LRRpredictor-A New LRR Motif Detection Method for Irregular Motifs of Plant NLR Proteins Using an Ensemble of Classifiers.
Identifieur interne : 000124 ( Main/Exploration ); précédent : 000123; suivant : 000125LRRpredictor-A New LRR Motif Detection Method for Irregular Motifs of Plant NLR Proteins Using an Ensemble of Classifiers.
Auteurs : Eliza C. Martin [Roumanie] ; Octavina C A. Sukarta [Pays-Bas] ; Laurentiu Spiridon [Roumanie] ; Laurentiu G. Grigore [Roumanie] ; Vlad Constantinescu [Roumanie] ; Robi Tacutu [Roumanie] ; Aska Goverse [Pays-Bas] ; Andrei-Jose Petrescu [Roumanie]Source :
- Genes [ 2073-4425 ] ; 2020.
Abstract
Leucine-rich-repeats (LRRs) belong to an archaic procaryal protein architecture that is widely involved in protein-protein interactions. In eukaryotes, LRR domains developed into key recognition modules in many innate immune receptor classes. Due to the high sequence variability imposed by recognition specificity, precise repeat delineation is often difficult especially in plant NOD-like Receptors (NLRs) notorious for showing far larger irregularities. To address this problem, we introduce here LRRpredictor, a method based on an ensemble of estimators designed to better identify LRR motifs in general but particularly adapted for handling more irregular LRR environments, thus allowing to compensate for the scarcity of structural data on NLR proteins. The extrapolation capacity tested on a set of annotated LRR domains from six immune receptor classes shows the ability of LRRpredictor to recover all previously defined specific motif consensuses and to extend the LRR motif coverage over annotated LRR domains. This analysis confirms the increased variability of LRR motifs in plant and vertebrate NLRs when compared to extracellular receptors, consistent with previous studies. Hence, LRRpredictor is able to provide novel insights into the diversification of LRR domains and a robust support for structure-informed analyses of LRRs in immune receptor functioning.
DOI: 10.3390/genes11030286
PubMed: 32182725
PubMed Central: PMC7140858
Affiliations:
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Martin</name><affiliation wicri:level="1"><nlm:affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</nlm:affiliation><country xml:lang="fr">Roumanie</country><wicri:regionArea>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest</wicri:regionArea><wicri:noRegion>060031 Bucharest</wicri:noRegion></affiliation></author><author><name sortKey="Sukarta, Octavina C A" sort="Sukarta, Octavina C A" uniqKey="Sukarta O" first="Octavina C A" last="Sukarta">Octavina C A. Sukarta</name><affiliation wicri:level="1"><nlm:affiliation>Laboratory of Nematology, Wageningen University and Research, 6700ES Wageningen, The Netherlands.</nlm:affiliation><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Laboratory of Nematology, Wageningen University and Research, 6700ES Wageningen</wicri:regionArea><wicri:noRegion>6700ES Wageningen</wicri:noRegion></affiliation></author><author><name sortKey="Spiridon, Laurentiu" sort="Spiridon, Laurentiu" uniqKey="Spiridon L" first="Laurentiu" last="Spiridon">Laurentiu Spiridon</name><affiliation wicri:level="1"><nlm:affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</nlm:affiliation><country xml:lang="fr">Roumanie</country><wicri:regionArea>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest</wicri:regionArea><wicri:noRegion>060031 Bucharest</wicri:noRegion></affiliation></author><author><name sortKey="Grigore, Laurentiu G" sort="Grigore, Laurentiu G" uniqKey="Grigore L" first="Laurentiu G" last="Grigore">Laurentiu G. Grigore</name><affiliation wicri:level="1"><nlm:affiliation>Space Comp SRL, 041512 Bucharest, Romania.</nlm:affiliation><country xml:lang="fr">Roumanie</country><wicri:regionArea>Space Comp SRL, 041512 Bucharest</wicri:regionArea><wicri:noRegion>041512 Bucharest</wicri:noRegion></affiliation></author><author><name sortKey="Constantinescu, Vlad" sort="Constantinescu, Vlad" uniqKey="Constantinescu V" first="Vlad" last="Constantinescu">Vlad Constantinescu</name><affiliation wicri:level="1"><nlm:affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</nlm:affiliation><country xml:lang="fr">Roumanie</country><wicri:regionArea>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest</wicri:regionArea><wicri:noRegion>060031 Bucharest</wicri:noRegion></affiliation></author><author><name sortKey="Tacutu, Robi" sort="Tacutu, Robi" uniqKey="Tacutu R" first="Robi" last="Tacutu">Robi Tacutu</name><affiliation wicri:level="1"><nlm:affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</nlm:affiliation><country xml:lang="fr">Roumanie</country><wicri:regionArea>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest</wicri:regionArea><wicri:noRegion>060031 Bucharest</wicri:noRegion></affiliation></author><author><name sortKey="Goverse, Aska" sort="Goverse, Aska" uniqKey="Goverse A" first="Aska" last="Goverse">Aska Goverse</name><affiliation wicri:level="1"><nlm:affiliation>Laboratory of Nematology, Wageningen University and Research, 6700ES Wageningen, The Netherlands.</nlm:affiliation><country xml:lang="fr">Pays-Bas</country><wicri:regionArea>Laboratory of Nematology, Wageningen University and Research, 6700ES Wageningen</wicri:regionArea><wicri:noRegion>6700ES Wageningen</wicri:noRegion></affiliation></author><author><name sortKey="Petrescu, Andrei Jose" sort="Petrescu, Andrei Jose" uniqKey="Petrescu A" first="Andrei-Jose" last="Petrescu">Andrei-Jose Petrescu</name><affiliation wicri:level="1"><nlm:affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</nlm:affiliation><country xml:lang="fr">Roumanie</country><wicri:regionArea>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest</wicri:regionArea><wicri:noRegion>060031 Bucharest</wicri:noRegion></affiliation></author></analytic><series><title level="j">Genes</title><idno type="eISSN">2073-4425</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Leucine-rich-repeats (LRRs) belong to an archaic procaryal protein architecture that is widely involved in protein-protein interactions. In eukaryotes, LRR domains developed into key recognition modules in many innate immune receptor classes. Due to the high sequence variability imposed by recognition specificity, precise repeat delineation is often difficult especially in plant NOD-like Receptors (NLRs) notorious for showing far larger irregularities. To address this problem, we introduce here LRRpredictor, a method based on an ensemble of estimators designed to better identify LRR motifs in general but particularly adapted for handling more irregular LRR environments, thus allowing to compensate for the scarcity of structural data on NLR proteins. The extrapolation capacity tested on a set of annotated LRR domains from six immune receptor classes shows the ability of LRRpredictor to recover all previously defined specific motif consensuses and to extend the LRR motif coverage over annotated LRR domains. This analysis confirms the increased variability of LRR motifs in plant and vertebrate NLRs when compared to extracellular receptors, consistent with previous studies. Hence, LRRpredictor is able to provide novel insights into the diversification of LRR domains and a robust support for structure-informed analyses of LRRs in immune receptor functioning.</div></front></TEI><pubmed><MedlineCitation Status="In-Process" Owner="NLM"><PMID Version="1">32182725</PMID><DateRevised><Year>2020</Year><Month>06</Month><Day>23</Day></DateRevised><Article PubModel="Electronic"><Journal><ISSN IssnType="Electronic">2073-4425</ISSN><JournalIssue CitedMedium="Internet"><Volume>11</Volume><Issue>3</Issue><PubDate><Year>2020</Year><Month>03</Month><Day>08</Day></PubDate></JournalIssue><Title>Genes</Title><ISOAbbreviation>Genes (Basel)</ISOAbbreviation></Journal><ArticleTitle>LRRpredictor-A New LRR Motif Detection Method for Irregular Motifs of Plant NLR Proteins Using an Ensemble of Classifiers.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">E286</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.3390/genes11030286</ELocationID><Abstract><AbstractText>Leucine-rich-repeats (LRRs) belong to an archaic procaryal protein architecture that is widely involved in protein-protein interactions. In eukaryotes, LRR domains developed into key recognition modules in many innate immune receptor classes. Due to the high sequence variability imposed by recognition specificity, precise repeat delineation is often difficult especially in plant NOD-like Receptors (NLRs) notorious for showing far larger irregularities. To address this problem, we introduce here LRRpredictor, a method based on an ensemble of estimators designed to better identify LRR motifs in general but particularly adapted for handling more irregular LRR environments, thus allowing to compensate for the scarcity of structural data on NLR proteins. The extrapolation capacity tested on a set of annotated LRR domains from six immune receptor classes shows the ability of LRRpredictor to recover all previously defined specific motif consensuses and to extend the LRR motif coverage over annotated LRR domains. This analysis confirms the increased variability of LRR motifs in plant and vertebrate NLRs when compared to extracellular receptors, consistent with previous studies. Hence, LRRpredictor is able to provide novel insights into the diversification of LRR domains and a robust support for structure-informed analyses of LRRs in immune receptor functioning.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Martin</LastName><ForeName>Eliza C</ForeName><Initials>EC</Initials><AffiliationInfo><Affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Sukarta</LastName><ForeName>Octavina C A</ForeName><Initials>OCA</Initials><AffiliationInfo><Affiliation>Laboratory of Nematology, Wageningen University and Research, 6700ES Wageningen, The Netherlands.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Spiridon</LastName><ForeName>Laurentiu</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Grigore</LastName><ForeName>Laurentiu G</ForeName><Initials>LG</Initials><AffiliationInfo><Affiliation>Space Comp SRL, 041512 Bucharest, Romania.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Constantinescu</LastName><ForeName>Vlad</ForeName><Initials>V</Initials><AffiliationInfo><Affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Tacutu</LastName><ForeName>Robi</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Goverse</LastName><ForeName>Aska</ForeName><Initials>A</Initials><Identifier Source="ORCID">0000-0002-7399-8743</Identifier><AffiliationInfo><Affiliation>Laboratory of Nematology, Wageningen University and Research, 6700ES Wageningen, The Netherlands.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Petrescu</LastName><ForeName>Andrei-Jose</ForeName><Initials>AJ</Initials><AffiliationInfo><Affiliation>Department of Bioinformatics and Structural Biochemistry, Institute of Biochemistry of the Romanian Academy, Splaiul Independentei 296, 060031 Bucharest, Romania.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><GrantList CompleteYN="Y"><Grant><GrantID>1</GrantID><Acronym>CX</Acronym><Agency>CSRD VA</Agency><Country>United States</Country></Grant></GrantList><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType><PublicationType UI="D013485">Research Support, Non-U.S. Gov't</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>03</Month><Day>08</Day></ArticleDate></Article><MedlineJournalInfo><Country>Switzerland</Country><MedlineTA>Genes (Basel)</MedlineTA><NlmUniqueID>101551097</NlmUniqueID><ISSNLinking>2073-4425</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="Y">LRR motif</Keyword><Keyword MajorTopicYN="Y">LRR structure</Keyword><Keyword MajorTopicYN="Y">NOD-like receptors</Keyword><Keyword MajorTopicYN="Y">R proteins</Keyword><Keyword MajorTopicYN="Y">leucine-rich repeat prediction</Keyword><Keyword MajorTopicYN="Y">supervised learning</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2020</Year><Month>02</Month><Day>07</Day></PubMedPubDate><PubMedPubDate 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Martin</name></noRegion><name sortKey="Constantinescu, Vlad" sort="Constantinescu, Vlad" uniqKey="Constantinescu V" first="Vlad" last="Constantinescu">Vlad Constantinescu</name><name sortKey="Grigore, Laurentiu G" sort="Grigore, Laurentiu G" uniqKey="Grigore L" first="Laurentiu G" last="Grigore">Laurentiu G. Grigore</name><name sortKey="Petrescu, Andrei Jose" sort="Petrescu, Andrei Jose" uniqKey="Petrescu A" first="Andrei-Jose" last="Petrescu">Andrei-Jose Petrescu</name><name sortKey="Spiridon, Laurentiu" sort="Spiridon, Laurentiu" uniqKey="Spiridon L" first="Laurentiu" last="Spiridon">Laurentiu Spiridon</name><name sortKey="Tacutu, Robi" sort="Tacutu, Robi" uniqKey="Tacutu R" first="Robi" last="Tacutu">Robi Tacutu</name></country><country name="Pays-Bas"><noRegion><name sortKey="Sukarta, Octavina C A" sort="Sukarta, Octavina C A" uniqKey="Sukarta O" first="Octavina C A" last="Sukarta">Octavina C A. Sukarta</name></noRegion><name sortKey="Goverse, Aska" sort="Goverse, Aska" uniqKey="Goverse A" first="Aska" last="Goverse">Aska Goverse</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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