| Title |
Reinforcement of STAT3 activity reprogrammes human embryonic stem cells to naive-like pluripotency
|
|---|---|
| Published in |
Nature Communications, May 2015
|
| DOI | 10.1038/ncomms8095 |
| Pubmed ID | |
| Authors |
Hongwei Chen, Irène Aksoy, Fabrice Gonnot, Pierre Osteil, Maxime Aubry, Claire Hamela, Cloé Rognard, Arnaud Hochard, Sophie Voisin, Emeline Fontaine, Magali Mure, Marielle Afanassieff, Elouan Cleroux, Sylvain Guibert, Jiaxuan Chen, Céline Vallot, Hervé Acloque, Clémence Genthon, Cécile Donnadieu, John De Vos, Damien Sanlaville, Jean- François Guérin, Michael Weber, Lawrence W Stanton, Claire Rougeulle, Bertrand Pain, Pierre-Yves Bourillot, Pierre Savatier |
| Abstract |
Leukemia inhibitory factor (LIF)/STAT3 signalling is a hallmark of naive pluripotency in rodent pluripotent stem cells (PSCs), whereas fibroblast growth factor (FGF)-2 and activin/nodal signalling is required to sustain self-renewal of human PSCs in a condition referred to as the primed state. It is unknown why LIF/STAT3 signalling alone fails to sustain pluripotency in human PSCs. Here we show that the forced expression of the hormone-dependent STAT3-ER (ER, ligand-binding domain of the human oestrogen receptor) in combination with 2i/LIF and tamoxifen allows human PSCs to escape from the primed state and enter a state characterized by the activation of STAT3 target genes and long-term self-renewal in FGF2- and feeder-free conditions. These cells acquire growth properties, a gene expression profile and an epigenetic landscape closer to those described in mouse naive PSCs. Together, these results show that temporarily increasing STAT3 activity is sufficient to reprogramme human PSCs to naive-like pluripotent cells. |
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Demographic breakdown
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Mendeley demographics
Geographical breakdown
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| Brazil | 1 | <1% |
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Demographic breakdown
| Readers by professional status | Count | As % |
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| Researcher | 34 | 18% |
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| Student > Bachelor | 15 | 8% |
| Other | 10 | 5% |
| Other | 20 | 11% |
| Unknown | 35 | 18% |
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| Medicine and Dentistry | 15 | 8% |
| Neuroscience | 3 | 2% |
| Computer Science | 2 | 1% |
| Other | 10 | 5% |
| Unknown | 36 | 19% |