Abstract  

The extracellular matrix (ECM) is a complex network of hundreds of proteins constituting the foundation that holds our cells together. The functions of the ECM extend far beyond its structural roles. It provides biochemical signals by directly binding to cell surface receptors or indirectly modulating growth factor signaling, which regulates many essential pathways controlling cellular functions, from proliferation and survival to migration and differentiation. Alteration of the ECM is linked to many diseases, including congenital diseases (e.g., Marfan syndrome, Alport syndrome, Ehlers–Danlos syndrome), musculo-skeletal diseases (e.g., osteoarthritis, myopathies), cardiovascular diseases, fibrosis, and cancer. Despite its importance, the ECM remains largely unexplored. For example, we have yet to decipher the ECM protein composition (or “matrisome”) of organs and tissues, or the ECM protein composition of specialized niches within tissues. We also do not fully understand the correlation between cell type and ECM proteins, nor do we know how the composition of the ECM changes over time and throughout the course of a disease. 

These gaps in knowledge are mainly due to the lack of adequate methods to study the ECM. The secretion and post-translational modifications that accumulate in the ECM over time are critical for proper ECM functions and cannot be fully studied by RNA-level observations only. Thus, protein-level evidence is key to understanding the function and dynamics of the ECM. However, ECM proteins – typically very large, heavily post-translationally modified, and highly insoluble – are underrepresented in global proteomic datasets. We propose to fill these gaps in knowledge by contributing our expertise in ECM biology, ECM proteomics, and computational biology to the technology development and mapping efforts of the Human BioMolecular Atlas Program (HuBMAP), and ultimately build spatially-resolved maps of the matrisome of all organs. To achieve this goal, we will pursue the following aims: 1) Reanalyze the vast amount of single-cell RNA-seq data generated by HuBMAP to identify the cell populations expressing ECM and ECM receptor gene transcripts for all organs; 2) Integrate existing imaging data and mass spectrometry data generated by the HuBMAP to build a model to predict protein co-expression and create spatially-resolved tissue maps of the ECM; 3) Contribute our 10+ years of expertise in ECM proteomics  to ensure the effectiveness of future data collection of ECM-relevant information by members of HuBMAP. For our efforts to benefit the entire scientific community, we will deploy all datasets and technologies via the HuBMAP Portal and via MatrisomeDB, the ECM protein knowledge database we previously developed (https://matrisomedb.org) . This mapping effort will constitute a first step toward understanding the roles of the ECM in health and diseases and toward the development of future ECM-focused diagnostic and therapeutic strategies.

Public health relevance statement

The extracellular matrix (ECM) is a complex assembly of hundreds of proteins and a critical regulator of cell, tissue, and organ functions. Yet, the ECM is understudied. Here, we propose to leverage the resources generated by the HuBMAP consortium to build and deploy spatially-resolved maps of the ECM of each tissue of the human body, a first step toward understanding ECM functions in health and disease.