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Biomedical subjects

Raoul J Bino

Publications and source records attributed to Raoul J Bino.

9 recordsLinked to original sources
PubMed2006

A comparative study on the effect of algal and fish oil on viability and cell proliferation of Caco-2 cells.

Polyunsaturated fatty acid (PUFA) rich micro-algal oil was tested in vitro and compared with fish oil for antiproliferative properties on cancer cells in vitro. Oils derived from Crypthecodinium cohnii, Schizochytrium sp. and Nitzschia laevis, three commercial algal oil capsules, and menhaden fish oil were used in cell viability and proliferation tests with human colon adenocarcinoma Caco-2 cells. With these tests no difference was found between algal oil and fish oil. The nonhydrolysed algal oils and fish oil showed a much lower toxic effect on cell viability, and cell proliferation in Caco-2 cells than the hydrolysed oils and the free fatty acids (FFAs). Eicosapentaenoic acid (EPA; C20:5n-3) and docosahexaenoic acid (DHA; C22:6n-3) were used as samples for comparison with the tested hydrolysed and nonhydrolysed oils. The hydrolysed samples showed comparative toxicity as the free fatty acids and no difference between algal and fish oil. Oxidative stress was shown to play a role in the antiproliferative properties of EPA and DHA, as alpha-tocopherol could partially reverse the EPA/DHA-induced effects. The results of the present study support a similar mode of action of algal oil and fish oil on cancer cells in vitro, in spite of their different PUFA content.

Antioxidants↗
PubMed2006

The genetics of plant metabolism.

Variation for metabolite composition and content is often observed in plants. However, it is poorly understood to what extent this variation has a genetic basis. Here, we describe the genetic analysis of natural variation in the metabolite composition in Arabidopsis thaliana. Instead of focusing on specific metabolites, we have applied empirical untargeted metabolomics using liquid chromatography-time of flight mass spectrometry (LC-QTOF MS). This uncovered many qualitative and quantitative differences in metabolite accumulation between A. thaliana accessions. Only 13.4% of the mass peaks were detected in all 14 accessions analyzed. Quantitative trait locus (QTL) analysis of more than 2,000 mass peaks, detected in a recombinant inbred line (RIL) population derived from the two most divergent accessions, enabled the identification of QTLs for about 75% of the mass signals. More than one-third of the signals were not detected in either parent, indicating the large potential for modification of metabolic composition through classical breeding.

Arabidopsis↗
PubMed2006

Alignment and statistical difference analysis of complex peptide data sets generated by multidimensional LC-MS.

A method for high-resolution proteomics analyses of complex protein mixtures is presented using multidimensional HPLC coupled to MS (MDLC-MS). The method was applied to identify proteins that are differentially expressed during fruit ripening of tomato. Protein extracts from red and green tomato fruits were digested by trypsin. The resulting highly complex peptide mixtures were separated by strong cation exchange chromatography (SCX), and subsequently analyzed by RP nano-LC coupled to quadrupole-TOF MS. For detailed quantitative comparison, triplicate RP-LC-MS runs were performed for each SCX fraction. The resulting data sets were analyzed using MetAlign software for noise and data reduction, multiple alignment and statistical variance analysis. For each RP-LC-MS chromatogram, up to 7000 mass components were detected. Peak intensity data were compared by multivariate and statistical analysis. This revealed a clear separation between the green and red tomato samples, and a clear separation of the different SCX fractions. MS/MS spectra were collected using the data-dependent acquisition mode from a selected set of differentially detected peptide masses, enabling the identification of proteins that were differentially expressed during ripening of tomato fruits. Our approach is a highly sensitive method to analyze proteins in complex mixtures without the need of isotope labeling.

Cation Exchange Resins↗
PubMed2006

A liquid chromatography-mass spectrometry-based metabolome database for tomato.

For the description of the metabolome of an organism, the development of common metabolite databases is of utmost importance. Here we present the Metabolome Tomato Database (MoTo DB), a metabolite database dedicated to liquid chromatography-mass spectrometry (LC-MS)- based metabolomics of tomato fruit (Solanum lycopersicum). A reproducible analytical approach consisting of reversed-phase LC coupled to quadrupole time-of-flight MS and photodiode array detection (PDA) was developed for large-scale detection and identification of mainly semipolar metabolites in plants and for the incorporation of the tomato fruit metabolite data into the MoTo DB. Chromatograms were processed using software tools for mass signal extraction and alignment, and intensity-dependent accurate mass calculation. The detected masses were assigned by matching their accurate mass signals with tomato compounds reported in literature and complemented, as much as possible, by PDA and MS/MS information, as well as by using reference compounds. Several novel compounds not previously reported for tomato fruit were identified in this manner and added to the database. The MoTo DB is available at http://appliedbioinformatics.wur.nl and contains all information so far assembled using this LC-PDA-quadrupole time-of-flight MS platform, including retention times, calculated accurate masses, PDA spectra, MS/MS fragments, and literature references. Unbiased metabolic profiling and comparison of peel and flesh tissues from tomato fruits validated the applicability of the MoTo DB, revealing that all flavonoids and alpha-tomatine were specifically present in the peel, while several other alkaloids and some particular phenylpropanoids were mainly present in the flesh tissue.

Chromatography, Liquid↗
PubMed2005

A novel approach for nontargeted data analysis for metabolomics. Large-scale profiling of tomato fruit volatiles.

To take full advantage of the power of functional genomics technologies and in particular those for metabolomics, both the analytical approach and the strategy chosen for data analysis need to be as unbiased and comprehensive as possible. Existing approaches to analyze metabolomic data still do not allow a fast and unbiased comparative analysis of the metabolic composition of the hundreds of genotypes that are often the target of modern investigations. We have now developed a novel strategy to analyze such metabolomic data. This approach consists of (1) full mass spectral alignment of gas chromatography (GC)-mass spectrometry (MS) metabolic profiles using the MetAlign software package, (2) followed by multivariate comparative analysis of metabolic phenotypes at the level of individual molecular fragments, and (3) multivariate mass spectral reconstruction, a method allowing metabolite discrimination, recognition, and identification. This approach has allowed a fast and unbiased comparative multivariate analysis of the volatile metabolite composition of ripe fruits of 94 tomato (Lycopersicon esculentum Mill.) genotypes, based on intensity patterns of >20,000 individual molecular fragments throughout 198 GC-MS datasets. Variation in metabolite composition, both between- and within-fruit types, was found and the discriminative metabolites were revealed. In the entire genotype set, a total of 322 different compounds could be distinguished using multivariate mass spectral reconstruction. A hierarchical cluster analysis of these metabolites resulted in clustering of structurally related metabolites derived from the same biochemical precursors. The approach chosen will further enhance the comprehensiveness of GC-MS-based metabolomics approaches and will therefore prove a useful addition to nontargeted functional genomics research.

Automation↗
PubMed2005

The light-hyperresponsive high pigment-2dg mutation of tomato: alterations in the fruit metabolome.

Overall metabolic modifications between fruit of light-hyperresponsive high-pigment (hp) tomato (Lycopersicon esculentum) mutant plants and isogenic nonmutant (wt) control plants were compared. Targeted metabolite analyses, as well as large-scale nontargeted mass spectrometry (MS)-based metabolite profiling, were used to phenotype the differences in fruit metabolite composition. Targeted high-performance liquid chromatography with photodiode array detection (HPLC-PDA) metabolite analyses showed higher levels of isoprenoids and phenolic compounds in hp-2dg fruit. Nontargeted GC-MS profiling of red fruits produced 25 volatile compounds that showed a 1.5-fold difference between the genotypes. Analyses of red fruits using HPLC coupled to high-resolution quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) in both ESI-positive and ESI-negative mode generated, respectively, 6168 and 5401 mass signals, of which 142 and 303 showed a twofold difference between the genotypes. hp-2dg fruits are characterized by overproduction of many metabolites, several of which are known for their antioxidant or photoprotective activities. These metabolites may now be more closely implicated as resources recruited by plants to respond to and manage light stress. The similarity in metabolic alterations in fruits of hp-1 and hp-2 mutant plants helps us to understand how hp mutations affect cellular processes.

Ascorbic Acid↗
PubMed2004

Gene expression programs during Brassica oleracea seed maturation, osmopriming, and germination are indicators of progression of the germination process and the stress tolerance level.

During seed maturation and germination, major changes in physiological status, gene expression, and metabolic events take place. Using chlorophyll sorting, osmopriming, and different drying regimes, Brassica oleracea seed lots of different maturity, stress tolerance, and germination behavior were created. Through careful physiological analysis of these seed lots combined with gene expression analysis using a dedicated cDNA microarray, gene expression could be correlated to physiological processes that occurred within the seeds. In addition, gene expression was studied during early stages of seed germination, prior to radicle emergence, since very little detailed information of gene expression during this process is available. During seed maturation expression of many known seed maturation genes, such as late-embryogenesis abundant or storage-compound genes, was high. Notably, a small but distinct subgroup of the maturation genes was found to correlate to seed stress tolerance in osmoprimed and dried seeds. Expression of these genes rapidly declined during priming and/or germination in water. The majority of the genes on the microarray were up-regulated during osmopriming and during germination on water, confirming the hypothesis that during osmopriming, germination-related processes are initiated. Finally, a large group of genes was up-regulated during germination on water, but not during osmopriming. These represent genes that are specific to germination in water. Germination-related gene expression was found to be partially reversible by physiological treatments such as slow drying of osmoprimed seeds. This correlated to the ability of seeds to withstand stress.

Brassica↗
PubMed2004

A proposed framework for the description of plant metabolomics experiments and their results.

The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known as ArMet (architecture for metabolomics). It encompasses the entire experimental time line from experiment definition and description of biological source material, through sample growth and preparation to the results of chemical analysis. Such formal data descriptions, which specify the full experimental context, enable principled comparison of data sets, allow proper interpretation of experimental results, permit the repetition of experiments and provide a basis for the design of systems for data storage and transmission. The current design and example implementations are freely available (http://www.armet.org/). We seek to advance discussion and community adoption of a standard for metabolomics, which would promote principled collection, storage and transmission of experiment data.

Database Management Systems↗