Novel light-based technologies to control cellular behavior
In the studies published in the Journal Nature Communications, researchers unveil novel light-based technologies to control cellular behavior with unprecedented accuracy. Led by CEPLAS member Matias Zurbriggen (HHU) and Mustafa Khammash at ETH Zurich’s Department of Biosystems Science and Engineering (D-BSSE), these studies showcase cybergenetics cutting-edge frameworks for using light to guide cell behavior in engineered two- and three-dimensional tissues.
The first study introduces µPatternScope, a sophisticated optogenetic platform that allows scientists to sculpt complex cell patterns by inducing apoptosis with high precision. µPatternScope uses image-guided, real-time feedback to control spatial light patterns that selectively trigger programmed cell death in mammalian cell cultures. The researchers demonstrated its capabilities through a “tic-tac-toe” game, in which light-controlled apoptosis patterns created the classic game grid, highlighting µPatternScope’s potential for interactive and dynamic cell patterning. This innovative approach has the potential to revolutionize applications in tissue engineering by enabling the creation of precisely structured tissue forms that mimic natural processes, such as morphogenesis.
The second study takes optogenetic control a step further, enabling the use of light-sensitive gene switches to modulate cellular behavior within three-dimensional tissue cultures. Researchers successfully demonstrated the controlled initiation of necroptosis and the regulation of synthetic WNT3A signaling in mammalian cell models by applying targeted blue and red light patterns. These developments are particularly promising for advancing 3D tissue models, as the team’s engineered system can manipulate critical cell behaviors in complex structures, supporting the potential for programmable organ and tissue models. This work offers novel experimental frameworks for studying cell communication and tissue formation in a controlled setting and suggests new avenues for the application of light-based genetic control in regenerative medicine and disease modeling.