Yury Tikunov

A Novel Approach for Nontargeted Data Analysis for Metabolomics. Large-Scale Profiling of Tomato Fruit Volatiles

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

RNA Interference Silencing of Chalcone Synthase, the First Step in the Flavonoid Biosynthesis Pathway, Leads to Parthenocarpic Tomato Fruits

Parthenocarpy, the formation of seedless fruits in the absence of functional fertilization, is a desirable trait for several important crop plants, including tomato (Solanum lycopersicum). Seedless fruits can be of great value for consumers, the processing industry, and breeding companies. In this article, we propose a novel strategy to obtain parthenocarpic tomatoes by down-regulation of the flavonoid biosynthesis pathway using RNA interference (RNAi)-mediated suppression of chalcone synthase (CHS), the first gene in the flavonoid pathway. In CHS RNAi plants, total flavonoid levels, transcript levels of both Chs1 and Chs2, as well as CHS enzyme activity were reduced by up to a few percent of the corresponding wild-type values. Surprisingly, all strong Chs-silenced tomato lines developed parthenocarpic fruits. Although a relation between flavonoids and parthenocarpic fruit development has never been described, it is well known that flavonoids are essential for pollen development and pollen tube growth and, hence, play an essential role in plant reproduction. The observed parthenocarpic fruit development appeared to be pollination dependent, and Chs RNAi fruits displayed impaired pollen tube growth. Our results lead to novel insight in the mechanisms underlying parthenocarpic fruit development. The potential of this technology for applications in plant breeding and biotechnology will be discussed.

The Tomato FRUITFULL Homologs TDR4/FUL1 and MBP7/FUL2 Regulate Ethylene-Independent Aspects of Fruit Ripening

Ripening of the tomato fruit is accompanied by an increase in ethylene production and involves color changes, altered sugar metabolism, tissue softening, and the synthesis of aroma volatiles. This study shows that the MADS domain transcription factors FUL1 and FUL2 play a role in the regulation of these ripening processes, but in an ethylene-independent manner. Tomato (Solanum lycopersicum) contains two close homologs of the Arabidopsis thaliana MADS domain transcription factor FRUITFULL (FUL), FUL1 (previously called TDR4) and FUL2 (previously MBP7). Both proteins interact with the ripening regulator RIPENING INHIBITOR (RIN) and are expressed during fruit ripening. To elucidate their function in tomato, we characterized single and double FUL1 and FUL2 knockdown lines. Whereas the single lines only showed very mild alterations in fruit pigmentation, the double silenced lines exhibited an orange-ripe fruit phenotype due to highly reduced lycopene levels, suggesting that FUL1 and FUL2 have a redundant function in fruit ripening. More detailed analyses of the phenotype, transcriptome, and metabolome of the fruits silenced for both FUL1 and FUL2 suggest that the genes are involved in cell wall modification, the production of cuticle components and volatiles, and glutamic acid (Glu) accumulation. Glu is responsible for the characteristic umami taste of the present-day cultivated tomato fruit. In contrast with previously identified ripening regulators, FUL1 and FUL2 do not regulate ethylene biosynthesis but influence ripening in an ethylene-independent manner. Our data combined with those of others suggest that FUL1/2 and TOMATO AGAMOUS-LIKE1 regulate different subsets of the known RIN targets, probably in a protein complex with the latter.

MSClust: a tool for unsupervised mass spectra extraction of chromatography-mass spectrometry ion-wise aligned data

Mass peak alignment (ion-wise alignment) has recently become a popular method for unsupervised data analysis in untargeted metabolic profiling. Here we present MSClust—a software tool for analysis GC–MS and LC–MS datasets derived from untargeted profiling. MSClust performs data reduction using unsupervised clustering and extraction of putative metabolite mass spectra from ion-wise chromatographic alignment data. The algorithm is based on the subtractive fuzzy clustering method that allows unsupervised determination of a number of metabolites in a data set and can deal with uncertain memberships of mass peaks in overlapping mass spectra. This approach is based purely on the actual information present in the data and does not require any prior metabolite knowledge. MSClust can be applied for both GC–MS and LC–MS alignment data sets.

A Role for Differential Glycoconjugation in the Emission of Phenylpropanoid Volatiles from Tomato Fruit Discovered Using a Metabolic Data Fusion Approach

A role for differential glycoconjugation in the emission of phenylpropanoid volatiles from ripening tomato fruit (Solanum lycopersicum) upon fruit tissue disruption has been discovered in this study. Application of a multiinstrumental analytical platform for metabolic profiling of fruits from a diverse collection of tomato cultivars revealed that emission of three discriminatory phenylpropanoid volatiles, namely methyl salicylate, guaiacol, and eugenol, took place upon disruption of fruit tissue through cleavage of the corresponding glycoconjugates, identified putatively as hexose-pentosides. However, in certain genotypes, phenylpropanoid volatile emission was arrested due to the corresponding hexose-pentoside precursors having been converted into glycoconjugate species of a higher complexity: dihexose-pentosides and malonyl-dihexose-pentosides. This glycoside conversion was established to occur in tomato fruit during the later phases of fruit ripening and has consequently led to the inability of red fruits of these genotypes to emit key phenylpropanoid volatiles upon fruit tissue disruption. This principle of volatile emission regulation can pave the way to new strategies for controlling tomato fruit flavor and taste.

Metabolomics and molecular marker analysis to explore pepper (Capsicum sp.) biodiversity

An overview of the metabolic diversity in ripe fruits of a collection of 32 diverse pepper (Capsicum sp.) accessions was obtained by measuring the composition of both semi-polar and volatile metabolites in fruit pericarp, using untargeted LC–MS and headspace GC–MS platforms, respectively. Accessions represented C. annuum, C. chinense, C. frutescens and C. baccatum species, which were selected based on variation in morphological characters, pungency and geographic origin. Genotypic analysis using AFLP markers confirmed the phylogenetic clustering of accessions according to Capsicum species and separated C. baccatum from the C. annuum–C. chinense–C. frutescens complex. Species-specific clustering was also observed when accessions were grouped based on their semi-polar metabolite profiles. In total 88 semi-polar metabolites could be putatively identified. A large proportion of these metabolites represented conjugates of the main pepper flavonoids (quercetin, apigenin and luteolin) decorated with different sugar groups at different positions along the aglycone. In addition, a large group of acyclic diterpenoid glycosides, called capsianosides, was found to be highly abundant in all C. annuum genotypes. In contrast to the variation in semi-polar metabolites, the variation in volatiles corresponded well to the differences in pungency between the accessions. This was particularly true for branched fatty acid esters present in pungent accessions, which may reflect the activity through the acyl branch of the metabolic pathway leading to capsaicinoids. In addition, large genetic variation was observed for many well-established pepper aroma compounds. These profiling data can be used in breeding programs aimed at improving metabolite-based quality traits such as flavour and health-related metabolites in pepper fruits.

A correlation network approach to metabolic data analysis for tomato fruits

Network analysis of correlations between abundances of metabolites across tomato genotypes can help in unraveling the biological basis of organoleptic variation in tomato. We illustrate how to construct and interpret simple correlations networks using metabolic data collected on a diverse set of tomato genotypes. Various types of correlations are calculated and displayed in the form of networks. Interpretations on the basis of network analyses are compared to interpretations following principal components analysis.

The expanded tomato fruit volatile landscape

The present review aims to synthesize our present knowledge about the mechanisms implied in the biosynthesis of volatile compounds in the ripe tomato fruit, which have a key role in tomato flavour. The difficulties in identifiying not only genes or genomic regions but also individual target compounds for plant breeding are addressed. Ample variability in the levels of almost any volatile compound exists, not only in the populations derived from interspecific crosses but also in heirloom varieties and even in commercial hybrids. Quantitative trait loci (QTLs) for all tomato aroma volatiles have been identified in collections derived from both intraspecific and interspecific crosses with different wild tomato species and they (i) fail to co-localize with structural genes in the volatile biosynthetic pathways and (ii) reveal very little coincidence in the genomic regions characterized, indicating that there is ample opportunity to reinforce the levels of the volatiles of interest. Some of the identified genes may be useful as markers or as biotechnological tools to enhance tomato aroma. Current knowledge about the major volatile biosynthetic pathways in the fruit is summarized. Finally, and based on recent reports, it is stressed that conjugation to other metabolites such as sugars seems to play a key role in the modulation of volatile release, at least in some metabolic pathways.

NON-SMOKY GLYCOSYLTRANSFERASE1 Prevents the Release of Smoky Aroma from Tomato Fruit

The activity of NON-SMOKY GLYCOSYLTRANSFERASE1 (NSGT1) mediates the conversion of hydrolysis-susceptible glycosides of phenylpropanoid volatiles into hydrolysis-resistant forms and prevents damage-induced release of these volatiles in tomato fruit. This leads to a perceivable reduction in the smoky aroma intensity of these fruits compared to fruits of cultivars containing a truncated NSGT1 gene. Phenylpropanoid volatiles are responsible for the key tomato fruit (Solanum lycopersicum) aroma attribute termed “smoky.” Release of these volatiles from their glycosylated precursors, rather than their biosynthesis, is the major determinant of smoky aroma in cultivated tomato. Using a combinatorial omics approach, we identified the NON-SMOKY GLYCOSYLTRANSFERASE1 (NSGT1) gene. Expression of NSGT1 is induced during fruit ripening, and the encoded enzyme converts the cleavable diglycosides of the smoky-related phenylpropanoid volatiles into noncleavable triglycosides, thereby preventing their deglycosylation and release from tomato fruit upon tissue disruption. In an nsgt1/nsgt1 background, further glycosylation of phenylpropanoid volatile diglycosides does not occur, thereby enabling their cleavage and the release of corresponding volatiles. Using reverse genetics approaches, the NSGT1-mediated glycosylation was shown to be the molecular mechanism underlying the major quantitative trait locus for smoky aroma. Sensory trials with transgenic fruits, in which the inactive nsgt1 was complemented with the functional NSGT1, showed a significant and perceivable reduction in smoky aroma. NSGT1 may be used in a precision breeding strategy toward development of tomato fruits with distinct flavor phenotypes.

A taste of sweet pepper: Volatile and non-volatile chemical composition of fresh sweet pepper (Capsicum annuum) in relation to sensory evaluation of taste

In this study volatile and non-volatile compounds, as well as some breeding parameters, were measured in mature fruits of elite sweet pepper (Capsicum annuum) lines and hybrids from a commercial breeding program, several cultivated genotypes and one gene bank accession. In addition, all genotypes were evaluated for taste by a trained descriptive sensory expert panel. Metabolic contrasts between genotypes were caused by clusters of volatile and non-volatile compounds, which could be related to metabolic pathways and common biochemical precursors. Clusters of phenolic derivatives, higher alkanes, sesquiterpenes and lipid derived volatiles formed the major determinants of the genotypic differences. Flavour was described with the use of 14 taste attributes, of which the texture related attributes and the sweet-sour contrast were the most discriminatory factors. The attributes juiciness, toughness, crunchiness, stickiness, sweetness, aroma, sourness and fruity/apple taste could be significantly predicted with combined volatile and non-volatile data. Fructose and (E)-2-hexen-1-ol were highly correlated with aroma, fruity/apple taste and sweetness. New relations were found for fruity/apple taste and sweetness with the compounds p-menth-1-en-9-al, (E)-β-ocimene, (Z)-2-penten-1-ol and (E)-geranylacetone. Based on the overall biochemical and sensory results, the perspectives for flavour improvement by breeding are discussed.