Seeing the forest for the trees : retrieving plant secondary biochemical pathways from metabolome networks

Over the last decade, a giant leap forward has been made in resolving the main bottleneck in metabolomics, i.e., the structural characterization of the many unknowns. This has led to the next challenge in this research field: retrieving biochemical pathway information from the various types of networks that can be constructed from metabolome data. Searching putative biochemical pathways, referred to as biotransformation paths, is complicated because several flaws occur during the construction of metabolome networks. Multiple network analysis tools have been developed to deal with these flaws, while in silico retrosynthesis is appearing as an alternative approach. In this review, the different types of metabolome networks, their flaws, and the various tools to trace these biotransformation paths are discussed

Unraveling the metabolome of grapevine through FT-ICR-MS : from nutritional value to pathogen resistance

Grapevine (Vitis vinifera L.) is one of most important fruit crops in the world due to its numerous food products, namely fresh and dried table grapes, wine and intermediate products, with a high economic importance worldwide. Concerning nutritional value, grapes are highly studied and a great diversity of secondary bioactive metabolites has already been identified. However, an important grapevine by-product, also containing a high nutritional value, but sometimes disregarded is grapevine leaves. They are an abundant source of compounds with interest in human health and are already included in human diet in several countries. The study of the nutritional values of this by-product is essential towards the improvement of food systems. Hence, in this PhD dissertation an untargeted metabolomic profiling of the leaves of Vitis vinifera cultivar ‘Pinot noir’ was performed by Fourier-transform ion cyclotron-resonance mass spectrometry (FT-ICR-MS), (CHAPTER II). Numerous compounds with diverse nutritional and pharmacological properties, particularly polyphenols and phenolic compounds, several phytosterols and fatty acids (the most represented lipids’ secondary class), were identified. Grapevine leaves were also evaluated for their antioxidant capacity. It was found that leaves present a high antioxidant capacity, similar to berries, putting grapevine leaves at the top of the list of foods with the highest antioxidant activity. Traditional premium cultivars of wine and table grapes are highly susceptible to various diseases. Grapevine downy mildew, powdery mildew and gray mold are caused, respectively, by the biotrophic oomycete Plasmopara viticola (Berk. & Curt.) Berl. & de Toni) Beri, et de Toni], by the biotrophic fungus Erysiphe necator (Schweinf.) Burrill) and by the necrotrophic fungus Botrytis cinerea Pers.). In Europe, disease management became one of the main tasks for viticulture, being the current strategy, for disease control, the massive use of fungicides and pesticides in each growing season. This practice has several associated problems, from the environmental impact to the economical level, and even in human health. The alternative approach to the application of pesticides is breeding for resistance, clearly the most effective and sustainable approach, particularly if coupled to the selection of desirable traits from local grapevine cultivars. However, a successful breeding program of grape plants with increased resistance traits against pathogens requires not only an understanding of the innate resistance mechanisms of cultivars against fungi/oomycetes, but also the identification of biomarkers of tolerance or susceptibility. Among these, metabolic biomarkers may prove particularly useful, not only because they can be determined in a high throughput way but, above all, because metabolites provide an accurate image of the metabolic state of the plant. To better understand the metabolic differences associated with intrinsic defence mechanisms of grapevine to pathogens, the metabolome of several genotypes with different tolerance degrees to fungal/oomycete pathogens was compared through an untargeted metabolomics approach by FT-ICR-MS (CHAPTERS III, IV and V). First, a comparison of two Vitis vinifera (V. vinifera cv. Trincadeira e V. vinifera cv. Regent, susceptible and tolerant, respectively, to pathogens) was performed and discriminatory compounds between these two cultivars, were identified (CHAPTER III). Also, through the comparison of the metabolome of one Vitis vinifera (V. vinifera cv. Cabernet Sauvignon, susceptible to pathogens) and one Vitis species (Vitis rotundifolia, tolerant), was possible to distinguish both genotypes and determine that Vitis rotundifolia metabolome appeared to be more complex according to the chemical formulas analysed (CHAPTER IV). Albeit grapevine metabolome is complex, it is possible to distinguish Vitis species and different genotypes within the same species. Ultimately, to identify compounds that contribute to the segregation between susceptible and tolerant grapevines, eleven Vitis genotypes, were compared at the metabolite level (CHAPTER V). From all the metabolites identified, seven compounds with a higher accumulation on susceptible genotypes were selected. Their metabolic pathways were analysed and the expression profile of biosynthesis and/or degradation enzymes coding genes was evaluated by Real-time Polymerase Chain Reaction (qPCR). qPCR studies require as internal controls one or more reference genes. Hence, in this study, ten possible reference genes were tested and the three most stable reference genes (ubiquitin-conjugating enzyme – UBQ, SAND family protein - SAND and elongation factor 1-alpha - EF1α) were established for our analysis and selected for qPCR data normalization. Our data revealed that the leucoanthocyanidin reductase 2 gene (LAR2) presented a significant increase of expression in susceptible genotypes, in accordance with catechin accumulation in this analysis group, being a possible metabolic constitutive biomarker, associated to susceptibility. The interaction of grapevine-P.viticola was also analysed by FT-ICR-MS (CHAPTERS VI and VII). The metabolome of Vitis vinifera cv. Trincadeira after 24 hours post-infection (hpi) was analysed and, based only on the chemical profile and representation plots, the discrimination between infected and non-infected grapevine leaves was possible (CHAPTER VI). A further analysis of Vitis vinifera cv. Trincadeira infected with P. viticola was performed through Matrix-assisted laser desorption/ionization (MALDI) FT-ICR-MS imaging, to identify leaf surface compounds related to the grapevine-pathogen interaction (CHAPTER VII). Putatively identified sucrose ions were more abundant on P. viticola infected leaves when compared to control ones. Also, sucrose was mainly located around the veins, which is an indicator of the correlation of putatively identified sucrose at P. viticola infection sites, leading to the hypothesis that the pathogen is extracting sucrose from grapevine to reproduce. Each chapter was written as a scientific article and has its own abstract, introduction, materials and methods, results and discussion, conclusion, acknowledgments and references. The results obtained in this PhD thesis are a starting point on the elucidation of the molecular mechanisms related to the intrinsic tolerance/susceptibility to different pathogens. Also, these results can be used for the development of new approaches and help to improve breeding and introgression line programs

Metabolic engineering and modelling of Escherichia coli for the production of succinate

Current climate issues and the ongoing depletion of oil reserves have led to an increased attention for biobased production processes. Not only the production of bio-energy but also biochemicals have gained interest. Recent reports of the US department of energy and the GROWTH program of the European commission review a comprehensive list of chemicals that can be produced via biological processes and which may be of great importance to sustain a green chemical industry in the future. Succinate is one of those biochemicals. Today, this compound is synthesised via maleic anhydride, which is produced by a petrochemical production process. The conditions which a biological production processes have to meet to be economically viable are quite strict. Such a process has to obtain a yield of 0.88 g/g, a rate between 1.8 and 2.5 g/l/h and a titer around 80 g/l. None of the available (reported) processes reach either of these values. In most cases the rate and the titer are still a problem. To optimise succinate production via metabolic engineering, first a mutation strategy has to be developed. This strategy can then be applied to a suitable production host. The choice of this host has nowadays become less important due to the recent developments in genetic engineering and synthetic biology. These developments allow the introduction or altering of almost every cellular function. What has become important is the availability of information on the potential host and its genetic accessibility. E. coli is therefore still an excellent host for the development of production processes. Since its isolation vast amounts of information have been gathered and several biological databases are devoted to it. Moreover, almost each cellular function has been modified. However, E. coli does not naturally produce succinate in large amounts. It will have to undergo some genetic modifications to overproduce this chemical. Which modifications are needed can be uncovered in silico. A functional and comparative genomics analyses of natural producing and non-producing strains revealed which genes and reactions may influence succinate production. The optimal biochemical route towards succinate is then uncovered via stoichiometric network analysis. For this analysis, elementary flux modes was combined with partial least squares regression. Both tools resulted in the identification of optimal biochemical production routes for several substrates and allowed to evaluate how reactions that do not naturally occur in E. coli may affect the succinate yield. The transport reaction is one of the reactions that could be identified by the EFM-PLS model. E. coli possesses both succinate import as well as export proteins. However, export is normally only active under anaerobic conditions and import under aerobic conditions. Therefore, the import protein was knocked out and the export protein was expressed with an artificial promoter. These modifications led to an increased succinate yield and production rate, but also revealed alternative import proteins. An analysis of the phenotype of mutant strains in these alternative importers did however not lead to increases in succinate yield. These mutations influenced biomass yield and growth rate. A second route that was identified in the stoichiometric network analysis was the glyoxylate route. This route correlated positively with succinate production and is strongly regulated by the transcription factors ArcA and IclR. In order to gain more insight into the synergy that may exist between both regulators, knock outs in both genes were studied under chemostat and batch conditions. This analysis revealed a synergetic effect between both proteins on the biomass yield. A strain in which both arcA and iclR are knocked out showed a biomass yield that approached the maximal theoretical yield. The single knock out strains did not have such an outspoken phenotype. Finally, several mutations were introduced and evaluated for succinate production and byproduct formation. The formation of acetate was studied in detail to uncover alternative acetate formation reactions. First, the known reactions, acetate kinase, phospho-acetyltransferase and pyruvate oxidase were knocked out. This resulted in a significant decrease in acetate production but not in the total elimination. Several alternatives such as citrate lyase and acetate CoA-transferase were evaluated, but without success. The remaining acetate formation reactions could not be identified. Succinate dehydrogenase can be seen as one of the most crucial enzymes for succinate production. This enzyme converts succinate into fumarate and therefore has to be knocked out to increase production. Strains that possess a succinate dehydrogenase deletion immediately show an increased production. However, pyruvate becomes one of the main byproducts. Several enzymes influence pyruvate production. The most important enzymes in the context of succinate production are PEP carboxykinase, oxaloacetate decarboxylase, malic enzyme, PEP carboxylase, and citrate synthase. The three former reactions are gluconeogenic reactions that can form futile cycles. Deletions in these genes resulted in an increase in biomass yield due to a more energy efficient metabolism, but does not increase succinate yield. Point mutations in PEP carboxylase and citrate synthase increased the flux towards the TCA cycle. The flux ratio between the glyoxylate pathway and the reductive and oxidative TCA cycle can be influenced by these enzymes. The activity of the reductive TCA is however strongly dependent on the availability of reduced equivalents. To modulate this availability a point mutation was introduced in FNR, an anaerobic transcription factor that activates the reductive TCA and represses the electron transport chain. Although none of the developed strains are economically viable yet, many of the mutations that have been introduced show great promise for future improvements. In fact, the next steps in strain development should not be to identify new targets to modify, but rather to fine tune activities of the routes towards succinate in such a way that the theoretical yields can be approached with sufficiently high rates

Metabolite and reaction inference based on enzyme specificities

Motivation: Many enzymes are not absolutely specific, or even promiscuous: they can catalyze transformations of more compounds than the traditional ones as listed in e.g. KEGG. This information is currently only available in databases, such as the BRENDA enzyme activity database. In this paper, we propose to model enzyme aspecificity by predicting whether an input compound is likely to be transformed by a certain enzyme. Such a predictor has many applications, for example to complete reconstructed metabolic networks, to aid in metabolic engineering or to help identify unknown peaks in mass spectra. Results: We have developed a system for metabolite and reaction inference based on enzyme specificities (MaRIboES). It employs structural and stereochemistry similarity measures and molecular fingerprints to generalise enzymatic reactions based on data available in BRENDA. Leave-one-out cross-validation shows that 80% of known reactions are predicted well. Application to the yeast glycolytic and pentose phosphate pathways predicts a large number of known and new reactions, often leading to the formation of novel compounds, as well as a number of interesting bypasses and cross-links.Electrical Engineering, Mathematics and Computer Scienc