Dealing with the unknown: Metabolomics and Metabolite Atlases

Metabolomics is the comprehensive profiling of the small molecule composition of a biological sample. Since metabolites are often the indirect products of gene expression, this approach is being used to provide new insights into a variety of biological systems (clinical, bioenergy, etc.). A grand challenge for metabolomics is the complexity of the data, which often include many experimental artifacts. This is compounded by the tremendous chemical diversity of metabolites. Identification of each uncharacterized metabolite is in many ways its own puzzle (compared with proteomics, which is based on predictable fragmentation patterns of polypeptides). Therefore, effective data reduction/prioritization strategies are critical for this rapidly developing field. Here we review liquid chromatography electrospray ionization mass spectrometry (LC/MS)-based metabolomics, methods for feature finding/prioritization, approaches for identifying unknown metabolites, and construction of method specific ‘Metabolite Atlases’.     

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

Anabolic steroids are banned in food producing livestock in Europe. Efficient methods based on mass spectrometry detection have been developed to ensure the control of such veterinary drug residues. Nevertheless, the use of "cocktails" composed of mixtures of low amounts of several substances as well as the synthesis of new compounds of unknown structure prevent efficient prevention. New analytical tools able to detect such abuse are today mandatory. In this context, metabolomics may represent new emerging strategies for investigating the global physiological effects associated to a family of substances and therefore, to suspect the administration of steroids. The purpose of the present study was to set up, assess and compare two complementary mass spectrometry-based metabolomic strategies as new tools to screen for steroid abuse in cattle and demonstrate the feasibility of such approaches. The protocols were developed in two European laboratories in charge of residues analysis in the field of food safety. Apart from sample preparation, the global process was different in both laboratories from LC-HRMS fingerprinting to multivariate data analysis through data processing and involved both LC-Orbitrap-XCMS and UPLC-ToF-MS-MetAlign strategies. The reproducibility of both sample preparation and MS measurements were assessed in order to guarantee that any differences in the acquired fingerprints were not caused by analytical variability but reflect metabolome modifications upon steroids administration. The protocols were then applied to urine samples collected on a large group of animals consisting of 12 control calves and 12 calves administrated with a mixture of 17β-estradiol 3-benzoate and 17β-nandrolone laureate esters according to a protocol reflecting likely illegal practices. The modifications in urine profiles as indicators of steroid administration have been evaluated in this context and proved the suitability of the approach for discriminating anabolic treated animals from control ones. Such an approach may therefore open a new way for the screening of anabolic steroid administration through targeted monitoring of relevant biomarkers highlighted as a result of the metabolomics study.     

(Xeno)metabolomics for the evaluation of aquatic organism’s exposure to field contaminated water

Environmental (xeno)metabolomics offers a major advantage compared to other approaches for the evaluation of aquatic organism’s exposure to contaminated water because its allows the simultaneous profiling of the xenometabolome (chemical xenobiotics and their metabolites accumulated in an organism exposed to environmental contaminants) and the metabolome (endogenous metabolites whose levels are altered due to an external stressor). This approach has been widely explored in lab exposure experiments, however in field studies environmental (xeno)metabolomics has only started in the last years. In this review, the papers published so far that have performed different (xeno)metabolomics approaches for the evaluation of aquatic organisms exposed to contaminated water are presented, together with their main achievements, current limitations, and future perspectives. The different analytical methods applied including sample pre-treatment (considering matrix type), platforms used (Nuclear Magnetic Resonance (NMR) and low- or high-resolution Mass Spectrometry (MS or HRMS)), and the analytical strategy (target vs non-target analysis) are discussed. The application of (xeno)metabolomics to provide information of xenobiotics mixtures accumulated in exposed organisms, either in lab or field studies, as well as biomarkers of exposure and biomarkers of effect are debated, and finally, the most commonly metabolic pathways disrupted by chemical contamination are highlighted.     

Current trends and challenges in sample preparation for global metabolomics using liquid chromatography–mass spectrometry

The choice of sample-preparation method is extremely important in metabolomic studies because it affects both the observed metabolite content and biological interpretation of the data. An ideal sample-preparation method for global metabolomics should (i) be as non-selective as possible to ensure adequate depth of metabolite coverage; (ii) be simple and fast to prevent metabolite loss and/or degradation during the preparation procedure and enable high-throughput; (iii) be reproducible; and (iv) incorporate a metabolism-quenching step to represent true metabolome composition at the time of sampling. Despite its importance, sample preparation is often an overlooked aspect of metabolomics, so the focus of this review is to explore the role, challenges, and trends in sample preparation specifically within the context of global metabolomics by liquid chromatography-mass spectrometry (LC-MS). This review will cover the most common methods including solvent precipitation and extraction, solid-phase extraction and ultrafiltration, and discuss how to improve analytical quality and metabolite coverage in metabolomic studies of biofluids, tissues, and mammalian cells. Recent developments in this field will also be critically examined, including in vivo methods, turbulent-flow chromatography, and dried blood spot sampling.     

Analytical methods for human biomonitoring of pesticides. A review

Biomonitoring of both currently-used and banned-persistent pesticides is a very useful tool for assessing human exposure to these chemicals. In this review, we present current approaches and recent advances in the analytical methods for determining the biomarkers of exposure to pesticides in the most commonly used specimens, such as blood, urine, and breast milk, and in emerging non-invasive matrices such as hair and meconium. We critically discuss the main applications for sample treatment, and the instrumental techniques currently used to determine the most relevant pesticide biomarkers. We finally look at the future trends in this field.     

Review of validation and reporting of non-targeted fingerprinting approaches for food authentication

Food fingerprinting approaches are expected to become a very potent tool in authentication processes aiming at a comprehensive characterization of complex food matrices. By non-targeted spectrometric or spectroscopic chemical analysis with a subsequent (multivariate) statistical evaluation of acquired data, food matrices can be investigated in terms of their geographical origin, species variety or possible adulterations. Although many successful research projects have already demonstrated the feasibility of non-targeted fingerprinting approaches, their uptake and implementation into routine analysis and food surveillance is still limited. In many proof-of-principle studies, the prediction ability of only one data set was explored, measured within a limited period of time using one instrument within one laboratory. Thorough validation strategies that guarantee reliability of the respective data basis and that allow conclusion on the applicability of the respective approaches for its fit-for-purpose have not yet been proposed. Within this review, critical steps of the fingerprinting workflow were explored to develop a generic scheme for multivariate model validation. As a result, a proposed scheme for “good practice” shall guide users through validation and reporting of non-targeted fingerprinting results. Furthermore, food fingerprinting studies were selected by a systematic search approach and reviewed with regard to (a) transparency of data processing and (b) validity of study results. Subsequently, the studies were inspected for measures of statistical model validation, analytical method validation and quality assurance measures. In this context, issues and recommendations were found that might be considered as an actual starting point for developing validation standards of non-targeted metabolomics approaches for food authentication in the future. Hence, this review intends to contribute to the harmonization and standardization of food fingerprinting, both required as a prior condition for the authentication of food in routine analysis and official control.     

Analytical methods for monitoring contaminants in food—An industrial perspective

Incoming legislation on the registration, evaluation, authorisation and restriction of chemical substances places responsibility on the chemical industry, including downstream users of chemicals, to provide appropriate safety information with which to improve the protection of human health and the environment through the better and earlier identification of the intrinsic properties of chemical substances. Food consumption is only one of several potential exposure routes, but if industrial chemicals enter the food chain, the diet may be a significant pathway of human exposure. Consequently strong measures are taken to protect the integrity of the human food chain and these are constantly revised to address perceived chemical safety threats. In order to understand the risk presented by the possible presence of a chemical residue in food, knowledge is required of its toxicology and of the level of exposure. Reliable exposure assessment requires robust analytical methodology. Existing standards for the validation and performance evaluation of methods have led to improved analytical capability and better inter-laboratory agreement of results. However, increasing the availability of robust, cost-effective methodology should be the benchmark for future developments in the field of food chemical residue analysis. Chromatography meets the needs of target analyses well and largely provides the selectivity of measurement needed to assess compliance with food regulatory limits. However, to keep pace with the increased need for expanded analytical capability – faster throughput, more analytes per sample – chromatographic separation capability still needs to grow. In this respect, orthogonal separation techniques and multi-dimensional chromatography are key tools for the future.     

Analytical challenges and solutions for performing metabolomic analysis of root exudates

Plant stress responses are mediated by the release of chemical compounds called exudates into the rhizosphere. These chemical substances include primary and secondary plant metabolites and play an important role in the plant defense mechanism. The identification, characterization and study of these compounds can open the door to numerous applications, from greener agriculture to enhanced phytoremediation. This paper critically reviews the most relevant sampling strategies, analytical methodologies, and data-mining approaches to study root exudates.Common analytical techniques are grounded in mass spectrometry or nuclear mass spectrometry, but less common biospectroscopy techniques could offer a new perspective in plant metabolomics due to the minimal sample processing they require. Finally, after analysis, the collected raw data must then be analyzed by means of different multivariate and univariate statistical approaches to test biological-response hypotheses. All in all, the assessment of root exudates calls for the development of hyphenated analytical methodologies, as well as efforts to consolidate data-preprocessing workflows.