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Peter James

Peter James

Professor

Peter James

Targeted proteomics for the indirect detection of dexamethasone treatment in bovines

Author

  • Roberto Stella
  • Federica Barrucci
  • Roberto Angeletti
  • Peter James
  • Clara Montesissa
  • Giancarlo Biancotto

Summary, in English

The illegal use of pharmacologically active compounds for growth promotion in food-producing species poses risks for consumer health and animal welfare. Surveillance relies on the quantification of drug residues in animal fluids or tissues, but the efficacy can be negatively affected due to undetectable residual concentrations in biological matrices. Consequently, techniques focusing on the indirect biological effects of exogenous compound administration have been proposed as more sensitive detection methods. The purpose of the present study is to develop a tandem mass spectrometry analytical method based on low-energy collision-induced dissociation (CID-MS/MS) using multiple reaction monitoring (MRM) for the quantification of 12 potential protein markers of skeletal muscle to detect anabolic treatments with dexamethasone. Protein markers identified in a previous study applying a 2D-DIGE proteomics approach have been quantified using the signature peptide method. A group of proteins were confirmed as reliable markers. Quantitative results enabled a predictive model to be defined based on logistic regression for the detection of treated animals. The developed model was finally cross-validated in an independent animal set. [Figure not available: see fulltext.]

Department/s

  • Department of Immunotechnology

Publishing year

2016-11

Language

English

Pages

8343-8353

Publication/Series

Analytical and Bioanalytical Chemistry

Volume

408

Issue

29

Document type

Journal article

Publisher

Springer

Topic

  • Analytical Chemistry
  • Pharmaceutical Sciences

Keywords

  • Absolute quantification
  • Bovine
  • Dexamethasone
  • Illegal treatments
  • Multiple reaction monitoring
  • Protein markers

Status

Published

ISBN/ISSN/Other

  • ISSN: 1618-2642