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BACKGROUND AND AIMS: Despite differences in physiology between dry and relative moist seeds, seed ageing tests most often use a temperature and seed moisture level that are higher than during dry storage used in commercial practice and gene banks. This study aimed to test whether seed ageing under dry conditions can be accelerated by storing under high-pressure oxygen. methods: Dry barley (Hordeum vulgare), cabbage (Brassica oleracea), lettuce (Lactuca sativa) and soybean (Glycine max) seeds were stored between 2 and 7 weeks in steel tanks under 18 MPa partial pressure of oxygen. Storage under high-pressure nitrogen gas or under ambient air pressure served as controls. The method was compared with storage at 45 °C after equilibration at 85 % relative humidity and long-term storage at the laboratory bench. Germination behaviour, seedling morphology and tocopherol levels were assessed. KEY RESULTS: The ageing of the dry seeds was indeed accelerated by storing under high-pressure oxygen. The morphological ageing symptoms of the stored seeds resembled those observed after ageing under long-term dry storage conditions. Barley appeared more tolerant of this storage treatment compared with lettuce and soybean. Less-mature harvested cabbage seeds were more sensitive, as was the case for primed compared with non-primed lettuce seeds. Under high-pressure oxygen storage the tocopherol levels of dry seeds decreased, in a linear way with the decline in seed germination, but remained unchanged in seeds deteriorated during storage at 45 °C after equilibration at 85 % RH. CONCLUSIONS: Seed storage under high-pressure oxygen offers a novel and relatively fast method to study the physiology and biochemistry of seed ageing at different seed moisture levels and temperatures, including those that are representative of the dry storage conditions as used in gene banks and commercial practice.
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Brassica/fisiologia , Glycine max/fisiologia , Hordeum/fisiologia , Lactuca/fisiologia , Oxigênio/efeitos adversos , Sementes/fisiologia , Brassica/anatomia & histologia , Germinação , Hordeum/anatomia & histologia , Temperatura Alta , Umidade , Lactuca/anatomia & histologia , Nitrogênio/efeitos adversos , Pressão Parcial , Raízes de Plantas/anatomia & histologia , Raízes de Plantas/fisiologia , Plântula/anatomia & histologia , Plântula/fisiologia , Sementes/anatomia & histologia , Glycine max/anatomia & histologia , Fatores de Tempo , Tocoferóis/análise , Água/fisiologiaRESUMO
MOTIVATION: Matching both the retention index (RI) and the mass spectrum of an unknown compound against a mass spectral reference library provides strong evidence for a correct identification of that compound. Data on retention indices are, however, available for only a small fraction of the compounds in such libraries. We propose a quantitative structure-RI model that enables the ranking and filtering of putative identifications of compounds for which the predicted RI falls outside a predefined window. RESULTS: We constructed multiple linear regression and support vector regression (SVR) models using a set of descriptors obtained with a genetic algorithm as variable selection method. The SVR model is a significant improvement over previous models built for structurally diverse compounds as it covers a large range (360-4100) of RI values and gives better prediction of isomer compounds. The hit list reduction varied from 41% to 60% and depended on the size of the original hit list. Large hit lists were reduced to a greater extend compared with small hit lists. AVAILABILITY: http://appliedbioinformatics.wur.nl/GC-MS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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Biologia Computacional/métodos , Cromatografia Gasosa-Espectrometria de Massas/métodos , Metabolômica/métodos , Algoritmos , Modelos LinearesRESUMO
INTRODUCTION: Metabolomics has become a valuable tool in many research areas. However, generating metabolomics-based biochemical profiles without any related bioactivity is only of indirect value in understanding a biological process. Therefore, metabolomics research could greatly benefit from tools that directly determine the bioactivity of the detected compounds. OBJECTIVE: We aimed to combine LC-MS metabolomics with a cell based receptor assay. This combination could increase the understanding of biological processes and may provide novel opportunities for functional metabolomics. METHODS: We developed a flow through biosensor with human cells expressing both the TRPV1, a calcium ion channel which responds to capsaicin, and the fluorescent intracellular calcium ion reporter, YC3.6. We have analysed three contrasting Capsicum varieties. Two were selected with contrasting degrees of spiciness for characterization by HPLC coupled to high mass resolution MS. Subsequently, the biosensor was then used to link individual pepper compounds with TRPV1 activity. RESULTS: Among the compounds in the crude pepper fruit extracts, we confirmed capsaicin and also identified both nordihydrocapsaicin and dihydrocapsaicin as true agonists of the TRPV1 receptor. Furthermore, the biosensor was able to detect receptor activity in extracts of both Capsicum fruits as well as a commercial product. Sensitivity of the biosensor to this commercial product was similar to the sensory threshold of a human sensory panel. CONCLUSION: Our results demonstrate that the TRPV1 biosensor is suitable for detecting bioactive metabolites. Novel opportunities may lie in the development of a continuous functional assay, where the biosensor is directly coupled to the LC-MS.
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The quality of rice in terms not only of its nutritional value but also in terms of its aroma and flavour is becoming increasingly important in modern rice breeding where global targets are focused on both yield stability and grain quality. In the present paper we have exploited advanced, multi-platform metabolomics approaches to determine the biochemical differences in 31 rice varieties from a diverse range of genetic backgrounds and origin. All were grown under the specific local conditions for which they have been bred and all aspects of varietal identification and sample purity have been guaranteed by local experts from each country. Metabolomics analyses using 6 platforms have revealed the extent of biochemical differences (and similarities) between the chosen rice genotypes. Comparison of fragrant rice varieties showed a difference in the metabolic profiles of jasmine and basmati varieties. However with no consistent separation of the germplasm class. Storage of grains had a significant effect on the metabolome of both basmati and jasmine rice varieties but changes were different for the two rice types. This shows how metabolic changes may help prove a causal relationship with developing good quality in basmati rice or incurring quality loss in jasmine rice in aged grains. Such metabolomics approaches are leading to hypotheses on the potential links between grain quality attributes, biochemical composition and genotype in the context of breeding for improvement. With this knowledge we shall establish a stronger, evidence-based foundation upon which to build targeted strategies to support breeders in their quest for improved rice varieties.
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The effects of conventional industrial processing steps on global phytochemical composition of broccoli, tomato and carrot purees were investigated by using a range of complementary targeted and untargeted metabolomics approaches including LC-PDA for vitamins, (1)H NMR for polar metabolites, accurate mass LC-QTOF MS for semi-polar metabolites, LC-MRM for oxylipins, and headspace GC-MS for volatile compounds. An initial exploratory experiment indicated that the order of blending and thermal treatments had the highest impact on the phytochemicals in the purees. This blending-heating order effect was investigated in more depth by performing alternate blending-heating sequences in triplicate on the same batches of broccoli, tomato and carrot. For each vegetable and particularly in broccoli, a large proportion of the metabolites detected in the purees was significantly influenced by the blending-heating order, amongst which were potential health-related phytochemicals and flavour compounds like vitamins C and E, carotenoids, flavonoids, glucosinolates and oxylipins. Our metabolomics data indicates that during processing the activity of a series of endogenous plant enzymes, such as lipoxygenases, peroxidases and glycosidases, including myrosinase in broccoli, is key to the final metabolite composition and related quality of the purees.
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Manipulação de Alimentos , Metabolômica , Verduras/química , Ácido Ascórbico/análise , Brassica/química , Carotenoides/análise , Cromatografia Líquida , Daucus carota/química , Flavonoides/análise , Cromatografia Gasosa-Espectrometria de Massas , Solanum lycopersicum/química , Espectrometria de Massas , Compostos Fitoquímicos/análiseRESUMO
Thermal processing of Brassica vegetables can lead to substantial loss of potential health-promoting glucosinolates (GLs). The extent of thermal degradation of a specific GL varies in different vegetables, possibly due to differences in the composition of other metabolites within the plant matrices. An untargeted metabolomics approach followed by random forest regression was applied to identify metabolites associated to thermal GL degradation in a segregating Brassica oleracea population. Out of 413 metabolites, 15 were associated with the degradation of glucobrassicin, six with that of glucoraphanin and two with both GLs. Among these 23 metabolites three were identified as flavonols (one kaempferol- and two quercetin-derivatives) and two as other GLs (4-methoxyglucobrassicin, gluconasturtiin). Twenty quantitative trait loci (QTLs) for these metabolites, which were associated with glucoraphanin and glucobrassicin degradation, were identified on linkage groups C01, C07 and C09. Two flavonols mapped on linkage groups C07 and C09 and co-localise with the QTL for GL degradation determined previously.
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Brassica/química , Glucosinolatos/química , Verduras/química , Brassica/genética , Brassica/metabolismo , Culinária , Glucosinolatos/metabolismo , Temperatura Alta , Cinética , Metabolômica , Locos de Características Quantitativas , Verduras/genética , Verduras/metabolismoRESUMO
Mass peak alignment (ion-wise alignment) has recently become a popular method for unsupervised data analysis in untargeted metabolic profiling. Here we present MSClust-a software tool for analysis GC-MS and LC-MS datasets derived from untargeted profiling. MSClust performs data reduction using unsupervised clustering and extraction of putative metabolite mass spectra from ion-wise chromatographic alignment data. The algorithm is based on the subtractive fuzzy clustering method that allows unsupervised determination of a number of metabolites in a data set and can deal with uncertain memberships of mass peaks in overlapping mass spectra. This approach is based purely on the actual information present in the data and does not require any prior metabolite knowledge. MSClust can be applied for both GC-MS and LC-MS alignment data sets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0368-2) contains supplementary material, which is available to authorized users.