0045-0016 White.indd

Understanding how mammalian cells function requires a dynamic perspective. However, owing to the complexity of signalling networks, these non-linear systems can easily elude human intuition. The central aim of systems biology is to improve our understanding of the temporal complexity of cell signalling pathways, using a combination of experimental and computational approaches. Live-cell imaging and computational modelling are compatible techniques which allow quantitative analysis of cell signalling pathway dynamics. Non-invasive imaging techniques, based on the use of various luciferases and fluorescent proteins, trace cellular events such as gene expression, protein–protein interactions and protein localization in cells. By employing a number of markers in a single assay, multiple parameters can be measured simultaneously in the same cell. Following acquisition using specialized microscopy, analysis of multi-parameter time-lapse images facilitates the identifi cation of important qualitative and quantitative relationships–linking intracellular signalling, gene expression and cell fate. 1 Present address: Instituto de Biotecnologia, UNAM (National University of Mexico), Cuernavaca, Mexico 2 To whom correspondence should be addressed (email MWhite@liverpool. ac.uk). 217 © The Authors Journal compilation © 2008 Biochemical Society 0045-0016 White.indd 217 6/25/08 5:02:31 AM © The Authors Journal compilation © 2008 Biochemical Society 218 Essays in Biochemistry volume 45 2008 Improvements in reporter genes coupled with signifi cant advances in detector technologies, are now allowing us to image gene expression non-invasively in individual living cells. These methods are providing remarkable insights into the dynamics of gene expression during complex processes, such as the cell cycle and the responses of cells to hormones, growth factors and nutrients. On a larger scale, dynamics of gene expression may also be monitored in living organisms. This new technology will greatly assist attempts to decipher the complex behaviours exhibited by biological signalling networks, for instance the ability to integrate multiple input signals over time, and generate specifi c outputs. Introduction: role of single-cell imaging in systems biology The eukaryotic cell receives a multitude of signals from the extracellular environment which it must interpret and respond to in an appropriate manner. These signals are transmitted within the cell using multiple pathways, which frequently involve protein translocation and the modification of signalling molecules. The resulting change in the activity of target proteins like transcription factors, then modulate the expression of a specifi c set of genes. Years of research have helped to elucidate individual molecular interactions within many signalling pathways. However, these signalling cascades, often drawn in isolation as static linear pathways, are complex interconnected signalling networks within cells, built up through integration of multiple pathways. One particular external signal may result in the simultaneous activation of many signalling pathways within the cell. Additionally, because cells are very rarely stimulated by just one isolated signal in vivo, the complexity of cellular signalling networks becomes vast. Understanding the molecular mechanisms controlling these activities across the whole network requires a simpler way to visualize the system complexity. The pathway output of transcription factor activity most probably results in the expression of genes encoding other signalling molecules. The understanding of pathway inputs and outputs becomes extremely complex when the expressed protein can in turn interact with the pathway, establishing non-linear feedback structures within the network. When considering system dynamics, the specifi c ordering and timing of individual processes become vital to determining the overall behaviour of the integrated signalling system. It is now important to defi ne where and how pathways interact, and to examine the functional effects of these interactions. The non-intuitive nature of non-linear systems is exhibited by a wide range of dynamical properties including bistability, adaptation and oscillations [1]. This requires data from single cells and mathematical approaches to help comprehend their behaviour. There are many instances in biology where the same activating signal can lead to quite different cellular responses in different cells or in the same cells at different times or under different conditions. This is achieved by specifi c 0045-0016 White.indd 218 6/25/08 5:02:31 AM © The Authors Journal compilation © 2008 Biochemical Society D. Mullassery et al. 219 interactions between signalling molecules, making the cellular environment critical for the correct interpretation of incoming signals. As cell populations are heterogeneous, the ability to acquire spatial and temporal information in a single cell is fundamental, requiring non-invasive methods of measuring cellular processes in the same cell over time. The visualization of cellular processes in vivo enables the investigation of important biological questions such as understanding the function of genes and gene products, and how they regulate cellular processes through complex signalling networks.