Integrating quantitative proteomics with accurate genome profiling of transcription factors by greenCUT&RUN
Abstract Genome-wide localization of chromatin and transcription regulators can be detected by a variety of techniques. Here, we describe a novel method ‘greenCUT&RUN’ for genome-wide profiling of transcription regulators, which has a very high sensitivity, resolution, accuracy and reproducibili...
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| Veröffentlicht in: | Nucleic acids research 2021-05, Vol.49 (9), p.e49-e49 |
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| container_title | Nucleic acids research |
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| creator | Nizamuddin, Sheikh Koidl, Stefanie Bhuiyan, Tanja Werner, Tamara V Biniossek, Martin L Bonvin, Alexandre M J J Lassmann, Silke Timmers, HThMarc |
| description | Abstract
Genome-wide localization of chromatin and transcription regulators can be detected by a variety of techniques. Here, we describe a novel method ‘greenCUT&RUN’ for genome-wide profiling of transcription regulators, which has a very high sensitivity, resolution, accuracy and reproducibility, whilst assuring specificity. Our strategy begins with tagging of the protein of interest with GFP and utilizes a GFP-specific nanobody fused to MNase to profile genome-wide binding events. By using a GFP-nanobody the greenCUT&RUN approach eliminates antibody dependency and variability. Robust genomic profiles were obtained with greenCUT&RUN, which are accurate and unbiased towards open chromatin. By integrating greenCUT&RUN with nanobody-based affinity purification mass spectrometry, ‘piggy-back’ DNA binding events can be identified on a genomic scale. The unique design of greenCUT&RUN grants target protein flexibility and yields high resolution footprints. In addition, greenCUT&RUN allows rapid profiling of mutants of chromatin and transcription proteins. In conclusion, greenCUT&RUN is a widely applicable and versatile genome-mapping technique. |
| doi_str_mv | 10.1093/nar/gkab038 |
| format | Article |
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Genome-wide localization of chromatin and transcription regulators can be detected by a variety of techniques. Here, we describe a novel method ‘greenCUT&RUN’ for genome-wide profiling of transcription regulators, which has a very high sensitivity, resolution, accuracy and reproducibility, whilst assuring specificity. Our strategy begins with tagging of the protein of interest with GFP and utilizes a GFP-specific nanobody fused to MNase to profile genome-wide binding events. By using a GFP-nanobody the greenCUT&RUN approach eliminates antibody dependency and variability. Robust genomic profiles were obtained with greenCUT&RUN, which are accurate and unbiased towards open chromatin. By integrating greenCUT&RUN with nanobody-based affinity purification mass spectrometry, ‘piggy-back’ DNA binding events can be identified on a genomic scale. The unique design of greenCUT&RUN grants target protein flexibility and yields high resolution footprints. In addition, greenCUT&RUN allows rapid profiling of mutants of chromatin and transcription proteins. In conclusion, greenCUT&RUN is a widely applicable and versatile genome-mapping technique.]]></description><identifier>ISSN: 0305-1048</identifier><identifier>ISSN: 1362-4962</identifier><identifier>EISSN: 1362-4962</identifier><identifier>DOI: 10.1093/nar/gkab038</identifier><identifier>PMID: 33524153</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Binding Sites ; CCAAT-Binding Factor - genetics ; CCAAT-Binding Factor - metabolism ; Genomics - methods ; Green Fluorescent Proteins - genetics ; Green Fluorescent Proteins - immunology ; HeLa Cells ; Humans ; Mass Spectrometry ; Methods Online ; Proteomics - methods ; Proto-Oncogene Proteins c-fos - genetics ; Proto-Oncogene Proteins c-fos - metabolism ; Recombinant Fusion Proteins - analysis ; Single-Domain Antibodies ; TATA-Box Binding Protein - genetics ; TATA-Box Binding Protein - metabolism ; Transcription Factors - metabolism</subject><ispartof>Nucleic acids research, 2021-05, Vol.49 (9), p.e49-e49</ispartof><rights>The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research. 2021</rights><rights>The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c412t-418e1c5fea732b6b29511d5784a7954a1223089dfb9f2ecc158490199ce50e203</citedby><cites>FETCH-LOGICAL-c412t-418e1c5fea732b6b29511d5784a7954a1223089dfb9f2ecc158490199ce50e203</cites><orcidid>0000-0001-7062-1417</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136828/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136828/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,724,777,781,861,882,1599,27905,27906,53772,53774</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33524153$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Nizamuddin, Sheikh</creatorcontrib><creatorcontrib>Koidl, Stefanie</creatorcontrib><creatorcontrib>Bhuiyan, Tanja</creatorcontrib><creatorcontrib>Werner, Tamara V</creatorcontrib><creatorcontrib>Biniossek, Martin L</creatorcontrib><creatorcontrib>Bonvin, Alexandre M J J</creatorcontrib><creatorcontrib>Lassmann, Silke</creatorcontrib><creatorcontrib>Timmers, HThMarc</creatorcontrib><title>Integrating quantitative proteomics with accurate genome profiling of transcription factors by greenCUT&RUN</title><title>Nucleic acids research</title><addtitle>Nucleic Acids Res</addtitle><description><![CDATA[Abstract
Genome-wide localization of chromatin and transcription regulators can be detected by a variety of techniques. Here, we describe a novel method ‘greenCUT&RUN’ for genome-wide profiling of transcription regulators, which has a very high sensitivity, resolution, accuracy and reproducibility, whilst assuring specificity. Our strategy begins with tagging of the protein of interest with GFP and utilizes a GFP-specific nanobody fused to MNase to profile genome-wide binding events. By using a GFP-nanobody the greenCUT&RUN approach eliminates antibody dependency and variability. Robust genomic profiles were obtained with greenCUT&RUN, which are accurate and unbiased towards open chromatin. By integrating greenCUT&RUN with nanobody-based affinity purification mass spectrometry, ‘piggy-back’ DNA binding events can be identified on a genomic scale. The unique design of greenCUT&RUN grants target protein flexibility and yields high resolution footprints. In addition, greenCUT&RUN allows rapid profiling of mutants of chromatin and transcription proteins. In conclusion, greenCUT&RUN is a widely applicable and versatile genome-mapping technique.]]></description><subject>Binding Sites</subject><subject>CCAAT-Binding Factor - genetics</subject><subject>CCAAT-Binding Factor - metabolism</subject><subject>Genomics - methods</subject><subject>Green Fluorescent Proteins - genetics</subject><subject>Green Fluorescent Proteins - immunology</subject><subject>HeLa Cells</subject><subject>Humans</subject><subject>Mass Spectrometry</subject><subject>Methods Online</subject><subject>Proteomics - methods</subject><subject>Proto-Oncogene Proteins c-fos - genetics</subject><subject>Proto-Oncogene Proteins c-fos - metabolism</subject><subject>Recombinant Fusion Proteins - analysis</subject><subject>Single-Domain Antibodies</subject><subject>TATA-Box Binding Protein - genetics</subject><subject>TATA-Box Binding Protein - metabolism</subject><subject>Transcription Factors - metabolism</subject><issn>0305-1048</issn><issn>1362-4962</issn><issn>1362-4962</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><sourceid>EIF</sourceid><recordid>eNp9kd9rFDEQx4Mo9qw--S55KkLZNj_vkhehHK0WioL0nkM2N7uN3U22SbbS_75p7yz64tPMMJ_5zjBfhD5SckKJ5qfBptP-1raEq1doQfmSNUIv2Wu0IJzIhhKhDtC7nH8RQgWV4i064FyymvIFur0MBfpkiw89vpttKL7U4h7wlGKBOHqX8W9fbrB1bq4c4B5CHJ_7nR-exmKHS7Ihu-Sn4mPAnXUlpozbB9wngLDeXB_93Hx_j950dsjwYR8P0ebi_Hr9rbn68fVyfXbVOEFZaQRVQJ3swK44a5ct05LSrVwpYVdaCksZ40TpbdfqjoFzVCqhCdXagSTACD9EX3a609yOsHUQ6nmDmZIfbXow0Xrzbyf4G9PHe6Pq8xRTVeDzXiDFuxlyMaPPDobBBohzNkwoKSmjS13R4x3qUsw5QfeyhhLzZI-p9pi9PZX-9PdlL-wfPypwtAPiPP1X6RFJFZwX</recordid><startdate>20210521</startdate><enddate>20210521</enddate><creator>Nizamuddin, Sheikh</creator><creator>Koidl, Stefanie</creator><creator>Bhuiyan, Tanja</creator><creator>Werner, Tamara V</creator><creator>Biniossek, Martin L</creator><creator>Bonvin, Alexandre M J J</creator><creator>Lassmann, Silke</creator><creator>Timmers, HThMarc</creator><general>Oxford University Press</general><scope>TOX</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>5PM</scope><orcidid>https://orcid.org/0000-0001-7062-1417</orcidid></search><sort><creationdate>20210521</creationdate><title>Integrating quantitative proteomics with accurate genome profiling of transcription factors by greenCUT&RUN</title><author>Nizamuddin, Sheikh ; Koidl, Stefanie ; Bhuiyan, Tanja ; Werner, Tamara V ; Biniossek, Martin L ; Bonvin, Alexandre M J J ; Lassmann, Silke ; Timmers, HThMarc</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c412t-418e1c5fea732b6b29511d5784a7954a1223089dfb9f2ecc158490199ce50e203</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Binding Sites</topic><topic>CCAAT-Binding Factor - genetics</topic><topic>CCAAT-Binding Factor - metabolism</topic><topic>Genomics - methods</topic><topic>Green Fluorescent Proteins - genetics</topic><topic>Green Fluorescent Proteins - immunology</topic><topic>HeLa Cells</topic><topic>Humans</topic><topic>Mass Spectrometry</topic><topic>Methods Online</topic><topic>Proteomics - methods</topic><topic>Proto-Oncogene Proteins c-fos - genetics</topic><topic>Proto-Oncogene Proteins c-fos - metabolism</topic><topic>Recombinant Fusion Proteins - analysis</topic><topic>Single-Domain Antibodies</topic><topic>TATA-Box Binding Protein - genetics</topic><topic>TATA-Box Binding Protein - metabolism</topic><topic>Transcription Factors - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Nizamuddin, Sheikh</creatorcontrib><creatorcontrib>Koidl, Stefanie</creatorcontrib><creatorcontrib>Bhuiyan, Tanja</creatorcontrib><creatorcontrib>Werner, Tamara V</creatorcontrib><creatorcontrib>Biniossek, Martin L</creatorcontrib><creatorcontrib>Bonvin, Alexandre M J J</creatorcontrib><creatorcontrib>Lassmann, Silke</creatorcontrib><creatorcontrib>Timmers, HThMarc</creatorcontrib><collection>Oxford Journals Open Access Collection</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>PubMed Central (Full Participant titles)</collection><jtitle>Nucleic acids research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Nizamuddin, Sheikh</au><au>Koidl, Stefanie</au><au>Bhuiyan, Tanja</au><au>Werner, Tamara V</au><au>Biniossek, Martin L</au><au>Bonvin, Alexandre M J J</au><au>Lassmann, Silke</au><au>Timmers, HThMarc</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Integrating quantitative proteomics with accurate genome profiling of transcription factors by greenCUT&RUN</atitle><jtitle>Nucleic acids research</jtitle><addtitle>Nucleic Acids Res</addtitle><date>2021-05-21</date><risdate>2021</risdate><volume>49</volume><issue>9</issue><spage>e49</spage><epage>e49</epage><pages>e49-e49</pages><issn>0305-1048</issn><issn>1362-4962</issn><eissn>1362-4962</eissn><abstract><![CDATA[Abstract
Genome-wide localization of chromatin and transcription regulators can be detected by a variety of techniques. Here, we describe a novel method ‘greenCUT&RUN’ for genome-wide profiling of transcription regulators, which has a very high sensitivity, resolution, accuracy and reproducibility, whilst assuring specificity. Our strategy begins with tagging of the protein of interest with GFP and utilizes a GFP-specific nanobody fused to MNase to profile genome-wide binding events. By using a GFP-nanobody the greenCUT&RUN approach eliminates antibody dependency and variability. Robust genomic profiles were obtained with greenCUT&RUN, which are accurate and unbiased towards open chromatin. By integrating greenCUT&RUN with nanobody-based affinity purification mass spectrometry, ‘piggy-back’ DNA binding events can be identified on a genomic scale. The unique design of greenCUT&RUN grants target protein flexibility and yields high resolution footprints. In addition, greenCUT&RUN allows rapid profiling of mutants of chromatin and transcription proteins. In conclusion, greenCUT&RUN is a widely applicable and versatile genome-mapping technique.]]></abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>33524153</pmid><doi>10.1093/nar/gkab038</doi><orcidid>https://orcid.org/0000-0001-7062-1417</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Binding Sites CCAAT-Binding Factor - genetics CCAAT-Binding Factor - metabolism Genomics - methods Green Fluorescent Proteins - genetics Green Fluorescent Proteins - immunology HeLa Cells Humans Mass Spectrometry Methods Online Proteomics - methods Proto-Oncogene Proteins c-fos - genetics Proto-Oncogene Proteins c-fos - metabolism Recombinant Fusion Proteins - analysis Single-Domain Antibodies TATA-Box Binding Protein - genetics TATA-Box Binding Protein - metabolism Transcription Factors - metabolism |
| title | Integrating quantitative proteomics with accurate genome profiling of transcription factors by greenCUT&RUN |
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