[1][2] Live single-cell studies can reveal key behaviours that would otherwise be masked in population averaging experiments such as western blots.
[3] In a live single-cell imaging experiment a fluorescent reporter is introduced into a cell line to measure the levels, localisation or activity of a signalling molecule.
Analysis of features describing the fluorescent reporter over time, can then lead to modelling and generation of biological conclusions from which further experimentation can be guided.
[7] Generally, these early studies focused on the localisation and behaviour of these fluorescently labelled proteins at the subcellular level over short periods of time.
However, this changed with pioneering studies looking at the tumour suppressor p53[8] and the stress and inflammation related protein NF-κB,[9] revealing there levels and localisation respectively to oscillate over periods of several hours.
Much of the growth in the field has come from improved gene editing tools such as CRISPR, this leading to development of a wide variety of fluorescent reporters.
Following live-cell imaging, automated tracking software is then employed to extract time series data from videos of cells.
[20] In the final stage of a live single-cell imaging study, modelling and analysis of time series data extracted from tracked cells is performed.
[23] A large overlap between analysis of single-cell live data, and modelling of biological systems using ordinary differential equations exists.
Results from this key data analysis step will drive further experimentation, for example by perturbing aspects of the system being studied and then comparing signalling dynamics with those of the control population.