Single live-cell imaging for systems biology

Dhanya Mullassery, Caroline A. Horton, Christopher D. Wood, Michael R H White

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    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 identification of important qualitative and quantitative relationships-linking intracellular signalling, gene expression and cell fate. Improvements in reporter genes coupled with significant 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 specific outputs. © The Authors Journal compilation. © 2008 Biochemical Society.
    Original languageEnglish
    Pages (from-to)121-134
    Number of pages13
    JournalEssays in biochemistry
    Publication statusPublished - 2008


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