Skip to main content
SpringerLink
Log in

Global urine fingerprinting by LC-ESI(+)-HRMS for better characterization of metabolic pathway disruption upon anabolic practices in bovine

  • Original Article
  • Published:
Metabolomics Aims and scope Submit manuscript

Abstract

The use of anabolic agents in meat producing animals is forbidden in Europe since 1988. Nevertheless, the possibility of widespread abuse of hormonal substances still exists, mainly due to economical benefits. The use of “omics” approach is a promising strategy to highlight anabolic hormone abuse by indirectly detecting their physiological action. In this context, the aim of this work was to set up a liquid chromatography – high resolution mass spectrometry based metabolomics workflow for the screening of a combined trenbolone acetate/estradiol implant abuse in cattle urine. Therefore, an untargeted metabolomics approach combining the information provided by reverse-phase liquid chromatography and hydrophilic interaction chromatography both coupled to high resolution mass spectrometry was developed and applied to characterize and compare cattle urinary metabolic profiles from non-implanted and implanted animals. The combination of both separation modes improved the metabolite information richness. Discrimination between treated and untreated animals was observed by application of multivariate statistical analysis. Moreover, OPLS models permitted to highlight the candidate biomarkers appearing as the ions which contribute the most in the observed discrimination. From the results obtained, metabolomics approaches can be considered as a powerful strategy for the detection of fraudulent anabolic treatments in cattle since global urinary metabolic response provides helpful discrimination.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Anizan, S., Bichon, E., Monteau, F., Cesbron, N., Antignac, J.-P., & Le Bizec, B. (2010). A new reliable sample preparation for high throughput focused steroid profiling by gas chromatography-mass spectrometry. Journal of Chromatography A, 1217, 6652–6660.

    Article  CAS  PubMed  Google Scholar 

  • Bartle, S. J., Preston, R. L., Brown, R. E., & Grant, R. J. (1992). Trenbolone acetate/estradiol combinations in feedlot steers: dose-response and implant carrier effects. Journal of Animal Science, 70, 1326–1332.

    CAS  PubMed  Google Scholar 

  • Blanco CE1, Popper P, Micevych P. (1997). Anabolic-androgenic steroid induced alterations in choline acetyltransferase messenger RNA levels of spinal cord motoneurons in the male rat. Neuroscience. 78(3):873-82.

  • Cone, E. J., Caplan, Y. H., Moser, F., Robert, T., Shelby, M. K., & Black, D. L. (2009). Normalization of urinary drug concentrations with specific gravity and creatinine. Journal of Analytical Toxicology, 33(1), 1–7.

    Article  CAS  PubMed  Google Scholar 

  • Council Directive 2003/74/EC (2003). Amending Council Directive 96/22/EC concerning the prohibition on the use in stockfarming of certain substances having a hormonal or thyrostatic action anf of beta-agonists. Official Journal of European Communities, L262, 17–21.

  • Council Directive 2008/97/EC (2008). Amending Council Directive 96/22/EC concerning the prohibition on the use in stockfarming of certain substances having a hormonal or thyrostatic action and of beta-agonists. Official Journal of European Communities, L318, 9–11.

  • Council Directive 96/22/EC (1996). Concerning the prohibition on the use in stockfarming of certain substances having a hormonal or thyrostatic action and of beta-agonists, and repealing Directives 81/602/EEC, 88/146/EEC and 88/299/EEC. Official Journal of European Communities, L125, 3–9.

  • Courant, F., Pinel, G., Bichon, E., Monteau, F., Antignac, J.-P., & Le Bizec, B. (2009). Development of a metabolomic approach based on liquid chromatography-high resolution mass spectrometry to screen for a clenbuterol abuse in calves. Analyst, 134, 1637–1646.

    Article  CAS  PubMed  Google Scholar 

  • Dervilly-Pinel, G., Courant, F., Chereau, S., Royer, A. L., Boyard-Kieken, F., Antignac, J. P., et al. (2012). Metabolomics in food analysis: application to the control of forbidden substances. Drug Testing and Analysis, 4, 59–69. doi:10.1002/dta.1349.

    Article  CAS  PubMed  Google Scholar 

  • FDA (2007). Freedom of information summary original new animal drug administration. NADA 141-269. REVALOR-XS (Trenbolone acetate and Estradiol) Implant (pellets) for cattle (Steers fed in confinement for slaughter). http://www.fda.gov/downloads/AnimalVeterinary/Products/ApprovedAnimalDrug/Products/FOIADrugSummaries/ucm062321.pdf. Accessed July 13, 2012.

  • Jacob, C. C., Dervilly-Pinel, G., Biancotto, G., & Le Bizec, B. (2013). Evaluation of specific gravity as normalization strategy for cattle urinary metabolome analysis. Metabolomics, 1–11, doi:10.1007/s11306-013-0604-z.

  • Johnson, B. J., Anderson, P. T., Meiske, J. C., & Dayton, W. R. (1996). Effect of a combined trenbolone acetate and estradiol implant on feedlot performance, carcass characteristics and carcass composition of feedlot steers. Journal of Animal Science, 74, 363–371.

    CAS  PubMed  Google Scholar 

  • Kind, T., & Fiehn, O. (2007). Seven golden rules for heuristic filtering of molecular formulas obtained by accurate mass spectrometry. BMC bioinformatics, 8, doi:10.1186/1471-2105-8-105.

  • MacDonald, M. A., Krueger, H., & Bogart, R. (1960). Rate and Efficiency of Gains in Beef Cattle. 8. Urinary Specific Gravity, pH, and Buffer Capacity in Beef Cattle (Vol. 54). Oregon State University: Technical Bulletin. Oregon Agricultural Experiment Station.

  • Pampusch, M. S., Johnson, B. J., White, M. E., Hathaway, M. R., Dunn, J. D., Waylan, A. T., et al. (2003). Time course of changes in growth factor mRNA levels in muscle of steroid-implanted and nonimplanted steers. Journal of Animal Science, 81, 2733–2740.

    CAS  PubMed  Google Scholar 

  • Patti, G. J., Tautenhahn, R., & Siuzdak, G. (2012). Meta-analysis of untargeted metabolomic data from multiple profiling experiments. Nature Protocols, 7(3), 508–516. doi:10.1038/nprot.2011.454.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Pinel, G., Weigel, S., Antignac, J.-P., Mooney, M. H., Elliot, C., Nielen, M. W. F., et al. (2010). Targeted and untargeted profiling of biological fluids to screen for anabolic practices in cattle. Trends in Analytical Chemistry, 29, 1269–1280.

    Article  CAS  Google Scholar 

  • Pinel, G., Weigel, S., Lommen, A., Chereau, S., Rambaud, L., Essers, M. L., et al. (2011). Assessment of two complementary LC-HRMS metabolomics strategies for the screening of anabolic steroid treatment in calves. Analytica Chimica Acta, 700, 144–154.

    Article  Google Scholar 

  • Ridgway, N. D. (2013). The role of phosphatidylcholine and choline metabolites to cell proliferation and survival. Critical Reviews in Biochemistry and Molecular Biology, 48(1), 20–38.

    Article  CAS  PubMed  Google Scholar 

  • Rijk, J. C. W., Lommen, A., Essers, M. L., Groot, M. J., Van Hende, J. M., Doeswijk, T. G., et al. (2009). Metabolomics approach to anabolic steroid urine profiling of bovines treated with prohormones. Analytical Chemistry, 81(16), 6879–6888.

    Article  CAS  PubMed  Google Scholar 

  • Smith, C. A., Want, E. J., O’Maille, G., Abagyan, R., & Siuzdak, G. (2006). XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Analytical Chemistry, 78(3), 779–787. doi:10.1021/ac051437y.

    Article  CAS  PubMed  Google Scholar 

  • Tautenhahn, R., Bottcher, C., & Neumann, S. (2008). Highly sensitive feature detection for high resolution LC/MS. BMC Bioinformatics, 9, 504. doi:10.1186/1471-2105-9-504.

    Article  PubMed Central  PubMed  Google Scholar 

  • Tautenhahn, R., Patti, G. J., Kalisiak, E., Miyamoto, T., Schmidt, M., Lo, F. Y., et al. (2011). metaXCMS: Second-order analysis of untargeted metabolomics data. Analytical Chemistry, 83(3), 696–700. doi:10.1021/ac102980g.

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Trygg, J., Holmes, E., & Lundstedt, T. (2007). Chemometrics in metabonomics. Journal of Proteome Research, 6, 469–479.

    Article  CAS  PubMed  Google Scholar 

  • van der Kloet, F. M., Bobeldijk, I., Verheij, E. R., & Jellema, R. H. (2009). Analytical Error Reduction Using Single Point Calibration for Accurate and Precise Metabolomic Phenotyping. Journal of Proteome Research, 8, 5132–5141.

    Article  PubMed  Google Scholar 

  • Werner, E., Heilier, J.-F., Ducruix, C., Ezan, E., Junot, C., & Tabet, J.-C. (2008). Mass spectrometry for the identification of the discriminating signals from metabolomics: Current status and future trends. Journal of Chromatography B-Analytical Technologies in the Biomedical and Life Sciences, 871(2), 143–163. doi:10.1016/j.jchromb.2008.07.004.

    Article  CAS  Google Scholar 

  • Westerhuis, J. A., Hoefsloot, H. C. J., Smit, S., Vis, D. J., Smilde, A. K., van Velzen, E. J. J., et al. (2008). Assessment of PLSDA cross validation. Metabolomics, 4, 81–89.

    Article  CAS  Google Scholar 

Download references

Aknowledgments

This work was financially supported by the Italian Ministry of Health (RF-IZV-2008-1175188). Authors thank Merck Animal Health for kindly providing the implant Revalor-XS®.

Conflict of interest

The authors have declared no conflicts of interest in the submission of this manuscript.

Author information

Authors and Affiliations

  1. LUNAM Université, ONIRIS, École nationale vétérinaire, agroalimentaire et de l’alimentation Nantes-Atlantique, Laboratoire d’Étude des Résidus et Contaminants dans les Aliments (LABERCA), Atlanpole – La Chantrerie, BP 40706, Nantes, 44307, France

    Cristina C. Jacob, Gaud Dervilly-Pinel, Fabrice Monteau & Bruno Le Bizec

  2. Department of Chemistry, Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro, 35020, Italy

    Giancarlo Biancotto

Authors
  1. Cristina C. Jacob
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Gaud Dervilly-Pinel
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Giancarlo Biancotto
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Fabrice Monteau
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Bruno Le Bizec
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Gaud Dervilly-Pinel.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Jacob, C.C., Dervilly-Pinel, G., Biancotto, G. et al. Global urine fingerprinting by LC-ESI(+)-HRMS for better characterization of metabolic pathway disruption upon anabolic practices in bovine. Metabolomics 11, 184–197 (2015). https://doi.org/10.1007/s11306-014-0685-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11306-014-0685-3

Keywords

Search

Navigation