Naba Alexandra, Clauser Karl R, Ding Huiming, Whittaker Charles A, Carr Steven A, Hynes Richard O
David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA.
Proteomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Matrix Biol. 2016 Jan;49:10-24. doi: 10.1016/j.matbio.2015.06.003. Epub 2015 Jul 8.
The extracellular matrix (ECM) is a fundamental component of multicellular organisms that provides mechanical and chemical cues that orchestrate cellular and tissue organization and functions. Degradation, hyperproduction or alteration of the composition of the ECM cause or accompany numerous pathologies. Thus, a better characterization of ECM composition, metabolism, and biology can lead to the identification of novel prognostic and diagnostic markers and therapeutic opportunities. The development over the last few years of high-throughput ("omics") approaches has considerably accelerated the pace of discovery in life sciences. In this review, we describe new bioinformatic tools and experimental strategies for ECM research, and illustrate how these tools and approaches can be exploited to provide novel insights in our understanding of ECM biology. We also introduce a web platform "the matrisome project" and the database MatrisomeDB that compiles in silico and in vivo data on the matrisome, defined as the ensemble of genes encoding ECM and ECM-associated proteins. Finally, we present a first draft of an ECM atlas built by compiling proteomics data on the ECM composition of 14 different tissues and tumor types.
细胞外基质(ECM)是多细胞生物的基本组成部分,它提供机械和化学信号,协调细胞和组织的组织及功能。ECM的降解、过度产生或组成改变会导致或伴随多种病理状况。因此,更好地描述ECM的组成、代谢和生物学特性可促成新型预后和诊断标志物的识别以及治疗机会的发现。过去几年高通量(“组学”)方法的发展极大地加快了生命科学的发现步伐。在本综述中,我们描述了用于ECM研究的新生物信息学工具和实验策略,并说明了如何利用这些工具和方法为我们对ECM生物学的理解提供新见解。我们还介绍了一个网络平台“基质组计划”以及数据库MatrisomeDB,该数据库汇编了关于基质组的计算机模拟和体内数据,基质组被定义为编码ECM和ECM相关蛋白的基因集合。最后,我们展示了通过汇编14种不同组织和肿瘤类型的ECM组成的蛋白质组学数据构建的ECM图谱初稿。