Top-down Phenomics of Arabidopsis thaliana

Abstract

Elucidating the function of each gene in a genome is important for understanding the whole organism. We previously constructed 4000 disruptant mutants of Arabidopsis by insertion of Ds transposons. Here, we describe a top-down phenomics approach based on metabolic profiling that uses one-dimensional Plants produce energy sources, foods, and industrial or medical materials that are necessary and useful for us. It has been expected to handle the metabolic flows so as to increase the amount of interested chemical resources in plants. For that purpose, comprehensive understanding of the metabolite network is required. Presumably, the metabolite network is regulated by both genetic information and cellular conditions. In recent years, to address the key factors regulating the metabolite network, metabolomics, the nontargeting comprehensive metabolite analysis of plants, has been introduced in plant research as well as other organisms. To elucidate the linkage between genetic information and metabolites, attempts to integrate transcriptome and metabolomics data have been made. Hirai et al.(1) described the linkage between the levels of some secondary metabolites, such as glucosinolates and the transcripts for genes encoding corresponding metabolic enzymes. However, such approaches for the primary metabolic pathway did not give us clear information on the regulatory systems, presumably due to higher complexity (1-3).To understand such complex biological phenomena, a systems biological approach should be one of the promising ways. To establish systems biology, a vast amount of information on cellular entities, such as transcript, proteins, and metabolites is required and combined functionally. Computational models have been developed for Escherichia coli and Saccharomyces cerevisiae based on data from gene disruption mutants (4 -8) and have proven to be useful for predicting the phenotypes of mutants, cellular behavior, and evolution (9 -13).Completion of the Arabidopsis and rice genome sequences (14 -17) has allowed the application of systems biology to plants (18,19). Furthermore, a large number of gene disruption mutants have been constructed in various plant species, especially Arabidopsis and rice. By taking advantage of these resources, functional genomic approaches can be used to elucidate the function of plant genes (20). In a previous report, we described a phenomic approach analyzing the effects of 4000 gene disruptions in Arabidopsis (21). We found that fewer than 5% of the gene disruptions caused a visible phenotype in the aerial parts, suggesting that a more detailed and practical methodology is needed to determine the effects of losses in gene function.For the purpose of establishing systems biology in plants, we propose the comprehensive analysis of gene disruptant lines by

Integrated analysis of transcriptome and metabolome of Arabidopsis albino or pale green mutants with disrupted nuclear-encoded chloroplast proteins

“…By comprehensively analyzing the mutants of those genes, we will be able to better understand the relationship between phenotypes (albino, pale-green, and silent phenotypes like wild-type) and the genes responsible, which may offer clues to understanding novel chloroplast systematic mechanisms. The analysis of albino mutants using one- and two- dimensional nuclear magnetic resonance spectroscopy has been reported (Tian et al 2007). NMR can be used to analyze metabolome in planta.…”

Chemical Profiling of Jatropha Tissues under Different Torrefaction Conditions: Application to Biomass Waste Recovery

“…The mixture was incubated at 50°C for 30 min with shaking, centrifuged at 15000 rpm for 5 min, the supernatant collected as HMWMs, and then analyzed using the 1 H– 13 C-HSQC NMR method. It was performed at 318 K with 32 scans as described previously [27], [28], [29]. The central DMSO solvent cross-peak was used as the internal reference (δC 39.5, δH 2.49 ppm).…”

Metabolomics of Arabidopsis Thaliana

“…In Arabidopsis [ 1 H]-NMR profiling gives data on amino-acids, mono and di-saccharides, organic acids, nucleotides, betaine/choline, flavonoid glycosides, phenylpropanoids -particularly sinapates, polyamines and glucosinolates. (Ward et al, 2003(Ward et al, , 2007Tian et al, 2007). [ 1 H]-NMR fingerprinting is well suited to high-throughput screening using pattern matching techniques, as the instrumentation is extremely stable and the data readily aligned and normalized, even across laboratories and instruments of different field strengths (Ward et al, 2010).…”

“…The two-dimensional (2D) technique known as [ 1 H]-J-resolved NMR (Viant, 2003) can be used to produce plots that are effectively 1D fingerprints, devoid of [ 1 H-1 H] coupling and thus avoid some of the problems of overlapping signals. Stable isotope labelling of Arabidopsis with 13 C or 15 N and the use of heteronuclear 2D techniques are extremely useful for tracking molecules in targeted experiments (Kikuchi et al, 2004;Tian et al, 2007). 2D-analyses is also a key tool to extract structural information, and NMR remains the method of choice for novel compound characterization.…”