Mechano-osmotic signals control chromatin state and fate transitions in pluripotent stem cells

机械渗透信号控制多能干细胞染色质状态和命运转变

阅读:5
作者:Kaitlin P McCreery, Aki Stubb, Rebecca Stephens, Nadezda A Fursova, Andrew Cook, Kai Kruse, Anja Michelbach, Leah C Biggs, Adib Keikhosravi, Sonja Nykänen, Christel Hydén-Granskog, Jizhong Zou, Jan-Wilm Lackmann, Carien M Niessen, Sanna Vuoristo, Yekaterina A Miroshnikova, Sara A Wickström

Abstract

Acquisition of specific cell shapes and morphologies is a central component of cell fate transitions. Although signaling circuits and gene regulatory networks that regulate pluripotent stem cell differentiation have been intensely studied, how these networks are integrated in space and time with morphological transitions and mechanical deformations to control state transitions remains a fundamental open question. Here, we focus on two distinct models of pluripotency, primed pluripotent stem cells and pre-implantation inner cell mass cells of human embryos to discover that cell fate transitions associate with rapid changes in nuclear shape and volume which collectively alter the nuclear mechanophenotype. Mechanistic studies in human induced pluripotent stem cells further reveal that these phenotypical changes and the associated active fluctuations of the nuclear envelope arise from growth factor signaling-controlled changes in chromatin mechanics and cytoskeletal confinement. These collective mechano-osmotic changes trigger global transcriptional repression and a condensation-prone environment that primes chromatin for a cell fate transition by attenuating repression of differentiation genes. However, while this mechano-osmotic chromatin priming has the potential to accelerate fate transitions and differentiation, sustained biochemical signals are required for robust induction of specific lineages. Our findings uncover a critical mechanochemical feedback mechanism that integrates nuclear mechanics, shape and volume with biochemical signaling and chromatin state to control cell fate transition dynamics.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。