Characterization of poplar metabotypes via mass difference enrichment analysis.
Identifieur interne : 001485 ( Main/Exploration ); précédent : 001484; suivant : 001486Characterization of poplar metabotypes via mass difference enrichment analysis.
Auteurs : Franco Moritz [Allemagne] ; Moritz Kaling [Allemagne] ; Jörg-Peter Schnitzler [Allemagne] ; Philippe Schmitt-Kopplin [Allemagne]Source :
- Plant, cell & environment [ 1365-3040 ] ; 2017.
Descripteurs français
- KwdFr :
- Analyse de Fourier (MeSH), Butadiènes (métabolisme), Génotype (MeSH), Hémiterpènes (génétique), Hémiterpènes (métabolisme), Métabolome (MeSH), Métabolomique (méthodes), Pentanes (métabolisme), Phosphoénolpyruvate (métabolisme), Populus (génétique), Populus (métabolisme), Prénylation (MeSH), Reproductibilité des résultats (MeSH), Spectrométrie de masse en tandem (MeSH), Stress oxydatif (MeSH), Voies et réseaux métaboliques (MeSH).
- MESH :
- génétique : Hémiterpènes, Populus.
- métabolisme : Butadiènes, Hémiterpènes, Pentanes, Phosphoénolpyruvate, Populus.
- méthodes : Métabolomique.
- Analyse de Fourier, Génotype, Métabolome, Prénylation, Reproductibilité des résultats, Spectrométrie de masse en tandem, Stress oxydatif, Voies et réseaux métaboliques.
English descriptors
- KwdEn :
- Butadienes (metabolism), Fourier Analysis (MeSH), Genotype (MeSH), Hemiterpenes (genetics), Hemiterpenes (metabolism), Metabolic Networks and Pathways (MeSH), Metabolome (MeSH), Metabolomics (methods), Oxidative Stress (MeSH), Pentanes (metabolism), Phosphoenolpyruvate (metabolism), Populus (genetics), Populus (metabolism), Prenylation (MeSH), Reproducibility of Results (MeSH), Tandem Mass Spectrometry (MeSH).
- MESH :
- chemical , genetics : Hemiterpenes.
- chemical , metabolism : Butadienes, Hemiterpenes, Pentanes, Phosphoenolpyruvate.
- genetics : Populus.
- metabolism : Populus.
- methods : Metabolomics.
- Fourier Analysis, Genotype, Metabolic Networks and Pathways, Metabolome, Oxidative Stress, Prenylation, Reproducibility of Results, Tandem Mass Spectrometry.
Abstract
Instrumentation technology for metabolomics has advanced drastically in recent years in terms of sensitivity and specificity. Despite these technical advances, data analytical strategies are still in their infancy in comparison with other 'omics'. Plants are known to possess an immense diversity of secondary metabolites. Typically, more than 70% of metabolomics data are not amenable to systems biological interpretation because of poor database coverage. Here, we propose a new general strategy for mass-spectrometry-based metabolomics that incorporates all exact mass features with known sum formulas into the evaluation and interpretation of metabolomics studies. We extend the use of mass differences, commonly used for feature annotation, by redefining them as variables that reflect the remaining 'omic' domains. The strategy uses exact mass difference network analyses exemplified for the metabolomic description of two grey poplar (Populus × canescens) genotypes that differ in their capability to emit isoprene. This strategy established a direct connection between the metabotype and the non-isoprene-emitting phenotype, as mass differences pertaining to prenylation reactions were over-represented in non-isoprene-emitting poplars. Not only was the analysis of mass differences able to grasp the known chemical biology of poplar, but it also improved the interpretability of yet unknown biochemical relationships.
DOI: 10.1111/pce.12878
PubMed: 27943315
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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Unit Analytical BioGeoChemistry, Helmholtz Zentrum München (HMGU), Neuherberg</wicri:regionArea><wicri:noRegion>Neuherberg</wicri:noRegion><wicri:noRegion>Neuherberg</wicri:noRegion><wicri:noRegion>Neuherberg</wicri:noRegion></affiliation></author><author><name sortKey="Kaling, Moritz" sort="Kaling, Moritz" uniqKey="Kaling M" first="Moritz" last="Kaling">Moritz Kaling</name><affiliation wicri:level="1"><nlm:affiliation>Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München (HMGU), Neuherberg, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München (HMGU), Neuherberg</wicri:regionArea><wicri:noRegion>Neuherberg</wicri:noRegion><wicri:noRegion>Neuherberg</wicri:noRegion><wicri:noRegion>Neuherberg</wicri:noRegion></affiliation><affiliation wicri:level="1"><nlm:affiliation>Research Unit Environmental Simulation, Institute of Biochemical Plant Pathology, Helmholtz Zentrum München 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Neuherberg</wicri:regionArea><wicri:noRegion>Neuherberg</wicri:noRegion><wicri:noRegion>Neuherberg</wicri:noRegion><wicri:noRegion>Neuherberg</wicri:noRegion></affiliation></author><author><name sortKey="Schmitt Kopplin, Philippe" sort="Schmitt Kopplin, Philippe" uniqKey="Schmitt Kopplin P" first="Philippe" last="Schmitt-Kopplin">Philippe Schmitt-Kopplin</name><affiliation wicri:level="1"><nlm:affiliation>Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München (HMGU), Neuherberg, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München (HMGU), Neuherberg</wicri:regionArea><wicri:noRegion>Neuherberg</wicri:noRegion><wicri:noRegion>Neuherberg</wicri:noRegion><wicri:noRegion>Neuherberg</wicri:noRegion></affiliation><affiliation wicri:level="4"><nlm:affiliation>Chair of Analytical Food Chemistry, Technische Universität München (TUM), Freising, Germany.</nlm:affiliation><country xml:lang="fr">Allemagne</country><wicri:regionArea>Chair of Analytical Food Chemistry, Technische Universität München (TUM), Freising</wicri:regionArea><wicri:noRegion>Freising</wicri:noRegion><orgName type="university">Université technique de Munich</orgName><placeName><settlement type="city">Munich</settlement><region type="land" nuts="1">Bavière</region><region type="district" nuts="2">District de Haute-Bavière</region></placeName></affiliation></author></analytic><series><title level="j">Plant, cell & environment</title><idno type="eISSN">1365-3040</idno><imprint><date when="2017" type="published">2017</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Butadienes (metabolism)</term><term>Fourier Analysis (MeSH)</term><term>Genotype (MeSH)</term><term>Hemiterpenes (genetics)</term><term>Hemiterpenes (metabolism)</term><term>Metabolic Networks and Pathways (MeSH)</term><term>Metabolome (MeSH)</term><term>Metabolomics (methods)</term><term>Oxidative Stress (MeSH)</term><term>Pentanes (metabolism)</term><term>Phosphoenolpyruvate (metabolism)</term><term>Populus (genetics)</term><term>Populus (metabolism)</term><term>Prenylation (MeSH)</term><term>Reproducibility of Results (MeSH)</term><term>Tandem Mass Spectrometry (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Analyse de Fourier (MeSH)</term><term>Butadiènes (métabolisme)</term><term>Génotype (MeSH)</term><term>Hémiterpènes (génétique)</term><term>Hémiterpènes (métabolisme)</term><term>Métabolome (MeSH)</term><term>Métabolomique (méthodes)</term><term>Pentanes (métabolisme)</term><term>Phosphoénolpyruvate (métabolisme)</term><term>Populus (génétique)</term><term>Populus (métabolisme)</term><term>Prénylation (MeSH)</term><term>Reproductibilité des résultats (MeSH)</term><term>Spectrométrie de masse en tandem (MeSH)</term><term>Stress oxydatif (MeSH)</term><term>Voies et réseaux métaboliques (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Hemiterpenes</term></keywords><keywords scheme="MESH" type="chemical" qualifier="metabolism" xml:lang="en"><term>Butadienes</term><term>Hemiterpenes</term><term>Pentanes</term><term>Phosphoenolpyruvate</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Populus</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Hémiterpènes</term><term>Populus</term></keywords><keywords scheme="MESH" qualifier="metabolism" xml:lang="en"><term>Populus</term></keywords><keywords scheme="MESH" qualifier="methods" xml:lang="en"><term>Metabolomics</term></keywords><keywords scheme="MESH" qualifier="métabolisme" xml:lang="fr"><term>Butadiènes</term><term>Hémiterpènes</term><term>Pentanes</term><term>Phosphoénolpyruvate</term><term>Populus</term></keywords><keywords scheme="MESH" qualifier="méthodes" xml:lang="fr"><term>Métabolomique</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Fourier Analysis</term><term>Genotype</term><term>Metabolic Networks and Pathways</term><term>Metabolome</term><term>Oxidative Stress</term><term>Prenylation</term><term>Reproducibility of Results</term><term>Tandem Mass Spectrometry</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Analyse de Fourier</term><term>Génotype</term><term>Métabolome</term><term>Prénylation</term><term>Reproductibilité des résultats</term><term>Spectrométrie de masse en tandem</term><term>Stress oxydatif</term><term>Voies et réseaux métaboliques</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Instrumentation technology for metabolomics has advanced drastically in recent years in terms of sensitivity and specificity. Despite these technical advances, data analytical strategies are still in their infancy in comparison with other 'omics'. Plants are known to possess an immense diversity of secondary metabolites. Typically, more than 70% of metabolomics data are not amenable to systems biological interpretation because of poor database coverage. Here, we propose a new general strategy for mass-spectrometry-based metabolomics that incorporates all exact mass features with known sum formulas into the evaluation and interpretation of metabolomics studies. We extend the use of mass differences, commonly used for feature annotation, by redefining them as variables that reflect the remaining 'omic' domains. The strategy uses exact mass difference network analyses exemplified for the metabolomic description of two grey poplar (Populus × canescens) genotypes that differ in their capability to emit isoprene. This strategy established a direct connection between the metabotype and the non-isoprene-emitting phenotype, as mass differences pertaining to prenylation reactions were over-represented in non-isoprene-emitting poplars. Not only was the analysis of mass differences able to grasp the known chemical biology of poplar, but it also improved the interpretability of yet unknown biochemical relationships.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">27943315</PMID><DateCompleted><Year>2017</Year><Month>12</Month><Day>22</Day></DateCompleted><DateRevised><Year>2017</Year><Month>12</Month><Day>22</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1365-3040</ISSN><JournalIssue CitedMedium="Internet"><Volume>40</Volume><Issue>7</Issue><PubDate><Year>2017</Year><Month>Jul</Month></PubDate></JournalIssue><Title>Plant, cell & environment</Title><ISOAbbreviation>Plant Cell Environ</ISOAbbreviation></Journal><ArticleTitle>Characterization of poplar metabotypes via mass difference enrichment analysis.</ArticleTitle><Pagination><MedlinePgn>1057-1073</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1111/pce.12878</ELocationID><Abstract><AbstractText>Instrumentation technology for metabolomics has advanced drastically in recent years in terms of sensitivity and specificity. Despite these technical advances, data analytical strategies are still in their infancy in comparison with other 'omics'. Plants are known to possess an immense diversity of secondary metabolites. Typically, more than 70% of metabolomics data are not amenable to systems biological interpretation because of poor database coverage. Here, we propose a new general strategy for mass-spectrometry-based metabolomics that incorporates all exact mass features with known sum formulas into the evaluation and interpretation of metabolomics studies. We extend the use of mass differences, commonly used for feature annotation, by redefining them as variables that reflect the remaining 'omic' domains. The strategy uses exact mass difference network analyses exemplified for the metabolomic description of two grey poplar (Populus × canescens) genotypes that differ in their capability to emit isoprene. This strategy established a direct connection between the metabotype and the non-isoprene-emitting phenotype, as mass differences pertaining to prenylation reactions were over-represented in non-isoprene-emitting poplars. Not only was the analysis of mass differences able to grasp the known chemical biology of poplar, but it also improved the interpretability of yet unknown biochemical relationships.</AbstractText><CopyrightInformation>© 2016 John Wiley & Sons Ltd.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Moritz</LastName><ForeName>Franco</ForeName><Initials>F</Initials><AffiliationInfo><Affiliation>Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München (HMGU), Neuherberg, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kaling</LastName><ForeName>Moritz</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München (HMGU), Neuherberg, Germany.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Research Unit Environmental Simulation, Institute of Biochemical Plant Pathology, Helmholtz Zentrum München (HMGU), Neuherberg, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Schnitzler</LastName><ForeName>Jörg-Peter</ForeName><Initials>JP</Initials><Identifier Source="ORCID">http://orcid.org/0000-0002-9825-867X</Identifier><AffiliationInfo><Affiliation>Research Unit Environmental Simulation, Institute of Biochemical Plant Pathology, Helmholtz Zentrum München (HMGU), Neuherberg, Germany.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Schmitt-Kopplin</LastName><ForeName>Philippe</ForeName><Initials>P</Initials><AffiliationInfo><Affiliation>Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München (HMGU), Neuherberg, Germany.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Chair of Analytical Food Chemistry, Technische Universität München (TUM), Freising, Germany.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2017</Year><Month>04</Month><Day>06</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Plant Cell Environ</MedlineTA><NlmUniqueID>9309004</NlmUniqueID><ISSNLinking>0140-7791</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D002070">Butadienes</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D045782">Hemiterpenes</NameOfSubstance></Chemical><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D010420">Pentanes</NameOfSubstance></Chemical><Chemical><RegistryNumber>0A62964IBU</RegistryNumber><NameOfSubstance UI="C005059">isoprene</NameOfSubstance></Chemical><Chemical><RegistryNumber>73-89-2</RegistryNumber><NameOfSubstance UI="D010728">Phosphoenolpyruvate</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D002070" MajorTopicYN="N">Butadienes</DescriptorName><QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D005583" MajorTopicYN="N">Fourier Analysis</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D005838" MajorTopicYN="N">Genotype</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D045782" MajorTopicYN="N">Hemiterpenes</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D053858" MajorTopicYN="N">Metabolic Networks and Pathways</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D055442" MajorTopicYN="N">Metabolome</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D055432" MajorTopicYN="N">Metabolomics</DescriptorName><QualifierName UI="Q000379" MajorTopicYN="Y">methods</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D018384" MajorTopicYN="N">Oxidative Stress</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D010420" MajorTopicYN="N">Pentanes</DescriptorName><QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D010728" MajorTopicYN="N">Phosphoenolpyruvate</DescriptorName><QualifierName UI="Q000378" MajorTopicYN="N">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D032107" MajorTopicYN="N">Populus</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName><QualifierName UI="Q000378" MajorTopicYN="Y">metabolism</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D054876" MajorTopicYN="N">Prenylation</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D015203" MajorTopicYN="N">Reproducibility of Results</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D053719" MajorTopicYN="N">Tandem Mass Spectrometry</DescriptorName></MeshHeading></MeshHeadingList><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Populus × canescens</Keyword><Keyword MajorTopicYN="N">mass difference analysis</Keyword><Keyword MajorTopicYN="N">metabolomics</Keyword><Keyword MajorTopicYN="N">networks</Keyword><Keyword MajorTopicYN="N">systems chemical biology</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2016</Year><Month>08</Month><Day>08</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2016</Year><Month>11</Month><Day>29</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2016</Year><Month>12</Month><Day>01</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2016</Year><Month>12</Month><Day>13</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2017</Year><Month>12</Month><Day>23</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2016</Year><Month>12</Month><Day>13</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">27943315</ArticleId><ArticleId IdType="doi">10.1111/pce.12878</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Allemagne</li></country><region><li>Bavière</li><li>District de Haute-Bavière</li></region><settlement><li>Munich</li></settlement><orgName><li>Université technique de Munich</li></orgName></list><tree><country name="Allemagne"><noRegion><name sortKey="Moritz, Franco" sort="Moritz, Franco" uniqKey="Moritz F" first="Franco" last="Moritz">Franco Moritz</name></noRegion><name sortKey="Kaling, Moritz" sort="Kaling, Moritz" uniqKey="Kaling M" first="Moritz" last="Kaling">Moritz Kaling</name><name sortKey="Kaling, Moritz" sort="Kaling, Moritz" uniqKey="Kaling M" first="Moritz" last="Kaling">Moritz Kaling</name><name sortKey="Schmitt Kopplin, Philippe" sort="Schmitt Kopplin, Philippe" uniqKey="Schmitt Kopplin P" first="Philippe" last="Schmitt-Kopplin">Philippe Schmitt-Kopplin</name><name sortKey="Schmitt Kopplin, Philippe" sort="Schmitt Kopplin, Philippe" uniqKey="Schmitt Kopplin P" first="Philippe" last="Schmitt-Kopplin">Philippe Schmitt-Kopplin</name><name sortKey="Schnitzler, Jorg Peter" sort="Schnitzler, Jorg Peter" uniqKey="Schnitzler J" first="Jörg-Peter" last="Schnitzler">Jörg-Peter Schnitzler</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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