Metabolic labeling of plant cell cultures with K(15)NO(3 )as a tool for quantitative analysis of proteins and metabolites

Strategies for robust quantitative comparison between different biological samples are of high importance in experiments that address biological questions beyond the establishment of protein lists. Here, we propose the use of (15)N-KNO(3 )as the only nitrogen source in Arabidopsis cell cultures in order to achieve a metabolically fully labeled cell population. Proteins from such metabolically labeled culture are distinguishable from unlabeled protein populations by a characteristic mass shift that depends on the amino acid composition of the tryptic peptide analyzed. In addition, the metabolically labeled cell extracts are also suitable for comparative quantitative analysis of nitrogen-containing cellular metabolic complement. Protein extracts from unlabeled and from standardized (15)N-labeled cells were combined into one sample for joined analytical processing. This has the advantage of (i) reduced experimental variability and (ii) immediate relative quantitation at the level of single extracted peptide and metabolite spectra. Together ease and accuracy of relative quantitation for profiling experiments is substantially improved. The metabolic labeling strategy has been validated by mixtures of protein extracts and metabolite extracts from the same cell cultures in known ratios of labeled to unlabeled extracts (1:1, 1:4, and 4:1). We conclude that saturating metabolic (15)N-labeling provides a robust and affordable integrative strategy to answer questions in quantitative proteomics and nitrogen focused metabolomics

Rapid transcriptional and metabolic regulation of the deacclimation process in cold acclimated Arabidopsis thaliana

Background: During low temperature exposure, temperate plant species increase their freezing tolerance in a process termed cold acclimation. This is accompanied by dampened oscillations of circadian clock genes and disrupted oscillations of output genes and metabolites. During deacclimation in response to warm temperatures, cold acclimated plants lose freezing tolerance and resume growth and development. While considerable effort has been directed toward understanding the molecular and metabolic basis of cold acclimation, much less information is available about the regulation of deacclimation.Results: We report metabolic (gas chromatography-mass spectrometry) and transcriptional (microarrays, quantitative RT-PCR) responses underlying deacclimation during the first 24 h after a shift of Arabidopsis thaliana (Columbia-0) plants cold acclimated at 4 °C back to warm temperature (20 °C). The data reveal a faster response of the transcriptome than of the metabolome and provide evidence for tightly regulated temporal responses at both levels. Metabolically, deacclimation is associated with decreasing contents of sugars, amino acids, glycolytic and TCA cycle intermediates, indicating an increased need for carbon sources and respiratory energy production for the activation of growth. The early phase of deacclimation also involves extensive down-regulation of protein synthesis and changes in the metabolism of lipids and cell wall components. Hormonal regulation appears particularly important during deacclimation, with extensive changes in the expression of genes related to auxin, gibberellin, brassinosteroid, jasmonate and ethylene metabolism. Members of several transcription factor families that control fundamental aspects of morphogenesis and development are significantly regulated during deacclimation, emphasizing that loss of freezing tolerance and growth resumption are transcriptionally highly interrelated processes. Expression patterns of some clock oscillator components resembled those under warm conditions, indicating at least partial re-activation of the circadian clock during deacclimation.Conclusions: This study provides the first combined metabolomic and transcriptomic analysis of the regulation of deacclimation in cold acclimated plants. The data indicate cascades of rapidly regulated genes and metabolites that underlie the developmental switch resulting in reduced freezing tolerance and the resumption of growth. They constitute a large-scale dataset of genes, metabolites and pathways that are crucial during the initial phase of deacclimation. The data will be an important reference for further analyses of this and other important but under-researched stress deacclimation processes

NLR Mutations Suppressing Immune Hybrid Incompatibility and Their Effects on Disease Resistance

Genetic divergence between populations can lead to reproductive isolation. Hybrid incompatibilities (HI) represent intermediate points along a continuum toward speciation. In plants, genetic variation in disease resistance (R) genes underlies several cases of HI. The progeny of a cross between Arabidopsis (Arabidopsis thaliana) accessions Landsberg erecta (Ler, Poland) and Kashmir2 (Kas2, central Asia) exhibits immune-related HI. This incompatibility is due to a genetic interaction between a cluster of eight TNL (TOLL/INTERLEUKIN1 RECEPTOR-NUCLEOTIDE BINDING-LEU RICH REPEAT) RPP1 (RECOGNITION OF PERONOSPORA PARASITICA1)-like genes (R1-R8) from Ler and central Asian alleles of a Strubbelig-family receptor-like kinase (SRF3) from Kas2. In characterizing mutants altered in Ler/Kas2 HI, we mapped multiple mutations to the RPP1-like Ler locus. Analysis of these suppressor of Ler/Kas2 incompatibility (sulki) mutants reveals complex, additive and epistatic interactions underlying RPP1-like Ler locus activity. The effects of these mutations were measured on basal defense, global gene expression, primary metabolism, and disease resistance to a local Hyaloperonospora arabidopsidis isolate (Hpa Gw) collected from Gorzów (Gw), where the Landsberg accession originated. Gene expression sectors and metabolic hallmarks identified for HI are both dependent and independent of RPP1-like Ler members. We establish that mutations suppressing immune-related Ler/Kas2 HI do not compromise resistance to Hpa Gw. QTL mapping analysis of Hpa Gw resistance point to RPP7 as the causal locus. This work provides insight into the complex genetic architecture of the RPP1-like Ler locus and immune-related HI in Arabidopsis and into the contributions of RPP1-like genes to HI and defense

Metabolic Profiling and Metabolite Correlation Network Analysis Reveal that Fusarium solani Induces Differential Metabolic Responses in Lotus japonicus and Lotus tenuis against Severe Phosphate Starvation

Root fungal endophytes are essential mediators of plant nutrition under mild stress conditions. However, variations in the rhizosphere environment, such as nutrient depletion, could result in a stressful situation for both partners, shifting mutualistic to nonconvenient interactions. Mycorrhizal fungi and dark septate endophytes (DSEs) have demonstrated their ability to facilitate phosphate (Pi) acquisition. However, few studies have investigated other plant–fungal interactions that take place in the root environment with regard to phosphate nutrition. In the present research work, we aimed to analyze the effect of extreme Pi starvation and the fungal endophyte Fusarium solani on the model Lotus japonicus and the crop L. tenuis. We conducted metabolomics analysis based on gas chromatography-mass spectrometry (GC-MS) on plant tissues under optimal conditions, severe Pi starvation and F.solani presence. By combining statistical and correlation network analysis strategies, we demonstrated the differential outcomes of the two plant species against the combination of treatments. The combination of nutritional stress and Fusarium presence activated significant modifications in the metabolism of L. japonicus affecting the levels of sugars, polyols and some amino acids. Our results display potential markers for further inspection of the factors related to plant nutrition and plant–fungal interactions.Fil: Nieva, Amira Susana del Valle. Max Planck Institute of Molecular Plant Physiology; Alemania. Deutscher Akademischer Austauschdienst; AlemaniaFil: Romero, Fernando Matias. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; ArgentinaFil: Erban, Alexander. Max Planck Institute of Molecular Plant Physiology; AlemaniaFil: Carrasco, Pedro. Universidad de Valencia; EspañaFil: Ruiz, Oscar Adolfo. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; ArgentinaFil: Kopka, Joachim. Max Planck Institute of Molecular Plant Physiology; Alemani

Discovery of food identity markers by metabolomics and machine learning technology

Verification of food authenticity establishes consumer trust in food ingredients and components of processed food. Next to genetic or protein markers, chemicals are unique identifiers of food components. Non-targeted metabolomics is ideally suited to screen food markers when coupled to efficient data analysis. This study explored feasibility of random forest (RF) machine learning, specifically its inherent feature extraction for non-targeted metabolic marker discovery. The distinction of chia, linseed, and sesame that have gained attention as “superfoods” served as test case. Chemical fractions of non-processed seeds and of wheat cookies with seed ingredients were profiled. RF technology classified original seeds unambiguously but appeared overdesigned for material with unique secondary metabolites, like sesamol or rosmarinic acid in the Lamiaceae, chia. Most unique metabolites were diluted or lost during cookie production but RF technology classified the presence of the seed ingredients in cookies with 6.7% overall error and revealed food processing markers, like 4-hydroxybenzaldehyde for chia and succinic acid monomethylester for linseed additions. RF based feature extraction was adequate for difficult classifications but marker selection should not be without human supervision. Combination with alternative data analysis technologies is advised and further testing of a wide range of seeds and food processing methods.Fil: Erban, Alexander. Max-Planck-Institute of Molecular Plant Physiology. Department of Molecular Physiology; AlemaniaFil: Fehrle, Ines. Max-Planck-Institute of Molecular Plant Physiology. Department of Molecular Physiology; AlemaniaFil: Martinez-Seidel, Federico. Max-Planck-Institute of Molecular Plant Physiology. Department of Molecular Physiology; AlemaniaFil: Brigante, Federico Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; ArgentinaFil: Lucini Mas, Agustín. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; ArgentinaFil: Baroni, María Verónica. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; ArgentinaFil: Wunderlin, Daniel Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Ciencia y Tecnología de Alimentos Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Ciencia y Tecnología de Alimentos Córdoba; ArgentinaFil: Kopka, Joachim. Max-Planck-Institute of Molecular Plant Physiology. Department of Molecular Physiology; Alemani

Characterization of the wheat leaf metabolome during grain filling and under varied N-supply

Progress in improving crop growth is an absolute goal despite the influence multifactorial components have on crop yield and quality. An Avalon × Cadenza doubled-haploid wheat mapping population was used to study the leaf metabolome of field grown wheat at weekly intervals during the time in which the canopy contributes to grain filling, i.e.,from anthesis to 5 weeks post-anthesis. Wheat was grown under four different nitrogen supplies reaching from residual soil N to a luxury over-fertilization (0, 100, 200, and 350 kg N ha−1). Four lines from a segregating doubled haploid population derived of a cross of the wheat elite cvs. Avalon and Cadenza were chosen as they showed pairwise differences in either N utilization efficiency (NUtE) or senescence timing. 108 annotated metabolites of primary metabolism and ions were determined. The analysis did not provide genotype specific markers because of a remarkable stability of the metabolome between lines. We speculate that the reason for failing to identify genotypic markers might be due to insufficient genetic diversity of the wheat parents and/or the known tendency of plants to keep metabolome homeostasis even under adverse conditions through multiple adaptations and rescue mechanism. The data, however, provided a consistent catalogue of metabolites and their respective responses to environmental and developmental factors and may bode well for future systems biology approaches, and support plant breeding and crop improvement