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Peter James

Peter James

Professor

Peter James

Proteomics for the detection of indirect markers of steroids treatment in bovine muscle

Author

  • Roberto Stella
  • Giancarlo Biancotto
  • Giorgio Arrigoni
  • Federica Barrucci
  • Roberto Angeletti
  • Peter James

Summary, in English

Despite the ban by the European Union, anabolic steroids might still be illicitly employed in bovine meat production. The surveillance of misuse of such potentially harmful molecules is necessary to guarantee consumers' health. Analytical methods for drug residue control are based on LC-MS/MS, but their efficacy can be hindered due to undetectable residual concentrations as a result of low-dosage treatments. Screening methods based on the recognition of indirect biological effects of growth promoters' administration, such as the alteration of protein expression, can improve the efficacy of surveillance. The present study was aimed at identifying modifications in the muscle protein expression pattern between bulls treated with an ear implant (Revalor-XS (R)) containing trenbolone acetate (200 mg) and estradiol (40 mg), and untreated animals. The analysis of skeletal muscle was carried out using a tandem mass tags shotgun proteomics approach. We defined 28 candidate protein markers with a significantly altered expression induced by steroids administration. A subset of 18 candidate markers was validated by SRM and allowed to build a predictive model based on partial least square discriminant analysis. Our findings confirm the effectiveness of the proteomics approach as potential tool to overcome analytical limitations of drug residue monitoring.

Department/s

  • Department of Immunotechnology

Publishing year

2015

Language

English

Pages

2332-2341

Publication/Series

Proteomics

Volume

15

Issue

13

Document type

Journal article

Publisher

John Wiley & Sons Inc.

Topic

  • Medical Biotechnology

Keywords

  • Animal proteomics
  • Bovine
  • Illicit treatments
  • Selected-reaction
  • monitoring
  • Steroids
  • Tandem mass tag quantification

Status

Published

ISBN/ISSN/Other

  • ISSN: 1615-9861