Opposite variations in fumarate and malate dominate metabolic phenotypes of Arabidopsis salicylate mutants with abnormal biomass under chilling.

In chilling conditions (5°C), salicylic acid (SA)-deficient mutants (sid2, eds5 and NahG) of Arabidopsis thaliana produced more biomass than wild type (Col-0), whereas the SA overproducer cpr1 was extremely stunted. The hypothesis that these phenotypes were reflected in metabolism was explored using 600 MHz (1) H nuclear magnetic resonance (NMR) analysis of unfractionated polar shoot extracts. Biomass-related metabolic phenotypes were identified as multivariate data models of these NMR 'fingerprints'. These included principal components that correlated with biomass. Also, partial least squares-regression models were found to predict the relative size of plants in previously unseen experiments in different light intensities, or relative size of one genotype from the others. The dominant signal in these models was fumarate, which was high in SA-deficient mutants, intermediate in Col-0 and low in cpr1 at 5°C. Among signals negatively correlated with biomass, malate was prominent. Abundance of transcripts of the FUM2 cytosolic fumarase (At5g50950) showed strong positive correlation with fumarate levels and with biomass, whereas no significant differences were found for the FUM1 mitochondrial fumarase (At2g47510). It was confirmed that the morphological effects of SA under chilling find expression in the metabolome, with a role of fumarate highlighted.

The metabolic transition during disease following infection of Arabidopsis thaliana by Pseudomonas syringae pv. tomato.

The outcome of bacterial infection in plants is determined by the ability of the pathogen to successfully occupy the apoplastic space and deliver a constellation of effectors that collectively suppress basal and effector-triggered immune responses. In this study, we examined the metabolic changes associated with establishment of disease using analytical techniques that interrogated a range of chemistries. We demonstrated clear differences in the metabolome of Arabidopsis thaliana leaves infected with virulent Pseudomonas syringae within 8 h of infection. In addition to confirmation of changes in phenolic and indolic compounds, we identified rapid alterations in the abundance of amino acids and other nitrogenous compounds, specific classes of glucosinolates, disaccharides, and molecules that influence the prevalence of reactive oxygen species. Our data illustrate that, superimposed on defence suppression, pathogens reconfigure host metabolism to provide the sustenance required to support exponentially growing populations of apoplastically localized bacteria. We performed a detailed baseline study reporting the metabolic dynamics associated with bacterial infection. Moreover, we have integrated these data with the results of transcriptome profiling to distinguish metabolomic pathways that are transcriptionally activated from those that are post-transcriptionally regulated.

Co-ordinated expression of amino acid metabolism in response to N and S deficiency during wheat grain filling.

Increasing demands for productivity together with environmental concerns about fertilizer use dictate that the future sustainability of agricultural systems will depend on improving fertilizer use efficiency. Characterization of the biological processes responsible for efficient fertilizer use will provide tools for crop improvement under reduced inputs. Transcriptomic and metabolomic approaches were used to study the impact of nitrogen (N) and sulphur (S) deficiency on N and S remobilization from senescing canopy tissues during grain filling in winter wheat (Triticum aestivum). Canopy tissue N was remobilized effectively to the grain after anthesis. S was less readily remobilized. Nuclear magnetic resonance (NMR) metabolite profiling revealed significant effects of suboptimal N or S supply in leaves but not in developing grain. Analysis of amino acid pools in the grain and leaves revealed a strategy whereby amino acid biosynthesis switches to the production of glutamine during grain filling. Glutamine accumulated in the first 7 d of grain development, prior to conversion to other amino acids and protein in the subsequent 21 d. Transcriptome analysis indicated that a down-regulation of the terminal steps in many amino acid biosynthetic pathways occurs to control pools of amino acids during leaf senescence. Grain N and S contents increased in parallel after anthesis and were not significantly affected by S deficiency, despite a suboptimal N:S ratio at final harvest. N deficiency resulted in much slower accumulation of grain N and S and lower final concentrations, indicating that vegetative tissue N has a greater control of the timing and extent of nutrient remobilization than S.

Tissue preparation using Arabidopsis.

The ability to track changes in the levels of many metabolites in plants has great utility in a number of biological contexts. A metabolomics experiment usually requires the comparison of different varieties in either a functional genomics context or in response to perturbation by an external treatment. Such treatments can result in subtle changes in the final chemical signature of the plant tissue, and therefore, any unwanted variance produced in the generation of that tissue must be minimised. Procedures for plant growth, harvesting, preparation of extracts, and the subsequent collection of data have been optimised to minimise experimental variation within the dataset. This chapter describes in detail how to generate reproducible Arabidopsis tissue suitable for a typical plant metabolomics experiment. Issues concerned with tissue sampling, harvesting, and storage are also discussed.

An inter-laboratory comparison demonstrates that [H]-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 [(1)H]-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 [(1)H]-NMR fingerprinting is the ideal technique for large scale plant metabolomics data collection requiring the participation of multiple laboratories.