Search

Nederland is een van de grootste producenten van champignons in de wereld. Er zijn echter de laatste decennia slechts weinig nieuwe champignon-gebaseerde producten op de markt gekomen. Dit project beoogt een aanzet te leveren tot de ontwikkeling van champignonrassen die zich onderscheiden in smaak en die zich daarnaast zichtbaar onderscheiden van de huidige commercieel verkrijgbare champignons. Als eerste stap voor dergelijk toekomstig veredelingsonderzoek moeten metabolieten in champignons worden geïdentificeerd die voorspellende waarde hebben voor de smaak. Als dergelijke merker-moleculen betrouwbaar zijn geïdentificeerd, kan in een vervolgproject daadwerkelijk een veredelingstraject worden opgestart. Uit een collectie van ongeveer 250 wildisolaten van de champignons is een selectie gemaakt van 43 isolaten die de gehele genetische variatie van de collectie min of meer omvatten. Deze isolaten zijn opgekweekt in 6 verschillende teeltproeven en aangeboden aan een sensorisch panel dat verschillende aspecten van de smaak heeft beoordeeld. Statistische analyse van de resultaten laat zien dat hoewel voor de meeste isolaten de smaak erg lijkt op de commercieel beschikbare witte champignons, er een aantal isolaten zijn die anders smaken. Dezelfde champignons die zijn aangeboden aan het sensorisch panel zijn daarnaast onderzocht op metaboliet samenstelling. Het is nog niet mogelijk gebleken om de verschillen in smaak te koppelen aan specifieke metaboliet samenstellingen in de champignons. Een van de oorzaken is de grote variatie in beoordeling van smaakaspecten door het sensorisch panel. Daarnaast bleek bij vergelijking van de verschillende batches van controle ras A15, ook batch tot batch variatie op te treden in metabolietgehalten. Vervolgens is geprobeerd om de variatie in beoordeling door het sensorisch smaakpanel te verminderen door: • Veel minder rassen aanbieden aan het sensorisch panel • Rassen met grootst mogelijk verschil in smaak aanbieden • Interne herhalingen

Turnip (Brassica rapa spp. rapa) is an important vegetable species, with a unique physiology. Several plant parts, including both the turnip tubers and leaves, are important for human consumption. During the development of turnip plants, the leaves function as metabolic source tissues, while the tuber first functions as a sink, while later the tuber turns into a source for development of flowers and seeds. In the present study, chemical changes were determined for two genotypes with different genetic background, and included seedling, young leaves, mature leaves, tuber surface, tuber core, stalk, flower and seed tissues, at seven different time points during plant development. As a basis for understanding changes in glucosinolates during plant development, the profile of glucosinolates was analysed using liquid chromatography (LC) coupled to mass spectrometry (MS). This analysis was complemented by a gene expression analysis, focussed on GLS biosynthesis, which could explain part of the observed variation, pointing to important roles of specific gene orthologues for defining the chemical differences. Substantial differences in glucosinolate profiles were observed between above-ground tissues and turnip tuber, reflecting the differences in physiological role. In addition, differences between the two genotypes and between tissues that were harvested early or late during the plant lifecycle. The importance of the observed differences in glucosinolate profile for the ecophysiology of the turnip and for breeding turnips with optimal chemical profiles is discussed.

Introduction: Lettuce (Lactuca sativa L.) is generally not specifically acknowledged for its taste and nutritional value, while its cultivation suffers from limited resistance against several pests and diseases. Such key traits are known to be largely dependent on the ability of varieties to produce specific phytochemicals. Objectives: We aimed to identify promising genetic resources for the improvement of phytochemical composition of lettuce varieties. Methods: Phytochemical variation was investigated using 150 Lactuca genebank accessions, comprising a core set of the lettuce gene pool, and resulting data were related to available phenotypic information. Results: A hierarchical cluster analysis of the variation in relative abundance of 2026 phytochemicals, revealed by untargeted metabolic profiling, strongly resembled the known lettuce gene pool structure, indicating that the observed variation was to a large extent genetically determined. Many phytochemicals appeared species-specific, of which several are generally related to traits that are associated with plant health or nutritional value. For a large number of phytochemicals the relative abundance was either positively or negatively correlated with available phenotypic data on resistances against pests and diseases, indicating their potential role in plant resistance. Particularly the more primitive lettuces and the closely related wild relatives showed high levels of (poly)phenols and vitamin C, thus representing potential genetic resources for improving nutritional traits in modern crop types. Conclusion: Our large-scale analysis of phytochemical variation is unprecedented in lettuce and demonstrated the ample availability of suitable genetic resources for the development of improved lettuce varieties with higher nutritional quality and more sustainable production.

Reverse-transfected cell arrays in microfluidic systems have great potential to perform large-scale parallel screening of G protein-coupled receptor (GPCR) activation. Here, we report the preparation of a novel platform using reverse transfection of HEK293 cells, imaging by stereo-fluorescence microscopy in a flowcell format, real-time monitoring of cytosolic calcium ion fluctuations using the fluorescent protein Cameleon and analysis of GPCR responses to sequential sample exposures. To determine the relationship between DNA concentration and gene expression, we analyzed cell arrays made with variable concentrations of plasmid DNA encoding fluorescent proteins and the Neurokinin 1 (NK1) receptor. We observed pronounced effects on gene expression of both the specific and total DNA concentration. Reverse transfected spots with NK1 plasmid DNA at 1% of total DNA still resulted in detectable NK1 activation when exposed to its ligand. By varying the GPCR DNA concentration in reverse transfection, the sensitivity and robustness of the receptor response for sequential sample exposures was optimized. An injection series is shown for an array containing the NK1 receptor, bitter receptor TAS2R8 and controls. Both receptors were exposed 14 times to alternating samples of two ligands. Specific responses remained reproducible. This platform introduces new opportunities for high throughput screening of GPCR libraries.

Self-organizing maps (SOMs) are popular tools for grouping and visualizing data in many areas of science. This paper describes recent changes in package kohonen, implementing several different forms of SOMs. These changes are primarily focused on making the package more useable for large data sets. Memory consumption has decreased dramatically, amongst others, by replacing the old interface to the underlying compiled code by a new one relying on Rcpp. The batch SOM algorithm for training has been added in both sequential and parallel forms. A final important extension of the package’s repertoire is the possibility to define and use data-dependent distance functions, extremely useful in cases where standard distances like the Euclidean distance are not appropriate. Several examples of possible applications are presented.

Annotation of metabolites is an essential, yet problematic, aspect of mass spectrometry (MS)-based metabolomics assays. The current repertoire of definitive annotations of metabolite spectra in public MS databases is limited and suffers from lack of chemical and taxonomic diversity. Furthermore, the heterogeneity of the data prevents the development of universally applicable metabolite annotation tools. Here we present a combined experimental and computational platform to advance this key issue in metabolomics. WEIZMASS is a unique reference metabolite spectral library developed from high-resolution MS data acquired from a structurally diverse set of 3,540 plant metabolites. We also present MatchWeiz, a multi-module strategy using a probabilistic approach to match library and experimental data. This strategy allows efficient and high-confidence identification of dozens of metabolites in model and exotic plants, including metabolites not previously reported in plants or found in few plant species to date.

Likelihood estimates of the Dirichlet distribution parameters can be obtained only through numerical algorithms. Such algorithms can provide estimates outside the correct range for the parameters and/or can require a large amount of iterations to reach convergence. These problems can be aggravated if good starting values are not provided. In this paper we discuss several approaches that can partially avoid these problems providing a good trade-off between efficiency and stability. The performances of these approaches are compared on high-dimensional real and simulated data., Peer Reviewed

Item does not contain fulltext

Item does not contain fulltext

Radboud Universiteit Nijmegen, 10 februari 2011, Promotor : Buydens, L.M.C. Co-promotores : Wehrens, Ron, Bauerschmidt, S., Contains fulltext : 83245.pdf (publisher's version ) (Open Access)

RU Radboud Universiteit Nijmegen, 2 april 2008, Promotores : Buydens, L.M.C., Murray-Rust, P. Co-promotor : Wehrens, Ron, Contains fulltext : 72267.pdf (author's version ) (Open Access)

Contains fulltext : 36421.pdf (publisher's version ) (Closed access)

Contains fulltext : 36528.pdf (publisher's version ) (Closed access), This article shows, the use of supervised self-organizing maps (SOMs) to explore large numbers of experimental or simulated crystal structures and to visualize structure-property relationships. The examples show how powder diffraction patterns together with one or more structural properties, such as cell volume, space group, and lattice energy, are used to determine the positions of the crystal structures in the maps. The weighted cross-correlation criterion is used as the similarity measure for the diffraction patterns. The results show that supervised SOMs offer a better and more interpretable mapping than unsupervised SOMs, which makes exploration of large sets of structures easier and allows for the classification and prediction of properties. Combining diffraction pattern and lattice energy similarity using a SOM outperforms the separate use of those properties and offers a powerful tool for subset selection in polymorph prediction.

Contains fulltext : 34606.pdf (publisher's version ) (Closed access)

Item does not contain fulltext, Our current knowledge of the general factor requirement in transcription by the three mammalian RNA polymerases is based on a small number of model promoters. Here, we present a comprehensive chromatin immunoprecipitation (ChIP)-on-chip analysis for 28 transcription factors on a large set of known and novel TATA-binding protein (TBP)-binding sites experimentally identified via ChIP cloning. A large fraction of identified TBP-binding sites is located in introns or lacks a gene/mRNA annotation and is found to direct transcription. Integrated analysis of the ChIP-on-chip data and functional studies revealed that TAF12 hitherto regarded as RNA polymerase II (RNAP II)-specific was found to be also involved in RNAP I transcription. Distinct profiles for general transcription factors and TAF-containing complexes were uncovered for RNAP II promoters located in CpG and non-CpG islands suggesting distinct transcription initiation pathways. Our study broadens the spectrum of general transcription factor function and uncovers a plethora of novel, functional TBP-binding sites in the human genome.

Item does not contain fulltext

Contains fulltext : 35596.pdf (publisher's version ) (Closed access)

Item does not contain fulltext