomarkers for SK and NC, 31 for CK and NC, and 8 for CK and SK with area under the curve (AUC) values. Our results showed the potential biomarkers from CK, SK, and NC, including carbohydrates, fatty acids, amino acids, even sitosterol and vitamin E isomers, etc. 2-piperidinecarboxylic acid and cis-9-hexadecenoic acid were closely associated with metabolic perturbations in ketosis as Glc, BHBA and NEFA for dealing with metabolic disturbances of ketosis in clinical practice. However, further research is needed to explain changes of 2,3,4-trihydroxybutyric acid, 3,4-dihydroxybutyric acid, α-aminobutyric acid, methylmalonic acid, sitosterol and α-tocopherol in CK and SK, and to reveal differences between CK and SK. CONCLUSION: Our study shows that some new biomarkers of ketosis from plasma may find new metabolic changes to have clinically new utility and significance in diagnosis, prognosis, and prevention of ketosis in the future. |
format | Online Article Text |
id | pubmed-3849279 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-38492792013-12-05 Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry Zhang, Hongyou Wu, Ling Xu, Chuang Xia, Cheng Sun, Lingwei Shu, Shi BMC Vet Res Research Article BACKGROUND: Ketosis is an important problem for dairy cows` production performance. However, it is still little known about plasma metabolomics details of dairy ketosis. RESULTS: A gas chromatography/mass spectrometry (GC/MS) technique was used to investigate plasma metabolic differences in cows that had clinical ketosis (CK, n=22), subclinical ketosis (SK, n=32), or were clinically normal controls (NC, n=22). The endogenous plasma metabolome was measured by chemical derivatization followed by GC/MS, which led to the detection of 267 variables. A two-sample t-test of 30, 32, and 13 metabolites showed statistically significant differences between SK and NC, CK and NC, and CK and SK, respectively. Orthogonal signal correction-partial least-square discriminant analysis (OPLS-DA) revealed that the metabolic patterns of both CK and SK were mostly similar, with the exception of a few differences. The development of CK and SK involved disturbances in many metabolic pathways, mainly including fatty acid metabolism, amino acid metabolism, glycolysis, gluconeogenesis, and the pentose phosphate pathway. A diagnostic model arbitrary two groups was constructed using OPLS-DA and receiver–operator characteristic curves (ROC). Multivariate statistical diagnostics yielded the 19 potential biomarkers for SK and NC, 31 for CK and NC, and 8 for CK and SK with area under the curve (AUC) values. Our results showed the potential biomarkers from CK, SK, and NC, including carbohydrates, fatty acids, amino acids, even sitosterol and vitamin E isomers, etc. 2-piperidinecarboxylic acid and cis-9-hexadecenoic acid were closely associated with metabolic perturbations in ketosis as Glc, BHBA and NEFA for dealing with metabolic disturbances of ketosis in clinical practice. However, further research is needed to explain changes of 2,3,4-trihydroxybutyric acid, 3,4-dihydroxybutyric acid, α-aminobutyric acid, methylmalonic acid, sitosterol and α-tocopherol in CK and SK, and to reveal differences between CK and SK. CONCLUSION: Our study shows that some new biomarkers of ketosis from plasma may find new metabolic changes to have clinically new utility and significance in diagnosis, prognosis, and prevention of ketosis in the future. BioMed Central 2013-09-26 /pmc/articles/PMC3849279/ /pubmed/24070026 http://dx.doi.org/10.1186/1746-6148-9-186 Text en Copyright © 2013 Zhang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Zhang, Hongyou Wu, Ling Xu, Chuang Xia, Cheng Sun, Lingwei Shu, Shi Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry |
title | Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry |
title_full | Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry |
title_fullStr | Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry |
title_full_unstemmed | Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry |
title_short | Plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry |
title_sort | plasma metabolomic profiling of dairy cows affected with ketosis using gas chromatography/mass spectrometry |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3849279/ https://www.ncbi.nlm.nih.gov/pubmed/24070026 http://dx.doi.org/10.1186/1746-6148-9-186 |
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