Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Disentangling hexaploid genetics : towards DNA-informed breeding for postharvest performance in chrysanthemum
Geest, Geert van - \ 2017
Wageningen University. Promotor(en): R.G.F. Visser, co-promotor(en): U. van Meeteren; P.F.P. Arens. - Wageningen : Wageningen University - ISBN 9789463436427 - 142
chrysanthemum - plant breeding - postharvest quality - hexaploidy - polyploidy - quantitative trait loci - phenotypes - linkage mapping - metabolomics - polymorphism - dna - chrysanthemum - plantenveredeling - kwaliteit na de oogst - hexaploïdie - polyploïdie - loci voor kwantitatief kenmerk - fenotypen - koppelingskartering - metabolomica - polymorfisme - dna

DNA-informed selection can strongly improve the process of plant breeding. It requires the detection of DNA polymorphisms, calculation of genetic linkage, access to reliable phenotypes and methods to detect genetic loci associated with phenotypic traits of interest. Cultivated chrysanthemum is an outcrossing hexaploid with an unknown mode of inheritance. This complicates the development of resources and methods that enable the detection of trait loci. Postharvest performance is an essential trait in chrysanthemum, but is difficult to measure. This makes it an interesting but challenging trait to phenotype and detect associated genetic loci. In this thesis I describe the development of resources and methods to enable phenotyping for postharvest performance, genetic linkage map construction and detection of quantitative trait loci in hexaploid chrysanthemum.

Postharvest performance is a complicated trait because it is related to many different disorders that reduce quality. One of these disorders in chrysanthemum is disk floret degreening, which occurs after long storage. In chapter 2, we show that degreening can be prevented by feeding the flower heads with sucrose, suggesting carbohydrate starvation plays a role in the degreening process. To investigate the response to carbohydrate starvation of genotypes with different sensitivity to disk floret degreening, we investigated the metabolome of sugar-fed and carbohydrate-starved disk florets by 1H-NMR and HPAEC. We show that the metabolome is severely altered at carbohydrate starvation. In general, starvation results in an upregulation of amino acid and secondary metabolism. Underlying causes of genotypic differences explaining variation in disk floret degreening in the three investigated genotypes remained to be elucidated, but roles of regulation of respiration rate and camphor metabolism were posed as possible candidates.

In chapter 3, disk floret degreening was found to be the most important postharvest disorder after 3 weeks of storage among 44 white chrysanthemum cultivars. To investigate the inheritance of disk floret degreening, we crossed two genotypes with opposite phenotypic values of both disk floret degreening and carbohydrate content to obtain a population segregating for disk floret degreening. To phenotype the cultivar panel and the bi-parental population precisely and in a high throughput manner, we developed a method that quantified colour of detached capitula over time. This method was validated with visual observations of disk floret degreening during vase life tests. In a subset of the bi-parental population we measured carbohydrate content of the disk florets at harvest. The amount of total carbohydrates co-segregated with sensitivity to degreening, which shows that the difference in disk floret degreening sensitivity between the parents could be explained by their difference in carbohydrate content. However, the correlation was rather weak, indicating carbohydrate content is not the only factor playing a role.

In order to develop resources for DNA-informed breeding, one needs to be able to characterize DNA polymorphisms. In chapter 4, we describe the development of a genotyping array containing 183,000 single nucleotide polymorphisms (SNPs). These SNPs were acquired by sequencing the transcriptome of 13 chrysanthemum cultivars. By comparing the genomic dosage based on the SNP assay and the dosage as estimated by the read depth from the transcriptome sequencing data, we show that alleles are expressed conform the genomic dosage, which contradicts to what is often found in disomic polyploids. In line with this finding, we conclusively show that cultivated chrysanthemum exhibits genome-wide hexasomic inheritance, based on the segregation ratios of large numbers of different types of markers in two different populations.

Tools for genetic analysis in diploids are widely available, but these have limited use for polyploids. In chapter 5, we present a modular software package that enables genetic linkage map construction in tetraploids and hexaploids. Because of the modularity, functionality for other ploidy levels can be easily added. The software is written in the programming language R and we named it polymapR. It can generate genetic linkage maps from marker dosage scores in an F1 population, while taking the following steps: data inspection and filtering, linkage analysis, linkage group assignment and marker ordering. It is the first software package that can handle polysomic hexaploid and partial polysomic tetraploid data, and has advantages over other polyploid mapping software because of its scalability and cross-platform applicability.

With the marker dosage scores of the bi-parental F1 population from the genotyping array and the developed methods to perform linkage analysis we constructed an integrated genetic linkage map for the hexaploid bi-parental population described in chapter 3 and 4. We describe this process in chapter 6. With this integrated linkage map, we reconstructed the inheritance of parental haplotypes for each individual, and expressed this as identity-by-descent (IBD) probabilities. The phenotypic data on disk floret degreening sensitivity that was acquired as described in chapter 3, was used in addition to three other traits to detect quantitative trait loci (QTL). These QTL were detected based on the IBD probabilities of 1 centiMorgan intervals of each parental homologue. This enabled us to study genetic architecture by estimating the effects of each separate allele within a QTL on the trait. We showed that for many QTL the trait was affected by more than two alleles.

In chapter 7, the findings in this thesis are discussed in the context of breeding for heterogeneous traits, the implications of the mode of inheritance for breeding and the advantages and disadvantages of polyploidy in crop breeding. In conclusion, this thesis provides in general a significant step for DNA-informed breeding in polysomic hexaploids, and for postharvest performance in chrysanthemum in particular.

Identification of metabolites involved in heat stress response in different tomato genotypes
Paupière, Marine J. - \ 2017
Wageningen University. Promotor(en): R.G.F. Visser, co-promotor(en): A.G. Bovy; Y.M. Tikunov. - Wageningen : Wageningen University - ISBN 9789463431842 - 168
solanum lycopersicum - tomatoes - genotypes - heat stress - heat tolerance - pollen - metabolomes - metabolites - metabolomics - solanum lycopersicum - tomaten - genotypen - warmtestress - hittetolerantie - stuifmeel - metabolomen - metabolieten - metabolomica

Tomato production is threatened by climate change. High temperatures lead to a decrease of fruit set which correlates with a decrease of pollen fertility. The low viability of tomato pollen under heat stress was previously shown to be associated with alterations in specific metabolites. In this thesis, we used untargeted metabolomics approaches to broaden the identification of metabolites affected by heat stress. We assessed the suitability of pollen isolation methods for metabolomics analysis and considered the pitfalls for our further analysis. We explored the developmental metabolomes of pollen and anthers of different tomato genotypes under control and high temperature conditions and identified that microsporogenesis is a critical developmental stage for the production of mature and fertile pollen grain under heat stress. Several metabolites were putatively associated with tolerance to high temperature such as specific flavonoids, polyamines and alkaloids. These metabolites can be further used as markers in breeding programs to develop new genotypes tolerant to high temperatures.

Regulation of cucumber (Cucumis sativus) induced defence against the two-spotted spider mite (Tetranychus urticae
He, J. - \ 2016
Wageningen University. Promotor(en): Harro Bouwmeester; Marcel Dicke, co-promotor(en): Iris Kappers. - Wageningen : Wageningen University - ISBN 9789462576810 - 211
cucumis sativus - cucumbers - induced resistance - plant pests - tetranychus urticae - mites - defence mechanisms - herbivore induced plant volatiles - herbivory - metabolomics - terpenoids - genomics - cucumis sativus - komkommers - geïnduceerde resistentie - plantenplagen - tetranychus urticae - mijten - verdedigingsmechanismen - herbivoor-geinduceerde plantengeuren - herbivorie - metabolomica - terpenen - genomica

Plants have evolved mechanisms to combat herbivory. These mechanisms can be classified as direct defences which have a negative influence on the herbivores and indirect defence that attracts natural enemies of the attacking herbivores. Both direct and indirect defences can be constantly present or induced upon attack. This study, using cucumber (Cucumis sativus) and the two-spotted spider mite (Tetranychus urticae) as model, aimed to reveal the molecular mechanisms underlying the induced defence during herbivory, with emphasis on transcriptional changes and the involved TFs, the enzymatic function of the genes associated with volatile biosynthesis, and their promoters which regulate their expression.

Big data dringen door in de tuinbouw. Naar een volledig begrip van plantgedrag en productkwaliteit
Kierkels, T. ; Zedde, H.J. van de - \ 2015
Onder Glas 12 (2015)11. - p. 24 - 25.
tuinbouw - glastuinbouw - innovaties - landbouwkundig onderzoek - kunstmatige intelligentie - gewaskwaliteit - plantenveredeling - sorteren - kwaliteit - teeltsystemen - 3d analyse - metabolomica - genomica - transcriptomica - horticulture - greenhouse horticulture - innovations - agricultural research - artificial intelligence - crop quality - plant breeding - sorting - quality - cropping systems - 3d analysis - metabolomics - genomics - transcriptomics
Vijftien onderzoeksgroepen van Wageningen UR hebben de handen ineengeslagen om te komen tot het beter meten, begrijpen en voorspellen van plantgedrag en productkwaliteit. Het vakgebied heet ‘Plant phenomics’ en maakt gebruik van innovatieve technieken en sensoren. Het doel is een betere beheersing van teelt- en veredelingsproces en productkwaliteit. Toepassingen voor de praktijk liggen nog vooral op het terrein van sorteren en automatische kwaliteitsbeoordeling.
Correlating composition and functionality of soy protein hydrolysates used in animal cell cultures
Gupta, A.J. - \ 2015
Wageningen University. Promotor(en): Harry Gruppen, co-promotor(en): Peter Wierenga; J.W. Boots. - Wageningen : Wageningen University - ISBN 9789462573208 - 127
sojaeiwit - eiwithydrolysaten - functionele eigenschappen - warmtebehandeling - celculturen - chemische samenstelling - metabolomica - soya protein - protein hydrolysates - functional properties - heat treatment - cell cultures - chemical composition - metabolomics

Abstract

Soy protein hydrolysates are often supplemented to chemically defined (CD) media in cell cultures, but there is little understanding of the effect of their composition on their functionality (viable cell density, total immunoglobulin (IgG), and specific IgG production). To identify the key parameters (e.g. compound classes) that determine their functionality, hydrolysates were prepared from different starting materials (meal, concentrates, and isolate) and from soybean meal that was heated for different time periods. The functionality of these hydrolysates were compared to those of industrial hydrolysates. From the comparison, it was shown that the variation in industrial and experimental processes of hydrolysate production induced larger variation in the functionality than the variation in starting materials. Moreover, it was observed that the correlations between the functionality and compositional parameters observed in one experiment were absent in the other experiments. During the study, it became apparent that the variations in other factors, like CD media and temperature during culturing also resulted in variation in functionality. The extent of variations in the functionality due to variation in CD media and temperature during culturing was equivalent to the variation caused by varying the hydrolysate composition. The functionality data of the different experiments were fitted with a model that described the relation between specific IgG production and viable cell density. Using the model, the maximum achievable total IgG production could be calculated for a culture condition. This information can provide directions for further optimization of hydrolysates to maximize total IgG production.

Physiological and molecular adaptations of Lactococcus lactis to near-zero growth conditions
Ercan, O. - \ 2014
Wageningen University. Promotor(en): Michiel Kleerebezem, co-promotor(en): Eddy Smid. - Wageningen : Wageningen University - ISBN 9789462570719 - 206
lactococcus lactis - adaptatiefysiologie - voedselmicrobiologie - groeitempo - groeispanning - transcriptomica - metabolomica - lactococcus lactis - adaptation physiology - food microbiology - growth rate - growth stress - transcriptomics - metabolomics

Lactococcus lactis is an important lactic acid bacteria (LAB) species that is used for the manufacture of dairy products, such as cheese, buttermilk, and other fermented products. The predominant function of this bacterium in dairy fermentation is the production of lactic acid, as its major fermentation end-product that contributes to preservation and microbial safety of the product. Moreover, L. lactis is frequently encountered in natural ecosystems such as in (rotting) plant material.

Due to restricted energy source availability, natural microbial communities commonly live in a situation that can be characterized as ‘hunger’, which is different from strict nutrient-starvation. As a consequence, environmental microbes commonly grow at very low-growth rates as compared to laboratory cultures. Analogously, microorganisms can experience such nutrient-poor conditions in diverse industrial fermentation applications. For example, LAB encounter extreme low or no energy source availability during the extended ripening process of cheeses or dry sausages, which can take months. Despite these harsh environmental conditions, many LAB are able to remain viable in these processes for months and sustain a low-level metabolic activity, which plays an important role in their contribution to flavor and aroma formation in the product matrix.

In this thesis, the quantitative physiology of L. lactis at near-zero specific growth rates was studies, employing both metabolic and genome-wide transcriptome studies in an experimental set-up of carbon-limited retentostat cultivation. Chapter 2 describes how retentostat cultivation enables uncoupling of growth and non-growth related processes in L. lactis, allowing the quantitative analysis of the physiological adaptations of this bacterium to near-zero growth rates. In chapter 3, transcriptome and metabolome analyses were integrated to understand the molecular adaptation of L. lactis to near-zero specific growth rate, and expand the studies in chapter 2 towards gene regulations patterns that play a profound role in zero-growth adaptation. Chapter 4 describes the enhanced robustness to several stress conditions of L. lactis after its adaptation to extremely low-specific growth rate by carbon-limited retentostat cultivation. In this chapter correlations were modelled that quantitatively and accurately describe the relationships between growth-rate, stress-robustness, and stress-gene expression levels, revealing correlation coefficients for each of the varieties involved. Chapter 5 evaluates the distinction between the transcriptome responses to extended carbon-limited growth and severe starvation conditions, where the latter condition was elicited by switching off the medium supply of the retentostat cultures described in chapter 1. Chapter 6 highlights the comparison of the physiological and molecular adaptations of industrially important microorganisms towards carbon-limited retentostat conditions. In conclusion, this thesis describes the quantitative physiological, metabolic, and genome-wide transcriptional adaptations of L. lactis at near-zero specific growth rates induced by carbon source limited retentostat cultivation, and compares these molecular adaptations to those elicited by strict carbon-starvation conditions.

Plant metabolomics and the golden age of Dutch painting
Hall, R.D. - \ 2014
Wageningen : Wageningen University, Wageningen UR - ISBN 9789461739735 - 24
metabolomica - plantensamenstelling - fytochemie - schilderijen - geschiedenis - nederland - metabolomics - plant composition - phytochemistry - paintings - history - netherlands
Breeding for pepper fruit quality: a genitical metabolomics approach
Wahyuni, Y. - \ 2014
Wageningen University. Promotor(en): Raoul Bino, co-promotor(en): Arnaud Bovy; E. Sudarmonowati; A.R. Ballester. - Wageningen : Wageningen University - ISBN 9789461739582 - 193
capsicum annuum - capsicum frutescens - capsicum chinense - capsicum baccatum - plantenveredeling - metabolomica - gewaskwaliteit - secundaire metabolieten - gezondheid - genetische kartering - rijp worden - capsicum annuum - capsicum frutescens - capsicum chinense - capsicum baccatum - plant breeding - metabolomics - crop quality - secondary metabolites - health - genetic mapping - ripening

A diverse collection of 32 pepper accessions was analysed for variation in health-related metabolites, such as carotenoids, capsaicinoids, flavonoids and vitamins C and E. For each of the metabolites analysed, there was a lot of variation among the accessions and it was possible to identify accessions with high amounts of specific metabolites. While all accessions contained high levels of vitamin C, accession C. chinenseAC2212 was found to be an excellent source of vitamin E, whereas C. annuumLong Sweet accumulated high levels of the flavonoid quercetin. A genetical metabolomics approach was used to study the genetic basis of metabolic traits in a segregating F2 population based on a cross between two contrasting pepper genotypes. This led to the identification of several metabolites QTL hotspots. The genetic basis for the accumulation of several flavonoids in pepper fruit was further investigated, by combining metabolic, gene expression and candidate gene-based marker data. This provided valuable insight into the key genes important for flavonoid accumulation in pepper fruit. The results of this study will help breeders to assist future breeding programs aimed at optimizing the levels of nutritional compounds in pepper fruit.

Text mining for metabolic reaction extraction from scientific literature
Risse, J.E. - \ 2014
Wageningen University. Promotor(en): Ton Bisseling; Jack Leunissen, co-promotor(en): P.E. van der Vet. - Wageningen : Wageningen University - ISBN 9789461739001 - 138
metabolomica - gegevensanalyse - databanken - text mining - publicaties - wetenschappelijk onderzoek - moleculaire biologie - thesauri - enzymen - metabolieten - metabolomics - data analysis - databases - text mining - publications - scientific research - molecular biology - thesauri - enzymes - metabolites

Science relies on data in all its different forms. In molecular biology and bioinformatics in particular large scale data generation has taken centre stage in the form of high-throughput experiments. In line with this exponential increase of experimental data has been the near exponential growth of scientific publications. Yet where classical data mining techniques are still capable of coping with this deluge in structured data (Chapter 2), access of information found in scientific literature is still limited to search engines allowing searches on the level keywords, titles and abstracts. However, large amounts of knowledge about biological entities and their relations are held within the body of articles. When extracted, this data can be used as evidence for existing knowledge or hypothesis generation making scientific literature a valuable scientific resource. To unlock the information inside the articles requires a dedicated set of techniques and approaches tailored to the unstructured nature of free text. Analogous to the field of data mining for the analysis of structured data, the field of text mining has emerged for unstructured text and a number of applications has been developed in that field.

This thesis is about text mining in the field of metabolomics. The work focusses on strategies for accessing large collections of scientific text and on the text mining steps required to extract metabolic reactions and their constituents, enzymes and metabolites, from scientific text. Metabolic reactions are important for our understanding of metabolic processes within cells and that information provides an important link between genotype phenotype. Furthermore information about metabolic reactions stored in databases is far from complete making it an excellent target for our text mining application.

In order to access the scientific publications for further analysis they can be used as flat text or loaded into database systems. In Chapter 2we assessed and discussed the capabilities and performance of XML-type database systems to store and access very large collections of XML-type documents in the form of the Medline corpus, a collection of more than 20 million of scientific abstracts. XML data formats are common in the field of bioinformatics and are also at the core of most web services. With the increasing amount of data stored in XML comes the need for storing and accessing the data. The database systems were evaluated on a number of aspects broadly ranging from technical requirements to ease-of-use and performance. The performance of the different XML-type database systems was measured Medline abstract collections of increasing size and with a number of different queries. One of the queries assessed the capabilities of each database system to search the full-text of each abstract, which would allow access to the information within the text without further text analysis. The results show that all database systems cope well with the small and medium dataset, but that the full dataset remains a challenge. Also the query possibilities varied greatly across all studied databases. This led us to conclude that the performances and possibilities of the different database types vary greatly, also depending on the type of research question. There is no single system that outperforms the others; instead different circumstances can lead to a different optimal solution. Some of these scenarios are presented in the chapter.

Among the conclusions of Chapter 2is that conventional data mining techniques do not work for the natural language part of a publication beyond simple retrieval queries based on pattern matching. The natural language used in written text is too unstructured for that purpose and requires dedicated text mining approaches, the main research topic of this thesis. Two major tasks of text mining are named entity recognition, the identification of relevant entities in the text, and relation extraction, the identification of relations between those named entities. For both text mining tasks many different techniques and approaches have been developed. For the named entity recognition of enzymes and metabolites we used a dictionary-based approach (Chapter 3) and for metabolic reaction extraction a full grammar approach (Chapter 4).

In Chapter 3we describe the creation of two thesauri, one for enzymes and one for metabolites with the specific goal of allowing named entity identification, the mapping of identified synonyms to a common identifier, for metabolic reaction extraction. In the case of the enzyme thesaurus these identifiers are Enzyme Nomenclature numbers (EC number), in the case of the metabolite thesaurus KEGG metabolite identifiers. These thesauri are applied to the identification of enzymes and metabolites in the text mining approach of Chapter 4. Both were created from existing data sources by a series of automated steps followed by manual curation. Compared to a previously published chemical thesaurus, created entirely with automated steps, our much smaller metabolite thesaurus performed on the same level for F-measure with a slightly higher precision. The enzyme thesaurus produced results equal to our metabolite thesaurus. The compactness of our thesauri permits the manual curation step important in guaranteeing accuracy of the thesaurus contents, whereas creation from existing resources by automated means limits the effort required for creation. We concluded that our thesauri are compact and of high quality, and that this compactness does not greatly impact recall.

In Chapter 4we studied the applicability and performance of a full parsing approach using the two thesauri described in Chapter 3 for the extraction of metabolic reactions from scientific full-text articles. For this we developed a text mining pipeline built around a modified dependency parser from the AGFL grammar lab using a pattern-based approach to extract metabolic reactions from the parsing output. Results of a comparison to a modified rule-based approach by Czarnecki et al.using three previously described metabolic pathways from the EcoCyc database show a slightly lower recall compared to the rule-based approach, but higher precision. We concluded that despite its current recall our full parsing approach to metabolic reaction extraction has high precision and potential to be used to (re-)construct metabolic pathways in an automated setting. Future improvements to the grammar and relation extraction rules should allow reactions to be extracted with even higher specificity.

To identify potential improvements to the recall, the effect of a number of text pre-processing steps on the performance was tested in a number of experiments. The one experiment that had the most effect on performance was the conversion of schematic chemical formulas to syntactic complete sentences allowing them to be analysed by the parser. In addition to the improvements to the text mining approach described in Chapter 4I make suggestions in Chapter 5 for potential improvements and extensions to our full parsing approach for metabolic reaction extraction. Core focus here is the increase of recall by optimising each of the steps required for the final goal of extracting metabolic reactions from the text. Some of the discussed improvements are to increase the coverage of the used thesauri, possibly with specialist thesauri depending on the analysed literature. Another potential target is the grammar, where there is still room to increase parsing success by taking into account the characteristics of biomedical language. On a different level are suggestions to include some form of anaphora resolution and across sentence boundary search to increase the amount of information extracted from literature.

In the second part of Chapter 5I make suggestions as to how to maximise the information gained from the text mining results. One of the first steps should be integration with other biomedical databases to allow integration with existing knowledge about metabolic reactions and other biological entities. Another aspect is some form of ranking or weighting of the results to be able to distinguish between high quality results useful for automated analyses and lower quality results still useful for manual approaches. Furthermore I provide a perspective on the necessity of computational literature analysis in the form of text mining. The main reasoning here is that human annotators cannot keep up with the amount of publications so that some form of automated analysis is unavoidable. Lastly I discuss the role of text mining in bioinformatics and with that also the accessibility of both text mining results and the literature resources necessary to create them. An important requirement for the future of text mining is that the barriers around high-throughput access to literature for text mining applications have to be removed. With regards to accessing text mining results, there is a long way to go for many applications, including ours, before they can be used directly by biologists. A major factor is that these applications rarely feature a suitable user interface and easy to use setup.

To conclude, I see the main role of a text mining system like ours mainly in gathering evidence for existing knowledge and giving insights into the nuances of the research landscape of a given topic. When using the results of our reaction extraction system for the identification of ‘new’ reactions it is important to go back to the actual evidence presented for extra validations and to cross-validate the predictions with other resources or experiments. Ideally text mining will be used for generation of hypotheses, in which the researcher uses text mining findings to get ideas on, in our case, new connections between metabolites and enzymes; subsequently the researcher needs to go back to the original texts for further study. In this role text mining is an essential tool on the workbench of the molecular biologist.

An integrated approach involving metabolomics and transcriptomics for a system-wide understanding of the interaction between tomato and Cladosporium fulvum
Etalo, D.W. - \ 2014
Wageningen University. Promotor(en): Harro Bouwmeester, co-promotor(en): Matthieu Joosten; Ric de Vos. - Wageningen : Wageningen University - ISBN 9789461738219 - 270
solanum lycopersicum - plantenziekteverwekkende schimmels - passalora fulva - plant-microbe interacties - metabolomica - genexpressie - genomica - ziekteresistentie - virulentie - solanum lycopersicum - plant pathogenic fungi - passalora fulva - plant-microbe interactions - metabolomics - gene expression - genomics - disease resistance - virulence
Potato genetical genomics: investigating the genetic basis of primary metabolism and its relationship to the phenotype
Carreño Quintero, N. - \ 2013
Wageningen University. Promotor(en): Harro Bouwmeester; Richard Visser, co-promotor(en): Joost Keurentjes; Christian Bachem. - Wageningen : Wageningen University - ISBN 9789461738110 - 180
solanum tuberosum - aardappelen - genomica - metabolisme - genetische analyse - metabolomica - metabolomen - fenotypen - loci voor kwantitatief kenmerk - solanum tuberosum - potatoes - genomics - metabolism - genetic analysis - metabolomics - metabolomes - phenotypes - quantitative trait loci

Primary metabolism is essential for plant growth and survival and it is therefore involved in all physiological processes of the plant. In the past years the advancements in large-scale and high-throughput technologies have enhanced our ability to characterize the plant metabolome. The development of methods for the simultaneous analysis of many different plant metabolites and the necessary software for subsequent data analysis have further expanded the possibilities to investigate plant responses from a system-oriented perspective. This allows the comparison of genetic and phenotypic variation at different molecular levels, enabling us to find associations between genotype and phenotype and their intermediate levels of information transduction. Metabolomics has become increasingly important for the characterization of the metabolic status of plants under different environmental and genetic perturbations. The economic importance of potato and the increasing availability of genetic and molecular resources have stimulated research on many different aspects of the physiology of this crop and the regulation of complex traits. We used the available tools to explore the genetic basis of the composition and content of primary metabolites in a potato population. In this research, the possibilities to combine metabolite profiling with genetic information are explored to identify the genetic factors determining primary metabolism and to infer links between metabolites and agronomic phenotypes.

Control of Pig Reproduction IX
Rodriguez-Martinez, H. ; Soede, N.M. ; Flowers, W.L. - \ 2013
Leicestershire, United Kingdom : Context Products Ltd (Society of Reproduction and Fertility volume 68) - ISBN 9781899043484 - 345
varkens - geslachtelijke voortplanting - gameten - embryo's - kunstmatige inseminatie - embryotransplantatie - zwangerschap - partus - pasgeborenen - biggen - overleving - biotechnologie - metabolomica - eiwitexpressieanalyse - kunstmatige selectie - pigs - sexual reproduction - gametes - embryos - artificial insemination - embryo transfer - pregnancy - parturition - neonates - piglets - survival - biotechnology - metabolomics - proteomics - artificial selection
Systems biology and statistical data integration of ~omics data sets
Acharjee, A. - \ 2013
Wageningen University. Promotor(en): Richard Visser, co-promotor(en): Chris Maliepaard. - S.l. : s.n. - ISBN 9789461735843 - 177
systeembiologie - statistische gegevens - gegevensanalyse - gegevens verzamelen - metabolomica - loci voor kwantitatief kenmerk - genomica - eiwitexpressieanalyse - solanum tuberosum - aardappelen - databanken - systems biology - statistical data - data analysis - data collection - metabolomics - quantitative trait loci - genomics - proteomics - solanum tuberosum - potatoes - databases

In this thesis quality traits of potato were related to different highly multivariate ~omics datasets containing information on proteins, primary and secondary metabolites and gene expression. The objectives were to explore and compare different statistical techniques that are able to quantify these relationships, and to identify components responsible for prediction of quality. We propose a strategy to integrate two or more of such datasets and to select subsets of predictive components. We used potato flesh colour as an example trait and identified metabolites and expressed genes that are associated with flesh colour. We identified two putative novel non-volatile glycosides of carotenoid-derived metabolites and a novel putative connection with the flavonoid pathway. From a gas chromatography data set we identified genetic factors underlying variation in primary metabolism and found the amino acid beta-alanine associated with starch content. Finally we performed an integrated analysis with gene expression, metabolites and proteomics data and present an approach to select a limited set of predictive genes, metabolites and proteins.

Genes for seed quality : integrating physiology and genetical genomics to mine for seed quality genes in tomato
Kazmi, R.H. - \ 2013
Wageningen University. Promotor(en): Harro Bouwmeester, co-promotor(en): Henk Hilhorst; Wilco Ligterink. - S.l. : s.n. - ISBN 9789461735201 - 243
solanum lycopersicum - solanum pimpinellifolium - tomaten - zaadkwaliteit - genen - plantenfysiologie - genomica - fenotypen - metabolomica - solanum lycopersicum - solanum pimpinellifolium - tomatoes - seed quality - genes - plant physiology - genomics - phenotypes - metabolomics

Seed quality in tomato is associated with many complex physiological and genetical traits. The performance of seeds is determined by three interlinked and interactive components that constitute a performance triangle of genetics, physiological quality and the environment. So far, there has been little or no discussion about the genetic analysis of seed and seedling traits in tomato at a systems level. To the best of our knowledge, the present study is the first systemic analysis of the genetics of seed and seedling traits, adding to a growing body of information on tomato seed quality. With the aim of improving the production of high-quality tomato seeds, a multidisciplinary study (physiology, genetics and genomics) was undertaken to develop and evaluate methods for improving the percentage, rate and uniformity of germination and early seedling development, and for increasing the range of environmental conditions for germination. Primarily, we explored the natural variation present in a Solanum lycopersicum x Solanum pimpinellifolium RIL population to dissect the molecular-genetic mechanisms controlling seed quality. Although previous solutions to issues associated with seed quality phenotypes seemed promising, none have utilized the integration of genomic, phenotypic and metabolic datasets to understand seed quality in tomato.Thus, the integration of metabolic and genomic analysis contributed to a comprehensive biological understanding of observed phenotypic differences between RILs of S. lycopersicumx S. pimpinellifolium. Here we describe, for the first time, the use of a generalized genetical genomics (GGG) model in tomato seeds that incorporates genetics, as well as environmental effects, and we applied this approach to map traditional quantitative trait loci (Genetic QTLs) and QTLs that are the result of interaction between the genetics and environmental changes (Genetic x Environmental QTLs). This model uses chosen environmental perturbations (different seed developmental stages, i.e. dry and 6h imbibed seeds) in combination with the analysis of genetic variation present in the RIL population, to study the change of metabolites over the multiple environments and to identify genotype-by-environment interactions. This thesis gives an account of the integration of genotyping, phenotyping and a molecular phenotype using metabolomics in generating a novel understanding of seed phenotypes and their interaction with the environment. In summary, the integration of phenotypic and metabolomics data has facilitated the identification of potential biomarkers for better understanding of the complex nature of tomato seed quality.

Systematic metabolite annotation and identification in complex biological extracts : combining robust mass spectrometry fragmentation and nuclear magnetic resonance spectroscopy
Hooft, J.J.J. van der - \ 2012
Wageningen University. Promotor(en): Raoul Bino; Sacco de Vries, co-promotor(en): Jacques Vervoort; Ric de Vos. - S.l. : s.n. - ISBN 9789461732347 - 256
metabolieten - metabolomica - massaspectrometrie - kernmagnetische resonantiespectroscopie - metabolische profilering - metabolische fingerprinting - metabolites - metabolomics - mass spectrometry - nuclear magnetic resonance spectroscopy - metabolic profiling - metabolic fingerprinting

Detailed knowledge of the chemical content of organisms, organs, tissues, and cells is needed to fully characterize complex biological systems. The high chemical variety of compounds present in biological systems is illustrated by the presence of a large variety of compounds, ranging from apolar lipids, semi-polar phenolic conjugates, toward polar sugars. A molecules’ chemical structure forms the basis to understand its biological function. The chemical identification process of small molecules (i.e., metabolites) is still one of the major focus points in metabolomics research. Actually, no single analytical platform exists that can measure and identify all existing metabolites. In this thesis, two analytical techniques that are widely used within metabolite identification studies have been combined, i.e. mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR). MS was used to ionize the metabolites and to record their molecular weight and to provide substructure information based on fragmentation in the mass spectrometer. NMR gave the comprehensive structural information on the chemical environment of protons and their linkage to other protons within the molecule. The additional structural information as compared to MS is at the cost of an increased amount of compound needed for NMR detection and spectra generation. Here we combined both analytical methods into a liquid chromatography (LC)-based platform that concentrated compounds based on their specific mass; thereby providing a direct link between MS and NMR data. Another platform was developed that generated robust multistage MSn data, i.e., the systematic fragmentation of metabolites and subsequent fragmentation of resulting fragments.

This thesis aims to accelerate metabolite identification of low abundant plant and human derived compounds by following a systematic approach. The acquired structural information from MSn and 1D-1H-NMR spectra resulted in the complete elucidation of phenolic metabolites in microgram scale from both plant and human origin.

In the chapter 1, the analytical techniques and terms used throughout the thesis are introduced. The second chapterdescribes how a high mass resolution MSn fragmentation approach was tested in both negative and positive ionization modes for differentiation and identification of metabolites, using a series of 121 polyphenolic molecules. An injection robot was used to infuse the reference compounds one by one into a hybrid mass spectrometer, combining MSn possibilities with accurate mass read-out. This approach resulted in reproducible and robust MSn fragmentation trees up to MS5, which were differential even for closely related compounds. Accurate MSn-based spectral trees were shown to be robust and powerful to distinguish metabolites with similar elemental formula (i.e. isomers), thereby assisting compound identification and annotation in complex biological samples. In the third chapter, we tested the annotation power of this spectral tree approach for annotation of phenolic compounds in crude extracts from Lycopersicum esculentum(tomato) and the model plant Arabipopsis thaliana. Partial MSn spectral trees were generated directly after chromatographic elution (LC-MSn). Detailed MSn spectral trees could be recorded with the use of a collector/injector robot.We were able to discriminate flavonoid glycosides based on their unique MSn fragmentation patterns in either negative or positive ionization mode. Following this approach, we could annotate 127 metabolites in the tomato and Arabidopsis extracts, including 21 novel metabolites. The good quality MSn spectral trees obtained can be used to populate MSn databases and the protocols to generate the spectral trees are a good basis to further expand this database with more diverse compounds.

Chapter 4 then describes how an automated platform, coupling chromatography with MS and NMR (LC-MS-solid phase extraction-NMR), was developed that can trap and transfer metabolites based on their mass values from a complex biological extract in order to obtain NMR spectra of the trapped LC-MS peak, out of minute amounts of sample and analyte. Extracts from tomatoes modified in their flavonoid biosynthesis pathway were used as proof of principle for the metabolite identification process. This approach resulted in the complete structural elucidation of 10 flavonoid glycosides. This study shows that improving the link between the mass signals and NMR peaks derived from the selected LC-MS peaks decreases the time needed for elucidation of the metabolite structures. In addition, automated 1D-1H-NMR spectrum fitting of the experimental data obtained in this study using the PERCH NMR software further speeded up the candidate rejection process.

Chapter 5 illustrates how the two developed analytical platforms could be used for the successful selection, annotation, and identification of 177 phenolic compounds present in different extracts of Camellia sinensis, i.e. green, white, and black tea extracts, including the full identification of microgram amounts of complex acylated conjugates of kaempferol and quercetin. Principal component analysis based on the relative abundance of the annotated phenolic compounds in 17 commercially available black, green and white tea products separated the black teas from the green and white teas, thereby illustrating the differential phenolic metabolite contents of black tea as compared to green and white teas. The change in phenolic profiles reflects the polymerization reactions occurring upon transformation of green tea into black tea. This study shows that the combined use of MSn spectral trees and LC-MS-solid phase extraction-NMR leads to a more comprehensive metabolite description thereby facilitating the comparison of tea and other plant samples.

In chapter 6, we aimed to structurally elucidate and quantify polyphenol-derived conjugates present in the human body by studying the urinary excretion of these conjugates.We applied a combination of a solid phase extraction preparation step and the two HPLC-coupled analytical platforms as described in chapters 2 and 3. This analytical strategy resulted in the annotation of 138 urinary metabolites including 35 completely identified valerolactone conjugates. These valerolactones are microbial break-down products of tea phenols. NMR predictions of glucuronidated and sulphonated core metabolites were performed in order to confirm the NMR peak assignments on the basis of 1D-1H-NMR data only. In addition, 26 hours quantitative excretion profiles for certain valerolactone conjugates were obtained using diagnostic proton signals in the 1D-1H-NMR spectra of urine fractions.

In the seventh chapter, the current state of metabolite identification and expected challenges in the structural elucidation of metabolites at (sub)microgram amounts are discussed. The work in this thesis and of other groups working on the hyphenation of MS and NMR shows that the complete de novo identification of microgram amounts and even lower of compound is feasible by using MS guided solid phase extractiontrapping in combination with 1D-1H-NMR or UPLC-TOF-MS isolation followed by capillary NMR. Semi-automated annotation of compounds based on their MS and NMR features is now feasible for some well studied compound classes and groups.

Altogether, the developed platforms yield new and improved insights in the phenolic profiles of well-studied plants as well as a comprehensive picture of the metabolic fate of green tea polyphenols upon intake in the human body. The followed metabolite identification strategy is useful for other studies that aim to elucidate bioactive compounds, especially when only small sample volumes are available. This thesis also contributes to the acquisition of good quality data for metabolite identification by acquiring robust MSn fragmentation spectra and 1D-1H-NMR spectra of partial purified analytes at microgram scale, which paves the path for further developments in data acquisition and analysis, as well as the unravelling of yet unknown metabolites in a faster, more systematic and automated manner.

Application of omics technologies for environmental risk assessment of genetically modified plants : arabidopsis and modified defence mechanisms as a model study
Houshyani Hassanzadeh, B. - \ 2012
Wageningen University. Promotor(en): Harro Bouwmeester; Raoul Bino, co-promotor(en): Iris Kappers. - [S.l. : s.n. - ISBN 9789461731036 - 230
transgene planten - genetische modificatie - metabolomica - arabidopsis thaliana - verdedigingsmechanismen - risicoschatting - plantenbiotechnologie - milieu - niet-doelorganismen - transgenic plants - genetic engineering - metabolomics - arabidopsis thaliana - defence mechanisms - risk assessment - plant biotechnology - environment - nontarget organisms

As a result of rapid biotechnological developments in the past century, genetically modified (GM) crops were developed and introduced for field application. Despite the advantages of these crops and the professional marketing policies, people also started questioning the safety of GM products for humans and the environment. In response to that, scientific advisory bodies (such as COGEM, The Netherlands Commission on Genetic Modification) suggested that, among other measurements, an environmental risk assessment (ERA) of a GM crop should be done before introduction into the field. Ecological knowledge about the possible effects was considered a vital component of that assessment. In 2007, the Dutch Government initiated the ERGO (Ecology Regarding Gene-modified Organisms) research programme to generate a scientific basis for a sound ecological risk analysis. The main objective of the ERGO-programme was to develop ecology-based guidelines for how to best assess the possible ecological side-effects of new GM crops. Also the European Food Safety Authority (EFSA) recognised the interaction of a GM crop with non-target organisms as a potential environmental risk and therefore they provided guidelines for selection of a range of non-target organisms and phenotypes to be studied under laboratory conditions as part of a GM crop risk assessment study. These guidelines formed the basis for the ERGO research themes.

Parallel to the new biotechnological developments leading to the introduction of GM plants into the environment, new analytical techniques were also introduced that revolutionized the field of analytical biology. High throughput analytical platforms, collectively called omics technologies, created opportunities for untargeted analysis of cellular components with biological and ecological functions including mRNAs (transcriptomics), proteins (proteomics) and metabolites (metabolomics). These analytical platforms were recommended by several researchers in the field of GM food/feed safety for the analysis and comparison of a GM product with its safe counterpart. However, EFSA failed to formulate concrete rules about the application of the omics platforms in GM risk assessment perhaps due to a lack of consensus about where and how to employ these technologies in the whole ERA of GM plants. In the ERGO programme, exploration of the potential to apply omics platforms for ERA of GM crops was therefore one of the objectives.

This PhD thesis originates from one of the ERGO themes, assessment of the effect of genetic modification on non-target organisms. Under this theme with three PhD students a multidisciplinary approach was pursued to provide guidelines for how to evaluate non-target effects of GM crops altered in insect resistance using ecological methods as well as omics platforms. In this PhD thesis, I set out to find solutions for some of the limitations in the application of omics platforms such as the lack of a statistical method to evaluate the differences between GM vs. wild type plants at the omics level and the question what would be a fair reference for the judgement about the effect of genetic modification. As a model for the evaluation of the impact of genetic modification on the omics phenotype we used three insect defence traits that we introduced using genetic modification into several different Arabidopsis thaliana accessions. The first trait, indirect defence, was the production of the volatile (E)-nerolidol which has been shown to attract predatory mites that can control spider mites. The other two traits were direct defence traits and consisted of overexpression of the transcription factor (MYB28) to boost aliphatic glucosinolate biosynthesis and the introduction of Cry1from Bacillus thuringiensis encoding the Bt toxin that is effective against lepidopteran insects (caterpillars). As a reference for comparison of the effects of the genetic modification, we used a panel of wild type A. thaliana accessions that were selected in this study and publically available data of different accessions and individuals of a RIL population that together constitute the baseline, the variation present in the non-GM background germplasm. To allow for comparison of large datasets with this baseline, in Chapter 2 a statistical measure was developed, which we coined hyper-plane distance and which was used to assess the non-target effects of our genetic modification in transcriptomics as well as metabolomics analyses. In omics untargeted analyses, multivariate, hyper-dimensional data are generated, making global comparison of samples or groups of samples very difficult. In chapter 2 a method was developed to calculate a distance between the metabolome - analysed on three different metabolomics platforms - of genotypes or environments. Hereto, we employed principal component analysis (PCA) to reduce the number of analysed metabolites to a series of principal components (PCs) or dimensions of a PCA plot. The scores of the samples on a number of PCs, representing the relative position of samples to each other on those PCs, were subsequently used in an analysis of similarity (ANOSIM). In this manner, we used the variation in the samples’ PC scores to derive a distance between groups of samples on a multi-dimensional plot, the hyper-plane distance, in the case of metabolites called the metabolic distance. This distance represents between-group differences as well as within-group differences and therefore is a measure of the overlap between groups in a multi-dimensional context. Furthermore, it was also possible to statistically test the calculated distance in ANOSIM by permuting the samples’ scores to produce a P-value for the calculated distance. Hyper-plane distance gives a single measure for the difference between groups of samples in a PCA hyper-plane, something that is impossible visually with many samples of many groups in a multi-dimensional context. The metabolic distance was used to select metabolically diverged accessions of A. thaliana and to determine the impact of the environment on the metabolome of A. thaliana. The accessions thus selected (An-1, Col-0, Cvi and Eri) are representative for the metabolome diversity across the set of analysed accessions, and hence represent the baseline metabolome.

Engineering A. thaliana to produce the volatile (E)-nerolidol was used to alter indirect defence in A. thaliana. In Chapter 3 several genetic engineering strategies were used to generate transgenic lines that uniformly emit sufficient amount of the volatile. Combination of the gene responsible for (E)-nerolidol biosynthesis (FaNES1) with the gene responsible for biosynthesis of its precursor, farnesyl diphosphate synthase (FPS1L), both equipped with mitochondrial targeting signal, resulted in higher production of (E)-nerolidol than with FaNES1 alone. The transgenic production of (E)-nerolidol in Arabidopsis also resulted in the formation of non-volatile conjugates. Adding also 3-hydroxy-3-methylglutaryl CoA reductase 1 (HMGR1), a rate limiting enzyme of the mevalonate pathway, resulted in a further increase in the production of (E)-nerolidol as well as its non-volatile conjugates. Transgenic A. thaliana plants emitting (E)-nerolidol were more attractive to the insect Diadegma semiclausum, which is an important endoparasitoid of the larvae of Plutella xylostella (cabbage moth).

In Chapters 4 and 5 the chemical changes in and effects of transgenic A. thaliana accessions altered in indirect or direct defence on insect behaviour were characterised. In Chapter 4 the mitochondrial-targeted nerolidol synthase (COX-FaNES1) and the gene encoding the enzyme for the substrate (FPP) biosynthesis in mitochondria (COX-FPS2) were introduced into three A. thaliana accessions. Transgenic plants also emitted (E)-DMNT and linalool in addition to (E)-nerolidol. The aphid, Brevicoryne brassicae, was repelled by the transgenic lines of two of the accessions, although its performance on the transgenic lines was not affected. The aphid parasitoid, Diaeretiella rapae, preferred aphid-infested transgenic plants over aphid-infested wild-type for two of the accessions. Although another aphid predator, Episyrphus balteatus, did not differentiate between aphid-infested transgenic or wild-type plants, the results suggest that genetically engineering plants to modify their emission of VOCs holds promise for improving control of herbivores.

In Chapter 5, MYB28 was overexpressed in three A. thaliana accessions. MYB28 overexpression had different effects (positive as well as negative) on the total aliphatic glucosinolate level in different transformation events of the same genetic background, possibly as a result of tight post-transcriptional regulation of MYB28. Furthermore, enhancement of the aliphatic glucosinolate pathway seems to be genetic background specific. Leaf damage by Brassicaceae generalist Mamestra brassicae and specialist Plutella xylostella were negatively affected by MYB28 overexpression, giving promises for improvement of chewing pest damage control. Higher glucosinolate levels as a result of MYB28 overexpression affected insect performance positively in the specialist and negatively in the generalist. Statistical analysis revealed the differential influence of certain structural groups of aliphatic glucosinolates on the two different insects.

Chapter 6 demonstrates the application of the hyper-plane distance for the assessment of GM-mediated effects on the transcriptome. In this case, publicly available meta data containing the natural transcriptome variation in A. thaliana were proposed as a reference. Using this approach we showed that GM Arabidopsis lines with a novel indirect defence trait display changes in the transcriptome due to introduction of pleiotropic transgenes. However, the observed changes were well within the range of variation and plasticity in gene expression occurring naturally in A. thaliana. We also showed that unintended changes in the transcriptome are the result of other factors than the novel trait itself. This is an important observation because it implies that untargeted effects could be avoided or changed by using other strategies for transformation.

In Chapter 7 all the transgenic lines generated in my thesis work were included in a metabolomics approach to study the effect of genetic modification on the metabolome level. The primary selected accessions of A. thaliana (Chapter 2) formed the baseline metabolome and the hyper-plane distance measurement was employed for analysis of differences. Untargeted metabolomics analyses using GC-TOF-MS and LC-TOF-MS of shoot and root material showed that the metabolome of most of the transgenic lines was substantially equal to the baseline even though the baseline did not yet include environment-induced metabolome variation. We suggest that substantial equivalence of a GM line’s metabolome with the baseline can be used to infer a low or even no risk of the particular genetic modification for non-target organisms and can be used as a first-pass criterion in the assessment of non-target ecological effects.

Chapter 8 was written in collaboration with the two other PhD students from the same ERGO project. It summarizes and discusses the most important conclusions of the research done by the three PhD students and integrates the results in the form of guidelines for assessing the non-target ecological effects of a new GM crop. These guidelines suggest rules that must be taken into consideration when a request for permission for field trials or commercialisation of a new GM crop is submitted to COGEM.

Plant Metabolomics: Methods and Protocols
Hardy, N.W. ; Hall, R.D. - \ 2012
London : Springer – Humana Press (Methods in molecular biology 860) - ISBN 9781617795930 - 340
planten - metabolomica - plantenfysiologie - methodologie - protocollen - plants - metabolomics - plant physiology - methodology - protocols
The dynamic interplay of microbiota and mucosa drives establishment of homeostasis in conventionalized mice
Aidy, S.F. El - \ 2012
Wageningen University. Promotor(en): Michiel Kleerebezem, co-promotor(en): Peter van Baarlen; Erwin Zoetendal. - S.l. : s.n. - ISBN 9789461731951 - 168
kiemvrije dieren - muizen - darmmicro-organismen - homeostase - slijmvlies van het spijsverteringskanaal - transcriptomica - metabolomica - germfree animals - mice - intestinal microorganisms - homeostasis - digestive tract mucosa - transcriptomics - metabolomics

The intimate interplay between gut microbiota, host, and nutrient flow is crucial in defining the health status of the host. During microbial conventionalization of germfree mice, tightly regulated molecular responses assure the establishment of homeostasis and immune tolerance towards the microbiota. To decipher the temporal and regional dynamics of host-microbiota communication during the process of conventionalization, a combination of transcriptomics, (immune-)histology, metabonomics (tissue, urine, and plasma), as well as MITchip (Mouse Intestinal Tract chip) based microbiota profiling was employed. To this end, C57/B6 J germfree mice were conventionalized with mouse fecal microbiota and responses were followed in a time-resolved manner for thirty days. The colonizing microbiota was characterized by a shift from low towards higher diversity of its composition, over the period of conventionalization. Microbial colonization was rapidly (after one day) reflected by increased concentrations of specific urine and jejunal metabolites as well as by biologically relevant changes in jejunal tissue transcriptome profiles. Conversely, ileal and colonic transcriptome responses could be measured later, after four days post-conventionalization, and led towards stable molecular profiles at sixteen and thirty days of conventionalization, albeit with region-specific differences. The major molecular responses included strong induction of innate immune response followed by stimulation of adaptive and regulatory immune functions, as well as modulation of metabolic pathways involved in lipid, carbohydrate, and anabolic metabolism. Conventionalization was characterized by two stages separated by one stage of a single day which, particularly in the colon, resembled a transient stage of inflammation, based on transcriptomes, histology and transiently elevated levels of specific plasma markers. This state coincided with temporal domination of specific microbial groups that have previously been identified as “pathobionts”, suggestive of a transient state of dysbiosis. Extensive transcriptome profile analyses throughout the GI tract enabled the identification of central gene regulatory networks that govern the molecular responses during conventionalization and are proposed to serve as genetic signatures for the control of intestinal homeostasis in mice. Nearly all genes in these regulatory networks have human orthologues, suggesting that the biological findings of this study is also relevant for human intestinal biology. In support of this hypothesis, in the jejunum, the identified gene regulatory network appeared to be strongly associated with human metabolic disorders. This notion also suggests that at least in mice, possibly also in human, there is a prominent role of the proximal small intestine in systemic metabolic control.

This thesis exemplifies the pivotal role of the dynamic molecular interactions between the microbiota and the intestinal mucosa, in the establishment and maintenance of mucosal homeostasis in healthy mice. The molecular signatures obtained from these studies in mice may provide novel diagnostic tools and/or therapeutic targets in humans for specific disorders associated with intestinal dysbiosis and loss of mucosal homeostasis.

Keywords: C57/BL6 J mice, conventionalization, transcriptomics, (immune-)histology, metabonomics, microbiota

Genetical metabolomics in apples (Malus x domestica Borkh)
Khan, S.A. - \ 2012
Wageningen University. Promotor(en): Evert Jacobsen, co-promotor(en): Henk Schouten. - S.l. : s.n. - ISBN 9789461731371 - 184
appels - malus - plantenveredeling - moleculaire veredeling - metabolomica - moleculaire genetica - genetische modificatie - apples - malus - plant breeding - molecular breeding - metabolomics - molecular genetics - genetic engineering

The aim of this thesis was finding genes that control the production of potentially health beneficial metabolites in apple fruits. The approach was genetic mapping of secondary metabolites such as phenolic compounds in an F1 progeny, leading to the detection of genetic loci that controlled these metabolites. At these genetic loci candidate genes were identified, using the whole genome sequence of apple, and it was investigated whether the expression of these candidate genes in the F1 progeny correlated with the metabolite levels.

The cultivated apple (Malus x domestica Borkh) is among the most diverse and ubiquitously cultivated fruit species. It belongs to the family of Rosaceae which includes many commercial fruit species such as pear, strawberry, cherry, peach, apricot, almond, black cherry, and crab apple. Apple has a haploid chromosome number of 17. It is a self-incompatible and highly heterozygous crop. The breeding is further hampered by the long juvenile period which makes breeding in this crop a very slow process.

The saying “An apple a day keeps the doctor away” has encouraged many researchers to search for the “magic” ingredients found in apple. Due to the beneficial role of apple phenolics, it is also called as a “new agrochemical crop”. Apple possesses many health beneficial properties for human beings as it is a rich source of phenolic compounds.It has been associated with reducing the risks of certain diseases such as cancers, particularly prostate, liver, colon, and lung cancers, cardiovascular diseases, coronary heart diseases, asthma, type-2 diabetes, thrombotic stroke, and ischemic heart disease.

The second chapter of this thesis describes the construction of genetic linkage maps of the parents of a segregating population derived from the cross between the cultivars ‘Prima’ and ‘Fiesta’. For this purpose the already available linkage maps, as described in this chapter, were made denser by inclusion of 240 Diversity Array Technology (DArT) markers. Thus the total number of markers for ‘Prima’ and ‘Fiesta’ integrated map reached to 820. DArT-markers are hybridization based dominant DNA-markers. DArT provides a high-throughput whole genome genotyping platform for the detection and scoring of hundreds of polymorphic loci without any need for prior sequence information. This is the first report on DArT in horticultural trees. Genetic mapping of DArT markers in two mapping populations and their integration with other marker types showed that DArT is a powerful high throughput method for obtaining accurate and reproducible marker data, at low cost per data point. This method appears to be suitable for aligning the genetic maps of different segregating populations. Sequencing of the marker clones showed that they are significantly enriched for low copy, gene rich regions.

Chapter 3 describes metabolic diversity of Malus. Wild germplasm was compared to advanced breeding selections and to the segregating F1 population from the cross between the cultivars ‘Prima’ and ‘Fiesta’. The metabolic profiles were analyzed by means of liquid chromatography-mass spectrometry (LC-MS). LC-MS is an analytical chemistry technique that combines the physical separation capabilities of liquid chromatography with the mass analysis capabilities of mass spectrometry. This resulted in the detection of 418 putative metabolites in the peel and 254 in the flesh. Fruits from 23 wild species, eight advanced selections and the segregating F1 population were analyzed. The data were subjected to Principle Components Analysis (PCA). Variance analysis of the first PC showed that genetic variation accounted for 96.6 % in peel and 97.4 % in flesh of the total metabolic variation. Technical variation accounted for 1.4 % and 0.8%, while environmental variation accounted for 2.0% and 1.8% in peel and flesh respectively. The genetic variation between wild genotypes was very large, compared to the advanced selections and the F1 progeny. Only 8 % of the genetic variation of the first principle component was captured by the advanced selections. This indicates strong genetic erosion during breeding. This genetic erosion was mainly caused by reduction of the levels of several flavonoids including catechin, epicatechin and procyanidins. PCA of the F1 progeny of the ‘Prima’ x ‘Fiesta’ cross showed a clear 3:1 Mendelian segregation of metabolites. These metabolites were 4.2 fold less in both peel and flesh in progeny that had inherited the recessive alleles of a gene at the top of Linkage Group16 (LG16) from the heterozygous parents.

We found a separate group of 11 metabolites in peel and 12 in flesh. These metabolites were putatively identified as glycosylated forms of b-glycols: R-octane-1, 3-diol and its unsaturated form R-5-(Z)-octene-1, 3-diol which have a potential role in controlling infection by microorganisms and influence the aroma of some ciders. The levels of these metabolites were up to 50 fold more abundant in some progeny compared to both parents. Genetic mapping showed that this strong increase was caused by one locus at the top of LG8, in progeny that had inherited only the recessive alleles of that locus from the heterozygous parents. This research illustrates not only the strong genetic erosion in apple breeding regarding metabolic diversity, and strong reduction of flavonoids in some progeny, but also shows that inbreeding can lead to a strong increase of metabolites that were present at much lower levels in both parents and advanced selections. This loss and gain of metabolites was especially observed in case of accumulation of recessive alleles during inbreeding.

The genetic factors controlling metabolite composition were studied in more detail in Chapter 4. We investigated the genetic factors of the quantitative variation of these potentially beneficial compounds (Chapter 3, 4), by combining the genetic maps (Chapter 2) with the LC-MS data for thesegregating F1 population from the cross ‘Prima’ x ‘Fiesta’. This resulted into metabolite quantitative trait loci (mQTLs). When using the software MetaNetwork, 669 significant mQTLs were detected: 488 in the peel and 181 mQTLs in the flesh. Four linkage groups (LGs) i.e. LG1, LG8, LG13 and LG16 were found to contain mQTL hotspots, mainly regulating metabolites that belong to the phenylpropanoid pathway. These include various metabolites i.e. sinapate hexoside, coumaroyl hexoside, phloridzin, quinic acids, phenolic esters, kaempferol glycosides, quercetin glycosides, cyanidin pnetoside, flavan-3-ols (catechin, epicatechin), and procyanidins. The genetics of annotated metabolites was studied in more detail using MapQTL®. It was found that quercetin conjugates had mQTLs on LG1 and LG13. The most important mQTL hotspot with the largest number of metabolites was, however, detected at the top of LG16: mQTLs for 32 peel-related and 17 flesh-related phenolic compounds. The metabolites that mapped in the mQTL hotspot on LG16 all belong to the phenylpropanoid pathway of secondary metabolites. These compounds showed a monogenic Mendelian inheritance in a 3:1 segregation ratio. Procyanidins dimer II was used as a representative of the numerous compounds that mapped at the LG16 mQTL hotspot. By means of graphical genotyping of this monogenic trait, a genetic window could be made in which the gene that caused the mQTL hotspot should reside. We located structural genes involved in the phenolic biosynthetic pathway, using the genetic map together with the published whole genome sequence of apple. The structural gene leucoanthocyanidin reductase (MdLAR1) was detected in the mQTL hotspot window on LG16, as were seven transcription factor genes. To our knowledge, this is the first time that a QTL analysis was performed on such a high number of metabolites in an outbreeding plant species.

The expression of the candidate genes found in the mQTL window on LG16 was studied and discussed in Chapter 5. qPCR was used for this purpose and it was found that the expression of only the structural gene MdLAR1 was strongly positively correlated with the metabolite procyanidin dimer II content. Neither the expression profiles of other structural genes of the phenylpropanoid pathway, the transcription factor genes at the mQTL hotspot, nor of transcription factor genes outside the mQTLs hotspot, showed any significant correlation with the procyanidin dimmer II content that mapped at the mQTL hotpot. This indicates that MdLAR1 was the gene, which caused this mQTL hotspot (Chapter 5). The progeny that had inherited one or two copies of the dominant alleles (Mm, MM) showed on the average a 4.4 and 11.8 fold higher expression level of MdLAR1 respectively, compared to the progeny that had inherited the recessive alleles only (mm). This led to a 4.0 fold increase of procyanidin dimer II level at the ripe stage.

Strikingly, at the mQTL hotspot at the top of LG16, there is also a locus that controls acidity of the ripe fruits. However, the dominant alleles for acidity appeared to be in repulsion to the dominant alleles for high metabolite levels (Chapter 6). This shows that acidity is controlled by another gene than the metabolite levels. The combination of the genetic position based on the whole apple genome sequence, annotation of potential genes, and expression profiling indicated that the malic acid transporter gene MdALMT2 was responsible for the clear differences in malic acid content and pH in mature apple fruits of the segregating F1 population. The genetic inheritance of at least one dominant allele (MaMa/Mama) of this gene sufficed for a three-fold increase of the malic acid concentration and a reduction of the pH from 4 to 3 in ripe apples, compared to the presence of only the lower expressed recessive allele (mama). This malic acid transporter gene is located at the top of LG16.Malic acid is the predominant organic acid associated with the pH in apple fruits. It is synthesized in the cytoplasm and transported into the cell vacuole. The concentration of malic acid in the cell vacuole determines the pH of the cell. pH is very important for the overall taste of many fruits, including apple, and has profound effects on the organoleptic quality of apples. The pH of mature apples was genetically mapped on LG16 in the segregating population from the cross ‘Prima’ x ‘Fiesta’. To our knowledge, this is the first time that the genetic segregation of the pH in apple is assigned to a specific gene. Further, this gene has not been reported yet in conjunction to pH of apples or other fruits. After cloning of the MdALMT2 gene, it can be used for, proof of principle, influencing the acidic of existing varieties either by silencing this gene in more acidic cultivars or by inserting this gene into the low acidic cultivars. Another step would be to develop an allele specific molecular marker for selection (Marker Assisted Selection) of the acidity of fruits already at seedling stage, five years before the trees carry fruits.

In another study, a dominantly mutated allele of the transcription factor gene MdMYB10,including its upstream promoter, coding region and terminator sequence, was introduced by transformation into apple, strawberry and potato plants. The dominantly inherited mutant allele of MdMYB10 from apple induces anthocyanin production throughout the plant, also at the early stage after transformation. The aim was to determine whether MdMYB10 could be used as a visible selectable marker for plant transformation as an alternative to chemically selectable markers, such as kanamycin resistance. After transformation, the color of calli, shoots and well-growing plants were evaluated. Red and green shoots were harvested from apple explants and examined for the presence of the MdMYB10 gene by PCR analysis. Red shoots of apple explants always contained the MdMYB10 gene but not all MdMYB10 containing shoots were red. Strawberry plants transformed with the MdMYB10 gene showed anthocyanin accumulation in leaves and roots. No visible accumulation of anthocyanin could be observed in potato plants grown in vitro, even the ones carrying the MdMYB10 gene. However, acid methanol extracts of potato shoots or roots carrying the MdMYB10 gene contained up to four times higher anthocyanin content than control plants. Therefore, anthocyanin production as a result of the dominant MdMYB1010 gene can be used as a selectable marker for apple, strawberry and potato transformation, replacing kanamycin resistance gene such as nptII. We reported this MdMYB10 as a cisgenic selectable marker gene for apple transformation (Chapter 7). The results from all experimental chapters have been discussed in a broader sense in the general discussion (Chapter 8). The future prospectives and potential challenges in the genetical metabolomics are also highlighted. The approaches we developed in the current thesis could be used not only for developing potentially a more healthy and improved apple but can also be applied for the genetical metabolomics studies in other important crops.

Zonnige toekomst voor carotenoïden uit algen
Hark, M. van der; Lamers, P.P. - \ 2011
Voedingsmiddelentechnologie (2011)11. - ISSN 0042-7934 - p. 20 - 21.
dunaliella - carotenoïden - metabolomica - industriële microbiologie - algen - biobased economy - dunaliella - carotenoids - metabolomics - industrial microbiology - algae - biobased economy
Algenonderzoeker Packo Lamers keek naar het celmetabolisme en gebruikte dat als ingang voor de procesvoering. De alg Dunaliella salina produceerde vervolgens tien keer zo veel carotenoïden als in commerciële open vijvers. Productie op grote schaal in bioreactoren lijkt daarmee haalbaar.En zijn methode is breed toepasbaar op pigmenten en visvetzuren
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