SUMMARYThe unbiased and comprehensive analysis of metabolites in any organism presents a major challenge if proper peak annotation and unambiguous assignment of the biological origin of the peaks are required. Here we provide a comprehensive multi-isotope labelling-based strategy using fully labelled 13 C, 15 N and 34 S plant tissues, in combination with a fractionated metabolite extraction protocol. The extraction procedure allows for the simultaneous extraction of polar, semi-polar and hydrophobic metabolites, as well as for the extraction of proteins and starch. After labelling and extraction, the metabolites and lipids were analysed using a highresolution mass spectrometer providing accurate MS and all-ion fragmentation data, providing an unambiguous readout for every detectable isotope-labelled peak. The isotope labelling assisted peak annotation process employed can be applied in either an automated database-dependent or a database-independent analysis of the plant polar metabolome and lipidome. As a proof of concept, the developed methods and technologies were applied and validated using Arabidopsis thaliana leaf and root extracts. Along with a large repository of assigned elemental compositions, which is provided, we show, using selected examples, the accuracy and reliability of the developed workflow.

Metabolomics is rapidly becoming an integral part of many life science studies ranging from disease diagnostics to systems biology. However, a number of problems such as the discrimination of biological from non-biological signals, efficient compound annotation, and reliable quantification are still not satisfactorily solved in untargeted LC-MS-based metabolomics research. Extending our previous work on direct infusion-based metabolomics, we here describe a (13)C isotope labeling strategy in combination with an Ultra Performance Liquid Chromatography Fourier Transform Ion Cyclotron Resonance Mass Spectrometry-based approach (UPLC-FTICR MS) which provides a technological platform offering solutions to a number of the above-mentioned problems. We further demonstrate that the use of a fully labeled metabolome is not only beneficial for high end mass spectrometers, such as that used in this study but also provides a considerable improvement to every other mass spectrometry-based metabolomic platform.

Understanding the molecular basis of plant performance under water-limiting conditions will help to breed crop plants with a lower water demand. We investigated the physiological and gene expression response of drought-tolerant (IR57311 and LC-93-4) and droughtsensitive (Nipponbare and Taipei 309) rice (Oryza sativa L.) cultivars to 18 days of drought stress in climate chamber experiments. Drought stressed plants grew significantly slower than the controls. Gene expression profiles were measured in leaf samples with the 20 K NSF oligonucleotide microarray. A linear model was fitted to the data to identify genes that were significantly regulated under drought stress. In all drought stressed cultivars, 245 genes were significantly repressed and 413 genes induced. Genes differing in their expression pattern under drought stress between tolerant and sensitive cultivars were identified by the genotype 9 environment (G 9 E) interaction term. More genes were significantly drought regulated in the sensitive than in the tolerant cultivars. Localizing all expressed genes on the rice genome map, we checked which genes with a significant G 9 E interaction colocalized with published quantitative trait loci regions for drought tolerance. These genes are more likely to be important for drought tolerance in an agricultural environment. To identify the metabolic processes with a significant G 9 E effect, we adapted the analysis software MapMan for rice. We found a drought stress induced shift toward senescence related degradation processes that was more pronounced in the sensitive than in the tolerant cultivars. In spite of higher growth rates and water use, more photosynthesis related genes were down-regulated in the tolerant than in the sensitive cultivars.

The carbon and nitrogen metabolism of Arabidopsis plants grown in sunlight differs from plants grown with artificial light, even when the spectral quality and sinusoidal profile of sunlight are approximated experimentally.

Rice provides about half of the calories consumed in Asian countries, but its productivity is often reduced by drought, especially when grown under rain-fed conditions. Cultivars with increased drought tolerance have been bred over centuries. Slow selection for drought tolerance on the basis of phenotypic traits may be accelerated by using molecular markers identified through expression and metabolic profiling. Previously, we identified 46 candidate genes with significant genotype × environment interaction in an expression profiling study on four cultivars with contrasting drought tolerance. These potential markers and in addition GC-MS quantified metabolites were tested in 21 cultivars from both indica and japonica background that varied in drought tolerance. Leaf blades were sampled from this population of cultivars grown under control or long-term drought condition and subjected to expression analysis by qRT-PCR and metabolite profiling. Under drought stress, metabolite levels correlated mainly negatively with performance parameters, but eight metabolites correlated positively. For 28 genes, a significant correlation between expression level and performance under drought was confirmed. Negative correlations were predominant. Among those with significant positive correlation was the gene coding for a cytosolic fructose-1,6-bisphosphatase. This enzyme catalyzes a highly regulated step in C-metabolism. The metabolic and transcript marker candidates for drought tolerance were identified in a highly diverse population of cultivars. Thus, these markers may be used to select for tolerance in a wide range of rice germplasms.

A selection of 21 rice cultivars (Oryza sativa L. ssp. indica and japonica) was characterized under moderate long-term drought stress by comprehensive physiological analyses and determination of the contents of polyamines and selected metabolites directly related to polyamine metabolism. To investigate the potential regulation of polyamine biosynthesis at the transcriptional level, the expression of 21 genes encoding enzymes involved in these pathways were analyzed by qRT-PCR. Analysis of the genomic loci revealed that 11 of these genes were located in drought-related QTL regions, in agreement with a proposed role of polyamine metabolism in rice drought tolerance. The cultivars differed widely in their drought tolerance and parameters such as biomass and photosynthetic quantum yield were significantly affected by drought treatment. Under optimal irrigation free putrescine was the predominant polyamine followed by free spermidine and spermine. When exposed to drought putrescine levels decreased markedly and spermine became predominant in all cultivars. There were no correlations between polyamine contents and drought tolerance. GC-MS analysis revealed drought-induced changes of the levels of ornithine/arginine (substrate), substrates of polyamine synthesis, proline, product of a competing pathway and GABA, a potential degradation product. Gene expression analysis indicated that ADC-dependent polyamine biosynthesis responded much more strongly to drought than the ODC-dependent pathway. Nevertheless the fold change in transcript abundance of ODC1 under drought stress was linearly correlated with the drought tolerance of the cultivars. Combining metabolite and gene expression data, we propose a model of the coordinate adjustment of polyamine biosynthesis for the accumulation of spermine under drought conditions.

Climate models predict an increased likelihood of seasonal droughts for many areas of the world. Breeding for drought tolerance could be accelerated by marker-assisted selection. As a basis for marker identification, we studied the genetic variance, predictability of field performance and potential costs of tolerance in potato (Solanum tuberosum L.). Potato produces high calories per unit of water invested, but is drought-sensitive. In 14 independent pot or field trials, 34 potato cultivars were grown under optimal and reduced water supply to determine starch yield. In an artificial dataset, we tested several stress indices for their power to distinguish tolerant and sensitive genotypes independent of their yield potential. We identified the deviation of relative starch yield from the experimental median (DRYM) as the most efficient index. DRYM corresponded qualitatively to the partial least square model-based metric of drought stress tolerance in a stress effect model. The DRYM identified significant tolerance variation in the European potato cultivar population to allow tolerance breeding and marker identification. Tolerance results from pot trials correlated with those from field trials but predicted field performance worse than field growth parameters. Drought tolerance correlated negatively with yield under optimal conditions in the field. The distribution of yield data versus DRYM indicated that tolerance can be combined with average yield potentials, thus circumventing potential yield penalties in tolerance breeding.

Systems responses to drought stress of four potato reference cultivars with differential drought tolerance (Solanum tuberosum L.) were investigated by metabolome profiling and RNA sequencing. Systems analysis was based on independent field and greenhouse trials. Robust differential drought responses across all cultivars under both conditions comprised changes of proline, raffinose, galactinol, arabitol, arabinonic acid, chlorogenic acid and 102 transcript levels. The encoded genes contained a high proportion of heat shock proteins and proteins with signalling or regulatory functions, for example, a homolog of abscisic acid receptor PYL4. Constitutive differences of the tolerant compared with the sensitive cultivars included arbutin, octopamine, ribitol and 248 transcripts. The gene products of many of these transcripts were pathogen response related, such as receptor kinases, or regulatory proteins, for example, a homolog of the Arabidopsis FOUR LIPS MYB-regulator of stomatal cell proliferation. Functional enrichment analyses imply heat stress as a major acclimation component of potato leaves to long-term drought stress. Enhanced heat stress during drought can be caused by loss of transpiration cooling. This effect and CO limitation are the main consequences of drought-induced or abscisic acid-induced stomatal closure. Constitutive differences in metabolite and transcript levels between tolerant and sensitive cultivars indicate interactions of drought tolerance and pathogen resistance in potato.