Metabolomics of transgenic maize combining Fourier transform-ion cyclotron resonance-mass spectrometry, capillary electrophoresis-mass spectrometry and pressurized liquid extraction

The utility of metabolomics as a tool to inform maize biology

With the rise of high-throughput omics tools and the importance of maize and its products as food and bioethanol, maize metabolism has been extensively explored. Modern maize is still rich in genetic and phenotypic variation, yielding a wide range of structurally and functionally diverse metabolites. The maize metabolome is also incredibly dynamic in terms of topology and subcellular compartmentalization. In this review, we examine a broad range of studies that cover recent developments in maize metabolism. Particular attention is given to current methodologies and to the use of metabolomics as a tool to define biosynthetic pathways and address biological questions. We also touch upon the use of metabolomics to understand maize natural variation and evolution, with a special focus on research that has used metabolite-based genome-wide association studies (mGWASs).

Comparison of generational effect on proteins and metabolites in non-transgenic and transgenic soybean seeds through the insertion of the cp4-EPSPS gene assessed by omics-based platforms

This work evaluates different generations of transgenic (cp4-EPSPS gene) and non-transgenic soybean plants through proteomics and metabolomics. For proteomics purpose, 24 differentially abundant protein spots were found through 2-D DIGE, being 4 belonging to transgenic plants. From this total, 19 were successfully identified, storage proteins as predominant class. Some identified proteins are involved in growing and cell division, and stress response, such as LEA and dehydrin. For metabolomics, 17 compounds were putatively annotated, mainly belonging to the secondary metabolism, such as flavonoids. From these analyzes, all generations and varieties of the soybean are prone to be differentiate by PLS-DA. According to our results, transgenic plants appear to be more stable than non-transgenic ones. In addition, the omics-based approaches allowed access some relations between those differential spot proteins and metabolites, mainly those storage proteins and flavonoid.

Reply to 'Comments on two recent publications on GM maize and Roundup'

The opinion expressed by Eriksson and colleagues' fails to recognise that there are no standard experimental designs for academic investigations involving omics analyses of genetically modified crops and that the only valid comparator to determine the effect of the process of transgenesis is a near isogenic variety grown at the same time and location, as was the case in our investigation of NK603 maize. Eriksson does not acknowledge that the quality of the rat liver tissues in our chronic Roundup toxicity study has neither been questioned nor branded as unsuitable for further investigation. In addition, Eriksson fails to appreciate that the statistical methods we used to analyse the liver metabolomics dataset are recognised as appropriate as some of a number of approaches that can be taken. Moreover, Eriksson neglects to mention that the proteomics analysis of the liver tissues highlights structural and functional damage from Roundup exposure. Thus our results are sound and the claims by Eriksson and colleagues of experimental flaws are unfounded.Replying to: Eriksson et al. Sci Rep 8 (2018); https://doi.org/10.1038/s41598-018-30440-7 .

Metabolomic analysis of mammalian cells and human tissue through one-pot two stage derivatizations using sheathless capillary electrophoresis-electrospray ionization-mass spectrometry

Analysis of metabolites is often performed using separations coupled to mass spectrometry which is challenging due to their vast structural heterogeneity and variable charge states. Metabolites are often separated based on their class/functional group which in large part determine their acidity or basicity. This charge state dictates the ionization mode and efficiency of the molecule. To improve the sensitivity and expand the coverage of the mammalian metabolome, multifunctional derivatization with sheathless CE-ESI-MS was undertaken. In this work, amines, hydroxyls and carboxylates were labeled with tertiary amines tags. This derivatization was performed in under 100 min and resulted in high positive charge states for all analytes investigated. Amino acids and organic acids showed average limits of detection of 76 nM with good linearity of 0.96 and 10% RSD for peak area. Applying this metabolomic profiling system to bovine aortic endothelial cells showed changes in 15 metabolites after treatment with high glucose. The sample injection volume on-capillary was <300 cells for quantitative analyses. Targeted metabolites were found in human tissue, which indicates possible application of the system complex metabolome quantitation.

Characterization of GMO or glyphosate effects on the composition of maize grain and maize-based diet for rat feeding

INTRODUCTION

In addition to classical targeted biochemical analyses, metabolomic analyses seem pertinent to reveal expected as well as unexpected compositional differences between plant genetically modified organisms (GMO) and non-GMO samples. Data previously published in the existing literature led to divergent conclusions on the effect of maize transgenes on grain compositional changes and feeding effects. Therefore, a new study examining field-grown harvested products and feeds derived from them remains useful.

OBJECTIVES

Our aim was to use a metabolomics approach to characterize grain and grain-based diet compositional changes for two GMO events, one involving Bacillus thuringiensis toxin to provide insect resistance and the other one conferring herbicide tolerance by detoxification of glyphosate. We also investigated the potential compositional modifications induced by the use of a glyphosate-based herbicide on the transgenic line conferring glyphosate tolerance.

RESULTS

The majority of statistically significant differences in grain composition, evidenced by the use of 1H-NMR profiling of polar extracts and LC-ESI-QTOF-MS profiling of semi-polar extracts, could be attributed to the combined effect of genotype and environment. In comparison, transgene and glyphosate effects remained limited in grain for the compound families studied. Some but not all compositional changes observed in grain were also detected in grain-based diets formulated for rats.

CONCLUSION

Only part of the data previously published in the existing literature on maize grains of plants with the same GMO events could be reproduced in our experiment. All spectra have been deposited in a repository freely accessible to the public. Our grain and diet characterization opened the way for an in depth study of the effects of these diets on rat health.

Recent advances in the application of capillary electromigration methods for food analysis and Foodomics

This review work presents and discusses the main applications of capillary electromigration methods in food analysis and Foodomics. Papers that were published during the period February 2015-February 2017 are included following the previous review by Acunha et al. (Electrophoresis 2016, 37, 111-141). The paper shows the large variety of food related molecules that have been analyzed by CE including amino acids, biogenic amines, carbohydrates, chiral compounds, contaminants, DNAs, food additives, heterocyclic amines, lipids, peptides, pesticides, phenols, pigments, polyphenols, proteins, residues, toxins, vitamins, small organic and inorganic compounds, as well as other minor compounds. This work describes the last results on food quality and safety, nutritional value, storage, bioactivity, as well as uses of CE for monitoring food interactions and food processing including recent microchips developments and new applications of CE in Foodomics.

Foodomics and Food Safety: Where We Are

The power of foodomics as a discipline that is now broadly used for quality assurance of food products and adulteration identification, as well as for determining the safety of food, is presented. Concerning sample preparation and application, maintenance of highly sophisticated instruments for both high-performance and high-throughput techniques, and analysis and data interpretation, special attention has to be paid to the development of skilled analysts. The obtained data shall be integrated under a strong bioinformatics environment. Modern mass spectrometry is an extremely powerful analytical tool since it can provide direct qualitative and quantitative information about a molecule of interest from only a minute amount of sample. Quality of this information is influenced by the sample preparation procedure, the type of mass spectrometer used and the analyst's skills. Technical advances are bringing new instruments of increased sensitivity, resolution and speed to the market. Other methods presented here give additional information and can be used as complementary tools to mass spectrometry or for validation of obtained results. Genomics and transcriptomics, as well as affinity-based methods, still have a broad use in food analysis. Serious drawbacks of some of them, especially the affinity-based methods, are the cross-reactivity between similar molecules and the influence of complex food matrices. However, these techniques can be used for pre-screening in order to reduce the large number of samples. Great progress has been made in the application of bioinformatics in foodomics. These developments enabled processing of large amounts of generated data for both identification and quantification, and for corresponding modeling.

Metabolomic Assessment of Key Maize Resources: GC-MS and NMR Profiling of Grain from B73 Hybrids of the Nested Association Mapping (NAM) Founders and of Geographically Diverse Landraces

The present study expands metabolomic assessments of maize beyond commercial lines to include two sets of hybrids used extensively in the scientific community. One set included hybrids derived from the nested association mapping (NAM) founder lines, a collection of 25 inbreds selected on the basis of genetic diversity and used to investigate the genetic basis of complex plant traits. A second set included 24 hybrids derived from a collection of landraces representative of native diversity from North and South America that may serve as a source of new alleles for improving modern maize hybrids. Metabolomic analysis of grain harvested from these hybrids utilized gas chromatography-time-of-flight mass spectrometry (GC-TOF-MS) and (1)H nuclear magnetic resonance spectroscopy ((1)H NMR) techniques. Results highlighted extensive metabolomic variation in grain from both hybrid sets, but also demonstrated that, within each hybrid set, subpopulations could be differentiated in a pattern consistent with the known genetic and compositional variation of these lines. Correlation analysis did not indicate a strong association of the metabolomic data with grain nutrient composition, although some metabolites did show moderately strong correlations with agronomic features such as plant and ear height. Overall, this study provides insights into the extensive metabolomic diversity associated with conventional maize germplasm.

Capillary Electrophoresis in Metabolomics

Metabolomics is an analytical toolbox to describe (all) low-molecular-weight compounds in a biological system, as cells, tissues, urine, and feces, as well as in serum and plasma. To analyze such complex biological samples, high requirements on the analytical technique are needed due to the high variation in compound physico-chemistry (cholesterol derivatives, amino acids, fatty acids as SCFA, MCFA, or LCFA, or pathway-related metabolites belonging to each individual organism) and concentration dynamic range. All main separation techniques (LC-MS, GC-MS) are applied in routine to metabolomics hyphenated or not to mass spectrometry, and capillary electrophoresis is a powerful high-resolving technique but still underused in this field of complex samples. Metabolomics can be performed in the non-targeted way to gain an overview on metabolite profiles in biological samples. Targeted metabolomics is applied to analyze quantitatively pre-selected metabolites. This chapter reviews the use of capillary electrophoresis in the field of metabolomics and exemplifies solutions in metabolite profiling and analysis in urine and plasma.

Marine protein hydrolysates: their present and future perspectives in food chemistry – a review

Marine protein hydrolysates are usually prepared by the enzymatic digestion with different proteases at controlled pH and temperature.

Characterization and study of transgenic cultivars by capillary and microchip electrophoresis

Advances in biotechnology have increased the demand for suitable analytical techniques for the analysis of genetically modified organisms. Study of the substantial equivalence, discrimination between transgenic and non-transgenic cultivars, study of the unintended effects caused by a genetic modification or their response to diverse situations or stress conditions (e.g., environmental, climatic, infections) are some of the concerns that need to be addressed. Capillary electrophoresis (CE) is emerging as an alternative to conventional techniques for the study and characterization of genetically modified organisms. This article reviews the most recent applications of CE for the analysis and characterization of transgenic cultivars in the last five years. Different strategies have been described depending on the level analyzed (DNA, proteins or metabolites). Capillary gel electrophoresis (CGE) has shown to be particularly useful for the analysis of DNA fragments amplified by PCR. Metabolites and proteins have been mainly separated using capillary zone electrophoresis (CZE) using UV and MS detection. Electrophoretic chips have also proven their ability in the analysis of transgenic cultivars and a section describing the new applications is also included.

Metabolomics of genetically modified crops

Metabolomic-based approaches are increasingly applied to analyse genetically modified organisms (GMOs) making it possible to obtain broader and deeper information on the composition of GMOs compared to that obtained from traditional analytical approaches. The combination in metabolomics of advanced analytical methods and bioinformatics tools provides wide chemical compositional data that contributes to corroborate (or not) the substantial equivalence and occurrence of unintended changes resulting from genetic transformation. This review provides insight into recent progress in metabolomics studies on transgenic crops focusing mainly in papers published in the last decade.

Metabolite profiling and fingerprinting of Suillus species (Basidiomycetes) by electrospray mass spectrometry

The genus Suillus is known for the occurrence of a series of prenylated phenols and boviquinones. The extracts of four different Suillus species [S. bovinus, S. granulatus, S. tridentinus and S.variegatus) were investigated by using rapid ultra-performance Liquid chromatography/electrospray ionization mass spectrometry (UPLC/ESI-MS) and direct infusion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry (ESI-FT-ICR-MS). While direct infusion ESI-FT-ICR mass spectra give a fast overview concerning the elemental compositions of the compounds and, therefore, hints to the main metabolites, UPLC/ESI-tandem mass spectrometry is shown to be a useful tool for their identification. A principal component analysis (PCA) and hierarchical cluster analysis (HCA) based on the UPLC/ESI-MS clearly showed that the metabolite profiles can be used not only for the identification and classification of such fungi but also as a sophisticated and powerful tool for the chemotaxonomy of fungi. Furthermore, a clear discrimination of various types of biological samples (fruiting bodies versus mycelial cultures) is also possible. The orthogonal partial least squares (OPLS) two-class models of both UPLC/ESI-MS and ESI-FT-ICR-MS possess a clear differentiation of two compared Suillus species representing the between class variation and the within class variation. Based on generated S-plots and Loading plots, statistically significant metabolites could be identified as potential biomarker for one species.

Ultrahigh resolution mass spectrometry-based metabolic characterization reveals cerebellum as a disturbed region in two animal models

In the previous reports about cognitive dysfunction, cerebellum was thought to be a less affected tissue by genetic or environmental alterations in comparison to other tissues in the brain including hippocampus under the same conditions. In this work, we investigated two types of metabolomic alterations inside the cerebellum tissue. The first one addressed the differences in the metabolomics profiles between Transgenic (Tg) CRND8 of Alzheimer's disease mice and non-transgenic (non-Tg) littermates. The second one addressed the metabolic differences between wild type mice exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and wild type mice which are not exposed to this toxic compound. For these two investigations, ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR/MS) was implemented. As a result, the significant changes of each comparison were tentatively annotated by the high mass accuracy generated from the measurements in the negative ion mode. The biosynthesis of amino acids was also enhanced pronouncedly, and perturbation of purine metabolism was also observed in Tg mice compared to non-Tg littermates. In another animal model, the reduced levels of amino acids were found whereas the intermediate levels in purine metabolism and fatty acids including fatty acid conjugated metabolites were elevated in cerebellar tissues of mice exposed to TCDD compared to control group. Collectively, it was demonstrated that FT-ICR/MS was a powerful tool for interpretation of the elemental compositions of the peaks, revealing that the metabolic perturbations in cerebellar tissues of mice were induced by either genetic manipulation or environmental factor. Therefore, the non-targeted approach, alternatively, provides various metabolic phenotypes for the systems-level mirror of the complex etiology of neurotoxicity in the cerebellum.

Metabolic effect of an exogenous gene on transgenic Beauveria bassiana using liquid chromatography-mass spectrometry-based metabolomics

Genetic modification of Beauveria bassiana with the scorpion neurotoxin aaIT gene can distinctly increase its insecticidal activity, whereas the effect of this exogenous gene on the metabolism of B. bassiana is unknown until now. Thus, we investigate the global metabolic profiling of mycelia and conidia of transgenic and wild-type B. bassiana by liquid chromatography-mass spectrometry (LC-MS). Principal component analysis (PCA) and orthogonal projection to latent structure discriminant analysis (OPLS-DA) reveal clear discrimination of wild-type mycelia and conidia from transgenic mycelia and conidia. The decrease of glycerophospholipids, carnitine, and fatty acids and the increase of oxylipins, glyoxylate, pyruvic acid, acetylcarnitine, fumarate, ergothioneine, and trehalose in transgenic mycelia indicate the enhanced oxidative reactions. In contrast, most metabolites related to oxidative stress are not altered significantly in conidia, which implies that there will be no significant oxidative stress reaction when the aaIT gene is quiescent in cells.

Metabolomics platforms for genome wide association studies--linking the genome to the metabolome

Genome-wide association studies (GWAS) reveal links between genetic variance and predisposition to disease. With the advent of modern 'omics-technologies', GWAS can now identify the genetic factors that influence intermediate traits on pathways to disease, such as blood concentrations of carbohydrates, lipids, amino acids, and secondary metabolites, hormones and signal molecules. At the example of recent GWAS with metabolic traits (mGWAS) we review the high-throughput screening approaches that are available to further advance the field.

Infectomics Screening for Novel Antiviral Drug Targets

Preclinical Research

Copyright 2012 Wiley-Liss, Inc., A Wiley Company

Infectomics, a novel way to globally and comprehensively understand the interactions between microbial pathogens and their hosts, has significantly expanded understanding of the microbial infections. The infectomics view of viral–host interactions on the viral perspective principally focuses on gene acquisition, deletion, and point mutation, while traditional antiviral drug discovery concentrates on viral encoding proteins. Recently, high‐throughput technologies, such as mass spectrometry‐based proteomics, activity‐based protein profiling, microarray analysis, yeast two‐hybrid assay, small interfering RNA screening, and micro RNA profiling, have been gradually employed in the research of virus–host interactions. Besides, signaling pathways and cellular processes involved in viral–host interactions provide new insights of infectomics in antiviral drug discovery. In this review, we summarize related infectomics approaches in the studies of virus–host interactions, which shed light on the development of novel antiviral drug targets screening.

Recent advances in enrichment techniques for trace analysis in capillary electrophoresis

CE is gaining great popularity as a well-established separation technique for many fields such as pharmaceutical research, clinical application, environmental monitoring, and food analysis, owing to its high resolving power, rapidity, and small amount of samples and reagents required. However, the sensitivity in CE analysis is still considered as being inferior to that in HPLC analysis. Diverse enrichment methods and techniques have been increasingly developed for overcoming this issue. In this review, we summarize the recent advances in enrichment techniques containing off-line preconcentration (sample preparation) and on-line concentration (sample stacking) to enhancing sensitivity in CE for trace analysis over the last 5 years. Some relatively new cleanup and preconcentration methods involving the use of dispersive liquid-liquid microextraction, supercritical fluid extraction, matrix solid-phase dispersion, etc., and the continued use and improvement of conventional SPE, have been comprehensively reviewed and proved effective preconcentration alternatives for liquid, semisolid, and solid samples. As for CE on-line stacking, we give an overview of field amplication, sweeping, pH regulation, and transient isotachophoresis, and the coupling of multiple modes. Moreover, some limitations and comparisons related to such methods/techniques are also discussed. Finally, the combined use of various enrichment techniques and some significant attempts are proposed to further promote analytical merits in CE.

Proteomics insight into the biological safety of transgenic modification of rice as compared with conventional genetic breeding and spontaneous genotypic variation

The potential of unintended effects caused by transgenic events is a key issue in the commercialization of genetically modified (GM) crops. To investigate whether transgenic events cause unintended effects, we used comparative proteomics approaches to evaluate proteome differences in seeds from 2 sets of GM indica rice, herbicide-resistant Bar68-1 carrying bar and insect-resistant 2036-1a carrying cry1Ac/sck, and their respective controls D68 and MH86, as well as indica variety MH63, a parental line for breeding MH86, and japonica variety ZH10. This experimental design allowed for comparing proteome difference caused by transgenes, conventional genetic breeding, and natural genetic variation. Proteomics analysis revealed the maximum numbers of differentially expressed proteins between indica and japonica cultivars, second among indica varieties with relative small difference between MH86 and MH63, and the minimum between GM rice and respective control, thus indicating GM events do not substantially alter proteome profiles as compared with conventional genetic breeding and natural genetic variation. Mass spectrometry analysis revealed 234 proteins differentially expressed in the 6 materials, and these proteins were involved in different cellular and metabolic processes with a prominent skew toward metabolism (31.2%), protein synthesis and destination (25.2%), and defense response (22.4%). In these seed proteomes, proteins implicated in the 3 prominent biological processes showed significantly different composite expression patterns and were major factors differentiating japonica and indica cultivars, as well as indica varieties. Thus, metabolism, protein synthesis and destination, and defense response in seeds are important in differentiating rice cultivars and varieties.

Metabolite profiling of maize kernels--genetic modification versus environmental influence

A metabolite profiling approach based on gas chromatography-mass spectrometry (GC-MS) was applied to investigate the metabolite profiles of genetically modified (GM) Bt-maize (DKC78-15B, TXP 138F) and Roundup Ready-maize (DKC78-35R). For the comparative investigation of the impact of genetic modification versus environmental influence on the metabolite profiles, GM maize was grown together with the non-GM near-isogenic comparators under different environmental conditions, including several growing locations and seasons in Germany and South Africa. Analyses of variance (ANOVA) revealed significant differences between GM and non-GM maize grown in Germany and South Africa. For the factor genotype, 4 and 3%, respectively, of the total number of peaks detected by GC-MS showed statistically significant differences (p < 0.01) in peak heights as compared to the respective isogenic lines. However, ANOVA for the factor environment (growing location, season) revealed higher numbers of significant differences (p < 0.01) between the GM and the non-GM maize grown in Germany (42%) and South Africa (10%), respectively. This indicates that the majority of differences observed are related to natural variability rather than to the genetic modifications. In addition, multivariate data assessment by means of principal component analysis revealed that environmental factors, that is, growing locations and seasons, were dominant parameters driving the variability of the maize metabolite profiles.

Metabolic profiling based on LC/MS to evaluate unintended effects of transgenic rice with cry1Ac and sck genes

As a primary characteristic of substantial equivalence, the evaluation of unintended effects of genetically modified plants has been evolving into an important field of research. In this study, a metabolic profiling method for rice seeds was developed using rapid resolution liquid chromatography/quadrupole time-of-flight mass spectrometry. The analytical properties of the method, including the linearity, reproducibility, intra-day precision and inter-day precision, were investigated and were found to be satisfactory. The method was then applied to investigate the differences between transgenic rice and its native counterparts, in addition to the differences found between native rice with different sowing dates or locations. Global metabolic phenotype differences were visualized, and metabolites from different discriminated groups were discovered using multivariate data analysis. The results indicated that environmental factors played a greater role than gene modification for most metabolites, including tryptophan, 9,10,13-trihydroxyoctadec-11-enoic acid, and lysophosphatidylethanolamine 16:0. The concentrations of phytosphingosine, palmitic acid, 5-hydroxy-2-octadenoic acid and three other unidentified metabolites varied slightly due to gene modification.

Foodomics: MS-based strategies in modern food science and nutrition

Modern research in food science and nutrition is moving from classical methodologies to advanced analytical strategies in which MS-based techniques play a crucial role. In this context, Foodomics has been recently defined as a new discipline that studies food and nutrition domains through the application of advanced omics technologies in which MS techniques are considered indispensable. Applications of Foodomics include the genomic, transcriptomic, proteomic, and/or metabolomic study of foods for compound profiling, authenticity, and/or biomarker-detection related to food quality or safety; the development of new transgenic foods, food contaminants, and whole toxicity studies; new investigations on food bioactivity, food effects on human health, etc. This review work does not intend to provide an exhaustive revision of the many works published so far on food analysis using MS techniques. The aim of the present work is to provide an overview of the different MS-based strategies that have been (or can be) applied in the new field of Foodomics, discussing their advantages and drawbacks. Besides, some ideas about the foreseen development and applications of MS-techniques in this new discipline are also provided.

Effects of genetically modified T2A-1 rice on faecal microflora of rats during 90 day supplementation

BACKGROUND

Many animal studies have been performed on products with the Bacillus thuringiensis insecticidal toxin-encoding gene (Bt products), but less have focused on its effects on intestinal microflora owing to difficulties in culturing. This 90 day study was designed to assess unintended effects of genetically modified T2A-1 rice (GMR) on selected intestinal bacteria (Lactobacillus group, Bifidobacterium genus, Escherichia coli subgroup, Enterococcus genus and Clostridium perfringens) of rats by the real-time polymerase chain reaction (PCR) method.

RESULTS

During the whole experiment, no statistically significant differences in the numbers of specific bacteria and total bacteria were found between the GMR group and its parental group. At all stages of the experiment the two main probiotics (Lactobacillus group and Bifidobacterium genus) in faeces accounted for 11-23% of the total bacteria, whereas the conditional pathogens (E. coli subgroup, Enterococcus genus and C. perfringens) made up less than 1% of the total bacteria. B/E (log(10) copies of Bifidobacterium genome g(-1) faeces/log(10) copies of E. coli genome g(-1) faeces) ratios from 1.19 to 1.34 were obtained. Furthermore, significant correlations (P < 0.01) between the real-time PCR method and the plate count method were found, with r values ranging from 0.60 to 0.75.

CONCLUSION

No adverse effects on the numbers of specific bacteria in rat faeces were observed as a result of GMR feeding. The real-time PCR method is recommended in further studies on the composition and dynamics of the intestinal bacteria community for better safety assessment of GM materials.

MS-based analytical methodologies to characterize genetically modified crops

The development of genetically modified crops has had a great impact on the agriculture and food industries. However, the development of any genetically modified organism (GMO) requires the application of analytical procedures to confirm the equivalence of the GMO compared to its isogenic non-transgenic counterpart. Moreover, the use of GMOs in foods and agriculture faces numerous criticisms from consumers and ecological organizations that have led some countries to regulate their production, growth, and commercialization. These regulations have brought about the need of new and more powerful analytical methods to face the complexity of this topic. In this regard, MS-based technologies are increasingly used for GMOs analysis to provide very useful information on GMO composition (e.g., metabolites, proteins). This review focuses on the MS-based analytical methodologies used to characterize genetically modified crops (also called transgenic crops). First, an overview on genetically modified crops development is provided, together with the main difficulties of their analysis. Next, the different MS-based analytical approaches applied to characterize GM crops are critically discussed, and include "-omics" approaches and target-based approaches. These methodologies allow the study of intended and unintended effects that result from the genetic transformation. This information is considered to be essential to corroborate (or not) the equivalence of the GM crop with its isogenic non-transgenic counterpart.

Thirty years of capillary electrophoresis in food analysis laboratories: potential applications

CE has generated considerable interest in the research community since instruments were introduced by different trading companies in the 1990s. Nowadays, CE is popular due to its simplicity, speed, highly efficient separations and minimal solvent and reagent consumption; it can also be included as a useful technique in the nanotechnology field and it covers a wide range of specific applications in different fields (chemical, pharmaceutical, genetic, clinical, food and environmental). CE has been very well evaluated in research laboratories for several years, and different new approaches to improve sensitivity (one of the main drawbacks of CE) and robustness have been proposed. However, this technique is still not well accepted in routine laboratories for food analysis. Researching in data bases, it is easy to find several electrophoretic methods to determine different groups of analytes and sometimes they are compared in terms of sensitivity, selectivity, precision and applicability with other separation techniques. Although these papers frequently prove the potential of this methodology in spiked samples, it is not common to find a discussion of the well-known complexity of the matrices to extract analytes from the sample and/or to study the interferences in the target analytes. Summarizing, the majority of CE scientific papers focus primarily on the effects upon the separation of the analytes while ignoring their behavior if these analytes are presented in real samples.