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  • 1
    Language: English
    In: Analytical and Bioanalytical Chemistry, 2011, Vol.400(7), pp.1967-1978
    Description: Next-generation sequencing provides technologies which sequence whole prokaryotic and eukaryotic genomes in days, perform genome-wide association studies, chromatin immunoprecipitation followed by sequencing and RNA sequencing for transcriptome studies. An exponentially growing volume of sequence data can be anticipated, yet functional interpretation does not keep pace with the amount of data produced. In principle, these data contain all the secrets of living systems, the genotype–phenotype relationship. Firstly, it is possible to derive the structure and connectivity of the metabolic network from the genotype of an organism in the form of the stoichiometric matrix N . This is, however, static information. Strategies for genome-scale measurement, modelling and predicting of dynamic metabolic networks need to be applied. Consequently, metabolomics science—the quantitative measurement of metabolism in conjunction with metabolic modelling—is a key discipline for the functional interpretation of whole genomes and especially for testing the numerical predictions of metabolism based on genome-scale metabolic network models. In this context, a systematic equation is derived based on metabolomics covariance data and the genome-scale stoichiometric matrix which describes the genotype–phenotype relationship.
    Keywords: Genotype–phenotype relationship ; Systems biology ; Metabolomics ; Proteomics ; Genome annotation ; Gene models ; Metabolic modelling ; Flux balance analysis ; Dynamic modelling ; Stochastic differential equations ; Covariance ; Principal components analysis ; Phenotypic plasticity
    ISSN: 1618-2642
    E-ISSN: 1618-2650
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  • 2
    Language: English
    In: Analytical and Bioanalytical Chemistry, June 15, 2011, Vol.400(7), p.1967(12)
    Description: Next-generation sequencing provides technologies which sequence whole prokaryotic and eukaryotic genomes in days, perform genome-wide association studies, chromatin immunoprecipitation followed by sequencing and RNA sequencing for transcriptome studies. An exponentially growing volume of sequence data can be anticipated, yet functional interpretation does not keep pace with the amount of data produced. In principle, these data contain all the secrets of living systems, the genotype--phenotype relationship. Firstly, it is possible to derive the structure and connectivity of the metabolic network from the genotype of an organism in the form of the stoichiometric matrix N. This is, however, static information. Strategies for genome-scale measurement, modelling and predicting of dynamic metabolic networks need to be applied. Consequently, metabolomics science--the quantitative measurement of metabolism in conjunction with metabolic modelling--is a key discipline for the functional interpretation of whole genomes and especially for testing the numerical predictions of metabolism based on genome-scale metabolic network models. In this context, a systematic equation is derived based on metabolomics covariance data and the genome-scale stoichiometric matrix which describes the genotype--phenotype relationship. Keywords Genotype--phenotype relationship * Systems biology * Metabolomics * Proteomics * Genome annotation * Gene models * Metabolic modelling * Flux balance analysis * Dynamic modelling * Stochastic differential equations * Covariance * Principal components analysis * Phenotypic plasticity
    Keywords: Genomes – Analysis ; DNA Sequencing – Analysis ; RNA – Analysis ; Genomics – Analysis
    ISSN: 1618-2642
    Source: Cengage Learning, Inc.
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  • 3
    Language: English
    In: Journal of Proteomics, 10 December 2011, Vol.75(1), pp.284-305
    Description: Plants have shaped our human life form from the outset. With the emerging recognition of world population feeding, global climate change and limited energy resources with fossil fuels, the relevance of plant biology and biotechnology is becoming dramatically important. One key issue is to improve plant productivity and abiotic/biotic stress resistance in agriculture due to restricted land area and increasing environmental pressures. Another aspect is the development of CO -neutral plant resources for fiber/biomass and biofuels: a transition from first generation plants like sugar cane, maize and other important nutritional crops to second and third generation energy crops such as and trees for lignocellulose and algae for biomass and feed, hydrogen and lipid production. At the same time we have to conserve and protect natural diversity and species richness as a foundation of our life on earth. Here, biodiversity banks are discussed as a foundation of current and future plant breeding research. Consequently, it can be anticipated that plant biology and ecology will have more indispensable future roles in all socio-economic aspects of our life than ever before. We therefore need an in-depth understanding of the physiology of single plant species for practical applications as well as the translation of this knowledge into complex natural as well as anthropogenic ecosystems. Latest developments in biological and bioanalytical research will lead into a paradigm shift towards trying to understand organisms at a systems level and in their ecosystemic context: (i) shotgun and next-generation genome sequencing, gene reconstruction and annotation, (ii) genome-scale molecular analysis using OMICS technologies and (iii) computer-assisted analysis, modeling and interpretation of biological data. Systems biology combines these molecular data, genetic evolution, environmental cues and species interaction with the understanding, modeling and prediction of active biochemical networks up to whole species populations. This process relies on the development of new technologies for the analysis of molecular data, especially genomics, metabolomics and proteomics data. The ambitious aim of these non-targeted ‘omic’ technologies is to extend our understanding beyond the analysis of separated parts of the system, in contrast to traditional reductionistic hypothesis-driven approaches. The consequent integration of genotyping, pheno/morphotyping and the analysis of the molecular phenotype using metabolomics, proteomics and transcriptomics will reveal a novel understanding of plant metabolism and its interaction with the environment. The analysis of single model systems – plants, fungi, animals and bacteria – will finally emerge in the analysis of populations of plants and other organisms and their adaptation to the ecological niche. In parallel, this novel understanding of ecophysiology will translate into knowledge-based approaches in crop plant biotechnology and marker- or genome-assisted breeding approaches. In this review the foundations of green systems biology are described and applications in ecosystems research are presented. Knowledge exchange of ecosystems research and green biotechnology merging into green systems biology is anticipated based on the principles of natural variation, biodiversity and the genotype–phenotype environment relationship as the fundamental drivers of ecology and evolution. ► Foundations of Green Systems Biology. ► Iterative workflow to investigate the genotype-phenotype-map in ecology/evolution. ► Integration of genomic reconstruction and functional modeling approaches. ► International research networks and translational plant breeding. ► Socio-economic relevance of Green Systems Biology.
    Keywords: Cimmyt ; Inrri ; Natural Variation ; Biodiversity ; Biofuels ; Financial Market ; Land Grabbing ; Marker-Assisted Selection (Mas) ; Genome-Assisted Breeding (Gab) ; Ecosystems ; Ecology ; Ecophysiology ; Genotype ; Phenotype ; Phenotypic Plasticity ; Plant Systems Biology ; Modeling ; Genome Annotation ; Green Revolution ; Next Generation Sequencing (Ngs) ; Genome-Wide Associations (Gwa) ; Single Nucleotide Polymorphisms (Snp) ; Anatomy & Physiology ; Ecology
    ISSN: 1874-3919
    E-ISSN: 18767737
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  • 4
    In: PLoS ONE, 2014, Vol.9(5)
    Description: The metabolome is a highly dynamic entity and the final readout of the genotype x environment x phenotype (GxExP) relationship of an organism. Monitoring metabolite dynamics over time thus theoretically encrypts the whole range of possible chemical and biochemical transformations of small molecules involved in metabolism. The bottleneck is, however, the sheer number of unidentified structures in these samples. This represents the next challenge for metabolomics technology and is comparable with genome sequencing 30 years ago. At the same time it is impossible to handle the amount of data involved in a metabolomics analysis manually. Algorithms are therefore imperative to allow for automated m/z feature extraction and subsequent structure or pathway assignment. Here we provide an automated pathway inference strategy comprising measurements of metabolome time series using LC- MS with high resolution and high mass accuracy. An algorithm was developed, called mzGroupAnalyzer , to automatically explore the metabolome for the detection of metabolite transformations caused by biochemical or chemical modifications. Pathways are extracted directly from the data and putative novel structures can be identified. The detected m/z features can be mapped on a van Krevelen diagram according to their H/C and O/C ratios for pattern recognition and to visualize oxidative processes and biochemical transformations. This method was applied to Arabidopsis thaliana treated simultaneously with cold and high light. Due to a protective antioxidant response the plants turn from green to purple color via the accumulation of flavonoid structures. The detection of potential biochemical pathways resulted in 15 putatively new compounds involved in the flavonoid-pathway. These compounds were further validated by product ion spectra from the same data. The mzGroupAnalyzer is implemented in the graphical user interface (GUI) of the metabolomics toolbox COVAIN (Sun & Weckwerth, 2012, Metabolomics 8: 81–93). The strategy can be extended to any biological system.
    Keywords: Research Article ; Biology And Life Sciences ; Computer And Information Sciences ; Physical Sciences ; Research And Analysis Methods
    E-ISSN: 1932-6203
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  • 5
    Language: English
    In: Plant physiology, August 2013, Vol.162(4), pp.1822-33
    Description: Investigation of the metabolome and the transcriptome of pollen of lily (Lilium longiflorum) gave a comprehensive overview of metabolic pathways active during pollen germination and tube growth. More than 100 different metabolites were determined simultaneously by gas chromatography coupled to mass spectrometry, and expressed genes of selected metabolic pathways were identified by next-generation sequencing of lily pollen transcripts. The time-dependent changes in metabolite abundances, as well as the changes after inhibition of the mitochondrial electron transport chain, revealed a fast and dynamic adaption of the metabolic pathways in the range of minutes. The metabolic state prior to pollen germination differed clearly from the metabolic state during pollen tube growth, as indicated by principal component analysis of all detected metabolites and by detailed observation of individual metabolites. For instance, the amount of sucrose increased during the first 60 minutes of pollen culture but decreased during tube growth, while glucose and fructose showed the opposite behavior. Glycolysis, tricarbonic acid cycle, glyoxylate cycle, starch, and fatty acid degradation were activated, providing energy during pollen germination and tube growth. Inhibition of the mitochondrial electron transport chain by antimycin A resulted in an immediate production of ethanol and a fast rearrangement of metabolic pathways, which correlated with changes in the amounts of the majority of identified metabolites, e.g. a rapid increase in γ-aminobutyric acid indicated the activation of a γ-aminobutyric acid shunt in the tricarbonic acid cycle, while ethanol fermentation compensated the reduced ATP production after inhibition of the oxidative phosphorylation.
    Keywords: Germination -- Physiology ; Lilium -- Metabolism ; Pollen Tube -- Growth & Development
    ISSN: 00320889
    E-ISSN: 1532-2548
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  • 6
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 06 December 2016, Vol.113(49), pp.E7937-E7946
    Description: Ammonia-oxidizing archaea (AOA) are among the most abundant microorganisms and key players in the global nitrogen and carbon cycles. They share a common energy metabolism but represent a heterogeneous group with respect to their environmental distribution and adaptions, growth requirements, and genome contents. We report here the genome and proteome of Nitrososphaera viennensis EN76, the type species of the archaeal class Nitrososphaeria of the phylum Thaumarchaeota encompassing all known AOA. N. viennensis is a soil organism with a 2.52-Mb genome and 3,123 predicted protein-coding genes. Proteomic analysis revealed that nearly 50% of the predicted genes were translated under standard laboratory growth conditions. Comparison with genomes of closely related species of the predominantly terrestrial Nitrososphaerales as well as the more streamlined marine Nitrosopumilales [Candidatus (Ca.) order] and the acidophile "Ca. Nitrosotalea devanaterra" revealed a core genome of AOA comprising 860 genes, which allowed for the reconstruction of central metabolic pathways common to all known AOA and expressed in the N. viennensis and "Ca Nitrosopelagicus brevis" proteomes. Concomitantly, we were able to identify candidate proteins for as yet unidentified crucial steps in central metabolisms. In addition to unraveling aspects of core AOA metabolism, we identified specific metabolic innovations associated with the Nitrososphaerales mediating growth and survival in the soil milieu, including the capacity for biofilm formation, cell surface modifications and cell adhesion, and carbohydrate conversions as well as detoxification of aromatic compounds and drugs.
    Keywords: Ammonia Oxidation ; Archaea ; Biofilm ; Comparative Genomics ; Proteomics ; Adaptation, Biological ; Genome, Archaeal ; Proteome ; Ammonia -- Metabolism ; Archaea -- Genetics
    ISSN: 00278424
    E-ISSN: 1091-6490
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  • 7
    Language: English
    In: Journal of Organometallic Chemistry, April 15, 2015, Vol.782, p.103(8)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jorganchem.2015.01.005 Byline: Vladimir Chobot, Franz Hadacek, Wolfram Weckwerth, Lenka Kubicova Abstract: Anthranilic acid (ANA) and 3-hydroxyanthranilic acid (3-HANA) are kynurenine pathway intermediates of the tryptophan metabolism. A hitherto unemployed method combination, differential pulse voltammetry, mass spectrometry (nano-ESI-MS), deoxyribose degradation and iron(II) autoxidation assays has been employed for studying of their redox chemistry and their interactions with iron(II) and iron(III) ions. Both acids inhibited the Fenton reaction by iron chelation and ROS scavenging in the deoxyribose degradation assay. In the iron(II) autoxidation assay, anthranilic acid showed antioxidant effects, whereas 3-hydroxyanthranilic acid exhibited apparent pro-oxidant activity. The differential pulse voltammograms of free metabolites and their iron(II) coordination complexes reflected these properties. Nano-ESI-MS confirmed ANA and 3-HANA as efficient iron(II) chelators, both of which form coordination complexes of ligand:iron(II) ratio 1:1, 2:1, and 3:1. In addition, nano-ESI-MS analyses of the oxidation effects by hydroxyl radical attack identified 3-HANA as strikingly more susceptible than ANA. 3-HANA susceptibility to oxidation may explain its decreased concentrations in the reaction mixture. The presented observations can add to explaining why 3-HANA levels decrease in patients with some neurological and other diseases which can often associated with elevated concentrations of ROS. Author Affiliation: (a) Division of Molecular Systems Biology, Department of Ecogenomics and Systems Biology, Faculty of Life Sciences, University of Vienna, Althanstrasse 14, Vienna A-1090, Austria (b) Plant Biochemistry, Albrecht-von-Haller Institut, Georg-August-Universitat Gottingen, Justus-von-Liebig-Weg 11, Gottingen D-37077, Germany Article History: Received 17 October 2014; Revised 7 January 2015; Accepted 8 January 2015
    Keywords: Mass Spectrometry – Chemical Properties ; Mass Spectrometry – Comparative Analysis ; Metabolites – Chemical Properties ; Metabolites – Comparative Analysis ; Tryptophan – Chemical Properties ; Tryptophan – Comparative Analysis ; Nervous System Diseases – Chemical Properties ; Nervous System Diseases – Comparative Analysis ; Antioxidants (Nutrients) – Chemical Properties ; Antioxidants (Nutrients) – Comparative Analysis ; Monosaccharides – Chemical Properties ; Monosaccharides – Comparative Analysis
    ISSN: 0022-328X
    Source: Cengage Learning, Inc.
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  • 8
    Language: English
    In: Journal of Organometallic Chemistry, April 15, 2015, Vol.782, p.111(5)
    Description: To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jorganchem.2015.01.030 Byline: Lenka Kubicova, Franz Hadacek, Wolfram Weckwerth, Vladimir Chobot Abstract: The tryptophan metabolite, quinolinic (2,3-pyridinedicarboxylic) acid, is known as an endogenous neurotoxin. Quinolinic acid can form coordination complexes with iron or copper. The effects of quinolinic acid on reactive oxygen species production in the presence of iron or copper were explored by a combination of chemical assays, classical site-specific and ascorbic acid-free variants of the deoxyribose degradation assay, and mass spectrometry (ESI-MS). Quinolinic acid showed evident antioxidant activity in chemical assays, but the effect was more pronounced in the presence of copper as transition metal catalyst than in presence of iron. Nano-ESI-MS confirmed the ability of quinolinic acid to form coordination complexes with iron(II) or copper(II) and quinolinic acid stability against oxidative attack by hydroxyl radicals. The results illustrate a highly milieu-dependent quinolinic acid chemistry when it enters reactions as competitive ligand. Author Affiliation: (a) Division of Molecular Systems Biology, Department of Ecogenomics and Systems Biology, Faculty of Life Sciences, University of Vienna, Althanstrasse 14, Vienna A-1090, Austria (b) Plant Biochemistry, Albrecht-von-Haller Institut, Georg-August-Universitat Gottingen, Justus-von-Liebig-Weg 11, Gottingen D-37077, Germany Article History: Received 31 October 2014; Revised 4 January 2015; Accepted 14 January 2015
    Keywords: Mass Spectrometry ; Tryptophan ; Metabolites ; Copper Compounds ; Antioxidants (Nutrients) ; Monosaccharides ; Pyridine
    ISSN: 0022-328X
    Source: Cengage Learning, Inc.
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  • 9
    In: Plant Journal, July 2010, Vol.63(1), pp.1-17
    Description: Protein phosphorylation/dephosphorylation is a central post‐translational modification in plant hormone signaling, but little is known about its extent and function. Although pertinent protein kinases and phosphatases have been predicted and identified for a variety of hormone responses, classical biochemical approaches have so far revealed only a few candidate proteins and even fewer phosphorylation sites. Here we performed a global quantitative analysis of the Arabidopsis phosphoproteome in response to a time course of treatments with various plant hormones using phosphopeptide enrichment and subsequent mass accuracy precursor alignment (MAPA). The use of three time points, 1, 3 and 6 h, in combination with five phytohormone treatments, abscisic acid (ABA), indole‐3‐acetic acid (IAA), gibberellic acid (GA), jasmonic acid (JA) and kinetin, resulted in 324 000 precursor ions from 54 LC‐Orbitrap‐MS analyses quantified and aligned in a data matrix with the dimension of 6000 × 54 using the ProtMax algorithm. To dissect the phytohormone responses, multivariate principal/independent components analysis was performed. In total, 152 phosphopeptides were identified as differentially regulated; these phosphopeptides are involved in a wide variety of signaling pathways. New phosphorylation sites were identified for ABA response element binding factors that showed a specific increase in response to ABA. New phosphorylation sites were also found for RLKs and auxin transporters. We found that different hormones regulate distinct amino acid residues of members of the same protein families. In contrast, tyrosine phosphorylation of the Gα subunit appeared to be a common response for multiple hormones, demonstrating global cross‐talk among hormone signaling pathways.
    Keywords: Aba ; Areb ; B‐Zip ; Arabidopsis ; Mass Spectrometry ; Phosphoproteomics
    ISSN: 0960-7412
    E-ISSN: 1365-313X
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  • 10
    Language: English
    In: Proceedings of the National Academy of Sciences of the United States of America, 17 August 2010, Vol.107(33), pp.14915-20
    Description: The integral peroxisomal membrane proteins PEX10, PEX2, and PEX12 contain a zinc RING finger close to the C terminus. Loss of function of these peroxins causes embryo lethality at the heart stage in Arabidopsis. Preventing the coordination of Zn(2+) ions by amino acid substitutions in PEX10, PEX2, and PEX12 and overexpressing the resulting conditional sublethal mutations in WT uncovered additional functions of PEX10. Plants overexpressing DeltaZn-mutant PEX10 display deformed peroxisomal shapes causing diminished contact with chloroplasts and possibly with mitochondria. These changes correlated with impaired metabolite transfer and, at high CO(2), recoverable defective photorespiration plus dwarfish phenotype. The N-terminal PEX10 domain is critical for peroxisome biogenesis and plant development. A point mutation in the highly conserved TLGEEY motif results in vermiform peroxisome shape without impairing organelle contact. Addition of an N-terminal T7 tag to WT PEX0 resulted in partially recoverable reduced growth and defective inflorescences persisting under high CO(2). In contrast, plants overexpressing PEX2-DeltaZn-T7 grow like WT in normal atmosphere, contain normal-shaped peroxisomes, but display impaired peroxisomal matrix protein import. PEX12-DeltaZn-T7 mutants exhibit unimpaired import of matrix protein and normal-shaped peroxisomes when grown in normal atmosphere. During seed germination, glyoxysomes form a reticulum around the lipid bodies for mobilization of storage oil. The formation of this glyoxysomal reticulum seemed to be impaired in PEX10-DeltaZn but not in PEX2-DeltaZn-T7 or PEX12-DeltaZn-T7 plants. Both cytosolic PEX10 domains seem essential for peroxisome structure but differ in metabolic function, suggesting a role for this plant peroxin in addition to the import of matrix protein via ubiquitination of PEX5.
    Keywords: Arabidopsis -- Metabolism ; Arabidopsis Proteins -- Metabolism ; Membrane Proteins -- Metabolism ; Membrane Transport Proteins -- Metabolism ; Peroxisomes -- Metabolism
    ISSN: 00278424
    E-ISSN: 1091-6490
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