CHAPTER 1 General introduction and outline of the thesis Kashif Ali Natural Products Laboratory, Institute of Biology, Leiden University, The Netherlands 1
Chapter 1 General Introduction Grapevine (Vitis spp.) is globally one of the most important fruit species due to the numerous uses of its fruits, especially in the production of wine. Grapes and wine posses a significant place in the earliest written archives and associated with many agricultural and religious activities and ancient historical development of human culture (Thomas et al. 1993; Bowers et al. 1999). Grapevine has been easily cultivated across the globe but more successfully in temperate climate regions with enough rain, warm and dry summers with mild winters (Vivier and Pretorius 2000). The Vitaceae family consists of almost one thousand species, grouped in seventeen genera. Grapevines are classified in the Vitis genus and among the Vitis species, Vitis vinifera is currently one of the most cultivated fruit crops around the world because of its use in wine production (Lodhi and Reisch 1995). It is accepted that plants are capable to produce compounds of complex and diverse structures and functions, known as primary and secondary metabolites. These metabolites are not only vital for the living system to perform the normal physiological functions but also crucial to deal with numerous biotic and abiotic stress factors (Lewinsohn et al. 2001; Dixon 2001; Harborne 2001). The total number of metabolites in plants is roughly estimated in the range of 30,000 (Oksman-Caldentey and Inzé 2004; Verpoorte et al. 2008) and the unbiased analysis of all these metabolites can provide useful information to define living systems at the level of genes, transcript, and proteins (Jander et al. 2004; Trethewey et al. 1999). The approach aimed towards providing a comprehensive qualitative and quantitative overview of all the metabolites present in a system at a particular time is termed as Metabolomics. With the advancement in the field of analytical chemistry, more powerful and sophisticated tools (like mass spectrometry and nuclear magnetic resonance) for such chemical analyses have been introduced. Chemical analysis techniques applied to metabolites profiling should be unbiased, rapid, and reproducible, while requiring only simple sample preparation. Many platforms are being used for the high throughput analysis of plant metabolites, but vary according to their sensitivity (Kopka et al. 2004; Verpoorte et al. 2008). The development of methods and algorithms for the multivariate statistical modeling have contributed much to metabolomics as they opened the way for handling the huge datasets of large-scale metabolic analyses (Crockford et al. 2006). 2
General introduction Nuclear magnetic resonance has an exceptional place in the chemical analyses of food and apart from its routine use in the identification, characterization, and structure elucidation of molecules, NMR is now increasingly popular in the area of metabolome analysis (Son et al. 2009). Although criticized for its low sensitivity, the most promising features of NMR are its non-destructive nature, simple sample preparation and short measurement time. A major advantage of NMR is that materials such as wine, beverages, and body fluids can be measured as such; hence the spectral data can be directly used for quantification as the peak intensity is directly proportional to molar concentration. The nonselectivity of NMR made it an ideal tool for the profiling of a broad range of metabolites in the field of agriculture (Dixon et al. 2006). A reliable extraction of metabolites from the biological matrices is necessary for an accurate snap shot of the metabolome. The complete coverage is always a difficult task due to the presence of a wide array of compounds at different concentrations with varied polarities. This, with other factors as well, makes a single, high throughput extraction procedure nearly incapable to extract the whole range of metabolites. Based on sample chemistry and aim of the research, many extraction protocols for metabolomics studies have been published, offering different advantages but also having limitations (Lisec et al. 2006; De Vos et al. 2007; Kruger et al. 2008; Kim et al. 2010). For samples with special characteristics like high sugar content (grape berries, for example), the analytical method needs to be combined with a more specific sample preparation (the use of solid phase extraction, for instance) in order to detect minor compounds. Chemical characterization of the phenotype of an organism has become the focal point in recent years. The analysis of low molecular weight compounds, i.e. metabolites, seems to reflect the physiological activities of an organism or tissue under different conditions. In combination with different multivariate data analyses tools, such as principal components analysis (PCA), NMR has been used for the fingerprinting or metabolic profiling of various sample types (Brescia et al. 2002; Charlton et al. 2002). This combination has been very useful for the characterization of different plant species (Kim et al. 2005), and cultivars as well (Ali et al. 2009). In the case of berries, NMR coupled to multivariate analyses has been used to study the effects of growing areas, vintage, soil, and climate (Pereira et al. 2005; Pereira et al. 2006a). 3
Chapter 1 Being one of the most important fruits, knowledge regarding the development and maturation of grape berries is of great economical interest. Climacteric fruit such as tomatoes and apples have been well studied but comparatively less is known about the development and ripening of non-climacteric fruits e.g. grapes and strawberry (Giovannoni 2004; Given et al. 1988). Considerable scientific efforts have been made to understand the complex series of physical and biochemical changes of grape berries during their development cycle (Coombe 1992). But today, the major concerns of the viticulturists are size, coloration, control of ripening, acidity, and volatile and nonvolatile contents of the grape berry. The chemical analysis of complex mixtures like wine can be of great importance as it can be used for the differentiation of wines based on the grapevine variety, yeast strain, geographical origin, terroir, and vintage. Different factors like grapevine variety, harvest time, vineyard environment, yeast strain, winemaking technologies, storage time, and human practices, have an affect on wine quality which is determined by the concentration and composition of the compounds present. Thus on this chemical basis, classification and characterization of wine is feasible through qualitative and quantitative information of the wine constituents (Pérez-Magariño and González-San José 2006; Castillo-Sánchez et al. 2006; Matejicek et al. 2005; Guash-Jane et al. 2004). The most important and basic factor for making wine of good quality is the grape variety and because of this many articles on grapes and wine quality relationships have been published (Gergaud and Ginsburgh 2008). In addition to their economic and social importance of grapes, an increasing number of medicinal advantages have also been attributed to this fruit. Grapes and wine are known to contain relatively high concentrations of phenolics which results in many health effecting properties. Studies using human (Zern et al. 2005), and animal (Cui et al. 2002; Fuhrman et al. 2005; Seymour et al. 2008) models have shown that grapes and wine phenolics possess anti-oxidative and anti-inflammatory properties. The obvious importance of this fruit and its product, i.e. wine, make the generation of metabolic profiling data imperative in order to create a comprehensive understanding of different metabolic behaviors responsible for several key physiological and pharmacological activities of grapes and wine. 4
General introduction The studies of phytoalexins provide a large field of interest for plant pathologist and biochemists concerning the aspects of biosynthesis of these compounds in plants and their metabolism by pathogenic organisms. Phytoalexins are low molecular weight antimicrobial secondary metabolites that are produced upon microbial infection of the plant (Harborne 1999). Since phytoalexins have been shown to possess biological activities against a wide range of pathogens, they can be considered as part of plant disease resistance (Derckel et al. 1999). Although phytoalexins display an enormous chemical diversity, in Vitaceae they seem to constitute a rather restricted group of molecules belonging to the stilbene family, with the basic skeleton based on resveratrol. It has been demonstrated that resveratrol and its oxidation products like α-, β-, ε-, and γ- viniferins, are synthesized by grapevine leaves following fungal infection and UV light irradiation (Langcake and Pryce 1977). A study showed that these phytoalexins were produced in different grapevine cultivars when infected with the downy mildew pathogen Plasmopara viticola (Pezet et al. 2004). Schnee et al. (2008) showed that upon infection with powdery mildew (Erysiphe necator), the fungal growth is restricted on leaves in resistant cultivars and the amount of stilbenes expressed at the infection site allowed to discriminate resistant and susceptible cultivars. Aim of the thesis The aim of this research is to generate NMR spectroscopy and chemometrics-based metabolic profiling data in order to characterize different grape cultivars and wine types and vintage, to study grapes physiological processes like berry growth and response against infection, and to correlate the profiling data with the bioactivity data using chemometrics methods. Outline of the thesis The thesis begins with a comprehensive review on grapevine and wine chemistry, an overview on their pharmacological importance, diseases and phytoalexins in grapevine, and with a brief account of the role of biotechnology in grape and wine research (Chapter 2). A literature survey related to different platforms used in plant metabolomics and their key applications in grapes and wine are presented in Chapter 3. 5
Chapter 1 The optimization of the pre-analytical method for NMR spectroscopy-based metabolomics of different grape cultivars (Chapter 4) and the application of this method to understand the biochemical changes happening during berry ripening are discussed in Chapter 5. The use of chemometric methods for the prediction of anti- TNFα activity in the different grape cultivars, at different developmental stages, is presented in Chapter 6. White wine type and vintage characterization along with the evaluation of metabolites responsible for different sensory attributes in wine was also performed (Chapter 7). The inhibition potential of different red wines from different vintages against TNFα production is also assessed and presented in Chapter 8. Related to grapevine diseases, the metabolic characterization of six different (non-infected) grapevine cultivars was performed to underline the metabolic differences (Chapter 9). The metabolic response generated by a resistant and a susceptible cultivar against the pathogen, Plasmopara viticola, was also analyzed and discussed in Chapter 10. Finally in Chapter 11, a general discussion, conclusions, and future perspectives related to grapes and wine research are presented. 6