Chapter New Opportunities in Metabolomics and Biochemical Phenotyping for Plant Systems Biology

Pollution contro

New Opportunities in Metabolomics and Biochemical Phenotyping for Plant Systems Biology

Pollution contro

Correlation Network Analysis reveals a sequential reorganization of metabolic and transcriptional states during germination and gene-metabolite relationships in developing seedlings of Arabidopsis

<p>Abstract</p> <p>Background</p> <p>Holistic profiling and systems biology studies of nutrient availability are providing more and more insight into the mechanisms by which gene expression responds to diverse nutrients and metabolites. Less is known about the mechanisms by which gene expression is affected by endogenous metabolites, which can change dramatically during development. Multivariate statistics and correlation network analysis approaches were applied to non-targeted profiling data to investigate transcriptional and metabolic states and to identify metabolites potentially influencing gene expression during the heterotrophic to autotrophic transition of seedling establishment.</p> <p>Results</p> <p>Microarray-based transcript profiles were obtained from extracts of Arabidopsis seeds or seedlings harvested from imbibition to eight days-old. ¹H-NMR metabolite profiles were obtained for corresponding samples. Analysis of transcript data revealed high differential gene expression through seedling emergence followed by a period of less change. Differential gene expression increased gradually to day 8, and showed two days, 5 and 7, with a very high proportion of up-regulated genes, including transcription factor/signaling genes. Network cartography using spring embedding revealed two primary clusters of highly correlated metabolites, which appear to reflect temporally distinct metabolic states. Principle Component Analyses of both sets of profiling data produced a chronological spread of time points, which would be expected of a developmental series. The network cartography of the transcript data produced two distinct clusters comprising days 0 to 2 and days 3 to 8, whereas the corresponding analysis of metabolite data revealed a shift of day 2 into the day 3 to 8 group. A metabolite and transcript pair-wise correlation analysis encompassing all time points gave a set of 237 highly significant correlations. Of 129 genes correlated to sucrose, 44 of them were known to be sucrose responsive including a number of transcription factors.</p> <p>Conclusions</p> <p>Microarray analysis during germination and establishment revealed major transitions in transcriptional activity at time points potentially associated with developmental transitions. Network cartography using spring-embedding indicate that a shift in the state of nutritionally important metabolites precedes a major shift in the transcriptional state going from germination to seedling emergence. Pair-wise linear correlations of transcript and metabolite levels identified many genes known to be influenced by metabolites, and provided other targets to investigate metabolite regulation of gene expression during seedling establishment.</p

Virus-induced gene complementation reveals a transcription factor network in modulation of tomato fruit ripening

Plant virus technology, in particular virus-induced gene silencing, is a widely used reverse- and forward-genetics tool in plant functional genomics. However the potential of virus technology to express genes to induce phenotypes or to complement mutants in order to understand the function of plant genes is not well documented. Here we exploit Potato virus X as a tool for virus-induced gene complementation (VIGC). Using VIGC in tomato, we demonstrated that ectopic viral expression of LeMADS-RIN, which encodes a MADS-box transcription factor (TF), resulted in functional complementation of the non-ripening rin mutant phenotype and caused fruits to ripen. Comparative gene expression analysis indicated that LeMADS-RIN up-regulated expression of the SBP-box (SQUAMOSA promoter binding protein-like) gene LeSPL-CNR, but down-regulated the expression of LeHB-1, an HD-Zip homeobox TF gene. Our data support the hypothesis that a transcriptional network may exist among key TFs in the modulation of fruit ripening in tomato

MeRy-B: a web knowledgebase for the storage, visualization, analysis and annotation of plant NMR metabolomic profiles

<p>Abstract</p> <p>Background</p> <p>Improvements in the techniques for metabolomics analyses and growing interest in metabolomic approaches are resulting in the generation of increasing numbers of metabolomic profiles. Platforms are required for profile management, as a function of experimental design, and for metabolite identification, to facilitate the mining of the corresponding data. Various databases have been created, including organism-specific knowledgebases and analytical technique-specific spectral databases. However, there is currently no platform meeting the requirements for both profile management and metabolite identification for nuclear magnetic resonance (NMR) experiments.</p> <p>Description</p> <p>MeRy-B, the first platform for plant ¹H-NMR metabolomic profiles, is designed (<it>i</it>) to provide a knowledgebase of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata, (<it>ii</it>) for queries and visualization of the data, (<it>iii</it>) to discriminate between profiles with spectrum visualization tools and statistical analysis, (<it>iv</it>) to facilitate compound identification. It contains lists of plant metabolites and unknown compounds, with information about experimental conditions, the factors studied and metabolite concentrations for several plant species, compiled from more than one thousand annotated NMR profiles for various organs or tissues.</p> <p>Conclusion</p> <p>MeRy-B manages all the data generated by NMR-based plant metabolomics experiments, from description of the biological source to identification of the metabolites and determinations of their concentrations. It is the first database allowing the display and overlay of NMR metabolomic profiles selected through queries on data or metadata. MeRy-B is available from <url>http://www.cbib.u-bordeaux2.fr/MERYB/index.php</url>.</p

1H-NMR metabolomics: Profiling method for a rapid and efficient screening of transgenic plants

Metabolomics-based approaches are methods of choice for studying changes in fruit composition induced by  environmental or genetic modulation of biochemical pathways in the fruit. Owing to enzyme redundancy and  high plasticity of the metabolic network, transgenic alteration of the activity of the enzymes from the central metabolism very often results in only slight modifications of the fruit composition. In order to avoid costly and  time-consuming plant analysis, we used a fast and sensitive 1H-NMR-based metabolomic profiling technique  allowing discovery of slight metabolite variations in a large number of samples. Here, we describe the  screening of transgenic tomato plants in which two genes from the central metabolism, phosphoenolpyruvate  carboxylase (EC.3.4.1.1) and malate synthase (EC 2.3.3.9) were silenced by antisens and RNAi strategy.  1H-NMR metabolomic profiles of methanol-d4 D2O buffer extracts of tomato fruit flesh were acquired and  subjected to unsupervised multivariate statistical analysis. 1H-NMR spectra were binned into variable-size  spectral domains, making it possible to get an overall analysis of a large number of resonances, even in the  case of uncontrolled variation of the chemical shift. Principal component analysis was used to separate groups  of samples and to relate known and unknown metabolites to transgenic events. The screening of 100 samples,  from extraction to data mining, took 36 h. Thus, this procedure allows the rapid selection of metabolic  phenotypes of interest among about 30 transgenic lines.Key words: Metabolome, GMO, tomato, fruit, 1H-NMR profiling, screening

An inter-laboratory comparison demonstrates that [1H]-NMR metabolite fingerprinting is a robust technique for collaborative plant metabolomic data collection

In any metabolomics experiment, robustness and reproducibility of data collection is of vital importance. These become more important in collaborative studies where data is to be collected on multiple instruments. With minimisation of variance in sample preparation and instrument performance it is possible to elucidate even subtle differences in metabolite fingerprints due to genotype or biological treatment. In this paper we report on an inter laboratory comparison of plant derived samples by [1H]-NMR spectroscopy across five different sites and within those sites utilising instruments with different probes and magnetic field strengths of 9.4 T (400 MHz), 11.7 T (500 MHz) and 14.1 T (600 MHz). Whilst the focus of the study is on consistent data collection across laboratories, aspects of sample stability and the requirement for sample rotation within the NMR magnet are also discussed. Comparability of the datasets from participating laboratories was exceptionally good and the data were amenable to comparative analysis by multivariate statistics. Field strength differences can be adjusted for in the data pre-processing and multivariate analysis demonstrating that [1H]-NMR fingerprinting is the ideal technique for large scale plant metabolomics data collection requiring the participation of multiple laboratories

A DEMETER-like DNA demethylase protein governs tomato fruit ripening

In plants, genomic DNA methylation which contributes to development and stress responses can be actively removed by DEMETER-like DNA demethylases (DML). Indeed, in Arabidopsis DMLs are important for maternal imprinting and endosperm demethylation, but only few studies demonstrate the developmental roles of active DNA demethylation conclusively in this plant. Here we show a direct cause and effect relationship between active DNA demethylation mainly mediated by the tomato DML, SlDML2, and fruit ripening; an important developmental process unique to plants. RNAi SlDML2 knock-down results in ripening inhibition via hypermethylation and repression of the expression of genes encoding ripening transcription factors and rate-limiting enzymes of key biochemical processes such as carotenoid synthesis. Our data demonstrate that active DNA demethylation is central to the control of ripening in tomat