Secreting the extracellular matrix in health and disease – MatSec
All animals have an extracellular matrix (ECM) – secreted materials that assemble into a biomechanical, 3D scaffold that defines the form and function of multicellular tissue. The ECM comprises up to 70% of our dry weight and its most abundant components are collagens, which alone comprise 25% of the body’s protein weight. For correct ECM assembly, cells must secrete folded collagens and degrade misfolded collagens. When either secretion or degradation go wrong, the resultant ECM is misassembled leading to problems in tissue building. This proposal aims to reveal fundamental mechanisms of collagen sorting in the early secretory pathway.
The early secretory pathway, at the interface between endoplasmic reticulum (ER) exit sites (ERES), the ER-Golgi Intermediate Compartment (ERGIC), and the Golgi, is a vital gateway to control the quantity and quality of collagens, which then go on to assemble into an ECM. The components that establish this subcompartmentation and how they control collagen secretion remain unclear.
Collagens are a challenging secretory cargo for cells because they are huge. My discoveries of TANGO1 as a master organiser of the ERES-Golgi interface, provide an ideal platform for mechanistic insight into how collagen sorting between secretion and degradation is carried out, and therefore how it contributes to tissue building.
We will 1 Reconstruct an ERES to understand collagen 'filtration' at the ERES. 2 Determine how misfolded collagens are sorted for degradation at the ERES and 3 Identify the pathophysiological alterations in skin tumours that occur when ERES sorting fails.
Project coordination
Ishier RAOTE (Institut Jacques Monod)
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Partnership
IJM Institut Jacques Monod
Help of the ANR 349,877 euros
Beginning and duration of the scientific project:
February 2024
- 48 Months