MatriCom, a single-cell RNA-sequencing data mining tool to infer cell-extracellular matrix interactions

Area of Science:

• Biochemistry
• Bioinformatics
• Cell Biology

Background:

• The extracellular matrix (ECM) provides structural support and mediates cell signaling in multicellular organisms.
• Protein interactions within the ECM and with cell receptors are crucial for tissue development and function.
• Understanding these interactions is key to deciphering cellular communication and tissue remodeling.

Purpose of the Study:

• To introduce MatriCom, a novel web application and R package for inferring ECM and cell-ECM communications.
• To leverage a comprehensive database (MatriComDB) of over 25,000 curated interactions for accurate imputation.
• To provide a tool for analyzing user-generated and public scRNA-Seq datasets.

Main Methods:

• Development of MatriCom, a web application and R package.
• Utilizing the MatriComDB, a curated database of matrisome component interactions.
• Applying interaction imputation algorithms to single-cell RNA sequencing (scRNA-Seq) data.
• Incorporating specific rules governing ECM protein interactions.

Main Results:

• Construction of the first human kidney matrisome communication network.
• Analysis of 46 scRNA-Seq datasets from healthy adult tissues.
• Identification of conserved and diverse ECM assemblies and cell/ECM interaction mechanisms.
• Demonstration of MatriCom's capability to generate novel biological insights.

Conclusions:

• MatriCom provides a powerful platform for dissecting ECM and cell-ECM communication networks.
• The tool facilitates the study of tissue-specific ECM organization and signaling.
• MatriCom aids in understanding the evolutionary conservation and diversification of ECM interactions across tissues.