Literature DB >> 19298887

Identification of potential gene expression biomarkers for the surveillance of anabolic agents in bovine blood cells.

Irmgard Riedmaier1, Ales Tichopad, Martina Reiter, Michael W Pfaffl, Heinrich H D Meyer.   

Abstract

In the EU, the use of anabolic steroids in food producing animals has been forbidden since 1988. The routine methods used in practice are based on the detection of hormonal residues. To overcome these routine methods, growth-promoting agents are sometimes administered at concentrations below the detection limit and new anabolic substances are designed. Therefore, new monitoring systems are needed to overcome the misuse of anabolic agents in meat production. In this study, a new monitoring system was applied: the quantification of mRNA gene expression changes by quantitative real time reverse transcription polymerase chain reaction (qRT-PCR). Blood was selected as ideal tissue for biomarker screening. From the literature, it is known that steroid hormones affect mRNA gene expression of the different blood cells, which can easily be taken from the living animal. In an animal trial, 18 Nguni heifers were separated to two groups of nine animals. One group served as untreated control and the other group was treated with a combination of trenbolone acetate plus estradiol for 39 days in order to allow the detection of the effect on mRNA expression in blood at three time points. Candidate genes used for developing a biomarker pattern were chosen by screening the actual literature for anabolic effects on blood cells. It could be demonstrated that the combination of trenbolone acetate plus estradiol significantly influences mRNA expression of the steroid receptors (ER-alpha and GR-alpha), the apoptosis regulator Fas, the proinflammatory interleukins IL-1alpha, IL-1beta and IL-6 and of MHCII, CK, MTPN, RBM5 and Actin-beta. Advanced statistical analysis by Principal Components Analysis (PCA) indicated that these genes represent potential biomarkers for this hormone combination in whole blood.

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Year:  2009        PMID: 19298887     DOI: 10.1016/j.aca.2009.02.014

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  6 in total

1.  Feasibility of a liver transcriptomics approach to assess bovine treatment with the prohormone dehydroepiandrosterone (DHEA).

Authors:  Jeroen C W Rijk; Ad A C M Peijnenburg; Peter J M Hendriksen; Johan M Van Hende; Maria J Groot; Michel W F Nielen
Journal:  BMC Vet Res       Date:  2010-09-16       Impact factor: 2.741

2.  Identification of transcriptional biomarkers by RNA-sequencing for improved detection of β2-agonists abuse in goat skeletal muscle.

Authors:  Luyao Zhao; Shuming Yang; Yongyou Cheng; Can Hou; Xinyong You; Jie Zhao; Ying Zhang; Wenjing He
Journal:  PLoS One       Date:  2017-07-26       Impact factor: 3.240

3.  New surveillance concepts in food safety in meat producing animals: the advantage of high throughput 'omics' technologies - A review.

Authors:  Michael W Pfaffl; Irmgard Riedmaier-Sprenzel
Journal:  Asian-Australas J Anim Sci       Date:  2018-05-31       Impact factor: 2.509

4.  Tracing recombinant bovine somatotropin ab(use) through transcriptomics: the potential of bovine somatic cells in a multi-dose longitudinal study.

Authors:  Alexandre Lamas; Patricia Regal; Beatriz Vázquez; José Manuel Miranda; Alberto Cepeda; Carlos Manuel Franco
Journal:  Sci Rep       Date:  2019-03-18       Impact factor: 4.379

5.  Transcriptomic markers meet the real world: finding diagnostic signatures of corticosteroid treatment in commercial beef samples.

Authors:  Sara Pegolo; Guglielmo Gallina; Clara Montesissa; Francesca Capolongo; Serena Ferraresso; Caterina Pellizzari; Lisa Poppi; Massimo Castagnaro; Luca Bargelloni
Journal:  BMC Vet Res       Date:  2012-10-30       Impact factor: 2.741

6.  Tracing Recombinant Bovine Somatotropin Ab(Use) Through Gene Expression in Blood, Hair Follicles, and Milk Somatic Cells: A Matrix Comparison.

Authors:  Alexandre Lamas; Patricia Regal; Beatriz Vazquez; José Manuel Miranda; Alberto Cepeda; Carlos Manuel Franco
Journal:  Molecules       Date:  2018-07-13       Impact factor: 4.411

  6 in total

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