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Targeted proteomics for the indirect detection of dexamethasone treatment in bovines

Stella, Roberto; Barrucci, Federica; Angeletti, Roberto; James, Peter LU ; Montesissa, Clara and Biancotto, Giancarlo (2016) In Analytical and Bioanalytical Chemistry 408(29). p.8343-8353
Abstract

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... (More)

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.]

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Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Absolute quantification, Bovine, Dexamethasone, Illegal treatments, Multiple reaction monitoring, Protein markers
in
Analytical and Bioanalytical Chemistry
volume
408
issue
29
pages
8343 - 8353
publisher
Springer
external identifiers
  • scopus:84989184601
  • wos:000388736700009
ISSN
1618-2642
DOI
10.1007/s00216-016-9951-8
language
English
LU publication?
yes
id
2c182294-179d-4fdf-a2ae-8e5bc0c4062f
date added to LUP
2016-10-31 08:31:45
date last changed
2017-09-18 11:28:43
@article{2c182294-179d-4fdf-a2ae-8e5bc0c4062f,
  abstract     = {<p>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.]</p>},
  author       = {Stella, Roberto and Barrucci, Federica and Angeletti, Roberto and James, Peter and Montesissa, Clara and Biancotto, Giancarlo},
  issn         = {1618-2642},
  keyword      = {Absolute quantification,Bovine,Dexamethasone,Illegal treatments,Multiple reaction monitoring,Protein markers},
  language     = {eng},
  number       = {29},
  pages        = {8343--8353},
  publisher    = {Springer},
  series       = {Analytical and Bioanalytical Chemistry},
  title        = {Targeted proteomics for the indirect detection of dexamethasone treatment in bovines},
  url          = {http://dx.doi.org/10.1007/s00216-016-9951-8},
  volume       = {408},
  year         = {2016},
}