Rationally Designing Organoid-Matrix Feedback
Organoids are 3D multicellular structures derived from stem cells that self-organise and assemble into simplified replicas of the organs from which they originate. While not all organs and tissue types have been recapitulated as organoid models to date, for many organs they have become highly useful tools for the study of development and disease, as well as for drug discovery. However, many currently used organoid culture systems rely on animal-derived extracellular matrices (ECMs), such as basement membrane extracts derived from Engelbreth-Holm-Swarm mouse sarcomas. These matrices suffer from batch-to-batch variability, limited tuneability, and ethical concerns associated with animal use. Moreover, these animal-derived ECM mimics are often relatively static in nature, which impacts the growth of organ and tissue types as organoids. In the human body, growing tissues and organs continuously remodel the surrounding extracellular matrix to create optimal conditions for their own growth and differentiation. Static matrices do not provide this dynamic feedback for growing cells, contributing to reduced accuracy or viability in the resulting organoids. The development of well-defined, animal-free, and dynamic matrices that can respond to cellular cues would therefore represent a major step forward for reliable and scalable organoid culture.
Funded initially by an SNSF Spark grant, we are exploring the development of environmentally responsive, fully synthetic cell culture matrices based on recombinantly produced mechanosensitive proteins immobilised on biomass-derived polymers to create mechanically dynamic hydrogels. These matrices are designed to provide a well-defined, animal-free alternative to conventional culture systems while enabling dynamic interactions between cells and their environment. We are interested in assessing to what extent these, so-called dynamic cell instructive matrices (DCIMs), can adapt their viscoelastic behaviour as a function of chemical and mechanical cues from organoids in culture. Such dynamic culture matrices would not only support more accurate and reproducible organoid growth, but also enable the tuning of proliferation and differentiation of cell types within the organoid through an organoid–matrix feedback loop. Our goal is not only to create healthy and accurate organoid models, but also to recapitulate disease states for modelling and drug discovery. Ultimately, by understanding how mechanical cues influence differentiation patterns in these artificial systems, we aim to shed light on the mechanical drivers of disease states in human tissues.
Team Members:
Yves Erdin (alumnus), Elisa Sohrmann (MSc intern, alumna), Jonas Waidele (MSc Student, alumnus)
Cooperation Partners:
University Children’s Hospital Basel, University Hospital Basel, University of Zurich, Free University of Berlin, University College Dublin
Funding:
Swiss National Science Foundation (Spark) (2024)
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