Lamba Rijuta, Paguntalan Asia M, Petrov Petar B, Naba Alexandra, Izzi Valerio
Faculty of Biochemistry and Molecular Medicine & Faculty of Medicine, BioIM Unit, University of Oulu, Oulu, FI-90014, Finland.
Department of Physiology and Biophysics, University of Illinois Chicago, Chicago, IL 60612, USA.
bioRxiv. 2024 Dec 16:2024.12.10.627834. doi: 10.1101/2024.12.10.627834.
The ECM is a complex and dynamic meshwork of proteins that forms the framework of all multicellular organisms. Protein interactions within the ECM are critical to building and remodeling the ECM meshwork, while interactions between ECM proteins and cell surface receptors are essential for the initiation of signal transduction and the orchestration of cellular behaviors. Here, we report the development of MatriCom, a web application (https://matrinet.shinyapps.io/matricom) and a companion R package (https://github.com/Izzilab/MatriCom), devised to mine scRNA-Seq datasets and infer communications between ECM components and between different cell populations and the ECM. To impute interactions from expression data, MatriCom relies on a unique database, MatriComDB, that includes over 25,000 curated interactions involving matrisome components, with data on 80% of the ~1,000 genes that compose the mammalian matrisome. MatriCom offers the option to query open-access datasets sourced from large sequencing efforts (Tabula Sapiens, The Human Protein Atlas, HuBMAP) or to process user-generated datasets. MatriCom is also tailored to account for the specific rules governing ECM protein interactions and offers options to customize the output through stringency filters. We illustrate the usability of MatriCom with the example of the human kidney matrisome communication network. Last, we demonstrate how the integration of 46 scRNA-Seq datasets led to the identification of both ubiquitous and tissue-specific ECM communication patterns. We envision that MatriCom will become a powerful resource to elucidate the roles of different cell populations in ECM-ECM and cell-ECM interactions and their dysregulations in the context of diseases such as cancer or fibrosis.
细胞外基质（ECM）是一种复杂且动态的蛋白质网络，构成了所有多细胞生物的框架。ECM内的蛋白质相互作用对于构建和重塑ECM网络至关重要，而ECM蛋白质与细胞表面受体之间的相互作用对于信号转导的启动和细胞行为的协调至关重要。在这里，我们报告了MatriCom的开发，它是一个网络应用程序（https://matrinet.shinyapps.io/matricom）和一个配套的R包（https://github.com/Izzilab/MatriCom），旨在挖掘单细胞RNA测序（scRNA-Seq）数据集，并推断ECM组件之间以及不同细胞群体与ECM之间的通信。为了从表达数据中推断相互作用，MatriCom依赖于一个独特的数据库MatriComDB，该数据库包含超过25000条经过整理的涉及基质体成分的相互作用，其中有关于构成哺乳动物基质体的约1000个基因中80%的数据。MatriCom提供了查询来自大型测序项目（Tabula Sapiens、人类蛋白质图谱、HuBMAP）的开放获取数据集或处理用户生成数据集的选项。MatriCom还经过定制以考虑控制ECM蛋白质相互作用的特定规则，并提供通过严格性过滤器自定义输出的选项。我们以人类肾脏基质体通信网络为例说明了MatriCom的可用性。最后，我们展示了46个scRNA-Seq数据集的整合如何导致识别出普遍存在的和组织特异性的ECM通信模式。我们设想MatriCom将成为一种强大的资源，用于阐明不同细胞群体在ECM-ECM和细胞-ECM相互作用中的作用，以及它们在癌症或纤维化等疾病背景下的失调情况。
