A Continuous Molecular Roadmap to iPSC Reprogramming through Progression Analysis of Single-Cell Mass Cytometry
Identifieur interne : 000961 ( Ncbi/Merge ); précédent : 000960; suivant : 000962A Continuous Molecular Roadmap to iPSC Reprogramming through Progression Analysis of Single-Cell Mass Cytometry
Auteurs : Eli R. Zunder [États-Unis] ; Ernesto Lujan [États-Unis] ; Yury Goltsev [États-Unis] ; Marius Wernig [États-Unis] ; Garry P. Nolan [États-Unis]Source :
- Cell stem cell [ 1934-5909 ] ; 2015.
Abstract
To analyze cellular reprogramming at the single-cell level, mass cytometry was used to simultaneously measure markers of pluripotency, differentiation, cell-cycle status, and cellular signaling throughout the reprogramming process. Time-resolved progression analysis of the resulting data sets was used to construct a continuous molecular roadmap for three independent reprogramming systems. Although these systems varied substantially in Oct4, Sox2, Klf4, and c-Myc stoichiometry, they presented a common set of reprogramming landmarks. Early in the reprogramming process, Oct4highKlf4high cells transitioned to a CD73highCD104highCD54low partially reprogrammed state. Ki67low cells from this intermediate population reverted to a MEF-like phenotype, but Ki67high cells advanced through the M-E-T and then bifurcated into two distinct populations: an ESC-like NanoghighSox2highCD54high population and a mesendoderm-like NanoglowSox2lowLin28high CD24highPDGFR-αhigh population. The methods developed here for time-resolved, single-cell progression analysis may be used for the study of additional complex and dynamic systems, such as cancer progression and embryonic development.
Url:
DOI: 10.1016/j.stem.2015.01.015
PubMed: 25748935
PubMed Central: 4401090
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<author><name sortKey="Lujan, Ernesto" sort="Lujan, Ernesto" uniqKey="Lujan E" first="Ernesto" last="Lujan">Ernesto Lujan</name>
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<series><title level="j">Cell stem cell</title>
<idno type="ISSN">1934-5909</idno>
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<imprint><date when="2015">2015</date>
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<front><div type="abstract" xml:lang="en"><title>SUMMARY</title>
<p id="P2">To analyze cellular reprogramming at the single-cell level, mass cytometry was used to simultaneously measure markers of pluripotency, differentiation, cell-cycle status, and cellular signaling throughout the reprogramming process. Time-resolved progression analysis of the resulting data sets was used to construct a continuous molecular roadmap for three independent reprogramming systems. Although these systems varied substantially in Oct4, Sox2, Klf4, and c-Myc stoichiometry, they presented a common set of reprogramming landmarks. Early in the reprogramming process, Oct4<sup>high</sup>
Klf4<sup>high</sup>
cells transitioned to a CD73<sup>high</sup>
CD104<sup>high</sup>
CD54<sup>low</sup>
partially reprogrammed state. Ki67<sup>low</sup>
cells from this intermediate population reverted to a MEF-like phenotype, but Ki67<sup>high</sup>
cells advanced through the M-E-T and then bifurcated into two distinct populations: an ESC-like Nanog<sup>high</sup>
Sox2<sup>high</sup>
CD54<sup>high</sup>
population and a mesendoderm-like Nanog<sup>low</sup>
Sox2<sup>low</sup>
Lin28<sup>high</sup>
CD24<sup>high</sup>
PDGFR-α<sup>high</sup>
population. The methods developed here for time-resolved, single-cell progression analysis may be used for the study of additional complex and dynamic systems, such as cancer progression and embryonic development.</p>
</div>
</front>
</TEI>
<pmc article-type="research-article"><pmc-comment>The publisher of this article does not allow downloading of the full text in XML form.</pmc-comment>
<pmc-dir>properties manuscript</pmc-dir>
<front><journal-meta><journal-id journal-id-type="nlm-journal-id">101311472</journal-id>
<journal-id journal-id-type="pubmed-jr-id">34100</journal-id>
<journal-id journal-id-type="nlm-ta">Cell Stem Cell</journal-id>
<journal-id journal-id-type="iso-abbrev">Cell Stem Cell</journal-id>
<journal-title-group><journal-title>Cell stem cell</journal-title>
</journal-title-group>
<issn pub-type="ppub">1934-5909</issn>
<issn pub-type="epub">1875-9777</issn>
</journal-meta>
<article-meta><article-id pub-id-type="pmid">25748935</article-id>
<article-id pub-id-type="pmc">4401090</article-id>
<article-id pub-id-type="doi">10.1016/j.stem.2015.01.015</article-id>
<article-id pub-id-type="manuscript">NIHMS664657</article-id>
<article-categories><subj-group subj-group-type="heading"><subject>Article</subject>
</subj-group>
</article-categories>
<title-group><article-title>A Continuous Molecular Roadmap to iPSC Reprogramming through Progression Analysis of Single-Cell Mass Cytometry</article-title>
</title-group>
<contrib-group><contrib contrib-type="author"><name><surname>Zunder</surname>
<given-names>Eli R.</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="author-notes" rid="FN1">4</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Lujan</surname>
<given-names>Ernesto</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
<xref ref-type="aff" rid="A3">3</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Goltsev</surname>
<given-names>Yury</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Wernig</surname>
<given-names>Marius</given-names>
</name>
<xref ref-type="aff" rid="A2">2</xref>
</contrib>
<contrib contrib-type="author"><name><surname>Nolan</surname>
<given-names>Garry P.</given-names>
</name>
<xref ref-type="aff" rid="A1">1</xref>
<xref ref-type="corresp" rid="cor1">*</xref>
</contrib>
</contrib-group>
<aff id="A1"><label>1</label>
Department of Microbiology and Immunology, Baxter Laboratory for Stem Cell Biology, Stanford University School of Medicine, Stanford, CA 94305, USA</aff>
<aff id="A2"><label>2</label>
Department of Pathology, Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA</aff>
<aff id="A3"><label>3</label>
Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA</aff>
<author-notes><corresp id="cor1"><label>*</label>
Correspondence: <email>gnolan@stanford.edu</email>
</corresp>
<fn id="FN1"><label>4</label>
<p id="P1">Co-first author</p>
</fn>
</author-notes>
<pub-date pub-type="nihms-submitted"><day>26</day>
<month>2</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="ppub"><day>5</day>
<month>3</month>
<year>2015</year>
</pub-date>
<pub-date pub-type="pmc-release"><day>05</day>
<month>3</month>
<year>2016</year>
</pub-date>
<volume>16</volume>
<issue>3</issue>
<fpage>323</fpage>
<lpage>337</lpage>
<pmc-comment>elocation-id from pubmed: 10.1016/j.stem.2015.01.015</pmc-comment>
<permissions><copyright-statement>© 2015 Elsevier Inc.</copyright-statement>
<copyright-year>2015</copyright-year>
</permissions>
<abstract><title>SUMMARY</title>
<p id="P2">To analyze cellular reprogramming at the single-cell level, mass cytometry was used to simultaneously measure markers of pluripotency, differentiation, cell-cycle status, and cellular signaling throughout the reprogramming process. Time-resolved progression analysis of the resulting data sets was used to construct a continuous molecular roadmap for three independent reprogramming systems. Although these systems varied substantially in Oct4, Sox2, Klf4, and c-Myc stoichiometry, they presented a common set of reprogramming landmarks. Early in the reprogramming process, Oct4<sup>high</sup>
Klf4<sup>high</sup>
cells transitioned to a CD73<sup>high</sup>
CD104<sup>high</sup>
CD54<sup>low</sup>
partially reprogrammed state. Ki67<sup>low</sup>
cells from this intermediate population reverted to a MEF-like phenotype, but Ki67<sup>high</sup>
cells advanced through the M-E-T and then bifurcated into two distinct populations: an ESC-like Nanog<sup>high</sup>
Sox2<sup>high</sup>
CD54<sup>high</sup>
population and a mesendoderm-like Nanog<sup>low</sup>
Sox2<sup>low</sup>
Lin28<sup>high</sup>
CD24<sup>high</sup>
PDGFR-α<sup>high</sup>
population. The methods developed here for time-resolved, single-cell progression analysis may be used for the study of additional complex and dynamic systems, such as cancer progression and embryonic development.</p>
</abstract>
</article-meta>
</front>
</pmc>
<affiliations><list><country><li>États-Unis</li>
</country>
<region><li>Californie</li>
</region>
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<tree><country name="États-Unis"><region name="Californie"><name sortKey="Zunder, Eli R" sort="Zunder, Eli R" uniqKey="Zunder E" first="Eli R." last="Zunder">Eli R. Zunder</name>
</region>
<name sortKey="Goltsev, Yury" sort="Goltsev, Yury" uniqKey="Goltsev Y" first="Yury" last="Goltsev">Yury Goltsev</name>
<name sortKey="Lujan, Ernesto" sort="Lujan, Ernesto" uniqKey="Lujan E" first="Ernesto" last="Lujan">Ernesto Lujan</name>
<name sortKey="Lujan, Ernesto" sort="Lujan, Ernesto" uniqKey="Lujan E" first="Ernesto" last="Lujan">Ernesto Lujan</name>
<name sortKey="Nolan, Garry P" sort="Nolan, Garry P" uniqKey="Nolan G" first="Garry P." last="Nolan">Garry P. Nolan</name>
<name sortKey="Wernig, Marius" sort="Wernig, Marius" uniqKey="Wernig M" first="Marius" last="Wernig">Marius Wernig</name>
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