Metabolic characterization of loci affecting sensory attributes in tomato allows an assessment of the influence of the levels of primary metabolites and volatile organic contents

Numerous studies have revealed the extent of genetic and phenotypic variation between both species and cultivars of tomato. Using a series of tomato lines resulting from crosses between a cherry tomato and three independent large fruit cultivar (Levovil, VilB, and VilD), extensive profiling of both central primary metabolism and volatile organic components of the fruit was performed. In this study, it was possible to define a number of quantitative trait loci (QTLs) which determined the levels of primary metabolites and/or volatile organic components and to evaluate their co-location with previously defined organoleptic QTLs. Correlation analyses between either the primary metabolites or the volatile organic compounds and organoleptic properties revealed a number of interesting associations, including pharmaceutical aroma–guaiacol and sourness–alanine, across the data set. Considerable correlation within the levels of primary metabolites or volatile organic compounds, respectively, were also observed. However, there was relatively little association between the levels of primary metabolites and volatile organic compounds, implying that they are not tightly linked to one another. A notable exception to this was the strong association between the levels of sucrose and those of a number of volatile organic compounds. The combined data presented here are thus discussed both with respect to those obtained recently from wide interspecific crosses of tomato and within the framework of current understanding of the chemical basis of fruit taste

Transcription factors relevant to auxin signalling coordinate broad-spectrum metabolic shifts including sulphur metabolism

A systems approach has previously been used to follow the response behaviour of Arabidopsis thaliana plants upon sulphur limitation. A response network was reconstructed from a time series of transcript and metabolite profiles, integrating complex metabolic and transcript data in order to investigate a potential causal relationship. The resulting scale-free network allowed potential transcriptional regulators of sulphur metabolism to be identified. Here, three sulphur-starvation responsive transcription factors, IAA13, IAA28, and ARF-2 (ARF1-Binding Protein), all of which are related to auxin signalling, were selected for further investigation. IAA28 overexpressing and knock-down lines showed no major morphological changes, whereas IAA13- and ARF1-BP-overexpressing plants grew more slowly than the wild type. Steady-state metabolite levels and expression of pathway-relevant genes were monitored under normal and sulphate-depleted conditions. For all lines, changes in transcript and metabolite levels were observed, yet none of these changes could exclusively be linked to sulphur stress. Instead, up- or down-regulation of the transcription factors caused metabolic changes which in turn affected sulphur metabolism. Auxin-relevant transcription factors are thus part of a complex response pattern to nutrient starvation that serve as coordinators of the metabolic shifts driving sulphur homeostasis rather then as direct effectors of the sulphate assimilation pathway. This study provides the first evidence ever presented that correlates auxin-related transcriptional regulators with primary plant metabolism

Contents of cysteine (upper row), γ-glutamylcysteine (GEC; middle row), and glutathione (GSH; lower row) are shown for plants overexpressing , , and , respectively, or down-regulated with respect to

Plants were grown for 10 weeks on soil before thiol extraction. knock-downs are represented by cross-hatched columns, overexpressing lines by white columns, and wild-type (WT) and empty-vector control lines (EV) by black columns. Values are the mean ±SD of three independent experiments. Asterisks indicate that the difference between the wild-type plants and the manipulated transgenic plants was significant using -tests ( ≤0.05).<p><b>Copyright information:</b></p><p>Taken from "Transcription factors relevant to auxin signalling coordinate broad-spectrum metabolic shifts including sulphur metabolism"</p><p></p><p>Journal of Experimental Botany 2008;59(10):2831-2846.</p><p>Published online Jan 2008</p><p>PMCID:PMC2486478.</p><p></p

Heat map generated from amino acid measurements reflecting log base 2-transformed and normalized amino acid levels and its similarity among themselves and the genotypes

The top colour bar indicates the relative log base 2-fold changes ranging between reduced relative (red) and increased relative (blue) contents of amino acids with respect to the wild-type.<p><b>Copyright information:</b></p><p>Taken from "Transcription factors relevant to auxin signalling coordinate broad-spectrum metabolic shifts including sulphur metabolism"</p><p></p><p>Journal of Experimental Botany 2008;59(10):2831-2846.</p><p>Published online Jan 2008</p><p>PMCID:PMC2486478.</p><p></p

Phenotype of mature knock-down plants, a sketch depicting the location of the T-DNA insertions, and quantification of gene expression in mutant plants

(A) Wild-type plants (left in each picture) and three mutant plants (right) at 10 weeks. Each of three individually selected homozygote mutant plants is presented. The plants were grown at the same time. (B) Identification of T-DNA insertion. Boxes in black represent exons, lines represent non-coding regions, and boxes in grey indicate T-DNA insertions. (C) q-RT-PCR analysis of plants derived from the knock-down screen. RNA was extracted from 28-d-old soil-grown plants. Ratios to controls are shown.<p><b>Copyright information:</b></p><p>Taken from "Transcription factors relevant to auxin signalling coordinate broad-spectrum metabolic shifts including sulphur metabolism"</p><p></p><p>Journal of Experimental Botany 2008;59(10):2831-2846.</p><p>Published online Jan 2008</p><p>PMCID:PMC2486478.</p><p></p

Expression analysis of , , and , respectively, in overexpressing lines from 28-d-old soil-grown plants with northern blot hybridization and q-RT-PCR, respectively

(A) Wild-type and empty-vector plants served as controls. RNA from 10 plants per treatment was extracted and 10 μg total RNA was subjected to northern blot analysis. Gene-specific probes were radioactively labelled and hybridized as described in Materials and methods. Equal loading in each track is demonstrated by comparing the amount of the 28S rRNA. Transcript sizes are given in brackets. (B) Quantification of gene expression in transgenic plants overexpressing , , and , respectively. Gene expression was assessed by q-RT-PCR as described in Materials and methods. The data represent the average relative to the gene expression in control plants.<p><b>Copyright information:</b></p><p>Taken from "Transcription factors relevant to auxin signalling coordinate broad-spectrum metabolic shifts including sulphur metabolism"</p><p></p><p>Journal of Experimental Botany 2008;59(10):2831-2846.</p><p>Published online Jan 2008</p><p>PMCID:PMC2486478.</p><p></p

Heat-map visualization and cluster tree representations of amino acid contents and genotypes

Data were obtained from experiments where plants were starved of sulphate for 10 d. The heat-map was generated by using log base 2-transformed fold changes. The given data represent the ratio of the determined amino acids for control and starved plants. Each amino acid is represented by a single column and each genotype by a single row. Red indicates decreased relative metabolite content whereas blue indicates increased relative contents of amino acids compared with the wild-type. Separated heat-map visualization of amino acid contents in control and mutant plants are presented in in available at online and the respective diagrams in Fig. S2.<p><b>Copyright information:</b></p><p>Taken from "Transcription factors relevant to auxin signalling coordinate broad-spectrum metabolic shifts including sulphur metabolism"</p><p></p><p>Journal of Experimental Botany 2008;59(10):2831-2846.</p><p>Published online Jan 2008</p><p>PMCID:PMC2486478.</p><p></p