简介

在动态的环境里面，细胞们通过各遗传途径的相互作用交流运转着。哺乳动物免疫反应就是各类不同的细胞协同合作的一个惊人例子。细胞与细胞之间的交流主要是通过信号分子形成时间与空间浓度梯度来介导的，这就要求细胞对一个大范围内的信号强度产生响应。这篇文章采用高通量的微流体细胞培养(high-throughput microfluidic cell culture)和荧光显微镜，定量基因表达分析和建立数学模型等研究手段来评估到底单个哺乳动物细胞如何对不同浓度的信号分子TNF-α产生相应的响应。 并高度肯定了以单细胞级别进行高通量基因定量对研究生物系统如何运作的价值。

Letter

Nature  466, 267-271 (8 July 2010) | doi:10.1038/nature09145; Received 29  December 2009; Accepted 28 April 2010; Published online 27 June 2010
Single-cell NF-κB dynamics reveal digital activation and analogue information processing Savaş Tay1,2,4, Jacob J. Hughey1,4, Timothy K. Lee1, Tomasz Lipniacki3, Stephen R. Quake1,2 & Markus W. Covert1
1.  Department of Bioengineering, Stanford University, Stanford, California 94305, USA

2.  Howard Hughes Medical Institute, Stanford, California 94305, USA

3.  Institute of Fundamental Technological Research, Warsaw 02-106, Poland

4.  These authors contributed equally to this work.

Abstract

Cells  operate in dynamic environments using extraordinary communication  capabilities that emerge from the interactions of genetic circuitry. The  mammalian immune response is a striking example of the coordination of different cell types1. Cell-to-cell communication is primarily mediated  by signalling molecules that form spatiotemporal concentration  gradients, requiring cells to respond to a wide range of signal  intensities2. Here we use high-throughput microfluidic cell culture3 and  fluorescence microscopy, quantitative gene expression analysis and  mathematicalmodelling to investigate how single mammalian cells respond  to different concentrations of the signaling molecule tumour-necrosis  factor (TNF)-α, and relay information to the gene expression programs by means of the transcription factor nuclear factor (NF)-κB. We measured NF-κB activity in thousands of live cells under TNF-α  doses covering four orders of magnitude. We find, in contrast to  population-level studies with bulk assays2, that the activation is  heterogeneous and is a digital process at the single-cell level with  fewer cells responding at lower doses. Cells also encode a subtle set of  analogue parameters to modulate the outcome; these parameters include  NF-κB  peak intensity, response time and number of oscillations. We developed a  stochastic mathematical model that reproduces both the digital and  analogue dynamics as well as most gene expression profiles at all  measured conditions, constituting a broadly applicable model for TNF-α-induced NF-κB  signalling in various types of cells. These results highlight the value  of high-throughput quantitative measurements with single-cell  resolution in understanding how biological systems operate.