Targeted metabolic reconstruction: a novel approach for the characterization of plant-pathogen interactions.
Identifieur interne : 001649 ( Main/Exploration ); précédent : 001648; suivant : 001650Targeted metabolic reconstruction: a novel approach for the characterization of plant-pathogen interactions.
Auteurs : Andrés Pinz N [Colombie] ; Luis M. Rodriguez-R ; Andrés González ; Adriana Bernal ; Silvia RestrepoSource :
- Briefings in bioinformatics [ 1477-4054 ] ; 2011.
Descripteurs français
- KwdFr :
- MESH :
- méthodes : Biologie informatique.
- parasitologie : Maladies des plantes, Solanum tuberosum.
- pathogénicité : Phytophthora infestans.
- Génome, Interactions hôte-parasite, Voies et réseaux métaboliques.
English descriptors
- KwdEn :
- MESH :
- methods : Computational Biology.
- parasitology : Plant Diseases, Solanum tuberosum.
- pathogenicity : Phytophthora infestans.
- Genome, Host-Parasite Interactions, Metabolic Networks and Pathways.
Abstract
Genome-scale metabolic reconstruction (GEMR), along with flux balance analysis, has been widely used to study complex metabolic networks in several microbial organisms. This approach is of particular applicability in biological systems where the lack of kinetics data is typical. This is the case of plant-pathogen interactions, where these methods open the possibility of studying host metabolic network phenotype during the interaction with pathogens. Since GEMRs are based on sequenced genomes, its applicability to organisms where genomic information is lacking is limited. Here we describe an alternative approach to GEMR: targeted metabolic reconstruction, where network reconstruction is guided by transcriptomic data instead of genomic information. This approach is being applied successfully in our laboratory for the Phytophthora infestans--Solanum tuberosum pathosystem.
DOI: 10.1093/bib/bbq009
PubMed: 20353961
Affiliations:
Links toward previous steps (curation, corpus...)
Le document en format XML
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This approach is of particular applicability in biological systems where the lack of kinetics data is typical. This is the case of plant-pathogen interactions, where these methods open the possibility of studying host metabolic network phenotype during the interaction with pathogens. Since GEMRs are based on sequenced genomes, its applicability to organisms where genomic information is lacking is limited. Here we describe an alternative approach to GEMR: targeted metabolic reconstruction, where network reconstruction is guided by transcriptomic data instead of genomic information. This approach is being applied successfully in our laboratory for the Phytophthora infestans--Solanum tuberosum pathosystem.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" Owner="NLM"><PMID Version="1">20353961</PMID><DateCompleted><Year>2011</Year><Month>07</Month><Day>22</Day></DateCompleted><DateRevised><Year>2011</Year><Month>03</Month><Day>22</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1477-4054</ISSN><JournalIssue CitedMedium="Internet"><Volume>12</Volume><Issue>2</Issue><PubDate><Year>2011</Year><Month>Mar</Month></PubDate></JournalIssue><Title>Briefings in bioinformatics</Title><ISOAbbreviation>Brief Bioinform</ISOAbbreviation></Journal><ArticleTitle>Targeted metabolic reconstruction: a novel approach for the characterization of plant-pathogen interactions.</ArticleTitle><Pagination><MedlinePgn>151-62</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1093/bib/bbq009</ELocationID><Abstract><AbstractText>Genome-scale metabolic reconstruction (GEMR), along with flux balance analysis, has been widely used to study complex metabolic networks in several microbial organisms. This approach is of particular applicability in biological systems where the lack of kinetics data is typical. This is the case of plant-pathogen interactions, where these methods open the possibility of studying host metabolic network phenotype during the interaction with pathogens. Since GEMRs are based on sequenced genomes, its applicability to organisms where genomic information is lacking is limited. Here we describe an alternative approach to GEMR: targeted metabolic reconstruction, where network reconstruction is guided by transcriptomic data instead of genomic information. 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Rodriguez-R</name></noCountry><country name="Colombie"><noRegion><name sortKey="Pinz N, Andres" sort="Pinz N, Andres" uniqKey="Pinz N A" first="Andrés" last="Pinz N">Andrés Pinz N</name></noRegion></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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