The evolving landscape of cell surface pattern recognition across plant immune networks.
Identifieur interne : 000023 ( Main/Exploration ); précédent : 000022; suivant : 000024The evolving landscape of cell surface pattern recognition across plant immune networks.
Auteurs : Adam D. Steinbrenner [États-Unis]Source :
- Current opinion in plant biology [ 1879-0356 ] ; 2020.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- chemical , genetics : Receptors, Pattern Recognition.
- genetics : Plant Immunity, Plants.
- Cell Membrane, Oomycetes, Signal Transduction.
Abstract
To recognize diverse threats, plants monitor extracellular molecular patterns and transduce intracellular immune signaling through receptor complexes at the plasma membrane. Pattern recognition occurs through a prototypical network of interacting proteins, comprising A) receptors that recognize inputs associated with a growing number of pest and pathogen classes (bacteria, fungi, oomycetes, caterpillars), B) co-receptor kinases that participate in binding and signaling, and C) cytoplasmic kinases that mediate first stages of immune output. While this framework has been elucidated in reference accessions of model organisms, network components are part of gene families with widespread variation, potentially tuning immunocompetence for specific contexts. Most dramatically, variation in receptor repertoires determines the range of ligands acting as immunogenic inputs for a given plant. Diversification of receptor kinase (RK) and related receptor-like protein (RLP) repertoires may tune responses even within a species. Comparative genomics at pangenome scale will reveal patterns and features of immune network variation.
DOI: 10.1016/j.pbi.2020.05.001
PubMed: 32615401
Affiliations:
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Le document en format XML
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Steinbrenner</name><affiliation wicri:level="4"><nlm:affiliation>Department of Biology, University of Washington, Seattle WA 98195, USA; Washington Research Foundation, Seattle, WA 98102, USA. Electronic address: astein10@uw.edu.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Biology, University of Washington, Seattle WA 98195, USA; Washington Research Foundation, Seattle, WA 98102</wicri:regionArea><placeName><region type="state">Washington (État)</region><settlement type="city">Seattle</settlement></placeName><orgName type="university">Université de Washington</orgName></affiliation></author></analytic><series><title level="j">Current opinion in plant biology</title><idno type="eISSN">1879-0356</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Cell Membrane (MeSH)</term><term>Oomycetes (MeSH)</term><term>Plant Immunity (genetics)</term><term>Plants (genetics)</term><term>Receptors, Pattern Recognition (genetics)</term><term>Signal Transduction (MeSH)</term></keywords><keywords scheme="KwdFr" xml:lang="fr"><term>Immunité des plantes (génétique)</term><term>Membrane cellulaire (MeSH)</term><term>Oomycetes (MeSH)</term><term>Plantes (génétique)</term><term>Récepteurs de reconnaissance de motifs moléculaires (génétique)</term><term>Transduction du signal (MeSH)</term></keywords><keywords scheme="MESH" type="chemical" qualifier="genetics" xml:lang="en"><term>Receptors, Pattern Recognition</term></keywords><keywords scheme="MESH" qualifier="genetics" xml:lang="en"><term>Plant Immunity</term><term>Plants</term></keywords><keywords scheme="MESH" qualifier="génétique" xml:lang="fr"><term>Immunité des plantes</term><term>Plantes</term><term>Récepteurs de reconnaissance de motifs moléculaires</term></keywords><keywords scheme="MESH" xml:lang="en"><term>Cell Membrane</term><term>Oomycetes</term><term>Signal Transduction</term></keywords><keywords scheme="MESH" xml:lang="fr"><term>Membrane cellulaire</term><term>Oomycetes</term><term>Transduction du signal</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">To recognize diverse threats, plants monitor extracellular molecular patterns and transduce intracellular immune signaling through receptor complexes at the plasma membrane. Pattern recognition occurs through a prototypical network of interacting proteins, comprising A) receptors that recognize inputs associated with a growing number of pest and pathogen classes (bacteria, fungi, oomycetes, caterpillars), B) co-receptor kinases that participate in binding and signaling, and C) cytoplasmic kinases that mediate first stages of immune output. While this framework has been elucidated in reference accessions of model organisms, network components are part of gene families with widespread variation, potentially tuning immunocompetence for specific contexts. Most dramatically, variation in receptor repertoires determines the range of ligands acting as immunogenic inputs for a given plant. Diversification of receptor kinase (RK) and related receptor-like protein (RLP) repertoires may tune responses even within a species. Comparative genomics at pangenome scale will reveal patterns and features of immune network variation.</div></front></TEI><pubmed><MedlineCitation Status="MEDLINE" IndexingMethod="Automated" Owner="NLM"><PMID Version="1">32615401</PMID><DateCompleted><Year>2020</Year><Month>10</Month><Day>08</Day></DateCompleted><DateRevised><Year>2020</Year><Month>10</Month><Day>08</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1879-0356</ISSN><JournalIssue CitedMedium="Internet"><Volume>56</Volume><PubDate><Year>2020</Year><Month>08</Month></PubDate></JournalIssue><Title>Current opinion in plant biology</Title><ISOAbbreviation>Curr Opin Plant Biol</ISOAbbreviation></Journal><ArticleTitle>The evolving landscape of cell surface pattern recognition across plant immune networks.</ArticleTitle><Pagination><MedlinePgn>135-146</MedlinePgn></Pagination><ELocationID EIdType="pii" ValidYN="Y">S1369-5266(20)30053-4</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1016/j.pbi.2020.05.001</ELocationID><Abstract><AbstractText>To recognize diverse threats, plants monitor extracellular molecular patterns and transduce intracellular immune signaling through receptor complexes at the plasma membrane. Pattern recognition occurs through a prototypical network of interacting proteins, comprising A) receptors that recognize inputs associated with a growing number of pest and pathogen classes (bacteria, fungi, oomycetes, caterpillars), B) co-receptor kinases that participate in binding and signaling, and C) cytoplasmic kinases that mediate first stages of immune output. While this framework has been elucidated in reference accessions of model organisms, network components are part of gene families with widespread variation, potentially tuning immunocompetence for specific contexts. Most dramatically, variation in receptor repertoires determines the range of ligands acting as immunogenic inputs for a given plant. Diversification of receptor kinase (RK) and related receptor-like protein (RLP) repertoires may tune responses even within a species. Comparative genomics at pangenome scale will reveal patterns and features of immune network variation.</AbstractText><CopyrightInformation>Copyright © 2020 Elsevier Ltd. All rights reserved.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Steinbrenner</LastName><ForeName>Adam D</ForeName><Initials>AD</Initials><AffiliationInfo><Affiliation>Department of Biology, University of Washington, Seattle WA 98195, USA; Washington Research Foundation, Seattle, WA 98102, USA. Electronic address: astein10@uw.edu.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType><PublicationType UI="D016454">Review</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>06</Month><Day>29</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Curr Opin Plant Biol</MedlineTA><NlmUniqueID>100883395</NlmUniqueID><ISSNLinking>1369-5266</ISSNLinking></MedlineJournalInfo><ChemicalList><Chemical><RegistryNumber>0</RegistryNumber><NameOfSubstance UI="D051192">Receptors, Pattern Recognition</NameOfSubstance></Chemical></ChemicalList><CitationSubset>IM</CitationSubset><MeshHeadingList><MeshHeading><DescriptorName UI="D002462" MajorTopicYN="N">Cell Membrane</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D009868" MajorTopicYN="Y">Oomycetes</DescriptorName></MeshHeading><MeshHeading><DescriptorName UI="D057865" MajorTopicYN="N">Plant Immunity</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D010944" MajorTopicYN="Y">Plants</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D051192" MajorTopicYN="N">Receptors, Pattern Recognition</DescriptorName><QualifierName UI="Q000235" MajorTopicYN="N">genetics</QualifierName></MeshHeading><MeshHeading><DescriptorName UI="D015398" MajorTopicYN="N">Signal Transduction</DescriptorName></MeshHeading></MeshHeadingList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year><Month>12</Month><Day>02</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2020</Year><Month>04</Month><Day>30</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2020</Year><Month>05</Month><Day>04</Day></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>7</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>10</Month><Day>9</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>7</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>ppublish</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32615401</ArticleId><ArticleId IdType="pii">S1369-5266(20)30053-4</ArticleId><ArticleId IdType="doi">10.1016/j.pbi.2020.05.001</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Washington (État)</li></region><settlement><li>Seattle</li></settlement><orgName><li>Université de Washington</li></orgName></list><tree><country name="États-Unis"><region name="Washington (État)"><name sortKey="Steinbrenner, Adam D" sort="Steinbrenner, Adam D" uniqKey="Steinbrenner A" first="Adam D" last="Steinbrenner">Adam D. 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