Predicting plant immunity gene expression by identifying the decoding mechanism of calcium signatures

Calcium plays a key role in determining the specificity of a vast array of signalling pathways in plants. Cellular calcium elevations with different characteristics (calcium signatures) carry information on the identity of the primary stimulus, ensuring appropriate downstream responses. However, the...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:The New phytologist 2018-03, Vol.217 (4), p.1598-1609
Hauptverfasser: Lenzoni, Gioia, Liu, Junli, Knight, Marc R.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 1609
container_issue 4
container_start_page 1598
container_title The New phytologist
container_volume 217
creator Lenzoni, Gioia
Liu, Junli
Knight, Marc R.
description Calcium plays a key role in determining the specificity of a vast array of signalling pathways in plants. Cellular calcium elevations with different characteristics (calcium signatures) carry information on the identity of the primary stimulus, ensuring appropriate downstream responses. However, the mechanism for decoding calcium signatures is unknown. To determine this, decoding of the salicylic acid (SA)-mediated plant immunity signalling network controlling gene expression was examined. A dynamic mathematical model of the SA-mediated plant immunity network was developed. This model was used to predict responses to different calcium signatures; these were validated empirically using quantitative real-time PCR to measure gene expression. The mechanism for decoding calcium signatures to control expression of plant immunity genes enhanced disease susceptibility 1 (EDS1) and isochorismate synthase 1 (ICS1) was identified. Calcium, calmodulin, calmodulin-binding transcription activators (CAMTA)3 and calmodulin binding protein 60g (CBP60g) together amplify each calcium signature into three active signals, simultaneously regulating expression. The time required for calcium to return to steady-state level also quantitatively regulates gene expression. Decoding of calcium signatures occurs via nonlinear interactions between these active signals, producing a unique response in each case. Key properties of the calcium signatures are not intuitive, exemplifying the importance of mathematical modelling approaches. This approach can be applied to identifying the decoding mechanisms of other plant calcium signalling pathways.
doi_str_mv 10.1111/nph.14924
format Article
fullrecord <record><control><sourceid>jstor_proqu</sourceid><recordid>TN_cdi_proquest_miscellaneous_1975021473</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><jstor_id>90018939</jstor_id><sourcerecordid>90018939</sourcerecordid><originalsourceid>FETCH-LOGICAL-c4764-66960dd5af277f17e1474299a8a465a9a354b902ba5be3717f494555560a49a23</originalsourceid><addsrcrecordid>eNp1kE1P3DAQhq2qCLaUQ39AK0tc2kPAX7Ezxwq1pRICDkXiFjnJZNerxEntRCX_vl4WOCAxF2uk5300fgn5xNkZT3Pux80ZVyDUO7LiSkNWcGnekxVjosi00vdH5EOMW8YY5FockiMBgheGwYrgbcDG1ZPzazp21k_U9f3s3bTQNXqk-DAGjNENnlYLdQ36ybXLjp42SBush2a39FhvrHexp0NLa9vVbu5pdGtvpznlP5KD1nYRT57eY3L388efi8vs6ubX74vvV1mtjFaZ1qBZ0-S2Fca03CBXRgkAW1ilcwtW5qoCJiqbVygNN60ClafRzCqwQh6Tr3vvGIa_M8ap7F2ssUsfw2GOJQeTM5GsMqGnr9DtMAefrksUKCllYXSivu2pOgwxBmzLMbjehqXkrNx1X6buy8fuE_vlyThXPTYv5HPZCTjfA_9ch8vbpvL69vJZ-Xmf2MZpCC8JYIwXIEH-BwkYlz0</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1994333876</pqid></control><display><type>article</type><title>Predicting plant immunity gene expression by identifying the decoding mechanism of calcium signatures</title><source>Free E-Journal (出版社公開部分のみ)</source><source>Wiley Online Library Free Content</source><source>Wiley Online Library All Journals</source><source>JSTOR</source><creator>Lenzoni, Gioia ; Liu, Junli ; Knight, Marc R.</creator><creatorcontrib>Lenzoni, Gioia ; Liu, Junli ; Knight, Marc R.</creatorcontrib><description>Calcium plays a key role in determining the specificity of a vast array of signalling pathways in plants. Cellular calcium elevations with different characteristics (calcium signatures) carry information on the identity of the primary stimulus, ensuring appropriate downstream responses. However, the mechanism for decoding calcium signatures is unknown. To determine this, decoding of the salicylic acid (SA)-mediated plant immunity signalling network controlling gene expression was examined. A dynamic mathematical model of the SA-mediated plant immunity network was developed. This model was used to predict responses to different calcium signatures; these were validated empirically using quantitative real-time PCR to measure gene expression. The mechanism for decoding calcium signatures to control expression of plant immunity genes enhanced disease susceptibility 1 (EDS1) and isochorismate synthase 1 (ICS1) was identified. Calcium, calmodulin, calmodulin-binding transcription activators (CAMTA)3 and calmodulin binding protein 60g (CBP60g) together amplify each calcium signature into three active signals, simultaneously regulating expression. The time required for calcium to return to steady-state level also quantitatively regulates gene expression. Decoding of calcium signatures occurs via nonlinear interactions between these active signals, producing a unique response in each case. Key properties of the calcium signatures are not intuitive, exemplifying the importance of mathematical modelling approaches. This approach can be applied to identifying the decoding mechanisms of other plant calcium signalling pathways.</description><identifier>ISSN: 0028-646X</identifier><identifier>EISSN: 1469-8137</identifier><identifier>DOI: 10.1111/nph.14924</identifier><identifier>PMID: 29218709</identifier><language>eng</language><publisher>England: New Phytologist Trust</publisher><subject>Calcium ; Calcium signalling ; Calcium-binding protein ; Calmodulin ; Decoding ; Disease control ; Disease resistance ; DNA ; Gene expression ; Immunity ; Interactions ; Isochorismate synthase ; Mathematical analysis ; Mathematical models ; Modelling ; Nucleotide sequence ; PCR ; Plant diseases ; Plant immunity ; Proteins ; Salicylic acid ; Signal transduction ; Signatures ; Specificity ; Transcription ; Transcription factors</subject><ispartof>The New phytologist, 2018-03, Vol.217 (4), p.1598-1609</ispartof><rights>Copyright © 2018 New Phytologist Trust</rights><rights>2017 The Authors. New Phytologist © 2017 New Phytologist Trust</rights><rights>2017 The Authors. New Phytologist © 2017 New Phytologist Trust.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4764-66960dd5af277f17e1474299a8a465a9a354b902ba5be3717f494555560a49a23</citedby><cites>FETCH-LOGICAL-c4764-66960dd5af277f17e1474299a8a465a9a354b902ba5be3717f494555560a49a23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.jstor.org/stable/pdf/90018939$$EPDF$$P50$$Gjstor$$H</linktopdf><linktohtml>$$Uhttps://www.jstor.org/stable/90018939$$EHTML$$P50$$Gjstor$$H</linktohtml><link.rule.ids>314,780,784,803,1416,1432,27922,27923,45572,45573,46407,46831,58015,58248</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29218709$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Lenzoni, Gioia</creatorcontrib><creatorcontrib>Liu, Junli</creatorcontrib><creatorcontrib>Knight, Marc R.</creatorcontrib><title>Predicting plant immunity gene expression by identifying the decoding mechanism of calcium signatures</title><title>The New phytologist</title><addtitle>New Phytol</addtitle><description>Calcium plays a key role in determining the specificity of a vast array of signalling pathways in plants. Cellular calcium elevations with different characteristics (calcium signatures) carry information on the identity of the primary stimulus, ensuring appropriate downstream responses. However, the mechanism for decoding calcium signatures is unknown. To determine this, decoding of the salicylic acid (SA)-mediated plant immunity signalling network controlling gene expression was examined. A dynamic mathematical model of the SA-mediated plant immunity network was developed. This model was used to predict responses to different calcium signatures; these were validated empirically using quantitative real-time PCR to measure gene expression. The mechanism for decoding calcium signatures to control expression of plant immunity genes enhanced disease susceptibility 1 (EDS1) and isochorismate synthase 1 (ICS1) was identified. Calcium, calmodulin, calmodulin-binding transcription activators (CAMTA)3 and calmodulin binding protein 60g (CBP60g) together amplify each calcium signature into three active signals, simultaneously regulating expression. The time required for calcium to return to steady-state level also quantitatively regulates gene expression. Decoding of calcium signatures occurs via nonlinear interactions between these active signals, producing a unique response in each case. Key properties of the calcium signatures are not intuitive, exemplifying the importance of mathematical modelling approaches. This approach can be applied to identifying the decoding mechanisms of other plant calcium signalling pathways.</description><subject>Calcium</subject><subject>Calcium signalling</subject><subject>Calcium-binding protein</subject><subject>Calmodulin</subject><subject>Decoding</subject><subject>Disease control</subject><subject>Disease resistance</subject><subject>DNA</subject><subject>Gene expression</subject><subject>Immunity</subject><subject>Interactions</subject><subject>Isochorismate synthase</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Modelling</subject><subject>Nucleotide sequence</subject><subject>PCR</subject><subject>Plant diseases</subject><subject>Plant immunity</subject><subject>Proteins</subject><subject>Salicylic acid</subject><subject>Signal transduction</subject><subject>Signatures</subject><subject>Specificity</subject><subject>Transcription</subject><subject>Transcription factors</subject><issn>0028-646X</issn><issn>1469-8137</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp1kE1P3DAQhq2qCLaUQ39AK0tc2kPAX7Ezxwq1pRICDkXiFjnJZNerxEntRCX_vl4WOCAxF2uk5300fgn5xNkZT3Pux80ZVyDUO7LiSkNWcGnekxVjosi00vdH5EOMW8YY5FockiMBgheGwYrgbcDG1ZPzazp21k_U9f3s3bTQNXqk-DAGjNENnlYLdQ36ybXLjp42SBush2a39FhvrHexp0NLa9vVbu5pdGtvpznlP5KD1nYRT57eY3L388efi8vs6ubX74vvV1mtjFaZ1qBZ0-S2Fca03CBXRgkAW1ilcwtW5qoCJiqbVygNN60ClafRzCqwQh6Tr3vvGIa_M8ap7F2ssUsfw2GOJQeTM5GsMqGnr9DtMAefrksUKCllYXSivu2pOgwxBmzLMbjehqXkrNx1X6buy8fuE_vlyThXPTYv5HPZCTjfA_9ch8vbpvL69vJZ-Xmf2MZpCC8JYIwXIEH-BwkYlz0</recordid><startdate>201803</startdate><enddate>201803</enddate><creator>Lenzoni, Gioia</creator><creator>Liu, Junli</creator><creator>Knight, Marc R.</creator><general>New Phytologist Trust</general><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>7SN</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H95</scope><scope>L.G</scope><scope>M7N</scope><scope>P64</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>201803</creationdate><title>Predicting plant immunity gene expression by identifying the decoding mechanism of calcium signatures</title><author>Lenzoni, Gioia ; Liu, Junli ; Knight, Marc R.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4764-66960dd5af277f17e1474299a8a465a9a354b902ba5be3717f494555560a49a23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Calcium</topic><topic>Calcium signalling</topic><topic>Calcium-binding protein</topic><topic>Calmodulin</topic><topic>Decoding</topic><topic>Disease control</topic><topic>Disease resistance</topic><topic>DNA</topic><topic>Gene expression</topic><topic>Immunity</topic><topic>Interactions</topic><topic>Isochorismate synthase</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Modelling</topic><topic>Nucleotide sequence</topic><topic>PCR</topic><topic>Plant diseases</topic><topic>Plant immunity</topic><topic>Proteins</topic><topic>Salicylic acid</topic><topic>Signal transduction</topic><topic>Signatures</topic><topic>Specificity</topic><topic>Transcription</topic><topic>Transcription factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Lenzoni, Gioia</creatorcontrib><creatorcontrib>Liu, Junli</creatorcontrib><creatorcontrib>Knight, Marc R.</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Ecology Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) 1: Biological Sciences &amp; Living Resources</collection><collection>Aquatic Science &amp; Fisheries Abstracts (ASFA) Professional</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>The New phytologist</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Lenzoni, Gioia</au><au>Liu, Junli</au><au>Knight, Marc R.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Predicting plant immunity gene expression by identifying the decoding mechanism of calcium signatures</atitle><jtitle>The New phytologist</jtitle><addtitle>New Phytol</addtitle><date>2018-03</date><risdate>2018</risdate><volume>217</volume><issue>4</issue><spage>1598</spage><epage>1609</epage><pages>1598-1609</pages><issn>0028-646X</issn><eissn>1469-8137</eissn><abstract>Calcium plays a key role in determining the specificity of a vast array of signalling pathways in plants. Cellular calcium elevations with different characteristics (calcium signatures) carry information on the identity of the primary stimulus, ensuring appropriate downstream responses. However, the mechanism for decoding calcium signatures is unknown. To determine this, decoding of the salicylic acid (SA)-mediated plant immunity signalling network controlling gene expression was examined. A dynamic mathematical model of the SA-mediated plant immunity network was developed. This model was used to predict responses to different calcium signatures; these were validated empirically using quantitative real-time PCR to measure gene expression. The mechanism for decoding calcium signatures to control expression of plant immunity genes enhanced disease susceptibility 1 (EDS1) and isochorismate synthase 1 (ICS1) was identified. Calcium, calmodulin, calmodulin-binding transcription activators (CAMTA)3 and calmodulin binding protein 60g (CBP60g) together amplify each calcium signature into three active signals, simultaneously regulating expression. The time required for calcium to return to steady-state level also quantitatively regulates gene expression. Decoding of calcium signatures occurs via nonlinear interactions between these active signals, producing a unique response in each case. Key properties of the calcium signatures are not intuitive, exemplifying the importance of mathematical modelling approaches. This approach can be applied to identifying the decoding mechanisms of other plant calcium signalling pathways.</abstract><cop>England</cop><pub>New Phytologist Trust</pub><pmid>29218709</pmid><doi>10.1111/nph.14924</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0028-646X
ispartof The New phytologist, 2018-03, Vol.217 (4), p.1598-1609
issn 0028-646X
1469-8137
language eng
recordid cdi_proquest_miscellaneous_1975021473
source Free E-Journal (出版社公開部分のみ); Wiley Online Library Free Content; Wiley Online Library All Journals; JSTOR
subjects Calcium
Calcium signalling
Calcium-binding protein
Calmodulin
Decoding
Disease control
Disease resistance
DNA
Gene expression
Immunity
Interactions
Isochorismate synthase
Mathematical analysis
Mathematical models
Modelling
Nucleotide sequence
PCR
Plant diseases
Plant immunity
Proteins
Salicylic acid
Signal transduction
Signatures
Specificity
Transcription
Transcription factors
title Predicting plant immunity gene expression by identifying the decoding mechanism of calcium signatures
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-14T15%3A21%3A03IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-jstor_proqu&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Predicting%20plant%20immunity%20gene%20expression%20by%20identifying%20the%20decoding%20mechanism%20of%20calcium%20signatures&rft.jtitle=The%20New%20phytologist&rft.au=Lenzoni,%20Gioia&rft.date=2018-03&rft.volume=217&rft.issue=4&rft.spage=1598&rft.epage=1609&rft.pages=1598-1609&rft.issn=0028-646X&rft.eissn=1469-8137&rft_id=info:doi/10.1111/nph.14924&rft_dat=%3Cjstor_proqu%3E90018939%3C/jstor_proqu%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1994333876&rft_id=info:pmid/29218709&rft_jstor_id=90018939&rfr_iscdi=true