Assessment of two complementary liquid chromatography coupled to high resolution mass spectrometry metabolomics strategies for the screening of anabolic steroid treatment in calves

Innovative molecular networking analysis of steroids and characterisation of the urinary steroidome

Steroids are cholesterol-derived biomolecules that play an essential role in biological processes. These substances used as growth promoters in animals are strictly regulated worldwide. Targeted assays are the conventional methods of monitoring steroid abuse, with limitations: only detect known metabolites. Metabolism leads to many potential compounds (isomers), which complicates the analysis. Thus, to overcome these limitations, non-targeted analysis offers new opportunities for a deeper understanding of metabolites related to steroid metabolism. Molecular networking (MN) appears to be an innovative strategy combining high-resolution mass spectrometry and specific data processing to study metabolic pathways. In the present study, two databases and networks of steroids were constructed to lay the foundations for the implementation of the GNPS-MN approach. Steroids of the same family were grouped together, nandrolone and testosterone were linked to other analogues. This network and associated database were then applied to a few urine samples in order to demonstrate the annotation capacity in steroidome study. The results show that MN strategy could be used to study steroid metabolism and highlight biomarkers.

Anabolic steroids in livestock production: Background and implications for chemical food safety

The use of steroids in livestock animals is a source of concern for consumers because of the risks associated with the presence of their residues in foodstuffs of animal origin. Technological advances such as mass spectrometry have made it possible to play a fundamental role in controlling such practices, firstly for the discovery of marker metabolites but also for the monitoring of these compounds under the regulatory framework. Current control strategies rely on the monitoring of either the parent drug or its metabolites in various matrices of interest. As some of these steroids also have an endogenous status specific strategies have to be applied for control purposes. This review aims to provide a comprehensive and up-to-date knowledge of analytical strategies, whether targeted or non-targeted, and whether they focus on markers of exposure or effect in the specific context of chemical food safety regarding the use of anabolic steroids in livestock. The role of new approaches in data acquisition (e.g. ion mobility), processing and analysis, (e.g. molecular networking), is also discussed.

From sound check to encore: A journey through high-resolution mass spectrometry-based food analyses and metabolomics

This manuscript presents a comprehensive review of high-resolution mass spectrometry in the field of food analysis and metabolomics. We have followed the historical evolution of metabolomics, its associated techniques and technologies, and its increasing role in food science and research. The review provides a critical comparison and synthesis of tentative identification guidelines proposed for over 15 years, offering a condensed resource for researchers in the field. We have also examined a wide range of recent metabolomics studies, showcasing various methodologies and highlighting key findings as a testimony of the versatility of the field and the possibilities it offers. In doing so, we have also carefully provided a compilation of the software tools that may be employed in this type of studies. The manuscript also explores the prospects of high-resolution mass spectrometry and metabolomics in food science. By covering the history, guidelines, applications, and tools of metabolomics, this review attempts to become a comprehensive guide for researchers in a rapidly evolving field.

Nandrolone and estradiol biomarkers identification in bovine urine applying a liquid chromatography high-resolution mass spectrometry metabolomics approach

With the aim of specifically investigating patterns associated with three steroid treatments (17β-nandrolone, 17β-estradiol, and 17β-nandrolone + 17β-estradiol) in bovine, an reversed phase liquid chromatography (RPLC)-electrospray ionization (ESI)(+/-)-high-resolution mass spectrometry (HRMS) study was conducted to characterize the urinary profiles of involved animals. Although specific fingerprints with strong differences could be highlighted between urinary metabolite profiles within urine samples collected on control and treated animals, it appeared further that significant discriminations could also be observed between steroid treatments, evidencing thus specific patterns and candidate biomarkers associated to each treatment. An MS-2 structural elucidation step enabled level-1 identification of two biomarkers mainly involved in energy pathways, in relation to skeletal muscle functioning. These results make it possible to envisage a global strategy for the detection of anabolic practices involving steroids, while at the same time providing clues as to the compounds used, which would facilitate the confirmation stage to follow.

Extending the Lipidome Coverage by Combining Different Mass Spectrometric Platforms: An Innovative Strategy to Answer Chemical Food Safety Issues

From a general public health perspective, a strategy combining non-targeted and targeted lipidomics MS-based approaches is proposed to identify disrupted patterns in serum lipidome upon growth promoter treatment in pigs. Evaluating the relative contributions of the platforms involved, the study aims at investigating the potential of innovative analytical approaches to highlight potential chemical food safety threats. Serum samples collected during an animal experiment involving control and treated pigs, whose food had been supplemented with ractopamine, were extracted and characterised using three MS strategies: Non-targeted RP LC-HRMS; the targeted Lipidyzer™ platform (differential ion mobility associated with shotgun lipidomics) and a homemade LC-HRMS triglyceride platform. The strategy enabled highlighting specific lipid profile patterns involving various lipid classes, mainly in relation to cholesterol esters, sphingomyelins, lactosylceramide, phosphatidylcholines and triglycerides. Thanks to the combination of non-targeted and targeted MS approaches, various compartments of the pig serum lipidome could be explored, including commonly characterised lipids (Lipidyzer™), triglyceride isomers (Triglyceride platform) and unique lipid features (non-targeted LC-HRMS). Thanks to their respective characteristics, the complementarity of the three tools could be demonstrated for public health purposes, with enhanced coverage, level of characterization and applicability.

Applying metabolomics to veterinary pharmacology and therapeutics

Metabolomics is the large-scale study of low-molecular-weight substances in a biological system in a given physiological state at a given time point. Metabolomics can be applied to identify predictors of inter-individual variability in drug response, provide clinicians with data useful for decision-making processes in drug selection, and inform about the pharmacokinetics and pharmacodynamics of a drug. It is, therefore, an exceptional approach for gaining new understanding effects in the field of comparative veterinary pharmacology. However, the incorporation of metabolomics into veterinary pharmacology and toxicology is not yet widespread, and this is probably, at least in part, a result of its highly multidisciplinary nature. This article reviews the potential applications of metabolomics in veterinary pharmacology and therapeutics. It integrates key concepts for designing metabolomics studies and analyzing and interpreting metabolomics data, providing solid foundations for applying metabolomics to the study of drugs in all veterinary species.

Comprehensive Metabolomics Analysis of Nontargeted LC-HRMS Data Provides Valuable Insights Regarding the Origin of Veterinary Drug Residues

Liquid chromatography coupled with high resolution mass spectrometry (LC-HRMS) complements standard triple-quadrupole mass spectrometry in veterinary drug residue control. LC-HRMS offers the opportunity for nontargeted screening for metabolites and biomarkers representing metabolic changes. In this work, the feasibility of a nontargeted metabolomics approach based on LC-HRMS data (LC-Q-Orbitrap and LC-Q-TOF) to distinguish between porcine muscle tissue from infected animals and from healthy animals is demonstrated. The differences arise from various compounds associated with metabolic changes in infected animals. Two new biomarker candidates have been identified: tripeptide prolyphenylalanylglycine and a lysophosphatidylcholine derivative. For the first time, a bivariate data analysis procedure is described that may be used to evaluate whether the presence of antibiotic residues points to a therapeutic application or may be the result of a contamination during sampling and/or analysis.

Making complex measurements of meat composition fast: Application of rapid evaporative ionisation mass spectrometry to measuring meat quality and fraud

Increasing demands are being placed on meat producers to verify more about their product with regards to safety, quality and authenticity. There are many methods that can detect aspects of these parameters in meat, yet most are too slow to keep up with the demands of modern meat processing plants and supply chains. A new technology, Rapid Evaporative Ionisation Mass Spectrometry (REIMS), has the potential to bridge the gap between advanced laboratory measurements and technology that can screen for quality, safety and authenticity parameters in a single measurement. Analysis with REIMS generates a detailed mass spectral fingerprint representative of a meat sample without the need for sample processing. REIMS has successfully been used to detect species fraud, detect use of hormones in meat animals, monitor meat processing and to detect off flavours such as boar taint. The aim of this review is to summarize these and other applications to highlight the potential of REIMS for meat analysis. Sampling methods and important considerations for data analysis are discussed as well as limitations of the technology and remaining challenges for practical adoption.

Profiling of Metabolomic Changes in Plasma and Urine of Pigs Caused by Illegal Administration of Testosterone Esters

The use of anabolic steroid hormones as growth promoters in feed for farm animals has been banned in the European Union since 1988 on the basis of Council Directive 96/22/EC. However, there is still ongoing monitoring and reporting of positive findings of these banned substances in EU countries. The aim of this work was to investigate the efficacy and discriminatory ability of metabolic fingerprinting after the administration of 17β-testosterone esters to pigs. Plasma and urine samples were chromatographically separated on a Hypersil Gold C18 column. High resolution mass spectrometry metabolomic fingerprints were analysed on a hybrid mass spectrometer Q-Exactive. Three independent multivariate statistical methods, namely principal component analysis, clustre analysis, and orthogonal partial least squares discriminant analysis showed significant differences between the treated and control groups of pigs even 14 days after the administration of the hormonal drug. Plasma samples were also analysed by a conventional quantitative analysis using liquid chromatography with tandem mass spectrometry and a pharmacokinetic curve was constructed based on the results. In this case, no testosterone residue was detected 14 days after the administration. The results clearly showed that a metabolomics approach can be a useful and effective tool for the detection and monitoring of banned anabolic steroids used illegally in pig fattening.

Comprehensive steroid profiling by liquid chromatography coupled to high resolution mass spectrometry

A steroidomics workflow has been developed in the objective of monitoring a wide range (n >150) of steroids in urine. The proposed workflow relies on the optimization of an adequate SPE extraction step followed by an UHPLC-HRMS/MS simultaneous analysis of both free and conjugated forms of C18, C19 and C21 steroid hormones. On the basis of 44 selected steroids, representative of main classes of steroids constituting the steroidome, the performances of the developed workflow were evaluated in terms of selectivity, repeatability (< 13%) and linearity (R2> 0.985 in the concentration range [0.01-10 ng/mL]). As metabolites identification and characterization constitute the bottleneck of such profiling approaches, a homemade database was created encompassing a large number of characterized free and conjugated steroids (n> 150) for putative steroid-like biomarkers identification purposes. The efficiency of the workflow in highlighting fine modifications within the urinary steroidome was assessed in the frame of an anabolic treatment involving an intra-muscular administration of boldenone undecylenate (2 mg/kg) to veals (n=6) and the investigation of potential steroid biomarkers. Besides monitoring known phase II metabolites of boldenone in the bovine specie, namely, boldenone glucuronide and sulfate, the applied strategy also permitted to observe, upon boldenone administration, a modified profile of epiboldenone glucuronide. Furthermore, 31 signals corresponding to non-identified steroid species could also be highlighted as impacted upon the exogenous steroid treatment. This study is the first to simultaneously investigate both free and conjugated C18, C19 and C21 steroid hormones in their native form using UHPLC-HRMS/MS and allowing their comprehensive profiling. This strategy was probed in-vivo.

Discovery of urinary biomarkers to discriminate between exogenous and semi-endogenous thiouracil in cattle: A parallel-like randomized design

In the European Union, the use of thyreostats for animal fattening purposes has been banned and monitoring plans have been established to detect potential abuse. However, this is not always straightforward as thyreostats such as thiouracil may also have a semi-endogenous origin. Therefore, this study aimed at defining urinary metabolites, which may aid in defining the origin of detected thiouracil. Hereto, a parallel-like randomized in vivo study was conducted in which calves (n = 8) and cows (n = 8) were subjected to either a control treatment, rapeseed-enriched diet to induce semi-endogenous formation, or thiouracil treatment. Urine samples (n = 330) were assessed through metabolic fingerprinting, employing liquid-chromatography and Q-Exactive^TM Orbitrap mass spectrometry. Urinary fingerprints comprised up to 40,000 features whereby multivariate discriminant analysis was able to point out significant metabolome differences between treatments (Q²(Y) ≥ 0.873). Using the validated models, a total of twelve metabolites (including thiouracil) were assigned marker potential. Combining these markers into age-dependent biomarker panels rendered a tool by which sample classification could be improved in comparison with thiouracil-based thresholds, and this during on-going thiouracil treatment (specificities ≥ 95.2% and sensitivities ≥ 85.7%), post-treatment (sensitivities ≥ 80% for ≥ 24 h after last administration), and simulated low-dose thiouracil treatment (exogenous thiouracil below 30 ng μL^-1). Moreover, the metabolic relevance of revealed markers was supported by the suggested identities, for which a structural link with thiouracil could be determined in most cases. The proposed biomarker panels may contribute to a more justified decision-making in monitoring thiouracil abuse.

Traumatic Brain Injury Alters the Metabolism and Facilitates Alzheimer's Disease in a Murine Model

A majority of Alzheimer's disease (AD) cases are sporadic without known cause. People who suffered from traumatic brain injury (TBI) are more likely to develop neurodegeneration and cognitive impairments. However, the role of TBI in pathophysiology of AD remains elusive. The present study intended to explore the effect of TBI on metabolism and its role in AD pathogenesis. We subjected double transgenic AD model mice APP23/PS45 to TBI. We found that TBI promoted β-secretase cleavage of amyloid β precursor protein and amyloid β protein deposition, and exuberated the cognitive impairments in AD mouse models. ¹H nuclear magnetic resonance (¹H-NMR)-based metabolomics with multivariate analysis was performed to investigate the characteristic metabolites and the related metabolic pathways in the serum and urine samples of the mice. TBI affected the metabolic patterns, methylamine metabolism, and amino acid metabolism in serum samples. Urinary metabolites showed that glycolysis and the tricarboxylic acid (TCA) cycle were perturbed. The results indicate that TBI might facilitate Alzheimer's pathogenesis by altering metabolism and inducing mitochondrial dysfunction. The study suggests that metabolite changes could also serve as biomarkers for TBI-induced neurodegeneration.

Told through the wine: A liquid chromatography-mass spectrometry interplatform comparison reveals the influence of the global approach on the final annotated metabolites in non-targeted metabolomics

This work focuses on the influence of the selected LC-HRMS platform on the final annotated compounds in non-targeted metabolomics. Two platforms that differed in columns, mobile phases, gradients, chromatographs, mass spectrometers (Orbitrap [Platform#1] and Q-TOF [Platform#2]), data processing and marker selection protocols were compared. A total of 42 wines samples from three different protected denomination of origin (PDO) were analyzed. At the feature level, good (O)PLS-DA models were obtained for both platforms (Q(2)[Platform#1]=0.89, 0.83 and 0.72; Q(2)[Platform#2]=0.86, 0.86 and 0.77 for Penedes, Ribera del Duero and Rioja wines respectively) with 100% correctly classified samples in all cases. At the annotated metabolite level, platforms proposed 9 and 8 annotated metabolites respectively which were identified by matching standards or the MS/MS spectra of the compounds. At this stage, there was no coincidence among platforms regarding the suggested metabolites. When screened on the raw data, 6 and 5 of these compounds were detected on the other platform with a similar trend. Some of the detected metabolites showed complimentary information when integrated on biological pathways. Through the use of some examples at the annotated metabolite level, possible explanations of this initial divergence on the results are presented. This work shows the complications that may arise on the comparison of non-targeted metabolomics platforms even when metabolite focused approaches are used in the identification.

Sample normalization methods in quantitative metabolomics

To reveal metabolomic changes caused by a biological event in quantitative metabolomics, it is critical to use an analytical tool that can perform accurate and precise quantification to examine the true concentration differences of individual metabolites found in different samples. A number of steps are involved in metabolomic analysis including pre-analytical work (e.g., sample collection and storage), analytical work (e.g., sample analysis) and data analysis (e.g., feature extraction and quantification). Each one of them can influence the quantitative results significantly and thus should be performed with great care. Among them, the total sample amount or concentration of metabolites can be significantly different from one sample to another. Thus, it is critical to reduce or eliminate the effect of total sample amount variation on quantification of individual metabolites. In this review, we describe the importance of sample normalization in the analytical workflow with a focus on mass spectrometry (MS)-based platforms, discuss a number of methods recently reported in the literature and comment on their applicability in real world metabolomics applications. Sample normalization has been sometimes ignored in metabolomics, partially due to the lack of a convenient means of performing sample normalization. We show that several methods are now available and sample normalization should be performed in quantitative metabolomics where the analyzed samples have significant variations in total sample amounts.

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.

Evaluation of the discriminative potential of a novel biomarker for estradiol treatments in bovine animals

The endogenous occurrence of natural hormones obstructs the application of classical targeted methods as confirmatory options. In the case of estradiol, the ultimate confirmation of its exogenous administration relies on gas chromatography coupled to combustion/isotope ratio mass spectrometry (GC-C/IRMS). A serum dipeptide composed of pyroglutamic acid and phenylalanine was identified as a potential biomarker of estradiol treatments in adult cows. To evaluate its potential to pinpoint suspicious samples, samples from prepubertal females under different estrogenic treatments have been analyzed. The results confirmed the up-regulation of the dipeptide in adult bovines. The 2-week-old females exhibited short-lasting responses only in a few animals. The 6-month-old female showed a delayed but clear increase on the biomarker level. The composition of the anabolic preparations, the dose, and/or the administration route are possible additional reasons for the reduced response in young animals. A comparison to previous results reported by various researchers is included.

Potential of mass spectrometry metabolomics for chemical food safety

This review aims to describe the most significant applications of mass spectrometry-based metabolomics in the field of chemical food safety. A particular discussion of all the different analytical steps involved in the metabolomics workflow (sample preparation, mass spectrometry analytical platform and data processing) will be addressed.

Molecular effects of supraphysiological doses of doping agents on health

Supraphysiological doses of doping agents, such as T/DHT and GH/IGF-1, affect cellular pathways associated with apoptosis and inflammation.

Advances in the detection of designer steroids in anti-doping

The abuse of unknown designer androgenic anabolic steroids (AAS) is considered to be an issue of significant importance, as AAS are the choice of doping preference according to World Anti-doping Agency statistics. In addition, unknown designer AAS are preferred since the World Anti-doping Agency mass spectrometric identification criteria cannot be applied to unknown molecules. Consequently, cheating athletes have a strong motive to use designer AAS in order to both achieve performance enhancement and to escape from testing positive in anti-doping tests. To face the problem, a synergy is required between the anti-doping analytical science and sports anti-doping regulations. This Review examines various aspects of the designer AAS. First, the structural modifications of the already known AAS to create new designer molecules are explained. A list of the designer synthetic and endogenous AAS is then presented. Second, we discuss progress in the detection of designer AAS using: mass spectrometry and bioassays; analytical data processing of the unknown designer AAS; metabolite synthesis; and, long-term storage of urine and blood samples. Finally, the introduction of regulations from sports authorities as preventive measures for long-term storage and reprocessing of samples, initially reported as negatives, is discussed.

Basics of mass spectrometry based metabolomics

The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18).

Application of gas chromatography-mass spectrometry/combustion/isotope ratio mass spectrometry (GC-MS/C/IRMS) to detect the abuse of 17β-estradiol in cattle

Although the ability to differentiate between endogenous steroids and synthetic homologues on the basis of their (13)C/(12)C isotopic ratio has been known for over a decade, this technique has been scarcely implemented for food safety purposes. In this study, a method was developed using gas chromatography-mass spectrometry/combustion/isotope ratio mass spectrometry (GC-MS/C/IRMS) to demonstrate the abuse of 17β-estradiol in cattle, by comparison of the (13)C/(12)C ratios of the main metabolite 17α-estradiol and an endogenous reference compound (ERC), 5-androstene-3β,17α-diol, in bovine urine. The intermediate precisions were determined as 0.46 and 0.26‰ for 5-androstene-3β,17α-diol and 17α-estradiol, respectively. This is, to the authors' knowledge, the first reported use of GC-MS/C/IRMS for the analysis of steroid compounds for food safety issues.

Metabolomic profiling of in vivo plasma responses to dioxin-associated dietary contaminant exposure in rats: implications for identification of sources of animal and human exposure

Dioxin contamination of the food chain typically occurs when cocktails of combustion residues or polychlorinated biphenyl (PCB) containing oils become incorporated into animal feed. These highly toxic compounds are bioaccumulative with small amounts posing a major health risk. The ability to identify animal exposure to these compounds prior to their entry into the food chain may be an invaluable tool to safeguard public health. Dioxin-like compounds act by a common mode of action and this suggests that markers or patterns of response may facilitate identification of exposed animals. However, secondary co-contaminating compounds present in typical dioxin sources may affect responses to compounds. This study has investigated for the first time the potential of a metabolomics platform to distinguish between animals exposed to different sources of dioxin contamination through their diet. Sprague-Dawley rats were given feed containing dioxin-like toxins from hospital incinerator soot, a common PCB oil standard and pure 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) (normalized at 0.1 μg/kg TEQ) and acquired plasma was subsequently biochemically profiled using ultra high performance liquid chromatography (UPLC) quadropole time-of-flight-mass spectrometry (QTof-MS). An OPLS-DA model was generated from acquired metabolite fingerprints and validated which allowed classification of plasma from individual animals into the four dietary exposure study groups with a level of accuracy of 97-100%. A set of 24 ions of importance to the prediction model, and which had levels significantly altered between feeding groups, were positively identified as deriving from eight identifiable metabolites including lysophosphatidylcholine (16:0) and tyrosine. This study demonstrates the enormous potential of metabolomic-based profiling to provide a powerful and reliable tool for the detection of dioxin exposure in food-producing animals.

An integrated strategy for in vivo metabolite profiling using high-resolution mass spectrometry based data processing techniques

An ongoing challenge of drug metabolite profiling is to detect and identify unknown or low-level metabolites in complex biological matrices. Here we present a generic strategy for metabolite detection using multiple accurate-mass-based data processing tools via the analysis of rat samples of two model drug candidates, AZD6280 and AZ12488024. First, the function of isotopic pattern recognition was proved to be highly effective in the detection of metabolites derived from [(14)C]-AZD6280 that possesses a distinct isotopic pattern. The metabolites revealed using this approach were in excellent qualitative correlation to those observed in radiochromatograms. Second, the effectiveness of accurate mass based untargeted data mining tools such as background subtraction, mass defect filtering, or a data mining package (MZmine) used for metabolomic analysis in detection of metabolites of [(14)C]-AZ12488024 in rat urine, feces, bile and plasma samples was examined and a total of 33 metabolites of AZ12488024 were detected. Among them, at least 16 metabolites were only detected by the aid of the data mining packages and not via radiochromatograms. New metabolic pathways such as S-oxidation and thiomethylation reactions occurring on the thiazole ring were proposed based on the processed data. The results of these experiments also demonstrated that accurate mass-based mass defect filtering (MDF) and data mining techniques used in metabolomics are complementary and can be valuable tools for delineating low-level metabolites in complex matrices. Furthermore, the application of distinct multiple data-mining algorithms in parallel, or in tandem, can be effective for rapidly profiling in vivo drug metabolites.

Impact of the emergence of designer drugs upon sports doping testing

Historically, dope-testing methods have been developed to target specific and known threats to the integrity of sport. Traditionally, the source of new analytical targets for which testing was required were derived almost exclusively from the pharmaceutical industry. More recently, the emergence of designer drugs, such as tetrahydrogestrinone that are specifically intended to evade detection, or novel chemicals intended to circumvent laws controlling the sale and distribution of recreational drugs, such as anabolic steroids, stimulants and cannabinoids, have become a significant issue. In this review, we shall consider the emergence of designer drugs and the response of dope-testing laboratories to these new threats, in particular developments in analytical methods, instrumentation and research intended to detect their abuse, and we consider the likely future impact of these approaches.

Development of a new screening method for the detection of antibiotic residues in muscle tissues using liquid chromatography and high resolution mass spectrometry with a LC-LTQ-Orbitrap instrument

A liquid chromatography-high resolution mass spectrometry (LC-HRMS) method was developed for screening meat for a wide range of antibiotics used in veterinary medicine. Full-scan mode under high resolution mass spectral conditions using an LTQ-Orbitrap mass spectrometer with resolving power 60,000 full width at half maximum (FWHM) was applied for analysis of the samples. Samples were prepared using two extraction protocols prior to LC-HRMS analysis. The scope of the method focuses on screening the following main families of antibacterial veterinary drugs: penicillins, cephalosporins, sulfonamides, macrolides, tetracyclines, aminoglucosides and quinolones. Compounds were successfully identified in spiked samples from their accurate mass and LC retention times from the acquired full-scan chromatogram. Automated data processing using ToxId software allowed rapid treatment of the data. Analyses of muscle tissues from real samples collected from antibiotic-treated animals was carried out using the above methodology and antibiotic residues were identified unambiguously. Further analysis of the data for real samples allowed the identification of the targeted antibiotic residues but also non-targeted compounds, such as some of their metabolites.

Gas chromatography coupled to mass spectrometry-based metabolomic to screen for anabolic practices in cattle: identification of 5α-androst-2-en-17-one as new biomarker of 4-androstenedione misuse

The use of anabolic steroids as growth promoters for meat-producing animals is banned within the European Union. However, screening for the illegal use of natural steroid hormones still represents a difficult challenge because of the high interindividual and physiological variability of the endogenous concentration levels in animals. In this context, the development of untargeted profiling approaches for identifying new relevant biomarkers of exposure and/or effect has been emerging for a couple of years. The present study deals with an untargeted metabolomics approach on the basis of GC-MS aiming to reveal potential biomarkers signing a fraudulent administration of 4-androstenedione (AED), an anabolic androgenic steroid chosen as template. After a sample preparation based on microextraction by packed sorbent, urinary profiles of the free and deglucurono-conjugates urinary metabolites were acquired by GC-MS in the full-scan acquisition mode. Data processing and chemometric procedures highlighted 125 ions, allowing discrimination between samples collected before and after an administration of 4-AED. After a first evaluation of the signal robustness using additional and independent non-compliant samples, 17 steroid-like metabolites were pointed out as relevant candidate biomarkers. All these metabolites were then monitored using a targeted GC-MS/MS method for an additional assessment of their capacity to be used as biomarkers. Finally, two steroids, namely 5α-androstane-3β,17α-diol and 5α-androst-2-en-17-one, were concluded to be compatible with such a definition and which could be finally usable for screening purpose of AED abuse in cattle.