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用于研究干细胞命运的组合信号微环境。

Combinatorial signaling microenvironments for studying stem cell fate.

作者信息

Flaim Christopher J, Teng Dayu, Chien Shu, Bhatia Sangeeta N

机构信息

Department of Bioengineering and Medicine, University of California-San Diego, La Jolla, CA 92093-0412, USA.

出版信息

Stem Cells Dev. 2008 Feb;17(1):29-39. doi: 10.1089/scd.2007.0085.

DOI:10.1089/scd.2007.0085
PMID:18271698
Abstract

Extracellular matrix (ECM) and growth factor signaling networks are known to interact in a complex manner. Therefore, reductionist approaches that test the cellular response to individual ECM components and growth factors cannot be used to predict the response to more complex mixtures without knowledge of the underlying signaling network. To address this challenge, we have developed a technology platform to experimentally probe the interactions of ECM components and soluble growth factors on stem cell fate. We present a multiwell microarray platform that allows 1200 simultaneous experiments on 240 unique signaling environments. Mixtures of extracellular matrix (fibronectin, laminin, collagen I, collagen III, collagen IV) are arrayed using a robotic spotter and arranged in a multiwell format. Embryonic stem (ES) cells adhere to ECM spots and are cultured in mixtures of soluble factors [wnt3a, activin A, bone morphogenetic protein-4 (BMP-4), and fibroblast growth factor-4 (FGF-4)]. Differentiation along the cardiac lineage is monitored by myosin heavy chain-alpha-green fluorescent protein (MHC alpha-GFP) reporter expression as compared to growth by monitoring nuclear DNA, and both signals are quantified using a confocal microarray scanner. In developing the platform, we characterized the amount of deposited protein, the fluorescent readout of GFP expression and DNA content, and the use of a laser-based scanner as compared to fluorescent microscopy for data acquisition. The effects of growth factors on growth and differentiation are consistent with previously reported literature, and preliminary evidence of interactive signaling is illuminated. This versatile technique is compatible with virtually any set of insoluble and soluble cues, leverages existing software and hardware, and represents a step toward developing the 'systems biology' of stem cells.

摘要

已知细胞外基质(ECM)和生长因子信号网络以复杂的方式相互作用。因此,在不了解潜在信号网络的情况下,测试细胞对单个ECM成分和生长因子的反应的简化方法无法用于预测对更复杂混合物的反应。为了应对这一挑战,我们开发了一个技术平台,以实验方式探究ECM成分和可溶性生长因子对干细胞命运的相互作用。我们展示了一个多孔微阵列平台,该平台允许在240种独特的信号环境中同时进行1200个实验。使用机器人点样仪将细胞外基质(纤连蛋白、层粘连蛋白、I型胶原、III型胶原、IV型胶原)的混合物进行阵列,并以多孔形式排列。胚胎干细胞(ES细胞)粘附在ECM斑点上,并在可溶性因子[Wnt3a、激活素A、骨形态发生蛋白-4(BMP-4)和成纤维细胞生长因子-4(FGF-4)]的混合物中培养。与通过监测核DNA来监测生长相比,通过肌球蛋白重链α-绿色荧光蛋白(MHCα-GFP)报告基因表达来监测沿心脏谱系的分化,并且使用共聚焦微阵列扫描仪对这两个信号进行定量。在开发该平台时,我们对沉积蛋白的量、GFP表达和DNA含量的荧光读数以及与荧光显微镜相比使用基于激光的扫描仪进行数据采集进行了表征。生长因子对生长和分化的影响与先前报道的文献一致,并揭示了相互作用信号的初步证据。这种通用技术几乎与任何一组不溶性和可溶性信号线索兼容,利用了现有的软件和硬件,代表了朝着发展干细胞“系统生物学”迈出的一步。

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