A role for “omics” technologies in food safety assessment

Data fusion of elemental and metabolic fingerprints of asparagus with random forest approaches

BACKGROUND

Various analytical methods such as liquid chromatography-mass spectrometry (LC-MS) and inductively coupled plasma-mass spectrometry (ICP-MS) are used for the characterisation and authentication of foods. These two analytical techniques target very different parts of the complex composition of the samples and therefore fusion of the data promises better performance of the corresponding models.

RESULTS

ICP-MS and LC-MS data were fused for the classification of the geographical origin of 220 asparagus samples with random forest. The results show that the combination of elemental and metabolomic fingerprints leads to an improvement of the accuracy from approximately 88 % to 92.3 %. In particular, the fusion improves the classification of small groups, which is reflected by an increase in the Cohen's Kappa value from around 0.7 to 0.8. Furthermore, we applied surrogate minimal depth (SMD) to elemental fingerprints and fused data of elemental and metabolomic fingerprints for the first time. This made it possible to select relevant features and evaluate their mutual impact on the classification model, illustrating the interplay of the elemental and metabolic variables in the fused random forest model.

SIGNIFICANCE

Using the classification of the geographical origin of asparagus, we show that the fusion of LC-MS and ICP-MS data is useful for improving the performance of food authentication. Furthermore, we show that SMD can be applied to analyse the mutual impact of features of single data sets but also across multiple data sets in the context of data fusion.

Research Progress in the Extraction, Structural Characteristics, Bioactivity, and Commercial Applications of Oat β-Glucan: A Review

Oats (Avena sativa L.) are an important cereal crop with diverse applications in both food and forage. Oat β-glucan has gained attention for its beneficial biological activities, such as reducing cardiovascular risk, preventing diabetes, and enhancing intestinal health. Despite its potential, more comprehensive research is required to explore its preparation, modification, bioactivities, and applications. This review highlights recent advancements in the determination and preparation of oat β-glucan, explores its biological activities and mechanisms, and examines the impact of food processing techniques on its properties. This review is intended to provide a theoretical foundation and reference for the development and application of oat β-glucan in the functional food industry.

Effect of T-DNA Integration on Growth of Transgenic Populus × euramericana cv. Neva Underlying Field Stands

Multigene cotransformation has been widely used in the study of genetic improvement in crops and trees. However, little is known about the unintended effects and causes of multigene cotransformation in poplars. To gain insight into the unintended effects of T-DNA integration during multigene cotransformation in field stands, here, three lines (A1-A3) of Populus × euramericana cv. Neva (PEN) carrying Cry1Ac-Cry3A-BADH genes and three lines (B1-B3) of PEN carrying Cry1Ac-Cry3A-NTHK1 genes were used as research objects, with non-transgenic PEN as the control. Experimental stands were established at three common gardens in three locations and next generation sequencing (NGS) was used to identify the insertion sites of exogenous genes in six transgenic lines. We compared the growth data of the transgenic and control lines for four consecutive years. The results demonstrated that the tree height and diameter at breast height (DBH) of transgenic lines were significantly lower than those of the control, and the adaptability of transgenic lines in different locations varied significantly. The genotype and the experimental environment showed an interaction effect. A total of seven insertion sites were detected in the six transgenic lines, with B3 having a double-site insertion and the other lines having single copies. There are four insertion sites in the gene region and three insertion sites in the intergenic region. Analysis of the bases near the insertion sites showed that AT content was higher than the average chromosome content in four of the seven insertion sites within 1000 bp. Transcriptome analysis suggested that the differential expression of genes related to plant hormone transduction and lignin synthesis might be responsible for the slow development of plant height and DBH in transgenic lines. This study provides an integrated analysis of the unintended effects of transgenic poplar, which will benefit the safety assessment and reasonable application of genetically modified trees.

The potential of metabolomics in assessing global compositional changes resulting from the application of CRISPR/Cas9 technologies

Exhaustive analysis of genetically modified crops over multiple decades has increased societal confidence in the technology. New Plant Breeding Techniques are now emerging with improved precision and the ability to generate products containing no foreign DNA and mimic/replicate conventionally bred varieties. In the present study, metabolomic analysis was used to compare (i) tobacco genotypes with and without the CRISPR associated protein 9 (Cas9), (ii) tobacco lines with the edited and non-edited DE-ETIOLATED-1 gene without phenotype and (iii) leaf and fruit tissue from stable non-edited tomato progeny with and without the Cas9. In all cases, multivariate analysis based on the difference test using LC-HRMS/MS and GC-MS data indicated no significant difference in their metabolomes. The variations in metabolome composition that were evident could be associated with the processes of tissue culture regeneration and/or transformation (e.g. interaction with Agrobacterium). Metabolites responsible for the variance included quantitative changes of abundant, well characterised metabolites such as phenolics (e.g. chlorogenic acid) and several common sugars such as fructose. This study provides fundamental data on the characterisation of gene edited crops, that are important for the evaluation of the technology and its assessment. The approach also suggests that metabolomics could contribute to routine product-based analysis of crops/foods generated from New Plant Breeding approaches.

OMICS and Other Advanced Technologies in Mycological Applications

Fungi play many roles in different ecosystems. The precise identification of fungi is important in different aspects. Historically, they were identified based on morphological characteristics, but technological advancements such as polymerase chain reaction (PCR) and DNA sequencing now enable more accurate identification and taxonomy, and higher-level classifications. However, some species, referred to as "dark taxa", lack distinct physical features that makes their identification challenging. High-throughput sequencing and metagenomics of environmental samples provide a solution to identifying new lineages of fungi. This paper discusses different approaches to taxonomy, including PCR amplification and sequencing of rDNA, multi-loci phylogenetic analyses, and the importance of various omics (large-scale molecular) techniques for understanding fungal applications. The use of proteomics, transcriptomics, metatranscriptomics, metabolomics, and interactomics provides a comprehensive understanding of fungi. These advanced technologies are critical for expanding the knowledge of the Kingdom of Fungi, including its impact on food safety and security, edible mushrooms foodomics, fungal secondary metabolites, mycotoxin-producing fungi, and biomedical and therapeutic applications, including antifungal drugs and drug resistance, and fungal omics data for novel drug development. The paper also highlights the importance of exploring fungi from extreme environments and understudied areas to identify novel lineages in the fungal dark taxa.

Physicochemical Properties and Bacterial Community Profiling of Optimal Mahewu (A Fermented Food Product) Prepared Using White and Yellow Maize with Different Inocula

Mahewu is a fermented food product from maize, commonly consumed in Southern Africa. This study investigated the effect of optimizing fermentation (time and temperature) and boiling time of white maize (WM) and yellow maize (YM) mahewu, with the use of the Box–Behnken-response surface methodology (RSM). Fermentation time and temperature as well as boiling time were optimized and pH, total titratable acidity (TTA) and total soluble solids (TSS) determined. Results obtained showed that the processing conditions significantly (p ≤ 0.05) influenced the physicochemical properties. pH values of the mahewu samples ranged between 3.48–5.28 and 3.50–4.20 for YM mahewu and WM mahewu samples, respectively. Reduction in pH values after fermentation coincided with an increase in TTA as well as changes in the TSS values. Using the numerical multi-response optimisation of three investigated responses the optimal fermentation conditions were observed to be 25 °C for 54 h and a boiling time of 19 min for white maize mahewu and 29 °C for 72 h and a boiling time of 13 min for yellow maize mahewu. Thereafter white and yellow maize mahewu were prepared with the optimized conditions using different inocula (sorghum malt flour, wheat flour, millet malt flour or maize malt flour) and the pH, TTA and TSS of the derived mahewu samples determined. Additionally, amplicon sequencing of the 16S rRNA gene was used to characterise the relative abundance of bacterial genera in optimized mahewu samples, malted grains as well as flour samples. Major bacterial genera observed in the mahewu samples included Paenibacillus, Stenotrophomonas, Weissella, Pseudomonas, Lactococcus, Enterococcus, Lactobacillus, Bacillus, Massilia, Clostridium sensu stricto 1, Streptococcus, Staphylococcus, Sanguibacter, Roseococcus, Leuconostoc, Cutibacterium, Brevibacterium, Blastococcus, Sphingomonas and Pediococcus, with variations noted for YM mahewu and WM mahewu. As a result, the variations in physicochemical properties are due to differences in maize type and modification in processing conditions. This study also discovered the existence of variety of bacterial that can be isolated for controlled fermentation of mahewu.

Understanding of food biofilms by the application of omics techniques

Biofilms constitute a protective barrier for foodborne pathogens to survive under stressful food processing conditions. Therefore, studies into the development and control of biofilms by novel techniques are vital for the food industry. In recent years, foodomics techniques have been developed for biofilm studies, which contributed to a better understanding of biofilm behavior, physiology, composition, as well as their response to antibiofilm methods at different molecular levels including genes, RNA, proteins and metabolic metabolites. Throughout this review, the main studies where foodomics tools used to explore the mechanisms for biofilm formation, dispersal and elimination were reviewed. The data summarized from relevant studies are important to design novel and appropriate biofilm elimination methods for enhancing food safety at any point of food processing lines.

Problem formulation and phenotypic characterisation for the development of novel crops

Phenotypic characterisation provides important information about novel crops that helps their developers to make technical and commercial decisions. Phenotypic characterisation comprises two activities. Product characterisation checks that the novel crop has the qualities of a viable product-the intended traits have been introduced and work as expected, and no unintended changes have been made that will adversely affect the performance of the final product. Risk assessment evaluates whether the intended and unintended changes are likely to harm human health or the environment. Product characterisation follows the principles of problem formulation, namely that the characteristics required in the final product are defined and criteria to decide whether the novel crop will have these properties are set. The hypothesis that the novel crop meets the criteria are tested during product development. If the hypothesis is corroborated, development continues, and if the hypothesis is falsified, the product is redesigned or its development is halted. Risk assessment should follow the same principles. Criteria that indicate the crop poses unacceptable risk should be set, and the hypothesis that the crop does not possess those properties should be tested. However, risk assessment, particularly when considering unintended changes introduced by new plant breeding methods such as gene editing, often ignores these principles. Instead, phenotypic characterisation seeks to catalogue all unintended changes by profiling methods and then proceeds to work out whether any of the changes are important. This paper argues that profiling is an inefficient and ineffective method of phenotypic characterisation for risk assessment. It discusses reasons why profiling is favoured and corrects some misconceptions about problem formulation.

Using problem formulation to clarify the meaning of weight of evidence and biological relevance in environmental risk assessments for genetically modified crops

Weight of evidence and biological relevance are important concepts for risk assessment and decision-making over the use of GM crops; however, their meanings are not well defined. We use problem formulation to clarify the definition of these concepts and thereby identify data that are relevant for risk assessment. Problem formulation defines criteria for the acceptability of risk and devises rigorous tests of the hypothesis that the criteria are met. Corroboration or falsification of such hypotheses characterize risk and enable predictable and transparent decisions about whether certain risks from using a particular GM crop are acceptable. Decisions based on a weight of evidence approach use a synthesis of several lines of evidence, whereas a "definitive" approach to risk assessment enables some decisions to be based on the results of a single test. Data are biologically relevant for risk assessment only if they test a hypothesis that is useful for decision-making.

Food Authentication: Small-Molecule Profiling as a Tool for the Geographic Discrimination of German White Asparagus

For the first time, a non-targeted metabolomics approach by means of ultraperformance liquid chromatography coupled to electrospray quadruple time-of-flight mass spectrometry was chosen for the discrimination of geographical origins of white asparagus samples ( Asparagus officinalis). Over a period of four harvesting periods (4 years), approximately 400 asparagus samples were measured. Initially, four different liquid chromatography-mass spectrometry methods were used to detect as many metabolites as possible and to assess which method is most suitable. The most relevant marker compounds were linked to the influence of different plant stress parameters and climate effects. Some of the samples were also analyzed by isotope-ratio mass spectrometry (IRMS), which is the current gold standard for the discrimination of the geographical origin of asparagus. In summary, the analysis of the metabolome was proven to be quite suitable to determine the geographical origin of asparagus and seems to provide better interpretable results than IRMS studies.

Functional Metabolomics—A Useful Tool to Characterize Stress-Induced Metabolome Alterations Opening New Avenues towards Tailoring Food Crop Quality

The breeding of stress-tolerant cultivated plants that would allow for a reduction in harvest losses and undesirable decrease in quality attributes requires a new quality of knowledge on molecular markers associated with relevant agronomic traits, on quantitative metabolic responses of plants to stress challenges, and on the mechanisms controlling the biosynthesis of these molecules. By combining metabolomics with genomics, transcriptomics and proteomics datasets a more comprehensive knowledge of the composition of crop plants used for food or animal feed is possible. In order to optimize crop trait developments, to enhance crop yields and quality, as well as to guarantee nutritional and health factors that provide the possibility to create functional food or feedstuffs, knowledge about the plants’ metabolome is crucial. Next to classical metabolomics studies, this review focuses on several metabolomics-based working techniques, such as sensomics, lipidomics, hormonomics and phytometabolomics, which were used to characterize metabolome alterations during abiotic and biotic stress in order to find resistant food crops with a preferred quality or at least to produce functional food crops.

Identification of Aging-Associated Food Quality Changes in Citrus Products Using Untargeted Chemical Profiling

Chemometric techniques have seen wide application in biological and medical sciences, but they are still developing in the food sciences. This study illustrated the use of untargeted LC/MS chemometric methods to identify features (retention time_m/z) associated with food quality changes as products age (freshness). Extracts of three citrus fruit varietals aged over four time points that corresponded to noted changes in sensory attributes were chemically profiled and modeled by two discriminatory multivariate statistical techniques, projection partial least-squares discrimant analysis (PLS-DA) and machine learning random forest (RF). Age-associated compounds across the citrus platform were identified. Varietal was treated as a nuisance variable to emphasize aging chemistry, and further variable selection using age-related piecewise model generation and meta filtering to emphasize features associated with general aging chemistry common to all the citrus extracts. The identified features were further replicated in a validation study to illustrate the validity and persistence of these markers for applications in citrus food platforms.

Effect of Genetics, Environment, and Phenotype on the Metabolome of Maize Hybrids Using GC/MS and LC/MS

We evaluated the variability of metabolites in various maize hybrids due to the effect of environment, genotype, phenotype as well as the interaction of the first two factors. We analyzed 480 forage and the same number of grain samples from 21 genetically diverse non-GM Pioneer brand maize hybrids, including some with drought tolerance and viral resistance phenotypes, grown at eight North American locations. As complementary platforms, both GC/MS and LC/MS were utilized to detect a wide diversity of metabolites. GC/MS revealed 166 and 137 metabolites in forage and grain samples, respectively, while LC/MS captured 1341 and 635 metabolites in forage and grain samples, respectively. Univariate and multivariate analyses were utilized to investigate the response of the maize metabolome to the environment, genotype, phenotype, and their interaction. Based on combined percentages from GC/MS and LC/MS datasets, the environment affected 36% to 84% of forage metabolites, while less than 7% were affected by genotype. The environment affected 12% to 90% of grain metabolites, whereas less than 27% were affected by genotype. Less than 10% and 11% of the metabolites were affected by phenotype in forage and grain, respectively. Unsupervised PCA and HCA analyses revealed similar trends, i.e., environmental effect was much stronger than genotype or phenotype effects. On the basis of comparisons of disease tolerant and disease susceptible hybrids, neither forage nor grain samples originating from different locations showed obvious phenotype effects. Our findings demonstrate that the combination of GC/MS and LC/MS based metabolite profiling followed by broad statistical analysis is an effective approach to identify the relative impact of environmental, genetic and phenotypic effects on the forage and grain composition of maize hybrids.

Molecular responses of genetically modified maize to abiotic stresses as determined through proteomic and metabolomic analyses

Some genetically modified (GM) plants have transgenes that confer tolerance to abiotic stressors. Meanwhile, other transgenes may interact with abiotic stressors, causing pleiotropic effects that will affect the plant physiology. Thus, physiological alteration might have an impact on the product safety. However, routine risk assessment (RA) analyses do not evaluate the response of GM plants exposed to different environmental conditions. Therefore, we here present a proteome profile of herbicide-tolerant maize, including the levels of phytohormones and related compounds, compared to its near-isogenic non-GM variety under drought and herbicide stresses. Twenty differentially abundant proteins were detected between GM and non-GM hybrids under different water deficiency conditions and herbicide sprays. Pathway enrichment analysis showed that most of these proteins are assigned to energetic/carbohydrate metabolic processes. Among phytohormones and related compounds, different levels of ABA, CA, JA, MeJA and SA were detected in the maize varieties and stress conditions analysed. In pathway and proteome analyses, environment was found to be the major source of variation followed by the genetic transformation factor. Nonetheless, differences were detected in the levels of JA, MeJA and CA and in the abundance of 11 proteins when comparing the GM plant and its non-GM near-isogenic variety under the same environmental conditions. Thus, these findings do support molecular studies in GM plants Risk Assessment analyses.

Evaluation of metabolomics profiles of grain from maize hybrids derived from near-isogenic GM positive and negative segregant inbreds demonstrates that observed differences cannot be attributed unequivocally to the GM trait

INTRODUCTION

Past studies on plant metabolomes have highlighted the influence of growing environments and varietal differences in variation of levels of metabolites yet there remains continued interest in evaluating the effect of genetic modification (GM).

OBJECTIVES

Here we test the hypothesis that metabolomics differences in grain from maize hybrids derived from a series of GM (NK603, herbicide tolerance) inbreds and corresponding negative segregants can arise from residual genetic variation associated with backcrossing and that the effect of insertion of the GM trait is negligible.

METHODS

Four NK603-positive and negative segregant inbred males were crossed with two different females (testers). The resultant hybrids, as well as conventional comparator hybrids, were then grown at three replicated field sites in Illinois, Minnesota, and Nebraska during the 2013 season. Metabolomics data acquisition using gas chromatography-time of flight-mass spectrometry (GC-TOF-MS) allowed the measurement of 367 unique metabolite features in harvested grain, of which 153 were identified with small molecule standards. Multivariate analyses of these data included multi-block principal component analysis and ANOVA-simultaneous component analysis. Univariate analyses of all 153 identified metabolites was conducted based on significance testing (α = 0.05), effect size evaluation (assessing magnitudes of differences), and variance component analysis.

RESULTS

Results demonstrated that the largest effects on metabolomic variation were associated with different growing locations and the female tester. They further demonstrated that differences observed between GM and non-GM comparators, even in stringent tests utilizing near-isogenic positive and negative segregants, can simply reflect minor genomic differences associated with conventional back-crossing practices.

CONCLUSION

The effect of GM on metabolomics variation was determined to be negligible and supports that there is no scientific rationale for prioritizing GM as a source of variation.

Comparative Proteomic Analysis of Two Varieties of Genetically Modified (GM) Embrapa 5.1 Common Bean (Phaseolus vulgaris L.) and Their Non-GM Counterparts

The genetically modified (GM) common bean event Embrapa 5.1 was commercially approved in Brazil in 2011; it is resistant to golden mosaic virus infection. In the present work grain proteome profiles of two Embrapa 5.1 common bean varieties, Pérola and Pontal, and their non-GM counterparts were compared by two-dimensional gel electrophoresis (2-DE) followed by mass spectrometry (MS). Analyses detected 23 spots differentially accumulated between GM Pérola and non-GM Pérola and 21 spots between GM Pontal and non-GM Pontal, although they were not the same proteins in Pérola and Pontal varieties, indicating that the variability observed may not be due to the genetic transformation. Among them, eight proteins were identified in Pérola varieties, and four proteins were identified in Pontal. Moreover, we applied principal component analysis (PCA) on 2-DE data, and variation between varieties was explained in the first two principal components. This work provides a first 2-DE-MS/MS-based analysis of Embrapa 5.1 common bean grains.

Modifying glycoalkaloid content in transgenic potato--Metabolome impacts

Metabolite profiling has been used to assess the potential for unintended composition changes in potato (Solanum tuberosum L. cv. Desirée) tubers, which have been genetically modified (GM) to reduce glycoalkaloid content, via the independent down-regulation of three genes SGT1, SGT2 and SGT3 known to be involved in glycoalkaloid biosynthesis. Differences between the three groups of antisense lines and control lines were assessed using liquid chromatography-mass spectrometry (LC-MS) and gas chromatography (GC)-MS, and data analysed using principal component analysis and analysis of variance. Compared with the wild-type (WT) control, LC-MS revealed not only the expected changes in specific glycoalkaloid levels in the GM lines, but also significant changes in several other metabolites, some of which were explicable in terms of known pathways. Analysis of polar and non-polar metabolites by GC-MS revealed other significant (unintended) differences between SGT lines and the WT, but also between the WT control and other control lines used.

Effect of stacking insecticidal cry and herbicide tolerance epsps transgenes on transgenic maize proteome

BACKGROUND

The safe use of stacked transgenic crops in agriculture requires their environmental and health risk assessment, through which unintended adverse effects are examined prior to their release in the environment. Molecular profiling techniques can be considered useful tools to address emerging biosafety gaps. Here we report the first results of a proteomic profiling coupled to transgene transcript expression analysis of a stacked commercial maize hybrid containing insecticidal and herbicide tolerant traits in comparison to the single event hybrids in the same genetic background.

RESULTS

Our results show that stacked genetically modified (GM) genotypes were clustered together and distant from other genotypes analyzed by PCA. Twenty-two proteins were shown to be differentially modulated in stacked and single GM events versus non-GM isogenic maize and a landrace variety with Brazilian genetic background. Enrichment analysis of these proteins provided insight into two major metabolic pathway alterations: energy/carbohydrate and detoxification metabolism. Furthermore, stacked transgene transcript levels had a significant reduction of about 34% when compared to single event hybrid varieties.

CONCLUSIONS

Stacking two transgenic inserts into the genome of one GM maize hybrid variety may impact the overall expression of endogenous genes. Observed protein changes differ significantly from those of single event lines and a conventional counterpart. Some of the protein modulation did not fall within the range of the natural variability for the landrace used in this study. Higher expression levels of proteins related to the energy/carbohydrate metabolism suggest that the energetic homeostasis in stacked versus single event hybrid varieties also differ. Upcoming global databases on outputs from "omics" analyses could provide a highly desirable benchmark for the safety assessment of stacked transgenic crop events. Accordingly, further studies should be conducted in order to address the biological relevance and implications of such changes.

Risk assessment, formation, and mitigation of dietary acrylamide: current status and future prospects

Acrylamide (AA) was firstly detected in food in 2002, and since then, studies on AA analysis, occurrence, formation, toxicity, risk assessment and mitigation have been extensively carried out, which have greatly advanced understanding of this particular biohazard at both academic and industrial levels. There is considerable variation in the levels of AA in different foods and different brands of the same food; therefore, so far, a general upper limit for AA in food is not available. In addition, the link of dietary AA to human cancer is still under debate, although AA has been known as a potential cause of various toxic effects including carcinogenic effects in experimental animals. Furthermore, the oxidized metabolite of AA, glycidamide (GA), is more toxic than AA. Both AA and GA can form adducts with protein, DNA, and hemoglobin, and some of those adducts can serve as biomarkers for AA exposure; their potential roles in the linking of AA to human cancer, reproductive defects or other diseases, however, are unclear. This review addresses the state-of-the-art understanding of AA, focusing on risk assessment, mechanism of formation and strategies of mitigation in foods. The potential application of omics to AA risk assessment is also discussed.

Analytical method evaluation and discovery of variation within maize varieties in the context of food safety: transcript profiling and metabolomics

Profiling techniques such as microarrays, proteomics, and metabolomics are used widely to assess the overall effects of genetic background, environmental stimuli, growth stage, or transgene expression in plants. To assess the potential regulatory use of these techniques in agricultural biotechnology, we carried out microarray and metabolomic studies of 3 different tissues from 11 conventional maize varieties. We measured technical variations for both microarrays and metabolomics, compared results from individual plants and corresponding pooled samples, and documented variations detected among different varieties with individual plants or pooled samples. Both microarray and metabolomic technologies are reproducible and can be used to detect plant-to-plant and variety-to-variety differences. A pooling strategy lowered sample variations for both microarray and metabolomics while capturing variety-to-variety variation. However, unknown genomic sequences differing between maize varieties might hinder the application of microarrays. High-throughput metabolomics could be useful as a tool for the characterization of transgenic crops. However, researchers will have to take into consideration the impact on the detection and quantitation of a wide range of metabolites on experimental design as well as validation and interpretation of results.

Sequencing, characterization, and gene expression analysis of the histidine decarboxylase gene cluster of Morganella morganii

The histidine decarboxylase gene cluster of Morganella morganii DSM30146(T) was sequenced, and four open reading frames, named hdcT1, hdc, hdcT2, and hisRS were identified. Two putative histidine/histamine antiporters (hdcT1 and hdcT2) were located upstream and downstream the hdc gene, codifying a pyridoxal-P dependent histidine decarboxylase, and followed by hisRS gene encoding a histidyl-tRNA synthetase. This organization was comparable with the gene cluster of other known Gram negative bacteria, particularly with that of Klebsiella oxytoca. Recombinant Escherichia coli strains harboring plasmids carrying the M. morganii hdc gene were shown to overproduce histidine decarboxylase, after IPTG induction at 37 °C for 4 h. Quantitative RT-PCR experiments revealed the hdc and hisRS genes were highly induced under acidic and histidine-rich conditions. This work represents the first description and identification of the hdc-related genes in M. morganii. Results support the hypothesis that the histidine decarboxylation reaction in this prolific histamine producing species may play a role in acid survival. The knowledge of the role and the regulation of genes involved in histidine decarboxylation should improve the design of rational strategies to avoid toxic histamine production in foods.

Food safety: importance of composition for assessing genetically modified cassava (Manihot esculenta Crantz)

The importance of food composition in safety assessments of genetically modified (GM) food is described for cassava ( Manihot esculenta Crantz) that naturally contains significantly high levels of cyanogenic glycoside (CG) toxicants in roots and leaves. The assessment of the safety of GM cassava would logically require comparison with a non-GM crop with a proven "history of safe use". This study investigates this statement for cassava. A non-GM comparator that qualifies would be a processed product with CG level below the approved maximum level in food and that also satisfies a "worst case" of total dietary consumption. Although acute and chronic toxicity benchmark CG values for humans have been determined, intake data are scarce. Therefore, the non-GM cassava comparator is defined on the "best available knowledge". We consider nutritional values for cassava and conclude that CG residues in food should be a priority topic for research.

Application of absolute qPCR as a screening method to detect illicit 17β-oestradiol administration in male cattle

It has been previously demonstrated that the progesterone receptor gene is up-regulated in the sex accessory glands of pre-pubertal and adult male bovines after 17β-oestradiol treatment. In the present study, a qualitative screening method was optimised to detect 17β-oestradiol treatment using absolute quantification by qPCR of the progesterone receptor gene to determine the amount of gene expression in bulbo-urethral glands. An external standard curve was generated and developed with TaqMan® technology. Based on two in vivo experiments, the decision limit CCα, sensitivity and specificity of this screening method were established. Trial 1 consisted of 32 Friesian veal calves divided into two groups: group A (n = 12), consisting of animals treated with four doses of 17β-oestradiol (5 mg week(-1) per animal); and group B (n = 20), consisting of control animals. Trial 2 was performed on 26 Charolaise beef cattle that either received five doses of 17β-oestradiol (group C; 20 mg week(-1) per animal; n = 6) or remained untreated (group D; n = 20). Further, progesterone receptor gene expression was evaluated in beef and veal calves for human consumption. A specific CCα on 20 Piedmontese control beef cattle was calculated to include these animals in a field investigation. Five out of 190 beef cattle and 26 out of 177 calves tested expressed the progesterone receptor gene above their respective CCα and they were classified as being suspected of 17β-oestradiol treatment. Additionally, 58% of veal calves that tested suspect via qPCR exhibited histological lesions of the bulbo-urethral gland tissue, which are typical of oestrogen administration and are consistent with hyperplasia and metaplasia of the glandular epithelium.

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.

Review of current and "omics" methods for assessing the toxicity (genotoxicity, teratogenicity and nephrotoxicity) of herbal medicines and mushrooms

ETHNOPHARMACOLOGICAL RELEVANCE

The increasing use of traditional herbal medicines around the world requires more scientific evidence for their putative harmlessness. To this end, a plethora of methods exist, more or less satisfying. In this post-genome era, recent reviews are however scarce, not only on the use of new "omics" methods (transcriptomics, proteomics, metabonomics) for genotoxicity, teratogenicity, and nephrotoxicity assessment, but also on conventional ones.

METHODS

The present work aims (i) to review conventional methods used to assess genotoxicity, teratogenicity and nephrotoxicity of medicinal plants and mushrooms; (ii) to report recent progress in the use of "omics" technologies in this field; (iii) to underline advantages and limitations of promising methods; and lastly (iv) to suggest ways whereby the genotoxicity, teratogenicity, and nephrotoxicity assessment of traditional herbal medicines could be more predictive.

RESULTS

Literature and safety reports show that structural alerts, in silico and classical in vitro and in vivo predictive methods are often used. The current trend to develop "omics" technologies to assess genotoxicity, teratogenicity and nephrotoxicity is promising but most often relies on methods that are still not standardized and validated.

CONCLUSION

Hence, it is critical that toxicologists in industry, regulatory agencies and academic institutions develop a consensus, based on rigorous methods, about the reliability and interpretation of endpoints. It will also be important to regulate the integration of conventional methods for toxicity assessments with new "omics" technologies.

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.

Comparability of imazapyr-resistant Arabidopsis created by transgenesis and mutagenesis

The Arabidopsis CSR1 gene codes for the enzyme acetohydroxyacid synthase (AHAS, EC 2.2.1.6), also known as acetolactate synthase, which catalyzes the first step in branched-chain amino acid biosynthesis. It is inhibited by several classes of herbicides, including the imidazolinone herbicides, such as imazapyr; however, a substitution mutation in csr1-2 (Ser-653-Asn) confers selective resistance to the imidazolinones. The transcriptome of csr1-2 seedlings grown in the presence of imazapyr has been shown in a previous study (Manabe in Plant Cell Physiol 48:1340-1358, 2007) to be identical to that of wild-type seedlings indicating that AHAS is the sole target of imazapyr and that the mutation is not associated with pleiotropic effects detectable by transcriptome analysis. In this study, a lethal null mutant, csr1-7, created by a T-DNA insertion into the CSR1 gene was complemented with a randomly-inserted 35S/CSR1-2/NOS transgene in a subsequent genetic transformation event. A comparison of the csr1-2 substitution mutant with the transgenic lines revealed that all were resistant to imazapyr; however, the transgenic lines yielded significantly higher levels of resistance and greater biomass accumulation in the presence of imazapyr. Microarray analysis revealed few differences in their transcriptomes. The most notable was a sevenfold to tenfold elevation in the CSR1-2 transcript level. The data indicate that transgenesis did not create significant unintended pleiotropic effects on gene expression and that the mutant and transgenic lines were highly similar, except for the level of herbicide resistance.

Molecular profiling--a tool for addressing emerging gaps in the comparative risk assessment of GMOs

Assessing the risks of genetically modified organisms (GMOs) is required by both international agreement and domestic legislation. Many view the use of the "omics" tools for profiling classes of molecules as useful in risk assessment, but no consensus has formed on the need or value of these techniques for assessing the risks of all GMOs. In this and many other cases, experts support case-by-case use of molecular profiling techniques for risk assessment. We review the latest research on the applicability and usefulness of molecular profiling techniques for GMO risk assessment. As more and more kinds of GMOs and traits are developed, broader use of molecular profiling in a risk assessment may be required to supplement the comparative approach to risk assessment. The literature-based discussions on the use of profiling appear to have settled on two findings: 1. profiling techniques are reliable and relevant, at least no less so than other techniques used in risk assessment; and 2. although not required routinely, regulators should be aware of when they are needed. The dismissal of routine molecular profiling may be confusing to regulators who then lack guidance on when molecular profiling might be worthwhile. Molecular profiling is an important way to increase confidence in risk assessments if the profiles are properly designed to address relevant risks and are applied at the correct stage of the assessment.

Plant natural variability may affect safety assessment data

Before market introduction, genetic engineered (GE) food products, like any other novel food product, are subjected to extensive assessment of their potential effects on human health. In recent years, a number of profiling technologies have been explored aiming to increase the probability of detecting any unpredictable unintended effect and, consequently improving the efficiency of GE food safety assessment. These techniques still present limitations associated with the interpretation of the observed differences with respect to their biological relevance and toxicological significance. In order to address this issue, in this study, we have performed 2D-gel electrophoresis of five different ears of five different MON810 maize plants and of other five of the non-transgenic near-isogenic line. We have also performed 2D-gel electrophoresis of the pool of the five protein extractions of MON810 and control lines. We have notice that, in this example, the exclusive use of data from 2D-electrophoresed pooled samples, to compare these two lines, would be insufficient for an adequate safety evaluation. We conclude that, when using "omics" technologies, it is extremely important to eliminate all potential differences due to factors not related to the ones under study, and to understand the role of natural plant-to-plant variability in the encountered differences.