The body’s tissues are held together by a mesh of proteins and sugars called the extracellular matrix, which makes up a third of human body mass and is altered in nearly every genetic and acquired disease. Despite its importance, scientists still do not understand how this matrix is built, maintained, or replaced over time, and that gap has blocked efforts to treat conditions where tissue degenerates or becomes scarred. This project aims to overcome three specific barriers: imaging the matrix in high detail, tracking how it changes in living tissue, and building computer models that predict when healthy matrix turns unhealthy. If successful, the work could lead to early diagnostic tests that detect matrix breakdown before symptoms appear, and eventually to precision therapies that reprogramme the matrix to prevent or reverse tissue decline. The research is fundamental science—it tackles basic questions about how a core component of our bodies works—but those answers are a prerequisite for developing treatments for fibrosis, degenerative diseases, and other matrix-related disorders.
View original technical description
Extracellular matrix is essential for multicellular life. As a third of body mass, it surrounds cells, defines tissue architecture, and provides instructive signals for diverse cellular processes. Altered matrix is a hallmark of almost all genetic and acquired disorders leading to debilitating tissue degeneration and fibrosis. Major gaps in understanding the normal assembly, maintenance and turnover of matrix have limited disease studies and prevented the development of effective matrix-targeted therapies. Our goal is to identify strategies to reprogramme matrix and thereby prolong tissue health. However, there are key conceptual and technical barriers to understanding how altered matrix leads to tissue decline. By innovating and improving technologies we aim to overcome three important barriers: 1) Resolve matrix in high definition including post-translational modification and physical properties; 2) Create tools to track and manipulate the living matrix to understand turnover and spatial dynamics; and 3) Integrate and model matrix data to predict, test and define the transition from tissue health to decline. We will build capacity and improve access to matrix research in broader scientific and clinical communities. Success will enable early diagnostics to detect loss of matrix regulation and the development of precision strategies for matrix reprogramming across multiple disease aetiologies.
Plain English summaries and category classifications on this site are generated by AI and may not perfectly reflect the original research.
Is something wrong? Let us know