Periodic Reporting for period 3 - MECHEMGUI (The integration of mechanical and chemical signals in neuronal guidance)
Reporting period: 2021-06-01 to 2022-11-30
During the development of the brain, neurons extend long processes called “axons” through a crowded environment along well-defined pathways to connect to distant cells. These connections eventually give rise to highly complex neuronal networks, along which information is transmitted and processed throughout the body. Past research has identified a variety of small signalling molecules that cells in the brain secrete to tell developing neurons where to grow. However, these molecules alone cannot explain the complex neuronal growth patterns we see.
We recently showed that neurons also respond to mechanical cues, such as local tissue stiffness, suggesting that mechanical signals are likely an important missing part of the puzzle. However, how neurons feel tissue stiffness, and how mechanical (tissue stiffness) and chemical (small signalling molecules) signals work together to guide growing neurons during development is currently unknown. As defects in axon guidance can lead to a variety of so-called neurodevelopmental disorders, understanding how neuronal growth is regulated is crucial not only for our understanding of brain development but also for illuminating new facets of human diseases.
This project aims to close this comprehension gap. By combining state-of-the-art approaches in physics, engineering and biology, we investigate mechanosensitive molecular mechanisms that regulate neuronal growth and guidance. In particular, we are developing new methods that allow us to investigate how tissue stiffness impacts neuronal growth directly (through regulation of the forces exerted by neurons on their environment) and indirectly (by modulating chemical signalling pathways). Ultimately, we will develop a mathematical model based on our findings, which will enable us to predict where axons in the developing brain grow.
The proposed research challenges current concepts in developmental biology and is very relevant to many other areas in biology. Our results will not only shed new light on the complex control mechanisms of cellular growth and motility, but could also lead to novel biomedical approaches aimed at facilitating neuronal re-growth and regeneration in the damaged nervous system.
We recently showed that neurons also respond to mechanical cues, such as local tissue stiffness, suggesting that mechanical signals are likely an important missing part of the puzzle. However, how neurons feel tissue stiffness, and how mechanical (tissue stiffness) and chemical (small signalling molecules) signals work together to guide growing neurons during development is currently unknown. As defects in axon guidance can lead to a variety of so-called neurodevelopmental disorders, understanding how neuronal growth is regulated is crucial not only for our understanding of brain development but also for illuminating new facets of human diseases.
This project aims to close this comprehension gap. By combining state-of-the-art approaches in physics, engineering and biology, we investigate mechanosensitive molecular mechanisms that regulate neuronal growth and guidance. In particular, we are developing new methods that allow us to investigate how tissue stiffness impacts neuronal growth directly (through regulation of the forces exerted by neurons on their environment) and indirectly (by modulating chemical signalling pathways). Ultimately, we will develop a mathematical model based on our findings, which will enable us to predict where axons in the developing brain grow.
The proposed research challenges current concepts in developmental biology and is very relevant to many other areas in biology. Our results will not only shed new light on the complex control mechanisms of cellular growth and motility, but could also lead to novel biomedical approaches aimed at facilitating neuronal re-growth and regeneration in the damaged nervous system.
We have developed new experimental techniques and data analysis software to investigate how neurons feel and respond to the mechanical properties of their environment. These enable us now to investigate how neurons respond to the stiffness of their environment.
During the first period, we found that neurons and other cells do not adapt their own stiffness to that of their environment, which contradicts a long-standing paradigm in the field. However, neuronal forces increase on stiffer substrate, and so does the activity of the mechanosensitive ion channel Piezo1. We investigated how Piezo1 is activated and what its activity triggers inside cells. We identified first molecules that are involved in both chemical and mechanical signalling, which could thus serve as interface between the two different types of signals. We are now extending our studies to other types of neurons and to living brains.
During the first period, we found that neurons and other cells do not adapt their own stiffness to that of their environment, which contradicts a long-standing paradigm in the field. However, neuronal forces increase on stiffer substrate, and so does the activity of the mechanosensitive ion channel Piezo1. We investigated how Piezo1 is activated and what its activity triggers inside cells. We identified first molecules that are involved in both chemical and mechanical signalling, which could thus serve as interface between the two different types of signals. We are now extending our studies to other types of neurons and to living brains.
We have advanced the field by providing new experimental tools and AI-based data analysis software to the community. Also, we have accumulated new knowledge in diverse areas of science, which we published in highly visible, cross-disciplinary journals. By the end of the project, we expect to know mechanotransduction pathways in neurons, understand how mechanical and chemical signals can be integrated by neurons, and to be able to predict axon growth patterns in vivo, which is currently not always possible.