QuimP software for quantifying cellular morphodynamics

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Over the last twenty years live cell microscopy has made enormous progress in visualising dynamic processes inside living cells. To learn how specific cellular functions are normally regulated or affected by disease requires mapping cellular dynamics in a quantitative manner. This is a difficult task, because cells are highly deformable and can adopt complex shapes. Therefore we cannot use landmarks to map corresponding regions within one cell over time, or, what is even more difficult, aggregate data from multiple cells. To date no general solutions to this problem exist. We have pioneered mapping the regulatory dynamics of the actin cytoskeleton in cells. Assembly of actin into dense networks of filaments adjacent to the cell membrane drives cellular shape changes and migration, as needed for example when immune cells chase bacterial intruders. To this end we have developed QuimP (Quantitative Imaging of Membrane Proteins) image analysis software. The main tasks QuimP performs are 1) automated tracing of cell outlines in image time series, 2) matching corresponding regions on the cell boundary at subsequent time points, 3) extracting spatial distributions of fluorescently labelled constituents of the membrane or the cell cortex. The results can be analysed in many different ways. A large number of global parameters such as cell speed, directionality of movement, elongation and many more can be easily computed. Detailed spatio-temporal maps can be generated to perform statistical analyses of measurements such as fluorescence or membrane curvature, and ask how they are related. A main feature is that maps can be processed to automatically identify particular events, for example the formation of actin rich protrusions driving cell motility. These events can then serve as landmarks and multiple events from many cells with different molecular labels can be combined to obtain a detailed picture of the underlying regulatory dynamics. QuimP has been used by us, and groups in the UK and worldwide to study different aspects of cell motility. Users have closely informed its development. It has contributed to a number of important discoveries, for example that in metastatic breast cancers cells membrane protrusions and retractions are highly synchronized both in space and in time, which can explain why these cells move more efficiently than non-metastatic cells. These results suggest the possibility to use QuimP for example to assay the invasiveness of cancer cells. Because of its origin QuimP is currently regarded as a highly specialised tool for the cell motility research community. However, its ability to map spatio-temporal cellular dynamics at the membrane and in the cell cortex, makes QuimP an obvious choice for studying a host of other problems. These include in particular cellular responses to external stimuli, which are transmitted through receptors in the cell membrane. The molecular signalling machinery that is triggered by the activation of membrane receptors is in large parts closely associated with the membrane and therefore easily accessible through QuimP. In a recent example QuimP has been used to study how binding of chemical signals to membrane receptors results in their subsequent internalisation, important to prevent overly prolonged cell stimulation.We here propose to enhance the usability of QuimP and make it accessible to a broader user group. This requires changes to the user interface and improving documentation, better handling of large-scale image data, and will benefit from integration of our most recent developments in other areas, which concern cell detection and 3D cell surface reconstruction.