Non-Targeted LC-MS Metabolomics Approach towards an Authentication of the Geographical Origin of Grain Maize (Zea mays L.) Samples.

Safety along the food and feed supply chain is an emerging topic and closely linked to the ability to analytical trace the geographical origin of food or feed. In this study, ultra-performance liquid chromatography coupled with electrospray ionization quadrupole-time-of-flight mass spectrometry was used to trace back the geographical origin of 151 grain maize (Zea mays L.) samples from seven countries using a high resolution non-targeted metabolomics approach. Multivariate data analysis and univariate statistics were used to identify promising marker features related to geographical origin. Classification using only 20 selected markers with the Random Forest algorithm led to 90.5% correctly classified samples with 100 times repeated 10-fold cross-validation. The selected markers were assigned to the class of triglycerides, diglycerides and phospholipids. The marker set was further evaluated for its ability to separate between one sample class and the rest of the dataset, yielding accuracies above 89%. This demonstrates the high potential of the non-polar metabolome to authenticate the geographic origin of grain maize samples. Furthermore, this suggests that focusing on only a few lipids with high potential for grain maize authentication could be a promising approach for later transfer of the method to routine analysis.

NMR spectroscopy in wine authentication: An official control perspective.

Wine authentication is vital in identifying malpractice and fraud, and various physical and chemical analytical techniques have been employed for this purpose. Besides wet chemistry, these include chromatography, isotopic ratio mass spectrometry, optical spectroscopy, and nuclear magnetic resonance (NMR) spectroscopy, which have been applied in recent years in combination with chemometric approaches. For many years, 2 H NMR spectroscopy was the method of choice and achieved official recognition in the detection of sugar addition to grape products. Recently, 1 H NMR spectroscopy, a simpler and faster method (in terms of sample preparation), has gathered more and more attention in wine analysis, even if it still lacks official recognition. This technique makes targeted quantitative determination of wine ingredients and nontargeted detection of the metabolomic fingerprint of a wine sample possible. This review summarizes the possibilities and limitations of 1 H NMR spectroscopy in analytical wine authentication, by reviewing its applications as reported in the literature. Examples of commercial and open-source solutions combining NMR spectroscopy and chemometrics are also examined herein, together with its opportunities of becoming an official method.

Non-targeted detection of paprika adulteration using mid-infrared spectroscopy and one-class classification - Is it data preprocessing that makes the performance?

A method for the non-targeted detection of paprika adulteration was developed using Fourier transform mid-infrared (FT-MIR) spectroscopy and one-class soft independent modelling of class analogy (OCSIMCA). One-class models based on commercially available paprika powders were developed and optimised to provide >80% sensitivity by external validation. The performances of the established models for adulteration detection were tested by predicting spiked paprika samples with various types of fraudulent material and levels of adulterations including 1% (w/w) Sudan I, 1% (w/w) Sudan IV, 3% (w/w) lead chromate, 3% (w/w) lead oxide, 5% (w/w) silicon dioxide, 10% (w/w) polyvinyl chloride, and 10% (w/w) gum arabic. Further, the influence of data preprocessing on the model performance was investigated. Relationship between classification results and data preprocessing was identified and specificity >80% was achieved for all adulterants by applying different preprocessing methods including standard normal variate (SNV), first and second derivatives, smoothing, and combinations thereof.

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.

Metabolic Effect Level Index Links Multivariate Metabolic Fingerprints to Ecotoxicological Effect Assessment.

A major goal of ecotoxicology is the prediction of adverse outcomes for populations from sensitive and early physiological responses. A snapshot of the physiological state of an organism can be provided by metabolic fingerprints. However, to inform chemical risk assessment, multivariate metabolic fingerprints need to be converted to readable end points suitable for effect estimation and comparison. The concentration- and time-dependent responsiveness of metabolic fingerprints to the PS-II inhibitor isoproturon was investigated by use of a Myriophyllum spicatum bioassay. Hydrophilic and lipophilic leaf extracts were analyzed with gas chromatography-mass spectrometry (GC-MS) and preprocessed with XCMS. Metabolic changes were aggregated in the quantitative metabolic effect level index (MELI), allowing effect estimation from Hill-based concentration-response models. Hereby, the most sensitive response on the concentration scale was revealed by the hydrophilic MELI, followed by photosynthetic efficiency and, 1 order of magnitude higher, by the lipophilic MELI and shoot length change. In the hydrophilic MELI, 50% change compares to 30% inhibition of photosynthetic efficiency and 10% inhibition of dry weight change, indicating effect development on different response levels. In conclusion, aggregated metabolic fingerprints provide quantitative estimates and span a broad response spectrum, potentially valuable for establishing adverse outcome pathways of chemicals in environmental risk assessment.

High-throughput concentration-response analysis for omics datasets.

Omics-based methods are increasingly used in current ecotoxicology. Therefore, a large number of observations for various toxic substances and organisms are available and may be used for identifying modes of action, adverse outcome pathways, or novel biomarkers. For these purposes, good statistical analysis of toxicogenomic data is vital. In contrast to established ecotoxicological techniques, concentration-response modeling is rarely used for large datasets. Instead, statistical hypothesis testing is prevalent, which provides only a limited scope for inference. The present study therefore applied automated concentration-response modeling for 3 different ecotoxicotranscriptomic and ecotoxicometabolomic datasets. The modeling process was performed by simultaneously applying 9 different regression models, representing distinct mechanistic, toxicological, and statistical ideas that result in different curve shapes. The best-fitting models were selected by using Akaike's information criterion. The linear and exponential models represented the best data description for more than 50% of responses. Models generating U-shaped curves were frequently selected for transcriptomic signals (30%), and sigmoid models were identified as best fit for many metabolomic signals (21%). Thus, selecting the models from an array of different types seems appropriate, because concentration-response functions may vary because of the observed response type, and they also depend on the compound, the organism, and the investigated concentration and exposure duration range. The application of concentration-response models can help to further tap the potential of omics data and is a necessary step for quantitative mixture effect assessment at the molecular response level.

Bioassays with unicellular algae: deviations from exponential growth and its implications for toxicity test results.

Growth assays with unicellular green algae are an established tool in ecotoxicological effect assessment for chemicals and environmental samples. From an ecological perspective it seems appropriate to use the growth rate as a process variable rather than a measure of biomass gain for calculating inhibitory effects of contaminants. The notion of simple exponential growth for the description of the population increase in undisturbed suspension cultures of unicellular green algae, however, seems to be an oversimplification. Experimental findings describe the increase in biomass, cell number, the development of cell volume distributions of populations, and the relationship between cell size and chlorophyll content for individual cells over one generation at a time resolution of 2-h intervals. It was observed that algal populations of Desmodesmus subspicatus show a time pattern of cell size growth; the average cell volume increases about sixfold, without corresponding increase in population size. This is followed by a distinct cell division phase with little gain in biomass. This synchronous growth behavior despite continuous illumination may be explained by the multiple fission characteristic of unicellular green algae which is an adaptation to cyclic light-dark changes in the environment. It might be controlled by an independent cell cycle clock. For routine regulatory testing fluorescence-based measurements rather than cell counting minimizes the confounding effect on toxicity determination. For investigations of time-dependent effects, e.g., by pulsed exposure, an alternative mechanistically based growth function for unicellular algae is proposed that accommodates for the observed growth pattern.

Physicochemical substance properties as indicators for unreliable exposure in microplate-based bioassays.

In the last years many efforts were made to transform standardized algal test protocols into low-cost microplate assays. While advantages were pointed out frequently, limitations are not systematically addressed, thus hindering a widespread utilisation. In this study a group of organic substances with a wide distribution of volatility (logKAW from -6.53 to -2.13) and lipophilicity (logKOW from 1.26 to 4.92) was investigated with respect to the influence of these physicochemical properties on their algal toxicity in different assays. Therefore the EC50 values were determined with a microplate assay based on ISO 8692 protocol and the results were compared with those of an established algal growth inhibition test conducted in air tight glass vessels. Using the ratio of the EC50 values, a clear connection between biological response and volatility as well as lipophilicity of test substances could be detected. Chemicals with a logKOW higher than 3 or a Henry coefficient logKAW higher than -4 were identified as less effective in the microplate assay than in the comparative assay. The loss in nominal concentration due to physicochemical properties could be shown to contribute to this using HPLC analysis. Consequently, when using microplate assay's one should be aware that lipophilic and volatile chemicals might be underestimated in their toxicity, which could be indicated from evaluating related physicochemical properties modelled from structural information prior to an experimental investigation.

On the mode of action of N-phenyl-2-naphthylamine in plants.

N-phenyl-2-naphthylamine, a sediment contaminant previously identified as a major toxicant of site-specific importance was investigated for its mode of toxic action. From short-term bioassays with daphnids, fish eggs, bacteria, and algae it appears that this compound has specific phytotoxic properties at concentrations below 100 microg/L, which cannot be explained assuming an unspecific narcosis type of action in plants. Also, hydroxy-, nitro-, and methylderivatives show clear excess toxicity as compared to baseline toxic effects. Of several plant-specific growth and development processes investigated, only photosynthesis could be demonstrated to be affected at short exposure times and low concentrations. Disturbance of primary photosynthetic reactions such as oxygen evolution and fluorescence quenching, however, becomes only apparent after 2-3 h of exposure, which is in sharp contrast to known specific inhibitors targeting processes such as electron transport or ATP production. This, and concentration-time-effect modeling lead to the suggestion that N-phenyl-2-naphthylamine acts intracellular as a reactive compound in cell membranes producing irreversible, and thus cumulative, damage over time in algae. The effects may become first apparent in membrane-rich compartments such as the algal chloroplast.