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单细胞解析的细胞间通讯模型解释了造血中的谱系承诺。

A single-cell resolved cell-cell communication model explains lineage commitment in hematopoiesis.

机构信息

Department of Quantitative and Computational Biology, University of Southern California, 1050 Childs Way, Los Angeles, CA 90089, USA.

出版信息

Development. 2021 Dec 15;148(24). doi: 10.1242/dev.199779. Epub 2021 Dec 22.

DOI:10.1242/dev.199779
PMID:34935903
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8722395/
Abstract

Cells do not make fate decisions independently. Arguably, every cell-fate decision occurs in response to environmental signals. In many cases, cell-cell communication alters the dynamics of the internal gene regulatory network of a cell to initiate cell-fate transitions, yet models rarely take this into account. Here, we have developed a multiscale perspective to study the granulocyte-monocyte versus megakaryocyte-erythrocyte fate decisions. This transition is dictated by the GATA1-PU.1 network: a classical example of a bistable cell-fate system. We show that, for a wide range of cell communication topologies, even subtle changes in signaling can have pronounced effects on cell-fate decisions. We go on to show how cell-cell coupling through signaling can spontaneously break the symmetry of a homogenous cell population. Noise, both intrinsic and extrinsic, shapes the decision landscape profoundly, and affects the transcriptional dynamics underlying this important hematopoietic cell-fate decision-making system. This article has an associated 'The people behind the papers' interview.

摘要

细胞不会独立做出命运决定。可以说,每一个细胞命运的决定都是对环境信号的反应。在许多情况下,细胞间的通讯改变了细胞内部基因调控网络的动态,从而启动细胞命运的转变,但模型很少考虑到这一点。在这里,我们开发了一种多尺度的视角来研究粒细胞-单核细胞与巨核细胞-红细胞命运的决定。这种转变由 GATA1-PU.1 网络决定:这是一个双稳态细胞命运系统的经典例子。我们表明,对于广泛的细胞通讯拓扑结构,即使信号的细微变化也会对细胞命运的决定产生显著的影响。我们接着展示了通过信号的细胞间耦合如何自发地打破同质细胞群体的对称性。噪声,无论是内在的还是外在的,深刻地塑造了决策景观,并影响了这个重要的造血细胞命运决策系统的转录动力学。本文有一个相关的“论文背后的人物”访谈。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/38a8344e367b/develop-148-199779-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/0f39c43c0f48/develop-148-199779-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/52f161d6b7d2/develop-148-199779-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/9376e9163ce1/develop-148-199779-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/a43a187bf139/develop-148-199779-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/d60b400313ad/develop-148-199779-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/38a8344e367b/develop-148-199779-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/0f39c43c0f48/develop-148-199779-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/52f161d6b7d2/develop-148-199779-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/9376e9163ce1/develop-148-199779-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/a43a187bf139/develop-148-199779-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/d60b400313ad/develop-148-199779-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3ec8/8722395/38a8344e367b/develop-148-199779-g6.jpg

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