Carolina Salazar

Being sessile organisms, plants evolved sophisticated acclimation mechanisms to cope with abiotic challenges in their environment. These are activated at the initial site of exposure to stress, as well as in systemic tissues that have not been subjected to stress (termed systemic acquired acclimation [SAA]). Although SAA is thought to play a key role in plant survival during stress, little is known about the signaling mechanisms underlying it. Here, we report that SAA in plants requires at least two different signals: an autopropagating wave of reactive oxygen species (ROS) that rapidly spreads from the initial site of exposure to the entire plant and a stress-specific signal that conveys abiotic stress specificity. We further demonstrate that SAA is stress specific and that a temporal-spatial interaction between ROS and abscisic acid regulates rapid SAA to heat stress in plants. In addition, we demonstrate that the rapid ROS signal is associated with the propagation of electric signals in Arabidopsis thaliana. Our findings unravel some of the basic signaling mechanisms underlying SAA in plants and reveal that signaling events and transcriptome and metabolome reprogramming of systemic tissues in response to abiotic stress occur at a much faster rate than previously envisioned.

The Medicago truncatula NIP/LATD (for Numerous Infections and Polyphenolics/Lateral root-organ Defective) gene encodes a protein found in a clade of nitrate transporters within the large NRT1(PTR) family that also encodes transporters of dipeptides and tripeptides, dicarboxylates, auxin, and abscisic acid. Of the NRT1(PTR) members known to transport nitrate, most are low-affinity transporters. Here, we show that M. truncatula nip/latd mutants are more defective in their lateral root responses to nitrate provided at low (250 μm) concentrations than at higher (5 mm) concentrations; however, nitrate uptake experiments showed no discernible differences in uptake in the mutants. Heterologous expression experiments showed that MtNIP/LATD encodes a nitrate transporter: expression in Xenopus laevis oocytes conferred upon the oocytes the ability to take up nitrate from the medium with high affinity, and expression of MtNIP/LATD in an Arabidopsis chl1(nrt1.1) mutant rescued the chlorate susceptibility phenotype. X. laevis oocytes expressing mutant Mtnip-1 and Mtlatd were unable to take up nitrate from the medium, but oocytes expressing the less severe Mtnip-3 allele were proficient in nitrate transport. M. truncatula nip/latd mutants have pleiotropic defects in nodulation and root architecture. Expression of the Arabidopsis NRT1.1 gene in mutant Mtnip-1 roots partially rescued Mtnip-1 for root architecture defects but not for nodulation defects. This suggests that the spectrum of activities inherent in AtNRT1.1 is different from that possessed by MtNIP/LATD, but it could also reflect stability differences of each protein in M. truncatula. Collectively, the data show that MtNIP/LATD is a high-affinity nitrate transporter and suggest that it could have another function.

Metabolomics is the methodology that identifies and measures global pools of small molecules (of less than about 1,000 Da) of a biological sample, which are collectively called the metabolome. Metabolomics can therefore reveal the metabolic outcome of a genetic or environmental perturbation of a metabolic regulatory network, and thus provide insights into the structure and regulation of that network. Because of the chemical complexity of the metabolome and limitations associated with individual analytical platforms for determining the metabolome, it is currently difficult to capture the complete metabolome of an organism or tissue, which is in contrast to genomics and transcriptomics. This paper describes the analysis of Arabidopsis metabolomics data sets acquired by a consortium that includes five analytical laboratories, bioinformaticists, and biostatisticians, which aims to develop and validate metabolomics as a hypothesis-generating functional genomics tool. The consortium is determining the metabolomes of Arabidopsis T-DNA mutant stocks, grown in standardized controlled environment optimized to minimize environmental impacts on the metabolomes. Metabolomics data were generated with seven analytical platforms, and the combined data is being provided to the research community to formulate initial hypotheses about genes of unknown function (GUFs). A public database (www.PlantMetabolomics.org) has been developed to provide the scientific community with access to the data along with tools to allow for its interactive analysis. Exemplary datasets are discussed to validate the approach, which illustrate how initial hypotheses can be generated from the consortium-produced metabolomics data, integrated with prior knowledge to provide a testable hypothesis concerning the functionality of GUFs.

In spite of the large arsenal of methodologies developed for amino acid assessment in complex matrices, their implementation in metabolomics studies involving wide-ranging mutant screening is hampered by their lack of high-throughput, sensitivity, reproducibility, and/or wide dynamic range. In response to the challenge of developing amino acid analysis methods that satisfy the criteria required for metabolomic studies, improved reverse-phase high-performance liquid chromatography-mass spectrometry (RPHPLC-MS) methods have been recently reported for large-scale screening of metabolic phenotypes. However, these methods focus on the direct analysis of underivatized amino acids and, therefore, problems associated with insufficient retention and resolution are observed due to the hydrophilic nature of amino acids. It is well known that derivatization methods render amino acids more amenable for reverse phase chromatographic analysis by introducing highly-hydrophobic tags in their carboxylic acid or amino functional group. Therefore, an analytical platform that combines the 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate (AQC) pre-column derivatization method with ultra performance liquid chromatography-electrospray ionization-tandem mass spectrometry (UPLC-ESI-MS/MS) is presented in this article. For numerous reasons typical amino acid derivatization methods would be inadequate for large scale metabolic projects. However, AQC derivatization is a simple, rapid and reproducible way of obtaining stable amino acid adducts amenable for UPLC-ESI-MS/MS and the applicability of the method for high-throughput metabolomic analysis in Arabidopsis thaliana is demonstrated in this study. Overall, the major advantages offered by this amino acid analysis method include high-throughput, enhanced sensitivity and selectivity; characteristics that showcase its utility for the rapid screening of the preselected plant metabolites without compromising the quality of the metabolic data. The presented method enabled thirty-eight metabolites (proteinogenic amino acids and related compounds) to be analyzed within 10 min with detection limits down to 1.02 × 10-11 M (i.e., atomole level on column), which represents an improved sensitivity of 1 to 5 orders of magnitude compared to existing methods. Our UPLC-ESI-MS/MS method is one of the seven analytical platforms used by the Arabidopsis Metabolomics Consortium. The amino acid dataset obtained by analysis of Arabidopsis T-DNA mutant stocks with our platform is captured and open to the public in the web portal PlantMetabolomics.org. The analytical platform herein described could find important applications in other studies where the rapid, high-throughput and sensitive assessment of low abundance amino acids in complex biosamples is necessary.