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Is a plant’s ploidy status reflected in its metabolome?

Is a plant’s ploidy status reflected in its metabolome? | Plant Metabolomics | Scoop.it
With the enrichment of metabolomic information in a diverse number of plants, the obtained datasets reflect on important aspects of plant growth, function, physiology, productivity, and adaptation to changing biotic and abiotic environments. Many of these plant species are natural polyploids that are either model plants, crops, or are of commercial interest. Decades of efforts have resulted in artificially induced polyploids from in vitro micropropagation practices as well. Recent efforts using next generation, high throughput genome sequencing approaches have contributed to our growing understanding of their genome ploidy status and the inherent biosynthetic potentials of encoded metabolomes. However, the ever perplexing questions galore regarding the metabolic status of these polyploids across plant genomes remained. Thus,...
Biswapriya B Misra's insight:

With the enrichment of metabolomic information in a diverse number of plants, the obtained datasets reflect on important aspects of plant growth, function, physiology, productivity, and adaptation to changing biotic and abiotic environments. Many of these plant species are natural polyploids that are either model plants, crops, or are of commercial interest. Decades of efforts have resulted in artificially induced polyploids from in vitro micropropagation practices as well. Recent efforts using next generation, high throughput genome sequencing approaches have contributed to our growing understanding of their genome ploidy status and the inherent biosynthetic potentials of encoded metabolomes. However, the ever perplexing questions galore regarding the metabolic status of these polyploids across plant genomes remained. Thus we collated information on metabolomes of polyploids and asked whether they reflect the ploidy status of these plants. We conclude that polyploids, either natural or those induced artificially, demonstrate (i) enhanced primary metabolism, (ii) enhanced secondary metabolism, i.e., terpenoids, phenylpropanoids, flavonoids, and alkaloids content, and (iii) increased bioactive constituents to enable polyploids to counteract against environmental challenges in a more efficient manner in the plant species included in this review.

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Metab2MeSH - Biological Substance Annotation with MeSH Terms

Metab2MeSH - Biological Substance Annotation with MeSH Terms | Plant Metabolomics | Scoop.it
Metab2MeSH uses a statistical approach to reliably and automatically annotate metabolites with the concepts defined in MeSH (Medical Subject Headings), the National Library of Medicine’s controlled vocabulary for biomedical concepts. These annotations provide links from chemical substances to the biomedical research literature and complement existing resources including PubChem and the Human Metabolome Database.
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Metab2MeSH uses a statistical approach to reliably and automatically annotate metabolites with the concepts defined in MeSH (Medical Subject Headings), the National Library of Medicine’s controlled vocabulary for biomedical concepts. These annotations provide links from chemical substances to the biomedical research literature and complement existing resources including PubChem and the Human Metabolome Database.

 
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Poplar trees reconfigure the transcriptome and metabolome in response to drought in a genotype- and time-of-day-dependent manner

Background Drought has a major impact on tree growth and survival. Understanding tree responses to this stress can have important application in both conservation of forest health, and in production forestry. Trees of the genus Populus provide an excellent opportunity to explore the mechanistic underpinnings of forest tree drought responses, given the growing molecular resources that are available for this taxon. Here, foliar tissue of six water-deficit stressed P. balsamifera genotypes was analysed for variation in the metabolome in response to drought and time of day by using an untargeted metabolite profiling technique, gas chromatography/mass-spectrometry (GC/MS). Results Significant variation in the metabolome was observed in response the imposition of water-deficit stress. Notably, organic acid intermediates such as succinic and malic acid had lower concentrations in leaves exposed to drought, whereas galactinol and raffinose were found in increased concentrations. A number of metabolites with significant difference in accumulation under water-deficit conditions exhibited intraspecific variation in metabolite accumulation. Large magnitude fold-change accumulation was observed in three of the six genotypes. In order to understand the interaction between the transcriptome and metabolome, an integrated analysis of the drought-responsive transcriptome and the metabolome was performed. One P. balsamifera genotype, AP-1006, demonstrated a lack of congruence between the magnitude of the drought transcriptome response and the magnitude of the metabolome response. More specifically, metabolite profiles in AP-1006 demonstrated the smallest changes in response to water-deficit conditions. Conclusions Pathway analysis of the transcriptome and metabolome revealed specific genotypic responses with respect to primary sugar accumulation, citric acid metabolism, and raffinose family oligosaccharide biosynthesis. The intraspecific variation in the molecular strategies that underpin the responses to drought among genotypes may have an important role in the maintenance of forest health and productivity.
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Background Drought has a major impact on tree growth and survival. Understanding tree responses to this stress can have important application in both conservation of forest health, and in production forestry. Trees of the genus Populus provide an excellent opportunity to explore the mechanistic underpinnings of forest tree drought responses, given the growing molecular resources that are available for this taxon. Here, foliar tissue of six water-deficit stressed P. balsamifera genotypes was analysed for variation in the metabolome in response to drought and time of day by using an untargeted metabolite profiling technique, gas chromatography/mass-spectrometry (GC/MS). Results Significant variation in the metabolome was observed in response the imposition of water-deficit stress. Notably, organic acid intermediates such as succinic and malic acid had lower concentrations in leaves exposed to drought, whereas galactinol and raffinose were found in increased concentrations. A number of metabolites with significant difference in accumulation under water-deficit conditions exhibited intraspecific variation in metabolite accumulation. Large magnitude fold-change accumulation was observed in three of the six genotypes. In order to understand the interaction between the transcriptome and metabolome, an integrated analysis of the drought-responsive transcriptome and the metabolome was performed. One P. balsamifera genotype, AP-1006, demonstrated a lack of congruence between the magnitude of the drought transcriptome response and the magnitude of the metabolome response. More specifically, metabolite profiles in AP-1006 demonstrated the smallest changes in response to water-deficit conditions. Conclusions Pathway analysis of the transcriptome and metabolome revealed specific genotypic responses with respect to primary sugar accumulation, citric acid metabolism, and raffinose family oligosaccharide biosynthesis. The intraspecific variation in the molecular strategies that underpin the responses to drought among genotypes may have an important role in the maintenance of forest health and productivity.

 
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MPEA

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MPEA is a rapid tool for functional analysis and biological interpretation of metabolic profiling data. In particular, MPEA is designed to be used with data generated by gas chromatography–mass spectrometry (GC–MS); one of the most prominent analytical methods for metabolic studies and able to quantify hundreds of small molecules from biological extracts in a single run.

The concept of MPEA is the same as that of the widely-accepted GSEA (gene set enrichment analysis). MPEA accepts a ranked list of mass spectra and tests whether metabolites belonging to some KEGG-pathway tend to occur toward the top (or bottom) of this list. More specifically, the identity of the query analytes is solved by using ms-analysis tool at GMD. The mass spectrum of the query analyte is compared against the spectral library and the query analyte is marked to belong to the KEGG pathways to which its matching reference analytes belong. Ambiguous analyte identifications are solved and for each KEGG-pathway hypergeometic distribution is then applied to calculate the statistical enrichment of KEGG-compounds of the pathways within the data (MPEA tests if there are more analytes belonging to the pathway in the list than could be expected by change.) The statistical test is repetitively performed by walking down the analyte list and the most significant rank position is stored for each pathway. To reliably estimate the random chance to obtain a result as significant as the one obtained, the entire statistical process is done multiple times after randomizing the order of analytes and by calculating permutation based enrichment values.

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MRM-Ion Pair Finder: a systematic approach to transform non-targeted mode to pseudo-targeted mode for metabolomics study based on liquid chromatography-mass spectrometry

MRM-Ion Pair Finder: a systematic approach to transform non-targeted mode to pseudo-targeted mode for metabolomics study based on liquid chromatography-mass spectrometry | Plant Metabolomics | Scoop.it
Biswapriya B Misra's insight:

Pseudo-targeted metabolic profiling is a novel strategy combining the advantages of both targeted and untargeted methods. The strategy obtains metabolites and their product ions from Q-TOF MS by information-dependent acquisition (IDA), then picks targeted ion-pair and measures them on a triple-quadrupole MS by multiple reaction monitoring (MRM). The picking of ion pairs from thousands of candidates is the most time-consuming step of pseudo-targeted strategy. Herein, a systematic and automated approach and software (MRM-Ion Pair Finder) were developed to acquire characteristic MRM ion pairs by precursor ions alignment, MS2 spectrum extraction and reduction, characteristic product ion selection, and ion fusion. To test the reliability of the approach, a mixture of 15 metabolite standards was firstly analyzed and the representative ion pairs were correctly picked out, then pooled serum samples were further studied and the results were confirmed by the manual selection. Finally, a comparison with a commercial peak alignment software was performed, a good characteristic ion coverage of metabolites was obtained. As a proof of concept, the proposed approach was applied to a metabolomics study of liver cancer, 854 metabolite ion pairs were defined in the positive ion mode from serum. Our approach provides a high throughput method which is reliable to acquire MRM ion pairs for pseudo-targeted metabolomics with improved metabolite coverage and facilitate more reliable biomarkers discoveries.

 
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BioSMXpress - Identification of unknown Biochemical Structures in Metabolomics

BioSMXpress - Identification of unknown Biochemical Structures in Metabolomics | Plant Metabolomics | Scoop.it
BioSMXpress was designed and developed as an enhancement to BioSM. BioSMXpress is, on average, 8 times faster than BioSM without compromising the quality of the predictions made. BioSMXpress will be an extremely useful tool in the timely identification of unknown biochemical structures in metabolomics.
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BioSMXpress was designed and developed as an enhancement to BioSM. BioSMXpress is, on average, 8 times faster than BioSM without compromising the quality of the predictions made. BioSMXpress will be an extremely useful tool in the timely identification of unknown biochemical structures in metabolomics.

 
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Diel metabolomics analysis of a hot spring chlorophototrophic microbial mat leads to new hypotheses of community member metabolisms | Microbial Physiology and Metabolism

Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptive and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number of predominant taxa inhabit this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms, and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g., glycolate) and fermentation (e.g., acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gasses (e.g., H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: (1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; (2) photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; (3) glycolate and lactate are exchanged among Synechococcus and Roseiflexus spp.; and (4) fluctuations in many metabolite pools (e.g., wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences in their niches.
Biswapriya B Misra's insight:

Dynamic environmental factors such as light, nutrients, salt, and temperature continuously affect chlorophototrophic microbial mats, requiring adaptive and acclimative responses to stabilize composition and function. Quantitative metabolomics analysis can provide insights into metabolite dynamics for understanding community response to such changing environmental conditions. In this study, we quantified volatile organic acids, polar metabolites (amino acids, glycolytic and citric acid cycle intermediates, nucleobases, nucleosides, and sugars), wax esters, and polyhydroxyalkanoates, resulting in the identification of 104 metabolites and related molecules in thermal chlorophototrophic microbial mat cores collected over a diel cycle in Mushroom Spring, Yellowstone National Park. A limited number of predominant taxa inhabit this community and their functional potentials have been previously identified through metagenomic and metatranscriptomic analyses and in situ metabolisms, and metabolic interactions among these taxa have been hypothesized. Our metabolomics results confirmed the diel cycling of photorespiration (e.g., glycolate) and fermentation (e.g., acetate, propionate, and lactate) products, the carbon storage polymers polyhydroxyalkanoates, and dissolved gasses (e.g., H2 and CO2) in the waters overlying the mat, which were hypothesized to occur in major mat chlorophototrophic community members. In addition, we have formulated the following new hypotheses: (1) the morning hours are a time of biosynthesis of amino acids, DNA, and RNA; (2) photo-inhibited cells may also produce lactate via fermentation as an alternate metabolism; (3) glycolate and lactate are exchanged amongSynechococcus and Roseiflexus spp.; and (4) fluctuations in many metabolite pools (e.g., wax esters) at different times of day result from species found at different depths within the mat responding to temporal differences in their niches.

  
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Metabolomics-Based Chemotaxonomic Classification of Streptomyces spp. and its Correlation with Antibacterial Activity.

Metabolomics-Based Chemotaxonomic Classification of Streptomyces spp. and its Correlation with Antibacterial Activity. | Plant Metabolomics | Scoop.it
J Microbiol Biotechnol. 2015 Apr 15. [Epub ahead of print]
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Secondary metabolite-based chemotaxonomic classification of Streptomyces (8 species, 14 strains) was performed using ultra-performance liquid chromatography-quadrupole-time-of-flight-mass spectrometry with multivariate statistical analysis. Most strains were generally well separated by grouping under each species. In particular, S. rimosus was discriminated from the remaining 7 species (S. coelicolor, S. griseus, S. indigoferus, S. peucetius, S. rubrolavendulae, S. scabiei, and S. virginiae) in partial least squares discriminant analysis, and oxytetracycline and rimocidin were identified as S. rimosus-specific metabolites. S. rimosus also showed high antibacterial activity against Xanthomonas oryzae pv. oryzae (Xoo), the pathogen responsible for rice bacterial blight. This study demonstrated that metabolite-based chemotaxonomic classification is an effective tool for distinguishing Streptomyces spp. and for determining their species-specific metabolites.

  
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luis Quiros-Guerrero's curator insight, April 20, 9:49 PM

excellent approach.

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Distinct metabolomic signatures are associated with longevity in humans

Distinct metabolomic signatures are associated with longevity in humans | Plant Metabolomics | Scoop.it
onge
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Alterations in metabolism influence lifespan in experimental models, but data in humans are lacking. Here we use liquid chromatography/mass spectrometry to quantify 217 plasma metabolites and examine their relation to longevity in a large cohort of men and women followed for up to 20 years. We find that, higher concentrations of the citric acid cycle intermediate, isocitrate, and the bile acid, taurocholate, are associated with lower odds of longevity, defined as attaining 80 years of age. Higher concentrations of isocitrate, but not taurocholate, are also associated with worse cardiovascular health at baseline, as well as risk of future cardiovascular disease and death. None of the metabolites identified are associated with cancer risk. Our findings suggest that some, but not all, metabolic pathways related to human longevity are linked to the risk of common causes of death.

 
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GS-align for Glycan Structure Alignment and Similarity Measurement

GS-align for Glycan Structure Alignment and Similarity Measurement | Plant Metabolomics | Scoop.it
Motivation: Glycans play critical roles in many biological processes, and their structural diversity is key for specific protein-glycan recognition. Comparative structural studies of biological molecules provide useful insight into their biological relationships. However, most computational tools are designed for protein structure, and despite their importance, there is no currently available tool for comparing glycan structures in a sequence order- and size-independent manner.

Results: A novel method, GS-align, is developed for glycan structure alignment and similarity measurement. GS-align generates possible alignments between two glycan structures through iterative maximum clique search and fragment superposition. The optimal alignment is then determined by the maximum structural similarity score, GS-score, which is size-independent. Benchmark tests against the PDB N-linked glycan library and PDB homologous/non-homologous N-glycoprotein sets indicate that GS-align is a robust computational tool to align glycan structures and quantify their structural similarity. GS-align is also applied to template-based glycan structure prediction and monosaccharide substitution matrix generation to illustrate its utility.
Biswapriya B Misra's insight:

Motivation: Glycans play critical roles in many biological processes, and their structural diversity is key for specific protein-glycan recognition. Comparative structural studies of biological molecules provide useful insight into their biological relationships. However, most computational tools are designed for protein structure, and despite their importance, there is no currently available tool for comparing glycan structures in a sequence order- and size-independent manner.

Results: A novel method, GS-align, is developed for glycan structure alignment and similarity measurement. GS-align generates possible alignments between two glycan structures through iterative maximum clique search and fragment superposition. The optimal alignment is then determined by the maximum structural similarity score, GS-score, which is size-independent. Benchmark tests against the PDB N-linked glycan library and PDB homologous/non-homologous N-glycoprotein sets indicate that GS-align is a robust computational tool to align glycan structures and quantify their structural similarity. GS-align is also applied to template-based glycan structure prediction and monosaccharide substitution matrix generation to illustrate its utility.

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Transcriptome and Metabolite Profiling of the Infection Cycle of Zymoseptoria tritici on Wheat Reveals a Biphasic Interaction with Plant Immunity Involving Differential Pathogen Chromosomal Contrib...

Transcriptome and Metabolite Profiling of the Infection Cycle of Zymoseptoria tritici on Wheat Reveals a Biphasic Interaction with Plant Immunity Involving Differential Pathogen Chromosomal Contrib... | Plant Metabolomics | Scoop.it
The hemibiotrophic fungus Zymoseptoria tritici causes Septoria tritici blotch disease of wheat (Triticum aestivum). Pathogen reproduction on wheat occurs without cell penetration, suggesting that dynamic and intimate intercellular communication occurs between fungus and plant throughout the disease cycle. We used deep RNA sequencing and metabolomics to investigate the physiology of plant and pathogen throughout an asexual reproductive cycle of Z. tritici on wheat leaves. Over 3,000 pathogen genes, more than 7,000 wheat genes, and more than 300 metabolites were differentially regulated. Intriguingly, individual fungal chromosomes contributed unequally to the overall gene expression changes. Early transcriptional down-regulation of putative host defense genes was detected in inoculated leaves. There was little evidence for fungal nutrient acquisition from the plant throughout symptomless colonization by Z. tritici, which may instead be utilizing lipid and fatty acid stores for growth. However, the fungus then subsequently manipulated specific plant carbohydrates, including fructan metabolites, during the switch to necrotrophic growth and reproduction. This switch coincided with increased expression of jasmonic acid biosynthesis genes and large-scale activation of other plant defense responses. Fungal genes encoding putative secondary metabolite clusters and secreted effector proteins were identified with distinct infection phase-specific expression patterns, although functional analysis suggested that many have overlapping/redundant functions in virulence. The pathogenic lifestyle of Z. tritici on wheat revealed through this study, involving initial defense suppression by a slow-growing extracellular and nutritionally limited pathogen followed by defense (hyper) activation during reproduction, reveals a subtle modification of the conceptual definition of hemibiotrophic plant infection.
Biswapriya B Misra's insight:

The hemibiotrophic fungus Zymoseptoria tritici causes Septoria tritici blotch disease of wheat (Triticum aestivum). Pathogen reproduction on wheat occurs without cell penetration, suggesting that dynamic and intimate intercellular communication occurs between fungus and plant throughout the disease cycle. We used deep RNA sequencing and metabolomics to investigate the physiology of plant and pathogen throughout an asexual reproductive cycle of Z. tritici on wheat leaves. Over 3,000 pathogen genes, more than 7,000 wheat genes, and more than 300 metabolites were differentially regulated. Intriguingly, individual fungal chromosomes contributed unequally to the overall gene expression changes. Early transcriptional down-regulation of putative host defense genes was detected in inoculated leaves. There was little evidence for fungal nutrient acquisition from the plant throughout symptomless colonization by Z. tritici, which may instead be utilizing lipid and fatty acid stores for growth. However, the fungus then subsequently manipulated specific plant carbohydrates, including fructan metabolites, during the switch to necrotrophic growth and reproduction. This switch coincided with increased expression of jasmonic acid biosynthesis genes and large-scale activation of other plant defense responses. Fungal genes encoding putative secondary metabolite clusters and secreted effector proteins were identified with distinct infection phase-specific expression patterns, although functional analysis suggested that many have overlapping/redundant functions in virulence. The pathogenic lifestyle of Z. tritici on wheat revealed through this study, involving initial defense suppression by a slow-growing extracellular and nutritionally limited pathogen followed by defense (hyper) activation during reproduction, reveals a subtle modification of the conceptual definition of hemibiotrophic plant infection.

 
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A Novel Pyrimidin-Like Plant Activator Stimulates Plant Disease Resistance and Promotes Growth

A Novel Pyrimidin-Like Plant Activator Stimulates Plant Disease Resistance and Promotes Growth | Plant Metabolomics | Scoop.it
Plant activators are chemicals that induce plant defense responses to a broad spectrum of pathogens. Here, we identified a new potential plant activator, 5-(cyclopropylmethyl)-6-methyl-2-(2-pyridyl)pyrimidin-4-ol,named PPA (pyrimidin-type plant activator). Compared with benzothiadiazole S-methyl ester (BTH), a functional analog of salicylic acid (SA), PPA was fully soluble in water and increased fresh weight of rice (Oryza sativa) and Arabidopsis plants at low concentrations. In addition, PPA also promoted lateral root development. Microarray data and real-time PCR revealed that PPA-treated leaves not challenged with pathogen showed up-regulation of genes related to reactive oxygen species (ROS), defenses and SA. During bacterial infection, Arabidopsis plants pretreated with PPA showed dramatically decreased disease symptoms and an earlier and stronger ROS burst, compared with plants pretreated with BTH. Microscopy revealed that H2O2 accumulated in the cytosol, plasma membrane and cell wall around intracellular bacteria, and also on the bacterial cell wall, indicating that H2O2 was directly involved in killing bacteria. The increase in ROS-related gene expression also supported this observation. Our results indicate that PPA enhances plant defenses against pathogen invasion through the plant redox system, and as a water-soluble compound that can promote plant growth, has broad potential applications in agriculture.
Biswapriya B Misra's insight:

Plant activators are chemicals that induce plant defense responses to a broad spectrum of pathogens. Here, we identified a new potential plant activator, 5-(cyclopropylmethyl)-6-methyl-2-(2-pyridyl)pyrimidin-4-ol,named PPA (pyrimidin-type plant activator). Compared with benzothiadiazole S-methyl ester (BTH), a functional analog of salicylic acid (SA), PPA was fully soluble in water and increased fresh weight of rice (Oryza sativa) and Arabidopsis plants at low concentrations. In addition, PPA also promoted lateral root development. Microarray data and real-time PCR revealed that PPA-treated leaves not challenged with pathogen showed up-regulation of genes related to reactive oxygen species (ROS), defenses and SA. During bacterial infection, Arabidopsis plants pretreated with PPA showed dramatically decreased disease symptoms and an earlier and stronger ROS burst, compared with plants pretreated with BTH. Microscopy revealed that H2O2 accumulated in the cytosol, plasma membrane and cell wall around intracellular bacteria, and also on the bacterial cell wall, indicating that H2O2was directly involved in killing bacteria. The increase in ROS-related gene expression also supported this observation. Our results indicate that PPA enhances plant defenses against pathogen invasion through the plant redox system, and as a water-soluble compound that can promote plant growth, has broad potential applications in agriculture.

  
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mQTL.NMR: An Integrated Suite for Genetic Mapping of Quantitative Variations of 1H NMR-Based Metabolic Profiles

mQTL.NMR: An Integrated Suite for Genetic Mapping of Quantitative Variations of 1H NMR-Based Metabolic Profiles | Plant Metabolomics | Scoop.it
High-throughput 1H nuclear magnetic resonance (NMR) is an increasingly popular robust approach for qualitative and quantitative metabolic profiling, which can be used in conjunction with genomic techniques to discover novel genetic associations through metabotype quantitative trait locus (mQTL) mapping. There is therefore a crucial necessity to develop specialized tools for an accurate detection and unbiased interpretability of the genetically determined metabolic signals. Here we introduce and implement a combined chemoinformatic approach for objective and systematic analysis of untargeted 1H NMR-based metabolic profiles in quantitative genetic contexts. The R/Bioconductor mQTL.NMR package was designed to (i) perform a series of preprocessing steps restoring spectral dependency in collinear NMR data sets to reduce the multiple testing burden, (ii) carry out robust and accurate mQTL mapping in human cohorts as well as in rodent models, (iii) statistically enhance structural assignment of genetically determined metabolites, and (iv) illustrate results with a series of visualization tools. Built-in flexibility and implementation in the powerful R/Bioconductor framework allow key preprocessing steps such as peak alignment, normalization, or dimensionality reduction to be tailored to specific problems. The mQTL.NMR package is freely available with its source code through the Comprehensive R/Bioconductor repository and its own website (http://www.ican-institute.org/tools/). It represents a significant advance to facilitate untargeted metabolomic data processing and quantitative analysis and their genetic mapping.
Biswapriya B Misra's insight:

High-throughput 1H nuclear magnetic resonance (NMR) is an increasingly popular robust approach for qualitative and quantitative metabolic profiling, which can be used in conjunction with genomic techniques to discover novel genetic associations through metabotype quantitative trait locus (mQTL) mapping. There is therefore a crucial necessity to develop specialized tools for an accurate detection and unbiased interpretability of the genetically determined metabolic signals. Here we introduce and implement a combined chemoinformatic approach for objective and systematic analysis of untargeted 1H NMR-based metabolic profiles in quantitative genetic contexts. The R/Bioconductor mQTL.NMR package was designed to (i) perform a series of preprocessing steps restoring spectral dependency in collinear NMR data sets to reduce the multiple testing burden, (ii) carry out robust and accurate mQTL mapping in human cohorts as well as in rodent models, (iii) statistically enhance structural assignment of genetically determined metabolites, and (iv) illustrate results with a series of visualization tools. Built-in flexibility and implementation in the powerful R/Bioconductor framework allow key preprocessing steps such as peak alignment, normalization, or dimensionality reduction to be tailored to specific problems. The mQTL.NMR package is freely available with its source code through the Comprehensive R/Bioconductor repository and its own website (http://www.ican-institute.org/tools/). It represents a significant advance to facilitate untargeted metabolomic data processing and quantitative analysis and their genetic mapping.

 
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MPEA - Metabolite Pathway Enrichment Analysis

MPEA - Metabolite Pathway Enrichment Analysis | Plant Metabolomics | Scoop.it
MPEA :: DESCRIPTION MPEA is a rapid tool for functional analysis and biological interpretation of metabolic profiling data. In particular, MPEA is designed to be used with data generated by gas chr...
Biswapriya B Misra's insight:

MPEA is a rapid tool for functional analysis and biological interpretation of metabolic profiling data. In particular, MPEA is designed to be used with data generated by gas chromatography mass spectrometry (GCMS); one of the most prominent analytical methods for metabolic studies and able to quantify hundreds of small molecules from biological extracts in a single run.

 
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Metabolome Searcher - Metabolite Identification and Metabolic Pathway Mapping

Metabolome Searcher - Metabolite Identification and Metabolic Pathway Mapping | Plant Metabolomics | Scoop.it
Metabolome Searcher :: DESCRIPTION Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability. ::DEVELOPER Meta...
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Metabolome Searcher, a web-based tool, facilitates putative compound identification of MS output based on genome-restricted metabolic capability.

 
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metabosearch - Mass-based Metabolite Identification using multiple databases

metabosearch - Mass-based Metabolite Identification using multiple databases | Plant Metabolomics | Scoop.it
metabosearch :: DESCRIPTION MetaboSearch performs mass-based metabolite search simultaneously against the four major metabolite databases: Human Metabolome DataBase (HMDB), Madison Metabolomics Con...
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MetaboSearch performs mass-based metabolite search simultaneously against the four major metabolite databases: Human Metabolome DataBase (HMDB), Madison Metabolomics Consortium Database (MMCD), Metlin, and LipidMaps.

 
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luis Quiros-Guerrero's curator insight, April 25, 12:16 PM

usefull tool for dereplication...

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Method for the Compound Annotation of Conjugates in Nontargeted Metabolomics Using Accurate Mass Spectrometry, Multistage Product Ion Spectra and Compound Database Searching

Biswapriya B Misra's insight:

Owing to biotransformation, xenobiotics are often found in conjugated form in biological samples such as urine and plasma. Liquid chromatography coupled with accurate mass spectrometry with multistage collision-induced dissociation provides spectral information concerning these metabolites in complex materials. Unfortunately, compound databases typically do not contain a sufficient number of records for such conjugates. We report here on the development of a novel protocol, referred to as ChemProphet, to annotate compounds, including conjugates, using compound databases such as PubChem and ChemSpider. The annotation of conjugates involves three steps: 1. Recognition of the type and number of conjugates in the sample; 2. Compound search and annotation of the deconjugated form; and 3. In silico evaluation of the candidate conjugate. ChemProphet assigns a spectrum to each candidate by automatically exploring the substructures corresponding to the observed product ion spectrum. When finished, it annotates the candidates assigning a rank for each candidate based on the calculated score that ranks its relative likelihood. We assessed our protocol by annotating a benchmark dataset by including the product ion spectra for 102 compounds, annotating the commercially available standard for quercetin 3-glucuronide, and by conducting a model experiment using urine from mice that had been administered a green tea extract. The results show that by using the ChemProphet approach, it is possible to annotate not only the deconjugated molecules but also the conjugated molecules using an automatic interpretation method based on deconjugation that involves multistage collision-induced dissociation and in silico calculated conjugation.

  
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luis Quiros-Guerrero's curator insight, April 25, 12:18 PM

interesting topic.. one xenobiotic transformed in different ways...

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Development of Versatile Isotopic Labeling Reagents for Profiling the Amine Submetabolome by Liquid Chromatography Mass Spectrometry

Development of Versatile Isotopic Labeling Reagents for Profiling the Amine Submetabolome by Liquid Chromatography Mass Spectrometry | Plant Metabolomics | Scoop.it
Biswapriya B Misra's insight:

Metabolomic profiling involves relative quantification of metabolites in comparative samples and identification of the significant metabolites that differentiate different groups (e.g., diseased vs. controls). Chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) is an enabling technique that can provide improved metabolome coverage and metabolite quantification. However, chemical identification of labeled metabolites can still be a challenge. In this work, a new set of isotopic labeling reagents offering versatile properties to enhance both detection and identification are described. They were prepared by a glycine molecule (or its isotopic counterpart) and an aromatic acid with varying structures through a simple three-step synthesis route. In addition to relatively low costs of synthesizing the reagents, this reaction route allows adjusting reagent property in accordance with the desired application objective. To date, two isotopic reagents, 4-dimethylaminobenzoylamido acetic acid N-hydroxylsuccinimide ester (DBAA-NHS) and 4-methoxybenzoylamido acetic acid N-hydroxylsuccinimide ester (MBAA-NHS), for labeling the amine-containing metabolites (i.e., amine submetabolome) have been synthesized. The labeling conditions and the related LC-MS method have been optimized. We demonstrate that DBAA labeling can increase the metabolite detectability because of the presence of an electrospray ionization (ESI)-active dimethylaminobenzoyl group. On the other hand, MBAA labeled metabolites can be fragmented in MS/MS and pseudo MS3 experiments to provide structural information on metabolites of interest. Thus, these reagents can be tailored to quantitative profiling of the amine submetabolome as well as metabolite identification in metabolomics applications.

 
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Understanding developmental and adaptive cues in pine through metabolite profiling and co-expression network analysis.

Understanding developmental and adaptive cues in pine through metabolite profiling and co-expression network analysis. | Plant Metabolomics | Scoop.it
Conifers include long-lived evergreen trees of great economic and ecological importance, including pines and spruces. During their long lives conifers must respond to seasonal environmental changes, adapt to unpredictable environmental stresses, and co-ordinate their adaptive adjustments with internal developmental programmes. To gain insights into these responses, we examined metabolite and transcriptomic profiles of needles from naturally growing 25-year-old maritime pine (Pinus pinaster L. Aiton) trees over a year. The effect of environmental parameters such as temperature and rain on needle development were studied. Our results show that seasonal changes in the metabolite profiles were mainly affected by the needles' age and acclimation for winter, but changes in transcript profiles were mainly dependent on climatic factors. The relative abundance of most transcripts correlated well with temperature, particularly for genes involved in photosynthesis or winter acclimation. Gene network analysis revealed relationships between 14 co-expressed gene modules and development and adaptation to environmental stimuli. Novel Myb transcription factors were identified as candidate regulators during needle development. Our systems-based analysis provides integrated data of the seasonal regulation of maritime pine growth, opening new perspectives for understanding the complex regulatory mechanisms underlying conifers' adaptive responses. Taken together, our results suggest that the environment regulates the transcriptome for fine tuning of the metabolome during development.
Biswapriya B Misra's insight:

Conifers include long-lived evergreen trees of great economic and ecological importance, including pines and spruces. During their long lives conifers must respond to seasonal environmental changes, adapt to unpredictable environmental stresses, and co-ordinate their adaptive adjustments with internal developmental programmes. To gain insights into these responses, we examined metabolite and transcriptomic profiles of needles from naturally growing 25-year-old maritime pine (Pinus pinaster L. Aiton) trees over a year. The effect of environmental parameters such as temperature and rain on needle development were studied. Our results show that seasonal changes in the metabolite profiles were mainly affected by the needles' age and acclimation for winter, but changes in transcript profiles were mainly dependent on climatic factors. The relative abundance of most transcripts correlated well with temperature, particularly for genes involved in photosynthesis or winter acclimation. Gene network analysis revealed relationships between 14 co-expressed gene modules and development and adaptation to environmental stimuli. Novel Myb transcription factors were identified as candidate regulators during needle development. Our systems-based analysis provides integrated data of the seasonal regulation of maritime pine growth, opening new perspectives for understanding the complex regulatory mechanisms underlying conifers' adaptive responses. Taken together, our results suggest that the environment regulates the transcriptome for fine tuning of the metabolome during development.

 
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IPO: a tool for automated optimization of XCMS parameters

Untargeted metabolomics generates a huge amount of data. Software packages for automated data processing are crucial to successfully process these data. A variety of such software packages exist, but the outcome of data processing strongly depends on algorithm parameter settings. If they are not carefully chosen, suboptimal parameter settings can easily lead to biased results. Therefore, parameter settings also require optimization. Several parameter optimization approaches have already been proposed, but a software package for parameter optimization which is free of intricate experimental labeling steps, fast and widely applicable is still missing.
Biswapriya B Misra's insight:

Background Untargeted metabolomics generates a huge amount of data. Software packages for automated data processing are crucial to successfully process these data. A variety of such software packages exist, but the outcome of data processing strongly depends on algorithm parameter settings. If they are not carefully chosen, suboptimal parameter settings can easily lead to biased results. Therefore, parameter settings also require optimization. Several parameter optimization approaches have already been proposed, but a software package for parameter optimization which is free of intricate experimental labeling steps, fast and widely applicable is still missing. Results We implemented the software package IPO (‘Isotopologue Parameter Optimization’) which is fast and free of labeling steps, and applicable to data from different kinds of samples and data from different methods of liquid chromatography - high resolution mass spectrometry and data from different instruments. IPO optimizes XCMS peak picking parameters by using natural, stable 13C isotopic peaks to calculate a peak picking score. Retention time correction is optimized by minimizing relative retention time differences within peak groups. Grouping parameters are optimized by maximizing the number of peak groups that show one peak from each injection of a pooled sample. The different parameter settings are achieved by design of experiments, and the resulting scores are evaluated using response surface models. IPO was tested on three different data sets, each consisting of a training set and test set. IPO resulted in an increase of reliable groups (146% - 361%), a decrease of non-reliable groups (3% - 8%) and a decrease of the retention time deviation to one third. Conclusions IPO was successfully applied to data derived from liquid chromatography coupled to high resolution mass spectrometry from three studies with different sample types and different chromatographic methods and devices. We were also able to show the potential of IPO to increase the reliability of metabolomics data. The source code is implemented in R, tested on Linux and Windows and it is freely available for download at https://github.com/glibiseller/IPO. The training sets and test sets can be downloaded from https://health.joanneum.at/IPO.

 
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Solving the jigsaw puzzle of wound-healing potato cultivars: metabolite profiling and antioxidant activity of polar extracts.

Solving the jigsaw puzzle of wound-healing potato cultivars: metabolite profiling and antioxidant activity of polar extracts. | Plant Metabolomics | Scoop.it
Potato (Solanum tuberosum L.) is a worldwide food staple, but substantial waste accompanies the cultivation of this crop due to wounding of the outer skin and subsequent unfavorable healing conditions. Motivated by both economic and nutritional considerations, this metabolite profiling study aims to improve understanding of closing layer and wound periderm formation and guide the development of new methods to ensure faster and more complete healing after skin breakage. The polar metabolites of wound-healing tissues from four potato cultivars with differing patterns of tuber skin russeting (Norkotah Russet, Atlantic, Chipeta, and Yukon Gold) were analyzed at three and seven days after wounding, during suberized closing layer formation and nascent wound periderm development, respectively. The polar extracts were assessed using LC-MS and NMR spectroscopic methods, including multivariate analysis and tentative identification of 22 of the 24 biomarkers that discriminate among the cultivars at a given wound-healing time point or between developmental stages. Differences among the metabolites that could be identified from NMR- and MS-derived biomarkers highlight the strengths and limitations of each method, also demonstrating the complementarity of these approaches in terms of assembling a complete molecular picture of the tissue extracts. Both methods revealed that differences among the cultivar metabolite profiles diminish as healing proceeds during the period following wounding. The biomarkers included polyphenolic amines, flavonoid glycosides, phenolic acids and glycoalkaloids. Because wound healing is associated with oxidative stress, the free radical scavenging activities of the extracts from different cultivars were measured at each wounding time point, revealing significantly higher scavenging activity of the Yukon Gold periderm especially after 7 days of wounding.
Biswapriya B Misra's insight:

Potato (Solanum tuberosum L.) is a worldwide food staple, but substantial waste accompanies the cultivation of this crop due to wounding of the outer skin and subsequent unfavorable healing conditions. Motivated by both economic and nutritional considerations, this metabolite profiling study aims to improve understanding of closing layer and wound periderm formation and guide the development of new methods to ensure faster and more complete healing after skin breakage. The polar metabolites of wound-healing tissues from four potato cultivars with differing patterns of tuber skin russeting (Norkotah Russet, Atlantic, Chipeta, and Yukon Gold) were analyzed at three and seven days after wounding, during suberized closing layer formation and nascent wound periderm development, respectively. The polar extracts were assessed using LC-MS and NMR spectroscopic methods, including multivariate analysis and tentative identification of 22 of the 24 biomarkers that discriminate among the cultivars at a given wound-healing time point or between developmental stages. Differences among the metabolites that could be identified from NMR- and MS-derived biomarkers highlight the strengths and limitations of each method, also demonstrating the complementarity of these approaches in terms of assembling a complete molecular picture of the tissue extracts. Both methods revealed that differences among the cultivar metabolite profiles diminish as healing proceeds during the period following wounding. The biomarkers included polyphenolic amines, flavonoid glycosides, phenolic acids and glycoalkaloids. Because wound healing is associated with oxidative stress, the free radical scavenging activities of the extracts from different cultivars were measured at each wounding time point, revealing significantly higher scavenging activity of the Yukon Gold periderm especially after 7 days of wounding.

  
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Plant metabolomics: Resolution and quantification of elusive peaks in liquid chromatography–mass spectrometry profiles of complex plant extracts using multi-way decomposition methods

Plant metabolomics: Resolution and quantification of elusive peaks in liquid chromatography–mass spectrometry profiles of complex plant extracts using multi-way decomposition methods | Plant Metabolomics | Scoop.it
Previous studies on LC–MS metabolomic profiling of 127 F2 Barbarea vulgaris plants derived from a cross of parental glabrous (G) and pubescent (P) type, revealed four triterpenoid saponins (hederagenin cellobioside, oleanolic acid cellobioside, epihederagenin cellobioside, and gypsogenin cellobioside) that correlated with resistance of plants against the insect herbivore, Phyllotreta nemorum. In this study, for the first time, we demonstrate the efficiency of the multi-way decomposition method PARAllel FACtor analysis 2 (PARAFAC2) for exploring complex LC–MS data. PARAFAC2 enabled automated resolution and quantification of several elusive chromatographic peaks (e.g. overlapped, elution time shifted and low s/n ratio), which could not be detected and quantified by conventional chromatographic data analysis. Raw LC–MS data of 127 F2 B. vulgaris plants were arranged in a three-way array (elution time point × mass spectra × samples), divided into 17 different chromatographic intervals and each interval were individually modeled by PARAFAC2. Three main outputs of the PARAFAC2 models described: (1) elution time profile, (2) relative abundance, and (3) pure mass spectra of the resolved peaks modeled from each interval of the chromatographic data. PARAFAC2 scores corresponding to relative abundances of the resolved peaks were extracted and further used for correlation and partial least squares (PLS) analysis. A total of 71 PARAFAC2 components (which correspond to actual peaks, baselines and tails of neighboring peaks) were modeled from 17 different chromatographic retention time intervals of the LC–MS data. In addition to four previously known saponins, correlation- and PLS-analysis resolved five unknown saponin-like compounds that were significantly correlated with insect resistance. The method also enabled a good separation between resistant and susceptible F2 plants. PARAFAC2 spectral loadings corresponding to the pure mass spectra of chromatographic peaks matched well with experimentally recorded mass spectra (correlation based similarity >95%). This enabled to extract pure mass spectra of highly overlapped and low s/n ratio peaks.
Biswapriya B Misra's insight:

Previous studies on LC–MS metabolomic profiling of 127 F2 Barbarea vulgaris plants derived from a cross of parental glabrous (G) and pubescent (P) type, revealed four triterpenoid saponins (hederagenin cellobioside, oleanolic acid cellobioside, epihederagenin cellobioside, and gypsogenin cellobioside) that correlated with resistance of plants against the insect herbivore, Phyllotreta nemorum. In this study, for the first time, we demonstrate the efficiency of the multi-way decomposition method PARAllel FACtor analysis 2 (PARAFAC2) for exploring complex LC–MS data. PARAFAC2 enabled automated resolution and quantification of several elusive chromatographic peaks (e.g. overlapped, elution time shifted and low s/n ratio), which could not be detected and quantified by conventional chromatographic data analysis. Raw LC–MS data of 127 F2 B. vulgaris plants were arranged in a three-way array (elution time point × mass spectra × samples), divided into 17 different chromatographic intervals and each interval were individually modeled by PARAFAC2. Three main outputs of the PARAFAC2 models described: (1) elution time profile, (2) relative abundance, and (3) pure mass spectra of the resolved peaks modeled from each interval of the chromatographic data. PARAFAC2 scores corresponding to relative abundances of the resolved peaks were extracted and further used for correlation and partial least squares (PLS) analysis. A total of 71 PARAFAC2 components (which correspond to actual peaks, baselines and tails of neighboring peaks) were modeled from 17 different chromatographic retention time intervals of the LC–MS data. In addition to four previously known saponins, correlation- and PLS-analysis resolved five unknown saponin-like compounds that were significantly correlated with insect resistance. The method also enabled a good separation between resistant and susceptible F2 plants. PARAFAC2 spectral loadings corresponding to the pure mass spectra of chromatographic peaks matched well with experimentally recorded mass spectra (correlation based similarity >95%). This enabled to extract pure mass spectra of highly overlapped and low s/n ratio peaks.

 
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luis Quiros-Guerrero's curator insight, April 20, 9:47 PM

really cool work..

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Understanding developmental and adaptive cues in pine through metabolite profiling and co-expression network analysis

Understanding developmental and adaptive cues in pine through metabolite profiling and co-expression network analysis | Plant Metabolomics | Scoop.it
Conifers include long-lived evergreen trees of great economic and ecological importance, including pines and spruces. During their long lives conifers must respond to seasonal environmental changes, adapt to unpredictable environmental stresses, and co-ordinate their adaptive adjustments with internal developmental programmes. To gain insights into these responses, we examined metabolite and transcriptomic profiles of needles from naturally growing 25-year-old maritime pine (Pinus pinaster L. Aiton) trees over a year. The effect of environmental parameters such as temperature and rain on needle development were studied. Our results show that seasonal changes in the metabolite profiles were mainly affected by the needles’ age and acclimation for winter, but changes in transcript profiles were mainly dependent on climatic factors. The relative abundance of most transcripts correlated well with temperature, particularly for genes involved in photosynthesis or winter acclimation. Gene network analysis revealed relationships between 14 co-expressed gene modules and development and adaptation to environmental stimuli. Novel Myb transcription factors were identified as candidate regulators during needle development. Our systems-based analysis provides integrated data of the seasonal regulation of maritime pine growth, opening new perspectives for understanding the complex regulatory mechanisms underlying conifers’ adaptive responses. Taken together, our results suggest that the environment regulates the transcriptome for fine tuning of the metabolome during development.
Biswapriya B Misra's insight:

Conifers include long-lived evergreen trees of great economic and ecological importance, including pines and spruces. During their long lives conifers must respond to seasonal environmental changes, adapt to unpredictable environmental stresses, and co-ordinate their adaptive adjustments with internal developmental programmes. To gain insights into these responses, we examined metabolite and transcriptomic profiles of needles from naturally growing 25-year-old maritime pine (Pinus pinaster L. Aiton) trees over a year. The effect of environmental parameters such as temperature and rain on needle development were studied. Our results show that seasonal changes in the metabolite profiles were mainly affected by the needles’ age and acclimation for winter, but changes in transcript profiles were mainly dependent on climatic factors. The relative abundance of most transcripts correlated well with temperature, particularly for genes involved in photosynthesis or winter acclimation. Gene network analysis revealed relationships between 14 co-expressed gene modules and development and adaptation to environmental stimuli. Novel Myb transcription factors were identified as candidate regulators during needle development. Our systems-based analysis provides integrated data of the seasonal regulation of maritime pine growth, opening new perspectives for understanding the complex regulatory mechanisms underlying conifers’ adaptive responses. Taken together, our results suggest that the environment regulates the transcriptome for fine tuning of the metabolome during development.

 
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Untargeted UPLC-MS Profiling Pipeline to Expand Tissue Metabolome Coverage

Untargeted UPLC-MS Profiling Pipeline to Expand Tissue Metabolome Coverage | Plant Metabolomics | Scoop.it
Biswapriya B Misra's insight:

Metabolic profiling studies aim to achieve broad metabolome coverage in specific biological samples. However, wide metabolome coverage has proven difficult to achieve, mostly because of the diverse physicochemical properties of small molecules, obligating analysts to seek multiplatform and multimethod approaches. Challenges are even greater when it comes to applications to tissue samples, where tissue lysis and metabolite extraction can induce significant systematic variation in composition. We have developed a pipeline for obtaining the aqueous and organic compounds from diseased arterial tissue using two consecutive extractions, followed by a different untargeted UPLC-MS analysis method for each extract. Methods were rationally chosen and optimized to address the different physicochemical properties of each extract: hydrophilic interaction liquid chromatography (HILIC) for the aqueous extract and reversed-phase chromatography for the organic. This pipeline can be generic for tissue analysis as demonstrated by applications to different tissue types. The experimental setup and fast turnaround time of the two methods contributed toward obtaining highly reproducible features with exceptional chromatographic performance (CV % < 0.5%), making this pipeline suitable for metabolic profiling applications. We structurally assigned 226 metabolites from a range of chemical classes (e.g., carnitines, α-amino acids, purines, pyrimidines, phospholipids, sphingolipids, free fatty acids, and glycerolipids) which were mapped to their corresponding pathways, biological functions and known disease mechanisms. The combination of the two untargeted UPLC-MS methods showed high metabolite complementarity. We demonstrate the application of this pipeline to cardiovascular disease, where we show that the analyzed diseased groups (n = 120) of arterial tissue could be distinguished based on their metabolic profiles.

 
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Untargeted metabolomics investigation of volatile compounds involved in the development of apple superficial scald by PTR-ToF–MS

Untargeted metabolomics investigation of volatile compounds involved in the development of apple superficial scald by PTR-ToF–MS | Plant Metabolomics | Scoop.it
The superficial scald is an important physiological disorder affecting apple fruit during postharvest storage. To date, the accumulation, and further oxidation, of α-farnesene was considered as the most probable cause for the development of this physiopathy. In order to perform a more broad investigation, a PTR-ToF–MS (proton transfer reaction—time of flight—mass spectrometry) was employed to monitor the volatile organic compounds (VOCs) production along with the progression of this disorder in fruit of “Granny Smith”, an apple variety known to be highly susceptible to scald. The untargeted metabolite investigation was performed on both skin and pulp, as well as comparing control versus treated tissues with 1-methylcyclopropene (1-MCP), an ethylene competitor widely used to prevent the development of this phenomenon. The rapid and non-destructive analysis of the VOC array carried out by PTR-ToF–MS identified three specific groups of metabolites in the skin, among which the 6-methyl-5-hepten-2-one (MHO) resulted significantly associated with the development of the superficial scald in apple. The results proposed in this work suggest the use of this novel equipment for an on-line monitoring of the VOCs released by the apple during the postharvest storage, as well as to use MHO as a possible biochemical marker for an early detection of the superficial scald symptoms.
Biswapriya B Misra's insight:

The superficial scald is an important physiological disorder affecting apple fruit during postharvest storage. To date, the accumulation, and further oxidation, of α-farnesene was considered as the most probable cause for the development of this physiopathy. In order to perform a more broad investigation, a PTR-ToF–MS (proton transfer reaction—time of flight—mass spectrometry) was employed to monitor the volatile organic compounds (VOCs) production along with the progression of this disorder in fruit of “Granny Smith”, an apple variety known to be highly susceptible to scald. The untargeted metabolite investigation was performed on both skin and pulp, as well as comparing control versus treated tissues with 1-methylcyclopropene (1-MCP), an ethylene competitor widely used to prevent the development of this phenomenon. The rapid and non-destructive analysis of the VOC array carried out by PTR-ToF–MS identified three specific groups of metabolites in the skin, among which the 6-methyl-5-hepten-2-one (MHO) resulted significantly associated with the development of the superficial scald in apple. The results proposed in this work suggest the use of this novel equipment for an on-line monitoring of the VOCs released by the apple during the postharvest storage, as well as to use MHO as a possible biochemical marker for an early detection of the superficial scald symptoms.

 
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