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Cited by 124Ruminant Nutrition and Digestive PhysiologyAnimal Nutrition and PhysiologyMetabolomics and Mass Spectrometry Studies

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Rumen Fluid Metabolomics Analysis Associated with Feed Efficiency on Crossbred Steers

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Artegoitia, Virginia M., Foote, Andrew P., Lewis, Ronald M., Freetly, Harvey C.·2017·Scientific Reports
DOI 10.1038/s41598-017-02856-0PMC PMC5460109
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Abstract

The rumen has a central role in the efficiency of digestion in ruminants. To identify potential differences in rumen function that lead to differences in average daily gain (ADG), rumen fluid metabolomic analysis by LC-MS and multivariate/univariate statistical analysis were used to identify differences in rumen metabolites. Individual feed intake and body-weight was measured on 144 steers during 105 d on a high concentrate ration. Eight steers with the greatest ADG and 8 steers with the least-ADG with dry matter intake near the population average were selected. Blood and rumen fluid was collected from the 16 steers 26 d before slaughter and at slaughter, respectively. As a result of the metabolomics analysis of rumen fluid, 33 metabolites differed between the ADG groups based on t-test, fold changes and partial least square discriminant analysis. These metabolites were primarily involved in linoleic and alpha-linolenic metabolism (impact-value 1.0 and 0.75, respectively; P < 0.05); both pathways were down-regulated in the greatest-ADG compared with least-ADG group. Ruminal biohydrogenation might be associated with the overall animal production. The fatty acids were quantified in rumen and plasma using targeted MS to validate and evaluate the simple combination of metabolites that effectively predict ADG.

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Crossref · 10.1038/s41598-017-02856-0

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Figure 1 Ruminal metabolomic profile of the steers with the greatest average daily gain (high-ADG; open red triangle) and the least ADG (low-ADG; green plus) with similar average dry matter intake. (A) Principal component analysis for UPLC-qTOF 90 metabolites identified to differ between ADG by t-test (P < 0.1). (B) Partial Least Square-Discriminant Analysis for UPLC-qTOF 90 metabolites identified to differ between ADG by t-test (P < 0.1). One data point represents one steer.
Figure 1 Ruminal metabolomic profile of the steers with the greatest average daily gain (high-ADG; open red triangle) and the least ADG (low-ADG; green plus) with similar average dry matter intake. (A) Principal component analysis for UPLC-qTOF 90 metabolites identified to differ between ADG by t-test (P < 0.1). (B) Partial Least Square-Discriminant Analysis for UPLC-qTOF 90 metabolites identified to differ between ADG by t-test (P < 0.1). One data point represents one steer.CC BY · PubMed Central
Figure 2 Ruminal metabolomics pathway analysis by MetaboAnalyst 3.0 Software on the steers with the greatest average daily gain compare to the least ADG with similar average dry matter intake according to Bos taurus KEGG pathway database. UPLC-qTOF 90 metabolites identified to differ between ADG by t-test (P < 0.1). (a) Alpha-linolenic acid metabolism, (b) linoleic metabolism (c) taurine and hypotaurine metabolism d) phenylalanine, tyrosine and tryptophan (e) sphingolipids (f) phenylalanine (g) retinol (h) histidine (i) primary bile biosynthesis (j) glycerophospholipid (k) tyrosin (l) porphyrin and chlorophyll (m) steroid hormone biosynthesis (n) glutathione (o) Riboflavin (p) Gluconeogenesis. The darker the color and larger the size represent higher P-value from enrichment analysis and greater impact from the pathway topology analysis, respectively.
Figure 2 Ruminal metabolomics pathway analysis by MetaboAnalyst 3.0 Software on the steers with the greatest average daily gain compare to the least ADG with similar average dry matter intake according to Bos taurus KEGG pathway database. UPLC-qTOF 90 metabolites identified to differ between ADG by t-test (P < 0.1). (a) Alpha-linolenic acid metabolism, (b) linoleic metabolism (c) taurine and hypotaurine metabolism d) phenylalanine, tyrosine and tryptophan (e) sphingolipids (f) phenylalanine (g) retinol (h) histidine (i) primary bile biosynthesis (j) glycerophospholipid (k) tyrosin (l) porphyrin and chlorophyll (m) steroid hormone biosynthesis (n) glutathione (o) Riboflavin (p) Gluconeogenesis. The darker the color and larger the size represent higher P-value from enrichment analysis and greater impact from the pathway topology analysis, respectively.CC BY · PubMed Central
Figure 3 The integrative ruminal metabolic pathway changes on the steers with the greatest average daily gain compare to the least ADG with similar average dry matter intake according to Bos taurus KEGG pathway database. UPLC-qTOF 90 metabolites identified to differ between ADG by t-test (P < 0.1).
Figure 3 The integrative ruminal metabolic pathway changes on the steers with the greatest average daily gain compare to the least ADG with similar average dry matter intake according to Bos taurus KEGG pathway database. UPLC-qTOF 90 metabolites identified to differ between ADG by t-test (P < 0.1).CC BY · PubMed Central
Figure 4 Receiver operating curves (ROC) of fatty acids for the differential identification of feed efficiency on steers. (A) Rumen fluid ROC using the combination of pentadecanoic acid, palmitic acid, linoleic acid and alpha-linolenic acid. (B) Plasma ROC using the combination of arachidonic acid/docosahexanoic acid ratio and alpha-linolenic acid.
Figure 4 Receiver operating curves (ROC) of fatty acids for the differential identification of feed efficiency on steers. (A) Rumen fluid ROC using the combination of pentadecanoic acid, palmitic acid, linoleic acid and alpha-linolenic acid. (B) Plasma ROC using the combination of arachidonic acid/docosahexanoic acid ratio and alpha-linolenic acid.CC BY · PubMed Central
Figure 5 Overview of workflow utilized in the identification of biomarkers of feed efficiency on crossbreed steers.
Figure 5 Overview of workflow utilized in the identification of biomarkers of feed efficiency on crossbreed steers.CC BY · PubMed Central
Figure 6 Rumen sampling selection. The two animals groups were selected by the greatest average daily gain (high-ADG; open red triangle; n = 8) and the least ADG steers (low-ADG; green plus; n = 8) with similar average dry matter intake (dash line) from the total population (black dots; n = 144) evaluated.
Figure 6 Rumen sampling selection. The two animals groups were selected by the greatest average daily gain (high-ADG; open red triangle; n = 8) and the least ADG steers (low-ADG; green plus; n = 8) with similar average dry matter intake (dash line) from the total population (black dots; n = 144) evaluated.CC BY · PubMed Central

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Metadata

Authors
Artegoitia, V. M., Foote, A. P., Lewis, R. M., & Freetly, H. C.
Affiliations
  • University of Nebraska–Lincoln (US)
  • Roman L. Hruska U.S. Meat Animal Research Center (US)
Corresponding author
Freetly, Harvey C.
ORCID
Venue
Scientific Reports
Publisher
Springer Science and Business Media LLC
Published
2017-06-06
Volume
7
Issue
1
Pages
2864-2864
ISSN
2045-2322 (ISSN-L)
DOI
10.1038/s41598-017-02856-0
PMC
PMC5460109
OpenAlex
W2553397641
Cited by
123
References
37
Citations by year
2026: 7 · 2025: 4 · 2024: 32 · 2023: 15 · 2022: 15 · 2021: 16 · 2020: 15 · 2019: 7 · 2018: 11
FWCI
15.70
Type
journal article
Language
en
Open access
Licence
Locations
  • Scientific Reports (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, other-oa)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Lincoln (University of Nebraska) (submittedVersion)
  • Lincoln (University of Nebraska) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
U.S. Department of Agriculture
Topics
  • Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Ruminant Nutrition and Digestive Physiology
  • Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Animal Nutrition and Physiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
Keywords
feed efficiency, average daily gain, crossbred steers, high-concentrate diet, linoleic acid metabolism, alpha-linolenic acid metabolism, ruminal biohydrogenation, fatty acids, rumen metabolites, growth performance prediction
MeSH terms
Animals, Animal Feed, Breeding, Cattle, Crosses, Genetic, Fatty Acids, ROC Curve, Rumen, Extracellular Fluid, Metabolic Networks and Pathways, Metabolomics, Metabolome

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