Cell signaling occurs through a complex network of intermolecular interactions. Cell signaling is far from a simple linear transfer of information from one molecule to the next. Rather, there are feedback and feed-forward loops, convergence and divergence of signaling cascades, spatial elements such as requirements for molecule clustering and compartmentalization, stochastic elements, and many other complexities at every stage, from the cell surface receptor level to the end points of signaling. Combined, these elements lead to nonlinearities in signal transduction and cellular regulation, such as cooperativity, amplification, digitization, hysteresis and other behaviors that remain to be elucidated for a full understanding of cellular signaling.
Recent advances in cellular light microscopy, such as activity biosensor, single-molecule and super-resolution imaging are ideal for studying the complexity of cell signaling. These technologies allow the monitoring of molecular activities with high specificity in their native cellular context, with appropriate spatiotemporal resolution – from nanometres and milliseconds to micrometres and minutes, and beyond. Yet, the richness of microscopy data comes at a price: these data often reveal substantial molecular and cellular heterogeneity that is difficult to digest without proper analytical tools. Therefore, an integral part of cellular imaging studies of signaling are the associated computer vision, statistical analysis and mathematical modelling tools that help extract quantitative information from the microscopy data, thus enabling the probing of the complex behaviors of signaling networks.
The aim of this Research Topic is to cover recent promising trends in the development and utilization of quantitative imaging approaches for the study of cell signaling. Areas of interest include, but are not limited to:
• Development and application of biosensors
• High- and super-resolution studies, including single-molecule imaging
• Spatial regulation of cell signaling
• Kinetics of signal transduction
• Regulation of cell fate and cell state transitions
• Studies that integrate information across spatial or temporal scales
Cell signaling occurs through a complex network of intermolecular interactions. Cell signaling is far from a simple linear transfer of information from one molecule to the next. Rather, there are feedback and feed-forward loops, convergence and divergence of signaling cascades, spatial elements such as requirements for molecule clustering and compartmentalization, stochastic elements, and many other complexities at every stage, from the cell surface receptor level to the end points of signaling. Combined, these elements lead to nonlinearities in signal transduction and cellular regulation, such as cooperativity, amplification, digitization, hysteresis and other behaviors that remain to be elucidated for a full understanding of cellular signaling.
Recent advances in cellular light microscopy, such as activity biosensor, single-molecule and super-resolution imaging are ideal for studying the complexity of cell signaling. These technologies allow the monitoring of molecular activities with high specificity in their native cellular context, with appropriate spatiotemporal resolution – from nanometres and milliseconds to micrometres and minutes, and beyond. Yet, the richness of microscopy data comes at a price: these data often reveal substantial molecular and cellular heterogeneity that is difficult to digest without proper analytical tools. Therefore, an integral part of cellular imaging studies of signaling are the associated computer vision, statistical analysis and mathematical modelling tools that help extract quantitative information from the microscopy data, thus enabling the probing of the complex behaviors of signaling networks.
The aim of this Research Topic is to cover recent promising trends in the development and utilization of quantitative imaging approaches for the study of cell signaling. Areas of interest include, but are not limited to:
• Development and application of biosensors
• High- and super-resolution studies, including single-molecule imaging
• Spatial regulation of cell signaling
• Kinetics of signal transduction
• Regulation of cell fate and cell state transitions
• Studies that integrate information across spatial or temporal scales
