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Proteome-wide Prediction of Lysine Methylation Leads to Identification of H2BK43 Methylation and Outlines the Potential Methyllysine Proteome
Protein Lys methylation plays a critical role in numerous cellular processes, but it is challenging to identify Lys methylation in a systematic manner. Here we present an approach combining in silico prediction with targeted mass spectrometry (MS) to identify Lys methylation (Kme) sites at the prote...
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Published in: | Cell reports (Cambridge) 2020-07, Vol.32 (2), p.107896-107896, Article 107896 |
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creator | Biggar, Kyle K. Charih, Francois Liu, Huadong Ruiz-Blanco, Yasser B. Stalker, Leanne Chopra, Anand Connolly, Justin Adhikary, Hemanta Frensemier, Kristin Hoekstra, Matthew Galka, Marek Fang, Qi Wynder, Christopher Stanford, William L. Green, James R. Li, Shawn S.-C. |
description | Protein Lys methylation plays a critical role in numerous cellular processes, but it is challenging to identify Lys methylation in a systematic manner. Here we present an approach combining in silico prediction with targeted mass spectrometry (MS) to identify Lys methylation (Kme) sites at the proteome level. We develop MethylSight, a program that predicts Kme events solely on the physicochemical properties of residues surrounding the putative methylation sites, which then requires validation by targeted MS. Using this approach, we identify 70 new histone Kme marks with a 90% validation rate. H2BK43me2, which undergoes dynamic changes during stem cell differentiation, is found to be a substrate of KDM5b. Furthermore, MethylSight predicts that Lys methylation is a prevalent post-translational modification in the human proteome. Our work provides a useful resource for guiding systematic exploration of the role of Lys methylation in human health and disease.
[Display omitted]
•MethylSight is used to identify candidate methylation sites in the human proteome•45 histone methylation sites are uncovered by MethylSight and validated•The H2B-K43 methylation site is demethylated by KDM5B
Biggar et al. develop an algorithm to identify lysine methylation sites and use this resource to provide insight into the potential of the methyllysine proteome. The results also validate 45 new histone methylation sites by targeted mass spectrometry and show that one of these sites, H2B-K43me2, is a substrate of the KDM5B demethylase. |
doi_str_mv | 10.1016/j.celrep.2020.107896 |
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[Display omitted]
•MethylSight is used to identify candidate methylation sites in the human proteome•45 histone methylation sites are uncovered by MethylSight and validated•The H2B-K43 methylation site is demethylated by KDM5B
Biggar et al. develop an algorithm to identify lysine methylation sites and use this resource to provide insight into the potential of the methyllysine proteome. The results also validate 45 new histone methylation sites by targeted mass spectrometry and show that one of these sites, H2B-K43me2, is a substrate of the KDM5B demethylase.</description><identifier>ISSN: 2211-1247</identifier><identifier>EISSN: 2211-1247</identifier><identifier>DOI: 10.1016/j.celrep.2020.107896</identifier><identifier>PMID: 32668242</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Algorithms ; Amino Acid Sequence ; Animals ; Cell Differentiation ; Demethylation ; Female ; histone H1 ; histone H2B ; histone marks ; Histones - chemistry ; Histones - metabolism ; Humans ; Jumonji Domain-Containing Histone Demethylases - metabolism ; KDM5b ; Lysine - metabolism ; lysine methylation ; machine learning ; MCF-7 Cells ; Methylation ; methyllysine proteome ; Mice ; Mouse Embryonic Stem Cells - cytology ; Mouse Embryonic Stem Cells - metabolism ; Neurons - cytology ; non-histone methylation ; Nuclear Proteins - metabolism ; Proteome - metabolism ; Repressor Proteins - metabolism ; Software ; Substrate Specificity</subject><ispartof>Cell reports (Cambridge), 2020-07, Vol.32 (2), p.107896-107896, Article 107896</ispartof><rights>2020 The Author(s)</rights><rights>Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-aaf2da1ac89cb56449f9914e7f6bb8fe3f99f9bc61f8328c4e7c371d7dd787d63</citedby><cites>FETCH-LOGICAL-c474t-aaf2da1ac89cb56449f9914e7f6bb8fe3f99f9bc61f8328c4e7c371d7dd787d63</cites><orcidid>0000-0002-6039-2355 ; 0000-0002-1715-8379 ; 0000-0002-7931-8921</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32668242$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Biggar, Kyle K.</creatorcontrib><creatorcontrib>Charih, Francois</creatorcontrib><creatorcontrib>Liu, Huadong</creatorcontrib><creatorcontrib>Ruiz-Blanco, Yasser B.</creatorcontrib><creatorcontrib>Stalker, Leanne</creatorcontrib><creatorcontrib>Chopra, Anand</creatorcontrib><creatorcontrib>Connolly, Justin</creatorcontrib><creatorcontrib>Adhikary, Hemanta</creatorcontrib><creatorcontrib>Frensemier, Kristin</creatorcontrib><creatorcontrib>Hoekstra, Matthew</creatorcontrib><creatorcontrib>Galka, Marek</creatorcontrib><creatorcontrib>Fang, Qi</creatorcontrib><creatorcontrib>Wynder, Christopher</creatorcontrib><creatorcontrib>Stanford, William L.</creatorcontrib><creatorcontrib>Green, James R.</creatorcontrib><creatorcontrib>Li, Shawn S.-C.</creatorcontrib><title>Proteome-wide Prediction of Lysine Methylation Leads to Identification of H2BK43 Methylation and Outlines the Potential Methyllysine Proteome</title><title>Cell reports (Cambridge)</title><addtitle>Cell Rep</addtitle><description>Protein Lys methylation plays a critical role in numerous cellular processes, but it is challenging to identify Lys methylation in a systematic manner. Here we present an approach combining in silico prediction with targeted mass spectrometry (MS) to identify Lys methylation (Kme) sites at the proteome level. We develop MethylSight, a program that predicts Kme events solely on the physicochemical properties of residues surrounding the putative methylation sites, which then requires validation by targeted MS. Using this approach, we identify 70 new histone Kme marks with a 90% validation rate. H2BK43me2, which undergoes dynamic changes during stem cell differentiation, is found to be a substrate of KDM5b. Furthermore, MethylSight predicts that Lys methylation is a prevalent post-translational modification in the human proteome. Our work provides a useful resource for guiding systematic exploration of the role of Lys methylation in human health and disease.
[Display omitted]
•MethylSight is used to identify candidate methylation sites in the human proteome•45 histone methylation sites are uncovered by MethylSight and validated•The H2B-K43 methylation site is demethylated by KDM5B
Biggar et al. develop an algorithm to identify lysine methylation sites and use this resource to provide insight into the potential of the methyllysine proteome. The results also validate 45 new histone methylation sites by targeted mass spectrometry and show that one of these sites, H2B-K43me2, is a substrate of the KDM5B demethylase.</description><subject>Algorithms</subject><subject>Amino Acid Sequence</subject><subject>Animals</subject><subject>Cell Differentiation</subject><subject>Demethylation</subject><subject>Female</subject><subject>histone H1</subject><subject>histone H2B</subject><subject>histone marks</subject><subject>Histones - chemistry</subject><subject>Histones - metabolism</subject><subject>Humans</subject><subject>Jumonji Domain-Containing Histone Demethylases - metabolism</subject><subject>KDM5b</subject><subject>Lysine - metabolism</subject><subject>lysine methylation</subject><subject>machine learning</subject><subject>MCF-7 Cells</subject><subject>Methylation</subject><subject>methyllysine proteome</subject><subject>Mice</subject><subject>Mouse Embryonic Stem Cells - cytology</subject><subject>Mouse Embryonic Stem Cells - metabolism</subject><subject>Neurons - cytology</subject><subject>non-histone methylation</subject><subject>Nuclear Proteins - metabolism</subject><subject>Proteome - metabolism</subject><subject>Repressor Proteins - metabolism</subject><subject>Software</subject><subject>Substrate Specificity</subject><issn>2211-1247</issn><issn>2211-1247</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>DOA</sourceid><recordid>eNp9UctuEzEUtRCIVqV_gNAs2Uzwa2zPBgkqoBGp2gWsLY99TR1NxsF2QPkI_hmnk1SwqTf2vT4P-x6EXhO8IJiId-uFhTHBdkExPbSk6sUzdE4pIS2hXD7_53yGLnNe47oEJqTnL9EZo0Ioyuk5-nOXYoG4gfZ3cNDcJXDBlhCnJvpmtc9hguYGyv1-NA_dFRiXmxKbpYOpBB-sOaGv6cevnP2HNpNrbndlrCqVdF_1q1mlmfEIG2eH0yNeoRfejBkuj_sF-v7507er63Z1-2V59WHVWi55aY3x1BlirOrt0AnOe9_3hIP0YhiUB1ZL3w9WEK8YVbbeWCaJk85JJZ1gF2g567po1nqbwsakvY4m6IdGTD-0SSXYEbTFQ6c8G6jpgAOWg5fVT2HWiY75Dlett7PWNsWfO8hFb0Ku6YxmgrjLuo6Zc066TlYon6E2xZwT-EdrgvUhV73Wc676kKuec620N0eH3bAB90g6pVgB72cA1Jn9CpB0tgEmW7NMYEv9VHja4S86v7ci</recordid><startdate>20200714</startdate><enddate>20200714</enddate><creator>Biggar, Kyle K.</creator><creator>Charih, Francois</creator><creator>Liu, Huadong</creator><creator>Ruiz-Blanco, Yasser B.</creator><creator>Stalker, Leanne</creator><creator>Chopra, Anand</creator><creator>Connolly, Justin</creator><creator>Adhikary, Hemanta</creator><creator>Frensemier, Kristin</creator><creator>Hoekstra, Matthew</creator><creator>Galka, Marek</creator><creator>Fang, Qi</creator><creator>Wynder, Christopher</creator><creator>Stanford, William L.</creator><creator>Green, James R.</creator><creator>Li, Shawn S.-C.</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-6039-2355</orcidid><orcidid>https://orcid.org/0000-0002-1715-8379</orcidid><orcidid>https://orcid.org/0000-0002-7931-8921</orcidid></search><sort><creationdate>20200714</creationdate><title>Proteome-wide Prediction of Lysine Methylation Leads to Identification of H2BK43 Methylation and Outlines the Potential Methyllysine Proteome</title><author>Biggar, Kyle K. ; Charih, Francois ; Liu, Huadong ; Ruiz-Blanco, Yasser B. ; Stalker, Leanne ; Chopra, Anand ; Connolly, Justin ; Adhikary, Hemanta ; Frensemier, Kristin ; Hoekstra, Matthew ; Galka, Marek ; Fang, Qi ; Wynder, Christopher ; Stanford, William L. ; Green, James R. ; Li, Shawn S.-C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-aaf2da1ac89cb56449f9914e7f6bb8fe3f99f9bc61f8328c4e7c371d7dd787d63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Amino Acid Sequence</topic><topic>Animals</topic><topic>Cell Differentiation</topic><topic>Demethylation</topic><topic>Female</topic><topic>histone H1</topic><topic>histone H2B</topic><topic>histone marks</topic><topic>Histones - chemistry</topic><topic>Histones - metabolism</topic><topic>Humans</topic><topic>Jumonji Domain-Containing Histone Demethylases - metabolism</topic><topic>KDM5b</topic><topic>Lysine - metabolism</topic><topic>lysine methylation</topic><topic>machine learning</topic><topic>MCF-7 Cells</topic><topic>Methylation</topic><topic>methyllysine proteome</topic><topic>Mice</topic><topic>Mouse Embryonic Stem Cells - cytology</topic><topic>Mouse Embryonic Stem Cells - metabolism</topic><topic>Neurons - cytology</topic><topic>non-histone methylation</topic><topic>Nuclear Proteins - metabolism</topic><topic>Proteome - metabolism</topic><topic>Repressor Proteins - metabolism</topic><topic>Software</topic><topic>Substrate Specificity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Biggar, Kyle K.</creatorcontrib><creatorcontrib>Charih, Francois</creatorcontrib><creatorcontrib>Liu, Huadong</creatorcontrib><creatorcontrib>Ruiz-Blanco, Yasser B.</creatorcontrib><creatorcontrib>Stalker, Leanne</creatorcontrib><creatorcontrib>Chopra, Anand</creatorcontrib><creatorcontrib>Connolly, Justin</creatorcontrib><creatorcontrib>Adhikary, Hemanta</creatorcontrib><creatorcontrib>Frensemier, Kristin</creatorcontrib><creatorcontrib>Hoekstra, Matthew</creatorcontrib><creatorcontrib>Galka, Marek</creatorcontrib><creatorcontrib>Fang, Qi</creatorcontrib><creatorcontrib>Wynder, Christopher</creatorcontrib><creatorcontrib>Stanford, William L.</creatorcontrib><creatorcontrib>Green, James R.</creatorcontrib><creatorcontrib>Li, Shawn S.-C.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>Directory of Open Access Journals</collection><jtitle>Cell reports (Cambridge)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Biggar, Kyle K.</au><au>Charih, Francois</au><au>Liu, Huadong</au><au>Ruiz-Blanco, Yasser B.</au><au>Stalker, Leanne</au><au>Chopra, Anand</au><au>Connolly, Justin</au><au>Adhikary, Hemanta</au><au>Frensemier, Kristin</au><au>Hoekstra, Matthew</au><au>Galka, Marek</au><au>Fang, Qi</au><au>Wynder, Christopher</au><au>Stanford, William L.</au><au>Green, James R.</au><au>Li, Shawn S.-C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Proteome-wide Prediction of Lysine Methylation Leads to Identification of H2BK43 Methylation and Outlines the Potential Methyllysine Proteome</atitle><jtitle>Cell reports (Cambridge)</jtitle><addtitle>Cell Rep</addtitle><date>2020-07-14</date><risdate>2020</risdate><volume>32</volume><issue>2</issue><spage>107896</spage><epage>107896</epage><pages>107896-107896</pages><artnum>107896</artnum><issn>2211-1247</issn><eissn>2211-1247</eissn><abstract>Protein Lys methylation plays a critical role in numerous cellular processes, but it is challenging to identify Lys methylation in a systematic manner. Here we present an approach combining in silico prediction with targeted mass spectrometry (MS) to identify Lys methylation (Kme) sites at the proteome level. We develop MethylSight, a program that predicts Kme events solely on the physicochemical properties of residues surrounding the putative methylation sites, which then requires validation by targeted MS. Using this approach, we identify 70 new histone Kme marks with a 90% validation rate. H2BK43me2, which undergoes dynamic changes during stem cell differentiation, is found to be a substrate of KDM5b. Furthermore, MethylSight predicts that Lys methylation is a prevalent post-translational modification in the human proteome. Our work provides a useful resource for guiding systematic exploration of the role of Lys methylation in human health and disease.
[Display omitted]
•MethylSight is used to identify candidate methylation sites in the human proteome•45 histone methylation sites are uncovered by MethylSight and validated•The H2B-K43 methylation site is demethylated by KDM5B
Biggar et al. develop an algorithm to identify lysine methylation sites and use this resource to provide insight into the potential of the methyllysine proteome. The results also validate 45 new histone methylation sites by targeted mass spectrometry and show that one of these sites, H2B-K43me2, is a substrate of the KDM5B demethylase.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>32668242</pmid><doi>10.1016/j.celrep.2020.107896</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0002-6039-2355</orcidid><orcidid>https://orcid.org/0000-0002-1715-8379</orcidid><orcidid>https://orcid.org/0000-0002-7931-8921</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Amino Acid Sequence Animals Cell Differentiation Demethylation Female histone H1 histone H2B histone marks Histones - chemistry Histones - metabolism Humans Jumonji Domain-Containing Histone Demethylases - metabolism KDM5b Lysine - metabolism lysine methylation machine learning MCF-7 Cells Methylation methyllysine proteome Mice Mouse Embryonic Stem Cells - cytology Mouse Embryonic Stem Cells - metabolism Neurons - cytology non-histone methylation Nuclear Proteins - metabolism Proteome - metabolism Repressor Proteins - metabolism Software Substrate Specificity |
title | Proteome-wide Prediction of Lysine Methylation Leads to Identification of H2BK43 Methylation and Outlines the Potential Methyllysine Proteome |
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