A map of protein dynamics during cell-cycle progression and cell-cycle exit
The cell-cycle field has identified the core regulators that drive the cell cycle, but we do not have a clear map of the dynamics of these regulators during cell-cycle progression versus cell-cycle exit. Here we use single-cell time-lapse microscopy of Cyclin-Dependent Kinase 2 (CDK2) activity follo...
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creator | Gookin, Sara Min, Mingwei Phadke, Harsha Chung, Mingyu Moser, Justin Miller, Iain Carter, Dylan Spencer, Sabrina L |
description | The cell-cycle field has identified the core regulators that drive the cell cycle, but we do not have a clear map of the dynamics of these regulators during cell-cycle progression versus cell-cycle exit. Here we use single-cell time-lapse microscopy of Cyclin-Dependent Kinase 2 (CDK2) activity followed by endpoint immunofluorescence and computational cell synchronization to determine the temporal dynamics of key cell-cycle proteins in asynchronously cycling human cells. We identify several unexpected patterns for core cell-cycle proteins in actively proliferating (CDK2-increasing) versus spontaneously quiescent (CDK2-low) cells, including Cyclin D1, the levels of which we find to be higher in spontaneously quiescent versus proliferating cells. We also identify proteins with concentrations that steadily increase or decrease the longer cells are in quiescence, suggesting the existence of a continuum of quiescence depths. Our single-cell measurements thus provide a rich resource for the field by characterizing protein dynamics during proliferation versus quiescence. |
doi_str_mv | 10.1371/journal.pbio.2003268 |
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Here we use single-cell time-lapse microscopy of Cyclin-Dependent Kinase 2 (CDK2) activity followed by endpoint immunofluorescence and computational cell synchronization to determine the temporal dynamics of key cell-cycle proteins in asynchronously cycling human cells. We identify several unexpected patterns for core cell-cycle proteins in actively proliferating (CDK2-increasing) versus spontaneously quiescent (CDK2-low) cells, including Cyclin D1, the levels of which we find to be higher in spontaneously quiescent versus proliferating cells. We also identify proteins with concentrations that steadily increase or decrease the longer cells are in quiescence, suggesting the existence of a continuum of quiescence depths. Our single-cell measurements thus provide a rich resource for the field by characterizing protein dynamics during proliferation versus quiescence.</description><identifier>ISSN: 1545-7885</identifier><identifier>ISSN: 1544-9173</identifier><identifier>EISSN: 1545-7885</identifier><identifier>DOI: 10.1371/journal.pbio.2003268</identifier><identifier>PMID: 28892491</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Biochemistry ; Biology ; Biology and Life Sciences ; Cancer ; Cell Cycle ; Cell Line ; Chemistry ; Computer applications ; Contact Inhibition ; Cyclin D1 ; Cyclin D1 - metabolism ; Cyclin-dependent kinase 2 ; Cyclin-Dependent Kinase 2 - metabolism ; Cyclin-dependent kinases ; Data collection ; Dynamics ; Genomes ; Humans ; Immunofluorescence ; Kinases ; Medical research ; Methods and Resources ; Microscopy ; Observations ; Protein-protein interactions ; Proteins ; Regulators ; Research and Analysis Methods ; Single-Cell Analysis ; Software ; Stem cells ; Synchronism ; Synchronization</subject><ispartof>PLoS biology, 2017-09, Vol.15 (9), p.e2003268-e2003268</ispartof><rights>COPYRIGHT 2017 Public Library of Science</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Gookin S, Min M, Phadke H, Chung M, Moser J, Miller I, et al. (2017) A map of protein dynamics during cell-cycle progression and cell-cycle exit. PLoS Biol15(9): e2003268. https://doi.org/10.1371/journal.pbio.2003268</rights><rights>2017 Gookin et al 2017 Gookin et al</rights><rights>2017 Public Library of Science. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Gookin S, Min M, Phadke H, Chung M, Moser J, Miller I, et al. (2017) A map of protein dynamics during cell-cycle progression and cell-cycle exit. PLoS Biol15(9): e2003268. https://doi.org/10.1371/journal.pbio.2003268</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c761t-f79a2704f56048a8dc64177b01b60b4fc58181fbe3d71a037f3ce969911b03753</citedby><cites>FETCH-LOGICAL-c761t-f79a2704f56048a8dc64177b01b60b4fc58181fbe3d71a037f3ce969911b03753</cites><orcidid>0000-0002-5798-3007</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/PMC5608403/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC5608403/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/28892491$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Pines, Jonathon</contributor><creatorcontrib>Gookin, Sara</creatorcontrib><creatorcontrib>Min, Mingwei</creatorcontrib><creatorcontrib>Phadke, Harsha</creatorcontrib><creatorcontrib>Chung, Mingyu</creatorcontrib><creatorcontrib>Moser, Justin</creatorcontrib><creatorcontrib>Miller, Iain</creatorcontrib><creatorcontrib>Carter, Dylan</creatorcontrib><creatorcontrib>Spencer, Sabrina L</creatorcontrib><title>A map of protein dynamics during cell-cycle progression and cell-cycle exit</title><title>PLoS biology</title><addtitle>PLoS Biol</addtitle><description>The cell-cycle field has identified the core regulators that drive the cell cycle, but we do not have a clear map of the dynamics of these regulators during cell-cycle progression versus cell-cycle exit. Here we use single-cell time-lapse microscopy of Cyclin-Dependent Kinase 2 (CDK2) activity followed by endpoint immunofluorescence and computational cell synchronization to determine the temporal dynamics of key cell-cycle proteins in asynchronously cycling human cells. We identify several unexpected patterns for core cell-cycle proteins in actively proliferating (CDK2-increasing) versus spontaneously quiescent (CDK2-low) cells, including Cyclin D1, the levels of which we find to be higher in spontaneously quiescent versus proliferating cells. We also identify proteins with concentrations that steadily increase or decrease the longer cells are in quiescence, suggesting the existence of a continuum of quiescence depths. Our single-cell measurements thus provide a rich resource for the field by characterizing protein dynamics during proliferation versus quiescence.</description><subject>Biochemistry</subject><subject>Biology</subject><subject>Biology and Life Sciences</subject><subject>Cancer</subject><subject>Cell Cycle</subject><subject>Cell Line</subject><subject>Chemistry</subject><subject>Computer applications</subject><subject>Contact Inhibition</subject><subject>Cyclin D1</subject><subject>Cyclin D1 - metabolism</subject><subject>Cyclin-dependent kinase 2</subject><subject>Cyclin-Dependent Kinase 2 - metabolism</subject><subject>Cyclin-dependent kinases</subject><subject>Data collection</subject><subject>Dynamics</subject><subject>Genomes</subject><subject>Humans</subject><subject>Immunofluorescence</subject><subject>Kinases</subject><subject>Medical research</subject><subject>Methods and Resources</subject><subject>Microscopy</subject><subject>Observations</subject><subject>Protein-protein interactions</subject><subject>Proteins</subject><subject>Regulators</subject><subject>Research and Analysis Methods</subject><subject>Single-Cell Analysis</subject><subject>Software</subject><subject>Stem cells</subject><subject>Synchronism</subject><subject>Synchronization</subject><issn>1545-7885</issn><issn>1544-9173</issn><issn>1545-7885</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>DOA</sourceid><recordid>eNqVkkmP0zAUxyMEYobCN0AQiQscUrzGzgWpGrFUjBiJ7Wo5XoKr1C52gqbfHodmRi2aA8iyvP3e_y1-RfEUgiXEDL7ehDF62S93rQtLBABGNb9XnENKaMU4p_eP9mfFo5Q2ACDUIP6wOEOcN4g08Lz4uCq3clcGW-5iGIzzpd57uXUqlXqMznelMn1fqb3qzYR00aTkgi-l18dP5toNj4sHVvbJPJnXRfHt3duvFx-qy6v364vVZaVYDYfKskYiBoilNSBccq1qAhlrAWxr0BKrKIcc2tZgzaAEmFmsTFM3DYRtPlG8KJ4fdHd9SGKuQxKwoZBQVFOeifWB0EFuxC66rYx7EaQTfy5C7ISMg8uBC6Q14wQqrnNIGGBpUcsBbaREjVVQZa03s7ex3RqtjB-i7E9ET1-8-yG68Evk9DgBOAu8nAVi-DmaNIitS1PppDdhnOLGPE9So4y--Au9O7uZ6mROwHkbsl81iYoVBQxzCrLfRbG8g8pDm_y9wRvr8v2JwasTg8wM5nro5JiSWH_5_B_sp39nr76fsuTAqhhSisbe1hkCMbX9TUHE1PZibvts9uz4j26Nbvoc_wYkPPra</recordid><startdate>20170911</startdate><enddate>20170911</enddate><creator>Gookin, Sara</creator><creator>Min, Mingwei</creator><creator>Phadke, Harsha</creator><creator>Chung, Mingyu</creator><creator>Moser, Justin</creator><creator>Miller, Iain</creator><creator>Carter, Dylan</creator><creator>Spencer, Sabrina L</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><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>IOV</scope><scope>ISN</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>P64</scope><scope>PATMY</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>5PM</scope><scope>DOA</scope><scope>CZG</scope><orcidid>https://orcid.org/0000-0002-5798-3007</orcidid></search><sort><creationdate>20170911</creationdate><title>A map of protein dynamics during cell-cycle progression and cell-cycle exit</title><author>Gookin, Sara ; Min, Mingwei ; Phadke, Harsha ; Chung, Mingyu ; Moser, Justin ; Miller, Iain ; Carter, Dylan ; Spencer, Sabrina L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c761t-f79a2704f56048a8dc64177b01b60b4fc58181fbe3d71a037f3ce969911b03753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Biochemistry</topic><topic>Biology</topic><topic>Biology and Life Sciences</topic><topic>Cancer</topic><topic>Cell Cycle</topic><topic>Cell Line</topic><topic>Chemistry</topic><topic>Computer applications</topic><topic>Contact Inhibition</topic><topic>Cyclin D1</topic><topic>Cyclin D1 - metabolism</topic><topic>Cyclin-dependent kinase 2</topic><topic>Cyclin-Dependent Kinase 2 - metabolism</topic><topic>Cyclin-dependent kinases</topic><topic>Data collection</topic><topic>Dynamics</topic><topic>Genomes</topic><topic>Humans</topic><topic>Immunofluorescence</topic><topic>Kinases</topic><topic>Medical research</topic><topic>Methods and Resources</topic><topic>Microscopy</topic><topic>Observations</topic><topic>Protein-protein interactions</topic><topic>Proteins</topic><topic>Regulators</topic><topic>Research and Analysis Methods</topic><topic>Single-Cell Analysis</topic><topic>Software</topic><topic>Stem cells</topic><topic>Synchronism</topic><topic>Synchronization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gookin, Sara</creatorcontrib><creatorcontrib>Min, Mingwei</creatorcontrib><creatorcontrib>Phadke, Harsha</creatorcontrib><creatorcontrib>Chung, Mingyu</creatorcontrib><creatorcontrib>Moser, Justin</creatorcontrib><creatorcontrib>Miller, Iain</creatorcontrib><creatorcontrib>Carter, Dylan</creatorcontrib><creatorcontrib>Spencer, Sabrina L</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Gale In Context: Opposing Viewpoints</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Algology Mycology and Protozoology Abstracts (Microbiology C)</collection><collection>Biological Science Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Environmental Science Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Environmental Science Collection</collection><collection>Genetics Abstracts</collection><collection>MEDLINE - 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Here we use single-cell time-lapse microscopy of Cyclin-Dependent Kinase 2 (CDK2) activity followed by endpoint immunofluorescence and computational cell synchronization to determine the temporal dynamics of key cell-cycle proteins in asynchronously cycling human cells. We identify several unexpected patterns for core cell-cycle proteins in actively proliferating (CDK2-increasing) versus spontaneously quiescent (CDK2-low) cells, including Cyclin D1, the levels of which we find to be higher in spontaneously quiescent versus proliferating cells. We also identify proteins with concentrations that steadily increase or decrease the longer cells are in quiescence, suggesting the existence of a continuum of quiescence depths. Our single-cell measurements thus provide a rich resource for the field by characterizing protein dynamics during proliferation versus quiescence.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28892491</pmid><doi>10.1371/journal.pbio.2003268</doi><orcidid>https://orcid.org/0000-0002-5798-3007</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Biochemistry Biology Biology and Life Sciences Cancer Cell Cycle Cell Line Chemistry Computer applications Contact Inhibition Cyclin D1 Cyclin D1 - metabolism Cyclin-dependent kinase 2 Cyclin-Dependent Kinase 2 - metabolism Cyclin-dependent kinases Data collection Dynamics Genomes Humans Immunofluorescence Kinases Medical research Methods and Resources Microscopy Observations Protein-protein interactions Proteins Regulators Research and Analysis Methods Single-Cell Analysis Software Stem cells Synchronism Synchronization |
title | A map of protein dynamics during cell-cycle progression and cell-cycle exit |
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