Identification of a potential gene expression biomarker signature in bovine liver to detect the abuse of growth promoters

Influence of estradiol on bovine trophectoderm and uterine gene transcripts around maternal recognition of pregnancy†

Embryo survival and pregnancy success is increased among animals that exhibit estrus prior to fixed time-artificial insemination, but there are no differences in conceptus survival to d16. The objective of this study was to determine effects of preovulatory estradiol on uterine transcriptomes, select trophectoderm (TE) transcripts, and uterine luminal fluid proteins. Beef cows/heifers were synchronized, artificially inseminated (d0), and grouped into either high (highE2) or low (lowE2) preovulatory estradiol. Uteri were flushed (d16); conceptuses and endometrial biopsies (n = 29) were collected. RNA sequencing was performed on endometrium. Real-time polymerase chain reaction (RT-PCR) was performed on TE (n = 21) RNA to measure relative abundance of IFNT, PTGS2, TM4SF1, C3, FGFR2, and GAPDH. Uterine fluid was analyzed using 2D Liquid Chromatography with tandem mass spectrometry-based Isobaric tags for relative and absolute quantitation (iTRAQ) method. RT-PCR data were analyzed using the MIXED procedure in SAS. There were no differences in messenger RNA (mRNA) abundances in TE, but there were 432 differentially expressed genes (253 downregulated, 179 upregulated) in highE2/conceptus versus lowE2/conceptus groups. There were also 48 differentially expressed proteins (19 upregulated, 29 downregulated); 6 of these were differentially expressed (FDR < 0.10) at the mRNA level. Similar pathways for mRNA and proteins included: calcium signaling, protein kinase A signaling, and corticotropin-releasing hormone signaling. These differences in uterine function may be preparing the conceptus for improved likelihood of survival after d16 among highE2 animals.

On the trail of blood doping-microRNA fingerprints to monitor autologous blood transfusions in vivo

Autologous blood doping refers to the illegal re-transfusion of any quantities of blood or blood components with blood donor and recipient being the same person. The re-transfusion of stored erythrocyte concentrates is particularly attractive to high-performance athletes as this practice improves their oxygen capacity excessively. However, there is still no reliable detection method available. Analyzing circulating microRNA profiles of human subjects that underwent monitored autologous blood transfusions seems to be a highly promising approach to develop novel biomarkers for autologous blood doping. In this exploratory study, we randomly divided 30 healthy males into two different treatment groups and one control group and sampled whole blood at several time points at baseline, after whole blood donation and after transfusion of erythrocyte concentrates. Hematological variables were recorded and analyzed following the adaptive model of the Athlete Biological Passport. microRNA profiles were examined by small RNA sequencing and comprehensive multivariate data analyses, revealing microRNA fingerprints that reflect the sampling time point and transfusion volume. Neither individual microRNAs nor a signature of transfusion-dependent microRNAs reached superior sensitivity at 100% specificity compared to the Athlete Biological Passport (≤11% 6 h after transfusion versus ≤44% 2 days after transfusion). However, the window of autologous blood doping detection was different. Due to the heterogenous nature of doping, with athletes frequently combining multiple medications in order to both gain a competitive advantage and interfere with known testing methods, the true applicability of the molecular signature remains to be validated in real anti-doping testings.

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

In the European Union, the use of recombinant bovine somatotropin (rbST) in dairy cattle is forbidden. Monitoring rbST (ab)use by its direct detection in animal matrices still remains a challenging task. New monitoring methods based on indirect detection of the substance are necessary. A new transcriptomic system based on the use of high-throughput real-time PCR in combination with somatic cells was developed to control rbST administration in dairy animals. A total of nine cows, separated into control and rbST-treated groups, were included in the study. A subcutaneous injection containing 500 mg of rbST was administered to the treated group every 14 days, up to a total of 12 doses. Milk somatic cells (MSCs) were sampled from each animal at different time points throughout 8 months of study. It was possible to obtain the transcriptomic profile of 18 genes in MSCs of rbST-treated and control groups, and using univariate and multivariate statistical analysis control and treated animals were discriminated. The transcription of CCND1, IGF-1R, TNF and IL-1β genes resulted strongly influenced by rbST treatment. The combination of MSCs, transcriptomic tools and statistical analysis has allowed the selection of four genes as potential biomarkers that could be used in a transcriptomic panel for monitoring rbST administration in cows.

Discovery of potential transcriptional biomarkers in broiler chicken for detection of amantadine abuse based on RNA sequencing technology

The aim of this study was to identify candidate transcriptional biomarkers so as to provide a new method for monitoring amantadine residues during the feeding of broiler chicken. RNA sequencing (RNA-seq) and bioinformatic analyses were conducted to examine the transcriptomic changes and screen differentially expressed genes (DEGs) in broiler chicken breast muscle and liver tissues treated with amantadine. The results indicated that a total of 170 DEGs were screened from broiler chicken breast muscle tissues after amantadine was fed. Among the genes, 120 were up-regulated and 50 were down-regulated. The gene ontology (GO) terms for these genes mainly existed in the areas of hydrolase activity, immune reaction and chemokine activity. The significantly enriched pathways in the Kyoto Encyclopedia for Genes and Genomes (KEGG) were in phagosomes, cell adhesion molecules (CAMs), lysosomes and extracellular matrix (ECM) receptors. From the broiler chicken liver tissues, 172 DEGs were screened, among which 116 were up-regulated and 56 were down-regulated. The GO terms of these DEGs were related to functions such as catalytic activities, metabolic activities, oxidation-reduction activities, immune reactions and cofactor binding. The significantly enriched KEGG pathways existed in metabolism, CAM, ECM receptor reaction and drug metabolism-cytochrome P450. According to the fold-change (FC), significance levels, functional annotations and possible biological processes of DEGs, 11 and 9 candidate DEGs related to amantadine treatment were further screened from broiler chicken breast muscle and liver tissues, respectively. In addition, the quantitative real-time polymerase chain reaction (qRT-PCR) verification showed exactly concordant results with the RNA-seq data. Principal components analysis (PCA) on the qRT-PCR data resulted in the separation of treated samples from the control samples in both tissues. The results provided a basis for identification of transcriptional biomarkers for detecting amantadine residues in broiler chicken breast muscle and liver tissues.

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

The use of recombinant bovine somatotropin (rbST) in dairy cattle is forbidden in the European Union. Due to the very low circulating concentration of rbST in treated animals, its direct detection is still a challenge. Therefore, the use of indirect methods to detect the ab(use) of rbST in dairy cattle appears as a good alternative. In the past few years, gene expression demonstrated its utility in screening the use of illicit substances in both humans and animals. In this study, a comparison of three types of matrices (milk somatic cells, blood, and hair follicles) was carried out to evaluate their potential use for routine control of rbST using 15 gene-expression profiles. A total of six rbST-treated cows and three control cows were included in the study. A subcutaneous injection containing 500 mg of rbST was administered to the treated group. Samples of the three matrices were collected before rbST administration, and at three and nine days after treatment. The quality of RNA extracted was higher in the blood and hair-follicle samples than in the milk somatic cells. In the three matrices, there were significant differences in the expression of some genes, with milk somatic cells and blood presenting the the best matrices. On this note, the cyclin D1 (CCND1), interleukin 1 beta (IL-1β), tumor necrosis factor (TNF), and insulin-like growth factor 1 receptor (IGF-1R) genes showed potential as biomarkers of rbST treatment. Therefore, blood, somatic cells, and follicle hair should be considered as promising sources of RNA, and can be used in gene-expression assays to routinely control the illicit use of rbST.

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

The misuse of anabolic hormones or illegal drugs is a ubiquitous problem in animal husbandry and in food safety. The ban on growth promotants in food producing animals in the European Union is well controlled. However, application regimens that are difficult to detect persist, including newly designed anabolic drugs and complex hormone cocktails. Therefore identification of molecular endogenous biomarkers which are based on the physiological response after the illicit treatment has become a focus of detection methods. The analysis of the ‘transcriptome’ has been shown to have promise to discover the misuse of anabolic drugs, by indirect detection of their pharmacological action in organs or selected tissues. Various studies have measured gene expression changes after illegal drug or hormone application. So-called transcriptomic biomarkers were quantified at the mRNA and/or microRNA level by reverse transcription-quantitative polymerase chain reaction (RT-qPCR) technology or by more modern ‘omics’ and high throughput technologies including RNA-sequencing (RNA-Seq). With the addition of advanced bioinformatical approaches such as hierarchical clustering analysis or dynamic principal components analysis, a valid ‘biomarker signature’ can be established to discriminate between treated and untreated individuals. It has been shown in numerous animal and cell culture studies, that identification of treated animals is possible via our transcriptional biomarker approach. The high throughput sequencing approach is also capable of discovering new biomarker candidates and, in combination with quantitative RT-qPCR, validation and confirmation of biomarkers has been possible. These results from animal production and food safety studies demonstrate that analysis of the transcriptome has high potential as a new screening method using transcriptional ‘biomarker signatures’ based on the physiological response triggered by illegal substances.

Applicability of an innovative steroid-profiling method to determine synthetic growth promoter abuse in cattle

A robust LC-MS/MS method was developed to quantify a large number of phase I and phase II steroids in urine. The decision limit is for most compounds lower than 1ngml^-1 with a measurement uncertainty smaller than 30%. The method is fully validated and was applied to assess the influence of administered synthetic steroids and beta-agonists on the steroidogenesis. From three animal experiments, clenbuterol, diethylstilbestrol and stanozolol, the steroid profiles in urine of bovine animals were compared before and after treatment. It was demonstrated that the steroid profiles were altered due to these treatments. A predictive multivariate model was built to identify deviations from normal population steroid profiles. The abuse of synthetic steroids can be detected in urine samples from bovine animals using this model. The samples from the animal experiments were randomly analysed using this method and predictive model. It was shown that these samples were predicted correctly in the exogenous steroids group.

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

In this paper, high-throughput RNA-sequencing (RNA-seq) was used to search for transcriptional biomarkers for β₂-agonists. In combination with drug mechanisms, a smaller group of genes with higher detection accuracy was screened out. Unknown samples were first predicted by this group of genes, and liquid chromatograph tandem mass spectrometer (LC-MS/MS) was applied to positive samples to validate the biomarkers. The results of principal component analysis (PCA), hierarchical cluster analysis (HCA) and discriminant analysis (DA) indicated that the eight genes screened by high-throughput RNA-seq were able to distinguish samples in the experimental group and control group. Compared with the nine genes selected from an earlier literature, 17 genes including these nine genes were proven to have a more satisfactory effect, which validated the accuracy of gene selection by RNA-seq. Then, six key genes were selected from the 17 genes according to the variable importance in projection (VIP) value of greater than 1. The test results using the six genes and 17 genes were similar, revealing that the six genes were critical genes. By using the six genes, three positive samples possibly treated with drugs were screened out from 25 unknown samples through DA and partial least squares discriminant analysis (PLS-DA). Then, the three samples were verified by a standard method, and mapenterol was detected in a sample. Therefore, the six genes can be used as biomarkers to detect β₂-agonists. Compared with the previous study, accurate detection of β₂-agonists abuse using six key genes is an improvement method, which show great significance in the monitoring of β₂-agonists abuse in animal husbandry.

New Analytical Tool for the Detection of Ractopamine Abuse in Goat Skeletal Muscle by Potential Gene Expression Biomarkers

In this study, quantification of mRNA gene expression was examined as biomarkers to detect ractopamaine abuse and ractopamaine residues in cashmere goats. It was focused on the identification of potential gene expression biomarkers and describing the coreletionship between gene expression and residue level by 58 animals for 49 days. The results showed that administration periods and residue levels significantly influenced mRNA expressions of the β2-adrenergic receptor (β2AR), the enzymes PRKACB, ADCY3, ATP1A3, ATP2A3, PTH, and MYLK, and the immune factors IL-1β and TNF-α. Statistical analysis like principal components analysis (PCA), hierarchical cluster analysis (HCA), and discriminant analysis (DA) showed that these genes can serve as potential biomarkers for ractopamine in skeletal muscle and that they are also suitable for describing different residue levels separately.

The potential of circulating extracellular small RNAs (smexRNA) in veterinary diagnostics-Identifying biomarker signatures by multivariate data analysis

Worldwide growth and performance-enhancing substances are used in cattle husbandry to increase productivity. In certain countries however e.g., in the EU, these practices are forbidden to prevent the consumers from potential health risks of substance residues in food. To maximize economic profit, ‘black sheep‘ among farmers might circumvent the detection methods used in routine controls, which highlights the need for an innovative and reliable detection method. Transcriptomics is a promising new approach in the discovery of veterinary medicine biomarkers and also a missing puzzle piece, as up to date, metabolomics and proteomics are paramount. Due to increased stability and easy sampling, circulating extracellular small RNAs (smexRNAs) in bovine plasma were small RNA-sequenced and their potential to serve as biomarker candidates was evaluated using multivariate data analysis tools.

After running the data evaluation pipeline, the proportion of miRNAs (microRNAs) and piRNAs (PIWI-interacting small non-coding RNAs) on the total sequenced reads was calculated. Additionally, top 10 signatures were compared which revealed that the readcount data sets were highly affected by the most abundant miRNA and piRNA profiles. To evaluate the discriminative power of multivariate data analyses to identify animals after veterinary drug application on the basis of smexRNAs, OPLS-DA was performed. In summary, the quality of miRNA models using all mapped reads for both treatment groups (animals treated with steroid hormones or the β-agonist clenbuterol) is predominant to those generated with combined data sets or piRNAs alone. Using multivariate projection methodologies like OPLS-DA have proven the best potential to generate discriminative miRNA models, supported by small RNA-Seq data. Based on the presented comparative OPLS-DA, miRNAs are the favorable smexRNA biomarker candidates in the research field of veterinary drug abuse.